From 58fa8a70cb39a65ca478b778fe058da9bafbe308 Mon Sep 17 00:00:00 2001 From: bojiang Date: Sat, 18 May 2024 12:41:54 +0800 Subject: [PATCH 001/125] feat: repo/model/serve --- .gitignore | 161 ++++++++++++ LICENSE | 201 +++++++++++++++ README.md | 150 +++++++++++ cllama/__init__.py | 0 cllama/__main__.py | 295 +++++++++++++++++++++ cllama/aws.py | 630 +++++++++++++++++++++++++++++++++++++++++++++ cllama/spec.py | 11 + pyproject.toml | 22 ++ req.txt | 7 + 9 files changed, 1477 insertions(+) create mode 100644 .gitignore create mode 100644 LICENSE create mode 100644 README.md create mode 100644 cllama/__init__.py create mode 100644 cllama/__main__.py create mode 100644 cllama/aws.py create mode 100644 cllama/spec.py create mode 100644 pyproject.toml create mode 100644 req.txt diff --git a/.gitignore b/.gitignore new file mode 100644 index 00000000..7751b092 --- /dev/null +++ b/.gitignore @@ -0,0 +1,161 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# poetry +# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control +#poetry.lock + +# pdm +# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. +#pdm.lock +# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it +# in version control. +# https://pdm.fming.dev/#use-with-ide +.pdm.toml + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +# PyCharm +# JetBrains specific template is maintained in a separate JetBrains.gitignore that can +# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore +# and can be added to the global gitignore or merged into this file. 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+

Self-host LLMs with vLLM and BentoML

+
+ +This is a BentoML example project, showing you how to serve and deploy open-source Large Language Models using [vLLM](https://vllm.ai), a high-throughput and memory-efficient inference engine. + +See [here](https://github.com/bentoml/BentoML?tab=readme-ov-file#%EF%B8%8F-what-you-can-build-with-bentoml) for a full list of BentoML example projects. + +💡 This example is served as a basis for advanced code customization, such as custom model, inference logic or vLLM options. For simple LLM hosting with OpenAI compatible endpoint without writing any code, see [OpenLLM](https://github.com/bentoml/OpenLLM). + + +## Prerequisites + +- You have installed Python 3.8+ and `pip`. See the [Python downloads page](https://www.python.org/downloads/) to learn more. +- You have a basic understanding of key concepts in BentoML, such as Services. We recommend you read [Quickstart](https://docs.bentoml.com/en/1.2/get-started/quickstart.html) first. +- If you want to test the Service locally, you need a Nvidia GPU with at least 16G VRAM. +- (Optional) We recommend you create a virtual environment for dependency isolation for this project. See the [Conda documentation](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) or the [Python documentation](https://docs.python.org/3/library/venv.html) for details. + +## Install dependencies + +```bash +git clone https://github.com/bentoml/BentoVLLM.git +cd BentoVLLM/mistral-7b-instruct +pip install -r requirements.txt && pip install -f -U "pydantic>=2.0" +``` + +## Run the BentoML Service + +We have defined a BentoML Service in `service.py`. Run `bentoml serve` in your project directory to start the Service. + +```bash +$ bentoml serve . + +2024-01-18T07:51:30+0800 [INFO] [cli] Starting production HTTP BentoServer from "service:VLLM" listening on http://localhost:3000 (Press CTRL+C to quit) +INFO 01-18 07:51:40 model_runner.py:501] Capturing the model for CUDA graphs. This may lead to unexpected consequences if the model is not static. To run the model in eager mode, set 'enforce_eager=True' or use '--enforce-eager' in the CLI. +INFO 01-18 07:51:40 model_runner.py:505] CUDA graphs can take additional 1~3 GiB memory per GPU. If you are running out of memory, consider decreasing `gpu_memory_utilization` or enforcing eager mode. +INFO 01-18 07:51:46 model_runner.py:547] Graph capturing finished in 6 secs. +``` + +The server is now active at [http://localhost:3000](http://localhost:3000/). You can interact with it using the Swagger UI or in other different ways. + +
+ +CURL + +```bash +curl -X 'POST' \ + 'http://localhost:3000/generate' \ + -H 'accept: text/event-stream' \ + -H 'Content-Type: application/json' \ + -d '{ + "prompt": "Explain superconductors like I'\''m five years old", + "tokens": null +}' +``` + +
+ +
+ +Python client + +```python +import bentoml + +with bentoml.SyncHTTPClient("http://localhost:3000") as client: + response_generator = client.generate( + prompt="Explain superconductors like I'm five years old", + tokens=None + ) + for response in response_generator: + print(response) +``` + +
+ +
+ +OpenAI-compatible endpoints + +This Service uses the `@openai_endpoints` decorator to set up OpenAI-compatible endpoints (`chat/completions` and `completions`). This means your client can interact with the backend Service (in this case, the VLLM class) as if they were communicating directly with OpenAI's API. This [utility](mistral-7b-instruct/bentovllm_openai/) does not affect your BentoML Service code, and you can use it for other LLMs as well. + +```python +from openai import OpenAI + +client = OpenAI(base_url='http://localhost:3000/v1', api_key='na') + +# Use the following func to get the available models +client.models.list() + +chat_completion = client.chat.completions.create( + model="mistralai/Mistral-7B-Instruct-v0.2", + messages=[ + { + "role": "user", + "content": "Explain superconductors like I'm five years old" + } + ], + stream=True, +) +for chunk in chat_completion: + # Extract and print the content of the model's reply + print(chunk.choices[0].delta.content or "", end="") +``` + +**Note**: If your Service is deployed with [protected endpoints on BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html#access-protected-deployments), you need to set the environment variable `OPENAI_API_KEY` to your BentoCloud API key first. + +```bash +export OPENAI_API_KEY={YOUR_BENTOCLOUD_API_TOKEN} +``` + +You can then use the following line to replace the client in the above code snippet. Refer to [Obtain the endpoint URL](https://docs.bentoml.com/en/latest/bentocloud/how-tos/call-deployment-endpoints.html#obtain-the-endpoint-url) to retrieve the endpoint URL. + +```python +client = OpenAI(base_url='your_bentocloud_deployment_endpoint_url/v1') +``` + +
+ +For detailed explanations of the Service code, see [vLLM inference](https://docs.bentoml.org/en/latest/use-cases/large-language-models/vllm.html). + +## Deploy to BentoCloud + +After the Service is ready, you can deploy the application to BentoCloud for better management and scalability. [Sign up](https://www.bentoml.com/) if you haven't got a BentoCloud account. + +Make sure you have [logged in to BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html), then run the following command to deploy it. + +```bash +bentoml deploy . +``` + +Once the application is up and running on BentoCloud, you can access it via the exposed URL. + +**Note**: For custom deployment in your own infrastructure, use [BentoML to generate an OCI-compliant image](https://docs.bentoml.com/en/latest/guides/containerization.html). + + +## Different LLM Models + +Besides the mistral-7b-instruct model, we have examples for other models in subdirectories of this repository. Below is a list of these models and links to the example subdirectories. + +- [Mistral-7B-Instruct-v0.2](mistral-7b-instruct/) +- [Mixtral-8x7B-Instruct-v0.1 with gptq quantization](mistral-7b-instruct/) +- [Llama-2-7b-chat-hf](llama2-7b-chat/) +- [SOLAR-10.7B-v1.0](solar-10.7b-instruct/) + + +## LLM tools integration examples + +- Every model directory contains codes to add OpenAI compatible endpoints to the BentoML service. +- [outlines-integration/](outlines-integration/) contains the code to integrate with [outlines](https://github.com/outlines-dev/outlines) for structured generation. diff --git a/cllama/__init__.py b/cllama/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/cllama/__main__.py b/cllama/__main__.py new file mode 100644 index 00000000..9c08f408 --- /dev/null +++ b/cllama/__main__.py @@ -0,0 +1,295 @@ +import typer +import shlex +import os +from typing_extensions import TypedDict +import collections + +import prompt_toolkit +import shutil +import pydantic +import yaml +import json +import questionary +import re +import subprocess +import pyaml +import pathlib +from cllama.spec import GPU_MEMORY + + +ERROR_STYLE = "red" +SUCCESS_STYLE = "green" + + +CLLAMA_HOME = pathlib.Path.home() / ".openllm_next" +REPO_DIR = CLLAMA_HOME / "repos" +TEMP_DIR = CLLAMA_HOME / "temp" +VENV_DIR = CLLAMA_HOME / "venv" + +REPO_DIR.mkdir(exist_ok=True, parents=True) +TEMP_DIR.mkdir(exist_ok=True, parents=True) +VENV_DIR.mkdir(exist_ok=True, parents=True) + +CONFIG_FILE = CLLAMA_HOME / "config.json" + + +app = typer.Typer() +repo_app = typer.Typer() +model_app = typer.Typer() + +app.add_typer(repo_app, name="repo") +app.add_typer(model_app, name="model") + + +class Config(pydantic.BaseModel): + repos: dict[str, str] = { + "default": "git+https://github.com/bojiang/bentovllm@main#subdirectory=bentoml" + } + default_repo: str = "default" + + +def _load_config(): + if CONFIG_FILE.exists(): + with open(CONFIG_FILE) as f: + return Config(**json.load(f)) + return Config() + + +def _save_config(config): + with open(CONFIG_FILE, "w") as f: + json.dump(config.dict(), f, indent=2) + + +class RepoInfo(TypedDict): + name: str + path: str + url: str + server: str + owner: str + repo: str + branch: str + + +class ModelInfo(TypedDict): + repo: RepoInfo + path: str + + +class BentoInfo(TypedDict): + model: ModelInfo + bento_yaml: dict + + +def _load_model_map() -> dict[str, dict[str, ModelInfo]]: + model_map = collections.defaultdict(dict) + config = _load_config() + for repo_name, repo_url in config.repos.items(): + server, owner, repo, branch = _parse_repo_url(repo_url) + repo_dir = REPO_DIR / server / owner / repo + for path in repo_dir.glob("bentoml/bentos/*/*"): + if path.is_dir(): + model_map[path.parent.name][path.name] = ModelInfo( + repo=RepoInfo( + name=repo_name, + url=repo_url, + server=server, + owner=owner, + repo=repo, + branch=branch, + path=str(repo_dir), + ), + path=str(path), + ) + elif path.is_file(): + with open(path) as f: + origin_name = f.read().strip() + origin_path = path.parent / origin_name + model_map[path.parent.name][path.name] = ModelInfo( + repo=RepoInfo( + name=repo_name, + url=repo_url, + server=server, + owner=owner, + repo=repo, + branch=branch, + path=str(repo_dir), + ), + path=str(origin_path), + ) + return model_map + + +GIT_REPO_RE = re.compile( + r"git\+https://(?P.+)/(?P.+)/(?P.+?)(@(?P.+))?$" +) + + +@repo_app.command(name="list") +def repo_list(): + config = _load_config() + pyaml.pprint(config.repos) + + +def _parse_repo_url(repo_url): + """ + parse the git repo url to server, owner, repo name, branch + >>> _parse_repo_url("git+https://github.com/bojiang/bentovllm@main") + ('github.com', 'bojiang', 'bentovllm', 'main') + + >>> _parse_repo_url("git+https://github.com/bojiang/bentovllm") + ('github.com', 'bojiang', 'bentovllm', 'main') + """ + match = GIT_REPO_RE.match(repo_url) + if not match: + raise ValueError(f"Invalid git repo url: {repo_url}") + return ( + match.group("server"), + match.group("owner"), + match.group("repo"), + match.group("branch") or "main", + ) + + +@repo_app.command(name="add") +def repo_add(name: str, repo: str): + name = name.lower() + if not name.isidentifier(): + questionary.print( + f"Invalid repo name: {name}, should only contain letters, numbers and underscores", + style=ERROR_STYLE, + ) + return + + config = _load_config() + if name in config.repos: + override = questionary.confirm( + f"Repo {name} already exists({config.repos[name]}), override?" + ).ask() + if not override: + return + + config.repos[name] = repo + _save_config(config) + pyaml.pprint(config.repos) + + +@repo_app.command(name="remove") +def repo_remove(name: str): + config = _load_config() + if name not in config.repos: + questionary.print(f"Repo {name} does not exist", style=ERROR_STYLE) + return + + del config.repos[name] + _save_config(config) + pyaml.pprint(config.repos) + + +def _run_command(cmd, cwd=None, env=None, copy_env=True): + questionary.print("\n") + env = env or {} + if cwd: + questionary.print(f"$ cd {cwd}", style="bold") + if env: + for k, v in env.items(): + questionary.print(f"$ export {k}={shlex.quote(v)}", style="bold") + if copy_env: + env = {**os.environ, **env} + questionary.print(f"$ {' '.join(cmd)}", style="bold") + try: + subprocess.run(cmd, cwd=cwd, env=env, check=True) + except subprocess.CalledProcessError: + questionary.print("Command failed", style=ERROR_STYLE) + return + + +@repo_app.command(name="update") +def repo_update(): + config = _load_config() + repos_in_use = set() + for name, repo in config.repos.items(): + server, owner, repo_name, branch = _parse_repo_url(repo) + repos_in_use.add((server, owner, repo_name)) + repo_dir = REPO_DIR / server / owner / repo_name + if not repo_dir.exists(): + repo_dir.parent.mkdir(parents=True, exist_ok=True) + try: + cmd = [ + "git", + "clone", + "--branch", + branch, + f"https://{server}/{owner}/{repo_name}.git", + str(repo_dir), + ] + _run_command(cmd) + except subprocess.CalledProcessError: + shutil.rmtree(repo_dir, ignore_errors=True) + questionary.print(f"Failed to clone repo {name}", style=ERROR_STYLE) + else: + try: + cmd = ["git", "fetch", "origin", branch] + _run_command(cmd, cwd=repo_dir) + cmd = ["git", "reset", "--hard", f"origin/{branch}"] + _run_command(cmd, cwd=repo_dir) + except: + shutil.rmtree(repo_dir, ignore_errors=True) + questionary.print(f"Failed to update repo {name}", style=ERROR_STYLE) + for repo_dir in REPO_DIR.glob("*/*/*"): + if tuple(repo_dir.parts[-3:]) not in repos_in_use: + shutil.rmtree(repo_dir, ignore_errors=True) + questionary.print(f"Removed unused repo {repo_dir}") + questionary.print("Repos updated", style=SUCCESS_STYLE) + + +@model_app.command(name="list") +def model_list(): + pyaml.pprint(_load_model_map()) + + +def _get_bento_info(tag): + model_map = _load_model_map() + bento, version = tag.split(":") + if bento not in model_map or version not in model_map[bento]: + questionary.print(f"Model {tag} not found", style=ERROR_STYLE) + return + model_info = model_map[bento][version] + path = pathlib.Path(model_info["path"]) + + bento_file = path / "bento.yaml" + bento_info = yaml.safe_load(bento_file.read_text()) + return BentoInfo( + model=model_info, + bento_yaml=bento_info, + ) + + +@model_app.command(name="get") +def model_get(tag: str): + bento_info = _get_bento_info(tag) + if bento_info: + pyaml.pprint(bento_info) + + +def _serve_model(model: str): + if ":" not in model: + model = f"{model}:latest" + bento_info = _get_bento_info(model) + if not bento_info: + questionary.print(f"Model {model} not found", style=ERROR_STYLE) + return + cmd = ["bentoml", "serve", model] + env = { + "CLLAMA_MODEL": model, + "BENTOML_HOME": bento_info["model"]["repo"]["path"] + "/bentoml", + } + _run_command(cmd, env=env) + + +@app.command() +def serve(model: str): + _serve_model(model) + + +if __name__ == "__main__": + app() diff --git a/cllama/aws.py b/cllama/aws.py new file mode 100644 index 00000000..27d86ba9 --- /dev/null +++ b/cllama/aws.py @@ -0,0 +1,630 @@ +import typer +import typing +import collections + +import prompt_toolkit +from prompt_toolkit import print_formatted_text as print +import time +import uuid +import shutil +import pydantic +from urllib.parse import urlparse +import yaml +import json +import bentoml +import questionary +import os +import re +import subprocess +import pyaml +import pathlib +from cllama.spec import GPU_MEMORY + +ERROR_STYLE = "red" +SUCCESS_STYLE = "green" + + +CLLAMA_HOME = pathlib.Path.home() / ".openllm_next" +REPO_DIR = CLLAMA_HOME / "repos" +TEMP_DIR = CLLAMA_HOME / "temp" +VENV_DIR = CLLAMA_HOME / "venv" + +REPO_DIR.mkdir(exist_ok=True, parents=True) +TEMP_DIR.mkdir(exist_ok=True, parents=True) +VENV_DIR.mkdir(exist_ok=True, parents=True) + +CONFIG_FILE = CLLAMA_HOME / "config.json" + + +app = typer.Typer() +repo_app = typer.Typer() +model_app = typer.Typer() + +app.add_typer(repo_app, name="repo") +app.add_typer(model_app, name="model") + + +class Config(pydantic.BaseModel): + repos: dict[str, str] = { + "default": "git+https://github.com/bojiang/bentovllm@main#subdirectory=bentoml" + } + default_repo: str = "default" + + +def _load_config(): + if CONFIG_FILE.exists(): + with open(CONFIG_FILE) as f: + return Config(**json.load(f)) + return Config() + + +def _save_config(config): + with open(CONFIG_FILE, "w") as f: + json.dump(config.dict(), f, indent=2) + + +class ModelInfo(typing.TypedDict): + repo: str + path: str + + +def _load_model_map() -> dict[str, dict[str, ModelInfo]]: + model_map = collections.defaultdict(dict) + config = _load_config() + for repo_name, repo_url in config.repos.items(): + server, owner, repo, _ = _parse_repo_url(repo_url) + repo_dir = REPO_DIR / server / owner / repo + for path in repo_dir.glob("bentoml/bentos/*/*"): + if path.is_dir(): + model_map[path.parent.name][path.name] = ModelInfo( + repo=repo_name, + path=str(path), + ) + elif path.is_file(): + with open(path) as f: + origin_name = f.read().strip() + origin_path = path.parent / origin_name + model_map[path.parent.name][path.name] = ModelInfo( + repo=repo_name, + path=str(origin_path), + ) + return model_map + + +GIT_REPO_RE = re.compile( + r"git\+https://(?P.+)/(?P.+)/(?P.+?)(@(?P.+))?$" +) + + +@repo_app.command(name="list") +def repo_list(): + config = _load_config() + pyaml.pprint(config.repos) + + +def _parse_repo_url(repo_url): + """ + parse the git repo url to server, owner, repo name, branch + >>> _parse_repo_url("git+https://github.com/bojiang/bentovllm@main") + ('github.com', 'bojiang', 'bentovllm', 'main') + + >>> _parse_repo_url("git+https://github.com/bojiang/bentovllm") + ('github.com', 'bojiang', 'bentovllm', 'main') + """ + match = GIT_REPO_RE.match(repo_url) + if not match: + raise ValueError(f"Invalid git repo url: {repo_url}") + return ( + match.group("server"), + match.group("owner"), + match.group("repo"), + match.group("branch") or "main", + ) + + +@repo_app.command(name="add") +def repo_add(name: str, repo: str): + name = name.lower() + if not name.isidentifier(): + questionary.print( + f"Invalid repo name: {name}, should only contain letters, numbers and underscores", + style=ERROR_STYLE, + ) + return + + config = _load_config() + if name in config.repos: + override = questionary.confirm( + f"Repo {name} already exists({config.repos[name]}), override?" + ).ask() + if not override: + return + + config.repos[name] = repo + _save_config(config) + pyaml.pprint(config.repos) + + +@repo_app.command(name="remove") +def repo_remove(name: str): + config = _load_config() + if name not in config.repos: + questionary.print(f"Repo {name} does not exist", style=ERROR_STYLE) + return + + del config.repos[name] + _save_config(config) + pyaml.pprint(config.repos) + + +def _run_command(cmd, cwd=None): + questionary.print(f"\n$ {' '.join(cmd)}", style="bold") + subprocess.run(cmd, cwd=cwd, check=True) + + +@repo_app.command(name="update") +def repo_update(): + config = _load_config() + repos_in_use = set() + for name, repo in config.repos.items(): + server, owner, repo_name, branch = _parse_repo_url(repo) + repos_in_use.add((server, owner, repo_name)) + repo_dir = REPO_DIR / server / owner / repo_name + if not repo_dir.exists(): + repo_dir.parent.mkdir(parents=True, exist_ok=True) + try: + cmd = [ + "git", + "clone", + "--branch", + branch, + f"https://{server}/{owner}/{repo_name}.git", + str(repo_dir), + ] + _run_command(cmd) + except subprocess.CalledProcessError: + shutil.rmtree(repo_dir, ignore_errors=True) + questionary.print(f"Failed to clone repo {name}", style=ERROR_STYLE) + else: + try: + cmd = ["git", "fetch", "origin", branch] + _run_command(cmd, cwd=repo_dir) + cmd = ["git", "reset", "--hard", f"origin/{branch}"] + _run_command(cmd, cwd=repo_dir) + except: + shutil.rmtree(repo_dir, ignore_errors=True) + questionary.print(f"Failed to update repo {name}", style=ERROR_STYLE) + for repo_dir in REPO_DIR.glob("*/*/*"): + if tuple(repo_dir.parts[-3:]) not in repos_in_use: + shutil.rmtree(repo_dir, ignore_errors=True) + questionary.print(f"Removed unused repo {repo_dir}") + questionary.print("Repos updated", style=SUCCESS_STYLE) + + +@model_app.command(name="list") +def model_list(): + pyaml.pprint(_load_model_map()) + + +def _get_bento_info(tag): + model_map = _load_model_map() + bento, version = tag.split(":") + if bento not in model_map or version not in model_map[bento]: + questionary.print(f"Model {tag} not found", style=ERROR_STYLE) + return + model_info = model_map[bento][version] + repo_name = model_info["repo"] + path = pathlib.Path(model_info["path"]) + + bento_file = path / "bento.yaml" + bento_info = yaml.safe_load(bento_file.read_text()) + return bento_info + + +@model_app.command(name="get") +def model_get(tag: str): + bento_info = _get_bento_info(tag) + if bento_info: + pyaml.pprint(bento_info) + + +def _filter_instance_types( + instance_types, + gpu_count, + gpu_memory=None, + gpu_type=None, + level="match", +): + if gpu_memory is None: + if gpu_type is None: + raise ValueError("Either gpu_memory or gpu_type must be provided") + gpu_memory = GPU_MEMORY[gpu_type] + + def _check_instance(spec): + if gpu_count == 0 or gpu_count is None: + if "GpuInfo" in spec: + return False + else: + return True + else: + gpus = spec.get("GpuInfo", {}).get("Gpus", []) + if len(gpus) == 0: + return False + it_gpu = gpus[0] + it_gpu_mem = it_gpu["MemoryInfo"]["SizeInMiB"] / 1024 + + if it_gpu["Count"] == gpu_count and it_gpu_mem == gpu_memory: + return True + elif it_gpu["Count"] >= gpu_count and it_gpu_mem >= gpu_memory: + if level == "match": + return False + elif level == "usable": + return True + else: + assert False + else: + return False + + def _sort_key(spec): + return ( + spec["InstanceType"].split(".")[0], + spec.get("GpuInfo", {}).get("Gpus", [{}])[0].get("Count", 0), + spec.get("VCpuInfo", {}).get("DefaultVCpus", 0), + spec.get("MemoryInfo", {}).get("SizeInMiB", 0), + ) + + return sorted(filter(_check_instance, instance_types), key=_sort_key) + + +def _resolve_git_package(package): + match = REG_GITPACKAGE.match(package) + if not match: + raise ValueError(f"Invalid git package: {package}") + repo_url, branch, subdirectory = match.groups() + parsed = urlparse(repo_url) + + path_parts = [parsed.netloc] + parsed.path.split("/") + + return repo_url, branch, subdirectory, path_parts + + +def _get_it_card(spec): + """ + InstanceType: g4dn.2xlarge + VCpuInfo: + DefaultCores: 32 + DefaultThreadsPerCore: 2 + DefaultVCpus: 64 + + MemoryInfo: + SizeInMiB: 32768 + + GpuInfo: + Gpus: + - Count: 1 + Manufacturer: NVIDIA + MemoryInfo: + SizeInMiB: 16384 + Name: T4 + TotalGpuMemoryInMiB: 16384 + """ + return f"cpus: {spec['VCpuInfo']['DefaultVCpus']}, mem: {spec['MemoryInfo']['SizeInMiB']}, gpu: {spec['GpuInfo']['Gpus'][0]['Name']} x {spec['GpuInfo']['Gpus'][0]['Count']}, cost: $0.1/hour" + + +def _ensure_aws_security_group(group_name="cllama-http-default"): + try: + existing_groups = subprocess.check_output( + [ + "aws", + "ec2", + "describe-security-groups", + "--filters", + f"Name=group-name,Values={group_name}", + "--no-cli-pager", + ] + ) + existing_groups = json.loads(existing_groups) + if existing_groups["SecurityGroups"]: + return existing_groups["SecurityGroups"][0]["GroupId"] + + result = subprocess.check_output( + [ + "aws", + "ec2", + "create-security-group", + "--group-name", + group_name, + "--description", + "Default VPC security group for cllama services", + "--no-cli-pager", + ] + ) + result = json.loads(result) + security_group_id = result["GroupId"] + + subprocess.check_call( + [ + "aws", + "ec2", + "authorize-security-group-ingress", + "--group-id", + security_group_id, + "--protocol", + "tcp", + "--port", + "80", + "--cidr", + "0.0.0.0/0", + "--no-cli-pager", + ] + ) + subprocess.check_call( + [ + "aws", + "ec2", + "authorize-security-group-ingress", + "--group-id", + security_group_id, + "--protocol", + "tcp", + "--port", + "443", + "--cidr", + "0.0.0.0/0", + "--no-cli-pager", + ] + ) + subprocess.check_call( + [ + "aws", + "ec2", + "authorize-security-group-ingress", + "--group-id", + security_group_id, + "--protocol", + "tcp", + "--port", + "22", + "--cidr", + "0.0.0.0/0", + "--no-cli-pager", + ] + ) + return security_group_id + except subprocess.CalledProcessError as e: + raise RuntimeError(f"Failed to create security group: {e}") + + +@app.command() +def serve(model: str, tag: str = "latest", force_rebuild: bool = False): + if ":" in model: + model, tag = model.split(":") + if tag == "latest": + tag = next(iter(MODEL_INFOS[model].keys())) + + package = MODEL_INFOS[model][tag] + repo, branch, subdirectory, path_parts = _resolve_git_package(package) + repo_dir = REPO_DIR.joinpath(*path_parts) + bento_project_dir = repo_dir / subdirectory + + if force_rebuild: + shutil.rmtree(repo_dir, ignore_errors=True) + + if not repo_dir.exists(): + repo_dir.parent.mkdir(parents=True, exist_ok=True) + try: + cmd = ["git", "clone", "--branch", branch, repo, str(repo_dir)] + print(f"\n$ {' '.join(cmd)}") + subprocess.run(cmd, check=True) + except: + shutil.rmtree(repo_dir, ignore_errors=True) + raise + + bento_info = _get_bento_info(f"{model}:{tag}", bento_project_dir) + + if len(bento_info["services"]) != 1: + raise ValueError("Only support one service currently") + + envs = {} + if len(bento_info.get("envs", [])) > 0: + for env in bento_info["envs"]: + if env["name"] == "CLLAMA_MODEL": + envs[env["name"]] = f"{model}:{tag}" + continue + if env["name"] in os.environ: + value = os.environ.get(env["name"]) + questionary.print(f"Using environment value for {env['name']}") + elif env.get("value"): + value = questionary.text( + f"Enter value for {env['name']}", + default=env["value"], + ).ask() + else: + value = questionary.text( + f"Enter value for {env['name']}", + ).ask() + envs[env["name"]] = value + + cloud_provider = questionary.select( + "Select a cloud provider", + choices=[ + questionary.Choice(title="Local", value="aws"), + questionary.Choice(title="BentoCloud", value="cloud"), + ], + ).ask() + + if cloud_provider == "cloud": + cloud_provider = questionary.select( + "You haven't logged in to BentoCloud, select an action", + choices=[ + questionary.Choice(title="Login with Token", value="login"), + questionary.Choice(title="Sign up ($10 free credit)", value="signup"), + ], + ).ask() + if cloud_provider == "login": + token = questionary.text("Enter your token").ask() + cmd = ["bentoml", "cloud", "login", "--token", token] + # print(f"\n$ {' '.join(cmd)}") + try: + subprocess.check_call(cmd) + except subprocess.CalledProcessError: + raise RuntimeError("Failed to login") + elif cloud_provider == "signup": + token = questionary.text( + "Open https://cloud.bentoml.org/signup in your browser", + ).ask() + # cmd = ["bentoml", "cloud", "signup"] + # print(f"\n$ {' '.join(cmd)}") + # try: + # subprocess.check_call(cmd) + # except subprocess.CalledProcessError: + # raise RuntimeError("Failed to sign up") + + elif cloud_provider == "aws": + try: + cmd = ["aws", "ec2", "describe-instance-types", "--no-cli-pager"] + print(f"\n$ {' '.join(cmd)}") + _instance_types = subprocess.check_output(cmd, text=True) + except subprocess.CalledProcessError: + raise + # print(e) + # _cli_install_aws() + available_it_infos = json.loads(_instance_types)["InstanceTypes"] + # pyaml.p(available_it_infos) + + service = bento_info["services"][0] + if "config" not in service or "resources" not in service["config"]: + raise ValueError("Service config is missing") + elif "gpu" in service["config"]["resources"]: + gpu_count = service["config"]["resources"]["gpu"] + gpu_type = service["config"]["resources"].get("gpu_type") + gpu_memory = service["config"]["resources"].get("gpu_memory") + supported_its = _filter_instance_types( + available_it_infos, + gpu_count, + gpu_memory, + gpu_type, + ) + it = questionary.select( + "Select an instance type", + choices=[ + questionary.Choice( + title=_get_it_card(it_info), + value=it_info["InstanceType"], + ) + for it_info in supported_its + ], + ).ask() + security_group_id = _ensure_aws_security_group() + AMI = "ami-02623cf022763d4a1" + + init_script_file = TEMP_DIR / f"init_script_{str(uuid.uuid4())[:8]}.sh" + with open(init_script_file, "w") as f: + f.write( + INIT_SCRIPT_TEMPLATE.format( + repo=repo, + subdirectory=subdirectory, + model=model, + tag=tag, + env_args=" ".join([f"-e {k}={v}" for k, v in envs.items()]), + ) + ) + # grant permission + os.chmod(init_script_file, 0o755) + cmd = [ + "aws", + "ec2", + "run-instances", + "--image-id", + AMI, + "--instance-type", + it, + "--security-group-ids", + security_group_id, + "--user-data", + f"file://{init_script_file}", + "--key-name", + "jiang", + "--count", + "1", + "--no-cli-pager", + ] + # print(f"\n$ {' '.join(cmd)}") + try: + result = subprocess.check_output(cmd) + except subprocess.CalledProcessError: + raise RuntimeError("Failed to create instance") + result = json.loads(result) + instance_id = result["Instances"][0]["InstanceId"] + print(f"Deployment {instance_id} is created") + + cmd = [ + "aws", + "ec2", + "describe-instances", + "--instance-ids", + instance_id, + "--no-cli-pager", + ] + # print(f"\n$ {' '.join(cmd)}") + result = subprocess.check_output(cmd) + result = json.loads(result) + public_ip = result["Reservations"][0]["Instances"][0]["PublicIpAddress"] + print(f"Public IP: {public_ip}") + + server_start_time = time.time() + print("Server is starting...") + with prompt_toolkit.shortcuts.ProgressBar() as pb: + for _ in pb(range(100)): + start_time = time.time() + try: + with bentoml.SyncHTTPClient(f"http://{public_ip}"): + break + except Exception: + time.sleep(max(0, 6 - (time.time() - start_time))) + else: + raise RuntimeError("Instance is not ready after 10 minutes") + print(f"Server started in {time.time() - server_start_time:.2f} seconds") + print(f"HTTP server is ready at http://{public_ip}") + return + else: + raise ValueError("GPU is required for now") + if cloud_provider == "bentocloud": + cmd = ["bentoml", "cloud", "current-context"] + # print(f"\n$ {' '.join(cmd)}") + try: + output = subprocess.check_output(cmd, text=True) + except subprocess.CalledProcessError: + raise RuntimeError( + "Failed to get bentocloud login context, please login first", + ) + + +@app.command() +def run(model: str, tag: str = "latest", force_rebuild: bool = False): + serve(model, tag, force_rebuild) + + +INIT_SCRIPT_TEMPLATE = """#!/bin/bash +pip3 install bentoml +rm -r /usr/local/cuda* +git clone {repo} /root/bento_repo +export BENTOML_HOME=/root/bento_repo/{subdirectory} +bentoml containerize {model}:{tag} --image-tag {model}:{tag} +docker run --restart always --gpus all -d -p 80:3000 {env_args} {model}:{tag} + +nvidia-smi -q | grep -A2 "ECC Mode" | grep "Current" | grep "Enabled" +ECC_ENABLED=$? + +if [[ $ECC_ENABLED -eq 0 ]]; then + echo "ECC is enabled. Disabling now..." + nvidia-smi -e 0 + reboot +else + echo "ECC is not enabled. No changes made." +fi +""" + + +if __name__ == "__main__": + app() diff --git a/cllama/spec.py b/cllama/spec.py new file mode 100644 index 00000000..006041fc --- /dev/null +++ b/cllama/spec.py @@ -0,0 +1,11 @@ +GPU_MEMORY = { + "nvidia-tesla-t4": 16, + "nvidia-tesla-v100": 16, + "nvidia-tesla-p100": 16, + "nvidia-tesla-p4": 8, + "nvidia-tesla-k80": 12, + "nvidia-tesla-a100": 40, + "nvidia-tesla-a100-80gb": 80, + "nvidia-tesla-a10g": 24, + "nvidia-l4": 24, +} diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 00000000..75d7a40c --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,22 @@ +[build-system] +requires = ["setuptools>=42", "wheel"] +build-backend = "setuptools.build_meta" + +[project] +name = "cllama" +version = "0.0.1" +description = "A description of your package." +authors = [{name = "oasiszero", email = "oasis0.com@gmail.com"}] +license = {file = "LICENSE"} +dependencies = [ + "typer", + "bentoml", + "pyaml", + "fastapi", + "questionary", + "psutil", + "pathlib" +] + +[tool.typer] +src-dir = "cllama" diff --git a/req.txt b/req.txt new file mode 100644 index 00000000..4f08fb7b --- /dev/null +++ b/req.txt @@ -0,0 +1,7 @@ +typer +bentoml +pyaml +fastapi +questionary +psutil +pathlib From 3904af8a58b01489e6c5c7be6f4ca79c7ab0caed Mon Sep 17 00:00:00 2001 From: bojiang Date: Sat, 18 May 2024 13:10:52 +0800 Subject: [PATCH 002/125] refactor --- cllama/__main__.py | 295 --------------------------- {cllama => openllm_next}/__init__.py | 0 openllm_next/__main__.py | 19 ++ {cllama => openllm_next}/aws.py | 4 + openllm_next/common.py | 81 ++++++++ openllm_next/model.py | 87 ++++++++ openllm_next/repo.py | 127 ++++++++++++ openllm_next/serve.py | 26 +++ {cllama => openllm_next}/spec.py | 0 pyproject.toml | 4 +- 10 files changed, 346 insertions(+), 297 deletions(-) delete mode 100644 cllama/__main__.py rename {cllama => openllm_next}/__init__.py (100%) create mode 100644 openllm_next/__main__.py rename {cllama => openllm_next}/aws.py (99%) create mode 100644 openllm_next/common.py create mode 100644 openllm_next/model.py create mode 100644 openllm_next/repo.py create mode 100644 openllm_next/serve.py rename {cllama => openllm_next}/spec.py (100%) diff --git a/cllama/__main__.py b/cllama/__main__.py deleted file mode 100644 index 9c08f408..00000000 --- a/cllama/__main__.py +++ /dev/null @@ -1,295 +0,0 @@ -import typer -import shlex -import os -from typing_extensions import TypedDict -import collections - -import prompt_toolkit -import shutil -import pydantic -import yaml -import json -import questionary -import re -import subprocess -import pyaml -import pathlib -from cllama.spec import GPU_MEMORY - - -ERROR_STYLE = "red" -SUCCESS_STYLE = "green" - - -CLLAMA_HOME = pathlib.Path.home() / ".openllm_next" -REPO_DIR = CLLAMA_HOME / "repos" -TEMP_DIR = CLLAMA_HOME / "temp" -VENV_DIR = CLLAMA_HOME / "venv" - -REPO_DIR.mkdir(exist_ok=True, parents=True) -TEMP_DIR.mkdir(exist_ok=True, parents=True) -VENV_DIR.mkdir(exist_ok=True, parents=True) - -CONFIG_FILE = CLLAMA_HOME / "config.json" - - -app = typer.Typer() -repo_app = typer.Typer() -model_app = typer.Typer() - -app.add_typer(repo_app, name="repo") -app.add_typer(model_app, name="model") - - -class Config(pydantic.BaseModel): - repos: dict[str, str] = { - "default": "git+https://github.com/bojiang/bentovllm@main#subdirectory=bentoml" - } - default_repo: str = "default" - - -def _load_config(): - if CONFIG_FILE.exists(): - with open(CONFIG_FILE) as f: - return Config(**json.load(f)) - return Config() - - -def _save_config(config): - with open(CONFIG_FILE, "w") as f: - json.dump(config.dict(), f, indent=2) - - -class RepoInfo(TypedDict): - name: str - path: str - url: str - server: str - owner: str - repo: str - branch: str - - -class ModelInfo(TypedDict): - repo: RepoInfo - path: str - - -class BentoInfo(TypedDict): - model: ModelInfo - bento_yaml: dict - - -def _load_model_map() -> dict[str, dict[str, ModelInfo]]: - model_map = collections.defaultdict(dict) - config = _load_config() - for repo_name, repo_url in config.repos.items(): - server, owner, repo, branch = _parse_repo_url(repo_url) - repo_dir = REPO_DIR / server / owner / repo - for path in repo_dir.glob("bentoml/bentos/*/*"): - if path.is_dir(): - model_map[path.parent.name][path.name] = ModelInfo( - repo=RepoInfo( - name=repo_name, - url=repo_url, - server=server, - owner=owner, - repo=repo, - branch=branch, - path=str(repo_dir), - ), - path=str(path), - ) - elif path.is_file(): - with open(path) as f: - origin_name = f.read().strip() - origin_path = path.parent / origin_name - model_map[path.parent.name][path.name] = ModelInfo( - repo=RepoInfo( - name=repo_name, - url=repo_url, - server=server, - owner=owner, - repo=repo, - branch=branch, - path=str(repo_dir), - ), - path=str(origin_path), - ) - return model_map - - -GIT_REPO_RE = re.compile( - r"git\+https://(?P.+)/(?P.+)/(?P.+?)(@(?P.+))?$" -) - - -@repo_app.command(name="list") -def repo_list(): - config = _load_config() - pyaml.pprint(config.repos) - - -def _parse_repo_url(repo_url): - """ - parse the git repo url to server, owner, repo name, branch - >>> _parse_repo_url("git+https://github.com/bojiang/bentovllm@main") - ('github.com', 'bojiang', 'bentovllm', 'main') - - >>> _parse_repo_url("git+https://github.com/bojiang/bentovllm") - ('github.com', 'bojiang', 'bentovllm', 'main') - """ - match = GIT_REPO_RE.match(repo_url) - if not match: - raise ValueError(f"Invalid git repo url: {repo_url}") - return ( - match.group("server"), - match.group("owner"), - match.group("repo"), - match.group("branch") or "main", - ) - - -@repo_app.command(name="add") -def repo_add(name: str, repo: str): - name = name.lower() - if not name.isidentifier(): - questionary.print( - f"Invalid repo name: {name}, should only contain letters, numbers and underscores", - style=ERROR_STYLE, - ) - return - - config = _load_config() - if name in config.repos: - override = questionary.confirm( - f"Repo {name} already exists({config.repos[name]}), override?" - ).ask() - if not override: - return - - config.repos[name] = repo - _save_config(config) - pyaml.pprint(config.repos) - - -@repo_app.command(name="remove") -def repo_remove(name: str): - config = _load_config() - if name not in config.repos: - questionary.print(f"Repo {name} does not exist", style=ERROR_STYLE) - return - - del config.repos[name] - _save_config(config) - pyaml.pprint(config.repos) - - -def _run_command(cmd, cwd=None, env=None, copy_env=True): - questionary.print("\n") - env = env or {} - if cwd: - questionary.print(f"$ cd {cwd}", style="bold") - if env: - for k, v in env.items(): - questionary.print(f"$ export {k}={shlex.quote(v)}", style="bold") - if copy_env: - env = {**os.environ, **env} - questionary.print(f"$ {' '.join(cmd)}", style="bold") - try: - subprocess.run(cmd, cwd=cwd, env=env, check=True) - except subprocess.CalledProcessError: - questionary.print("Command failed", style=ERROR_STYLE) - return - - -@repo_app.command(name="update") -def repo_update(): - config = _load_config() - repos_in_use = set() - for name, repo in config.repos.items(): - server, owner, repo_name, branch = _parse_repo_url(repo) - repos_in_use.add((server, owner, repo_name)) - repo_dir = REPO_DIR / server / owner / repo_name - if not repo_dir.exists(): - repo_dir.parent.mkdir(parents=True, exist_ok=True) - try: - cmd = [ - "git", - "clone", - "--branch", - branch, - f"https://{server}/{owner}/{repo_name}.git", - str(repo_dir), - ] - _run_command(cmd) - except subprocess.CalledProcessError: - shutil.rmtree(repo_dir, ignore_errors=True) - questionary.print(f"Failed to clone repo {name}", style=ERROR_STYLE) - else: - try: - cmd = ["git", "fetch", "origin", branch] - _run_command(cmd, cwd=repo_dir) - cmd = ["git", "reset", "--hard", f"origin/{branch}"] - _run_command(cmd, cwd=repo_dir) - except: - shutil.rmtree(repo_dir, ignore_errors=True) - questionary.print(f"Failed to update repo {name}", style=ERROR_STYLE) - for repo_dir in REPO_DIR.glob("*/*/*"): - if tuple(repo_dir.parts[-3:]) not in repos_in_use: - shutil.rmtree(repo_dir, ignore_errors=True) - questionary.print(f"Removed unused repo {repo_dir}") - questionary.print("Repos updated", style=SUCCESS_STYLE) - - -@model_app.command(name="list") -def model_list(): - pyaml.pprint(_load_model_map()) - - -def _get_bento_info(tag): - model_map = _load_model_map() - bento, version = tag.split(":") - if bento not in model_map or version not in model_map[bento]: - questionary.print(f"Model {tag} not found", style=ERROR_STYLE) - return - model_info = model_map[bento][version] - path = pathlib.Path(model_info["path"]) - - bento_file = path / "bento.yaml" - bento_info = yaml.safe_load(bento_file.read_text()) - return BentoInfo( - model=model_info, - bento_yaml=bento_info, - ) - - -@model_app.command(name="get") -def model_get(tag: str): - bento_info = _get_bento_info(tag) - if bento_info: - pyaml.pprint(bento_info) - - -def _serve_model(model: str): - if ":" not in model: - model = f"{model}:latest" - bento_info = _get_bento_info(model) - if not bento_info: - questionary.print(f"Model {model} not found", style=ERROR_STYLE) - return - cmd = ["bentoml", "serve", model] - env = { - "CLLAMA_MODEL": model, - "BENTOML_HOME": bento_info["model"]["repo"]["path"] + "/bentoml", - } - _run_command(cmd, env=env) - - -@app.command() -def serve(model: str): - _serve_model(model) - - -if __name__ == "__main__": - app() diff --git a/cllama/__init__.py b/openllm_next/__init__.py similarity index 100% rename from cllama/__init__.py rename to openllm_next/__init__.py diff --git a/openllm_next/__main__.py b/openllm_next/__main__.py new file mode 100644 index 00000000..70e13f4d --- /dev/null +++ b/openllm_next/__main__.py @@ -0,0 +1,19 @@ +import typer +from openllm_next.model import app as model_app +from openllm_next.repo import app as repo_app +from openllm_next.serve import serve as serve_serve + + +app = typer.Typer() + +app.add_typer(repo_app, name="repo") +app.add_typer(model_app, name="model") + + +@app.command() +def serve(model: str): + serve_serve(model) + + +if __name__ == "__main__": + app() diff --git a/cllama/aws.py b/openllm_next/aws.py similarity index 99% rename from cllama/aws.py rename to openllm_next/aws.py index 27d86ba9..35c3c887 100644 --- a/cllama/aws.py +++ b/openllm_next/aws.py @@ -1,3 +1,7 @@ +""" +Deprecated +""" + import typer import typing import collections diff --git a/openllm_next/common.py b/openllm_next/common.py new file mode 100644 index 00000000..3d86851c --- /dev/null +++ b/openllm_next/common.py @@ -0,0 +1,81 @@ +import shlex +import os +from typing_extensions import TypedDict +import pydantic +import json +import questionary +import subprocess +import pathlib + + +ERROR_STYLE = "red" +SUCCESS_STYLE = "green" + + +CLLAMA_HOME = pathlib.Path.home() / ".openllm_next" +REPO_DIR = CLLAMA_HOME / "repos" +TEMP_DIR = CLLAMA_HOME / "temp" +VENV_DIR = CLLAMA_HOME / "venv" + +REPO_DIR.mkdir(exist_ok=True, parents=True) +TEMP_DIR.mkdir(exist_ok=True, parents=True) +VENV_DIR.mkdir(exist_ok=True, parents=True) + +CONFIG_FILE = CLLAMA_HOME / "config.json" + + +class Config(pydantic.BaseModel): + repos: dict[str, str] = { + "default": "git+https://github.com/bojiang/bentovllm@main#subdirectory=bentoml" + } + default_repo: str = "default" + + +def load_config(): + if CONFIG_FILE.exists(): + with open(CONFIG_FILE) as f: + return Config(**json.load(f)) + return Config() + + +def save_config(config): + with open(CONFIG_FILE, "w") as f: + json.dump(config.dict(), f, indent=2) + + +class RepoInfo(TypedDict): + name: str + path: str + url: str + server: str + owner: str + repo: str + branch: str + + +class ModelInfo(TypedDict): + repo: RepoInfo + path: str + + +class BentoInfo(TypedDict): + model: ModelInfo + bento_yaml: dict + + +def run_command(cmd, cwd=None, env=None, copy_env=True): + questionary.print("\n") + env = env or {} + if cwd: + questionary.print(f"$ cd {cwd}", style="bold") + if env: + for k, v in env.items(): + questionary.print(f"$ export {k}={shlex.quote(v)}", style="bold") + if copy_env: + env = {**os.environ, **env} + questionary.print(f"$ {' '.join(cmd)}", style="bold") + try: + subprocess.run(cmd, cwd=cwd, env=env, check=True) + except subprocess.CalledProcessError: + questionary.print("Command failed", style=ERROR_STYLE) + return diff --git a/openllm_next/model.py b/openllm_next/model.py new file mode 100644 index 00000000..86a84a3d --- /dev/null +++ b/openllm_next/model.py @@ -0,0 +1,87 @@ +import typer +import collections + +import yaml +import questionary +import pyaml +import pathlib +from openllm_next.common import ( + ERROR_STYLE, + REPO_DIR, + load_config, + ModelInfo, + RepoInfo, + BentoInfo, +) +from openllm_next.repo import _parse_repo_url + + +app = typer.Typer() + + +def _load_model_map() -> dict[str, dict[str, ModelInfo]]: + model_map = collections.defaultdict(dict) + config = load_config() + for repo_name, repo_url in config.repos.items(): + server, owner, repo, branch = _parse_repo_url(repo_url) + repo_dir = REPO_DIR / server / owner / repo + for path in repo_dir.glob("bentoml/bentos/*/*"): + if path.is_dir(): + model_map[path.parent.name][path.name] = ModelInfo( + repo=RepoInfo( + name=repo_name, + url=repo_url, + server=server, + owner=owner, + repo=repo, + branch=branch, + path=str(repo_dir), + ), + path=str(path), + ) + elif path.is_file(): + with open(path) as f: + origin_name = f.read().strip() + origin_path = path.parent / origin_name + model_map[path.parent.name][path.name] = ModelInfo( + repo=RepoInfo( + name=repo_name, + url=repo_url, + server=server, + owner=owner, + repo=repo, + branch=branch, + path=str(repo_dir), + ), + path=str(origin_path), + ) + return model_map + + +@app.command() +def list(): + pyaml.pprint(_load_model_map()) + + +def _get_bento_info(tag): + model_map = _load_model_map() + bento, version = tag.split(":") + if bento not in model_map or version not in model_map[bento]: + questionary.print(f"Model {tag} not found", style=ERROR_STYLE) + return + model_info = model_map[bento][version] + path = pathlib.Path(model_info["path"]) + + bento_file = path / "bento.yaml" + bento_info = yaml.safe_load(bento_file.read_text()) + return BentoInfo( + model=model_info, + bento_yaml=bento_info, + ) + + +@app.command() +def get(tag: str): + bento_info = _get_bento_info(tag) + if bento_info: + pyaml.pprint(bento_info) diff --git a/openllm_next/repo.py b/openllm_next/repo.py new file mode 100644 index 00000000..7dec6199 --- /dev/null +++ b/openllm_next/repo.py @@ -0,0 +1,127 @@ +import typer + +import shutil +import questionary +import re +import subprocess +import pyaml +from openllm_next.common import ( + ERROR_STYLE, + SUCCESS_STYLE, + REPO_DIR, + load_config, + save_config, + run_command, +) + + +app = typer.Typer() + + +GIT_REPO_RE = re.compile( + r"git\+https://(?P.+)/(?P.+)/(?P.+?)(@(?P.+))?$" +) + + +@app.command() +def list(): + config = load_config() + pyaml.pprint(config.repos) + + +def _parse_repo_url(repo_url): + """ + parse the git repo url to server, owner, repo name, branch + >>> _parse_repo_url("git+https://github.com/bojiang/bentovllm@main") + ('github.com', 'bojiang', 'bentovllm', 'main') + + >>> _parse_repo_url("git+https://github.com/bojiang/bentovllm") + ('github.com', 'bojiang', 'bentovllm', 'main') + """ + match = GIT_REPO_RE.match(repo_url) + if not match: + raise ValueError(f"Invalid git repo url: {repo_url}") + return ( + match.group("server"), + match.group("owner"), + match.group("repo"), + match.group("branch") or "main", + ) + + +@app.command() +def add(name: str, repo: str): + name = name.lower() + if not name.isidentifier(): + questionary.print( + f"Invalid repo name: {name}, should only contain letters, numbers and underscores", + style=ERROR_STYLE, + ) + return + + config = load_config() + if name in config.repos: + override = questionary.confirm( + f"Repo {name} already exists({config.repos[name]}), override?" + ).ask() + if not override: + return + + config.repos[name] = repo + save_config(config) + pyaml.pprint(config.repos) + + +@app.command() +def remove(name: str): + config = load_config() + if name not in config.repos: + questionary.print(f"Repo {name} does not exist", style=ERROR_STYLE) + return + + del config.repos[name] + save_config(config) + pyaml.pprint(config.repos) + + +@app.command() +def update(): + config = load_config() + repos_in_use = set() + for name, repo in config.repos.items(): + server, owner, repo_name, branch = _parse_repo_url(repo) + repos_in_use.add((server, owner, repo_name)) + repo_dir = REPO_DIR / server / owner / repo_name + if not repo_dir.exists(): + repo_dir.parent.mkdir(parents=True, exist_ok=True) + try: + cmd = [ + "git", + "clone", + "--branch", + branch, + f"https://{server}/{owner}/{repo_name}.git", + str(repo_dir), + ] + run_command(cmd) + except subprocess.CalledProcessError: + shutil.rmtree(repo_dir, ignore_errors=True) + questionary.print(f"Failed to clone repo {name}", style=ERROR_STYLE) + else: + try: + cmd = ["git", "fetch", "origin", branch] + run_command(cmd, cwd=repo_dir) + cmd = ["git", "reset", "--hard", f"origin/{branch}"] + run_command(cmd, cwd=repo_dir) + except: + shutil.rmtree(repo_dir, ignore_errors=True) + questionary.print(f"Failed to update repo {name}", style=ERROR_STYLE) + for repo_dir in REPO_DIR.glob("*/*/*"): + if tuple(repo_dir.parts[-3:]) not in repos_in_use: + shutil.rmtree(repo_dir, ignore_errors=True) + questionary.print(f"Removed unused repo {repo_dir}") + questionary.print("Repos updated", style=SUCCESS_STYLE) + + +if __name__ == "__main__": + app() diff --git a/openllm_next/serve.py b/openllm_next/serve.py new file mode 100644 index 00000000..36c51d35 --- /dev/null +++ b/openllm_next/serve.py @@ -0,0 +1,26 @@ +import typer +import questionary +from openllm_next.common import ERROR_STYLE, run_command +from openllm_next.model import _get_bento_info + +app = typer.Typer() + + +def _serve_model(model: str): + if ":" not in model: + model = f"{model}:latest" + bento_info = _get_bento_info(model) + if not bento_info: + questionary.print(f"Model {model} not found", style=ERROR_STYLE) + return + cmd = ["bentoml", "serve", model] + env = { + "CLLAMA_MODEL": model, + "BENTOML_HOME": bento_info["model"]["repo"]["path"] + "/bentoml", + } + run_command(cmd, env=env) + + +@app.command() +def serve(model: str): + _serve_model(model) diff --git a/cllama/spec.py b/openllm_next/spec.py similarity index 100% rename from cllama/spec.py rename to openllm_next/spec.py diff --git a/pyproject.toml b/pyproject.toml index 75d7a40c..fd461c97 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -3,7 +3,7 @@ requires = ["setuptools>=42", "wheel"] build-backend = "setuptools.build_meta" [project] -name = "cllama" +name = "openllm-next" version = "0.0.1" description = "A description of your package." authors = [{name = "oasiszero", email = "oasis0.com@gmail.com"}] @@ -19,4 +19,4 @@ dependencies = [ ] [tool.typer] -src-dir = "cllama" +src-dir = "openllm_next" From 42aabe6f3d0a4179339041e167383954f43933a2 Mon Sep 17 00:00:00 2001 From: bojiang <5886138+bojiang@users.noreply.github.com> Date: Sat, 18 May 2024 13:12:09 +0800 Subject: [PATCH 003/125] Update README.md --- README.md | 149 ------------------------------------------------------ 1 file changed, 149 deletions(-) diff --git a/README.md b/README.md index ceb0ae1c..8b137891 100644 --- a/README.md +++ b/README.md @@ -1,150 +1 @@ -
-

Self-host LLMs with vLLM and BentoML

-
-This is a BentoML example project, showing you how to serve and deploy open-source Large Language Models using [vLLM](https://vllm.ai), a high-throughput and memory-efficient inference engine. - -See [here](https://github.com/bentoml/BentoML?tab=readme-ov-file#%EF%B8%8F-what-you-can-build-with-bentoml) for a full list of BentoML example projects. - -💡 This example is served as a basis for advanced code customization, such as custom model, inference logic or vLLM options. For simple LLM hosting with OpenAI compatible endpoint without writing any code, see [OpenLLM](https://github.com/bentoml/OpenLLM). - - -## Prerequisites - -- You have installed Python 3.8+ and `pip`. See the [Python downloads page](https://www.python.org/downloads/) to learn more. -- You have a basic understanding of key concepts in BentoML, such as Services. We recommend you read [Quickstart](https://docs.bentoml.com/en/1.2/get-started/quickstart.html) first. -- If you want to test the Service locally, you need a Nvidia GPU with at least 16G VRAM. -- (Optional) We recommend you create a virtual environment for dependency isolation for this project. See the [Conda documentation](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) or the [Python documentation](https://docs.python.org/3/library/venv.html) for details. - -## Install dependencies - -```bash -git clone https://github.com/bentoml/BentoVLLM.git -cd BentoVLLM/mistral-7b-instruct -pip install -r requirements.txt && pip install -f -U "pydantic>=2.0" -``` - -## Run the BentoML Service - -We have defined a BentoML Service in `service.py`. Run `bentoml serve` in your project directory to start the Service. - -```bash -$ bentoml serve . - -2024-01-18T07:51:30+0800 [INFO] [cli] Starting production HTTP BentoServer from "service:VLLM" listening on http://localhost:3000 (Press CTRL+C to quit) -INFO 01-18 07:51:40 model_runner.py:501] Capturing the model for CUDA graphs. This may lead to unexpected consequences if the model is not static. To run the model in eager mode, set 'enforce_eager=True' or use '--enforce-eager' in the CLI. -INFO 01-18 07:51:40 model_runner.py:505] CUDA graphs can take additional 1~3 GiB memory per GPU. If you are running out of memory, consider decreasing `gpu_memory_utilization` or enforcing eager mode. -INFO 01-18 07:51:46 model_runner.py:547] Graph capturing finished in 6 secs. -``` - -The server is now active at [http://localhost:3000](http://localhost:3000/). You can interact with it using the Swagger UI or in other different ways. - -
- -CURL - -```bash -curl -X 'POST' \ - 'http://localhost:3000/generate' \ - -H 'accept: text/event-stream' \ - -H 'Content-Type: application/json' \ - -d '{ - "prompt": "Explain superconductors like I'\''m five years old", - "tokens": null -}' -``` - -
- -
- -Python client - -```python -import bentoml - -with bentoml.SyncHTTPClient("http://localhost:3000") as client: - response_generator = client.generate( - prompt="Explain superconductors like I'm five years old", - tokens=None - ) - for response in response_generator: - print(response) -``` - -
- -
- -OpenAI-compatible endpoints - -This Service uses the `@openai_endpoints` decorator to set up OpenAI-compatible endpoints (`chat/completions` and `completions`). This means your client can interact with the backend Service (in this case, the VLLM class) as if they were communicating directly with OpenAI's API. This [utility](mistral-7b-instruct/bentovllm_openai/) does not affect your BentoML Service code, and you can use it for other LLMs as well. - -```python -from openai import OpenAI - -client = OpenAI(base_url='http://localhost:3000/v1', api_key='na') - -# Use the following func to get the available models -client.models.list() - -chat_completion = client.chat.completions.create( - model="mistralai/Mistral-7B-Instruct-v0.2", - messages=[ - { - "role": "user", - "content": "Explain superconductors like I'm five years old" - } - ], - stream=True, -) -for chunk in chat_completion: - # Extract and print the content of the model's reply - print(chunk.choices[0].delta.content or "", end="") -``` - -**Note**: If your Service is deployed with [protected endpoints on BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html#access-protected-deployments), you need to set the environment variable `OPENAI_API_KEY` to your BentoCloud API key first. - -```bash -export OPENAI_API_KEY={YOUR_BENTOCLOUD_API_TOKEN} -``` - -You can then use the following line to replace the client in the above code snippet. Refer to [Obtain the endpoint URL](https://docs.bentoml.com/en/latest/bentocloud/how-tos/call-deployment-endpoints.html#obtain-the-endpoint-url) to retrieve the endpoint URL. - -```python -client = OpenAI(base_url='your_bentocloud_deployment_endpoint_url/v1') -``` - -
- -For detailed explanations of the Service code, see [vLLM inference](https://docs.bentoml.org/en/latest/use-cases/large-language-models/vllm.html). - -## Deploy to BentoCloud - -After the Service is ready, you can deploy the application to BentoCloud for better management and scalability. [Sign up](https://www.bentoml.com/) if you haven't got a BentoCloud account. - -Make sure you have [logged in to BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html), then run the following command to deploy it. - -```bash -bentoml deploy . -``` - -Once the application is up and running on BentoCloud, you can access it via the exposed URL. - -**Note**: For custom deployment in your own infrastructure, use [BentoML to generate an OCI-compliant image](https://docs.bentoml.com/en/latest/guides/containerization.html). - - -## Different LLM Models - -Besides the mistral-7b-instruct model, we have examples for other models in subdirectories of this repository. Below is a list of these models and links to the example subdirectories. - -- [Mistral-7B-Instruct-v0.2](mistral-7b-instruct/) -- [Mixtral-8x7B-Instruct-v0.1 with gptq quantization](mistral-7b-instruct/) -- [Llama-2-7b-chat-hf](llama2-7b-chat/) -- [SOLAR-10.7B-v1.0](solar-10.7b-instruct/) - - -## LLM tools integration examples - -- Every model directory contains codes to add OpenAI compatible endpoints to the BentoML service. -- [outlines-integration/](outlines-integration/) contains the code to integrate with [outlines](https://github.com/outlines-dev/outlines) for structured generation. From be31510a0114ef3a5929f2f5ce5f7b71cc47575b Mon Sep 17 00:00:00 2001 From: bojiang Date: Sat, 18 May 2024 13:16:25 +0800 Subject: [PATCH 004/125] style: rename --- openllm_next/model.py | 4 ++-- openllm_next/repo.py | 8 ++++---- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/openllm_next/model.py b/openllm_next/model.py index 86a84a3d..ddef098c 100644 --- a/openllm_next/model.py +++ b/openllm_next/model.py @@ -13,7 +13,7 @@ from openllm_next.common import ( RepoInfo, BentoInfo, ) -from openllm_next.repo import _parse_repo_url +from openllm_next.repo import parse_repo_url app = typer.Typer() @@ -23,7 +23,7 @@ def _load_model_map() -> dict[str, dict[str, ModelInfo]]: model_map = collections.defaultdict(dict) config = load_config() for repo_name, repo_url in config.repos.items(): - server, owner, repo, branch = _parse_repo_url(repo_url) + server, owner, repo, branch = parse_repo_url(repo_url) repo_dir = REPO_DIR / server / owner / repo for path in repo_dir.glob("bentoml/bentos/*/*"): if path.is_dir(): diff --git a/openllm_next/repo.py b/openllm_next/repo.py index 7dec6199..1e1d8321 100644 --- a/openllm_next/repo.py +++ b/openllm_next/repo.py @@ -29,13 +29,13 @@ def list(): pyaml.pprint(config.repos) -def _parse_repo_url(repo_url): +def parse_repo_url(repo_url): """ parse the git repo url to server, owner, repo name, branch - >>> _parse_repo_url("git+https://github.com/bojiang/bentovllm@main") + >>> parse_repo_url("git+https://github.com/bojiang/bentovllm@main") ('github.com', 'bojiang', 'bentovllm', 'main') - >>> _parse_repo_url("git+https://github.com/bojiang/bentovllm") + >>> parse_repo_url("git+https://github.com/bojiang/bentovllm") ('github.com', 'bojiang', 'bentovllm', 'main') """ match = GIT_REPO_RE.match(repo_url) @@ -89,7 +89,7 @@ def update(): config = load_config() repos_in_use = set() for name, repo in config.repos.items(): - server, owner, repo_name, branch = _parse_repo_url(repo) + server, owner, repo_name, branch = parse_repo_url(repo) repos_in_use.add((server, owner, repo_name)) repo_dir = REPO_DIR / server / owner / repo_name if not repo_dir.exists(): From f467796a54121d56b45a4766b25f991a912960dd Mon Sep 17 00:00:00 2001 From: bojiang Date: Sat, 18 May 2024 13:33:34 +0800 Subject: [PATCH 005/125] init --- .gitignore | 10 + Makefile | 14 + README.md | 150 ++++++ outlines-integration/.bentoignore | 5 + outlines-integration/README.md | 88 ++++ outlines-integration/bentofile.yaml | 9 + outlines-integration/requirements.txt | 5 + outlines-integration/service.py | 82 ++++ vllm-chat/.bentoignore | 5 + vllm-chat/README.md | 141 ++++++ vllm-chat/bentofile.yaml | 14 + vllm-chat/bentovllm_openai/__init__.py | 0 vllm-chat/bentovllm_openai/protocol.py | 441 ++++++++++++++++++ vllm-chat/bentovllm_openai/utils.py | 179 +++++++ vllm-chat/build/bentos/llama2/7b/README.md | 16 + .../build/bentos/llama2/7b/apis/openapi.yaml | 173 +++++++ .../build/bentos/llama2/7b/apis/schema.json | 35 ++ vllm-chat/build/bentos/llama2/7b/bento.yaml | 78 ++++ .../bentos/llama2/7b/env/docker/Dockerfile | 64 +++ .../bentos/llama2/7b/env/docker/entrypoint.sh | 56 +++ .../bentos/llama2/7b/env/python/install.sh | 48 ++ .../llama2/7b/env/python/requirements.txt | 4 + .../bentos/llama2/7b/env/python/version.txt | 1 + .../7b/src/bentovllm_openai/__init__.py | 0 .../7b/src/bentovllm_openai/protocol.py | 441 ++++++++++++++++++ .../llama2/7b/src/bentovllm_openai/utils.py | 179 +++++++ .../build/bentos/llama2/7b/src/service.py | 55 +++ vllm-chat/build/bentos/llama2/latest | 1 + vllm-chat/build/client_id | 2 + vllm-chat/requirements.txt | 3 + vllm-chat/service.py | 136 ++++++ 31 files changed, 2435 insertions(+) create mode 100644 .gitignore create mode 100644 Makefile create mode 100644 README.md create mode 100644 outlines-integration/.bentoignore create mode 100644 outlines-integration/README.md create mode 100644 outlines-integration/bentofile.yaml create mode 100644 outlines-integration/requirements.txt create mode 100644 outlines-integration/service.py create mode 100644 vllm-chat/.bentoignore create mode 100644 vllm-chat/README.md create mode 100644 vllm-chat/bentofile.yaml create mode 100644 vllm-chat/bentovllm_openai/__init__.py create mode 100644 vllm-chat/bentovllm_openai/protocol.py create mode 100644 vllm-chat/bentovllm_openai/utils.py create mode 100644 vllm-chat/build/bentos/llama2/7b/README.md create mode 100644 vllm-chat/build/bentos/llama2/7b/apis/openapi.yaml create mode 100644 vllm-chat/build/bentos/llama2/7b/apis/schema.json create mode 100644 vllm-chat/build/bentos/llama2/7b/bento.yaml create mode 100644 vllm-chat/build/bentos/llama2/7b/env/docker/Dockerfile create mode 100644 vllm-chat/build/bentos/llama2/7b/env/docker/entrypoint.sh create mode 100644 vllm-chat/build/bentos/llama2/7b/env/python/install.sh create mode 100644 vllm-chat/build/bentos/llama2/7b/env/python/requirements.txt create mode 100644 vllm-chat/build/bentos/llama2/7b/env/python/version.txt create mode 100644 vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/__init__.py create mode 100644 vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/protocol.py create mode 100644 vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/utils.py create mode 100644 vllm-chat/build/bentos/llama2/7b/src/service.py create mode 100644 vllm-chat/build/bentos/llama2/latest create mode 100644 vllm-chat/build/client_id create mode 100644 vllm-chat/requirements.txt create mode 100644 vllm-chat/service.py diff --git a/.gitignore b/.gitignore new file mode 100644 index 00000000..796b0eb8 --- /dev/null +++ b/.gitignore @@ -0,0 +1,10 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# Environments +venv/ + +# BentoML +bentoml/client_id diff --git a/Makefile b/Makefile new file mode 100644 index 00000000..0b01ca7c --- /dev/null +++ b/Makefile @@ -0,0 +1,14 @@ +PWD := $(shell pwd) + +BENTOML_HOME := $(PWD)/bentoml + +.PHONY: all +all: + @rm -rf $(BENTOML_HOME) + @mkdir -p $(BENTOML_HOME) + @cd vllm-chat && BENTOML_HOME=$(BENTOML_HOME) CLLAMA_MODEL=llama2:7b-chat bentoml build . --version 7b-chat + @cd vllm-chat && BENTOML_HOME=$(BENTOML_HOME) CLLAMA_MODEL=llama2:7b bentoml build . --version 7b + @cd vllm-chat && BENTOML_HOME=$(BENTOML_HOME) CLLAMA_MODEL=mistral:7b-instruct bentoml build . --version 7b-instruct + @cd vllm-chat && BENTOML_HOME=$(BENTOML_HOME) CLLAMA_MODEL=mistral:7b bentoml build . --version 7b + @cd vllm-chat && BENTOML_HOME=$(BENTOML_HOME) CLLAMA_MODEL=mixtral:8x7b-instruct bentoml build . --version 8x7b-instruct + @cd vllm-chat && BENTOML_HOME=$(BENTOML_HOME) CLLAMA_MODEL=mixtral:8x7b bentoml build . --version 8x7b diff --git a/README.md b/README.md new file mode 100644 index 00000000..ceb0ae1c --- /dev/null +++ b/README.md @@ -0,0 +1,150 @@ +
+

Self-host LLMs with vLLM and BentoML

+
+ +This is a BentoML example project, showing you how to serve and deploy open-source Large Language Models using [vLLM](https://vllm.ai), a high-throughput and memory-efficient inference engine. + +See [here](https://github.com/bentoml/BentoML?tab=readme-ov-file#%EF%B8%8F-what-you-can-build-with-bentoml) for a full list of BentoML example projects. + +💡 This example is served as a basis for advanced code customization, such as custom model, inference logic or vLLM options. For simple LLM hosting with OpenAI compatible endpoint without writing any code, see [OpenLLM](https://github.com/bentoml/OpenLLM). + + +## Prerequisites + +- You have installed Python 3.8+ and `pip`. See the [Python downloads page](https://www.python.org/downloads/) to learn more. +- You have a basic understanding of key concepts in BentoML, such as Services. We recommend you read [Quickstart](https://docs.bentoml.com/en/1.2/get-started/quickstart.html) first. +- If you want to test the Service locally, you need a Nvidia GPU with at least 16G VRAM. +- (Optional) We recommend you create a virtual environment for dependency isolation for this project. See the [Conda documentation](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) or the [Python documentation](https://docs.python.org/3/library/venv.html) for details. + +## Install dependencies + +```bash +git clone https://github.com/bentoml/BentoVLLM.git +cd BentoVLLM/mistral-7b-instruct +pip install -r requirements.txt && pip install -f -U "pydantic>=2.0" +``` + +## Run the BentoML Service + +We have defined a BentoML Service in `service.py`. Run `bentoml serve` in your project directory to start the Service. + +```bash +$ bentoml serve . + +2024-01-18T07:51:30+0800 [INFO] [cli] Starting production HTTP BentoServer from "service:VLLM" listening on http://localhost:3000 (Press CTRL+C to quit) +INFO 01-18 07:51:40 model_runner.py:501] Capturing the model for CUDA graphs. This may lead to unexpected consequences if the model is not static. To run the model in eager mode, set 'enforce_eager=True' or use '--enforce-eager' in the CLI. +INFO 01-18 07:51:40 model_runner.py:505] CUDA graphs can take additional 1~3 GiB memory per GPU. If you are running out of memory, consider decreasing `gpu_memory_utilization` or enforcing eager mode. +INFO 01-18 07:51:46 model_runner.py:547] Graph capturing finished in 6 secs. +``` + +The server is now active at [http://localhost:3000](http://localhost:3000/). You can interact with it using the Swagger UI or in other different ways. + +
+ +CURL + +```bash +curl -X 'POST' \ + 'http://localhost:3000/generate' \ + -H 'accept: text/event-stream' \ + -H 'Content-Type: application/json' \ + -d '{ + "prompt": "Explain superconductors like I'\''m five years old", + "tokens": null +}' +``` + +
+ +
+ +Python client + +```python +import bentoml + +with bentoml.SyncHTTPClient("http://localhost:3000") as client: + response_generator = client.generate( + prompt="Explain superconductors like I'm five years old", + tokens=None + ) + for response in response_generator: + print(response) +``` + +
+ +
+ +OpenAI-compatible endpoints + +This Service uses the `@openai_endpoints` decorator to set up OpenAI-compatible endpoints (`chat/completions` and `completions`). This means your client can interact with the backend Service (in this case, the VLLM class) as if they were communicating directly with OpenAI's API. This [utility](mistral-7b-instruct/bentovllm_openai/) does not affect your BentoML Service code, and you can use it for other LLMs as well. + +```python +from openai import OpenAI + +client = OpenAI(base_url='http://localhost:3000/v1', api_key='na') + +# Use the following func to get the available models +client.models.list() + +chat_completion = client.chat.completions.create( + model="mistralai/Mistral-7B-Instruct-v0.2", + messages=[ + { + "role": "user", + "content": "Explain superconductors like I'm five years old" + } + ], + stream=True, +) +for chunk in chat_completion: + # Extract and print the content of the model's reply + print(chunk.choices[0].delta.content or "", end="") +``` + +**Note**: If your Service is deployed with [protected endpoints on BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html#access-protected-deployments), you need to set the environment variable `OPENAI_API_KEY` to your BentoCloud API key first. + +```bash +export OPENAI_API_KEY={YOUR_BENTOCLOUD_API_TOKEN} +``` + +You can then use the following line to replace the client in the above code snippet. Refer to [Obtain the endpoint URL](https://docs.bentoml.com/en/latest/bentocloud/how-tos/call-deployment-endpoints.html#obtain-the-endpoint-url) to retrieve the endpoint URL. + +```python +client = OpenAI(base_url='your_bentocloud_deployment_endpoint_url/v1') +``` + +
+ +For detailed explanations of the Service code, see [vLLM inference](https://docs.bentoml.org/en/latest/use-cases/large-language-models/vllm.html). + +## Deploy to BentoCloud + +After the Service is ready, you can deploy the application to BentoCloud for better management and scalability. [Sign up](https://www.bentoml.com/) if you haven't got a BentoCloud account. + +Make sure you have [logged in to BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html), then run the following command to deploy it. + +```bash +bentoml deploy . +``` + +Once the application is up and running on BentoCloud, you can access it via the exposed URL. + +**Note**: For custom deployment in your own infrastructure, use [BentoML to generate an OCI-compliant image](https://docs.bentoml.com/en/latest/guides/containerization.html). + + +## Different LLM Models + +Besides the mistral-7b-instruct model, we have examples for other models in subdirectories of this repository. Below is a list of these models and links to the example subdirectories. + +- [Mistral-7B-Instruct-v0.2](mistral-7b-instruct/) +- [Mixtral-8x7B-Instruct-v0.1 with gptq quantization](mistral-7b-instruct/) +- [Llama-2-7b-chat-hf](llama2-7b-chat/) +- [SOLAR-10.7B-v1.0](solar-10.7b-instruct/) + + +## LLM tools integration examples + +- Every model directory contains codes to add OpenAI compatible endpoints to the BentoML service. +- [outlines-integration/](outlines-integration/) contains the code to integrate with [outlines](https://github.com/outlines-dev/outlines) for structured generation. diff --git a/outlines-integration/.bentoignore b/outlines-integration/.bentoignore new file mode 100644 index 00000000..d9cf1150 --- /dev/null +++ b/outlines-integration/.bentoignore @@ -0,0 +1,5 @@ +__pycache__/ +*.py[cod] +*$py.class +.ipynb_checkpoints +venv/ diff --git a/outlines-integration/README.md b/outlines-integration/README.md new file mode 100644 index 00000000..d3b4edfe --- /dev/null +++ b/outlines-integration/README.md @@ -0,0 +1,88 @@ +
+

Output structured data with Outlines and BentoML

+
+ +[Outlines](https://github.com/outlines-dev/outlines) is an open-source Python package for structured text generation, integrating with various models to produce controlled, format-specific outputs​. It offers capabilities like fast regex-structured generation, JSON generation following a JSON schema or a Pydantic model, and grammar-structured generation. + +This is a BentoML example project, demonstrating how to output structured data from an LLM using Outlines and BentoML. See [here](https://github.com/bentoml/BentoML?tab=readme-ov-file#%EF%B8%8F-what-you-can-build-with-bentoml) for a full list of BentoML example projects. + +## Prerequisites + +- You have installed Python 3.8+ and `pip`. See the [Python downloads page](https://www.python.org/downloads/) to learn more. +- You have a basic understanding of key concepts in BentoML, such as Services. We recommend you read [Quickstart](https://docs.bentoml.com/en/1.2/get-started/quickstart.html) first. +- If you want to test the Service locally, you need a Nvidia GPU with at least 16G VRAM. +- (Optional) We recommend you create a virtual environment for dependency isolation for this project. See the [Conda documentation](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) or the [Python documentation](https://docs.python.org/3/library/venv.html) for details. + +## Install dependencies + +```bash +git clone https://github.com/bentoml/BentoVLLM.git +cd BentoVLLM/outlines-integration +pip install -r requirements.txt && pip install -f -U "pydantic>=2.0" +``` + +## Run the BentoML Service + +We have defined a BentoML Service in `service.py`. Run `bentoml serve` in your project directory to start the Service. + +```bash +$ bentoml serve . + +2024-03-27T10:14:50+0000 [INFO] [cli] Starting production HTTP BentoServer from "service:VLLM" listening on http://localhost:3000 (Press CTRL+C to quit) +INFO 03-27 10:14:54 llm_engine.py:87] Initializing an LLM engine with config: model='mistralai/Mistral-7B-Instruct-v0.2', tokenizer='mistralai/Mistral-7B-Instruct-v0.2', tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.bfloat16, max_seq_len=1024, download_dir=None, load_format=auto, tensor_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto, device_config=cuda, seed=0) +``` + +The server is now active at [http://localhost:3000](http://localhost:3000/). You can interact with it using the Swagger UI or in other different ways. + +CURL + +```bash +curl -X 'POST' \ + 'http://localhost:3000/generate' \ + -H 'accept: text/event-stream' \ + -H 'Content-Type: application/json' \ + -d '{ + "prompt": "Create a user profile with the fields name, last_name and id. name should be common English first names. last_name should be common English last names. id should be a random integer", + "max_tokens": 1024, + "json_schema": "\n{\n \"title\": \"User\",\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\"type\": \"string\"},\n \"last_name\": {\"type\": \"string\"},\n \"id\": {\"type\": \"integer\"}\n }\n}\n", + "regex_string": null +}' +``` + +Python client + +```python +import bentoml + +with bentoml.SyncHTTPClient("http://localhost:3000") as client: + result = client.generate( + json_schema="\n{\n \"title\": \"User\",\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\"type\": \"string\"},\n \"last_name\": {\"type\": \"string\"},\n \"id\": {\"type\": \"integer\"}\n }\n}\n", + max_tokens=1024, + prompt="Create a user profile with the fields name, last_name and id. name should be common English first names. last_name should be common English last names. id should be a random integer", + regex_string="", + ) +``` + +Example output: + +```bash +{ + "name": "Oliver", + "last_name": "Johnson", + "id": 123456 +} +``` + +## Deploy to BentoCloud + +After the Service is ready, you can deploy the application to BentoCloud for better management and scalability. [Sign up](https://www.bentoml.com/) if you haven't got a BentoCloud account. + +Make sure you have [logged in to BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html), then run the following command to deploy it. + +```bash +bentoml deploy . +``` + +Once the application is up and running on BentoCloud, you can access it via the exposed URL. + +**Note**: For custom deployment in your own infrastructure, use [BentoML to generate an OCI-compliant image](https://docs.bentoml.com/en/latest/guides/containerization.html). diff --git a/outlines-integration/bentofile.yaml b/outlines-integration/bentofile.yaml new file mode 100644 index 00000000..54f2fb0a --- /dev/null +++ b/outlines-integration/bentofile.yaml @@ -0,0 +1,9 @@ +service: "service:VLLM" +labels: + owner: bentoml-team + stage: demo +include: +- "*.py" +python: + requirements_txt: "./requirements.txt" + lock_packages: false diff --git a/outlines-integration/requirements.txt b/outlines-integration/requirements.txt new file mode 100644 index 00000000..f706074e --- /dev/null +++ b/outlines-integration/requirements.txt @@ -0,0 +1,5 @@ +bentoml>=1.2.4 +torch==2.1.2 +transformers==4.38.2 +vllm==0.3.3 +outlines==0.0.37 diff --git a/outlines-integration/service.py b/outlines-integration/service.py new file mode 100644 index 00000000..f1be8970 --- /dev/null +++ b/outlines-integration/service.py @@ -0,0 +1,82 @@ +import uuid +import typing as t +from typing import AsyncGenerator + +import bentoml +from annotated_types import Ge, Le +from typing_extensions import Annotated + + +MAX_TOKENS = 1024 +PROMPT_TEMPLATE = """[INST] +Always assist with care, respect, and truth. Respond with utmost utility yet securely. Avoid harmful, unethical, prejudiced, or negative content. Ensure replies promote fairness and positivity. +{user_prompt} [/INST] """ + + +MODEL_ID = "mistralai/Mistral-7B-Instruct-v0.2" + +DEFAULT_SCHEMA = """ +{ + "title": "User", + "type": "object", + "properties": { + "name": {"type": "string"}, + "last_name": {"type": "string"}, + "id": {"type": "integer"} + } +} +""" + +DEFAULT_USER_PROMPT = "Create a user profile with the fields name, last_name and id. name should be common English first names. last_name should be common English last names. id should be a random integer" + + +@bentoml.service( + name="mistral-7b-instruct-outlines-service", + traffic={ + "timeout": 300, + }, + resources={ + "gpu": 1, + "gpu_type": "nvidia-l4", + }, +) +class VLLM: + def __init__(self) -> None: + from vllm import AsyncEngineArgs, AsyncLLMEngine + ENGINE_ARGS = AsyncEngineArgs( + model=MODEL_ID, + max_model_len=MAX_TOKENS + ) + + self.engine = AsyncLLMEngine.from_engine_args(ENGINE_ARGS) + + @bentoml.api + async def generate( + self, + prompt: str = DEFAULT_USER_PROMPT, + max_tokens: Annotated[int, Ge(128), Le(MAX_TOKENS)] = MAX_TOKENS, + json_schema: t.Optional[str] = DEFAULT_SCHEMA, + regex_string: t.Optional[str] = None, + ) -> AsyncGenerator[str, None]: + from vllm import SamplingParams + from outlines.integrations.vllm import JSONLogitsProcessor, RegexLogitsProcessor + + if json_schema is not None: + logits_processors = [JSONLogitsProcessor(json_schema, self.engine.engine)] + elif regex_string is not None: + logits_processors = [RegexLogitsProcessor(regex_string, self.engine.engine)] + else: + logits_processors = [] + + sampling_param = SamplingParams( + max_tokens=max_tokens, + logits_processors=logits_processors, + ) + prompt = PROMPT_TEMPLATE.format(user_prompt=prompt) + stream = await self.engine.add_request(uuid.uuid4().hex, prompt, sampling_param) + + cursor = 0 + async for request_output in stream: + text = request_output.outputs[0].text + yield text[cursor:] + cursor = len(text) diff --git a/vllm-chat/.bentoignore b/vllm-chat/.bentoignore new file mode 100644 index 00000000..d9cf1150 --- /dev/null +++ b/vllm-chat/.bentoignore @@ -0,0 +1,5 @@ +__pycache__/ +*.py[cod] +*$py.class +.ipynb_checkpoints +venv/ diff --git a/vllm-chat/README.md b/vllm-chat/README.md new file mode 100644 index 00000000..8796f668 --- /dev/null +++ b/vllm-chat/README.md @@ -0,0 +1,141 @@ +
+

Self-host Llama 2 7B with vLLM and BentoML

+
+ +This is a BentoML example project, showing you how to serve and deploy Llama 2 7B using [vLLM](https://vllm.ai), a high-throughput and memory-efficient inference engine. + +See [here](https://github.com/bentoml/BentoML?tab=readme-ov-file#%EF%B8%8F-what-you-can-build-with-bentoml) for a full list of BentoML example projects. + +💡 This example is served as a basis for advanced code customization, such as custom model, inference logic or vLLM options. For simple LLM hosting with OpenAI compatible endpoint without writing any code, see [OpenLLM](https://github.com/bentoml/OpenLLM). + + +## Prerequisites + +- You have installed Python 3.8+ and `pip`. See the [Python downloads page](https://www.python.org/downloads/) to learn more. +- You have a basic understanding of key concepts in BentoML, such as Services. We recommend you read [Quickstart](https://docs.bentoml.com/en/1.2/get-started/quickstart.html) first. +- You have gained access to Llama 2 7B on [its official website](https://llama.meta.com/) and [Hugging Face](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf). +- If you want to test the Service locally, you need a Nvidia GPU with at least 16G VRAM. +- (Optional) We recommend you create a virtual environment for dependency isolation for this project. See the [Conda documentation](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) or the [Python documentation](https://docs.python.org/3/library/venv.html) for details. + +## Install dependencies + +```bash +git clone https://github.com/bentoml/BentoVLLM.git +cd BentoVLLM/llama2-7b-chat +pip install -r requirements.txt && pip install -f -U "pydantic>=2.0" +``` + +## Download the model + +```bash +python import_model.py +``` + +## Run the BentoML Service + +We have defined a BentoML Service in `service.py`. Run `bentoml serve` in your project directory to start the Service. + +```python +$ bentoml serve . + +2024-01-18T07:51:30+0800 [INFO] [cli] Starting production HTTP BentoServer from "service:VLLM" listening on http://localhost:3000 (Press CTRL+C to quit) +INFO 01-18 07:51:40 model_runner.py:501] Capturing the model for CUDA graphs. This may lead to unexpected consequences if the model is not static. To run the model in eager mode, set 'enforce_eager=True' or use '--enforce-eager' in the CLI. +INFO 01-18 07:51:40 model_runner.py:505] CUDA graphs can take additional 1~3 GiB memory per GPU. If you are running out of memory, consider decreasing `gpu_memory_utilization` or enforcing eager mode. +INFO 01-18 07:51:46 model_runner.py:547] Graph capturing finished in 6 secs. +``` + +The server is now active at [http://localhost:3000](http://localhost:3000/). You can interact with it using the Swagger UI or in other different ways. + +
+ +CURL + +```bash +curl -X 'POST' \ + 'http://localhost:3000/generate' \ + -H 'accept: text/event-stream' \ + -H 'Content-Type: application/json' \ + -d '{ + "prompt": "Explain superconductors like I'\''m five years old", + "tokens": null +}' +``` + +
+ +
+ +Python client + +```python +import bentoml + +with bentoml.SyncHTTPClient("http://localhost:3000") as client: + response_generator = client.generate( + prompt="Explain superconductors like I'm five years old", + tokens=None + ) + for response in response_generator: + print(response) +``` + +
+ +
+ +OpenAI-compatible endpoints + +This Service uses the `@openai_endpoints` decorator to set up OpenAI-compatible endpoints (`chat/completions` and `completions`). This means your client can interact with the backend Service (in this case, the VLLM class) as if they were communicating directly with OpenAI's API. This [utility](bentovllm_openai/) does not affect your BentoML Service code, and you can use it for other LLMs as well. + +```python +from openai import OpenAI + +client = OpenAI(base_url='http://localhost:3000/v1', api_key='na') + +# Use the following func to get the available models +client.models.list() + +chat_completion = client.chat.completions.create( + model="meta-llama/Llama-2-7b-chat-hf", + messages=[ + { + "role": "user", + "content": "Explain superconductors like I'm five years old" + } + ], + stream=True, +) +for chunk in chat_completion: + # Extract and print the content of the model's reply + print(chunk.choices[0].delta.content or "", end="") +``` + +**Note**: If your Service is deployed with [protected endpoints on BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html#access-protected-deployments), you need to set the environment variable `OPENAI_API_KEY` to your BentoCloud API key first. + +```bash +export OPENAI_API_KEY={YOUR_BENTOCLOUD_API_TOKEN} +``` + +You can then use the following line to replace the client in the above code snippet. Refer to [Obtain the endpoint URL](https://docs.bentoml.com/en/latest/bentocloud/how-tos/call-deployment-endpoints.html#obtain-the-endpoint-url) to retrieve the endpoint URL. + +```python +client = OpenAI(base_url='your_bentocloud_deployment_endpoint_url/v1') +``` + +
+ +For detailed explanations of the Service code, see [vLLM inference](https://docs.bentoml.org/en/latest/use-cases/large-language-models/vllm.html). + +## Deploy to BentoCloud + +After the Service is ready, you can deploy the application to BentoCloud for better management and scalability. [Sign up](https://www.bentoml.com/) if you haven't got a BentoCloud account. + +Make sure you have [logged in to BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html), then run the following command to deploy it. + +```bash +bentoml deploy . +``` + +Once the application is up and running on BentoCloud, you can access it via the exposed URL. + +**Note**: For custom deployment in your own infrastructure, use [BentoML to generate an OCI-compliant image](https://docs.bentoml.com/en/latest/guides/containerization.html). diff --git a/vllm-chat/bentofile.yaml b/vllm-chat/bentofile.yaml new file mode 100644 index 00000000..f0f710f5 --- /dev/null +++ b/vllm-chat/bentofile.yaml @@ -0,0 +1,14 @@ +service: "service:VLLM" +labels: + owner: bentoml-team + stage: demo +include: +- "*.py" +- "bentovllm_openai/*.py" +python: + packages: + - git+https://github.com/bentoml/simple_di.git@master +envs: + - name: HF_TOKEN + - name: CLLAMA_MODEL + value: llama2 diff --git a/vllm-chat/bentovllm_openai/__init__.py b/vllm-chat/bentovllm_openai/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/vllm-chat/bentovllm_openai/protocol.py b/vllm-chat/bentovllm_openai/protocol.py new file mode 100644 index 00000000..7de4d1da --- /dev/null +++ b/vllm-chat/bentovllm_openai/protocol.py @@ -0,0 +1,441 @@ +from __future__ import annotations + +# Adapted from +# https://github.com/lm-sys/FastChat/blob/168ccc29d3f7edc50823016105c024fe2282732a/fastchat/protocol/openai_api_protocol.py +import time +import uuid +from typing import TYPE_CHECKING, Dict, List, Literal, Optional, Union + +from pydantic import BaseModel, Field, model_validator + +if TYPE_CHECKING: + import torch + from vllm.sampling_params import SamplingParams + + +def random_uuid() -> str: + return str(uuid.uuid4().hex) + + +class ErrorResponse(BaseModel): + object: str = "error" + message: str + type: str + param: Optional[str] = None + code: int + + +class ModelPermission(BaseModel): + id: str = Field(default_factory=lambda: f"modelperm-{random_uuid()}") + object: str = "model_permission" + created: int = Field(default_factory=lambda: int(time.time())) + allow_create_engine: bool = False + allow_sampling: bool = True + allow_logprobs: bool = True + allow_search_indices: bool = False + allow_view: bool = True + allow_fine_tuning: bool = False + organization: str = "*" + group: Optional[str] = None + is_blocking: str = False + + +class ModelCard(BaseModel): + id: str + object: str = "model" + created: int = Field(default_factory=lambda: int(time.time())) + owned_by: str = "vllm" + root: Optional[str] = None + parent: Optional[str] = None + permission: List[ModelPermission] = Field(default_factory=list) + + +class ModelList(BaseModel): + object: str = "list" + data: List[ModelCard] = Field(default_factory=list) + + +class UsageInfo(BaseModel): + prompt_tokens: int = 0 + total_tokens: int = 0 + completion_tokens: Optional[int] = 0 + + +class ResponseFormat(BaseModel): + # type must be "json_object" or "text" + type: str = Literal["text", "json_object"] + + +class ChatCompletionRequest(BaseModel): + # Ordered by official OpenAI API documentation + # https://platform.openai.com/docs/api-reference/chat/create + messages: List[Dict[str, str]] + model: str + frequency_penalty: Optional[float] = 0.0 + logit_bias: Optional[Dict[str, float]] = None + logprobs: Optional[bool] = False + top_logprobs: Optional[int] = None + max_tokens: Optional[int] = None + n: Optional[int] = 1 + presence_penalty: Optional[float] = 0.0 + response_format: Optional[ResponseFormat] = None + seed: Optional[int] = None + stop: Optional[Union[str, List[str]]] = Field(default_factory=list) + stream: Optional[bool] = False + temperature: Optional[float] = 0.7 + top_p: Optional[float] = 1.0 + user: Optional[str] = None + + # doc: begin-chat-completion-sampling-params + best_of: Optional[int] = None + use_beam_search: Optional[bool] = False + top_k: Optional[int] = -1 + min_p: Optional[float] = 0.0 + repetition_penalty: Optional[float] = 1.0 + length_penalty: Optional[float] = 1.0 + early_stopping: Optional[bool] = False + ignore_eos: Optional[bool] = False + min_tokens: Optional[int] = 0 + stop_token_ids: Optional[List[int]] = Field(default_factory=list) + skip_special_tokens: Optional[bool] = True + spaces_between_special_tokens: Optional[bool] = True + # doc: end-chat-completion-sampling-params + + # doc: begin-chat-completion-extra-params + echo: Optional[bool] = Field( + default=False, + description=( + "If true, the new message will be prepended with the last message " + "if they belong to the same role." + ), + ) + add_generation_prompt: Optional[bool] = Field( + default=True, + description=( + "If true, the generation prompt will be added to the chat template. " + "This is a parameter used by chat template in tokenizer config of the " + "model." + ), + ) + include_stop_str_in_output: Optional[bool] = Field( + default=False, + description=( + "Whether to include the stop string in the output. " + "This is only applied when the stop or stop_token_ids is set." + ), + ) + guided_json: Optional[Union[str, dict, BaseModel]] = Field( + default=None, + description=("If specified, the output will follow the JSON schema."), + ) + guided_regex: Optional[str] = Field( + default=None, + description=("If specified, the output will follow the regex pattern."), + ) + guided_choice: Optional[List[str]] = Field( + default=None, + description=("If specified, the output will be exactly one of the choices."), + ) + guided_grammar: Optional[str] = Field( + default=None, + description=("If specified, the output will follow the context free grammar."), + ) + + # doc: end-chat-completion-extra-params + + def to_sampling_params(self) -> SamplingParams: + if self.logprobs and not self.top_logprobs: + raise ValueError("Top logprobs must be set when logprobs is.") + + logits_processors = None + if self.logit_bias: + + def logit_bias_logits_processor( + token_ids: List[int], logits: torch.Tensor + ) -> torch.Tensor: + for token_id, bias in self.logit_bias.items(): + # Clamp the bias between -100 and 100 per OpenAI API spec + bias = min(100, max(-100, bias)) + logits[int(token_id)] += bias + return logits + + logits_processors = [logit_bias_logits_processor] + + from vllm.sampling_params import SamplingParams + + return SamplingParams( + n=self.n, + presence_penalty=self.presence_penalty, + frequency_penalty=self.frequency_penalty, + repetition_penalty=self.repetition_penalty, + temperature=self.temperature, + top_p=self.top_p, + min_p=self.min_p, + seed=self.seed, + stop=self.stop, + stop_token_ids=self.stop_token_ids, + max_tokens=self.max_tokens, + min_tokens=self.min_tokens, + logprobs=self.top_logprobs if self.logprobs else None, + prompt_logprobs=self.top_logprobs if self.echo else None, + best_of=self.best_of, + top_k=self.top_k, + ignore_eos=self.ignore_eos, + use_beam_search=self.use_beam_search, + early_stopping=self.early_stopping, + skip_special_tokens=self.skip_special_tokens, + spaces_between_special_tokens=self.spaces_between_special_tokens, + include_stop_str_in_output=self.include_stop_str_in_output, + length_penalty=self.length_penalty, + logits_processors=logits_processors, + ) + + @model_validator(mode="before") + @classmethod + def check_guided_decoding_count(cls, data): + guide_count = sum( + [ + "guided_json" in data and data["guided_json"] is not None, + "guided_regex" in data and data["guided_regex"] is not None, + "guided_choice" in data and data["guided_choice"] is not None, + ] + ) + if guide_count > 1: + raise ValueError( + "You can only use one kind of guided decoding " + "('guided_json', 'guided_regex' or 'guided_choice')." + ) + return data + + +class CompletionRequest(BaseModel): + # Ordered by official OpenAI API documentation + # https://platform.openai.com/docs/api-reference/completions/create + model: str + prompt: Union[List[int], List[List[int]], str, List[str]] + best_of: Optional[int] = None + echo: Optional[bool] = False + frequency_penalty: Optional[float] = 0.0 + logit_bias: Optional[Dict[str, float]] = None + logprobs: Optional[int] = None + max_tokens: Optional[int] = 16 + n: Optional[int] = 1 + presence_penalty: Optional[float] = 0.0 + seed: Optional[int] = None + stop: Optional[Union[str, List[str]]] = Field(default_factory=list) + stream: Optional[bool] = False + suffix: Optional[str] = None + temperature: Optional[float] = 1.0 + top_p: Optional[float] = 1.0 + user: Optional[str] = None + + # doc: begin-completion-sampling-params + use_beam_search: Optional[bool] = False + top_k: Optional[int] = -1 + min_p: Optional[float] = 0.0 + repetition_penalty: Optional[float] = 1.0 + length_penalty: Optional[float] = 1.0 + early_stopping: Optional[bool] = False + stop_token_ids: Optional[List[int]] = Field(default_factory=list) + ignore_eos: Optional[bool] = False + min_tokens: Optional[int] = 0 + skip_special_tokens: Optional[bool] = True + spaces_between_special_tokens: Optional[bool] = True + # doc: end-completion-sampling-params + + # doc: begin-completion-extra-params + include_stop_str_in_output: Optional[bool] = Field( + default=False, + description=( + "Whether to include the stop string in the output. " + "This is only applied when the stop or stop_token_ids is set." + ), + ) + response_format: Optional[ResponseFormat] = Field( + default=None, + description=( + "Similar to chat completion, this parameter specifies the format of " + "output. Only {'type': 'json_object'} or {'type': 'text' } is " + "supported." + ), + ) + guided_json: Optional[Union[str, dict, BaseModel]] = Field( + default=None, + description=("If specified, the output will follow the JSON schema."), + ) + guided_regex: Optional[str] = Field( + default=None, + description=("If specified, the output will follow the regex pattern."), + ) + guided_choice: Optional[List[str]] = Field( + default=None, + description=("If specified, the output will be exactly one of the choices."), + ) + guided_grammar: Optional[str] = Field( + default=None, + description=("If specified, the output will follow the context free grammar."), + ) + + # doc: end-completion-extra-params + + def to_sampling_params(self): + echo_without_generation = self.echo and self.max_tokens == 0 + + logits_processors = None + if self.logit_bias is not None: + + def logit_bias_logits_processor( + token_ids: List[int], logits: torch.Tensor + ) -> torch.Tensor: + for token_id, bias in self.logit_bias.items(): + # Clamp the bias between -100 and 100 per OpenAI API spec + bias = min(100, max(-100, bias)) + logits[int(token_id)] += bias + return logits + + logits_processors = [logit_bias_logits_processor] + + from vllm.sampling_params import SamplingParams + + return SamplingParams( + n=self.n, + best_of=self.best_of, + presence_penalty=self.presence_penalty, + frequency_penalty=self.frequency_penalty, + repetition_penalty=self.repetition_penalty, + temperature=self.temperature, + top_p=self.top_p, + top_k=self.top_k, + min_p=self.min_p, + seed=self.seed, + stop=self.stop, + stop_token_ids=self.stop_token_ids, + ignore_eos=self.ignore_eos, + max_tokens=self.max_tokens if not echo_without_generation else 1, + min_tokens=self.min_tokens, + logprobs=self.logprobs, + use_beam_search=self.use_beam_search, + early_stopping=self.early_stopping, + prompt_logprobs=self.logprobs if self.echo else None, + skip_special_tokens=self.skip_special_tokens, + spaces_between_special_tokens=(self.spaces_between_special_tokens), + include_stop_str_in_output=self.include_stop_str_in_output, + length_penalty=self.length_penalty, + logits_processors=logits_processors, + ) + + @model_validator(mode="before") + @classmethod + def check_guided_decoding_count(cls, data): + guide_count = sum( + [ + "guided_json" in data and data["guided_json"] is not None, + "guided_regex" in data and data["guided_regex"] is not None, + "guided_choice" in data and data["guided_choice"] is not None, + ] + ) + if guide_count > 1: + raise ValueError( + "You can only use one kind of guided decoding " + "('guided_json', 'guided_regex' or 'guided_choice')." + ) + return data + + +class LogProbs(BaseModel): + text_offset: List[int] = Field(default_factory=list) + token_logprobs: List[Optional[float]] = Field(default_factory=list) + tokens: List[str] = Field(default_factory=list) + top_logprobs: Optional[List[Optional[Dict[str, float]]]] = None + + +class CompletionResponseChoice(BaseModel): + index: int + text: str + logprobs: Optional[LogProbs] = None + finish_reason: Optional[Literal["stop", "length"]] = None + stop_reason: Union[None, int, str] = Field( + default=None, + description=( + "The stop string or token id that caused the completion " + "to stop, None if the completion finished for some other reason " + "including encountering the EOS token" + ), + ) + + +class CompletionResponse(BaseModel): + id: str = Field(default_factory=lambda: f"cmpl-{random_uuid()}") + object: str = "text_completion" + created: int = Field(default_factory=lambda: int(time.time())) + model: str + choices: List[CompletionResponseChoice] + usage: UsageInfo + + +class CompletionResponseStreamChoice(BaseModel): + index: int + text: str + logprobs: Optional[LogProbs] = None + finish_reason: Optional[Literal["stop", "length"]] = None + stop_reason: Union[None, int, str] = Field( + default=None, + description=( + "The stop string or token id that caused the completion " + "to stop, None if the completion finished for some other reason " + "including encountering the EOS token" + ), + ) + + +class CompletionStreamResponse(BaseModel): + id: str = Field(default_factory=lambda: f"cmpl-{random_uuid()}") + object: str = "text_completion" + created: int = Field(default_factory=lambda: int(time.time())) + model: str + choices: List[CompletionResponseStreamChoice] + usage: Optional[UsageInfo] = Field(default=None) + + +class ChatMessage(BaseModel): + role: str + content: str + + +class ChatCompletionResponseChoice(BaseModel): + index: int + message: ChatMessage + logprobs: Optional[LogProbs] = None + finish_reason: Optional[Literal["stop", "length"]] = None + stop_reason: Union[None, int, str] = None + + +class ChatCompletionResponse(BaseModel): + id: str = Field(default_factory=lambda: f"chatcmpl-{random_uuid()}") + object: str = "chat.completion" + created: int = Field(default_factory=lambda: int(time.time())) + model: str + choices: List[ChatCompletionResponseChoice] + usage: UsageInfo + + +class DeltaMessage(BaseModel): + role: Optional[str] = None + content: Optional[str] = None + + +class ChatCompletionResponseStreamChoice(BaseModel): + index: int + delta: DeltaMessage + logprobs: Optional[LogProbs] = None + finish_reason: Optional[Literal["stop", "length"]] = None + stop_reason: Union[None, int, str] = None + + +class ChatCompletionStreamResponse(BaseModel): + id: str = Field(default_factory=lambda: f"chatcmpl-{random_uuid()}") + object: str = "chat.completion.chunk" + created: int = Field(default_factory=lambda: int(time.time())) + model: str + choices: List[ChatCompletionResponseStreamChoice] + usage: Optional[UsageInfo] = Field(default=None) diff --git a/vllm-chat/bentovllm_openai/utils.py b/vllm-chat/bentovllm_openai/utils.py new file mode 100644 index 00000000..87da555f --- /dev/null +++ b/vllm-chat/bentovllm_openai/utils.py @@ -0,0 +1,179 @@ +from __future__ import annotations + +import asyncio +import typing as t + +from _bentoml_sdk.service.factory import Service +from fastapi import FastAPI, Request +from fastapi.responses import JSONResponse, StreamingResponse + +from .protocol import ChatCompletionRequest, CompletionRequest, ErrorResponse + +T = t.TypeVar("T", bound=object) + +if t.TYPE_CHECKING: + from vllm import AsyncLLMEngine + + +def openai_endpoints( + served_model: str, + response_role: str = "assistant", + chat_template: t.Optional[str] = None, + chat_template_model_id: t.Optional[str] = None, +): + + def openai_wrapper(svc: Service[T]): + + cls = svc.inner + app = FastAPI() + + class new_cls(cls): + + def __init__(self): + + super().__init__() + + # we need to import bentoml before vllm so + # `prometheus_client` won't cause import troubles + # That's also why we put these codes inside class's + # `__init__` function + import bentoml + from vllm.entrypoints.openai.serving_chat import OpenAIServingChat + from vllm.entrypoints.openai.serving_completion import ( + OpenAIServingCompletion, + ) + + # https://github.com/vllm-project/vllm/issues/2683 + class PatchedOpenAIServingChat(OpenAIServingChat): + def __init__( + self, + engine: AsyncLLMEngine, + served_model: str, + response_role: str, + chat_template=None, + ): + super(OpenAIServingChat, self).__init__( + engine=engine, + served_model=served_model, + lora_modules=None, + ) + self.response_role = response_role + try: + event_loop = asyncio.get_running_loop() + except RuntimeError: + event_loop = None + + if event_loop is not None and event_loop.is_running(): + event_loop.create_task( + self._load_chat_template(chat_template) + ) + else: + asyncio.run(self._load_chat_template(chat_template)) + + async def _load_chat_template(self, chat_template): + # Simply making this function async is usually already enough to give the parent + # class time to load the tokenizer (so usually no sleeping happens here) + # However, it feels safer to be explicit about this since asyncio does not + # guarantee the order in which scheduled tasks are run + while self.tokenizer is None: + await asyncio.sleep(0.1) + return super()._load_chat_template(chat_template) + + self.openai_serving_completion = OpenAIServingCompletion( + engine=self.engine, + served_model=served_model, + ) + + self.chat_template = chat_template + if self.chat_template is None and chat_template_model_id is not None: + from transformers import AutoTokenizer + + _tokenizer = AutoTokenizer.from_pretrained(chat_template_model_id) + self.chat_template = _tokenizer.chat_template + + self.openai_serving_chat = PatchedOpenAIServingChat( + engine=self.engine, + served_model=served_model, + response_role=response_role, + chat_template=self.chat_template, + ) + + @app.get("/models") + async def show_available_models(): + models = await self.openai_serving_chat.show_available_models() + return JSONResponse(content=models.model_dump()) + + @app.post("/chat/completions") + async def create_chat_completion( + request: ChatCompletionRequest, raw_request: Request + ): + generator = await self.openai_serving_chat.create_chat_completion( + request, raw_request + ) + if isinstance(generator, ErrorResponse): + return JSONResponse( + content=generator.model_dump(), status_code=generator.code + ) + if request.stream: + return StreamingResponse( + content=generator, media_type="text/event-stream" + ) + else: + return JSONResponse(content=generator.model_dump()) + + @app.post("/completions") + async def create_completion( + request: CompletionRequest, raw_request: Request + ): + generator = await self.openai_serving_completion.create_completion( + request, raw_request + ) + if isinstance(generator, ErrorResponse): + return JSONResponse( + content=generator.model_dump(), status_code=generator.code + ) + if request.stream: + return StreamingResponse( + content=generator, media_type="text/event-stream" + ) + else: + return JSONResponse(content=generator.model_dump()) + + new_cls.__name__ = "%s_OpenAI" % cls.__name__ + svc.inner = new_cls + svc.mount_asgi_app(app, path="/v1/") + return svc + + return openai_wrapper + + +# helper function to make a httpx client for BentoML service +def _make_httpx_client(url, svc): + + from urllib.parse import urlparse + + import httpx + from bentoml._internal.utils.uri import uri_to_path + + timeout = svc.config["traffic"]["timeout"] + headers = {"Runner-Name": svc.name} + parsed = urlparse(url) + transport = None + target_url = url + + if parsed.scheme == "file": + uds = uri_to_path(url) + transport = httpx.HTTPTransport(uds=uds) + target_url = "http://127.0.0.1:3000" + elif parsed.scheme == "tcp": + target_url = f"http://{parsed.netloc}" + + return ( + httpx.Client( + transport=transport, + timeout=timeout, + follow_redirects=True, + headers=headers, + ), + target_url, + ) diff --git a/vllm-chat/build/bentos/llama2/7b/README.md b/vllm-chat/build/bentos/llama2/7b/README.md new file mode 100644 index 00000000..f5c4669f --- /dev/null +++ b/vllm-chat/build/bentos/llama2/7b/README.md @@ -0,0 +1,16 @@ +# llama2:7b + +[![pypi_status](https://img.shields.io/badge/BentoML-1.2.11-informational)](https://pypi.org/project/BentoML) +[![documentation_status](https://readthedocs.org/projects/bentoml/badge/?version=latest)](https://docs.bentoml.com/) +[![join_slack](https://badgen.net/badge/Join/BentoML%20Slack/cyan?icon=slack)](https://l.bentoml.com/join-slack-swagger) +[![BentoML GitHub Repo](https://img.shields.io/github/stars/bentoml/bentoml?style=social)](https://github.com/bentoml/BentoML) +[![Twitter Follow](https://img.shields.io/twitter/follow/bentomlai?label=Follow%20BentoML&style=social)](https://twitter.com/bentomlai) + +This is a Machine Learning Service created with BentoML. + +## Help + +* [📖 Documentation](https://docs.bentoml.com/en/latest/): Learn how to use BentoML. +* [💬 Community](https://l.bentoml.com/join-slack-swagger): Join the BentoML Slack community. +* [🐛 GitHub Issues](https://github.com/bentoml/BentoML/issues): Report bugs and feature requests. +* Tip: you can also [customize this README](https://docs.bentoml.com/en/latest/concepts/bento.html#description). diff --git a/vllm-chat/build/bentos/llama2/7b/apis/openapi.yaml b/vllm-chat/build/bentos/llama2/7b/apis/openapi.yaml new file mode 100644 index 00000000..132bcddb --- /dev/null +++ b/vllm-chat/build/bentos/llama2/7b/apis/openapi.yaml @@ -0,0 +1,173 @@ +components: + schemas: + InternalServerError: + description: Internal Server Error + properties: + msg: + title: Message + type: string + type: + title: Error Type + type: string + required: + - msg + - type + title: InternalServerError + type: object + InvalidArgument: + description: Bad Request + properties: + msg: + title: Message + type: string + type: + title: Error Type + type: string + required: + - msg + - type + title: InvalidArgument + type: object + NotFound: + description: Not Found + properties: + msg: + title: Message + type: string + type: + title: Error Type + type: string + required: + - msg + - type + title: NotFound + type: object + generate__Input: + properties: + max_tokens: + default: 1024 + maximum: 1024 + minimum: 128 + title: Max Tokens + type: integer + prompt: + default: Explain superconductors like I'm five years old + title: Prompt + type: string + title: generate__Input + type: object +info: + contact: + email: contact@bentoml.com + name: BentoML Team + description: "# llama2:dev\n\n[![pypi_status](https://img.shields.io/badge/BentoML-1.2.11-informational)](https://pypi.org/project/BentoML)\n\ + [![documentation_status](https://readthedocs.org/projects/bentoml/badge/?version=latest)](https://docs.bentoml.com/)\n\ + [![join_slack](https://badgen.net/badge/Join/BentoML%20Slack/cyan?icon=slack)](https://l.bentoml.com/join-slack-swagger)\n\ + [![BentoML GitHub Repo](https://img.shields.io/github/stars/bentoml/bentoml?style=social)](https://github.com/bentoml/BentoML)\n\ + [![Twitter Follow](https://img.shields.io/twitter/follow/bentomlai?label=Follow%20BentoML&style=social)](https://twitter.com/bentomlai)\n\ + \nThis is a Machine Learning Service created with BentoML.\n\n## Help\n\n* [\U0001F4D6\ + \ Documentation](https://docs.bentoml.com/en/latest/): Learn how to use BentoML.\n\ + * [\U0001F4AC Community](https://l.bentoml.com/join-slack-swagger): Join the BentoML\ + \ Slack community.\n* [\U0001F41B GitHub Issues](https://github.com/bentoml/BentoML/issues):\ + \ Report bugs and feature requests.\n* Tip: you can also [customize this README](https://docs.bentoml.com/en/latest/concepts/bento.html#description).\n" + title: llama2 + version: None +openapi: 3.0.2 +paths: + /generate: + post: + description: '' + operationId: llama2__generate + requestBody: + content: + application/json: + schema: + properties: + max_tokens: + default: 1024 + maximum: 1024 + minimum: 128 + title: Max Tokens + type: integer + prompt: + default: Explain superconductors like I'm five years old + title: Prompt + type: string + title: Input + type: object + responses: + 200: + content: + text/event-stream: + schema: + title: strIODescriptor + type: string + description: Successful Response + 400: + content: + application/json: + schema: + $ref: '#/components/schemas/InvalidArgument' + description: Bad Request + 404: + content: + application/json: + schema: + $ref: '#/components/schemas/NotFound' + description: Not Found + 500: + content: + application/json: + schema: + $ref: '#/components/schemas/InternalServerError' + description: Internal Server Error + tags: + - Service APIs + x-bentoml-name: generate + /healthz: + get: + description: Health check endpoint. Expecting an empty response with status + code 200 when the service is in health state. The /healthz + endpoint is deprecated. (since Kubernetes v1.16) + responses: + '200': + description: Successful Response + tags: + - Infrastructure + /livez: + get: + description: Health check endpoint for Kubernetes. Healthy endpoint responses + with a 200 OK status. + responses: + '200': + description: Successful Response + tags: + - Infrastructure + /metrics: + get: + description: Prometheus metrics endpoint. The /metrics responses + with a 200. The output can then be used by a Prometheus sidecar + to scrape the metrics of the service. + responses: + '200': + description: Successful Response + tags: + - Infrastructure + /readyz: + get: + description: A 200 OK status from /readyz endpoint + indicated the service is ready to accept traffic. From that point and onward, + Kubernetes will use /livez endpoint to perform periodic health + checks. + responses: + '200': + description: Successful Response + tags: + - Infrastructure +servers: +- url: . +tags: +- description: BentoML Service API endpoints for inference. + name: Service APIs +- description: Common infrastructure endpoints for observability. + name: Infrastructure diff --git a/vllm-chat/build/bentos/llama2/7b/apis/schema.json b/vllm-chat/build/bentos/llama2/7b/apis/schema.json new file mode 100644 index 00000000..7917c5da --- /dev/null +++ b/vllm-chat/build/bentos/llama2/7b/apis/schema.json @@ -0,0 +1,35 @@ +{ + "name": "llama2", + "type": "service", + "routes": [ + { + "name": "generate", + "route": "/generate", + "batchable": false, + "input": { + "properties": { + "prompt": { + "default": "Explain superconductors like I'm five years old", + "title": "Prompt", + "type": "string" + }, + "max_tokens": { + "default": 1024, + "maximum": 1024, + "minimum": 128, + "title": "Max Tokens", + "type": "integer" + } + }, + "title": "Input", + "type": "object" + }, + "output": { + "title": "strIODescriptor", + "type": "string", + "is_stream": true, + "media_type": "text/event-stream" + } + } + ] +} \ No newline at end of file diff --git a/vllm-chat/build/bentos/llama2/7b/bento.yaml b/vllm-chat/build/bentos/llama2/7b/bento.yaml new file mode 100644 index 00000000..1c3e5f16 --- /dev/null +++ b/vllm-chat/build/bentos/llama2/7b/bento.yaml @@ -0,0 +1,78 @@ +service: service:VLLM +name: llama2 +version: 7b +bentoml_version: 1.2.11 +creation_time: '2024-04-21T09:17:39.844490+00:00' +labels: + owner: bentoml-team + stage: demo +models: [] +runners: [] +entry_service: llama2 +services: +- name: llama2 + service: '' + models: [] + dependencies: [] + config: + name: llama2 + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-l4 +envs: +- name: HF_TOKEN +schema: + name: llama2 + type: service + routes: + - name: generate + route: /generate + batchable: false + input: + properties: + prompt: + default: Explain superconductors like I'm five years old + title: Prompt + type: string + max_tokens: + default: 1024 + maximum: 1024 + minimum: 128 + title: Max Tokens + type: integer + title: Input + type: object + output: + title: strIODescriptor + type: string + is_stream: true + media_type: text/event-stream +apis: [] +docker: + distro: debian + python_version: '3.11' + cuda_version: null + env: + HF_TOKEN: '' + system_packages: null + setup_script: null + base_image: null + dockerfile_template: null +python: + requirements_txt: ./requirements.txt + packages: null + lock_packages: false + index_url: null + no_index: null + trusted_host: null + find_links: null + extra_index_url: null + pip_args: null + wheels: null +conda: + environment_yml: null + channels: null + dependencies: null + pip: null diff --git a/vllm-chat/build/bentos/llama2/7b/env/docker/Dockerfile b/vllm-chat/build/bentos/llama2/7b/env/docker/Dockerfile new file mode 100644 index 00000000..e57d9b5b --- /dev/null +++ b/vllm-chat/build/bentos/llama2/7b/env/docker/Dockerfile @@ -0,0 +1,64 @@ +# =========================================== +# +# THIS IS A GENERATED DOCKERFILE. DO NOT EDIT +# +# =========================================== + +# Block SETUP_BENTO_BASE_IMAGE +FROM python:3.11-slim as base-container + +ENV LANG=C.UTF-8 + +ENV LC_ALL=C.UTF-8 + +ENV PYTHONIOENCODING=UTF-8 + +ENV PYTHONUNBUFFERED=1 + + + +USER root + +ENV DEBIAN_FRONTEND=noninteractive +RUN rm -f /etc/apt/apt.conf.d/docker-clean; echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' > /etc/apt/apt.conf.d/keep-cache +RUN set -eux && \ + apt-get update -y && \ + apt-get install -q -y --no-install-recommends --allow-remove-essential \ + ca-certificates gnupg2 bash build-essential +# Block SETUP_BENTO_USER +ARG BENTO_USER=bentoml +ARG BENTO_USER_UID=1034 +ARG BENTO_USER_GID=1034 +RUN groupadd -g $BENTO_USER_GID -o $BENTO_USER && useradd -m -u $BENTO_USER_UID -g $BENTO_USER_GID -o -r $BENTO_USER +ARG HF_TOKEN= +ENV HF_TOKEN=$HF_TOKEN +ARG BENTO_PATH=/home/bentoml/bento +ENV BENTO_PATH=$BENTO_PATH +ENV BENTOML_HOME=/home/bentoml/ + +RUN mkdir $BENTO_PATH && chown bentoml:bentoml $BENTO_PATH -R +WORKDIR $BENTO_PATH + + + +# Block SETUP_BENTO_COMPONENTS +COPY --chown=bentoml:bentoml ./env/python ./env/python/ +# install python packages with install.sh +RUN bash -euxo pipefail /home/bentoml/bento/env/python/install.sh +COPY --chown=bentoml:bentoml . ./ + +# Block SETUP_BENTO_ENTRYPOINT +RUN rm -rf /var/lib/{apt,cache,log} +# Default port for BentoServer +EXPOSE 3000 + +# Expose Prometheus port +EXPOSE 3001 + +RUN chmod +x /home/bentoml/bento/env/docker/entrypoint.sh + +USER bentoml + +ENTRYPOINT [ "/home/bentoml/bento/env/docker/entrypoint.sh" ] + + diff --git a/vllm-chat/build/bentos/llama2/7b/env/docker/entrypoint.sh b/vllm-chat/build/bentos/llama2/7b/env/docker/entrypoint.sh new file mode 100644 index 00000000..df1892dd --- /dev/null +++ b/vllm-chat/build/bentos/llama2/7b/env/docker/entrypoint.sh @@ -0,0 +1,56 @@ +#!/usr/bin/env bash +set -Eeuo pipefail + +# check to see if this file is being run or sourced from another script +_is_sourced() { + # https://unix.stackexchange.com/a/215279 + [ "${#FUNCNAME[@]}" -ge 2 ] && + [ "${FUNCNAME[0]}" = '_is_sourced' ] && + [ "${FUNCNAME[1]}" = 'source' ] +} + +_main() { + # For backwards compatibility with the yatai<1.0.0, adapting the old "yatai" command to the new "start" command. + if [ "${#}" -gt 0 ] && [ "${1}" = 'python' ] && [ "${2}" = '-m' ] && { [ "${3}" = 'bentoml._internal.server.cli.runner' ] || [ "${3}" = "bentoml._internal.server.cli.api_server" ]; }; then # SC2235, use { } to avoid subshell overhead + if [ "${3}" = 'bentoml._internal.server.cli.runner' ]; then + set -- bentoml start-runner-server "${@:4}" + elif [ "${3}" = 'bentoml._internal.server.cli.api_server' ]; then + set -- bentoml start-http-server "${@:4}" + fi + # If no arg or first arg looks like a flag. + elif [[ "$#" -eq 0 ]] || [[ "${1:0:1}" =~ '-' ]]; then + # This is provided for backwards compatibility with places where user may have + # discover this easter egg and use it in their scripts to run the container. + if [[ -v BENTOML_SERVE_COMPONENT ]]; then + echo "\$BENTOML_SERVE_COMPONENT is set! Calling 'bentoml start-*' instead" + if [ "${BENTOML_SERVE_COMPONENT}" = 'http_server' ]; then + set -- bentoml start-http-server "$@" "$BENTO_PATH" + elif [ "${BENTOML_SERVE_COMPONENT}" = 'grpc_server' ]; then + set -- bentoml start-grpc-server "$@" "$BENTO_PATH" + elif [ "${BENTOML_SERVE_COMPONENT}" = 'runner' ]; then + set -- bentoml start-runner-server "$@" "$BENTO_PATH" + fi + else + set -- bentoml serve "$@" "$BENTO_PATH" + fi + fi + # Overide the BENTOML_PORT if PORT env var is present. Used for Heroku and Yatai. + if [[ -v PORT ]]; then + echo "\$PORT is set! Overiding \$BENTOML_PORT with \$PORT ($PORT)" + export BENTOML_PORT=$PORT + fi + # Handle serve and start commands that is passed to the container. + # Assuming that serve and start commands are the first arguments + # Note that this is the recommended way going forward to run all bentoml containers. + if [ "${#}" -gt 0 ] && { [ "${1}" = 'serve' ] || [ "${1}" = 'serve-http' ] || [ "${1}" = 'serve-grpc' ] || [ "${1}" = 'start-http-server' ] || [ "${1}" = 'start-grpc-server' ] || [ "${1}" = 'start-runner-server' ]; }; then + exec bentoml "$@" "$BENTO_PATH" + else + # otherwise default to run whatever the command is + # This should allow running bash, sh, python, etc + exec "$@" + fi +} + +if ! _is_sourced; then + _main "$@" +fi diff --git a/vllm-chat/build/bentos/llama2/7b/env/python/install.sh b/vllm-chat/build/bentos/llama2/7b/env/python/install.sh new file mode 100644 index 00000000..e2bac1c2 --- /dev/null +++ b/vllm-chat/build/bentos/llama2/7b/env/python/install.sh @@ -0,0 +1,48 @@ +#!/usr/bin/env bash +set -exuo pipefail + +# Parent directory https://stackoverflow.com/a/246128/8643197 +BASEDIR="$( cd -- "$( dirname -- "${BASH_SOURCE[0]:-$0}"; )" &> /dev/null && pwd 2> /dev/null; )" + +PIP_ARGS=() + +# BentoML by default generates two requirement files: +# - ./env/python/requirements.lock.txt: all dependencies locked to its version presented during `build` +# - ./env/python/requirements.txt: all dependencies as user specified in code or requirements.txt file +REQUIREMENTS_TXT="$BASEDIR/requirements.txt" +REQUIREMENTS_LOCK="$BASEDIR/requirements.lock.txt" +WHEELS_DIR="$BASEDIR/wheels" +BENTOML_VERSION=${BENTOML_VERSION:-1.2.11} +# Install python packages, prefer installing the requirements.lock.txt file if it exist +pushd "$BASEDIR" &>/dev/null +if [ -f "$REQUIREMENTS_LOCK" ]; then + echo "Installing pip packages from 'requirements.lock.txt'.." + pip3 install -r "$REQUIREMENTS_LOCK" "${PIP_ARGS[@]}" +else + if [ -f "$REQUIREMENTS_TXT" ]; then + echo "Installing pip packages from 'requirements.txt'.." + pip3 install -r "$REQUIREMENTS_TXT" "${PIP_ARGS[@]}" + fi +fi +popd &>/dev/null + +# Attempt to expand the glob pattern. The nullglob option ensures that +# the pattern itself is not returned if no files match. +shopt -s nullglob +wheels=($WHEELS_DIR/*.whl) + +if [ ${#wheels[@]} -gt 0 ]; then + echo "Installing wheels packaged in Bento.." + pip3 install "${wheels[@]}" "${PIP_ARGS[@]}" +fi + + +# Install the BentoML from PyPI if it's not already installed +if python3 -c "import bentoml" &> /dev/null; then + existing_bentoml_version=$(python3 -c "import bentoml; print(bentoml.__version__)") + if [ "$existing_bentoml_version" != "$BENTOML_VERSION" ]; then + echo "WARNING: using BentoML version ${existing_bentoml_version}" + fi +else + pip3 install bentoml=="$BENTOML_VERSION" +fi \ No newline at end of file diff --git a/vllm-chat/build/bentos/llama2/7b/env/python/requirements.txt b/vllm-chat/build/bentos/llama2/7b/env/python/requirements.txt new file mode 100644 index 00000000..7382d95a --- /dev/null +++ b/vllm-chat/build/bentos/llama2/7b/env/python/requirements.txt @@ -0,0 +1,4 @@ +bentoml==1.2.11 +torch==2.1.2 +vllm==0.4.0.post1 +transformers==4.39.3 diff --git a/vllm-chat/build/bentos/llama2/7b/env/python/version.txt b/vllm-chat/build/bentos/llama2/7b/env/python/version.txt new file mode 100644 index 00000000..2b6882dd --- /dev/null +++ b/vllm-chat/build/bentos/llama2/7b/env/python/version.txt @@ -0,0 +1 @@ +3.11.4 \ No newline at end of file diff --git a/vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/__init__.py b/vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/protocol.py b/vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/protocol.py new file mode 100644 index 00000000..7de4d1da --- /dev/null +++ b/vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/protocol.py @@ -0,0 +1,441 @@ +from __future__ import annotations + +# Adapted from +# https://github.com/lm-sys/FastChat/blob/168ccc29d3f7edc50823016105c024fe2282732a/fastchat/protocol/openai_api_protocol.py +import time +import uuid +from typing import TYPE_CHECKING, Dict, List, Literal, Optional, Union + +from pydantic import BaseModel, Field, model_validator + +if TYPE_CHECKING: + import torch + from vllm.sampling_params import SamplingParams + + +def random_uuid() -> str: + return str(uuid.uuid4().hex) + + +class ErrorResponse(BaseModel): + object: str = "error" + message: str + type: str + param: Optional[str] = None + code: int + + +class ModelPermission(BaseModel): + id: str = Field(default_factory=lambda: f"modelperm-{random_uuid()}") + object: str = "model_permission" + created: int = Field(default_factory=lambda: int(time.time())) + allow_create_engine: bool = False + allow_sampling: bool = True + allow_logprobs: bool = True + allow_search_indices: bool = False + allow_view: bool = True + allow_fine_tuning: bool = False + organization: str = "*" + group: Optional[str] = None + is_blocking: str = False + + +class ModelCard(BaseModel): + id: str + object: str = "model" + created: int = Field(default_factory=lambda: int(time.time())) + owned_by: str = "vllm" + root: Optional[str] = None + parent: Optional[str] = None + permission: List[ModelPermission] = Field(default_factory=list) + + +class ModelList(BaseModel): + object: str = "list" + data: List[ModelCard] = Field(default_factory=list) + + +class UsageInfo(BaseModel): + prompt_tokens: int = 0 + total_tokens: int = 0 + completion_tokens: Optional[int] = 0 + + +class ResponseFormat(BaseModel): + # type must be "json_object" or "text" + type: str = Literal["text", "json_object"] + + +class ChatCompletionRequest(BaseModel): + # Ordered by official OpenAI API documentation + # https://platform.openai.com/docs/api-reference/chat/create + messages: List[Dict[str, str]] + model: str + frequency_penalty: Optional[float] = 0.0 + logit_bias: Optional[Dict[str, float]] = None + logprobs: Optional[bool] = False + top_logprobs: Optional[int] = None + max_tokens: Optional[int] = None + n: Optional[int] = 1 + presence_penalty: Optional[float] = 0.0 + response_format: Optional[ResponseFormat] = None + seed: Optional[int] = None + stop: Optional[Union[str, List[str]]] = Field(default_factory=list) + stream: Optional[bool] = False + temperature: Optional[float] = 0.7 + top_p: Optional[float] = 1.0 + user: Optional[str] = None + + # doc: begin-chat-completion-sampling-params + best_of: Optional[int] = None + use_beam_search: Optional[bool] = False + top_k: Optional[int] = -1 + min_p: Optional[float] = 0.0 + repetition_penalty: Optional[float] = 1.0 + length_penalty: Optional[float] = 1.0 + early_stopping: Optional[bool] = False + ignore_eos: Optional[bool] = False + min_tokens: Optional[int] = 0 + stop_token_ids: Optional[List[int]] = Field(default_factory=list) + skip_special_tokens: Optional[bool] = True + spaces_between_special_tokens: Optional[bool] = True + # doc: end-chat-completion-sampling-params + + # doc: begin-chat-completion-extra-params + echo: Optional[bool] = Field( + default=False, + description=( + "If true, the new message will be prepended with the last message " + "if they belong to the same role." + ), + ) + add_generation_prompt: Optional[bool] = Field( + default=True, + description=( + "If true, the generation prompt will be added to the chat template. " + "This is a parameter used by chat template in tokenizer config of the " + "model." + ), + ) + include_stop_str_in_output: Optional[bool] = Field( + default=False, + description=( + "Whether to include the stop string in the output. " + "This is only applied when the stop or stop_token_ids is set." + ), + ) + guided_json: Optional[Union[str, dict, BaseModel]] = Field( + default=None, + description=("If specified, the output will follow the JSON schema."), + ) + guided_regex: Optional[str] = Field( + default=None, + description=("If specified, the output will follow the regex pattern."), + ) + guided_choice: Optional[List[str]] = Field( + default=None, + description=("If specified, the output will be exactly one of the choices."), + ) + guided_grammar: Optional[str] = Field( + default=None, + description=("If specified, the output will follow the context free grammar."), + ) + + # doc: end-chat-completion-extra-params + + def to_sampling_params(self) -> SamplingParams: + if self.logprobs and not self.top_logprobs: + raise ValueError("Top logprobs must be set when logprobs is.") + + logits_processors = None + if self.logit_bias: + + def logit_bias_logits_processor( + token_ids: List[int], logits: torch.Tensor + ) -> torch.Tensor: + for token_id, bias in self.logit_bias.items(): + # Clamp the bias between -100 and 100 per OpenAI API spec + bias = min(100, max(-100, bias)) + logits[int(token_id)] += bias + return logits + + logits_processors = [logit_bias_logits_processor] + + from vllm.sampling_params import SamplingParams + + return SamplingParams( + n=self.n, + presence_penalty=self.presence_penalty, + frequency_penalty=self.frequency_penalty, + repetition_penalty=self.repetition_penalty, + temperature=self.temperature, + top_p=self.top_p, + min_p=self.min_p, + seed=self.seed, + stop=self.stop, + stop_token_ids=self.stop_token_ids, + max_tokens=self.max_tokens, + min_tokens=self.min_tokens, + logprobs=self.top_logprobs if self.logprobs else None, + prompt_logprobs=self.top_logprobs if self.echo else None, + best_of=self.best_of, + top_k=self.top_k, + ignore_eos=self.ignore_eos, + use_beam_search=self.use_beam_search, + early_stopping=self.early_stopping, + skip_special_tokens=self.skip_special_tokens, + spaces_between_special_tokens=self.spaces_between_special_tokens, + include_stop_str_in_output=self.include_stop_str_in_output, + length_penalty=self.length_penalty, + logits_processors=logits_processors, + ) + + @model_validator(mode="before") + @classmethod + def check_guided_decoding_count(cls, data): + guide_count = sum( + [ + "guided_json" in data and data["guided_json"] is not None, + "guided_regex" in data and data["guided_regex"] is not None, + "guided_choice" in data and data["guided_choice"] is not None, + ] + ) + if guide_count > 1: + raise ValueError( + "You can only use one kind of guided decoding " + "('guided_json', 'guided_regex' or 'guided_choice')." + ) + return data + + +class CompletionRequest(BaseModel): + # Ordered by official OpenAI API documentation + # https://platform.openai.com/docs/api-reference/completions/create + model: str + prompt: Union[List[int], List[List[int]], str, List[str]] + best_of: Optional[int] = None + echo: Optional[bool] = False + frequency_penalty: Optional[float] = 0.0 + logit_bias: Optional[Dict[str, float]] = None + logprobs: Optional[int] = None + max_tokens: Optional[int] = 16 + n: Optional[int] = 1 + presence_penalty: Optional[float] = 0.0 + seed: Optional[int] = None + stop: Optional[Union[str, List[str]]] = Field(default_factory=list) + stream: Optional[bool] = False + suffix: Optional[str] = None + temperature: Optional[float] = 1.0 + top_p: Optional[float] = 1.0 + user: Optional[str] = None + + # doc: begin-completion-sampling-params + use_beam_search: Optional[bool] = False + top_k: Optional[int] = -1 + min_p: Optional[float] = 0.0 + repetition_penalty: Optional[float] = 1.0 + length_penalty: Optional[float] = 1.0 + early_stopping: Optional[bool] = False + stop_token_ids: Optional[List[int]] = Field(default_factory=list) + ignore_eos: Optional[bool] = False + min_tokens: Optional[int] = 0 + skip_special_tokens: Optional[bool] = True + spaces_between_special_tokens: Optional[bool] = True + # doc: end-completion-sampling-params + + # doc: begin-completion-extra-params + include_stop_str_in_output: Optional[bool] = Field( + default=False, + description=( + "Whether to include the stop string in the output. " + "This is only applied when the stop or stop_token_ids is set." + ), + ) + response_format: Optional[ResponseFormat] = Field( + default=None, + description=( + "Similar to chat completion, this parameter specifies the format of " + "output. Only {'type': 'json_object'} or {'type': 'text' } is " + "supported." + ), + ) + guided_json: Optional[Union[str, dict, BaseModel]] = Field( + default=None, + description=("If specified, the output will follow the JSON schema."), + ) + guided_regex: Optional[str] = Field( + default=None, + description=("If specified, the output will follow the regex pattern."), + ) + guided_choice: Optional[List[str]] = Field( + default=None, + description=("If specified, the output will be exactly one of the choices."), + ) + guided_grammar: Optional[str] = Field( + default=None, + description=("If specified, the output will follow the context free grammar."), + ) + + # doc: end-completion-extra-params + + def to_sampling_params(self): + echo_without_generation = self.echo and self.max_tokens == 0 + + logits_processors = None + if self.logit_bias is not None: + + def logit_bias_logits_processor( + token_ids: List[int], logits: torch.Tensor + ) -> torch.Tensor: + for token_id, bias in self.logit_bias.items(): + # Clamp the bias between -100 and 100 per OpenAI API spec + bias = min(100, max(-100, bias)) + logits[int(token_id)] += bias + return logits + + logits_processors = [logit_bias_logits_processor] + + from vllm.sampling_params import SamplingParams + + return SamplingParams( + n=self.n, + best_of=self.best_of, + presence_penalty=self.presence_penalty, + frequency_penalty=self.frequency_penalty, + repetition_penalty=self.repetition_penalty, + temperature=self.temperature, + top_p=self.top_p, + top_k=self.top_k, + min_p=self.min_p, + seed=self.seed, + stop=self.stop, + stop_token_ids=self.stop_token_ids, + ignore_eos=self.ignore_eos, + max_tokens=self.max_tokens if not echo_without_generation else 1, + min_tokens=self.min_tokens, + logprobs=self.logprobs, + use_beam_search=self.use_beam_search, + early_stopping=self.early_stopping, + prompt_logprobs=self.logprobs if self.echo else None, + skip_special_tokens=self.skip_special_tokens, + spaces_between_special_tokens=(self.spaces_between_special_tokens), + include_stop_str_in_output=self.include_stop_str_in_output, + length_penalty=self.length_penalty, + logits_processors=logits_processors, + ) + + @model_validator(mode="before") + @classmethod + def check_guided_decoding_count(cls, data): + guide_count = sum( + [ + "guided_json" in data and data["guided_json"] is not None, + "guided_regex" in data and data["guided_regex"] is not None, + "guided_choice" in data and data["guided_choice"] is not None, + ] + ) + if guide_count > 1: + raise ValueError( + "You can only use one kind of guided decoding " + "('guided_json', 'guided_regex' or 'guided_choice')." + ) + return data + + +class LogProbs(BaseModel): + text_offset: List[int] = Field(default_factory=list) + token_logprobs: List[Optional[float]] = Field(default_factory=list) + tokens: List[str] = Field(default_factory=list) + top_logprobs: Optional[List[Optional[Dict[str, float]]]] = None + + +class CompletionResponseChoice(BaseModel): + index: int + text: str + logprobs: Optional[LogProbs] = None + finish_reason: Optional[Literal["stop", "length"]] = None + stop_reason: Union[None, int, str] = Field( + default=None, + description=( + "The stop string or token id that caused the completion " + "to stop, None if the completion finished for some other reason " + "including encountering the EOS token" + ), + ) + + +class CompletionResponse(BaseModel): + id: str = Field(default_factory=lambda: f"cmpl-{random_uuid()}") + object: str = "text_completion" + created: int = Field(default_factory=lambda: int(time.time())) + model: str + choices: List[CompletionResponseChoice] + usage: UsageInfo + + +class CompletionResponseStreamChoice(BaseModel): + index: int + text: str + logprobs: Optional[LogProbs] = None + finish_reason: Optional[Literal["stop", "length"]] = None + stop_reason: Union[None, int, str] = Field( + default=None, + description=( + "The stop string or token id that caused the completion " + "to stop, None if the completion finished for some other reason " + "including encountering the EOS token" + ), + ) + + +class CompletionStreamResponse(BaseModel): + id: str = Field(default_factory=lambda: f"cmpl-{random_uuid()}") + object: str = "text_completion" + created: int = Field(default_factory=lambda: int(time.time())) + model: str + choices: List[CompletionResponseStreamChoice] + usage: Optional[UsageInfo] = Field(default=None) + + +class ChatMessage(BaseModel): + role: str + content: str + + +class ChatCompletionResponseChoice(BaseModel): + index: int + message: ChatMessage + logprobs: Optional[LogProbs] = None + finish_reason: Optional[Literal["stop", "length"]] = None + stop_reason: Union[None, int, str] = None + + +class ChatCompletionResponse(BaseModel): + id: str = Field(default_factory=lambda: f"chatcmpl-{random_uuid()}") + object: str = "chat.completion" + created: int = Field(default_factory=lambda: int(time.time())) + model: str + choices: List[ChatCompletionResponseChoice] + usage: UsageInfo + + +class DeltaMessage(BaseModel): + role: Optional[str] = None + content: Optional[str] = None + + +class ChatCompletionResponseStreamChoice(BaseModel): + index: int + delta: DeltaMessage + logprobs: Optional[LogProbs] = None + finish_reason: Optional[Literal["stop", "length"]] = None + stop_reason: Union[None, int, str] = None + + +class ChatCompletionStreamResponse(BaseModel): + id: str = Field(default_factory=lambda: f"chatcmpl-{random_uuid()}") + object: str = "chat.completion.chunk" + created: int = Field(default_factory=lambda: int(time.time())) + model: str + choices: List[ChatCompletionResponseStreamChoice] + usage: Optional[UsageInfo] = Field(default=None) diff --git a/vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/utils.py b/vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/utils.py new file mode 100644 index 00000000..87da555f --- /dev/null +++ b/vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/utils.py @@ -0,0 +1,179 @@ +from __future__ import annotations + +import asyncio +import typing as t + +from _bentoml_sdk.service.factory import Service +from fastapi import FastAPI, Request +from fastapi.responses import JSONResponse, StreamingResponse + +from .protocol import ChatCompletionRequest, CompletionRequest, ErrorResponse + +T = t.TypeVar("T", bound=object) + +if t.TYPE_CHECKING: + from vllm import AsyncLLMEngine + + +def openai_endpoints( + served_model: str, + response_role: str = "assistant", + chat_template: t.Optional[str] = None, + chat_template_model_id: t.Optional[str] = None, +): + + def openai_wrapper(svc: Service[T]): + + cls = svc.inner + app = FastAPI() + + class new_cls(cls): + + def __init__(self): + + super().__init__() + + # we need to import bentoml before vllm so + # `prometheus_client` won't cause import troubles + # That's also why we put these codes inside class's + # `__init__` function + import bentoml + from vllm.entrypoints.openai.serving_chat import OpenAIServingChat + from vllm.entrypoints.openai.serving_completion import ( + OpenAIServingCompletion, + ) + + # https://github.com/vllm-project/vllm/issues/2683 + class PatchedOpenAIServingChat(OpenAIServingChat): + def __init__( + self, + engine: AsyncLLMEngine, + served_model: str, + response_role: str, + chat_template=None, + ): + super(OpenAIServingChat, self).__init__( + engine=engine, + served_model=served_model, + lora_modules=None, + ) + self.response_role = response_role + try: + event_loop = asyncio.get_running_loop() + except RuntimeError: + event_loop = None + + if event_loop is not None and event_loop.is_running(): + event_loop.create_task( + self._load_chat_template(chat_template) + ) + else: + asyncio.run(self._load_chat_template(chat_template)) + + async def _load_chat_template(self, chat_template): + # Simply making this function async is usually already enough to give the parent + # class time to load the tokenizer (so usually no sleeping happens here) + # However, it feels safer to be explicit about this since asyncio does not + # guarantee the order in which scheduled tasks are run + while self.tokenizer is None: + await asyncio.sleep(0.1) + return super()._load_chat_template(chat_template) + + self.openai_serving_completion = OpenAIServingCompletion( + engine=self.engine, + served_model=served_model, + ) + + self.chat_template = chat_template + if self.chat_template is None and chat_template_model_id is not None: + from transformers import AutoTokenizer + + _tokenizer = AutoTokenizer.from_pretrained(chat_template_model_id) + self.chat_template = _tokenizer.chat_template + + self.openai_serving_chat = PatchedOpenAIServingChat( + engine=self.engine, + served_model=served_model, + response_role=response_role, + chat_template=self.chat_template, + ) + + @app.get("/models") + async def show_available_models(): + models = await self.openai_serving_chat.show_available_models() + return JSONResponse(content=models.model_dump()) + + @app.post("/chat/completions") + async def create_chat_completion( + request: ChatCompletionRequest, raw_request: Request + ): + generator = await self.openai_serving_chat.create_chat_completion( + request, raw_request + ) + if isinstance(generator, ErrorResponse): + return JSONResponse( + content=generator.model_dump(), status_code=generator.code + ) + if request.stream: + return StreamingResponse( + content=generator, media_type="text/event-stream" + ) + else: + return JSONResponse(content=generator.model_dump()) + + @app.post("/completions") + async def create_completion( + request: CompletionRequest, raw_request: Request + ): + generator = await self.openai_serving_completion.create_completion( + request, raw_request + ) + if isinstance(generator, ErrorResponse): + return JSONResponse( + content=generator.model_dump(), status_code=generator.code + ) + if request.stream: + return StreamingResponse( + content=generator, media_type="text/event-stream" + ) + else: + return JSONResponse(content=generator.model_dump()) + + new_cls.__name__ = "%s_OpenAI" % cls.__name__ + svc.inner = new_cls + svc.mount_asgi_app(app, path="/v1/") + return svc + + return openai_wrapper + + +# helper function to make a httpx client for BentoML service +def _make_httpx_client(url, svc): + + from urllib.parse import urlparse + + import httpx + from bentoml._internal.utils.uri import uri_to_path + + timeout = svc.config["traffic"]["timeout"] + headers = {"Runner-Name": svc.name} + parsed = urlparse(url) + transport = None + target_url = url + + if parsed.scheme == "file": + uds = uri_to_path(url) + transport = httpx.HTTPTransport(uds=uds) + target_url = "http://127.0.0.1:3000" + elif parsed.scheme == "tcp": + target_url = f"http://{parsed.netloc}" + + return ( + httpx.Client( + transport=transport, + timeout=timeout, + follow_redirects=True, + headers=headers, + ), + target_url, + ) diff --git a/vllm-chat/build/bentos/llama2/7b/src/service.py b/vllm-chat/build/bentos/llama2/7b/src/service.py new file mode 100644 index 00000000..86575ef6 --- /dev/null +++ b/vllm-chat/build/bentos/llama2/7b/src/service.py @@ -0,0 +1,55 @@ +import uuid +from typing import AsyncGenerator + +import bentoml +from annotated_types import Ge, Le +from bentovllm_openai.utils import openai_endpoints +from typing_extensions import Annotated + +MAX_TOKENS = 1024 +PROMPT_TEMPLATE = """[INST] <> +You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. + +If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. +<> + +{user_prompt} [/INST] """ + +MODEL_ID = "meta-llama/Llama-2-7b-chat-hf" + + +@openai_endpoints(served_model=MODEL_ID) +@bentoml.service( + name="llama2", + traffic={ + "timeout": 300, + }, + resources={ + "gpu": 1, + "gpu_type": "nvidia-l4", + }, +) +class VLLM: + def __init__(self) -> None: + from vllm import AsyncEngineArgs, AsyncLLMEngine + + ENGINE_ARGS = AsyncEngineArgs(model=MODEL_ID, max_model_len=MAX_TOKENS) + self.engine = AsyncLLMEngine.from_engine_args(ENGINE_ARGS) + + @bentoml.api + async def generate( + self, + prompt: str = "Explain superconductors like I'm five years old", + max_tokens: Annotated[int, Ge(128), Le(MAX_TOKENS)] = MAX_TOKENS, + ) -> AsyncGenerator[str, None]: + from vllm import SamplingParams + + SAMPLING_PARAM = SamplingParams(max_tokens=max_tokens) + prompt = PROMPT_TEMPLATE.format(user_prompt=prompt) + stream = await self.engine.add_request(uuid.uuid4().hex, prompt, SAMPLING_PARAM) + + cursor = 0 + async for request_output in stream: + text = request_output.outputs[0].text + yield text[cursor:] + cursor = len(text) diff --git a/vllm-chat/build/bentos/llama2/latest b/vllm-chat/build/bentos/llama2/latest new file mode 100644 index 00000000..824292c5 --- /dev/null +++ b/vllm-chat/build/bentos/llama2/latest @@ -0,0 +1 @@ +7b \ No newline at end of file diff --git a/vllm-chat/build/client_id b/vllm-chat/build/client_id new file mode 100644 index 00000000..46eda765 --- /dev/null +++ b/vllm-chat/build/client_id @@ -0,0 +1,2 @@ +creation_timestamp: 2024-04-10 12:55:41.120086+00:00 +id: d4b8f81e-4875-44d8-942b-0e0a0ed76c92 diff --git a/vllm-chat/requirements.txt b/vllm-chat/requirements.txt new file mode 100644 index 00000000..dbea4aa2 --- /dev/null +++ b/vllm-chat/requirements.txt @@ -0,0 +1,3 @@ +torch==2.1.2 +vllm==0.4.0.post1 +transformers==4.39.3 diff --git a/vllm-chat/service.py b/vllm-chat/service.py new file mode 100644 index 00000000..9e196a6a --- /dev/null +++ b/vllm-chat/service.py @@ -0,0 +1,136 @@ +import uuid +import os +from typing import AsyncGenerator +from typing_extensions import Annotated + +import bentoml +from annotated_types import Ge, Le +from bentovllm_openai.utils import openai_endpoints + + +PROMPT_TEMPLATE_MAP = { + "llama2:7b-chat": """[INST] <> +You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. + +If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. +<> + +{user_prompt} [/INST] """, + "mistral:7b-instruct": """[INST] +You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. + +If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. + +{user_prompt} [/INST] """, + "mixtral:8x7b-instruct": """[INST] +You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. + +If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. + +{user_prompt} [/INST] """, +} + +MODEL_ID_MAP = { + "llama2:7b-chat": "meta-llama/Llama-2-7b-chat-hf", + "mistral:7b-instruct": "mistralai/Mistral-7B-Instruct-v0.2", + "mixtral:8x7b-instruct": "TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ", +} + +SERVICE_CONFIG_MAP = { + "llama2:7b-chat": { + "name": "llama2", + "traffic": { + "timeout": 300, + }, + "resources": { + "gpu": 1, + "gpu_type": "nvidia-tesla-t4", + }, + }, + "mistral:7b-instruct": { + "name": "mistral", + "traffic": { + "timeout": 300, + }, + "resources": { + "gpu": 1, + "gpu_type": "nvidia-l4", + }, + }, + "mixtral:8x7b-instruct": { + "name": "mixtral", + "traffic": { + "timeout": 300, + }, + "resources": { + "gpu": 1, + "gpu_type": "nvidia-a100-80gb", + }, + }, +} + +MODEL_CONFIG_MAP = { + "llama2:7b-chat": { + "max_model_len": 1024, + }, + "mistral:7b-instruct": { + "max_model_len": 1024, + "dtype": "half", + }, + "mixtral:8x7b-instruct": { + "max_model_len": 8192, + "gpu_memory_utilization": 0.85, + "quantization": "gptq", + "dtype": "half", + }, +} + +MODEL_ALIAS_MAP = { + "llama2": "llama2:7b-chat", + "llama2:7b": "llama2:7b-chat", + "llama2:7b-chat": "llama2:7b-chat", + "mistral": "mistral:7b-instruct", + "mistral:7b": "mistral:7b-instruct", + "mistral:7b-instruct": "mistral:7b-instruct", + "mixtral": "mixtral:8x7b-instruct", + "mixtral:8x7b": "mixtral:8x7b-instruct", + "mixtral:8x7b-instruct": "mixtral:8x7b-instruct", +} + + +MODEL_ALIAS = os.environ["CLLAMA_MODEL"] +MODEL = MODEL_ALIAS_MAP[MODEL_ALIAS] +PROMPT_TEMPLATE = PROMPT_TEMPLATE_MAP[MODEL] +MODEL_ID = MODEL_ID_MAP[MODEL] +SERVICE_CONFIG = SERVICE_CONFIG_MAP[MODEL] +MODEL_CONFIG = MODEL_CONFIG_MAP[MODEL] + + +@openai_endpoints(served_model=MODEL_ID) +@bentoml.service(**SERVICE_CONFIG) +class VLLM: + def __init__(self) -> None: + from vllm import AsyncEngineArgs, AsyncLLMEngine + + ENGINE_ARGS = AsyncEngineArgs(model=MODEL_ID, **MODEL_CONFIG) + self.engine = AsyncLLMEngine.from_engine_args(ENGINE_ARGS) + + @bentoml.api + async def generate( + self, + prompt: str = "Explain superconductors like I'm five years old", + max_tokens: Annotated[ + int, Ge(128), Le(MODEL_CONFIG["max_model_len"]) + ] = MODEL_CONFIG["max_model_len"], + ) -> AsyncGenerator[str, None]: + from vllm import SamplingParams + + SAMPLING_PARAM = SamplingParams(max_tokens=max_tokens) + prompt = PROMPT_TEMPLATE.format(user_prompt=prompt) + stream = await self.engine.add_request(uuid.uuid4().hex, prompt, SAMPLING_PARAM) + + cursor = 0 + async for request_output in stream: + text = request_output.outputs[0].text + yield text[cursor:] + cursor = len(text) From 40705f84bd61d0645d3ea80b25449025ec1b420f Mon Sep 17 00:00:00 2001 From: bojiang <5886138+bojiang@users.noreply.github.com> Date: Mon, 20 May 2024 13:53:11 +0800 Subject: [PATCH 006/125] Update README.md --- README.md | 151 +----------------------------------------------------- 1 file changed, 1 insertion(+), 150 deletions(-) diff --git a/README.md b/README.md index ceb0ae1c..9146cb17 100644 --- a/README.md +++ b/README.md @@ -1,150 +1 @@ -
-

Self-host LLMs with vLLM and BentoML

-
- -This is a BentoML example project, showing you how to serve and deploy open-source Large Language Models using [vLLM](https://vllm.ai), a high-throughput and memory-efficient inference engine. - -See [here](https://github.com/bentoml/BentoML?tab=readme-ov-file#%EF%B8%8F-what-you-can-build-with-bentoml) for a full list of BentoML example projects. - -💡 This example is served as a basis for advanced code customization, such as custom model, inference logic or vLLM options. For simple LLM hosting with OpenAI compatible endpoint without writing any code, see [OpenLLM](https://github.com/bentoml/OpenLLM). - - -## Prerequisites - -- You have installed Python 3.8+ and `pip`. See the [Python downloads page](https://www.python.org/downloads/) to learn more. -- You have a basic understanding of key concepts in BentoML, such as Services. We recommend you read [Quickstart](https://docs.bentoml.com/en/1.2/get-started/quickstart.html) first. -- If you want to test the Service locally, you need a Nvidia GPU with at least 16G VRAM. -- (Optional) We recommend you create a virtual environment for dependency isolation for this project. See the [Conda documentation](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) or the [Python documentation](https://docs.python.org/3/library/venv.html) for details. - -## Install dependencies - -```bash -git clone https://github.com/bentoml/BentoVLLM.git -cd BentoVLLM/mistral-7b-instruct -pip install -r requirements.txt && pip install -f -U "pydantic>=2.0" -``` - -## Run the BentoML Service - -We have defined a BentoML Service in `service.py`. Run `bentoml serve` in your project directory to start the Service. - -```bash -$ bentoml serve . - -2024-01-18T07:51:30+0800 [INFO] [cli] Starting production HTTP BentoServer from "service:VLLM" listening on http://localhost:3000 (Press CTRL+C to quit) -INFO 01-18 07:51:40 model_runner.py:501] Capturing the model for CUDA graphs. This may lead to unexpected consequences if the model is not static. To run the model in eager mode, set 'enforce_eager=True' or use '--enforce-eager' in the CLI. -INFO 01-18 07:51:40 model_runner.py:505] CUDA graphs can take additional 1~3 GiB memory per GPU. If you are running out of memory, consider decreasing `gpu_memory_utilization` or enforcing eager mode. -INFO 01-18 07:51:46 model_runner.py:547] Graph capturing finished in 6 secs. -``` - -The server is now active at [http://localhost:3000](http://localhost:3000/). You can interact with it using the Swagger UI or in other different ways. - -
- -CURL - -```bash -curl -X 'POST' \ - 'http://localhost:3000/generate' \ - -H 'accept: text/event-stream' \ - -H 'Content-Type: application/json' \ - -d '{ - "prompt": "Explain superconductors like I'\''m five years old", - "tokens": null -}' -``` - -
- -
- -Python client - -```python -import bentoml - -with bentoml.SyncHTTPClient("http://localhost:3000") as client: - response_generator = client.generate( - prompt="Explain superconductors like I'm five years old", - tokens=None - ) - for response in response_generator: - print(response) -``` - -
- -
- -OpenAI-compatible endpoints - -This Service uses the `@openai_endpoints` decorator to set up OpenAI-compatible endpoints (`chat/completions` and `completions`). This means your client can interact with the backend Service (in this case, the VLLM class) as if they were communicating directly with OpenAI's API. This [utility](mistral-7b-instruct/bentovllm_openai/) does not affect your BentoML Service code, and you can use it for other LLMs as well. - -```python -from openai import OpenAI - -client = OpenAI(base_url='http://localhost:3000/v1', api_key='na') - -# Use the following func to get the available models -client.models.list() - -chat_completion = client.chat.completions.create( - model="mistralai/Mistral-7B-Instruct-v0.2", - messages=[ - { - "role": "user", - "content": "Explain superconductors like I'm five years old" - } - ], - stream=True, -) -for chunk in chat_completion: - # Extract and print the content of the model's reply - print(chunk.choices[0].delta.content or "", end="") -``` - -**Note**: If your Service is deployed with [protected endpoints on BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html#access-protected-deployments), you need to set the environment variable `OPENAI_API_KEY` to your BentoCloud API key first. - -```bash -export OPENAI_API_KEY={YOUR_BENTOCLOUD_API_TOKEN} -``` - -You can then use the following line to replace the client in the above code snippet. Refer to [Obtain the endpoint URL](https://docs.bentoml.com/en/latest/bentocloud/how-tos/call-deployment-endpoints.html#obtain-the-endpoint-url) to retrieve the endpoint URL. - -```python -client = OpenAI(base_url='your_bentocloud_deployment_endpoint_url/v1') -``` - -
- -For detailed explanations of the Service code, see [vLLM inference](https://docs.bentoml.org/en/latest/use-cases/large-language-models/vllm.html). - -## Deploy to BentoCloud - -After the Service is ready, you can deploy the application to BentoCloud for better management and scalability. [Sign up](https://www.bentoml.com/) if you haven't got a BentoCloud account. - -Make sure you have [logged in to BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html), then run the following command to deploy it. - -```bash -bentoml deploy . -``` - -Once the application is up and running on BentoCloud, you can access it via the exposed URL. - -**Note**: For custom deployment in your own infrastructure, use [BentoML to generate an OCI-compliant image](https://docs.bentoml.com/en/latest/guides/containerization.html). - - -## Different LLM Models - -Besides the mistral-7b-instruct model, we have examples for other models in subdirectories of this repository. Below is a list of these models and links to the example subdirectories. - -- [Mistral-7B-Instruct-v0.2](mistral-7b-instruct/) -- [Mixtral-8x7B-Instruct-v0.1 with gptq quantization](mistral-7b-instruct/) -- [Llama-2-7b-chat-hf](llama2-7b-chat/) -- [SOLAR-10.7B-v1.0](solar-10.7b-instruct/) - - -## LLM tools integration examples - -- Every model directory contains codes to add OpenAI compatible endpoints to the BentoML service. -- [outlines-integration/](outlines-integration/) contains the code to integrate with [outlines](https://github.com/outlines-dev/outlines) for structured generation. +Makefile for openllm-repo From 2d228e025db4ef96a0ae9bc1f5b0fb6117ad22ef Mon Sep 17 00:00:00 2001 From: bojiang <5886138+bojiang@users.noreply.github.com> Date: Mon, 20 May 2024 14:03:22 +0800 Subject: [PATCH 007/125] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 9146cb17..7626bf0e 100644 --- a/README.md +++ b/README.md @@ -1 +1 @@ -Makefile for openllm-repo +Makefile for [openllm-repo](https://github.com/bojiang/openllm-repo) From 003c5bd551da909e11ac200dcc9f416166b9b0b9 Mon Sep 17 00:00:00 2001 From: bojiang Date: Mon, 20 May 2024 17:43:04 +0800 Subject: [PATCH 008/125] phi WIP --- Makefile | 2 +- recipe.py | 136 ++++++++++++++++++ recipe.yaml | 24 ++++ vllm-chat/bentofile.yaml | 7 +- vllm-chat/bentovllm_openai/utils.py | 10 +- .../build/bentos/llama2/7b/src/service.py | 2 +- vllm-chat/config.yaml | 24 ++++ vllm-chat/requirements.txt | 1 + vllm-chat/service.py | 114 ++------------- 9 files changed, 208 insertions(+), 112 deletions(-) create mode 100644 recipe.py create mode 100644 recipe.yaml create mode 100644 vllm-chat/config.yaml diff --git a/Makefile b/Makefile index 0b01ca7c..464afa7b 100644 --- a/Makefile +++ b/Makefile @@ -1,6 +1,6 @@ PWD := $(shell pwd) -BENTOML_HOME := $(PWD)/bentoml +BENTOML_HOME := $(PWD)/../openllm-repo/bentoml .PHONY: all all: diff --git a/recipe.py b/recipe.py new file mode 100644 index 00000000..7192d8e9 --- /dev/null +++ b/recipe.py @@ -0,0 +1,136 @@ + + + +PROMPT_TEMPLATE_MAP = { + "llama2:7b-chat": """[INST] <> +You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. + +If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. +<> + +{user_prompt} [/INST] """, + "mistral:7b-instruct": """[INST] +You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. + +If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. + +{user_prompt} [/INST] """, + "mixtral:8x7b-instruct": """[INST] +You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. + +If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. + +{user_prompt} [/INST] """, + "phi3:3.8b-mini-instruct-4k-fp16": """<|user|> +{user_prompt}<|end|> +<|assistant|>""", +} + +MODEL_ID_MAP = { + "llama2:7b-chat": "meta-llama/Llama-2-7b-chat-hf", + "mistral:7b-instruct": "mistralai/Mistral-7B-Instruct-v0.2", + "mixtral:8x7b-instruct": "TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ", + "phi3:3.8b-mini-instruct-4k-fp16": "microsoft/Phi-3-mini-4k-instruct", +} + +SERVICE_CONFIG_MAP = { + "llama2:7b-chat": { + "name": "llama2", + "traffic": { + "timeout": 300, + }, + "resources": { + "gpu": 1, + "gpu_type": "nvidia-tesla-t4", + }, + }, + "mistral:7b-instruct": { + "name": "mistral", + "traffic": { + "timeout": 300, + }, + "resources": { + "gpu": 1, + "gpu_type": "nvidia-l4", + }, + }, + "mixtral:8x7b-instruct": { + "name": "mixtral", + "traffic": { + "timeout": 300, + }, + "resources": { + "gpu": 1, + "gpu_type": "nvidia-a100-80gb", + }, + }, + "phi3:3.8b-mini-instruct-4k-fp16": { + "name": "phi3", + "traffic": { + "timeout": 300, + }, + "resources": { + "gpu": 1, + "gpu_memory": "16GB", + }, + }, +} + +MODEL_CONFIG_MAP = { + "llama2:7b-chat": { + "max_model_len": 1024, + }, + "mistral:7b-instruct": { + "max_model_len": 1024, + "dtype": "half", + }, + "mixtral:8x7b-instruct": { + "max_model_len": 8192, + "gpu_memory_utilization": 0.85, + "quantization": "gptq", + "dtype": "half", + }, + "phi3:3.8b-mini-instruct-4k-fp16": { + "max_model_len": 4096, + "dtype": "half", + }, +} + +MODEL_ALIAS_MAP = { + "llama2": "llama2:7b-chat", + "llama2:7b": "llama2:7b-chat", + "llama2:7b-chat": "llama2:7b-chat", + "mistral": "mistral:7b-instruct", + "mistral:7b": "mistral:7b-instruct", + "mistral:7b-instruct": "mistral:7b-instruct", + "mixtral": "mixtral:8x7b-instruct", + "mixtral:8x7b": "mixtral:8x7b-instruct", + "mixtral:8x7b-instruct": "mixtral:8x7b-instruct", + "phi3": "phi3:3.8b-mini-instruct-4k-fp16", + "phi3:3.8b": "phi3:3.8b-mini-instruct-4k-fp16", + "phi3:mini": "phi3:3.8b-mini-instruct-4k-fp16", + "phi3:instruct": "phi3:3.8b-mini-instruct-4k-fp16", + "phi3:3.8b-mini-instruct": "phi3:3.8b-mini-instruct-4k-fp16", +} + + + +models: + "phi3:3.8b-mini-instruct-4k-fp16": + alias: + - latest + - 3.8b + - instruct + - mini + template: vllm-chat + service_config: + name: phi3 + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-tesla-t4 + engine_config: + model_id: microsoft/Phi-3-mini-4k-instruct + max_model_len: 4096 + dtype: half diff --git a/recipe.yaml b/recipe.yaml new file mode 100644 index 00000000..1d745967 --- /dev/null +++ b/recipe.yaml @@ -0,0 +1,24 @@ +"phi3:3.8b-mini-instruct-4k-fp16": + alias: + - latest + - 3.8b + - instruct + - mini + template: vllm-chat + service_config: + name: phi3 + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-tesla-t4 + engine_config: + model_id: microsoft/Phi-3-mini-4k-instruct + max_model_len: 4096 + dtype: half + prompt: + head: ~ + body: |- + <|user|> + {user_prompt}<|end|> + <|assistant|> diff --git a/vllm-chat/bentofile.yaml b/vllm-chat/bentofile.yaml index f0f710f5..1322978a 100644 --- a/vllm-chat/bentofile.yaml +++ b/vllm-chat/bentofile.yaml @@ -4,11 +4,10 @@ labels: stage: demo include: - "*.py" +- "config.yaml" - "bentovllm_openai/*.py" python: - packages: - - git+https://github.com/bentoml/simple_di.git@master + requirements_txt: "./requirements.txt" + lock_packages: false envs: - name: HF_TOKEN - - name: CLLAMA_MODEL - value: llama2 diff --git a/vllm-chat/bentovllm_openai/utils.py b/vllm-chat/bentovllm_openai/utils.py index 87da555f..88f1dd61 100644 --- a/vllm-chat/bentovllm_openai/utils.py +++ b/vllm-chat/bentovllm_openai/utils.py @@ -16,7 +16,7 @@ if t.TYPE_CHECKING: def openai_endpoints( - served_model: str, + served_model_names: list[str], response_role: str = "assistant", chat_template: t.Optional[str] = None, chat_template_model_id: t.Optional[str] = None, @@ -48,13 +48,13 @@ def openai_endpoints( def __init__( self, engine: AsyncLLMEngine, - served_model: str, + served_model_names: list[str], response_role: str, chat_template=None, ): super(OpenAIServingChat, self).__init__( engine=engine, - served_model=served_model, + served_model_names=served_model_names, lora_modules=None, ) self.response_role = response_role @@ -81,7 +81,7 @@ def openai_endpoints( self.openai_serving_completion = OpenAIServingCompletion( engine=self.engine, - served_model=served_model, + served_model_names=served_model_names, ) self.chat_template = chat_template @@ -93,7 +93,7 @@ def openai_endpoints( self.openai_serving_chat = PatchedOpenAIServingChat( engine=self.engine, - served_model=served_model, + served_model_names=served_model_names, response_role=response_role, chat_template=self.chat_template, ) diff --git a/vllm-chat/build/bentos/llama2/7b/src/service.py b/vllm-chat/build/bentos/llama2/7b/src/service.py index 86575ef6..662f3ec1 100644 --- a/vllm-chat/build/bentos/llama2/7b/src/service.py +++ b/vllm-chat/build/bentos/llama2/7b/src/service.py @@ -18,7 +18,7 @@ If a question does not make any sense, or is not factually coherent, explain why MODEL_ID = "meta-llama/Llama-2-7b-chat-hf" -@openai_endpoints(served_model=MODEL_ID) +@openai_endpoints(served_model_names=[MODEL_ID]) @bentoml.service( name="llama2", traffic={ diff --git a/vllm-chat/config.yaml b/vllm-chat/config.yaml new file mode 100644 index 00000000..75c48347 --- /dev/null +++ b/vllm-chat/config.yaml @@ -0,0 +1,24 @@ +alias: + - latest + - 3.8b + - instruct + - mini +template: vllm-chat +service_config: + name: phi3 + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-tesla-t4 +engine_config: + model: microsoft/Phi-3-mini-4k-instruct + max_model_len: 4096 + dtype: half + trust_remote_code: true +prompt: + head: ~ + body: |- + <|user|> + {user_prompt}<|end|> + <|assistant|> diff --git a/vllm-chat/requirements.txt b/vllm-chat/requirements.txt index dbea4aa2..d7e29143 100644 --- a/vllm-chat/requirements.txt +++ b/vllm-chat/requirements.txt @@ -1,3 +1,4 @@ torch==2.1.2 vllm==0.4.0.post1 transformers==4.39.3 +pyyaml diff --git a/vllm-chat/service.py b/vllm-chat/service.py index 9e196a6a..f8c84faa 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -1,118 +1,28 @@ import uuid -import os from typing import AsyncGenerator from typing_extensions import Annotated import bentoml from annotated_types import Ge, Le from bentovllm_openai.utils import openai_endpoints +import yaml -PROMPT_TEMPLATE_MAP = { - "llama2:7b-chat": """[INST] <> -You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. +CONFIG = yaml.safe_load(open("config.yaml")) -If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. -<> - -{user_prompt} [/INST] """, - "mistral:7b-instruct": """[INST] -You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. - -If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. - -{user_prompt} [/INST] """, - "mixtral:8x7b-instruct": """[INST] -You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. - -If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. - -{user_prompt} [/INST] """, -} - -MODEL_ID_MAP = { - "llama2:7b-chat": "meta-llama/Llama-2-7b-chat-hf", - "mistral:7b-instruct": "mistralai/Mistral-7B-Instruct-v0.2", - "mixtral:8x7b-instruct": "TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ", -} - -SERVICE_CONFIG_MAP = { - "llama2:7b-chat": { - "name": "llama2", - "traffic": { - "timeout": 300, - }, - "resources": { - "gpu": 1, - "gpu_type": "nvidia-tesla-t4", - }, - }, - "mistral:7b-instruct": { - "name": "mistral", - "traffic": { - "timeout": 300, - }, - "resources": { - "gpu": 1, - "gpu_type": "nvidia-l4", - }, - }, - "mixtral:8x7b-instruct": { - "name": "mixtral", - "traffic": { - "timeout": 300, - }, - "resources": { - "gpu": 1, - "gpu_type": "nvidia-a100-80gb", - }, - }, -} - -MODEL_CONFIG_MAP = { - "llama2:7b-chat": { - "max_model_len": 1024, - }, - "mistral:7b-instruct": { - "max_model_len": 1024, - "dtype": "half", - }, - "mixtral:8x7b-instruct": { - "max_model_len": 8192, - "gpu_memory_utilization": 0.85, - "quantization": "gptq", - "dtype": "half", - }, -} - -MODEL_ALIAS_MAP = { - "llama2": "llama2:7b-chat", - "llama2:7b": "llama2:7b-chat", - "llama2:7b-chat": "llama2:7b-chat", - "mistral": "mistral:7b-instruct", - "mistral:7b": "mistral:7b-instruct", - "mistral:7b-instruct": "mistral:7b-instruct", - "mixtral": "mixtral:8x7b-instruct", - "mixtral:8x7b": "mixtral:8x7b-instruct", - "mixtral:8x7b-instruct": "mixtral:8x7b-instruct", -} +ENGINE_CONFIG = CONFIG["engine_config"] +MODEL_ID = ENGINE_CONFIG["model"] +PROMPT_TEMPLATE = CONFIG["prompt"] +SERVICE_CONFIG = CONFIG["service_config"] -MODEL_ALIAS = os.environ["CLLAMA_MODEL"] -MODEL = MODEL_ALIAS_MAP[MODEL_ALIAS] -PROMPT_TEMPLATE = PROMPT_TEMPLATE_MAP[MODEL] -MODEL_ID = MODEL_ID_MAP[MODEL] -SERVICE_CONFIG = SERVICE_CONFIG_MAP[MODEL] -MODEL_CONFIG = MODEL_CONFIG_MAP[MODEL] - - -@openai_endpoints(served_model=MODEL_ID) +@openai_endpoints(served_model_names=[MODEL_ID]) @bentoml.service(**SERVICE_CONFIG) class VLLM: def __init__(self) -> None: from vllm import AsyncEngineArgs, AsyncLLMEngine - ENGINE_ARGS = AsyncEngineArgs(model=MODEL_ID, **MODEL_CONFIG) + ENGINE_ARGS = AsyncEngineArgs(**ENGINE_CONFIG) self.engine = AsyncLLMEngine.from_engine_args(ENGINE_ARGS) @bentoml.api @@ -120,13 +30,15 @@ class VLLM: self, prompt: str = "Explain superconductors like I'm five years old", max_tokens: Annotated[ - int, Ge(128), Le(MODEL_CONFIG["max_model_len"]) - ] = MODEL_CONFIG["max_model_len"], + int, Ge(128), Le(ENGINE_CONFIG["max_model_len"]) + ] = ENGINE_CONFIG["max_model_len"], ) -> AsyncGenerator[str, None]: from vllm import SamplingParams SAMPLING_PARAM = SamplingParams(max_tokens=max_tokens) - prompt = PROMPT_TEMPLATE.format(user_prompt=prompt) + prompt = (PROMPT_TEMPLATE["head"] or "") + PROMPT_TEMPLATE["body"].format( + user_prompt=prompt + ) stream = await self.engine.add_request(uuid.uuid4().hex, prompt, SAMPLING_PARAM) cursor = 0 From 6bbb4c0008c632dc7751b85a768c6229f5fe69f9 Mon Sep 17 00:00:00 2001 From: bojiang Date: Mon, 20 May 2024 18:26:16 +0800 Subject: [PATCH 009/125] new make --- Makefile | 7 +----- make.py | 51 ++++++++++++++++++++++++++++++++++++++++++++ recipe.yaml | 5 ++--- vllm-chat/service.py | 4 +++- 4 files changed, 57 insertions(+), 10 deletions(-) create mode 100644 make.py diff --git a/Makefile b/Makefile index 464afa7b..0aea40e9 100644 --- a/Makefile +++ b/Makefile @@ -6,9 +6,4 @@ BENTOML_HOME := $(PWD)/../openllm-repo/bentoml all: @rm -rf $(BENTOML_HOME) @mkdir -p $(BENTOML_HOME) - @cd vllm-chat && BENTOML_HOME=$(BENTOML_HOME) CLLAMA_MODEL=llama2:7b-chat bentoml build . --version 7b-chat - @cd vllm-chat && BENTOML_HOME=$(BENTOML_HOME) CLLAMA_MODEL=llama2:7b bentoml build . --version 7b - @cd vllm-chat && BENTOML_HOME=$(BENTOML_HOME) CLLAMA_MODEL=mistral:7b-instruct bentoml build . --version 7b-instruct - @cd vllm-chat && BENTOML_HOME=$(BENTOML_HOME) CLLAMA_MODEL=mistral:7b bentoml build . --version 7b - @cd vllm-chat && BENTOML_HOME=$(BENTOML_HOME) CLLAMA_MODEL=mixtral:8x7b-instruct bentoml build . --version 8x7b-instruct - @cd vllm-chat && BENTOML_HOME=$(BENTOML_HOME) CLLAMA_MODEL=mixtral:8x7b bentoml build . --version 8x7b + @BENTOML_HOME=$(BENTOML_HOME) python make.py diff --git a/make.py b/make.py new file mode 100644 index 00000000..97e69369 --- /dev/null +++ b/make.py @@ -0,0 +1,51 @@ +import yaml +import sys +import subprocess +import os +import shutil +import tempfile +import pathlib + + +with open("recipe.yaml") as f: + RECIPE = yaml.safe_load(f) + + +BENTOML_HOME = pathlib.Path(os.environ["BENTOML_HOME"]) + + +if __name__ == "__main__": + if len(sys.argv) == 2: + specified_model = sys.argv[1] + if specified_model not in RECIPE: + raise ValueError(f"Model {specified_model} not found in recipe") + else: + specified_model = None + + for model_name, config in RECIPE.items(): + if specified_model and model_name != specified_model: + continue + project = config["project"] + model_repo, model_version = model_name.split(":") + with tempfile.TemporaryDirectory() as tempdir: + tempdir = pathlib.Path(tempdir) + shutil.copytree(project, tempdir, dirs_exist_ok=True) + with open(tempdir / "config.yaml", "w") as f: + yaml.dump(config, f) + subprocess.run( + ["bentoml", "build", str(tempdir), "--version", model_version], + check=True, + cwd=tempdir, + env=os.environ, + ) + + # delete latest + (BENTOML_HOME / "bentos" / model_repo / "latest").unlink(missing_ok=True) + + # link alias + for alias in config.get("alias", []): + ALIAS_PATH = BENTOML_HOME / "bentos" / model_repo / alias + if ALIAS_PATH.exists(): + continue + with open(ALIAS_PATH, "w") as f: + f.write(model_name) diff --git a/recipe.yaml b/recipe.yaml index 1d745967..a417f89d 100644 --- a/recipe.yaml +++ b/recipe.yaml @@ -1,10 +1,9 @@ "phi3:3.8b-mini-instruct-4k-fp16": alias: - - latest - 3.8b - instruct - mini - template: vllm-chat + project: vllm-chat service_config: name: phi3 traffic: @@ -13,7 +12,7 @@ gpu: 1 gpu_type: nvidia-tesla-t4 engine_config: - model_id: microsoft/Phi-3-mini-4k-instruct + model: microsoft/Phi-3-mini-4k-instruct max_model_len: 4096 dtype: half prompt: diff --git a/vllm-chat/service.py b/vllm-chat/service.py index f8c84faa..aa6770ae 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -30,7 +30,9 @@ class VLLM: self, prompt: str = "Explain superconductors like I'm five years old", max_tokens: Annotated[ - int, Ge(128), Le(ENGINE_CONFIG["max_model_len"]) + int, + Ge(128), + Le(ENGINE_CONFIG["max_model_len"]), ] = ENGINE_CONFIG["max_model_len"], ) -> AsyncGenerator[str, None]: from vllm import SamplingParams From 1de59c58644aab962a18a820e05b2ac985f67b90 Mon Sep 17 00:00:00 2001 From: bojiang Date: Mon, 20 May 2024 18:45:22 +0800 Subject: [PATCH 010/125] clean --- recipe.yaml | 25 + vllm-chat/build/bentos/llama2/7b/README.md | 16 - .../build/bentos/llama2/7b/apis/openapi.yaml | 173 ------- .../build/bentos/llama2/7b/apis/schema.json | 35 -- vllm-chat/build/bentos/llama2/7b/bento.yaml | 78 ---- .../bentos/llama2/7b/env/docker/Dockerfile | 64 --- .../bentos/llama2/7b/env/docker/entrypoint.sh | 56 --- .../bentos/llama2/7b/env/python/install.sh | 48 -- .../llama2/7b/env/python/requirements.txt | 4 - .../bentos/llama2/7b/env/python/version.txt | 1 - .../7b/src/bentovllm_openai/__init__.py | 0 .../7b/src/bentovllm_openai/protocol.py | 441 ------------------ .../llama2/7b/src/bentovllm_openai/utils.py | 179 ------- .../build/bentos/llama2/7b/src/service.py | 55 --- vllm-chat/build/bentos/llama2/latest | 1 - vllm-chat/build/client_id | 2 - vllm-chat/service.py | 3 +- 17 files changed, 26 insertions(+), 1155 deletions(-) delete mode 100644 vllm-chat/build/bentos/llama2/7b/README.md delete mode 100644 vllm-chat/build/bentos/llama2/7b/apis/openapi.yaml delete mode 100644 vllm-chat/build/bentos/llama2/7b/apis/schema.json delete mode 100644 vllm-chat/build/bentos/llama2/7b/bento.yaml delete mode 100644 vllm-chat/build/bentos/llama2/7b/env/docker/Dockerfile delete mode 100644 vllm-chat/build/bentos/llama2/7b/env/docker/entrypoint.sh delete mode 100644 vllm-chat/build/bentos/llama2/7b/env/python/install.sh delete mode 100644 vllm-chat/build/bentos/llama2/7b/env/python/requirements.txt delete mode 100644 vllm-chat/build/bentos/llama2/7b/env/python/version.txt delete mode 100644 vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/__init__.py delete mode 100644 vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/protocol.py delete mode 100644 vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/utils.py delete mode 100644 vllm-chat/build/bentos/llama2/7b/src/service.py delete mode 100644 vllm-chat/build/bentos/llama2/latest delete mode 100644 vllm-chat/build/client_id diff --git a/recipe.yaml b/recipe.yaml index a417f89d..70633afd 100644 --- a/recipe.yaml +++ b/recipe.yaml @@ -1,5 +1,6 @@ "phi3:3.8b-mini-instruct-4k-fp16": alias: + - latest - 3.8b - instruct - mini @@ -21,3 +22,27 @@ <|user|> {user_prompt}<|end|> <|assistant|> +"llama2:7b-chat-fp16": + alias: + - latest + - 7b + - 7b-chat + project: vllm-chat + service_config: + name: llama2 + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-tesla-t4 + engine_config: + model: meta-llama/Llama-2-7b-chat-hf + max_model_len: 1024 + prompt: + head: ~ + body: |- + [INST] <> + You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. + If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. + <> + {user_prompt} [/INST] diff --git a/vllm-chat/build/bentos/llama2/7b/README.md b/vllm-chat/build/bentos/llama2/7b/README.md deleted file mode 100644 index f5c4669f..00000000 --- a/vllm-chat/build/bentos/llama2/7b/README.md +++ /dev/null @@ -1,16 +0,0 @@ -# llama2:7b - -[![pypi_status](https://img.shields.io/badge/BentoML-1.2.11-informational)](https://pypi.org/project/BentoML) -[![documentation_status](https://readthedocs.org/projects/bentoml/badge/?version=latest)](https://docs.bentoml.com/) -[![join_slack](https://badgen.net/badge/Join/BentoML%20Slack/cyan?icon=slack)](https://l.bentoml.com/join-slack-swagger) -[![BentoML GitHub Repo](https://img.shields.io/github/stars/bentoml/bentoml?style=social)](https://github.com/bentoml/BentoML) -[![Twitter Follow](https://img.shields.io/twitter/follow/bentomlai?label=Follow%20BentoML&style=social)](https://twitter.com/bentomlai) - -This is a Machine Learning Service created with BentoML. - -## Help - -* [📖 Documentation](https://docs.bentoml.com/en/latest/): Learn how to use BentoML. -* [💬 Community](https://l.bentoml.com/join-slack-swagger): Join the BentoML Slack community. -* [🐛 GitHub Issues](https://github.com/bentoml/BentoML/issues): Report bugs and feature requests. -* Tip: you can also [customize this README](https://docs.bentoml.com/en/latest/concepts/bento.html#description). diff --git a/vllm-chat/build/bentos/llama2/7b/apis/openapi.yaml b/vllm-chat/build/bentos/llama2/7b/apis/openapi.yaml deleted file mode 100644 index 132bcddb..00000000 --- a/vllm-chat/build/bentos/llama2/7b/apis/openapi.yaml +++ /dev/null @@ -1,173 +0,0 @@ -components: - schemas: - InternalServerError: - description: Internal Server Error - properties: - msg: - title: Message - type: string - type: - title: Error Type - type: string - required: - - msg - - type - title: InternalServerError - type: object - InvalidArgument: - description: Bad Request - properties: - msg: - title: Message - type: string - type: - title: Error Type - type: string - required: - - msg - - type - title: InvalidArgument - type: object - NotFound: - description: Not Found - properties: - msg: - title: Message - type: string - type: - title: Error Type - type: string - required: - - msg - - type - title: NotFound - type: object - generate__Input: - properties: - max_tokens: - default: 1024 - maximum: 1024 - minimum: 128 - title: Max Tokens - type: integer - prompt: - default: Explain superconductors like I'm five years old - title: Prompt - type: string - title: generate__Input - type: object -info: - contact: - email: contact@bentoml.com - name: BentoML Team - description: "# llama2:dev\n\n[![pypi_status](https://img.shields.io/badge/BentoML-1.2.11-informational)](https://pypi.org/project/BentoML)\n\ - [![documentation_status](https://readthedocs.org/projects/bentoml/badge/?version=latest)](https://docs.bentoml.com/)\n\ - [![join_slack](https://badgen.net/badge/Join/BentoML%20Slack/cyan?icon=slack)](https://l.bentoml.com/join-slack-swagger)\n\ - [![BentoML GitHub Repo](https://img.shields.io/github/stars/bentoml/bentoml?style=social)](https://github.com/bentoml/BentoML)\n\ - [![Twitter Follow](https://img.shields.io/twitter/follow/bentomlai?label=Follow%20BentoML&style=social)](https://twitter.com/bentomlai)\n\ - \nThis is a Machine Learning Service created with BentoML.\n\n## Help\n\n* [\U0001F4D6\ - \ Documentation](https://docs.bentoml.com/en/latest/): Learn how to use BentoML.\n\ - * [\U0001F4AC Community](https://l.bentoml.com/join-slack-swagger): Join the BentoML\ - \ Slack community.\n* [\U0001F41B GitHub Issues](https://github.com/bentoml/BentoML/issues):\ - \ Report bugs and feature requests.\n* Tip: you can also [customize this README](https://docs.bentoml.com/en/latest/concepts/bento.html#description).\n" - title: llama2 - version: None -openapi: 3.0.2 -paths: - /generate: - post: - description: '' - operationId: llama2__generate - requestBody: - content: - application/json: - schema: - properties: - max_tokens: - default: 1024 - maximum: 1024 - minimum: 128 - title: Max Tokens - type: integer - prompt: - default: Explain superconductors like I'm five years old - title: Prompt - type: string - title: Input - type: object - responses: - 200: - content: - text/event-stream: - schema: - title: strIODescriptor - type: string - description: Successful Response - 400: - content: - application/json: - schema: - $ref: '#/components/schemas/InvalidArgument' - description: Bad Request - 404: - content: - application/json: - schema: - $ref: '#/components/schemas/NotFound' - description: Not Found - 500: - content: - application/json: - schema: - $ref: '#/components/schemas/InternalServerError' - description: Internal Server Error - tags: - - Service APIs - x-bentoml-name: generate - /healthz: - get: - description: Health check endpoint. Expecting an empty response with status - code 200 when the service is in health state. The /healthz - endpoint is deprecated. (since Kubernetes v1.16) - responses: - '200': - description: Successful Response - tags: - - Infrastructure - /livez: - get: - description: Health check endpoint for Kubernetes. Healthy endpoint responses - with a 200 OK status. - responses: - '200': - description: Successful Response - tags: - - Infrastructure - /metrics: - get: - description: Prometheus metrics endpoint. The /metrics responses - with a 200. The output can then be used by a Prometheus sidecar - to scrape the metrics of the service. - responses: - '200': - description: Successful Response - tags: - - Infrastructure - /readyz: - get: - description: A 200 OK status from /readyz endpoint - indicated the service is ready to accept traffic. From that point and onward, - Kubernetes will use /livez endpoint to perform periodic health - checks. - responses: - '200': - description: Successful Response - tags: - - Infrastructure -servers: -- url: . -tags: -- description: BentoML Service API endpoints for inference. - name: Service APIs -- description: Common infrastructure endpoints for observability. - name: Infrastructure diff --git a/vllm-chat/build/bentos/llama2/7b/apis/schema.json b/vllm-chat/build/bentos/llama2/7b/apis/schema.json deleted file mode 100644 index 7917c5da..00000000 --- a/vllm-chat/build/bentos/llama2/7b/apis/schema.json +++ /dev/null @@ -1,35 +0,0 @@ -{ - "name": "llama2", - "type": "service", - "routes": [ - { - "name": "generate", - "route": "/generate", - "batchable": false, - "input": { - "properties": { - "prompt": { - "default": "Explain superconductors like I'm five years old", - "title": "Prompt", - "type": "string" - }, - "max_tokens": { - "default": 1024, - "maximum": 1024, - "minimum": 128, - "title": "Max Tokens", - "type": "integer" - } - }, - "title": "Input", - "type": "object" - }, - "output": { - "title": "strIODescriptor", - "type": "string", - "is_stream": true, - "media_type": "text/event-stream" - } - } - ] -} \ No newline at end of file diff --git a/vllm-chat/build/bentos/llama2/7b/bento.yaml b/vllm-chat/build/bentos/llama2/7b/bento.yaml deleted file mode 100644 index 1c3e5f16..00000000 --- a/vllm-chat/build/bentos/llama2/7b/bento.yaml +++ /dev/null @@ -1,78 +0,0 @@ -service: service:VLLM -name: llama2 -version: 7b -bentoml_version: 1.2.11 -creation_time: '2024-04-21T09:17:39.844490+00:00' -labels: - owner: bentoml-team - stage: demo -models: [] -runners: [] -entry_service: llama2 -services: -- name: llama2 - service: '' - models: [] - dependencies: [] - config: - name: llama2 - traffic: - timeout: 300 - resources: - gpu: 1 - gpu_type: nvidia-l4 -envs: -- name: HF_TOKEN -schema: - name: llama2 - type: service - routes: - - name: generate - route: /generate - batchable: false - input: - properties: - prompt: - default: Explain superconductors like I'm five years old - title: Prompt - type: string - max_tokens: - default: 1024 - maximum: 1024 - minimum: 128 - title: Max Tokens - type: integer - title: Input - type: object - output: - title: strIODescriptor - type: string - is_stream: true - media_type: text/event-stream -apis: [] -docker: - distro: debian - python_version: '3.11' - cuda_version: null - env: - HF_TOKEN: '' - system_packages: null - setup_script: null - base_image: null - dockerfile_template: null -python: - requirements_txt: ./requirements.txt - packages: null - lock_packages: false - index_url: null - no_index: null - trusted_host: null - find_links: null - extra_index_url: null - pip_args: null - wheels: null -conda: - environment_yml: null - channels: null - dependencies: null - pip: null diff --git a/vllm-chat/build/bentos/llama2/7b/env/docker/Dockerfile b/vllm-chat/build/bentos/llama2/7b/env/docker/Dockerfile deleted file mode 100644 index e57d9b5b..00000000 --- a/vllm-chat/build/bentos/llama2/7b/env/docker/Dockerfile +++ /dev/null @@ -1,64 +0,0 @@ -# =========================================== -# -# THIS IS A GENERATED DOCKERFILE. DO NOT EDIT -# -# =========================================== - -# Block SETUP_BENTO_BASE_IMAGE -FROM python:3.11-slim as base-container - -ENV LANG=C.UTF-8 - -ENV LC_ALL=C.UTF-8 - -ENV PYTHONIOENCODING=UTF-8 - -ENV PYTHONUNBUFFERED=1 - - - -USER root - -ENV DEBIAN_FRONTEND=noninteractive -RUN rm -f /etc/apt/apt.conf.d/docker-clean; echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' > /etc/apt/apt.conf.d/keep-cache -RUN set -eux && \ - apt-get update -y && \ - apt-get install -q -y --no-install-recommends --allow-remove-essential \ - ca-certificates gnupg2 bash build-essential -# Block SETUP_BENTO_USER -ARG BENTO_USER=bentoml -ARG BENTO_USER_UID=1034 -ARG BENTO_USER_GID=1034 -RUN groupadd -g $BENTO_USER_GID -o $BENTO_USER && useradd -m -u $BENTO_USER_UID -g $BENTO_USER_GID -o -r $BENTO_USER -ARG HF_TOKEN= -ENV HF_TOKEN=$HF_TOKEN -ARG BENTO_PATH=/home/bentoml/bento -ENV BENTO_PATH=$BENTO_PATH -ENV BENTOML_HOME=/home/bentoml/ - -RUN mkdir $BENTO_PATH && chown bentoml:bentoml $BENTO_PATH -R -WORKDIR $BENTO_PATH - - - -# Block SETUP_BENTO_COMPONENTS -COPY --chown=bentoml:bentoml ./env/python ./env/python/ -# install python packages with install.sh -RUN bash -euxo pipefail /home/bentoml/bento/env/python/install.sh -COPY --chown=bentoml:bentoml . ./ - -# Block SETUP_BENTO_ENTRYPOINT -RUN rm -rf /var/lib/{apt,cache,log} -# Default port for BentoServer -EXPOSE 3000 - -# Expose Prometheus port -EXPOSE 3001 - -RUN chmod +x /home/bentoml/bento/env/docker/entrypoint.sh - -USER bentoml - -ENTRYPOINT [ "/home/bentoml/bento/env/docker/entrypoint.sh" ] - - diff --git a/vllm-chat/build/bentos/llama2/7b/env/docker/entrypoint.sh b/vllm-chat/build/bentos/llama2/7b/env/docker/entrypoint.sh deleted file mode 100644 index df1892dd..00000000 --- a/vllm-chat/build/bentos/llama2/7b/env/docker/entrypoint.sh +++ /dev/null @@ -1,56 +0,0 @@ -#!/usr/bin/env bash -set -Eeuo pipefail - -# check to see if this file is being run or sourced from another script -_is_sourced() { - # https://unix.stackexchange.com/a/215279 - [ "${#FUNCNAME[@]}" -ge 2 ] && - [ "${FUNCNAME[0]}" = '_is_sourced' ] && - [ "${FUNCNAME[1]}" = 'source' ] -} - -_main() { - # For backwards compatibility with the yatai<1.0.0, adapting the old "yatai" command to the new "start" command. - if [ "${#}" -gt 0 ] && [ "${1}" = 'python' ] && [ "${2}" = '-m' ] && { [ "${3}" = 'bentoml._internal.server.cli.runner' ] || [ "${3}" = "bentoml._internal.server.cli.api_server" ]; }; then # SC2235, use { } to avoid subshell overhead - if [ "${3}" = 'bentoml._internal.server.cli.runner' ]; then - set -- bentoml start-runner-server "${@:4}" - elif [ "${3}" = 'bentoml._internal.server.cli.api_server' ]; then - set -- bentoml start-http-server "${@:4}" - fi - # If no arg or first arg looks like a flag. - elif [[ "$#" -eq 0 ]] || [[ "${1:0:1}" =~ '-' ]]; then - # This is provided for backwards compatibility with places where user may have - # discover this easter egg and use it in their scripts to run the container. - if [[ -v BENTOML_SERVE_COMPONENT ]]; then - echo "\$BENTOML_SERVE_COMPONENT is set! Calling 'bentoml start-*' instead" - if [ "${BENTOML_SERVE_COMPONENT}" = 'http_server' ]; then - set -- bentoml start-http-server "$@" "$BENTO_PATH" - elif [ "${BENTOML_SERVE_COMPONENT}" = 'grpc_server' ]; then - set -- bentoml start-grpc-server "$@" "$BENTO_PATH" - elif [ "${BENTOML_SERVE_COMPONENT}" = 'runner' ]; then - set -- bentoml start-runner-server "$@" "$BENTO_PATH" - fi - else - set -- bentoml serve "$@" "$BENTO_PATH" - fi - fi - # Overide the BENTOML_PORT if PORT env var is present. Used for Heroku and Yatai. - if [[ -v PORT ]]; then - echo "\$PORT is set! Overiding \$BENTOML_PORT with \$PORT ($PORT)" - export BENTOML_PORT=$PORT - fi - # Handle serve and start commands that is passed to the container. - # Assuming that serve and start commands are the first arguments - # Note that this is the recommended way going forward to run all bentoml containers. - if [ "${#}" -gt 0 ] && { [ "${1}" = 'serve' ] || [ "${1}" = 'serve-http' ] || [ "${1}" = 'serve-grpc' ] || [ "${1}" = 'start-http-server' ] || [ "${1}" = 'start-grpc-server' ] || [ "${1}" = 'start-runner-server' ]; }; then - exec bentoml "$@" "$BENTO_PATH" - else - # otherwise default to run whatever the command is - # This should allow running bash, sh, python, etc - exec "$@" - fi -} - -if ! _is_sourced; then - _main "$@" -fi diff --git a/vllm-chat/build/bentos/llama2/7b/env/python/install.sh b/vllm-chat/build/bentos/llama2/7b/env/python/install.sh deleted file mode 100644 index e2bac1c2..00000000 --- a/vllm-chat/build/bentos/llama2/7b/env/python/install.sh +++ /dev/null @@ -1,48 +0,0 @@ -#!/usr/bin/env bash -set -exuo pipefail - -# Parent directory https://stackoverflow.com/a/246128/8643197 -BASEDIR="$( cd -- "$( dirname -- "${BASH_SOURCE[0]:-$0}"; )" &> /dev/null && pwd 2> /dev/null; )" - -PIP_ARGS=() - -# BentoML by default generates two requirement files: -# - ./env/python/requirements.lock.txt: all dependencies locked to its version presented during `build` -# - ./env/python/requirements.txt: all dependencies as user specified in code or requirements.txt file -REQUIREMENTS_TXT="$BASEDIR/requirements.txt" -REQUIREMENTS_LOCK="$BASEDIR/requirements.lock.txt" -WHEELS_DIR="$BASEDIR/wheels" -BENTOML_VERSION=${BENTOML_VERSION:-1.2.11} -# Install python packages, prefer installing the requirements.lock.txt file if it exist -pushd "$BASEDIR" &>/dev/null -if [ -f "$REQUIREMENTS_LOCK" ]; then - echo "Installing pip packages from 'requirements.lock.txt'.." - pip3 install -r "$REQUIREMENTS_LOCK" "${PIP_ARGS[@]}" -else - if [ -f "$REQUIREMENTS_TXT" ]; then - echo "Installing pip packages from 'requirements.txt'.." - pip3 install -r "$REQUIREMENTS_TXT" "${PIP_ARGS[@]}" - fi -fi -popd &>/dev/null - -# Attempt to expand the glob pattern. The nullglob option ensures that -# the pattern itself is not returned if no files match. -shopt -s nullglob -wheels=($WHEELS_DIR/*.whl) - -if [ ${#wheels[@]} -gt 0 ]; then - echo "Installing wheels packaged in Bento.." - pip3 install "${wheels[@]}" "${PIP_ARGS[@]}" -fi - - -# Install the BentoML from PyPI if it's not already installed -if python3 -c "import bentoml" &> /dev/null; then - existing_bentoml_version=$(python3 -c "import bentoml; print(bentoml.__version__)") - if [ "$existing_bentoml_version" != "$BENTOML_VERSION" ]; then - echo "WARNING: using BentoML version ${existing_bentoml_version}" - fi -else - pip3 install bentoml=="$BENTOML_VERSION" -fi \ No newline at end of file diff --git a/vllm-chat/build/bentos/llama2/7b/env/python/requirements.txt b/vllm-chat/build/bentos/llama2/7b/env/python/requirements.txt deleted file mode 100644 index 7382d95a..00000000 --- a/vllm-chat/build/bentos/llama2/7b/env/python/requirements.txt +++ /dev/null @@ -1,4 +0,0 @@ -bentoml==1.2.11 -torch==2.1.2 -vllm==0.4.0.post1 -transformers==4.39.3 diff --git a/vllm-chat/build/bentos/llama2/7b/env/python/version.txt b/vllm-chat/build/bentos/llama2/7b/env/python/version.txt deleted file mode 100644 index 2b6882dd..00000000 --- a/vllm-chat/build/bentos/llama2/7b/env/python/version.txt +++ /dev/null @@ -1 +0,0 @@ -3.11.4 \ No newline at end of file diff --git a/vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/__init__.py b/vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/protocol.py b/vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/protocol.py deleted file mode 100644 index 7de4d1da..00000000 --- a/vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/protocol.py +++ /dev/null @@ -1,441 +0,0 @@ -from __future__ import annotations - -# Adapted from -# https://github.com/lm-sys/FastChat/blob/168ccc29d3f7edc50823016105c024fe2282732a/fastchat/protocol/openai_api_protocol.py -import time -import uuid -from typing import TYPE_CHECKING, Dict, List, Literal, Optional, Union - -from pydantic import BaseModel, Field, model_validator - -if TYPE_CHECKING: - import torch - from vllm.sampling_params import SamplingParams - - -def random_uuid() -> str: - return str(uuid.uuid4().hex) - - -class ErrorResponse(BaseModel): - object: str = "error" - message: str - type: str - param: Optional[str] = None - code: int - - -class ModelPermission(BaseModel): - id: str = Field(default_factory=lambda: f"modelperm-{random_uuid()}") - object: str = "model_permission" - created: int = Field(default_factory=lambda: int(time.time())) - allow_create_engine: bool = False - allow_sampling: bool = True - allow_logprobs: bool = True - allow_search_indices: bool = False - allow_view: bool = True - allow_fine_tuning: bool = False - organization: str = "*" - group: Optional[str] = None - is_blocking: str = False - - -class ModelCard(BaseModel): - id: str - object: str = "model" - created: int = Field(default_factory=lambda: int(time.time())) - owned_by: str = "vllm" - root: Optional[str] = None - parent: Optional[str] = None - permission: List[ModelPermission] = Field(default_factory=list) - - -class ModelList(BaseModel): - object: str = "list" - data: List[ModelCard] = Field(default_factory=list) - - -class UsageInfo(BaseModel): - prompt_tokens: int = 0 - total_tokens: int = 0 - completion_tokens: Optional[int] = 0 - - -class ResponseFormat(BaseModel): - # type must be "json_object" or "text" - type: str = Literal["text", "json_object"] - - -class ChatCompletionRequest(BaseModel): - # Ordered by official OpenAI API documentation - # https://platform.openai.com/docs/api-reference/chat/create - messages: List[Dict[str, str]] - model: str - frequency_penalty: Optional[float] = 0.0 - logit_bias: Optional[Dict[str, float]] = None - logprobs: Optional[bool] = False - top_logprobs: Optional[int] = None - max_tokens: Optional[int] = None - n: Optional[int] = 1 - presence_penalty: Optional[float] = 0.0 - response_format: Optional[ResponseFormat] = None - seed: Optional[int] = None - stop: Optional[Union[str, List[str]]] = Field(default_factory=list) - stream: Optional[bool] = False - temperature: Optional[float] = 0.7 - top_p: Optional[float] = 1.0 - user: Optional[str] = None - - # doc: begin-chat-completion-sampling-params - best_of: Optional[int] = None - use_beam_search: Optional[bool] = False - top_k: Optional[int] = -1 - min_p: Optional[float] = 0.0 - repetition_penalty: Optional[float] = 1.0 - length_penalty: Optional[float] = 1.0 - early_stopping: Optional[bool] = False - ignore_eos: Optional[bool] = False - min_tokens: Optional[int] = 0 - stop_token_ids: Optional[List[int]] = Field(default_factory=list) - skip_special_tokens: Optional[bool] = True - spaces_between_special_tokens: Optional[bool] = True - # doc: end-chat-completion-sampling-params - - # doc: begin-chat-completion-extra-params - echo: Optional[bool] = Field( - default=False, - description=( - "If true, the new message will be prepended with the last message " - "if they belong to the same role." - ), - ) - add_generation_prompt: Optional[bool] = Field( - default=True, - description=( - "If true, the generation prompt will be added to the chat template. " - "This is a parameter used by chat template in tokenizer config of the " - "model." - ), - ) - include_stop_str_in_output: Optional[bool] = Field( - default=False, - description=( - "Whether to include the stop string in the output. " - "This is only applied when the stop or stop_token_ids is set." - ), - ) - guided_json: Optional[Union[str, dict, BaseModel]] = Field( - default=None, - description=("If specified, the output will follow the JSON schema."), - ) - guided_regex: Optional[str] = Field( - default=None, - description=("If specified, the output will follow the regex pattern."), - ) - guided_choice: Optional[List[str]] = Field( - default=None, - description=("If specified, the output will be exactly one of the choices."), - ) - guided_grammar: Optional[str] = Field( - default=None, - description=("If specified, the output will follow the context free grammar."), - ) - - # doc: end-chat-completion-extra-params - - def to_sampling_params(self) -> SamplingParams: - if self.logprobs and not self.top_logprobs: - raise ValueError("Top logprobs must be set when logprobs is.") - - logits_processors = None - if self.logit_bias: - - def logit_bias_logits_processor( - token_ids: List[int], logits: torch.Tensor - ) -> torch.Tensor: - for token_id, bias in self.logit_bias.items(): - # Clamp the bias between -100 and 100 per OpenAI API spec - bias = min(100, max(-100, bias)) - logits[int(token_id)] += bias - return logits - - logits_processors = [logit_bias_logits_processor] - - from vllm.sampling_params import SamplingParams - - return SamplingParams( - n=self.n, - presence_penalty=self.presence_penalty, - frequency_penalty=self.frequency_penalty, - repetition_penalty=self.repetition_penalty, - temperature=self.temperature, - top_p=self.top_p, - min_p=self.min_p, - seed=self.seed, - stop=self.stop, - stop_token_ids=self.stop_token_ids, - max_tokens=self.max_tokens, - min_tokens=self.min_tokens, - logprobs=self.top_logprobs if self.logprobs else None, - prompt_logprobs=self.top_logprobs if self.echo else None, - best_of=self.best_of, - top_k=self.top_k, - ignore_eos=self.ignore_eos, - use_beam_search=self.use_beam_search, - early_stopping=self.early_stopping, - skip_special_tokens=self.skip_special_tokens, - spaces_between_special_tokens=self.spaces_between_special_tokens, - include_stop_str_in_output=self.include_stop_str_in_output, - length_penalty=self.length_penalty, - logits_processors=logits_processors, - ) - - @model_validator(mode="before") - @classmethod - def check_guided_decoding_count(cls, data): - guide_count = sum( - [ - "guided_json" in data and data["guided_json"] is not None, - "guided_regex" in data and data["guided_regex"] is not None, - "guided_choice" in data and data["guided_choice"] is not None, - ] - ) - if guide_count > 1: - raise ValueError( - "You can only use one kind of guided decoding " - "('guided_json', 'guided_regex' or 'guided_choice')." - ) - return data - - -class CompletionRequest(BaseModel): - # Ordered by official OpenAI API documentation - # https://platform.openai.com/docs/api-reference/completions/create - model: str - prompt: Union[List[int], List[List[int]], str, List[str]] - best_of: Optional[int] = None - echo: Optional[bool] = False - frequency_penalty: Optional[float] = 0.0 - logit_bias: Optional[Dict[str, float]] = None - logprobs: Optional[int] = None - max_tokens: Optional[int] = 16 - n: Optional[int] = 1 - presence_penalty: Optional[float] = 0.0 - seed: Optional[int] = None - stop: Optional[Union[str, List[str]]] = Field(default_factory=list) - stream: Optional[bool] = False - suffix: Optional[str] = None - temperature: Optional[float] = 1.0 - top_p: Optional[float] = 1.0 - user: Optional[str] = None - - # doc: begin-completion-sampling-params - use_beam_search: Optional[bool] = False - top_k: Optional[int] = -1 - min_p: Optional[float] = 0.0 - repetition_penalty: Optional[float] = 1.0 - length_penalty: Optional[float] = 1.0 - early_stopping: Optional[bool] = False - stop_token_ids: Optional[List[int]] = Field(default_factory=list) - ignore_eos: Optional[bool] = False - min_tokens: Optional[int] = 0 - skip_special_tokens: Optional[bool] = True - spaces_between_special_tokens: Optional[bool] = True - # doc: end-completion-sampling-params - - # doc: begin-completion-extra-params - include_stop_str_in_output: Optional[bool] = Field( - default=False, - description=( - "Whether to include the stop string in the output. " - "This is only applied when the stop or stop_token_ids is set." - ), - ) - response_format: Optional[ResponseFormat] = Field( - default=None, - description=( - "Similar to chat completion, this parameter specifies the format of " - "output. Only {'type': 'json_object'} or {'type': 'text' } is " - "supported." - ), - ) - guided_json: Optional[Union[str, dict, BaseModel]] = Field( - default=None, - description=("If specified, the output will follow the JSON schema."), - ) - guided_regex: Optional[str] = Field( - default=None, - description=("If specified, the output will follow the regex pattern."), - ) - guided_choice: Optional[List[str]] = Field( - default=None, - description=("If specified, the output will be exactly one of the choices."), - ) - guided_grammar: Optional[str] = Field( - default=None, - description=("If specified, the output will follow the context free grammar."), - ) - - # doc: end-completion-extra-params - - def to_sampling_params(self): - echo_without_generation = self.echo and self.max_tokens == 0 - - logits_processors = None - if self.logit_bias is not None: - - def logit_bias_logits_processor( - token_ids: List[int], logits: torch.Tensor - ) -> torch.Tensor: - for token_id, bias in self.logit_bias.items(): - # Clamp the bias between -100 and 100 per OpenAI API spec - bias = min(100, max(-100, bias)) - logits[int(token_id)] += bias - return logits - - logits_processors = [logit_bias_logits_processor] - - from vllm.sampling_params import SamplingParams - - return SamplingParams( - n=self.n, - best_of=self.best_of, - presence_penalty=self.presence_penalty, - frequency_penalty=self.frequency_penalty, - repetition_penalty=self.repetition_penalty, - temperature=self.temperature, - top_p=self.top_p, - top_k=self.top_k, - min_p=self.min_p, - seed=self.seed, - stop=self.stop, - stop_token_ids=self.stop_token_ids, - ignore_eos=self.ignore_eos, - max_tokens=self.max_tokens if not echo_without_generation else 1, - min_tokens=self.min_tokens, - logprobs=self.logprobs, - use_beam_search=self.use_beam_search, - early_stopping=self.early_stopping, - prompt_logprobs=self.logprobs if self.echo else None, - skip_special_tokens=self.skip_special_tokens, - spaces_between_special_tokens=(self.spaces_between_special_tokens), - include_stop_str_in_output=self.include_stop_str_in_output, - length_penalty=self.length_penalty, - logits_processors=logits_processors, - ) - - @model_validator(mode="before") - @classmethod - def check_guided_decoding_count(cls, data): - guide_count = sum( - [ - "guided_json" in data and data["guided_json"] is not None, - "guided_regex" in data and data["guided_regex"] is not None, - "guided_choice" in data and data["guided_choice"] is not None, - ] - ) - if guide_count > 1: - raise ValueError( - "You can only use one kind of guided decoding " - "('guided_json', 'guided_regex' or 'guided_choice')." - ) - return data - - -class LogProbs(BaseModel): - text_offset: List[int] = Field(default_factory=list) - token_logprobs: List[Optional[float]] = Field(default_factory=list) - tokens: List[str] = Field(default_factory=list) - top_logprobs: Optional[List[Optional[Dict[str, float]]]] = None - - -class CompletionResponseChoice(BaseModel): - index: int - text: str - logprobs: Optional[LogProbs] = None - finish_reason: Optional[Literal["stop", "length"]] = None - stop_reason: Union[None, int, str] = Field( - default=None, - description=( - "The stop string or token id that caused the completion " - "to stop, None if the completion finished for some other reason " - "including encountering the EOS token" - ), - ) - - -class CompletionResponse(BaseModel): - id: str = Field(default_factory=lambda: f"cmpl-{random_uuid()}") - object: str = "text_completion" - created: int = Field(default_factory=lambda: int(time.time())) - model: str - choices: List[CompletionResponseChoice] - usage: UsageInfo - - -class CompletionResponseStreamChoice(BaseModel): - index: int - text: str - logprobs: Optional[LogProbs] = None - finish_reason: Optional[Literal["stop", "length"]] = None - stop_reason: Union[None, int, str] = Field( - default=None, - description=( - "The stop string or token id that caused the completion " - "to stop, None if the completion finished for some other reason " - "including encountering the EOS token" - ), - ) - - -class CompletionStreamResponse(BaseModel): - id: str = Field(default_factory=lambda: f"cmpl-{random_uuid()}") - object: str = "text_completion" - created: int = Field(default_factory=lambda: int(time.time())) - model: str - choices: List[CompletionResponseStreamChoice] - usage: Optional[UsageInfo] = Field(default=None) - - -class ChatMessage(BaseModel): - role: str - content: str - - -class ChatCompletionResponseChoice(BaseModel): - index: int - message: ChatMessage - logprobs: Optional[LogProbs] = None - finish_reason: Optional[Literal["stop", "length"]] = None - stop_reason: Union[None, int, str] = None - - -class ChatCompletionResponse(BaseModel): - id: str = Field(default_factory=lambda: f"chatcmpl-{random_uuid()}") - object: str = "chat.completion" - created: int = Field(default_factory=lambda: int(time.time())) - model: str - choices: List[ChatCompletionResponseChoice] - usage: UsageInfo - - -class DeltaMessage(BaseModel): - role: Optional[str] = None - content: Optional[str] = None - - -class ChatCompletionResponseStreamChoice(BaseModel): - index: int - delta: DeltaMessage - logprobs: Optional[LogProbs] = None - finish_reason: Optional[Literal["stop", "length"]] = None - stop_reason: Union[None, int, str] = None - - -class ChatCompletionStreamResponse(BaseModel): - id: str = Field(default_factory=lambda: f"chatcmpl-{random_uuid()}") - object: str = "chat.completion.chunk" - created: int = Field(default_factory=lambda: int(time.time())) - model: str - choices: List[ChatCompletionResponseStreamChoice] - usage: Optional[UsageInfo] = Field(default=None) diff --git a/vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/utils.py b/vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/utils.py deleted file mode 100644 index 87da555f..00000000 --- a/vllm-chat/build/bentos/llama2/7b/src/bentovllm_openai/utils.py +++ /dev/null @@ -1,179 +0,0 @@ -from __future__ import annotations - -import asyncio -import typing as t - -from _bentoml_sdk.service.factory import Service -from fastapi import FastAPI, Request -from fastapi.responses import JSONResponse, StreamingResponse - -from .protocol import ChatCompletionRequest, CompletionRequest, ErrorResponse - -T = t.TypeVar("T", bound=object) - -if t.TYPE_CHECKING: - from vllm import AsyncLLMEngine - - -def openai_endpoints( - served_model: str, - response_role: str = "assistant", - chat_template: t.Optional[str] = None, - chat_template_model_id: t.Optional[str] = None, -): - - def openai_wrapper(svc: Service[T]): - - cls = svc.inner - app = FastAPI() - - class new_cls(cls): - - def __init__(self): - - super().__init__() - - # we need to import bentoml before vllm so - # `prometheus_client` won't cause import troubles - # That's also why we put these codes inside class's - # `__init__` function - import bentoml - from vllm.entrypoints.openai.serving_chat import OpenAIServingChat - from vllm.entrypoints.openai.serving_completion import ( - OpenAIServingCompletion, - ) - - # https://github.com/vllm-project/vllm/issues/2683 - class PatchedOpenAIServingChat(OpenAIServingChat): - def __init__( - self, - engine: AsyncLLMEngine, - served_model: str, - response_role: str, - chat_template=None, - ): - super(OpenAIServingChat, self).__init__( - engine=engine, - served_model=served_model, - lora_modules=None, - ) - self.response_role = response_role - try: - event_loop = asyncio.get_running_loop() - except RuntimeError: - event_loop = None - - if event_loop is not None and event_loop.is_running(): - event_loop.create_task( - self._load_chat_template(chat_template) - ) - else: - asyncio.run(self._load_chat_template(chat_template)) - - async def _load_chat_template(self, chat_template): - # Simply making this function async is usually already enough to give the parent - # class time to load the tokenizer (so usually no sleeping happens here) - # However, it feels safer to be explicit about this since asyncio does not - # guarantee the order in which scheduled tasks are run - while self.tokenizer is None: - await asyncio.sleep(0.1) - return super()._load_chat_template(chat_template) - - self.openai_serving_completion = OpenAIServingCompletion( - engine=self.engine, - served_model=served_model, - ) - - self.chat_template = chat_template - if self.chat_template is None and chat_template_model_id is not None: - from transformers import AutoTokenizer - - _tokenizer = AutoTokenizer.from_pretrained(chat_template_model_id) - self.chat_template = _tokenizer.chat_template - - self.openai_serving_chat = PatchedOpenAIServingChat( - engine=self.engine, - served_model=served_model, - response_role=response_role, - chat_template=self.chat_template, - ) - - @app.get("/models") - async def show_available_models(): - models = await self.openai_serving_chat.show_available_models() - return JSONResponse(content=models.model_dump()) - - @app.post("/chat/completions") - async def create_chat_completion( - request: ChatCompletionRequest, raw_request: Request - ): - generator = await self.openai_serving_chat.create_chat_completion( - request, raw_request - ) - if isinstance(generator, ErrorResponse): - return JSONResponse( - content=generator.model_dump(), status_code=generator.code - ) - if request.stream: - return StreamingResponse( - content=generator, media_type="text/event-stream" - ) - else: - return JSONResponse(content=generator.model_dump()) - - @app.post("/completions") - async def create_completion( - request: CompletionRequest, raw_request: Request - ): - generator = await self.openai_serving_completion.create_completion( - request, raw_request - ) - if isinstance(generator, ErrorResponse): - return JSONResponse( - content=generator.model_dump(), status_code=generator.code - ) - if request.stream: - return StreamingResponse( - content=generator, media_type="text/event-stream" - ) - else: - return JSONResponse(content=generator.model_dump()) - - new_cls.__name__ = "%s_OpenAI" % cls.__name__ - svc.inner = new_cls - svc.mount_asgi_app(app, path="/v1/") - return svc - - return openai_wrapper - - -# helper function to make a httpx client for BentoML service -def _make_httpx_client(url, svc): - - from urllib.parse import urlparse - - import httpx - from bentoml._internal.utils.uri import uri_to_path - - timeout = svc.config["traffic"]["timeout"] - headers = {"Runner-Name": svc.name} - parsed = urlparse(url) - transport = None - target_url = url - - if parsed.scheme == "file": - uds = uri_to_path(url) - transport = httpx.HTTPTransport(uds=uds) - target_url = "http://127.0.0.1:3000" - elif parsed.scheme == "tcp": - target_url = f"http://{parsed.netloc}" - - return ( - httpx.Client( - transport=transport, - timeout=timeout, - follow_redirects=True, - headers=headers, - ), - target_url, - ) diff --git a/vllm-chat/build/bentos/llama2/7b/src/service.py b/vllm-chat/build/bentos/llama2/7b/src/service.py deleted file mode 100644 index 662f3ec1..00000000 --- a/vllm-chat/build/bentos/llama2/7b/src/service.py +++ /dev/null @@ -1,55 +0,0 @@ -import uuid -from typing import AsyncGenerator - -import bentoml -from annotated_types import Ge, Le -from bentovllm_openai.utils import openai_endpoints -from typing_extensions import Annotated - -MAX_TOKENS = 1024 -PROMPT_TEMPLATE = """[INST] <> -You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. - -If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. -<> - -{user_prompt} [/INST] """ - -MODEL_ID = "meta-llama/Llama-2-7b-chat-hf" - - -@openai_endpoints(served_model_names=[MODEL_ID]) -@bentoml.service( - name="llama2", - traffic={ - "timeout": 300, - }, - resources={ - "gpu": 1, - "gpu_type": "nvidia-l4", - }, -) -class VLLM: - def __init__(self) -> None: - from vllm import AsyncEngineArgs, AsyncLLMEngine - - ENGINE_ARGS = AsyncEngineArgs(model=MODEL_ID, max_model_len=MAX_TOKENS) - self.engine = AsyncLLMEngine.from_engine_args(ENGINE_ARGS) - - @bentoml.api - async def generate( - self, - prompt: str = "Explain superconductors like I'm five years old", - max_tokens: Annotated[int, Ge(128), Le(MAX_TOKENS)] = MAX_TOKENS, - ) -> AsyncGenerator[str, None]: - from vllm import SamplingParams - - SAMPLING_PARAM = SamplingParams(max_tokens=max_tokens) - prompt = PROMPT_TEMPLATE.format(user_prompt=prompt) - stream = await self.engine.add_request(uuid.uuid4().hex, prompt, SAMPLING_PARAM) - - cursor = 0 - async for request_output in stream: - text = request_output.outputs[0].text - yield text[cursor:] - cursor = len(text) diff --git a/vllm-chat/build/bentos/llama2/latest b/vllm-chat/build/bentos/llama2/latest deleted file mode 100644 index 824292c5..00000000 --- a/vllm-chat/build/bentos/llama2/latest +++ /dev/null @@ -1 +0,0 @@ -7b \ No newline at end of file diff --git a/vllm-chat/build/client_id b/vllm-chat/build/client_id deleted file mode 100644 index 46eda765..00000000 --- a/vllm-chat/build/client_id +++ /dev/null @@ -1,2 +0,0 @@ -creation_timestamp: 2024-04-10 12:55:41.120086+00:00 -id: d4b8f81e-4875-44d8-942b-0e0a0ed76c92 diff --git a/vllm-chat/service.py b/vllm-chat/service.py index aa6770ae..f43894a1 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -11,12 +11,11 @@ import yaml CONFIG = yaml.safe_load(open("config.yaml")) ENGINE_CONFIG = CONFIG["engine_config"] -MODEL_ID = ENGINE_CONFIG["model"] PROMPT_TEMPLATE = CONFIG["prompt"] SERVICE_CONFIG = CONFIG["service_config"] -@openai_endpoints(served_model_names=[MODEL_ID]) +@openai_endpoints(served_model_names=[ENGINE_CONFIG["model"]]) @bentoml.service(**SERVICE_CONFIG) class VLLM: def __init__(self) -> None: From 669f95c248d68877755030e871289e23720e085f Mon Sep 17 00:00:00 2001 From: bojiang Date: Mon, 20 May 2024 20:57:38 +0800 Subject: [PATCH 011/125] use py config to workaround bentoml path --- make.py | 29 ++++++++++++++----- vllm-chat/{config.yaml => bento_constants.py} | 12 ++++---- vllm-chat/service.py | 9 +++--- 3 files changed, 34 insertions(+), 16 deletions(-) rename vllm-chat/{config.yaml => bento_constants.py} (94%) diff --git a/make.py b/make.py index 97e69369..8acac29f 100644 --- a/make.py +++ b/make.py @@ -14,6 +14,13 @@ with open("recipe.yaml") as f: BENTOML_HOME = pathlib.Path(os.environ["BENTOML_HOME"]) +CONSTANT_YAML_TMPL = r""" +CONSTANT_YAML = ''' +{} +''' +""" + + if __name__ == "__main__": if len(sys.argv) == 2: specified_model = sys.argv[1] @@ -30,8 +37,10 @@ if __name__ == "__main__": with tempfile.TemporaryDirectory() as tempdir: tempdir = pathlib.Path(tempdir) shutil.copytree(project, tempdir, dirs_exist_ok=True) - with open(tempdir / "config.yaml", "w") as f: - yaml.dump(config, f) + + with open(tempdir / "bento_constants.py", "w") as f: + f.write(CONSTANT_YAML_TMPL.format(yaml.dump(config))) + subprocess.run( ["bentoml", "build", str(tempdir), "--version", model_version], check=True, @@ -44,8 +53,14 @@ if __name__ == "__main__": # link alias for alias in config.get("alias", []): - ALIAS_PATH = BENTOML_HOME / "bentos" / model_repo / alias - if ALIAS_PATH.exists(): - continue - with open(ALIAS_PATH, "w") as f: - f.write(model_name) + if alias == "latest": + ALIAS_PATH = BENTOML_HOME / "bentos" / model_repo / alias + if ALIAS_PATH.exists(): + continue + with open(ALIAS_PATH, "w") as f: + f.write(model_name) + else: # bentoml currently only support latest alias, copy to other alias + shutil.copytree( + BENTOML_HOME / "bentos" / model_repo / model_version, + BENTOML_HOME / "bentos" / model_repo / alias, + ) diff --git a/vllm-chat/config.yaml b/vllm-chat/bento_constants.py similarity index 94% rename from vllm-chat/config.yaml rename to vllm-chat/bento_constants.py index 75c48347..2b4b5725 100644 --- a/vllm-chat/config.yaml +++ b/vllm-chat/bento_constants.py @@ -1,3 +1,4 @@ +CONSTANT_YAML = """ alias: - latest - 3.8b @@ -11,14 +12,15 @@ service_config: resources: gpu: 1 gpu_type: nvidia-tesla-t4 -engine_config: - model: microsoft/Phi-3-mini-4k-instruct - max_model_len: 4096 - dtype: half - trust_remote_code: true prompt: head: ~ body: |- <|user|> {user_prompt}<|end|> <|assistant|> +engine_config: + model: microsoft/Phi-3-mini-4k-instruct + max_model_len: 4096 + dtype: half + trust_remote_code: true +""" diff --git a/vllm-chat/service.py b/vllm-chat/service.py index f43894a1..f1bf109f 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -6,13 +6,14 @@ import bentoml from annotated_types import Ge, Le from bentovllm_openai.utils import openai_endpoints import yaml +from bento_constants import CONSTANT_YAML -CONFIG = yaml.safe_load(open("config.yaml")) +CONSTANTS = yaml.safe_load(CONSTANT_YAML) -ENGINE_CONFIG = CONFIG["engine_config"] -PROMPT_TEMPLATE = CONFIG["prompt"] -SERVICE_CONFIG = CONFIG["service_config"] +ENGINE_CONFIG = CONSTANTS["engine_config"] +PROMPT_TEMPLATE = CONSTANTS["prompt"] +SERVICE_CONFIG = CONSTANTS["service_config"] @openai_endpoints(served_model_names=[ENGINE_CONFIG["model"]]) From eafb5693eb8eedc7e380cca921c4b2a2e1b12255 Mon Sep 17 00:00:00 2001 From: bojiang Date: Mon, 20 May 2024 21:29:21 +0800 Subject: [PATCH 012/125] add llama2 awq --- recipe.yaml | 25 +++++++++++++++++++++++++ 1 file changed, 25 insertions(+) diff --git a/recipe.yaml b/recipe.yaml index 70633afd..c514d4d9 100644 --- a/recipe.yaml +++ b/recipe.yaml @@ -46,3 +46,28 @@ If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. <> {user_prompt} [/INST] +"llama2:7b-chat-awq-4bit": + alias: + - 7b-chat-4bit + project: vllm-chat + service_config: + name: llama2 + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-tesla-t4 + engine_config: + model: TheBloke/Llama-2-7B-Chat-AWQ + max_model_len: 1024 + quantization: awq + enforce_eager: true + + prompt: + head: ~ + body: |- + [INST] <> + You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. + If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. + <> + {user_prompt} [/INST] From 97e85743da521f41cf2eaf7731c4ee403f667c26 Mon Sep 17 00:00:00 2001 From: bojiang Date: Mon, 20 May 2024 21:36:14 +0800 Subject: [PATCH 013/125] fix clean repo --- openllm_next/common.py | 2 +- openllm_next/repo.py | 2 ++ 2 files changed, 3 insertions(+), 1 deletion(-) diff --git a/openllm_next/common.py b/openllm_next/common.py index 3d86851c..5241362c 100644 --- a/openllm_next/common.py +++ b/openllm_next/common.py @@ -26,7 +26,7 @@ CONFIG_FILE = CLLAMA_HOME / "config.json" class Config(pydantic.BaseModel): repos: dict[str, str] = { - "default": "git+https://github.com/bojiang/bentovllm@main#subdirectory=bentoml" + "default": "git+https://github.com/bojiang/openllm-repo@main" } default_repo: str = "default" diff --git a/openllm_next/repo.py b/openllm_next/repo.py index 1e1d8321..f3dd31bc 100644 --- a/openllm_next/repo.py +++ b/openllm_next/repo.py @@ -113,6 +113,8 @@ def update(): run_command(cmd, cwd=repo_dir) cmd = ["git", "reset", "--hard", f"origin/{branch}"] run_command(cmd, cwd=repo_dir) + cmd = ["git", "clean", "-fdx"] + run_command(cmd, cwd=repo_dir) except: shutil.rmtree(repo_dir, ignore_errors=True) questionary.print(f"Failed to update repo {name}", style=ERROR_STYLE) From 10ae5c64a93d747862d96a1064b271db88f3e13e Mon Sep 17 00:00:00 2001 From: bojiang Date: Mon, 20 May 2024 21:58:03 +0800 Subject: [PATCH 014/125] more spec --- openllm_next/spec.py | 29 +++++++++++++++++++---------- 1 file changed, 19 insertions(+), 10 deletions(-) diff --git a/openllm_next/spec.py b/openllm_next/spec.py index 006041fc..0023a2d0 100644 --- a/openllm_next/spec.py +++ b/openllm_next/spec.py @@ -1,11 +1,20 @@ -GPU_MEMORY = { - "nvidia-tesla-t4": 16, - "nvidia-tesla-v100": 16, - "nvidia-tesla-p100": 16, - "nvidia-tesla-p4": 8, - "nvidia-tesla-k80": 12, - "nvidia-tesla-a100": 40, - "nvidia-tesla-a100-80gb": 80, - "nvidia-tesla-a10g": 24, - "nvidia-l4": 24, +accelerator_details = { + "nvidia-gtx-1650": {"model": "GTX 1650", "memory_size": 4.0}, + "nvidia-gtx-1060": {"model": "GTX 1060", "memory_size": 6.0}, + "nvidia-gtx-1080-ti": {"model": "GTX 1080 Ti", "memory_size": 11.0}, + "nvidia-rtx-3060": {"model": "RTX 3060", "memory_size": 12.0}, + "nvidia-rtx-3060-ti": {"model": "RTX 3060 Ti", "memory_size": 8.0}, + "nvidia-rtx-3070-ti": {"model": "RTX 3070 Ti", "memory_size": 8.0}, + "nvidia-rtx-3080": {"model": "RTX 3080", "memory_size": 10.0}, + "nvidia-rtx-3080-ti": {"model": "RTX 3080 Ti", "memory_size": 12.0}, + "nvidia-rtx-3090": {"model": "RTX 3090", "memory_size": 24.0}, + "nvidia-tesla-p4": {"model": "P4", "memory_size": 8.0}, + "nvidia-tesla-p100": {"model": "P100", "memory_size": 16.0}, + "nvidia-tesla-k80": {"model": "K80", "memory_size": 12.0}, + "nvidia-tesla-t4": {"model": "T4", "memory_size": 16.0}, + "nvidia-tesla-v100": {"model": "V100", "memory_size": 16.0}, + "nvidia-l4": {"model": "L4", "memory_size": 24.0}, + "nvidia-tesla-a10g": {"model": "A10G", "memory_size": 24.0}, + "nvidia-a100-80gb": {"model": "A100", "memory_size": 80.0}, + "nvidia-tesla-a100": {"model": "A100", "memory_size": 40.0}, } From e49324fc86b23c96c4462cf81e6949eab950c132 Mon Sep 17 00:00:00 2001 From: bojiang <5886138+bojiang@users.noreply.github.com> Date: Mon, 20 May 2024 21:59:33 +0800 Subject: [PATCH 015/125] Delete recipe.py --- recipe.py | 136 ------------------------------------------------------ 1 file changed, 136 deletions(-) delete mode 100644 recipe.py diff --git a/recipe.py b/recipe.py deleted file mode 100644 index 7192d8e9..00000000 --- a/recipe.py +++ /dev/null @@ -1,136 +0,0 @@ - - - -PROMPT_TEMPLATE_MAP = { - "llama2:7b-chat": """[INST] <> -You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. - -If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. -<> - -{user_prompt} [/INST] """, - "mistral:7b-instruct": """[INST] -You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. - -If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. - -{user_prompt} [/INST] """, - "mixtral:8x7b-instruct": """[INST] -You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. - -If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. - -{user_prompt} [/INST] """, - "phi3:3.8b-mini-instruct-4k-fp16": """<|user|> -{user_prompt}<|end|> -<|assistant|>""", -} - -MODEL_ID_MAP = { - "llama2:7b-chat": "meta-llama/Llama-2-7b-chat-hf", - "mistral:7b-instruct": "mistralai/Mistral-7B-Instruct-v0.2", - "mixtral:8x7b-instruct": "TheBloke/Mixtral-8x7B-Instruct-v0.1-GPTQ", - "phi3:3.8b-mini-instruct-4k-fp16": "microsoft/Phi-3-mini-4k-instruct", -} - -SERVICE_CONFIG_MAP = { - "llama2:7b-chat": { - "name": "llama2", - "traffic": { - "timeout": 300, - }, - "resources": { - "gpu": 1, - "gpu_type": "nvidia-tesla-t4", - }, - }, - "mistral:7b-instruct": { - "name": "mistral", - "traffic": { - "timeout": 300, - }, - "resources": { - "gpu": 1, - "gpu_type": "nvidia-l4", - }, - }, - "mixtral:8x7b-instruct": { - "name": "mixtral", - "traffic": { - "timeout": 300, - }, - "resources": { - "gpu": 1, - "gpu_type": "nvidia-a100-80gb", - }, - }, - "phi3:3.8b-mini-instruct-4k-fp16": { - "name": "phi3", - "traffic": { - "timeout": 300, - }, - "resources": { - "gpu": 1, - "gpu_memory": "16GB", - }, - }, -} - -MODEL_CONFIG_MAP = { - "llama2:7b-chat": { - "max_model_len": 1024, - }, - "mistral:7b-instruct": { - "max_model_len": 1024, - "dtype": "half", - }, - "mixtral:8x7b-instruct": { - "max_model_len": 8192, - "gpu_memory_utilization": 0.85, - "quantization": "gptq", - "dtype": "half", - }, - "phi3:3.8b-mini-instruct-4k-fp16": { - "max_model_len": 4096, - "dtype": "half", - }, -} - -MODEL_ALIAS_MAP = { - "llama2": "llama2:7b-chat", - "llama2:7b": "llama2:7b-chat", - "llama2:7b-chat": "llama2:7b-chat", - "mistral": "mistral:7b-instruct", - "mistral:7b": "mistral:7b-instruct", - "mistral:7b-instruct": "mistral:7b-instruct", - "mixtral": "mixtral:8x7b-instruct", - "mixtral:8x7b": "mixtral:8x7b-instruct", - "mixtral:8x7b-instruct": "mixtral:8x7b-instruct", - "phi3": "phi3:3.8b-mini-instruct-4k-fp16", - "phi3:3.8b": "phi3:3.8b-mini-instruct-4k-fp16", - "phi3:mini": "phi3:3.8b-mini-instruct-4k-fp16", - "phi3:instruct": "phi3:3.8b-mini-instruct-4k-fp16", - "phi3:3.8b-mini-instruct": "phi3:3.8b-mini-instruct-4k-fp16", -} - - - -models: - "phi3:3.8b-mini-instruct-4k-fp16": - alias: - - latest - - 3.8b - - instruct - - mini - template: vllm-chat - service_config: - name: phi3 - traffic: - timeout: 300 - resources: - gpu: 1 - gpu_type: nvidia-tesla-t4 - engine_config: - model_id: microsoft/Phi-3-mini-4k-instruct - max_model_len: 4096 - dtype: half From a81796de369bfdc51d16f364e5d6824add2a7c9d Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 21 May 2024 00:14:57 +0800 Subject: [PATCH 016/125] add mistral --- recipe.yaml | 51 +++++++++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 49 insertions(+), 2 deletions(-) diff --git a/recipe.yaml b/recipe.yaml index c514d4d9..253656a5 100644 --- a/recipe.yaml +++ b/recipe.yaml @@ -56,13 +56,12 @@ timeout: 300 resources: gpu: 1 - gpu_type: nvidia-tesla-t4 + gpu_type: nvidia-rtx-3060 engine_config: model: TheBloke/Llama-2-7B-Chat-AWQ max_model_len: 1024 quantization: awq enforce_eager: true - prompt: head: ~ body: |- @@ -71,3 +70,51 @@ If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. <> {user_prompt} [/INST] +"mistral:7b-instruct-awq-4bit": + alias: [] + project: vllm-chat + service_config: + name: mistral + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-rtx-3060 + engine_config: + model: TheBloke/Mistral-7B-Instruct-v0.1-AWQ + max_model_len: 1024 + quantization: awq + enforce_eager: true + dtype: half + prompt: + head: ~ + body: |- + [INST] + You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. + If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. + {user_prompt} [/INST] +"mistral:7b-instruct-fp16": + alias: + - 7b + - 7b-instruct + - 7b-instruct-v0.1 + project: vllm-chat + service_config: + name: mistral + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-tesla-l4 + engine_config: + model: mistralai/Mistral-7B-Instruct-v0.1 + max_model_len: 1024 + enforce_eager: true + dtype: half + prompt: + head: ~ + body: |- + [INST] + You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. + If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. + {user_prompt} [/INST] From a4d9752d302c551680c522fe2b9cf2507bdef964 Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 21 May 2024 02:14:47 +0800 Subject: [PATCH 017/125] use community chat template --- recipe.yaml | 5 + vllm-chat/bento_constants.py | 1 + vllm-chat/bentofile.yaml | 2 + vllm-chat/chat_templates/.gitignore | 2 + vllm-chat/chat_templates/README.md | 229 ++++++++++++++++++ .../chat_templates/alpaca.jinja | 24 ++ .../chat_templates/amberchat.jinja | 27 +++ .../chat_templates/chatml.jinja | 18 ++ .../chat_templates/chatqa.jinja | 36 +++ .../chat_templates/falcon-instruct.jinja | 22 ++ .../chat_templates/gemma-it.jinja | 31 +++ .../chat_templates/llama-2-chat.jinja | 25 ++ .../chat_templates/llama-3-chat.jinja | 24 ++ .../chat_templates/mistral-instruct.jinja | 26 ++ .../chat_templates/openchat.jinja | 20 ++ .../chat_templates/chat_templates/phi-3.jinja | 17 ++ .../chat_templates/chat_templates/saiga.jinja | 23 ++ .../chat_templates/solar-instruct.jinja | 18 ++ .../chat_templates/vicuna.jinja | 24 ++ .../chat_templates/zephyr.jinja | 17 ++ .../generation_configs/alpaca.json | 6 + .../generation_configs/amberchat.json | 6 + .../generation_configs/chatqa.json | 6 + .../generation_configs/gemma-it.json | 6 + .../generation_configs/llama-2-chat.json | 6 + .../generation_configs/llama-3-chat.json | 6 + .../generation_configs/mistral-instruct.json | 6 + .../generation_configs/openchat.json | 6 + .../generation_configs/orca-2.json | 6 + .../generation_configs/phi-3.json | 6 + .../generation_configs/qwen2-chat.json | 6 + .../generation_configs/saiga.json | 6 + .../generation_configs/solar-instruct.json | 6 + .../generation_configs/vicuna.json | 6 + .../generation_configs/yi-chat.json | 6 + .../generation_configs/zephyr.json | 6 + vllm-chat/requirements.txt | 1 + vllm-chat/service.py | 57 +++++ 38 files changed, 745 insertions(+) create mode 100644 vllm-chat/chat_templates/.gitignore create mode 100644 vllm-chat/chat_templates/README.md create mode 100644 vllm-chat/chat_templates/chat_templates/alpaca.jinja create mode 100644 vllm-chat/chat_templates/chat_templates/amberchat.jinja create mode 100644 vllm-chat/chat_templates/chat_templates/chatml.jinja create mode 100644 vllm-chat/chat_templates/chat_templates/chatqa.jinja create mode 100644 vllm-chat/chat_templates/chat_templates/falcon-instruct.jinja create mode 100644 vllm-chat/chat_templates/chat_templates/gemma-it.jinja create mode 100644 vllm-chat/chat_templates/chat_templates/llama-2-chat.jinja create mode 100644 vllm-chat/chat_templates/chat_templates/llama-3-chat.jinja create mode 100644 vllm-chat/chat_templates/chat_templates/mistral-instruct.jinja create mode 100644 vllm-chat/chat_templates/chat_templates/openchat.jinja create mode 100644 vllm-chat/chat_templates/chat_templates/phi-3.jinja create mode 100644 vllm-chat/chat_templates/chat_templates/saiga.jinja create mode 100644 vllm-chat/chat_templates/chat_templates/solar-instruct.jinja create mode 100644 vllm-chat/chat_templates/chat_templates/vicuna.jinja create mode 100644 vllm-chat/chat_templates/chat_templates/zephyr.jinja create mode 100644 vllm-chat/chat_templates/generation_configs/alpaca.json create mode 100644 vllm-chat/chat_templates/generation_configs/amberchat.json create mode 100644 vllm-chat/chat_templates/generation_configs/chatqa.json create mode 100644 vllm-chat/chat_templates/generation_configs/gemma-it.json create mode 100644 vllm-chat/chat_templates/generation_configs/llama-2-chat.json create mode 100644 vllm-chat/chat_templates/generation_configs/llama-3-chat.json create mode 100644 vllm-chat/chat_templates/generation_configs/mistral-instruct.json create mode 100644 vllm-chat/chat_templates/generation_configs/openchat.json create mode 100644 vllm-chat/chat_templates/generation_configs/orca-2.json create mode 100644 vllm-chat/chat_templates/generation_configs/phi-3.json create mode 100644 vllm-chat/chat_templates/generation_configs/qwen2-chat.json create mode 100644 vllm-chat/chat_templates/generation_configs/saiga.json create mode 100644 vllm-chat/chat_templates/generation_configs/solar-instruct.json create mode 100644 vllm-chat/chat_templates/generation_configs/vicuna.json create mode 100644 vllm-chat/chat_templates/generation_configs/yi-chat.json create mode 100644 vllm-chat/chat_templates/generation_configs/zephyr.json diff --git a/recipe.yaml b/recipe.yaml index 253656a5..f27c6bf2 100644 --- a/recipe.yaml +++ b/recipe.yaml @@ -16,6 +16,7 @@ model: microsoft/Phi-3-mini-4k-instruct max_model_len: 4096 dtype: half + chat_template: phi-3 prompt: head: ~ body: |- @@ -38,6 +39,7 @@ engine_config: model: meta-llama/Llama-2-7b-chat-hf max_model_len: 1024 + chat_template: llama-2-chat prompt: head: ~ body: |- @@ -62,6 +64,7 @@ max_model_len: 1024 quantization: awq enforce_eager: true + chat_template: llama-2-chat prompt: head: ~ body: |- @@ -86,6 +89,7 @@ quantization: awq enforce_eager: true dtype: half + chat_template: mistral-instruct prompt: head: ~ body: |- @@ -111,6 +115,7 @@ max_model_len: 1024 enforce_eager: true dtype: half + chat_template: mistral-instruct prompt: head: ~ body: |- diff --git a/vllm-chat/bento_constants.py b/vllm-chat/bento_constants.py index 2b4b5725..e977fb9b 100644 --- a/vllm-chat/bento_constants.py +++ b/vllm-chat/bento_constants.py @@ -18,6 +18,7 @@ prompt: <|user|> {user_prompt}<|end|> <|assistant|> +chat_template: phi-3 engine_config: model: microsoft/Phi-3-mini-4k-instruct max_model_len: 4096 diff --git a/vllm-chat/bentofile.yaml b/vllm-chat/bentofile.yaml index 1322978a..1ef27b35 100644 --- a/vllm-chat/bentofile.yaml +++ b/vllm-chat/bentofile.yaml @@ -6,6 +6,8 @@ include: - "*.py" - "config.yaml" - "bentovllm_openai/*.py" +- "chat_templates/chat_templates/*.jinja" +- "chat_templates/generation_configs/*.json" python: requirements_txt: "./requirements.txt" lock_packages: false diff --git a/vllm-chat/chat_templates/.gitignore b/vllm-chat/chat_templates/.gitignore new file mode 100644 index 00000000..5b4f46f6 --- /dev/null +++ b/vllm-chat/chat_templates/.gitignore @@ -0,0 +1,2 @@ +test.py +__pycache__/ \ No newline at end of file diff --git a/vllm-chat/chat_templates/README.md b/vllm-chat/chat_templates/README.md new file mode 100644 index 00000000..fda02f98 --- /dev/null +++ b/vllm-chat/chat_templates/README.md @@ -0,0 +1,229 @@ +# chat_templates + +This is a repository that includes proper chat templates (or input formats) for large language models (LLMs), to support `transformers`'s `chat_template` [feature](https://huggingface.co/docs/transformers/chat_templating). + +We know that different models are trained with different input formats, especially for those instruction-tuned or chat models. This is especially noted in `transformers`'s new `chat_template` feature. However, I found that popular models (e.g., `vicuna`, `falcon`) on HuggingFace do not include this parameter in their `tokenizer_config.json` files, which may make it troublesome to properly run these models. Also, the `chat_template` feature requires to implement a Jinja template, which may be not intuitive to be directly done in the json files. + +So I collect proper chat templates of several popular models from official reference or implementations, which are put under `chat_templates`. If you are interested to include more chat templates, feel free to open a pull request. + +If you find this repo useful, please kindly cite it: +```tex +@misc{zheng-2024-chat-templates, + author = {Zheng, Chujie}, + title = {Chat Templates for HuggingFace Large Language Models}, + year = {2024}, + howpublished = {\url{https://github.com/chujiezheng/chat_templates}} +} +``` + +## Updates + +* **[05/2024]** Added support for Nvidia's **ChatQA** models +* **[04/2024]** Added support for Microsoft's **Phi-3** models +* **[04/2024]** Added support for Meta's **Llama-3** models +* **[02/2024]** Added support for Google's **Gemma** models +* **[02/2024]** Added usage explanation for **generation_configs** +* **[01/2024]** Added support for Alibaba's **Qwen2** models + +## What are Contained in This Repo? + +- [`chat_templates`](/chat_templates/) contains the jinja files of collected chat templates, which can be directly replaced in the Huggingface tokenizers. + +- [`generation_configs`](/generation_configs/) contains the corresponding json configs used for controlling the ending of response generations. Specially, **the `stop_token_ids` should be directly passed into the `generate` method by the `eos_token_id` argument.** + +## Supported Models + +| Model (Family) | Template File | Reference | Comment | +|-----------------------------------------------|--------------------------|-------------------------------------------------------------------------------------------------------------------------------------------| ------------------------------ | +| `llama-3-chat` **New** | `llama-3-chat.jinja` | [link](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct/blob/main/tokenizer_config.json#L2053) | Official template
`Meta-Llama-3-8B/70B-Instruct` | +| `phi-3` **New** | `phi-3.jinja` | [link](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct/blob/main/tokenizer_config.json#L338) | Official template
`Phi-3-mini-4k/128k-instruct` | +| `qwen2-chat` **New** | `chatml.jinja` | [link](https://huggingface.co/Qwen/Qwen1.5-72B-Chat/blob/main/tokenizer_config.json#L31) | ChatML format
`Qwen1.5-0.4B/1.8B/4B/7B/14B/72B-Chat` | +| `gemma-it` **New** | `gemma-it.jinja` | [link](https://huggingface.co/google/gemma-7b-it/blob/main/tokenizer_config.json#L1507) | `gemma-2b/7b-it`
**System message allowed** | +| `chatqa` **New** | `chatqa.jinja` | [link](https://huggingface.co/nvidia/Llama3-ChatQA-1.5-8B#when-context-is-available) | `Llama3-ChatQA-1.5-8B/70B`
**Context message allowed** | +| `llama-2-chat` | `llama-2-chat.jinja` | [link](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf/blob/main/tokenizer_config.json#L12) | Official template
`Llama-2-7b/13b/70b-chat-hf` | +| `mistral-instruct` | `mistral-instruct.jinja` | [link](https://docs.mistral.ai/usage/guardrailing) | `Mistral-7B-Instruct-v0.1/0.2`
**System message allowed** | +| `openchat` | `openchat.jinja` | [link](https://huggingface.co/openchat/openchat_3.5/blob/main/tokenizer_config.json#L51) | `openchat-3.5` | +| `zephyr` | `zephyr.jinja` | [link](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta/blob/main/tokenizer_config.json#L34) | `zephyr-7b-alpha/beta` | +| `yi-chat` | `chatml.jinja` | [link](https://huggingface.co/01-ai/Yi-6B-Chat/blob/main/tokenizer_config.json#L60) | ChatML format
`Yi-6B/34B-Chat` | +| `orca-2` | `chatml.jinja` | [link](https://huggingface.co/microsoft/Orca-2-7b) | ChatML format
`Orca-2-7b/13b` | +| `vicuna` | `vicuna.jinja` | [link](https://github.com/lm-sys/FastChat/blob/main/docs/vicuna_weights_version.md#prompt-template) | `vicuna-7b/13b-v1.5` | +| `falcon-instruct` | `falcon-instruct.jinja` | [link](https://github.com/lm-sys/FastChat/blob/d578599c69d060e6d40943f1b5b72af98956092a/fastchat/conversation.py#L675) | `falcon-7b/40b-instruct` | +| `starling-lm` | `openchat.jinja` | [link](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha/blob/main/tokenizer_config.json#L49) | `Starling-LM-7B-alpha/beta` | +| `solar-instruct` | `solar-instruct.jinja` | [link](https://huggingface.co/upstage/SOLAR-10.7B-Instruct-v1.0/blob/main/tokenizer_config.json#L31) | `SOLAR-10.7B-Instruct-v1.0` | +| `alpaca` | `alpaca.jinja` | [link](https://github.com/tatsu-lab/stanford_alpaca) | `alpaca`-style models, like `Platypus2-13B` | +| `amberchat` | `amberchat.jinja` | [link](https://huggingface.co/LLM360/AmberChat) | `AmberChat`, `AmberSafe` | +| `saiga` | `saiga.jinja` | [link](https://huggingface.co/IlyaGusev/saiga_mistral_7b_lora#saigamistral-7b-russian-mistral-based-chatbot) | `saiga`, a series of Russian models | + +## Examples of Setting `chat_template` + +### Example 1: `llama-3-chat` + +This example may check if the jinja file is correctly implemented. + +```python +from transformers import AutoTokenizer + +toker = AutoTokenizer.from_pretrained("meta-llama/Meta-Llama-3-8B", token="YOUR_OWN_TOKEN") +messages = [ + {'role': 'system', 'content': 'This is a system prompt.'}, + {'role': 'user', 'content': 'This is the first user input.'}, + {'role': 'assistant', 'content': 'This is the first assistant response.'}, + {'role': 'user', 'content': 'This is the second user input.'}, +] +print('###### Default (yet Correct) Chat Template ######') +print(toker.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)) +print('###### Corrected Chat Template ######') +chat_template = open('./chat_templates/llama-3-chat.jinja').read() +chat_template = chat_template.replace(' ', '').replace('\n', '') +toker.chat_template = chat_template +print(toker.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)) +``` + +Expected output: + +``` +###### Default (yet Correct) Chat Template ###### +<|begin_of_text|><|start_header_id|>system<|end_header_id|> + +This is a system prompt.<|eot_id|><|start_header_id|>user<|end_header_id|> + +This is the first user input.<|eot_id|><|start_header_id|>assistant<|end_header_id|> + +This is the first assistant response.<|eot_id|><|start_header_id|>user<|end_header_id|> + +This is the second user input.<|eot_id|><|start_header_id|>assistant<|end_header_id|> + + +###### Corrected Chat Template ###### +<|begin_of_text|><|start_header_id|>system<|end_header_id|> + +This is a system prompt.<|eot_id|><|start_header_id|>user<|end_header_id|> + +This is the first user input.<|eot_id|><|start_header_id|>assistant<|end_header_id|> + +This is the first assistant response.<|eot_id|><|start_header_id|>user<|end_header_id|> + +This is the second user input.<|eot_id|><|start_header_id|>assistant<|end_header_id|> +``` + +### Example 2: `llama-2-chat` + +This example may check if the jinja file is correctly implemented. + +```python +from transformers import AutoTokenizer + +toker = AutoTokenizer.from_pretrained("meta-llama/Llama-2-7b-chat-hf", token="YOUR_OWN_TOKEN") +messages = [ + {'role': 'system', 'content': 'This is a system prompt.'}, + {'role': 'user', 'content': 'This is the first user input.'}, + {'role': 'assistant', 'content': 'This is the first assistant response.'}, + {'role': 'user', 'content': 'This is the second user input.'}, +] +print('###### Default (yet Correct) Chat Template ######') +print(toker.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)) +print('###### Corrected Chat Template ######') +chat_template = open('./chat_templates/llama-2-chat.jinja').read() +chat_template = chat_template.replace(' ', '').replace('\n', '') +toker.chat_template = chat_template +print(toker.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)) +``` + +Expected output: + +``` +###### Default (yet Correct) Chat Template ###### +[INST] <> +This is a system prompt. +<> + +This is the first user input. [/INST] This is the first assistant response. [INST] This is the second user input. [/INST] +###### Corrected Chat Template ###### +[INST] <> +This is a system prompt. +<> + +This is the first user input. [/INST] This is the first assistant response. [INST] This is the second user input. [/INST] +``` + +### Example 3: `mistral-instruct` + +For `mistral-instruct` (also `gemma-it`), it does not natively support the `system` message, so passing the `system` message would raise error. + +```python +from transformers import AutoTokenizer + +toker = AutoTokenizer.from_pretrained("lmsys/vicuna-7b-v1.5") +messages = [ + {'role': 'system', 'content': 'This is a system prompt.'}, + {'role': 'user', 'content': 'This is the first user input.'}, + {'role': 'assistant', 'content': 'This is the first assistant response.'}, + {'role': 'user', 'content': 'This is the second user input.'}, +] +print('###### Default (but Improper) Chat Template ######') +# raising error +#print(toker.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)) +print('###### Corrected Chat Template ######') +chat_template = open('./chat_templates/mistral-instruct.jinja').read() +chat_template = chat_template.replace(' ', '').replace('\n', '') +toker.chat_template = chat_template +print(toker.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)) +``` + +Expected output: + +``` +###### Default (but Error-Raising) Chat Template ###### +jinja2.exceptions.TemplateError: Conversation roles must alternate user/assistant/user/assistant/... +###### Corrected Chat Template ###### +[INST] This is a system prompt. + +This is the first user input. [/INST] This is the first assistant response. [INST] This is the second user input. [/INST] +``` + +### Example 4: `vicuna` + +NOTE: In [fast-chat](https://github.com/lm-sys/FastChat/blob/d578599c69d060e6d40943f1b5b72af98956092a/fastchat/conversation.py#L287C3-L287C3), `vicuna` does not add linebreaks between roles' messages. But I found that adding linebreaks leads to a bit better performance (especially for the v1.5 version). + +Also, I found `vicuna-7/13/33b-v1.3` may not work well when given a system message different from its default one. So I would recommend to use `vicuna-7/13b-v1.5` instead. + +```python +from transformers import AutoTokenizer + +toker = AutoTokenizer.from_pretrained("lmsys/vicuna-7b-v1.5") +messages = [ + {'role': 'system', 'content': 'This is a system prompt.'}, + {'role': 'user', 'content': 'This is the first user input.'}, + {'role': 'assistant', 'content': 'This is the first assistant response.'}, + {'role': 'user', 'content': 'This is the second user input.'}, +] +print('###### Default (but Improper) Chat Template ######') +print(toker.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)) +print('###### Corrected Chat Template ######') +chat_template = open('./chat_templates/vicuna.jinja').read() +chat_template = chat_template.replace(' ', '').replace('\n', '') +toker.chat_template = chat_template +print(toker.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)) +``` + +Expected output: + +``` +###### Default (but Improper) Chat Template ###### +[INST] <> +This is a system prompt. +<> + +This is the first user input. [/INST] This is the first assistant response. [INST] This is the second user input. [/INST] +###### Corrected Chat Template ###### +This is a system prompt. + +USER: This is the first user input. +ASSISTANT: This is the first assistant response. +USER: This is the second user input. +ASSISTANT: +``` + +## Star History + +[![Star History Chart](https://api.star-history.com/svg?repos=chujiezheng/chat_templates&type=Date)](https://star-history.com/#chujiezheng/chat_templates&Date) diff --git a/vllm-chat/chat_templates/chat_templates/alpaca.jinja b/vllm-chat/chat_templates/chat_templates/alpaca.jinja new file mode 100644 index 00000000..def04b3b --- /dev/null +++ b/vllm-chat/chat_templates/chat_templates/alpaca.jinja @@ -0,0 +1,24 @@ +{% if messages[0]['role'] == 'system' %} + {% set loop_messages = messages[1:] %} + {% set system_message = messages[0]['content'].strip() + '\n\n' %} +{% else %} + {% set loop_messages = messages %} + {% set system_message = '' %} +{% endif %} + +{{ bos_token + system_message }} +{% for message in loop_messages %} + {% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %} + {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }} + {% endif %} + + {% if message['role'] == 'user' %} + {{ '### Instruction:\n' + message['content'].strip() + '\n\n' }} + {% elif message['role'] == 'assistant' %} + {{ '### Response:\n' + message['content'].strip() + eos_token + '\n\n' }} + {% endif %} + + {% if loop.last and message['role'] == 'user' and add_generation_prompt %} + {{ '### Instruction:\n' }} + {% endif %} +{% endfor %} \ No newline at end of file diff --git a/vllm-chat/chat_templates/chat_templates/amberchat.jinja b/vllm-chat/chat_templates/chat_templates/amberchat.jinja new file mode 100644 index 00000000..e6522943 --- /dev/null +++ b/vllm-chat/chat_templates/chat_templates/amberchat.jinja @@ -0,0 +1,27 @@ +{% if messages[0]['role'] == 'system' %} + {% set loop_messages = messages[1:] %} + {% set system_message = messages[0]['content'].strip() + '\n' %} +{% else %} + {% set loop_messages = messages %} + {% set system_message = '' %} +{% endif %} + +{% for message in loop_messages %} + {% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %} + {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }} + {% endif %} + + {% if loop.index0 == 0 %} + {{ bos_token + system_message }} + {% endif %} + + {% if message['role'] == 'user' %} + {{ '###Human: ' + message['content'].strip() + '\n' }} + {% elif message['role'] == 'assistant' %} + {{ '###Assistant: ' + message['content'].strip() + '\n' }} + {% endif %} + + {% if loop.last and message['role'] == 'user' and add_generation_prompt %} + {{ '###Assistant:' }} + {% endif %} +{% endfor %} \ No newline at end of file diff --git a/vllm-chat/chat_templates/chat_templates/chatml.jinja b/vllm-chat/chat_templates/chat_templates/chatml.jinja new file mode 100644 index 00000000..eaf45a6f --- /dev/null +++ b/vllm-chat/chat_templates/chat_templates/chatml.jinja @@ -0,0 +1,18 @@ +{% if messages[0]['role'] == 'system' %} + {% set offset = 1 %} +{% else %} + {% set offset = 0 %} +{% endif %} + +{{ bos_token }} +{% for message in messages %} + {% if (message['role'] == 'user') != (loop.index0 % 2 == offset) %} + {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }} + {% endif %} + + {{ '<|im_start|>' + message['role'] + '\n' + message['content'].strip() + '<|im_end|>\n' }} + + {% if loop.last and message['role'] == 'user' and add_generation_prompt %} + {{ '<|im_start|>assistant\n' }} + {% endif %} +{% endfor %} \ No newline at end of file diff --git a/vllm-chat/chat_templates/chat_templates/chatqa.jinja b/vllm-chat/chat_templates/chat_templates/chatqa.jinja new file mode 100644 index 00000000..714e8645 --- /dev/null +++ b/vllm-chat/chat_templates/chat_templates/chatqa.jinja @@ -0,0 +1,36 @@ +{{ bos_token }} +{% if messages[0]['role'] == 'system' %} + {% set loop_messages = messages[1:] %} + {% set system_message = 'System: ' + messages[0]['content'].strip() %} +{% else %} + {% set loop_messages = messages %} + {% set system_message = '' %} +{% endif %} + +{% if messages[0]['role'] == 'context' %} + {% set loop_messages = messages[1:] %} + {% set context_message = '\n\n' + messages[0]['content'].strip() %} +{% else %} + {% set loop_messages = messages %} + {% set context_message = '' %} +{% endif %} + +{% for message in loop_messages %} + {% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %} + {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }} + {% endif %} + + {% if loop.index0 == 0 %} + {{ system_message + context_message }} + {% endif %} + + {% if message['role'] == 'user' %} + {{ '\n\nUser: ' + content.strip() }} + {% elif message['role'] == 'assistant' %} + {{ '\n\nAssistant: ' + content.strip() }} + {% endif %} + + {% if loop.last and message['role'] == 'user' and add_generation_prompt %} + {{ '\n\nAssistant:' }} + {% endif %} +{% endfor %} \ No newline at end of file diff --git a/vllm-chat/chat_templates/chat_templates/falcon-instruct.jinja b/vllm-chat/chat_templates/chat_templates/falcon-instruct.jinja new file mode 100644 index 00000000..70f7cdfe --- /dev/null +++ b/vllm-chat/chat_templates/chat_templates/falcon-instruct.jinja @@ -0,0 +1,22 @@ +{% if messages[0]['role'] == 'system' %} + {% set loop_messages = messages[1:] %} + {% set system_message = messages[0]['content'] %} +{% else %} + {% set loop_messages = messages %} + {% set system_message = '' %} +{% endif %} + +{% for message in loop_messages %} + {% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %} + {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }} + {% endif %} + + {% if loop.index0 == 0 %} + {{ system_message.strip() }} + {% endif %} + {{ '\n\n' + message['role'].title() + ': ' + message['content'].strip().replace('\r\n', '\n').replace('\n\n', '\n') }} + + {% if loop.last and message['role'] == 'user' and add_generation_prompt %} + {{ '\n\nAssistant:' }} + {% endif %} +{% endfor %} \ No newline at end of file diff --git a/vllm-chat/chat_templates/chat_templates/gemma-it.jinja b/vllm-chat/chat_templates/chat_templates/gemma-it.jinja new file mode 100644 index 00000000..c643abc4 --- /dev/null +++ b/vllm-chat/chat_templates/chat_templates/gemma-it.jinja @@ -0,0 +1,31 @@ +{% if messages[0]['role'] == 'system' %} + {% set loop_messages = messages[1:] %} + {% set system_message = messages[0]['content'].strip() + '\n\n' %} +{% else %} + {% set loop_messages = messages %} + {% set system_message = '' %} +{% endif %} + +{% for message in loop_messages %} + {% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %} + {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }} + {% endif %} + + {% if loop.index0 == 0 %} + {% set content = system_message + message['content'] %} + {% else %} + {% set content = message['content'] %} + {% endif %} + + {% if (message['role'] == 'assistant') %} + {% set role = 'model' %} + {% else %} + {% set role = message['role'] %} + {% endif %} + + {{ '' + role + '\n' + content.strip() + '\n' }} + + {% if loop.last and message['role'] == 'user' and add_generation_prompt %} + {{'model\n'}} + {% endif %} +{% endfor %} diff --git a/vllm-chat/chat_templates/chat_templates/llama-2-chat.jinja b/vllm-chat/chat_templates/chat_templates/llama-2-chat.jinja new file mode 100644 index 00000000..2dcc5b4f --- /dev/null +++ b/vllm-chat/chat_templates/chat_templates/llama-2-chat.jinja @@ -0,0 +1,25 @@ +{% if messages[0]['role'] == 'system' %} + {% set loop_messages = messages[1:] %} + {% set system_message = '<>\n' + messages[0]['content'].strip() + '\n<>\n\n' %} +{% else %} + {% set loop_messages = messages %} + {% set system_message = '' %} +{% endif %} + +{% for message in loop_messages %} + {% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %} + {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }} + {% endif %} + + {% if loop.index0 == 0 %} + {% set content = system_message + message['content'] %} + {% else %} + {% set content = message['content'] %} + {% endif %} + + {% if message['role'] == 'user' %} + {{ bos_token + '[INST] ' + content.strip() + ' [/INST]' }} + {% elif message['role'] == 'assistant' %} + {{ ' ' + content.strip() + ' ' + eos_token }} + {% endif %} +{% endfor %} \ No newline at end of file diff --git a/vllm-chat/chat_templates/chat_templates/llama-3-chat.jinja b/vllm-chat/chat_templates/chat_templates/llama-3-chat.jinja new file mode 100644 index 00000000..70d294d4 --- /dev/null +++ b/vllm-chat/chat_templates/chat_templates/llama-3-chat.jinja @@ -0,0 +1,24 @@ +{{ bos_token }} +{% if messages[0]['role'] == 'system' %} + {% set loop_messages = messages[1:] %} + {% set system_message = '<|start_header_id|>' + 'system' + '<|end_header_id|>\n\n' + messages[0]['content'].strip() + '<|eot_id|>' %} +{% else %} + {% set loop_messages = messages %} + {% set system_message = '' %} +{% endif %} + +{% for message in loop_messages %} + {% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %} + {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }} + {% endif %} + + {% if loop.index0 == 0 %} + {{ system_message }} + {% endif %} + + {{ '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n' + message['content'].strip() + '<|eot_id|>' }} + + {% if loop.last and message['role'] == 'user' and add_generation_prompt %} + {{ '<|start_header_id|>' + 'assistant' + '<|end_header_id|>\n\n' }} + {% endif %} +{% endfor %} \ No newline at end of file diff --git a/vllm-chat/chat_templates/chat_templates/mistral-instruct.jinja b/vllm-chat/chat_templates/chat_templates/mistral-instruct.jinja new file mode 100644 index 00000000..7b746b60 --- /dev/null +++ b/vllm-chat/chat_templates/chat_templates/mistral-instruct.jinja @@ -0,0 +1,26 @@ +{% if messages[0]['role'] == 'system' %} + {% set loop_messages = messages[1:] %} + {% set system_message = messages[0]['content'].strip() + '\n\n' %} +{% else %} + {% set loop_messages = messages %} + {% set system_message = '' %} +{% endif %} + +{{ bos_token }} +{% for message in loop_messages %} + {% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %} + {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }} + {% endif %} + + {% if loop.index0 == 0 %} + {% set content = system_message + message['content'] %} + {% else %} + {% set content = message['content'] %} + {% endif %} + + {% if message['role'] == 'user' %} + {{ '[INST] ' + content.strip() + ' [/INST]' }} + {% elif message['role'] == 'assistant' %} + {{ ' ' + content.strip() + eos_token }} + {% endif %} +{% endfor %} \ No newline at end of file diff --git a/vllm-chat/chat_templates/chat_templates/openchat.jinja b/vllm-chat/chat_templates/chat_templates/openchat.jinja new file mode 100644 index 00000000..5004cd2e --- /dev/null +++ b/vllm-chat/chat_templates/chat_templates/openchat.jinja @@ -0,0 +1,20 @@ +{% if messages[0]['role'] == 'system' %} + {% set loop_messages = messages[1:] %} + {% set system_message = messages[0]['content'].strip() + '<|end_of_turn|>' %} +{% else %} + {% set loop_messages = messages %} + {% set system_message = '' %} +{% endif %} + +{{ bos_token + system_message }} +{% for message in loop_messages %} + {% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %} + {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }} + {% endif %} + + {{ 'GPT4 Correct ' + message['role'].title() + ': ' + message['content'] + '<|end_of_turn|>' }} + + {% if loop.last and message['role'] == 'user' and add_generation_prompt %} + {{ 'GPT4 Correct Assistant:' }} + {% endif %} +{% endfor %} \ No newline at end of file diff --git a/vllm-chat/chat_templates/chat_templates/phi-3.jinja b/vllm-chat/chat_templates/chat_templates/phi-3.jinja new file mode 100644 index 00000000..842b60ea --- /dev/null +++ b/vllm-chat/chat_templates/chat_templates/phi-3.jinja @@ -0,0 +1,17 @@ +{% if messages[0]['role'] == 'system' %} + {% set offset = 1 %} +{% else %} + {% set offset = 0 %} +{% endif %} + +{% for message in messages %} + {% if (message['role'] == 'user') != (loop.index0 % 2 == offset) %} + {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }} + {% endif %} + + {{ '<|' + message['role'] + '|>\n' + message['content'].strip() + '<|end|>' + '\n' }} + + {% if loop.last and message['role'] == 'user' and add_generation_prompt %} + {{ '<|assistant|>\n' }} + {% endif %} +{% endfor %} \ No newline at end of file diff --git a/vllm-chat/chat_templates/chat_templates/saiga.jinja b/vllm-chat/chat_templates/chat_templates/saiga.jinja new file mode 100644 index 00000000..79367646 --- /dev/null +++ b/vllm-chat/chat_templates/chat_templates/saiga.jinja @@ -0,0 +1,23 @@ +{% if messages[0]['role'] == 'system' %} + {% set loop_messages = messages[1:] %} + {% set system_message = bos_token + 'system' + '\n' + messages[0]['content'].strip() + eos_token %} +{% else %} + {% set loop_messages = messages %} + {% set system_message = '' %} +{% endif %} + +{% for message in loop_messages %} + {% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %} + {{ raise_exception('Conversation roles must alternate user/bot/user/bot/...') }} + {% endif %} + + {% if loop.index0 == 0 %} + {{ system_message }} + {% endif %} + + {{ bos_token + message['role'] + '\n' + message['content'].strip() + eos_token }} + + {% if loop.last and message['role'] == 'user' and add_generation_prompt %} + {{ bos_token + 'bot' }} + {% endif %} +{% endfor %} diff --git a/vllm-chat/chat_templates/chat_templates/solar-instruct.jinja b/vllm-chat/chat_templates/chat_templates/solar-instruct.jinja new file mode 100644 index 00000000..2cf7fef7 --- /dev/null +++ b/vllm-chat/chat_templates/chat_templates/solar-instruct.jinja @@ -0,0 +1,18 @@ +{% if messages[0]['role'] == 'system' %} + {% set offset = 1 %} +{% else %} + {% set offset = 0 %} +{% endif %} + +{{ bos_token }} +{% for message in messages %} + {% if (message['role'] == 'user') != (loop.index0 % 2 == offset) %} + {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }} + {% endif %} + + {{ '### ' + message['role'].title() + ':\n' + message['content'].strip() + '\n\n' }} + + {% if loop.last and message['role'] == 'user' and add_generation_prompt %} + {{ '### Assistant:\n' }} + {% endif %} +{% endfor %} \ No newline at end of file diff --git a/vllm-chat/chat_templates/chat_templates/vicuna.jinja b/vllm-chat/chat_templates/chat_templates/vicuna.jinja new file mode 100644 index 00000000..bbed85a4 --- /dev/null +++ b/vllm-chat/chat_templates/chat_templates/vicuna.jinja @@ -0,0 +1,24 @@ +{% if messages[0]['role'] == 'system' %} + {% set loop_messages = messages[1:] %} + {% set system_message = messages[0]['content'].strip() + '\n\n' %} +{% else %} + {% set loop_messages = messages %} + {% set system_message = '' %} +{% endif %} + +{{ bos_token + system_message }} +{% for message in loop_messages %} + {% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %} + {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }} + {% endif %} + + {% if message['role'] == 'user' %} + {{ 'USER: ' + message['content'].strip() + '\n' }} + {% elif message['role'] == 'assistant' %} + {{ 'ASSISTANT: ' + message['content'].strip() + eos_token + '\n' }} + {% endif %} + + {% if loop.last and message['role'] == 'user' and add_generation_prompt %} + {{ 'ASSISTANT:' }} + {% endif %} +{% endfor %} \ No newline at end of file diff --git a/vllm-chat/chat_templates/chat_templates/zephyr.jinja b/vllm-chat/chat_templates/chat_templates/zephyr.jinja new file mode 100644 index 00000000..dc70df86 --- /dev/null +++ b/vllm-chat/chat_templates/chat_templates/zephyr.jinja @@ -0,0 +1,17 @@ +{% if messages[0]['role'] == 'system' %} + {% set offset = 1 %} +{% else %} + {% set offset = 0 %} +{% endif %} + +{% for message in messages %} + {% if (message['role'] == 'user') != (loop.index0 % 2 == offset) %} + {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }} + {% endif %} + + {{ '<|' + message['role'] + '|>\n' + message['content'].strip() + eos_token + '\n' }} + + {% if loop.last and message['role'] == 'user' and add_generation_prompt %} + {{ '<|assistant|>\n' }} + {% endif %} +{% endfor %} \ No newline at end of file diff --git a/vllm-chat/chat_templates/generation_configs/alpaca.json b/vllm-chat/chat_templates/generation_configs/alpaca.json new file mode 100644 index 00000000..df0c567e --- /dev/null +++ b/vllm-chat/chat_templates/generation_configs/alpaca.json @@ -0,0 +1,6 @@ +{ + "chat_template": "chat_templates/alpaca.jinja", + "stop_str": null, + "stop_token_ids": [2], + "system_prompt": "Below is an instruction that describes a task. Write a response that appropriately completes the request." +} \ No newline at end of file diff --git a/vllm-chat/chat_templates/generation_configs/amberchat.json b/vllm-chat/chat_templates/generation_configs/amberchat.json new file mode 100644 index 00000000..e18dca79 --- /dev/null +++ b/vllm-chat/chat_templates/generation_configs/amberchat.json @@ -0,0 +1,6 @@ +{ + "chat_template": "chat_templates/amberchat.jinja", + "stop_str": "\n###Human", + "stop_token_ids": [2], + "system_prompt": null +} \ No newline at end of file diff --git a/vllm-chat/chat_templates/generation_configs/chatqa.json b/vllm-chat/chat_templates/generation_configs/chatqa.json new file mode 100644 index 00000000..597e6c5a --- /dev/null +++ b/vllm-chat/chat_templates/generation_configs/chatqa.json @@ -0,0 +1,6 @@ +{ + "chat_template": "chat_templates/chatqa.jinja", + "stop_str": null, + "stop_token_ids": [128001, 128009], + "system_prompt": "This is a chat between a user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions based on the context. The assistant should also indicate when the answer cannot be found in the context." +} \ No newline at end of file diff --git a/vllm-chat/chat_templates/generation_configs/gemma-it.json b/vllm-chat/chat_templates/generation_configs/gemma-it.json new file mode 100644 index 00000000..3deb31c7 --- /dev/null +++ b/vllm-chat/chat_templates/generation_configs/gemma-it.json @@ -0,0 +1,6 @@ +{ + "chat_template": "chat_templates/gemma-it.jinja", + "stop_str": null, + "stop_token_ids": [1, 107], + "system_prompt": null +} \ No newline at end of file diff --git a/vllm-chat/chat_templates/generation_configs/llama-2-chat.json b/vllm-chat/chat_templates/generation_configs/llama-2-chat.json new file mode 100644 index 00000000..47aaeb3b --- /dev/null +++ b/vllm-chat/chat_templates/generation_configs/llama-2-chat.json @@ -0,0 +1,6 @@ +{ + "chat_template": "chat_templates/llama-2-chat.jinja", + "stop_str": null, + "stop_token_ids": [2], + "system_prompt": "You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.\n\nIf a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information." +} \ No newline at end of file diff --git a/vllm-chat/chat_templates/generation_configs/llama-3-chat.json b/vllm-chat/chat_templates/generation_configs/llama-3-chat.json new file mode 100644 index 00000000..67362753 --- /dev/null +++ b/vllm-chat/chat_templates/generation_configs/llama-3-chat.json @@ -0,0 +1,6 @@ +{ + "chat_template": "chat_templates/llama-3-chat.jinja", + "stop_str": null, + "stop_token_ids": [128001, 128009], + "system_prompt": null +} \ No newline at end of file diff --git a/vllm-chat/chat_templates/generation_configs/mistral-instruct.json b/vllm-chat/chat_templates/generation_configs/mistral-instruct.json new file mode 100644 index 00000000..c3f12e59 --- /dev/null +++ b/vllm-chat/chat_templates/generation_configs/mistral-instruct.json @@ -0,0 +1,6 @@ +{ + "chat_template": "chat_templates/mistral-instruct.jinja", + "stop_str": null, + "stop_token_ids": [2], + "system_prompt": "Always assist with care, respect, and truth. Respond with utmost utility yet securely. Avoid harmful, unethical, prejudiced, or negative content. Ensure replies promote fairness and positivity." +} \ No newline at end of file diff --git a/vllm-chat/chat_templates/generation_configs/openchat.json b/vllm-chat/chat_templates/generation_configs/openchat.json new file mode 100644 index 00000000..8e658426 --- /dev/null +++ b/vllm-chat/chat_templates/generation_configs/openchat.json @@ -0,0 +1,6 @@ +{ + "chat_template": "chat_templates/openchat.jinja", + "stop_str": null, + "stop_token_ids": [2, 32000], + "system_prompt": null +} \ No newline at end of file diff --git a/vllm-chat/chat_templates/generation_configs/orca-2.json b/vllm-chat/chat_templates/generation_configs/orca-2.json new file mode 100644 index 00000000..1e854baa --- /dev/null +++ b/vllm-chat/chat_templates/generation_configs/orca-2.json @@ -0,0 +1,6 @@ +{ + "chat_template": "chat_templates/chatml.jinja", + "stop_str": null, + "stop_token_ids": [2, 32002], + "system_prompt": "You are Orca, an AI language model created by Microsoft. You are a cautious assistant. You carefully follow instructions. You are helpful and harmless and you follow ethical guidelines and promote positive behavior." +} \ No newline at end of file diff --git a/vllm-chat/chat_templates/generation_configs/phi-3.json b/vllm-chat/chat_templates/generation_configs/phi-3.json new file mode 100644 index 00000000..221e42b6 --- /dev/null +++ b/vllm-chat/chat_templates/generation_configs/phi-3.json @@ -0,0 +1,6 @@ +{ + "chat_template": "chat_templates/phi-3.jinja", + "stop_str": null, + "stop_token_ids": [2, 32000, 32007], + "system_prompt": null +} \ No newline at end of file diff --git a/vllm-chat/chat_templates/generation_configs/qwen2-chat.json b/vllm-chat/chat_templates/generation_configs/qwen2-chat.json new file mode 100644 index 00000000..2c2f7708 --- /dev/null +++ b/vllm-chat/chat_templates/generation_configs/qwen2-chat.json @@ -0,0 +1,6 @@ +{ + "chat_template": "chat_templates/openchat.jinja", + "stop_str": null, + "stop_token_ids": [151643, 151645], + "system_prompt": null +} \ No newline at end of file diff --git a/vllm-chat/chat_templates/generation_configs/saiga.json b/vllm-chat/chat_templates/generation_configs/saiga.json new file mode 100644 index 00000000..839f5b96 --- /dev/null +++ b/vllm-chat/chat_templates/generation_configs/saiga.json @@ -0,0 +1,6 @@ +{ + "chat_template": "chat_templates/saiga.jinja", + "stop_str": null, + "stop_token_ids": [2], + "system_prompt": "Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им." +} diff --git a/vllm-chat/chat_templates/generation_configs/solar-instruct.json b/vllm-chat/chat_templates/generation_configs/solar-instruct.json new file mode 100644 index 00000000..63acfff6 --- /dev/null +++ b/vllm-chat/chat_templates/generation_configs/solar-instruct.json @@ -0,0 +1,6 @@ +{ + "chat_template": "chat_templates/solar-instruct.jinja", + "stop_str": null, + "stop_token_ids": [2], + "system_prompt": null +} \ No newline at end of file diff --git a/vllm-chat/chat_templates/generation_configs/vicuna.json b/vllm-chat/chat_templates/generation_configs/vicuna.json new file mode 100644 index 00000000..c55d91c9 --- /dev/null +++ b/vllm-chat/chat_templates/generation_configs/vicuna.json @@ -0,0 +1,6 @@ +{ + "chat_template": "chat_templates/vicuna.jinja", + "stop_str": null, + "stop_token_ids": [2], + "system_prompt": "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions." +} \ No newline at end of file diff --git a/vllm-chat/chat_templates/generation_configs/yi-chat.json b/vllm-chat/chat_templates/generation_configs/yi-chat.json new file mode 100644 index 00000000..f53b41bb --- /dev/null +++ b/vllm-chat/chat_templates/generation_configs/yi-chat.json @@ -0,0 +1,6 @@ +{ + "chat_template": "chat_templates/chatml.jinja", + "stop_str": null, + "stop_token_ids": [2, 7], + "system_prompt": null +} \ No newline at end of file diff --git a/vllm-chat/chat_templates/generation_configs/zephyr.json b/vllm-chat/chat_templates/generation_configs/zephyr.json new file mode 100644 index 00000000..dd95ac13 --- /dev/null +++ b/vllm-chat/chat_templates/generation_configs/zephyr.json @@ -0,0 +1,6 @@ +{ + "chat_template": "chat_templates/zephyr.jinja", + "stop_str": null, + "stop_token_ids": [2], + "system_prompt": null +} \ No newline at end of file diff --git a/vllm-chat/requirements.txt b/vllm-chat/requirements.txt index d7e29143..6331d91e 100644 --- a/vllm-chat/requirements.txt +++ b/vllm-chat/requirements.txt @@ -2,3 +2,4 @@ torch==2.1.2 vllm==0.4.0.post1 transformers==4.39.3 pyyaml +jinja2 diff --git a/vllm-chat/service.py b/vllm-chat/service.py index f1bf109f..95caa3e9 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -1,4 +1,6 @@ import uuid +import json +import os from typing import AsyncGenerator from typing_extensions import Annotated @@ -13,9 +15,18 @@ CONSTANTS = yaml.safe_load(CONSTANT_YAML) ENGINE_CONFIG = CONSTANTS["engine_config"] PROMPT_TEMPLATE = CONSTANTS["prompt"] +CHAT_TEMPLATE = CONSTANTS["chat_template"] SERVICE_CONFIG = CONSTANTS["service_config"] +CHAT_TEMPLATE_PATH = os.path.join( + os.path.dirname(__file__), "chat_templates", "chat_templates" +) +GEN_CONFIG_PATH = os.path.join( + os.path.dirname(__file__), "chat_templates", "generation_configs" +) + + @openai_endpoints(served_model_names=[ENGINE_CONFIG["model"]]) @bentoml.service(**SERVICE_CONFIG) class VLLM: @@ -48,3 +59,49 @@ class VLLM: text = request_output.outputs[0].text yield text[cursor:] cursor = len(text) + + @bentoml.api + async def chat( + self, + messages: list[dict[str, str]], + max_tokens: Annotated[ + int, + Ge(128), + Le(ENGINE_CONFIG["max_model_len"]), + ] = ENGINE_CONFIG["max_model_len"], + ) -> AsyncGenerator[str, None]: + """ + light-weight chat API that takes in a list of messages and returns a response + """ + + from vllm import SamplingParams + import jinja2 + + JINJA_ENV = jinja2.Environment( + loader=jinja2.FileSystemLoader(CHAT_TEMPLATE_PATH) + ) + + with open(os.path.join(GEN_CONFIG_PATH, f"{CHAT_TEMPLATE}.json")) as f: + gen_config = json.load(f) + chat_template_file = gen_config["chat_template"].split("/")[-1] + template = JINJA_ENV.get_template(chat_template_file) + + SAMPLING_PARAM = SamplingParams( + max_tokens=max_tokens, + stop_token_ids=gen_config["stop_token_ids"], + stop=( + [gen_config["stop_str"]] if gen_config["stop_str"] is not None else [] + ), + ) + if gen_config["system_prompt"] and messages[0].get("role") != "system": + messages = [ + dict(role="system", content=gen_config["system_prompt"]) + ] + messages + prompt = template.render(messages=messages, add_generation_prompt=True) + stream = await self.engine.add_request(uuid.uuid4().hex, prompt, SAMPLING_PARAM) + + cursor = 0 + async for request_output in stream: + text = request_output.outputs[0].text + yield text[cursor:] + cursor = len(text) From 72068db844d8ffea49285505ef32736e56a77bbb Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 21 May 2024 02:18:59 +0800 Subject: [PATCH 018/125] clean old prompts --- recipe.yaml | 36 ------------------------------------ vllm-chat/bento_constants.py | 6 ------ vllm-chat/service.py | 8 ++++---- 3 files changed, 4 insertions(+), 46 deletions(-) diff --git a/recipe.yaml b/recipe.yaml index f27c6bf2..687c83a3 100644 --- a/recipe.yaml +++ b/recipe.yaml @@ -17,12 +17,6 @@ max_model_len: 4096 dtype: half chat_template: phi-3 - prompt: - head: ~ - body: |- - <|user|> - {user_prompt}<|end|> - <|assistant|> "llama2:7b-chat-fp16": alias: - latest @@ -40,14 +34,6 @@ model: meta-llama/Llama-2-7b-chat-hf max_model_len: 1024 chat_template: llama-2-chat - prompt: - head: ~ - body: |- - [INST] <> - You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. - If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. - <> - {user_prompt} [/INST] "llama2:7b-chat-awq-4bit": alias: - 7b-chat-4bit @@ -65,14 +51,6 @@ quantization: awq enforce_eager: true chat_template: llama-2-chat - prompt: - head: ~ - body: |- - [INST] <> - You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. - If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. - <> - {user_prompt} [/INST] "mistral:7b-instruct-awq-4bit": alias: [] project: vllm-chat @@ -90,13 +68,6 @@ enforce_eager: true dtype: half chat_template: mistral-instruct - prompt: - head: ~ - body: |- - [INST] - You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. - If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. - {user_prompt} [/INST] "mistral:7b-instruct-fp16": alias: - 7b @@ -116,10 +87,3 @@ enforce_eager: true dtype: half chat_template: mistral-instruct - prompt: - head: ~ - body: |- - [INST] - You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. - If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information. - {user_prompt} [/INST] diff --git a/vllm-chat/bento_constants.py b/vllm-chat/bento_constants.py index e977fb9b..684ecce6 100644 --- a/vllm-chat/bento_constants.py +++ b/vllm-chat/bento_constants.py @@ -12,12 +12,6 @@ service_config: resources: gpu: 1 gpu_type: nvidia-tesla-t4 -prompt: - head: ~ - body: |- - <|user|> - {user_prompt}<|end|> - <|assistant|> chat_template: phi-3 engine_config: model: microsoft/Phi-3-mini-4k-instruct diff --git a/vllm-chat/service.py b/vllm-chat/service.py index 95caa3e9..85495769 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -14,7 +14,6 @@ from bento_constants import CONSTANT_YAML CONSTANTS = yaml.safe_load(CONSTANT_YAML) ENGINE_CONFIG = CONSTANTS["engine_config"] -PROMPT_TEMPLATE = CONSTANTS["prompt"] CHAT_TEMPLATE = CONSTANTS["chat_template"] SERVICE_CONFIG = CONSTANTS["service_config"] @@ -45,12 +44,13 @@ class VLLM: Ge(128), Le(ENGINE_CONFIG["max_model_len"]), ] = ENGINE_CONFIG["max_model_len"], + stop: list[str] = [], ) -> AsyncGenerator[str, None]: from vllm import SamplingParams - SAMPLING_PARAM = SamplingParams(max_tokens=max_tokens) - prompt = (PROMPT_TEMPLATE["head"] or "") + PROMPT_TEMPLATE["body"].format( - user_prompt=prompt + SAMPLING_PARAM = SamplingParams( + max_tokens=max_tokens, + stop=stop, ) stream = await self.engine.add_request(uuid.uuid4().hex, prompt, SAMPLING_PARAM) From 2dcce43165f19ad0488ee3a204eb2d51f02ef21e Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 21 May 2024 02:30:22 +0800 Subject: [PATCH 019/125] trailing leading whitespace --- vllm-chat/service.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/vllm-chat/service.py b/vllm-chat/service.py index 85495769..144544bc 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -101,7 +101,13 @@ class VLLM: stream = await self.engine.add_request(uuid.uuid4().hex, prompt, SAMPLING_PARAM) cursor = 0 + strip_flag = True async for request_output in stream: text = request_output.outputs[0].text - yield text[cursor:] + assistant_message = text[cursor:] + if not strip_flag: # strip the leading whitespace + yield assistant_message + elif assistant_message.strip(): + strip_flag = False + yield assistant_message.lstrip() cursor = len(text) From 1860d9880e8ce215f641d17f9ffb546fadf64812 Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 21 May 2024 02:38:26 +0800 Subject: [PATCH 020/125] try fix chat template for openai api --- vllm-chat/service.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/vllm-chat/service.py b/vllm-chat/service.py index 144544bc..4e7c15dd 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -26,7 +26,10 @@ GEN_CONFIG_PATH = os.path.join( ) -@openai_endpoints(served_model_names=[ENGINE_CONFIG["model"]]) +@openai_endpoints( + served_model_names=[ENGINE_CONFIG["model"]], + chat_template_model_id=ENGINE_CONFIG["model"], +) @bentoml.service(**SERVICE_CONFIG) class VLLM: def __init__(self) -> None: From b0f53e2007faf14d6bfc5a3bd34e97fcf1baa3ae Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 21 May 2024 03:11:49 +0800 Subject: [PATCH 021/125] opt --- vllm-chat/service.py | 62 +++++++++++++++++++++++++++++--------------- 1 file changed, 41 insertions(+), 21 deletions(-) diff --git a/vllm-chat/service.py b/vllm-chat/service.py index 4e7c15dd..8f575109 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -3,6 +3,7 @@ import json import os from typing import AsyncGenerator from typing_extensions import Annotated +import functools import bentoml from annotated_types import Ge, Le @@ -18,12 +19,22 @@ CHAT_TEMPLATE = CONSTANTS["chat_template"] SERVICE_CONFIG = CONSTANTS["service_config"] -CHAT_TEMPLATE_PATH = os.path.join( - os.path.dirname(__file__), "chat_templates", "chat_templates" -) -GEN_CONFIG_PATH = os.path.join( - os.path.dirname(__file__), "chat_templates", "generation_configs" -) +@functools.lru_cache(maxsize=1) +def _get_gen_config(): + import jinja2 + + chat_template_path = os.path.join( + os.path.dirname(__file__), "chat_templates", "chat_templates" + ) + config_path = os.path.join( + os.path.dirname(__file__), "chat_templates", "generation_configs" + ) + jinja_env = jinja2.Environment(loader=jinja2.FileSystemLoader(chat_template_path)) + with open(os.path.join(config_path, f"{CHAT_TEMPLATE}.json")) as f: + gen_config = json.load(f) + chat_template_file = gen_config["chat_template"].split("/")[-1] + gen_config["template"] = jinja_env.get_template(chat_template_file) + return gen_config @openai_endpoints( @@ -48,12 +59,14 @@ class VLLM: Le(ENGINE_CONFIG["max_model_len"]), ] = ENGINE_CONFIG["max_model_len"], stop: list[str] = [], + **kwargs, ) -> AsyncGenerator[str, None]: from vllm import SamplingParams SAMPLING_PARAM = SamplingParams( max_tokens=max_tokens, stop=stop, + **kwargs, ) stream = await self.engine.add_request(uuid.uuid4().hex, prompt, SAMPLING_PARAM) @@ -66,41 +79,48 @@ class VLLM: @bentoml.api async def chat( self, - messages: list[dict[str, str]], + messages: list[dict[str, str]] = [ + {"role": "user", "content": "What is the meaning of life?"} + ], + model: str = "", max_tokens: Annotated[ int, Ge(128), Le(ENGINE_CONFIG["max_model_len"]), ] = ENGINE_CONFIG["max_model_len"], + stop: list[str] | str | None = None, + stop_token_ids: list[int] | None = None, ) -> AsyncGenerator[str, None]: """ light-weight chat API that takes in a list of messages and returns a response """ - from vllm import SamplingParams - import jinja2 - JINJA_ENV = jinja2.Environment( - loader=jinja2.FileSystemLoader(CHAT_TEMPLATE_PATH) - ) + gen_config = _get_gen_config() - with open(os.path.join(GEN_CONFIG_PATH, f"{CHAT_TEMPLATE}.json")) as f: - gen_config = json.load(f) - chat_template_file = gen_config["chat_template"].split("/")[-1] - template = JINJA_ENV.get_template(chat_template_file) + if stop_token_ids is None: + stop_token_ids = gen_config["stop_token_ids"] + if stop == "" or stop is None: + if gen_config["stop_str"] is None: + stop = [] + else: + stop = [gen_config["stop_str"]] SAMPLING_PARAM = SamplingParams( max_tokens=max_tokens, - stop_token_ids=gen_config["stop_token_ids"], - stop=( - [gen_config["stop_str"]] if gen_config["stop_str"] is not None else [] - ), + stop_token_ids=stop_token_ids, + stop=stop, ) if gen_config["system_prompt"] and messages[0].get("role") != "system": messages = [ dict(role="system", content=gen_config["system_prompt"]) ] + messages - prompt = template.render(messages=messages, add_generation_prompt=True) + + prompt = gen_config["template"].render( + messages=messages, + add_generation_prompt=True, + ) + stream = await self.engine.add_request(uuid.uuid4().hex, prompt, SAMPLING_PARAM) cursor = 0 From e7e84ad66af631bf6b4f9043be57dbfc43c7f1f3 Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 21 May 2024 04:26:49 +0800 Subject: [PATCH 022/125] fix template --- vllm-chat/service.py | 16 ++++++++++------ 1 file changed, 10 insertions(+), 6 deletions(-) diff --git a/vllm-chat/service.py b/vllm-chat/service.py index 8f575109..5a84e0e2 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -21,19 +21,18 @@ SERVICE_CONFIG = CONSTANTS["service_config"] @functools.lru_cache(maxsize=1) def _get_gen_config(): - import jinja2 - chat_template_path = os.path.join( os.path.dirname(__file__), "chat_templates", "chat_templates" ) config_path = os.path.join( os.path.dirname(__file__), "chat_templates", "generation_configs" ) - jinja_env = jinja2.Environment(loader=jinja2.FileSystemLoader(chat_template_path)) with open(os.path.join(config_path, f"{CHAT_TEMPLATE}.json")) as f: gen_config = json.load(f) chat_template_file = gen_config["chat_template"].split("/")[-1] - gen_config["template"] = jinja_env.get_template(chat_template_file) + with open(os.path.join(chat_template_path, chat_template_file)) as f: + chat_template = f.read() + gen_config["template"] = chat_template.replace(" ", "").replace("\n", "") return gen_config @@ -45,9 +44,11 @@ def _get_gen_config(): class VLLM: def __init__(self) -> None: from vllm import AsyncEngineArgs, AsyncLLMEngine + from transformers import AutoTokenizer ENGINE_ARGS = AsyncEngineArgs(**ENGINE_CONFIG) self.engine = AsyncLLMEngine.from_engine_args(ENGINE_ARGS) + self.tokenizer = AutoTokenizer.from_pretrained(ENGINE_CONFIG["model"]) @bentoml.api async def generate( @@ -98,6 +99,7 @@ class VLLM: gen_config = _get_gen_config() + # normalize inputs if stop_token_ids is None: stop_token_ids = gen_config["stop_token_ids"] if stop == "" or stop is None: @@ -116,8 +118,10 @@ class VLLM: dict(role="system", content=gen_config["system_prompt"]) ] + messages - prompt = gen_config["template"].render( - messages=messages, + self.tokenizer.chat_template = gen_config["template"] + prompt = self.tokenizer.apply_chat_template( + messages, + tokenize=False, add_generation_prompt=True, ) From d6e99135e086080357badd3b364303f1e3cfb19c Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 21 May 2024 04:28:43 +0800 Subject: [PATCH 023/125] update dependencies --- vllm-chat/requirements.txt | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/vllm-chat/requirements.txt b/vllm-chat/requirements.txt index 6331d91e..63880cab 100644 --- a/vllm-chat/requirements.txt +++ b/vllm-chat/requirements.txt @@ -1,5 +1,4 @@ -torch==2.1.2 -vllm==0.4.0.post1 -transformers==4.39.3 +torch==2.3.0 +vllm==0.4.2 +transformers==4.41.0 pyyaml -jinja2 From 284c88acf76016373ecfd174c3fa54288d766815 Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 21 May 2024 04:31:53 +0800 Subject: [PATCH 024/125] add local run --- openllm_next/__main__.py | 9 ++- openllm_next/{spec.py => accelerator_spec.py} | 2 +- openllm_next/aws.py | 3 - openllm_next/common.py | 32 +++++++---- openllm_next/serve.py | 55 ++++++++++++++++++- 5 files changed, 82 insertions(+), 19 deletions(-) rename openllm_next/{spec.py => accelerator_spec.py} (98%) diff --git a/openllm_next/__main__.py b/openllm_next/__main__.py index 70e13f4d..9da5c740 100644 --- a/openllm_next/__main__.py +++ b/openllm_next/__main__.py @@ -1,7 +1,7 @@ import typer from openllm_next.model import app as model_app from openllm_next.repo import app as repo_app -from openllm_next.serve import serve as serve_serve +from openllm_next.serve import serve as local_serve, run as local_run app = typer.Typer() @@ -12,7 +12,12 @@ app.add_typer(model_app, name="model") @app.command() def serve(model: str): - serve_serve(model) + local_serve(model) + + +@app.command() +def run(model: str): + local_run(model) if __name__ == "__main__": diff --git a/openllm_next/spec.py b/openllm_next/accelerator_spec.py similarity index 98% rename from openllm_next/spec.py rename to openllm_next/accelerator_spec.py index 0023a2d0..798b4c31 100644 --- a/openllm_next/spec.py +++ b/openllm_next/accelerator_spec.py @@ -1,4 +1,4 @@ -accelerator_details = { +ACCELERATOR_SPEC = { "nvidia-gtx-1650": {"model": "GTX 1650", "memory_size": 4.0}, "nvidia-gtx-1060": {"model": "GTX 1060", "memory_size": 6.0}, "nvidia-gtx-1080-ti": {"model": "GTX 1080 Ti", "memory_size": 11.0}, diff --git a/openllm_next/aws.py b/openllm_next/aws.py index 35c3c887..7df1c93a 100644 --- a/openllm_next/aws.py +++ b/openllm_next/aws.py @@ -432,9 +432,6 @@ def serve(model: str, tag: str = "latest", force_rebuild: bool = False): envs = {} if len(bento_info.get("envs", [])) > 0: for env in bento_info["envs"]: - if env["name"] == "CLLAMA_MODEL": - envs[env["name"]] = f"{model}:{tag}" - continue if env["name"] in os.environ: value = os.environ.get(env["name"]) questionary.print(f"Using environment value for {env['name']}") diff --git a/openllm_next/common.py b/openllm_next/common.py index 5241362c..10eec89f 100644 --- a/openllm_next/common.py +++ b/openllm_next/common.py @@ -63,19 +63,31 @@ class BentoInfo(TypedDict): bento_yaml: dict -def run_command(cmd, cwd=None, env=None, copy_env=True): - questionary.print("\n") +def run_command(cmd, cwd=None, env=None, copy_env=True, bg=False): env = env or {} - if cwd: - questionary.print(f"$ cd {cwd}", style="bold") - if env: - for k, v in env.items(): - questionary.print(f"$ export {k}={shlex.quote(v)}", style="bold") if copy_env: - env = {**os.environ, **env} - questionary.print(f"$ {' '.join(cmd)}", style="bold") + merged_env = {**os.environ, **env} + else: + merged_env = env + if not bg: + questionary.print("\n") + if cwd: + questionary.print(f"$ cd {cwd}", style="bold") + if env: + for k, v in env.items(): + questionary.print(f"$ export {k}={shlex.quote(v)}", style="bold") + questionary.print(f"$ {' '.join(cmd)}", style="bold") try: - subprocess.run(cmd, cwd=cwd, env=env, check=True) + if bg: + return subprocess.Popen( + cmd, + cwd=cwd, + env=merged_env, + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + ) + else: + subprocess.run(cmd, cwd=cwd, env=merged_env, check=True) except subprocess.CalledProcessError: questionary.print("Command failed", style=ERROR_STYLE) return diff --git a/openllm_next/serve.py b/openllm_next/serve.py index 36c51d35..9a5384d8 100644 --- a/openllm_next/serve.py +++ b/openllm_next/serve.py @@ -1,4 +1,5 @@ import typer +import asyncio import questionary from openllm_next.common import ERROR_STYLE, run_command from openllm_next.model import _get_bento_info @@ -6,7 +7,7 @@ from openllm_next.model import _get_bento_info app = typer.Typer() -def _serve_model(model: str): +def _serve_model(model: str, bg: bool = False): if ":" not in model: model = f"{model}:latest" bento_info = _get_bento_info(model) @@ -15,12 +16,60 @@ def _serve_model(model: str): return cmd = ["bentoml", "serve", model] env = { - "CLLAMA_MODEL": model, "BENTOML_HOME": bento_info["model"]["repo"]["path"] + "/bentoml", } - run_command(cmd, env=env) + return run_command(cmd, env=env, bg=bg) @app.command() def serve(model: str): _serve_model(model) + + +async def _run_model(model: str, timeout: int = 600): + server_proc = _serve_model(model, bg=True) + assert server_proc is not None + + import bentoml + + try: + questionary.print("Model loading...", style="green") + for _ in range(timeout): + try: + client = bentoml.AsyncHTTPClient( + "http://localhost:3000", timeout=timeout + ) + resp = await client.request("GET", "/readyz") + if resp.status_code == 200: + break + except bentoml.exceptions.BentoMLException: + await asyncio.sleep(1) + else: + questionary.print("Model failed to load", style="red") + return + + questionary.print("Model is ready", style="green") + messages = [] + while True: + try: + message = input("uesr: ") + messages.append(dict(role="user", content=message)) + print("assistant: ", end="") + assistant_message = "" + async for text in client.chat(messages=messages): # type: ignore + assistant_message += text + print(text, end="") + messages.append(dict(role="assistant", content=assistant_message)) + print() + + except KeyboardInterrupt: + break + finally: + questionary.print("\nStopping model server...", style="green") + server_proc.terminate() + questionary.print("Stopped model server", style="green") + + +@app.command() +def run(model: str): + asyncio.run(_run_model(model)) From a92e68b9fd9d0082721db82899787cff7732bb8d Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 21 May 2024 20:38:20 +0800 Subject: [PATCH 025/125] add cloud serve --- openllm_next/__main__.py | 2 + openllm_next/aws.py | 6 +- openllm_next/cloud.py | 121 +++++++++++++++++++++++++++++++++++++++ openllm_next/common.py | 33 +++++++---- openllm_next/model.py | 32 ++++++++++- openllm_next/serve.py | 35 ++++++----- 6 files changed, 194 insertions(+), 35 deletions(-) create mode 100644 openllm_next/cloud.py diff --git a/openllm_next/__main__.py b/openllm_next/__main__.py index 9da5c740..e29f41ed 100644 --- a/openllm_next/__main__.py +++ b/openllm_next/__main__.py @@ -2,12 +2,14 @@ import typer from openllm_next.model import app as model_app from openllm_next.repo import app as repo_app from openllm_next.serve import serve as local_serve, run as local_run +from openllm_next.cloud import app as cloud_app app = typer.Typer() app.add_typer(repo_app, name="repo") app.add_typer(model_app, name="model") +app.add_typer(cloud_app, name="cloud") @app.command() diff --git a/openllm_next/aws.py b/openllm_next/aws.py index 7df1c93a..d3156dcf 100644 --- a/openllm_next/aws.py +++ b/openllm_next/aws.py @@ -210,7 +210,7 @@ def model_list(): pyaml.pprint(_load_model_map()) -def _get_bento_info(tag): +def get_bento_info(tag): model_map = _load_model_map() bento, version = tag.split(":") if bento not in model_map or version not in model_map[bento]: @@ -227,7 +227,7 @@ def _get_bento_info(tag): @model_app.command(name="get") def model_get(tag: str): - bento_info = _get_bento_info(tag) + bento_info = get_bento_info(tag) if bento_info: pyaml.pprint(bento_info) @@ -424,7 +424,7 @@ def serve(model: str, tag: str = "latest", force_rebuild: bool = False): shutil.rmtree(repo_dir, ignore_errors=True) raise - bento_info = _get_bento_info(f"{model}:{tag}", bento_project_dir) + bento_info = get_bento_info(f"{model}:{tag}", bento_project_dir) if len(bento_info["services"]) != 1: raise ValueError("Only support one service currently") diff --git a/openllm_next/cloud.py b/openllm_next/cloud.py new file mode 100644 index 00000000..988f1bbf --- /dev/null +++ b/openllm_next/cloud.py @@ -0,0 +1,121 @@ +import typer +import json +import subprocess +import asyncio +import questionary +from openllm_next.common import ERROR_STYLE, run_command +from openllm_next.model import get_bento_info, get_deploy_cmd + +app = typer.Typer() + + +def _ensure_cloud_context(): + cmd = ["bentoml", "cloud", "current-context"] + try: + result = subprocess.check_output(cmd) + context = json.loads(result) + questionary.print(f"already logged in to {context['endpoint']}", style="green") + except subprocess.CalledProcessError: + action = questionary.select( + "bento cloud not logged in", + choices=[ + "I have a token", + "Get a token in two minutes", + ], + ).ask() + if action is None: + questionary.print("Cancelled", style=ERROR_STYLE) + raise typer.Exit(1) + elif action == "Get a token in two minutes": + questionary.print( + "Please visit https://cloud.bentoml.com to get your token", + style="green", + ) + token = questionary.text("Enter your token: (like cniluaxxxxxxxx)").ask() + if token is None: + questionary.print("Cancelled", style=ERROR_STYLE) + raise typer.Exit(1) + endpoint = questionary.text( + "Enter the endpoint: (like https://my-org.cloud.bentoml.com)" + ).ask() + if endpoint is None: + questionary.print("Cancelled", style=ERROR_STYLE) + raise typer.Exit(1) + cmd = [ + "bentoml", + "cloud", + "login", + "--api-token", + token, + "--endpoint", + endpoint, + ] + try: + result = subprocess.check_output(cmd) + questionary.print("Logged in successfully", style="green") + except subprocess.CalledProcessError: + questionary.print("Failed to login", style=ERROR_STYLE) + raise typer.Exit(1) + + +@app.command() +def serve(model: str): + _ensure_cloud_context() + cmd, env, cwd = get_deploy_cmd(model) + run_command(cmd, env=env, cwd=cwd) + + +async def _run_model(model: str, timeout: int = 600): + _ensure_cloud_context() + cmd, env, cwd = get_deploy_cmd(model) + server_proc = subprocess.Popen( + cmd, + env=env, + cwd=cwd, + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + ) + + import bentoml + + try: + questionary.print("Model loading...", style="green") + for _ in range(timeout): + try: + client = bentoml.AsyncHTTPClient( + "http://localhost:3000", timeout=timeout + ) + resp = await client.request("GET", "/readyz") + if resp.status_code == 200: + break + except bentoml.exceptions.BentoMLException: + await asyncio.sleep(1) + else: + questionary.print("Model failed to load", style="red") + return + + questionary.print("Model is ready", style="green") + messages = [] + while True: + try: + message = input("uesr: ") + messages.append(dict(role="user", content=message)) + print("assistant: ", end="") + assistant_message = "" + async for text in client.chat(messages=messages): # type: ignore + assistant_message += text + print(text, end="") + messages.append(dict(role="assistant", content=assistant_message)) + print() + + except KeyboardInterrupt: + break + finally: + questionary.print("\nStopping model server...", style="green") + server_proc.terminate() + questionary.print("Stopped model server", style="green") + + +@app.command() +def run(model: str): + asyncio.run(_run_model(model)) diff --git a/openllm_next/common.py b/openllm_next/common.py index 10eec89f..77c35ffe 100644 --- a/openllm_next/common.py +++ b/openllm_next/common.py @@ -1,4 +1,5 @@ import shlex +import sys import os from typing_extensions import TypedDict import pydantic @@ -63,13 +64,16 @@ class BentoInfo(TypedDict): bento_yaml: dict -def run_command(cmd, cwd=None, env=None, copy_env=True, bg=False): +def run_command( + cmd, + cwd=None, + env=None, + copy_env=True, + silent=False, + check=True, +) -> subprocess.CompletedProcess | subprocess.Popen | None: env = env or {} - if copy_env: - merged_env = {**os.environ, **env} - else: - merged_env = env - if not bg: + if not silent: questionary.print("\n") if cwd: questionary.print(f"$ cd {cwd}", style="bold") @@ -77,17 +81,24 @@ def run_command(cmd, cwd=None, env=None, copy_env=True, bg=False): for k, v in env.items(): questionary.print(f"$ export {k}={shlex.quote(v)}", style="bold") questionary.print(f"$ {' '.join(cmd)}", style="bold") + if copy_env: + env = {**os.environ, **env} + if cmd and cmd[0] == "bentoml": + cmd = [sys.executable, "-m", "bentoml"] + cmd[1:] + if cmd and cmd[0] == "python": + cmd = [sys.executable] + cmd[1:] try: - if bg: - return subprocess.Popen( + if silent: + return subprocess.run( cmd, cwd=cwd, - env=merged_env, + env=env, + check=check, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, ) else: - subprocess.run(cmd, cwd=cwd, env=merged_env, check=True) + return subprocess.run(cmd, cwd=cwd, env=env, check=check) except subprocess.CalledProcessError: questionary.print("Command failed", style=ERROR_STYLE) - return + return None diff --git a/openllm_next/model.py b/openllm_next/model.py index ddef098c..4ccbdbc5 100644 --- a/openllm_next/model.py +++ b/openllm_next/model.py @@ -63,7 +63,35 @@ def list(): pyaml.pprint(_load_model_map()) -def _get_bento_info(tag): +def get_serve_cmd(model: str): + if ":" not in model: + model = f"{model}:latest" + bento_info = get_bento_info(model) + if not bento_info: + questionary.print(f"Model {model} not found", style=ERROR_STYLE) + raise typer.Exit(1) + cmd = ["bentoml", "serve", model] + env = { + "BENTOML_HOME": bento_info["model"]["repo"]["path"] + "/bentoml", + } + return cmd, env, None + + +def get_deploy_cmd(model: str): + if ":" not in model: + model = f"{model}:latest" + bento_info = get_bento_info(model) + if not bento_info: + questionary.print(f"Model {model} not found", style=ERROR_STYLE) + raise typer.Exit(1) + cmd = ["bentoml", "deploy", model] + env = { + "BENTOML_HOME": bento_info["model"]["repo"]["path"] + "/bentoml", + } + return cmd, env, None + + +def get_bento_info(tag): model_map = _load_model_map() bento, version = tag.split(":") if bento not in model_map or version not in model_map[bento]: @@ -82,6 +110,6 @@ def _get_bento_info(tag): @app.command() def get(tag: str): - bento_info = _get_bento_info(tag) + bento_info = get_bento_info(tag) if bento_info: pyaml.pprint(bento_info) diff --git a/openllm_next/serve.py b/openllm_next/serve.py index 9a5384d8..6f874feb 100644 --- a/openllm_next/serve.py +++ b/openllm_next/serve.py @@ -1,34 +1,29 @@ import typer +import subprocess import asyncio +import os import questionary -from openllm_next.common import ERROR_STYLE, run_command -from openllm_next.model import _get_bento_info +from openllm_next.common import run_command +from openllm_next.model import get_serve_cmd app = typer.Typer() -def _serve_model(model: str, bg: bool = False): - if ":" not in model: - model = f"{model}:latest" - bento_info = _get_bento_info(model) - if not bento_info: - questionary.print(f"Model {model} not found", style=ERROR_STYLE) - return - cmd = ["bentoml", "serve", model] - env = { - "BENTOML_HOME": bento_info["model"]["repo"]["path"] + "/bentoml", - } - return run_command(cmd, env=env, bg=bg) - - @app.command() def serve(model: str): - _serve_model(model) + cmd, env, cwd = get_serve_cmd(model) + run_command(cmd, env=env, cwd=cwd) async def _run_model(model: str, timeout: int = 600): - server_proc = _serve_model(model, bg=True) - assert server_proc is not None + cmd, env, cwd = get_serve_cmd(model) + server_proc = subprocess.Popen( + cmd, + env={**os.environ, **env}, + cwd=cwd, + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + ) import bentoml @@ -64,6 +59,8 @@ async def _run_model(model: str, timeout: int = 600): except KeyboardInterrupt: break + except asyncio.CancelledError: + pass finally: questionary.print("\nStopping model server...", style="green") server_proc.terminate() From 38c6108c332b576d4ea3b07c794c270c5f2924fd Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 21 May 2024 21:25:23 +0800 Subject: [PATCH 026/125] fix: prompt env vars for cloud serve --- openllm_next/cloud.py | 20 ++++++++++---------- openllm_next/model.py | 27 +++++++++++++++++++++++++++ 2 files changed, 37 insertions(+), 10 deletions(-) diff --git a/openllm_next/cloud.py b/openllm_next/cloud.py index 988f1bbf..54fbdb9e 100644 --- a/openllm_next/cloud.py +++ b/openllm_next/cloud.py @@ -4,7 +4,7 @@ import subprocess import asyncio import questionary from openllm_next.common import ERROR_STYLE, run_command -from openllm_next.model import get_bento_info, get_deploy_cmd +from openllm_next.model import get_deploy_cmd app = typer.Typer() @@ -14,32 +14,32 @@ def _ensure_cloud_context(): try: result = subprocess.check_output(cmd) context = json.loads(result) - questionary.print(f"already logged in to {context['endpoint']}", style="green") + questionary.print( + f"BentoCloud already logged in: {context['endpoint']}", style="green" + ) except subprocess.CalledProcessError: action = questionary.select( "bento cloud not logged in", choices=[ - "I have a token", - "Get a token in two minutes", + "I have a BentoCloud account", + "Get an account in two minutes", ], ).ask() if action is None: questionary.print("Cancelled", style=ERROR_STYLE) raise typer.Exit(1) - elif action == "Get a token in two minutes": + elif action == "Get an account in two minutes": questionary.print( "Please visit https://cloud.bentoml.com to get your token", - style="green", + style="yellow", ) - token = questionary.text("Enter your token: (like cniluaxxxxxxxx)").ask() + token = questionary.text("Enter your token: (similar to cniluaxxxxxxxx)").ask() if token is None: - questionary.print("Cancelled", style=ERROR_STYLE) raise typer.Exit(1) endpoint = questionary.text( - "Enter the endpoint: (like https://my-org.cloud.bentoml.com)" + "Enter the endpoint: (similar to https://my-org.cloud.bentoml.com)" ).ask() if endpoint is None: - questionary.print("Cancelled", style=ERROR_STYLE) raise typer.Exit(1) cmd = [ "bentoml", diff --git a/openllm_next/model.py b/openllm_next/model.py index 4ccbdbc5..f7402d4d 100644 --- a/openllm_next/model.py +++ b/openllm_next/model.py @@ -1,4 +1,5 @@ import typer +import os import collections import yaml @@ -84,10 +85,36 @@ def get_deploy_cmd(model: str): if not bento_info: questionary.print(f"Model {model} not found", style=ERROR_STYLE) raise typer.Exit(1) + cmd = ["bentoml", "deploy", model] env = { "BENTOML_HOME": bento_info["model"]["repo"]["path"] + "/bentoml", } + + required_envs = bento_info["bento_yaml"].get("envs", []) + required_env_names = [env["name"] for env in required_envs if "name" in env] + if required_env_names: + questionary.print( + f"This model requires the following environment variables to run: {repr(required_env_names)}", + style="yellow", + ) + + for env_info in bento_info["bento_yaml"].get("envs", []): + if "name" not in env_info: + continue + if os.environ.get(env_info["name"]): + default = os.environ[env_info["name"]] + elif "value" in env_info: + default = env_info["value"] + else: + default = "" + value = questionary.text( + f"{env_info['name']}:", + default=default, + ).ask() + if value is None: + raise typer.Exit(1) + cmd += ["--env", f"{env_info['name']}={value}"] return cmd, env, None From 5db18195276f543996e6a5fce5211e15fef56c0f Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 21 May 2024 21:26:05 +0800 Subject: [PATCH 027/125] fix: use official chat_template first --- vllm-chat/bento_constants.py | 2 +- vllm-chat/service.py | 36 +++++++++++++++++++++--------------- 2 files changed, 22 insertions(+), 16 deletions(-) diff --git a/vllm-chat/bento_constants.py b/vllm-chat/bento_constants.py index 684ecce6..4ea1e145 100644 --- a/vllm-chat/bento_constants.py +++ b/vllm-chat/bento_constants.py @@ -4,7 +4,7 @@ alias: - 3.8b - instruct - mini -template: vllm-chat +project: vllm-chat service_config: name: phi3 traffic: diff --git a/vllm-chat/service.py b/vllm-chat/service.py index 5a84e0e2..ca15990b 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -15,19 +15,18 @@ from bento_constants import CONSTANT_YAML CONSTANTS = yaml.safe_load(CONSTANT_YAML) ENGINE_CONFIG = CONSTANTS["engine_config"] -CHAT_TEMPLATE = CONSTANTS["chat_template"] SERVICE_CONFIG = CONSTANTS["service_config"] @functools.lru_cache(maxsize=1) -def _get_gen_config(): +def _get_gen_config(community_chat_template: str) -> dict: chat_template_path = os.path.join( os.path.dirname(__file__), "chat_templates", "chat_templates" ) config_path = os.path.join( os.path.dirname(__file__), "chat_templates", "generation_configs" ) - with open(os.path.join(config_path, f"{CHAT_TEMPLATE}.json")) as f: + with open(os.path.join(config_path, f"{community_chat_template}.json")) as f: gen_config = json.load(f) chat_template_file = gen_config["chat_template"].split("/")[-1] with open(os.path.join(chat_template_path, chat_template_file)) as f: @@ -97,28 +96,35 @@ class VLLM: """ from vllm import SamplingParams - gen_config = _get_gen_config() + if CONSTANTS.get("chat_template"): # community chat template + gen_config = _get_gen_config(CONSTANTS["chat_template"]) + if not stop: + if gen_config["stop_str"]: + stop = [gen_config["stop_str"]] + else: + stop = [] + system_prompt = gen_config["system_prompt"] + self.tokenizer.chat_template = gen_config["template"] + else: + if not stop: + if self.tokenizer.eos_token is not None: + stop = [self.tokenizer.eos_token] + else: + stop = [] + system_prompt = None # normalize inputs if stop_token_ids is None: - stop_token_ids = gen_config["stop_token_ids"] - if stop == "" or stop is None: - if gen_config["stop_str"] is None: - stop = [] - else: - stop = [gen_config["stop_str"]] + stop_token_ids = [] SAMPLING_PARAM = SamplingParams( max_tokens=max_tokens, stop_token_ids=stop_token_ids, stop=stop, ) - if gen_config["system_prompt"] and messages[0].get("role") != "system": - messages = [ - dict(role="system", content=gen_config["system_prompt"]) - ] + messages + if system_prompt and messages[0].get("role") != "system": + messages = [dict(role="system", content=system_prompt)] + messages - self.tokenizer.chat_template = gen_config["template"] prompt = self.tokenizer.apply_chat_template( messages, tokenize=False, From d92d5ae6c91ceb15acd7251cbdcad2cd7c70fe1a Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 21 May 2024 21:34:42 +0800 Subject: [PATCH 028/125] chore: prompt message --- openllm_next/cloud.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/openllm_next/cloud.py b/openllm_next/cloud.py index 54fbdb9e..7f49fab8 100644 --- a/openllm_next/cloud.py +++ b/openllm_next/cloud.py @@ -12,23 +12,23 @@ app = typer.Typer() def _ensure_cloud_context(): cmd = ["bentoml", "cloud", "current-context"] try: - result = subprocess.check_output(cmd) + result = subprocess.check_output(cmd, stderr=subprocess.DEVNULL) context = json.loads(result) questionary.print( f"BentoCloud already logged in: {context['endpoint']}", style="green" ) except subprocess.CalledProcessError: action = questionary.select( - "bento cloud not logged in", + "BentoCloud not logged in", choices=[ "I have a BentoCloud account", - "Get an account in two minutes", + "get an account in two minutes", ], ).ask() if action is None: questionary.print("Cancelled", style=ERROR_STYLE) raise typer.Exit(1) - elif action == "Get an account in two minutes": + elif action == "get an account in two minutes": questionary.print( "Please visit https://cloud.bentoml.com to get your token", style="yellow", From 25eb616f025cba1ff39ba57678fa4ad3a464a054 Mon Sep 17 00:00:00 2001 From: bojiang Date: Thu, 23 May 2024 00:41:40 +0800 Subject: [PATCH 029/125] refactor: repo cache path --- openllm_next/__main__.py | 7 + openllm_next/aws.py | 631 --------------------------------------- openllm_next/common.py | 71 ++++- openllm_next/model.py | 37 +-- openllm_next/repo.py | 65 ++-- openllm_next/venv.py | 27 ++ pyproject.toml | 7 +- req.txt | 7 - 8 files changed, 146 insertions(+), 706 deletions(-) delete mode 100644 openllm_next/aws.py create mode 100644 openllm_next/venv.py delete mode 100644 req.txt diff --git a/openllm_next/__main__.py b/openllm_next/__main__.py index e29f41ed..c7d0083c 100644 --- a/openllm_next/__main__.py +++ b/openllm_next/__main__.py @@ -3,6 +3,7 @@ from openllm_next.model import app as model_app from openllm_next.repo import app as repo_app from openllm_next.serve import serve as local_serve, run as local_run from openllm_next.cloud import app as cloud_app +from openllm_next.common import VERBOSE_LEVEL app = typer.Typer() @@ -22,5 +23,11 @@ def run(model: str): local_run(model) +def main_callback(verbose: int = 0): + if verbose: + VERBOSE_LEVEL.set(verbose) + + if __name__ == "__main__": + app.callback()(main_callback) app() diff --git a/openllm_next/aws.py b/openllm_next/aws.py deleted file mode 100644 index d3156dcf..00000000 --- a/openllm_next/aws.py +++ /dev/null @@ -1,631 +0,0 @@ -""" -Deprecated -""" - -import typer -import typing -import collections - -import prompt_toolkit -from prompt_toolkit import print_formatted_text as print -import time -import uuid -import shutil -import pydantic -from urllib.parse import urlparse -import yaml -import json -import bentoml -import questionary -import os -import re -import subprocess -import pyaml -import pathlib -from cllama.spec import GPU_MEMORY - -ERROR_STYLE = "red" -SUCCESS_STYLE = "green" - - -CLLAMA_HOME = pathlib.Path.home() / ".openllm_next" -REPO_DIR = CLLAMA_HOME / "repos" -TEMP_DIR = CLLAMA_HOME / "temp" -VENV_DIR = CLLAMA_HOME / "venv" - -REPO_DIR.mkdir(exist_ok=True, parents=True) -TEMP_DIR.mkdir(exist_ok=True, parents=True) -VENV_DIR.mkdir(exist_ok=True, parents=True) - -CONFIG_FILE = CLLAMA_HOME / "config.json" - - -app = typer.Typer() -repo_app = typer.Typer() -model_app = typer.Typer() - -app.add_typer(repo_app, name="repo") -app.add_typer(model_app, name="model") - - -class Config(pydantic.BaseModel): - repos: dict[str, str] = { - "default": "git+https://github.com/bojiang/bentovllm@main#subdirectory=bentoml" - } - default_repo: str = "default" - - -def _load_config(): - if CONFIG_FILE.exists(): - with open(CONFIG_FILE) as f: - return Config(**json.load(f)) - return Config() - - -def _save_config(config): - with open(CONFIG_FILE, "w") as f: - json.dump(config.dict(), f, indent=2) - - -class ModelInfo(typing.TypedDict): - repo: str - path: str - - -def _load_model_map() -> dict[str, dict[str, ModelInfo]]: - model_map = collections.defaultdict(dict) - config = _load_config() - for repo_name, repo_url in config.repos.items(): - server, owner, repo, _ = _parse_repo_url(repo_url) - repo_dir = REPO_DIR / server / owner / repo - for path in repo_dir.glob("bentoml/bentos/*/*"): - if path.is_dir(): - model_map[path.parent.name][path.name] = ModelInfo( - repo=repo_name, - path=str(path), - ) - elif path.is_file(): - with open(path) as f: - origin_name = f.read().strip() - origin_path = path.parent / origin_name - model_map[path.parent.name][path.name] = ModelInfo( - repo=repo_name, - path=str(origin_path), - ) - return model_map - - -GIT_REPO_RE = re.compile( - r"git\+https://(?P.+)/(?P.+)/(?P.+?)(@(?P.+))?$" -) - - -@repo_app.command(name="list") -def repo_list(): - config = _load_config() - pyaml.pprint(config.repos) - - -def _parse_repo_url(repo_url): - """ - parse the git repo url to server, owner, repo name, branch - >>> _parse_repo_url("git+https://github.com/bojiang/bentovllm@main") - ('github.com', 'bojiang', 'bentovllm', 'main') - - >>> _parse_repo_url("git+https://github.com/bojiang/bentovllm") - ('github.com', 'bojiang', 'bentovllm', 'main') - """ - match = GIT_REPO_RE.match(repo_url) - if not match: - raise ValueError(f"Invalid git repo url: {repo_url}") - return ( - match.group("server"), - match.group("owner"), - match.group("repo"), - match.group("branch") or "main", - ) - - -@repo_app.command(name="add") -def repo_add(name: str, repo: str): - name = name.lower() - if not name.isidentifier(): - questionary.print( - f"Invalid repo name: {name}, should only contain letters, numbers and underscores", - style=ERROR_STYLE, - ) - return - - config = _load_config() - if name in config.repos: - override = questionary.confirm( - f"Repo {name} already exists({config.repos[name]}), override?" - ).ask() - if not override: - return - - config.repos[name] = repo - _save_config(config) - pyaml.pprint(config.repos) - - -@repo_app.command(name="remove") -def repo_remove(name: str): - config = _load_config() - if name not in config.repos: - questionary.print(f"Repo {name} does not exist", style=ERROR_STYLE) - return - - del config.repos[name] - _save_config(config) - pyaml.pprint(config.repos) - - -def _run_command(cmd, cwd=None): - questionary.print(f"\n$ {' '.join(cmd)}", style="bold") - subprocess.run(cmd, cwd=cwd, check=True) - - -@repo_app.command(name="update") -def repo_update(): - config = _load_config() - repos_in_use = set() - for name, repo in config.repos.items(): - server, owner, repo_name, branch = _parse_repo_url(repo) - repos_in_use.add((server, owner, repo_name)) - repo_dir = REPO_DIR / server / owner / repo_name - if not repo_dir.exists(): - repo_dir.parent.mkdir(parents=True, exist_ok=True) - try: - cmd = [ - "git", - "clone", - "--branch", - branch, - f"https://{server}/{owner}/{repo_name}.git", - str(repo_dir), - ] - _run_command(cmd) - except subprocess.CalledProcessError: - shutil.rmtree(repo_dir, ignore_errors=True) - questionary.print(f"Failed to clone repo {name}", style=ERROR_STYLE) - else: - try: - cmd = ["git", "fetch", "origin", branch] - _run_command(cmd, cwd=repo_dir) - cmd = ["git", "reset", "--hard", f"origin/{branch}"] - _run_command(cmd, cwd=repo_dir) - except: - shutil.rmtree(repo_dir, ignore_errors=True) - questionary.print(f"Failed to update repo {name}", style=ERROR_STYLE) - for repo_dir in REPO_DIR.glob("*/*/*"): - if tuple(repo_dir.parts[-3:]) not in repos_in_use: - shutil.rmtree(repo_dir, ignore_errors=True) - questionary.print(f"Removed unused repo {repo_dir}") - questionary.print("Repos updated", style=SUCCESS_STYLE) - - -@model_app.command(name="list") -def model_list(): - pyaml.pprint(_load_model_map()) - - -def get_bento_info(tag): - model_map = _load_model_map() - bento, version = tag.split(":") - if bento not in model_map or version not in model_map[bento]: - questionary.print(f"Model {tag} not found", style=ERROR_STYLE) - return - model_info = model_map[bento][version] - repo_name = model_info["repo"] - path = pathlib.Path(model_info["path"]) - - bento_file = path / "bento.yaml" - bento_info = yaml.safe_load(bento_file.read_text()) - return bento_info - - -@model_app.command(name="get") -def model_get(tag: str): - bento_info = get_bento_info(tag) - if bento_info: - pyaml.pprint(bento_info) - - -def _filter_instance_types( - instance_types, - gpu_count, - gpu_memory=None, - gpu_type=None, - level="match", -): - if gpu_memory is None: - if gpu_type is None: - raise ValueError("Either gpu_memory or gpu_type must be provided") - gpu_memory = GPU_MEMORY[gpu_type] - - def _check_instance(spec): - if gpu_count == 0 or gpu_count is None: - if "GpuInfo" in spec: - return False - else: - return True - else: - gpus = spec.get("GpuInfo", {}).get("Gpus", []) - if len(gpus) == 0: - return False - it_gpu = gpus[0] - it_gpu_mem = it_gpu["MemoryInfo"]["SizeInMiB"] / 1024 - - if it_gpu["Count"] == gpu_count and it_gpu_mem == gpu_memory: - return True - elif it_gpu["Count"] >= gpu_count and it_gpu_mem >= gpu_memory: - if level == "match": - return False - elif level == "usable": - return True - else: - assert False - else: - return False - - def _sort_key(spec): - return ( - spec["InstanceType"].split(".")[0], - spec.get("GpuInfo", {}).get("Gpus", [{}])[0].get("Count", 0), - spec.get("VCpuInfo", {}).get("DefaultVCpus", 0), - spec.get("MemoryInfo", {}).get("SizeInMiB", 0), - ) - - return sorted(filter(_check_instance, instance_types), key=_sort_key) - - -def _resolve_git_package(package): - match = REG_GITPACKAGE.match(package) - if not match: - raise ValueError(f"Invalid git package: {package}") - repo_url, branch, subdirectory = match.groups() - parsed = urlparse(repo_url) - - path_parts = [parsed.netloc] + parsed.path.split("/") - - return repo_url, branch, subdirectory, path_parts - - -def _get_it_card(spec): - """ - InstanceType: g4dn.2xlarge - VCpuInfo: - DefaultCores: 32 - DefaultThreadsPerCore: 2 - DefaultVCpus: 64 - - MemoryInfo: - SizeInMiB: 32768 - - GpuInfo: - Gpus: - - Count: 1 - Manufacturer: NVIDIA - MemoryInfo: - SizeInMiB: 16384 - Name: T4 - TotalGpuMemoryInMiB: 16384 - """ - return f"cpus: {spec['VCpuInfo']['DefaultVCpus']}, mem: {spec['MemoryInfo']['SizeInMiB']}, gpu: {spec['GpuInfo']['Gpus'][0]['Name']} x {spec['GpuInfo']['Gpus'][0]['Count']}, cost: $0.1/hour" - - -def _ensure_aws_security_group(group_name="cllama-http-default"): - try: - existing_groups = subprocess.check_output( - [ - "aws", - "ec2", - "describe-security-groups", - "--filters", - f"Name=group-name,Values={group_name}", - "--no-cli-pager", - ] - ) - existing_groups = json.loads(existing_groups) - if existing_groups["SecurityGroups"]: - return existing_groups["SecurityGroups"][0]["GroupId"] - - result = subprocess.check_output( - [ - "aws", - "ec2", - "create-security-group", - "--group-name", - group_name, - "--description", - "Default VPC security group for cllama services", - "--no-cli-pager", - ] - ) - result = json.loads(result) - security_group_id = result["GroupId"] - - subprocess.check_call( - [ - "aws", - "ec2", - "authorize-security-group-ingress", - "--group-id", - security_group_id, - "--protocol", - "tcp", - "--port", - "80", - "--cidr", - "0.0.0.0/0", - "--no-cli-pager", - ] - ) - subprocess.check_call( - [ - "aws", - "ec2", - "authorize-security-group-ingress", - "--group-id", - security_group_id, - "--protocol", - "tcp", - "--port", - "443", - "--cidr", - "0.0.0.0/0", - "--no-cli-pager", - ] - ) - subprocess.check_call( - [ - "aws", - "ec2", - "authorize-security-group-ingress", - "--group-id", - security_group_id, - "--protocol", - "tcp", - "--port", - "22", - "--cidr", - "0.0.0.0/0", - "--no-cli-pager", - ] - ) - return security_group_id - except subprocess.CalledProcessError as e: - raise RuntimeError(f"Failed to create security group: {e}") - - -@app.command() -def serve(model: str, tag: str = "latest", force_rebuild: bool = False): - if ":" in model: - model, tag = model.split(":") - if tag == "latest": - tag = next(iter(MODEL_INFOS[model].keys())) - - package = MODEL_INFOS[model][tag] - repo, branch, subdirectory, path_parts = _resolve_git_package(package) - repo_dir = REPO_DIR.joinpath(*path_parts) - bento_project_dir = repo_dir / subdirectory - - if force_rebuild: - shutil.rmtree(repo_dir, ignore_errors=True) - - if not repo_dir.exists(): - repo_dir.parent.mkdir(parents=True, exist_ok=True) - try: - cmd = ["git", "clone", "--branch", branch, repo, str(repo_dir)] - print(f"\n$ {' '.join(cmd)}") - subprocess.run(cmd, check=True) - except: - shutil.rmtree(repo_dir, ignore_errors=True) - raise - - bento_info = get_bento_info(f"{model}:{tag}", bento_project_dir) - - if len(bento_info["services"]) != 1: - raise ValueError("Only support one service currently") - - envs = {} - if len(bento_info.get("envs", [])) > 0: - for env in bento_info["envs"]: - if env["name"] in os.environ: - value = os.environ.get(env["name"]) - questionary.print(f"Using environment value for {env['name']}") - elif env.get("value"): - value = questionary.text( - f"Enter value for {env['name']}", - default=env["value"], - ).ask() - else: - value = questionary.text( - f"Enter value for {env['name']}", - ).ask() - envs[env["name"]] = value - - cloud_provider = questionary.select( - "Select a cloud provider", - choices=[ - questionary.Choice(title="Local", value="aws"), - questionary.Choice(title="BentoCloud", value="cloud"), - ], - ).ask() - - if cloud_provider == "cloud": - cloud_provider = questionary.select( - "You haven't logged in to BentoCloud, select an action", - choices=[ - questionary.Choice(title="Login with Token", value="login"), - questionary.Choice(title="Sign up ($10 free credit)", value="signup"), - ], - ).ask() - if cloud_provider == "login": - token = questionary.text("Enter your token").ask() - cmd = ["bentoml", "cloud", "login", "--token", token] - # print(f"\n$ {' '.join(cmd)}") - try: - subprocess.check_call(cmd) - except subprocess.CalledProcessError: - raise RuntimeError("Failed to login") - elif cloud_provider == "signup": - token = questionary.text( - "Open https://cloud.bentoml.org/signup in your browser", - ).ask() - # cmd = ["bentoml", "cloud", "signup"] - # print(f"\n$ {' '.join(cmd)}") - # try: - # subprocess.check_call(cmd) - # except subprocess.CalledProcessError: - # raise RuntimeError("Failed to sign up") - - elif cloud_provider == "aws": - try: - cmd = ["aws", "ec2", "describe-instance-types", "--no-cli-pager"] - print(f"\n$ {' '.join(cmd)}") - _instance_types = subprocess.check_output(cmd, text=True) - except subprocess.CalledProcessError: - raise - # print(e) - # _cli_install_aws() - available_it_infos = json.loads(_instance_types)["InstanceTypes"] - # pyaml.p(available_it_infos) - - service = bento_info["services"][0] - if "config" not in service or "resources" not in service["config"]: - raise ValueError("Service config is missing") - elif "gpu" in service["config"]["resources"]: - gpu_count = service["config"]["resources"]["gpu"] - gpu_type = service["config"]["resources"].get("gpu_type") - gpu_memory = service["config"]["resources"].get("gpu_memory") - supported_its = _filter_instance_types( - available_it_infos, - gpu_count, - gpu_memory, - gpu_type, - ) - it = questionary.select( - "Select an instance type", - choices=[ - questionary.Choice( - title=_get_it_card(it_info), - value=it_info["InstanceType"], - ) - for it_info in supported_its - ], - ).ask() - security_group_id = _ensure_aws_security_group() - AMI = "ami-02623cf022763d4a1" - - init_script_file = TEMP_DIR / f"init_script_{str(uuid.uuid4())[:8]}.sh" - with open(init_script_file, "w") as f: - f.write( - INIT_SCRIPT_TEMPLATE.format( - repo=repo, - subdirectory=subdirectory, - model=model, - tag=tag, - env_args=" ".join([f"-e {k}={v}" for k, v in envs.items()]), - ) - ) - # grant permission - os.chmod(init_script_file, 0o755) - cmd = [ - "aws", - "ec2", - "run-instances", - "--image-id", - AMI, - "--instance-type", - it, - "--security-group-ids", - security_group_id, - "--user-data", - f"file://{init_script_file}", - "--key-name", - "jiang", - "--count", - "1", - "--no-cli-pager", - ] - # print(f"\n$ {' '.join(cmd)}") - try: - result = subprocess.check_output(cmd) - except subprocess.CalledProcessError: - raise RuntimeError("Failed to create instance") - result = json.loads(result) - instance_id = result["Instances"][0]["InstanceId"] - print(f"Deployment {instance_id} is created") - - cmd = [ - "aws", - "ec2", - "describe-instances", - "--instance-ids", - instance_id, - "--no-cli-pager", - ] - # print(f"\n$ {' '.join(cmd)}") - result = subprocess.check_output(cmd) - result = json.loads(result) - public_ip = result["Reservations"][0]["Instances"][0]["PublicIpAddress"] - print(f"Public IP: {public_ip}") - - server_start_time = time.time() - print("Server is starting...") - with prompt_toolkit.shortcuts.ProgressBar() as pb: - for _ in pb(range(100)): - start_time = time.time() - try: - with bentoml.SyncHTTPClient(f"http://{public_ip}"): - break - except Exception: - time.sleep(max(0, 6 - (time.time() - start_time))) - else: - raise RuntimeError("Instance is not ready after 10 minutes") - print(f"Server started in {time.time() - server_start_time:.2f} seconds") - print(f"HTTP server is ready at http://{public_ip}") - return - else: - raise ValueError("GPU is required for now") - if cloud_provider == "bentocloud": - cmd = ["bentoml", "cloud", "current-context"] - # print(f"\n$ {' '.join(cmd)}") - try: - output = subprocess.check_output(cmd, text=True) - except subprocess.CalledProcessError: - raise RuntimeError( - "Failed to get bentocloud login context, please login first", - ) - - -@app.command() -def run(model: str, tag: str = "latest", force_rebuild: bool = False): - serve(model, tag, force_rebuild) - - -INIT_SCRIPT_TEMPLATE = """#!/bin/bash -pip3 install bentoml -rm -r /usr/local/cuda* -git clone {repo} /root/bento_repo -export BENTOML_HOME=/root/bento_repo/{subdirectory} -bentoml containerize {model}:{tag} --image-tag {model}:{tag} -docker run --restart always --gpus all -d -p 80:3000 {env_args} {model}:{tag} - -nvidia-smi -q | grep -A2 "ECC Mode" | grep "Current" | grep "Enabled" -ECC_ENABLED=$? - -if [[ $ECC_ENABLED -eq 0 ]]; then - echo "ECC is enabled. Disabling now..." - nvidia-smi -e 0 - reboot -else - echo "ECC is not enabled. No changes made." -fi -""" - - -if __name__ == "__main__": - app() diff --git a/openllm_next/common.py b/openllm_next/common.py index 77c35ffe..e2ab6a61 100644 --- a/openllm_next/common.py +++ b/openllm_next/common.py @@ -1,9 +1,9 @@ -import shlex import sys import os -from typing_extensions import TypedDict -import pydantic +import typing +from types import SimpleNamespace import json +from contextlib import contextmanager import questionary import subprocess import pathlib @@ -25,7 +25,26 @@ VENV_DIR.mkdir(exist_ok=True, parents=True) CONFIG_FILE = CLLAMA_HOME / "config.json" -class Config(pydantic.BaseModel): +T = typing.TypeVar("T") + +class ContextVar(typing.Generic[T]): + def __init__(self, default: T): + self._stack: list[T] = [] + self._default = default + + def get(self) -> T: + if self._stack: + return self._stack[-1] + return self._default + + def set(self, value): + self._stack.append(value) + + +VERBOSE_LEVEL = ContextVar(0) + + +class Config(SimpleNamespace): repos: dict[str, str] = { "default": "git+https://github.com/bojiang/openllm-repo@main" } @@ -44,25 +63,57 @@ def save_config(config): json.dump(config.dict(), f, indent=2) -class RepoInfo(TypedDict): +class RepoInfo(SimpleNamespace): name: str - path: str + cache_path: pathlib.Path url: str server: str owner: str repo: str branch: str + def tolist(self): + if VERBOSE_LEVEL.get() <= 0: + return self.name + if VERBOSE_LEVEL.get() <= 2: + return dict( + name=self.name, + cache_path=str(self.cache_path), + url=self.url, + server=self.server, + owner=self.owner, + repo=self.repo, + branch=self.branch, + ) -class ModelInfo(TypedDict): + +class ModelInfo(SimpleNamespace): repo: RepoInfo path: str + def tolist(self): + if VERBOSE_LEVEL.get() <= 0: + return f"{self.repo.name}" + if VERBOSE_LEVEL.get() <= 2: + return dict( + repo=self.repo.tolist(), + path=self.path, + ) -class BentoInfo(TypedDict): + +class BentoInfo(SimpleNamespace): model: ModelInfo bento_yaml: dict + def tolist(self): + if VERBOSE_LEVEL.get() <= 0: + return f"{self.model.repo.name}" + if VERBOSE_LEVEL.get() <= 2: + return dict( + model=self.model.tolist(), + bento_yaml=self.bento_yaml, + ) + def run_command( cmd, @@ -72,6 +123,8 @@ def run_command( silent=False, check=True, ) -> subprocess.CompletedProcess | subprocess.Popen | None: + import shlex + env = env or {} if not silent: questionary.print("\n") @@ -80,7 +133,7 @@ def run_command( if env: for k, v in env.items(): questionary.print(f"$ export {k}={shlex.quote(v)}", style="bold") - questionary.print(f"$ {' '.join(cmd)}", style="bold") + questionary.print(f"> {' '.join(cmd)}", style="bold") if copy_env: env = {**os.environ, **env} if cmd and cmd[0] == "bentoml": diff --git a/openllm_next/model.py b/openllm_next/model.py index f7402d4d..d8f6f4aa 100644 --- a/openllm_next/model.py +++ b/openllm_next/model.py @@ -8,10 +8,8 @@ import pyaml import pathlib from openllm_next.common import ( ERROR_STYLE, - REPO_DIR, load_config, ModelInfo, - RepoInfo, BentoInfo, ) from openllm_next.repo import parse_repo_url @@ -24,20 +22,11 @@ def _load_model_map() -> dict[str, dict[str, ModelInfo]]: model_map = collections.defaultdict(dict) config = load_config() for repo_name, repo_url in config.repos.items(): - server, owner, repo, branch = parse_repo_url(repo_url) - repo_dir = REPO_DIR / server / owner / repo - for path in repo_dir.glob("bentoml/bentos/*/*"): + repo = parse_repo_url(repo_url, repo_name) + for path in repo.cache_path.glob("bentoml/bentos/*/*"): if path.is_dir(): model_map[path.parent.name][path.name] = ModelInfo( - repo=RepoInfo( - name=repo_name, - url=repo_url, - server=server, - owner=owner, - repo=repo, - branch=branch, - path=str(repo_dir), - ), + repo=repo, path=str(path), ) elif path.is_file(): @@ -45,15 +34,7 @@ def _load_model_map() -> dict[str, dict[str, ModelInfo]]: origin_name = f.read().strip() origin_path = path.parent / origin_name model_map[path.parent.name][path.name] = ModelInfo( - repo=RepoInfo( - name=repo_name, - url=repo_url, - server=server, - owner=owner, - repo=repo, - branch=branch, - path=str(repo_dir), - ), + repo=repo, path=str(origin_path), ) return model_map @@ -73,7 +54,7 @@ def get_serve_cmd(model: str): raise typer.Exit(1) cmd = ["bentoml", "serve", model] env = { - "BENTOML_HOME": bento_info["model"]["repo"]["path"] + "/bentoml", + "BENTOML_HOME": bento_info.model.repo.path + "/bentoml", } return cmd, env, None @@ -88,10 +69,10 @@ def get_deploy_cmd(model: str): cmd = ["bentoml", "deploy", model] env = { - "BENTOML_HOME": bento_info["model"]["repo"]["path"] + "/bentoml", + "BENTOML_HOME": bento_info.model.repo.path + "/bentoml", } - required_envs = bento_info["bento_yaml"].get("envs", []) + required_envs = bento_info.bento_yaml.get("envs", []) required_env_names = [env["name"] for env in required_envs if "name" in env] if required_env_names: questionary.print( @@ -99,7 +80,7 @@ def get_deploy_cmd(model: str): style="yellow", ) - for env_info in bento_info["bento_yaml"].get("envs", []): + for env_info in bento_info.bento_yaml.get("envs", []): if "name" not in env_info: continue if os.environ.get(env_info["name"]): @@ -125,7 +106,7 @@ def get_bento_info(tag): questionary.print(f"Model {tag} not found", style=ERROR_STYLE) return model_info = model_map[bento][version] - path = pathlib.Path(model_info["path"]) + path = pathlib.Path(model_info.path) bento_file = path / "bento.yaml" bento_info = yaml.safe_load(bento_file.read_text()) diff --git a/openllm_next/repo.py b/openllm_next/repo.py index f3dd31bc..d8c4ed81 100644 --- a/openllm_next/repo.py +++ b/openllm_next/repo.py @@ -1,4 +1,5 @@ import typer +import pathlib import shutil import questionary @@ -12,6 +13,7 @@ from openllm_next.common import ( load_config, save_config, run_command, + RepoInfo, ) @@ -29,7 +31,7 @@ def list(): pyaml.pprint(config.repos) -def parse_repo_url(repo_url): +def parse_repo_url(repo_url, repo_name=None) -> RepoInfo: """ parse the git repo url to server, owner, repo name, branch >>> parse_repo_url("git+https://github.com/bojiang/bentovllm@main") @@ -41,11 +43,19 @@ def parse_repo_url(repo_url): match = GIT_REPO_RE.match(repo_url) if not match: raise ValueError(f"Invalid git repo url: {repo_url}") - return ( - match.group("server"), - match.group("owner"), - match.group("repo"), - match.group("branch") or "main", + server = match.group("server") + owner = match.group("owner") + repo = match.group("repo") + branch = match.group("branch") or "main" + cache_path = REPO_DIR / server / owner / repo + return RepoInfo( + name=repo if repo_name is None else repo_name, + url=repo_url, + server=server, + owner=owner, + repo=repo, + branch=branch, + cache_path=cache_path, ) @@ -88,40 +98,39 @@ def remove(name: str): def update(): config = load_config() repos_in_use = set() - for name, repo in config.repos.items(): - server, owner, repo_name, branch = parse_repo_url(repo) - repos_in_use.add((server, owner, repo_name)) - repo_dir = REPO_DIR / server / owner / repo_name - if not repo_dir.exists(): - repo_dir.parent.mkdir(parents=True, exist_ok=True) + for repo_name, repo in config.repos.items(): + repo = parse_repo_url(repo, repo_name) + repos_in_use.add((repo.server, repo.owner, repo.repo)) + if not repo.cache_path.exists(): + repo.cache_path.parent.mkdir(parents=True, exist_ok=True) try: cmd = [ "git", "clone", "--branch", - branch, - f"https://{server}/{owner}/{repo_name}.git", - str(repo_dir), + repo.branch, + f"https://{repo.server}/{repo.owner}/{repo.repo}.git", + str(repo.cache_path), ] run_command(cmd) except subprocess.CalledProcessError: - shutil.rmtree(repo_dir, ignore_errors=True) - questionary.print(f"Failed to clone repo {name}", style=ERROR_STYLE) + shutil.rmtree(repo.cache_path, ignore_errors=True) + questionary.print(f"Failed to clone repo {repo.name}", style=ERROR_STYLE) else: try: - cmd = ["git", "fetch", "origin", branch] - run_command(cmd, cwd=repo_dir) - cmd = ["git", "reset", "--hard", f"origin/{branch}"] - run_command(cmd, cwd=repo_dir) + cmd = ["git", "fetch", "origin", repo.branch] + run_command(cmd, cwd=repo.cache_path) + cmd = ["git", "reset", "--hard", f"origin/{repo.branch}"] + run_command(cmd, cwd=repo.cache_path) cmd = ["git", "clean", "-fdx"] - run_command(cmd, cwd=repo_dir) + run_command(cmd, cwd=repo.cache_path) except: - shutil.rmtree(repo_dir, ignore_errors=True) - questionary.print(f"Failed to update repo {name}", style=ERROR_STYLE) - for repo_dir in REPO_DIR.glob("*/*/*"): - if tuple(repo_dir.parts[-3:]) not in repos_in_use: - shutil.rmtree(repo_dir, ignore_errors=True) - questionary.print(f"Removed unused repo {repo_dir}") + shutil.rmtree(repo.cache_path, ignore_errors=True) + questionary.print(f"Failed to update repo {repo.name}", style=ERROR_STYLE) + for c in REPO_DIR.glob("*/*/*"): + if tuple(c.parts[-3:]) not in repos_in_use: + shutil.rmtree(c, ignore_errors=True) + questionary.print(f"Removed unused repo cache {c}") questionary.print("Repos updated", style=SUCCESS_STYLE) diff --git a/openllm_next/venv.py b/openllm_next/venv.py new file mode 100644 index 00000000..35629c31 --- /dev/null +++ b/openllm_next/venv.py @@ -0,0 +1,27 @@ + + + +def _resolve_package_versions(requirement: str) -> dict[str, str]: + from pip_requirements_parser import RequirementsFile + + requirements_txt = RequirementsFile.from_file( + requirement, + include_nested=True, + ) + deps: dict[str, str] = {} + for req in requirements_txt.requirements: + if ( + req.is_editable + or req.is_local_path + or req.is_url + or req.is_wheel + or not req.name + or not req.specifier + ): + continue + for sp in req.specifier: + if sp.operator == "==": + assert req.line is not None + deps[req.name] = req.line + break + return deps diff --git a/pyproject.toml b/pyproject.toml index fd461c97..04989725 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -9,13 +9,14 @@ description = "A description of your package." authors = [{name = "oasiszero", email = "oasis0.com@gmail.com"}] license = {file = "LICENSE"} dependencies = [ - "typer", "bentoml", - "pyaml", - "fastapi", + "typer", "questionary", + "pyaml", "psutil", "pathlib" + "pip_requirements_parser", + "venv", ] [tool.typer] diff --git a/req.txt b/req.txt deleted file mode 100644 index 4f08fb7b..00000000 --- a/req.txt +++ /dev/null @@ -1,7 +0,0 @@ -typer -bentoml -pyaml -fastapi -questionary -psutil -pathlib From 193d480b09748ef2f5eeb80db71ef736fc124e49 Mon Sep 17 00:00:00 2001 From: bojiang Date: Thu, 23 May 2024 02:00:45 +0800 Subject: [PATCH 030/125] fix --- make.py | 2 +- vllm-chat/service.py | 2 -- 2 files changed, 1 insertion(+), 3 deletions(-) diff --git a/make.py b/make.py index 8acac29f..689825df 100644 --- a/make.py +++ b/make.py @@ -58,7 +58,7 @@ if __name__ == "__main__": if ALIAS_PATH.exists(): continue with open(ALIAS_PATH, "w") as f: - f.write(model_name) + f.write(model_version) else: # bentoml currently only support latest alias, copy to other alias shutil.copytree( BENTOML_HOME / "bentos" / model_repo / model_version, diff --git a/vllm-chat/service.py b/vllm-chat/service.py index ca15990b..44c23626 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -59,14 +59,12 @@ class VLLM: Le(ENGINE_CONFIG["max_model_len"]), ] = ENGINE_CONFIG["max_model_len"], stop: list[str] = [], - **kwargs, ) -> AsyncGenerator[str, None]: from vllm import SamplingParams SAMPLING_PARAM = SamplingParams( max_tokens=max_tokens, stop=stop, - **kwargs, ) stream = await self.engine.add_request(uuid.uuid4().hex, prompt, SAMPLING_PARAM) From 340c003f6eeeb2bd814dc3cf9a52109378d1e075 Mon Sep 17 00:00:00 2001 From: bojiang Date: Thu, 23 May 2024 02:11:14 +0800 Subject: [PATCH 031/125] refactor(model): clean model schema --- openllm_next/common.py | 79 ++++++++++++++++++++-------- openllm_next/model.py | 115 ++++++++++++++++++++++------------------- openllm_next/repo.py | 39 ++++++++------ openllm_next/venv.py | 3 -- pyproject.toml | 2 +- 5 files changed, 143 insertions(+), 95 deletions(-) diff --git a/openllm_next/common.py b/openllm_next/common.py index e2ab6a61..3750f56c 100644 --- a/openllm_next/common.py +++ b/openllm_next/common.py @@ -1,4 +1,5 @@ import sys +import functools import os import typing from types import SimpleNamespace @@ -27,6 +28,7 @@ CONFIG_FILE = CLLAMA_HOME / "config.json" T = typing.TypeVar("T") + class ContextVar(typing.Generic[T]): def __init__(self, default: T): self._stack: list[T] = [] @@ -65,7 +67,7 @@ def save_config(config): class RepoInfo(SimpleNamespace): name: str - cache_path: pathlib.Path + path: pathlib.Path url: str server: str owner: str @@ -78,7 +80,7 @@ class RepoInfo(SimpleNamespace): if VERBOSE_LEVEL.get() <= 2: return dict( name=self.name, - cache_path=str(self.cache_path), + path=str(self.path), url=self.url, server=self.server, owner=self.owner, @@ -87,30 +89,63 @@ class RepoInfo(SimpleNamespace): ) -class ModelInfo(SimpleNamespace): - repo: RepoInfo - path: str - - def tolist(self): - if VERBOSE_LEVEL.get() <= 0: - return f"{self.repo.name}" - if VERBOSE_LEVEL.get() <= 2: - return dict( - repo=self.repo.tolist(), - path=self.path, - ) - - class BentoInfo(SimpleNamespace): - model: ModelInfo - bento_yaml: dict + repo: RepoInfo + path: pathlib.Path + + @property + def tag(self) -> str: + return f"{self.path.parent.name}:{self.path.name}" + + @functools.cached_property + def bento_yaml(self) -> dict: + import yaml + + bento_file = self.path / "bento.yaml" + return yaml.safe_load(bento_file.read_text()) + + @functools.cached_property + def pretty_yaml(self) -> dict: + def _pretty_routes(routes): + return { + route["route"]: { + "input": { + k: v["type"] for k, v in route["input"]["properties"].items() + }, + "output": route["output"]["type"], + } + for route in routes + } + + if len(self.bento_yaml["services"]) == 1: + pretty_yaml = { + "apis": _pretty_routes(self.bento_yaml["schema"]["routes"]), + "resources": self.bento_yaml["services"][0]["config"]["resources"], + "envs": self.bento_yaml["envs"], + } + return pretty_yaml + return self.bento_yaml + + def __str__(self): + if self.repo.name == "default": + return f"{self.tag}" + else: + return f"{self.tag} ({self.repo.name})" def tolist(self): - if VERBOSE_LEVEL.get() <= 0: - return f"{self.model.repo.name}" - if VERBOSE_LEVEL.get() <= 2: + verbose = VERBOSE_LEVEL.get() + if verbose <= 0: return dict( - model=self.model.tolist(), + tag=self.tag, + repo=self.repo.tolist(), + path=str(self.path), + model_card=self.pretty_yaml, + ) + if verbose <= 2: + return dict( + tag=self.tag, + repo=self.repo.tolist(), + path=str(self.path), bento_yaml=self.bento_yaml, ) diff --git a/openllm_next/model.py b/openllm_next/model.py index d8f6f4aa..2106f805 100644 --- a/openllm_next/model.py +++ b/openllm_next/model.py @@ -1,15 +1,11 @@ import typer import os -import collections -import yaml import questionary import pyaml -import pathlib from openllm_next.common import ( ERROR_STYLE, load_config, - ModelInfo, BentoInfo, ) from openllm_next.repo import parse_repo_url @@ -18,61 +14,87 @@ from openllm_next.repo import parse_repo_url app = typer.Typer() -def _load_model_map() -> dict[str, dict[str, ModelInfo]]: - model_map = collections.defaultdict(dict) +def list_bento(tag: str | None = None) -> list[BentoInfo]: + if tag is None: + glob_pattern = "bentoml/bentos/*/*" + elif ":" in tag: + repo_name, version = tag.split(":") + glob_pattern = f"bentoml/bentos/{repo_name}/{version}" + else: + glob_pattern = f"bentoml/bentos/{tag}/*" + + model_list = [] config = load_config() for repo_name, repo_url in config.repos.items(): repo = parse_repo_url(repo_url, repo_name) - for path in repo.cache_path.glob("bentoml/bentos/*/*"): - if path.is_dir(): - model_map[path.parent.name][path.name] = ModelInfo( + for path in repo.path.glob(glob_pattern): + if path.is_dir() and (path / "bento.yaml").exists(): + model = BentoInfo( repo=repo, - path=str(path), + path=path, ) elif path.is_file(): with open(path) as f: origin_name = f.read().strip() origin_path = path.parent / origin_name - model_map[path.parent.name][path.name] = ModelInfo( + model = BentoInfo( repo=repo, - path=str(origin_path), + path=origin_path, ) - return model_map + else: + model = None + if model: + model_list.append(model) + return model_list + + +def pick_bento(tag) -> BentoInfo: + model_list = list_bento(tag) + if len(model_list) == 0: + questionary.print("No models found", style=ERROR_STYLE) + raise typer.Exit(1) + if len(model_list) == 1: + return model_list[0] + model = questionary.select( + "Select a model", + choices=[questionary.Choice(str(model), value=model) for model in model_list], + ).ask() + if model is None: + raise typer.Exit(1) + return model @app.command() def list(): - pyaml.pprint(_load_model_map()) + pyaml.pprint( + list_bento(), + sort_dicts=False, + sort_keys=False, + ) -def get_serve_cmd(model: str): - if ":" not in model: - model = f"{model}:latest" - bento_info = get_bento_info(model) - if not bento_info: - questionary.print(f"Model {model} not found", style=ERROR_STYLE) - raise typer.Exit(1) - cmd = ["bentoml", "serve", model] +def get_serve_cmd(tag: str): + if ":" not in tag: + tag = f"{tag}:latest" + bento = pick_bento(tag) + cmd = ["bentoml", "serve", bento.tag] env = { - "BENTOML_HOME": bento_info.model.repo.path + "/bentoml", + "BENTOML_HOME": f"{bento.repo.path}/bentoml", } return cmd, env, None -def get_deploy_cmd(model: str): - if ":" not in model: - model = f"{model}:latest" - bento_info = get_bento_info(model) - if not bento_info: - questionary.print(f"Model {model} not found", style=ERROR_STYLE) - raise typer.Exit(1) +def get_deploy_cmd(tag: str): + if ":" not in tag: + tag = f"{tag}:latest" + bento = pick_bento(tag) - cmd = ["bentoml", "deploy", model] + cmd = ["bentoml", "deploy", bento.tag] env = { - "BENTOML_HOME": bento_info.model.repo.path + "/bentoml", + "BENTOML_HOME": f"{bento.repo.path}/bentoml", } - required_envs = bento_info.bento_yaml.get("envs", []) + required_envs = bento.bento_yaml.get("envs", []) required_env_names = [env["name"] for env in required_envs if "name" in env] if required_env_names: questionary.print( @@ -80,7 +102,7 @@ def get_deploy_cmd(model: str): style="yellow", ) - for env_info in bento_info.bento_yaml.get("envs", []): + for env_info in bento.bento_yaml.get("envs", []): if "name" not in env_info: continue if os.environ.get(env_info["name"]): @@ -99,25 +121,12 @@ def get_deploy_cmd(model: str): return cmd, env, None -def get_bento_info(tag): - model_map = _load_model_map() - bento, version = tag.split(":") - if bento not in model_map or version not in model_map[bento]: - questionary.print(f"Model {tag} not found", style=ERROR_STYLE) - return - model_info = model_map[bento][version] - path = pathlib.Path(model_info.path) - - bento_file = path / "bento.yaml" - bento_info = yaml.safe_load(bento_file.read_text()) - return BentoInfo( - model=model_info, - bento_yaml=bento_info, - ) - - @app.command() def get(tag: str): - bento_info = get_bento_info(tag) + bento_info = pick_bento(tag) if bento_info: - pyaml.pprint(bento_info) + pyaml.pprint( + bento_info.tolist(), + sort_dicts=False, + sort_keys=False, + ) diff --git a/openllm_next/repo.py b/openllm_next/repo.py index d8c4ed81..43d0e75a 100644 --- a/openllm_next/repo.py +++ b/openllm_next/repo.py @@ -1,5 +1,4 @@ import typer -import pathlib import shutil import questionary @@ -28,7 +27,11 @@ GIT_REPO_RE = re.compile( @app.command() def list(): config = load_config() - pyaml.pprint(config.repos) + pyaml.pprint( + config.repos, + sort_dicts=False, + sort_keys=False, + ) def parse_repo_url(repo_url, repo_name=None) -> RepoInfo: @@ -47,7 +50,7 @@ def parse_repo_url(repo_url, repo_name=None) -> RepoInfo: owner = match.group("owner") repo = match.group("repo") branch = match.group("branch") or "main" - cache_path = REPO_DIR / server / owner / repo + path = REPO_DIR / server / owner / repo return RepoInfo( name=repo if repo_name is None else repo_name, url=repo_url, @@ -55,7 +58,7 @@ def parse_repo_url(repo_url, repo_name=None) -> RepoInfo: owner=owner, repo=repo, branch=branch, - cache_path=cache_path, + path=path, ) @@ -79,7 +82,7 @@ def add(name: str, repo: str): config.repos[name] = repo save_config(config) - pyaml.pprint(config.repos) + questionary.print(f"Repo {name} added", style=SUCCESS_STYLE) @app.command() @@ -91,7 +94,7 @@ def remove(name: str): del config.repos[name] save_config(config) - pyaml.pprint(config.repos) + questionary.print(f"Repo {name} removed", style=SUCCESS_STYLE) @app.command() @@ -101,8 +104,8 @@ def update(): for repo_name, repo in config.repos.items(): repo = parse_repo_url(repo, repo_name) repos_in_use.add((repo.server, repo.owner, repo.repo)) - if not repo.cache_path.exists(): - repo.cache_path.parent.mkdir(parents=True, exist_ok=True) + if not repo.path.exists(): + repo.path.parent.mkdir(parents=True, exist_ok=True) try: cmd = [ "git", @@ -110,23 +113,27 @@ def update(): "--branch", repo.branch, f"https://{repo.server}/{repo.owner}/{repo.repo}.git", - str(repo.cache_path), + str(repo.path), ] run_command(cmd) except subprocess.CalledProcessError: - shutil.rmtree(repo.cache_path, ignore_errors=True) - questionary.print(f"Failed to clone repo {repo.name}", style=ERROR_STYLE) + shutil.rmtree(repo.path, ignore_errors=True) + questionary.print( + f"Failed to clone repo {repo.name}", style=ERROR_STYLE + ) else: try: cmd = ["git", "fetch", "origin", repo.branch] - run_command(cmd, cwd=repo.cache_path) + run_command(cmd, cwd=repo.path) cmd = ["git", "reset", "--hard", f"origin/{repo.branch}"] - run_command(cmd, cwd=repo.cache_path) + run_command(cmd, cwd=repo.path) cmd = ["git", "clean", "-fdx"] - run_command(cmd, cwd=repo.cache_path) + run_command(cmd, cwd=repo.path) except: - shutil.rmtree(repo.cache_path, ignore_errors=True) - questionary.print(f"Failed to update repo {repo.name}", style=ERROR_STYLE) + shutil.rmtree(repo.path, ignore_errors=True) + questionary.print( + f"Failed to update repo {repo.name}", style=ERROR_STYLE + ) for c in REPO_DIR.glob("*/*/*"): if tuple(c.parts[-3:]) not in repos_in_use: shutil.rmtree(c, ignore_errors=True) diff --git a/openllm_next/venv.py b/openllm_next/venv.py index 35629c31..254f7a86 100644 --- a/openllm_next/venv.py +++ b/openllm_next/venv.py @@ -1,6 +1,3 @@ - - - def _resolve_package_versions(requirement: str) -> dict[str, str]: from pip_requirements_parser import RequirementsFile diff --git a/pyproject.toml b/pyproject.toml index 04989725..78a484d3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -14,7 +14,7 @@ dependencies = [ "questionary", "pyaml", "psutil", - "pathlib" + "pathlib", "pip_requirements_parser", "venv", ] From 89f1b93e75023374f2103733b0716d3acf0c9811 Mon Sep 17 00:00:00 2001 From: bojiang Date: Thu, 23 May 2024 03:12:00 +0800 Subject: [PATCH 032/125] fix: functional --- openllm_next/cloud.py | 6 +- openllm_next/common.py | 36 ++++++++--- openllm_next/model.py | 57 +++++++++--------- openllm_next/repo.py | 134 ++++++++++++++++++++--------------------- openllm_next/serve.py | 6 +- 5 files changed, 129 insertions(+), 110 deletions(-) diff --git a/openllm_next/cloud.py b/openllm_next/cloud.py index 7f49fab8..df16bf2f 100644 --- a/openllm_next/cloud.py +++ b/openllm_next/cloud.py @@ -1,8 +1,10 @@ -import typer +import asyncio import json import subprocess -import asyncio + import questionary +import typer + from openllm_next.common import ERROR_STYLE, run_command from openllm_next.model import get_deploy_cmd diff --git a/openllm_next/common.py b/openllm_next/common.py index 3750f56c..b17d7a93 100644 --- a/openllm_next/common.py +++ b/openllm_next/common.py @@ -1,14 +1,14 @@ -import sys import functools -import os -import typing -from types import SimpleNamespace import json -from contextlib import contextmanager -import questionary -import subprocess +import os import pathlib +import subprocess +import sys +import typing +from contextlib import contextmanager +from types import SimpleNamespace +import questionary ERROR_STYLE = "red" SUCCESS_STYLE = "green" @@ -42,6 +42,14 @@ class ContextVar(typing.Generic[T]): def set(self, value): self._stack.append(value) + @contextmanager + def patch(self, value): + self._stack.append(value) + try: + yield + finally: + self._stack.pop() + VERBOSE_LEVEL = ContextVar(0) @@ -76,12 +84,18 @@ class RepoInfo(SimpleNamespace): def tolist(self): if VERBOSE_LEVEL.get() <= 0: - return self.name + return f"{self.name} ({self.url})" + if VERBOSE_LEVEL.get() <= 1: + return dict( + name=self.name, + url=self.url, + path=str(self.path), + ) if VERBOSE_LEVEL.get() <= 2: return dict( name=self.name, - path=str(self.path), url=self.url, + path=str(self.path), server=self.server, owner=self.owner, repo=self.repo, @@ -135,6 +149,8 @@ class BentoInfo(SimpleNamespace): def tolist(self): verbose = VERBOSE_LEVEL.get() if verbose <= 0: + return str(self) + if verbose <= 1: return dict( tag=self.tag, repo=self.repo.tolist(), @@ -168,7 +184,7 @@ def run_command( if env: for k, v in env.items(): questionary.print(f"$ export {k}={shlex.quote(v)}", style="bold") - questionary.print(f"> {' '.join(cmd)}", style="bold") + questionary.print(f"$ {' '.join(cmd)}", style="bold") if copy_env: env = {**os.environ, **env} if cmd and cmd[0] == "bentoml": diff --git a/openllm_next/model.py b/openllm_next/model.py index 2106f805..dc29bd23 100644 --- a/openllm_next/model.py +++ b/openllm_next/model.py @@ -1,20 +1,38 @@ -import typer import os +import typing -import questionary import pyaml -from openllm_next.common import ( - ERROR_STYLE, - load_config, - BentoInfo, -) -from openllm_next.repo import parse_repo_url +import questionary +import typer +from openllm_next.common import ERROR_STYLE, VERBOSE_LEVEL, BentoInfo, load_config +from openllm_next.repo import parse_repo_url app = typer.Typer() -def list_bento(tag: str | None = None) -> list[BentoInfo]: +@app.command() +def get(tag: str): + bento_info = pick_bento(tag) + if bento_info: + with VERBOSE_LEVEL.patch(1): + pyaml.pprint( + bento_info, + sort_dicts=False, + sort_keys=False, + ) + + +@app.command() +def list(): + pyaml.pprint( + list_bento(), + sort_dicts=False, + sort_keys=False, + ) + + +def list_bento(tag: str | None = None) -> typing.List[BentoInfo]: if tag is None: glob_pattern = "bentoml/bentos/*/*" elif ":" in tag: @@ -45,6 +63,7 @@ def list_bento(tag: str | None = None) -> list[BentoInfo]: model = None if model: model_list.append(model) + model_list.sort(key=lambda x: x.tag) return model_list @@ -64,15 +83,6 @@ def pick_bento(tag) -> BentoInfo: return model -@app.command() -def list(): - pyaml.pprint( - list_bento(), - sort_dicts=False, - sort_keys=False, - ) - - def get_serve_cmd(tag: str): if ":" not in tag: tag = f"{tag}:latest" @@ -119,14 +129,3 @@ def get_deploy_cmd(tag: str): raise typer.Exit(1) cmd += ["--env", f"{env_info['name']}={value}"] return cmd, env, None - - -@app.command() -def get(tag: str): - bento_info = pick_bento(tag) - if bento_info: - pyaml.pprint( - bento_info.tolist(), - sort_dicts=False, - sort_keys=False, - ) diff --git a/openllm_next/repo.py b/openllm_next/repo.py index 43d0e75a..2c93201d 100644 --- a/openllm_next/repo.py +++ b/openllm_next/repo.py @@ -1,90 +1,34 @@ +import re +import shutil +import subprocess + +import pyaml +import questionary import typer -import shutil -import questionary -import re -import subprocess -import pyaml from openllm_next.common import ( ERROR_STYLE, - SUCCESS_STYLE, REPO_DIR, - load_config, - save_config, - run_command, + SUCCESS_STYLE, RepoInfo, + load_config, + run_command, + save_config, ) - app = typer.Typer() -GIT_REPO_RE = re.compile( - r"git\+https://(?P.+)/(?P.+)/(?P.+?)(@(?P.+))?$" -) - - @app.command() def list(): config = load_config() pyaml.pprint( - config.repos, + [parse_repo_url(repo, name) for name, repo in config.repos.items()], sort_dicts=False, sort_keys=False, ) -def parse_repo_url(repo_url, repo_name=None) -> RepoInfo: - """ - parse the git repo url to server, owner, repo name, branch - >>> parse_repo_url("git+https://github.com/bojiang/bentovllm@main") - ('github.com', 'bojiang', 'bentovllm', 'main') - - >>> parse_repo_url("git+https://github.com/bojiang/bentovllm") - ('github.com', 'bojiang', 'bentovllm', 'main') - """ - match = GIT_REPO_RE.match(repo_url) - if not match: - raise ValueError(f"Invalid git repo url: {repo_url}") - server = match.group("server") - owner = match.group("owner") - repo = match.group("repo") - branch = match.group("branch") or "main" - path = REPO_DIR / server / owner / repo - return RepoInfo( - name=repo if repo_name is None else repo_name, - url=repo_url, - server=server, - owner=owner, - repo=repo, - branch=branch, - path=path, - ) - - -@app.command() -def add(name: str, repo: str): - name = name.lower() - if not name.isidentifier(): - questionary.print( - f"Invalid repo name: {name}, should only contain letters, numbers and underscores", - style=ERROR_STYLE, - ) - return - - config = load_config() - if name in config.repos: - override = questionary.confirm( - f"Repo {name} already exists({config.repos[name]}), override?" - ).ask() - if not override: - return - - config.repos[name] = repo - save_config(config) - questionary.print(f"Repo {name} added", style=SUCCESS_STYLE) - - @app.command() def remove(name: str): config = load_config() @@ -141,5 +85,61 @@ def update(): questionary.print("Repos updated", style=SUCCESS_STYLE) +GIT_REPO_RE = re.compile( + r"git\+https://(?P.+)/(?P.+)/(?P.+?)(@(?P.+))?$" +) + + +def parse_repo_url(repo_url, repo_name=None) -> RepoInfo: + """ + parse the git repo url to server, owner, repo name, branch + >>> parse_repo_url("git+https://github.com/bojiang/bentovllm@main") + ('github.com', 'bojiang', 'bentovllm', 'main') + + >>> parse_repo_url("git+https://github.com/bojiang/bentovllm") + ('github.com', 'bojiang', 'bentovllm', 'main') + """ + match = GIT_REPO_RE.match(repo_url) + if not match: + raise ValueError(f"Invalid git repo url: {repo_url}") + server = match.group("server") + owner = match.group("owner") + repo = match.group("repo") + branch = match.group("branch") or "main" + path = REPO_DIR / server / owner / repo + return RepoInfo( + name=repo if repo_name is None else repo_name, + url=repo_url, + server=server, + owner=owner, + repo=repo, + branch=branch, + path=path, + ) + + +@app.command() +def add(name: str, repo: str): + name = name.lower() + if not name.isidentifier(): + questionary.print( + f"Invalid repo name: {name}, should only contain letters, numbers and underscores", + style=ERROR_STYLE, + ) + return + + config = load_config() + if name in config.repos: + override = questionary.confirm( + f"Repo {name} already exists({config.repos[name]}), override?" + ).ask() + if not override: + return + + config.repos[name] = repo + save_config(config) + questionary.print(f"Repo {name} added", style=SUCCESS_STYLE) + + if __name__ == "__main__": app() diff --git a/openllm_next/serve.py b/openllm_next/serve.py index 6f874feb..cba519ad 100644 --- a/openllm_next/serve.py +++ b/openllm_next/serve.py @@ -1,8 +1,10 @@ -import typer -import subprocess import asyncio import os +import subprocess + import questionary +import typer + from openllm_next.common import run_command from openllm_next.model import get_serve_cmd From a17536c691d0b7d1b8f88dce799e6b058b51001d Mon Sep 17 00:00:00 2001 From: bojiang Date: Fri, 24 May 2024 04:51:22 +0800 Subject: [PATCH 033/125] feat: venv --- openllm_next/cloud.py | 3 + openllm_next/common.py | 67 +++++++++++++++++++--- openllm_next/model.py | 6 +- openllm_next/serve.py | 28 ++++++---- openllm_next/venv.py | 123 ++++++++++++++++++++++++++++++++++++++++- pyproject.toml | 1 - 6 files changed, 203 insertions(+), 25 deletions(-) diff --git a/openllm_next/cloud.py b/openllm_next/cloud.py index df16bf2f..56168b42 100644 --- a/openllm_next/cloud.py +++ b/openllm_next/cloud.py @@ -79,6 +79,7 @@ async def _run_model(model: str, timeout: int = 600): ) import bentoml + from httpx import ReadError try: questionary.print("Model loading...", style="green") @@ -92,6 +93,8 @@ async def _run_model(model: str, timeout: int = 600): break except bentoml.exceptions.BentoMLException: await asyncio.sleep(1) + except ReadError: + await asyncio.sleep(1) else: questionary.print("Model failed to load", style="red") return diff --git a/openllm_next/common.py b/openllm_next/common.py index b17d7a93..c9c49568 100644 --- a/openllm_next/common.py +++ b/openllm_next/common.py @@ -1,4 +1,5 @@ import functools +import hashlib import json import os import pathlib @@ -9,6 +10,7 @@ from contextlib import contextmanager from types import SimpleNamespace import questionary +import typer ERROR_STYLE = "red" SUCCESS_STYLE = "green" @@ -107,6 +109,9 @@ class BentoInfo(SimpleNamespace): repo: RepoInfo path: pathlib.Path + def __hash__(self): + return md5(str(self.path)) + @property def tag(self) -> str: return f"{self.path.parent.name}:{self.path.name}" @@ -166,17 +171,47 @@ class BentoInfo(SimpleNamespace): ) +@typing.overload def run_command( cmd, cwd=None, env=None, copy_env=True, + venv=None, silent=False, - check=True, -) -> subprocess.CompletedProcess | subprocess.Popen | None: + background: typing.Literal[False] = False, +) -> subprocess.CompletedProcess: ... + + +@typing.overload +def run_command( + cmd, + cwd=None, + env=None, + copy_env=True, + venv=None, + silent=False, + background: typing.Literal[True] = True, +) -> subprocess.Popen: ... + + +def run_command( + cmd, + cwd=None, + env=None, + copy_env=True, + venv=None, + silent=False, + background=False, +) -> subprocess.CompletedProcess | subprocess.Popen: + if background: + run_func = subprocess.Popen + else: + run_func = subprocess.run import shlex env = env or {} + cmd = [str(c) for c in cmd] if not silent: questionary.print("\n") if cwd: @@ -184,25 +219,41 @@ def run_command( if env: for k, v in env.items(): questionary.print(f"$ export {k}={shlex.quote(v)}", style="bold") + if venv: + questionary.print(f"$ source {venv / 'bin' / 'activate'}", style="bold") questionary.print(f"$ {' '.join(cmd)}", style="bold") + + if venv: + py = venv / "bin" / "python" + else: + py = sys.executable + if copy_env: env = {**os.environ, **env} + if cmd and cmd[0] == "bentoml": - cmd = [sys.executable, "-m", "bentoml"] + cmd[1:] + cmd = [py, "-m", "bentoml"] + cmd[1:] if cmd and cmd[0] == "python": - cmd = [sys.executable] + cmd[1:] + cmd = [py] + cmd[1:] + try: if silent: - return subprocess.run( + return run_func( # type: ignore cmd, cwd=cwd, env=env, - check=check, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, ) else: - return subprocess.run(cmd, cwd=cwd, env=env, check=check) + return run_func(cmd, cwd=cwd, env=env) except subprocess.CalledProcessError: questionary.print("Command failed", style=ERROR_STYLE) - return None + raise typer.Exit(1) + + +def md5(*strings: str) -> int: + m = hashlib.md5() + for s in strings: + m.update(s.encode()) + return int(m.hexdigest(), 16) diff --git a/openllm_next/model.py b/openllm_next/model.py index dc29bd23..cebcc4ee 100644 --- a/openllm_next/model.py +++ b/openllm_next/model.py @@ -7,6 +7,7 @@ import typer from openllm_next.common import ERROR_STYLE, VERBOSE_LEVEL, BentoInfo, load_config from openllm_next.repo import parse_repo_url +from openllm_next.venv import ensure_venv app = typer.Typer() @@ -83,10 +84,7 @@ def pick_bento(tag) -> BentoInfo: return model -def get_serve_cmd(tag: str): - if ":" not in tag: - tag = f"{tag}:latest" - bento = pick_bento(tag) +def get_serve_cmd(bento: BentoInfo): cmd = ["bentoml", "serve", bento.tag] env = { "BENTOML_HOME": f"{bento.repo.path}/bentoml", diff --git a/openllm_next/serve.py b/openllm_next/serve.py index cba519ad..17124455 100644 --- a/openllm_next/serve.py +++ b/openllm_next/serve.py @@ -1,30 +1,38 @@ import asyncio -import os -import subprocess import questionary import typer from openllm_next.common import run_command -from openllm_next.model import get_serve_cmd +from openllm_next.model import get_serve_cmd, pick_bento +from openllm_next.venv import ensure_venv app = typer.Typer() @app.command() def serve(model: str): - cmd, env, cwd = get_serve_cmd(model) - run_command(cmd, env=env, cwd=cwd) + if ":" not in model: + model = f"{model}:latest" + bento = pick_bento(model) + venv = ensure_venv(bento) + cmd, env, cwd = get_serve_cmd(bento) + run_command(cmd, env=env, cwd=cwd, venv=venv) async def _run_model(model: str, timeout: int = 600): - cmd, env, cwd = get_serve_cmd(model) - server_proc = subprocess.Popen( + if ":" not in model: + model = f"{model}:latest" + bento = pick_bento(model) + venv = ensure_venv(bento) + cmd, env, cwd = get_serve_cmd(bento) + server_proc = run_command( cmd, - env={**os.environ, **env}, + env=env, cwd=cwd, - stdout=subprocess.DEVNULL, - stderr=subprocess.DEVNULL, + venv=venv, + silent=True, + background=True, ) import bentoml diff --git a/openllm_next/venv.py b/openllm_next/venv.py index 254f7a86..a715036e 100644 --- a/openllm_next/venv.py +++ b/openllm_next/venv.py @@ -1,8 +1,20 @@ -def _resolve_package_versions(requirement: str) -> dict[str, str]: +import functools +import pathlib +import shutil +from types import SimpleNamespace +from typing import Iterable + +import questionary +import typer + +from openllm_next.common import VENV_DIR, VERBOSE_LEVEL, BentoInfo, md5, run_command + + +def _resolve_packages(requirement: str | pathlib.Path) -> dict[str, str]: from pip_requirements_parser import RequirementsFile requirements_txt = RequirementsFile.from_file( - requirement, + str(requirement), include_nested=True, ) deps: dict[str, str] = {} @@ -22,3 +34,110 @@ def _resolve_package_versions(requirement: str) -> dict[str, str]: deps[req.name] = req.line break return deps + + +class EnvSpec(SimpleNamespace): + python_version: str + python_packages: dict[str, str] + name_prefix = "" + + def __hash__(self): + return md5( + self.python_version, + *sorted(self.python_packages.values()), + ) + + +@functools.lru_cache +def _resolve_bento_env_specs(bento: BentoInfo): + ver_file = bento.path / "env" / "python" / "version.txt" + assert ver_file.exists(), f"cannot find version file in {bento.path}" + + lock_file = bento.path / "env" / "python" / "requirements.lock.txt" + if not lock_file.exists(): + lock_file = bento.path / "env" / "python" / "requirements.txt" + + python_packages = _resolve_packages(lock_file) + PREHEAT_PIP_PACKAGES = ["torch", "vllm"] + preheat_packages = { + k: v for k, v in python_packages.items() if k in PREHEAT_PIP_PACKAGES + } + ver = ver_file.read_text().strip() + return ( + EnvSpec( + python_version=ver, + python_packages=preheat_packages, + name_prefix=f"{bento.tag.replace(':', '_')}-1-", + ), + EnvSpec( + python_version=ver, + python_packages=python_packages, + name_prefix=f"{bento.tag.replace(':', '_')}-2-", + ), + ) + + +def _ensure_venv( + env_spec: EnvSpec, parrent_venv: pathlib.Path | None = None +) -> pathlib.Path: + venv = VENV_DIR / str(hash(env_spec)) + if not venv.exists(): + questionary.print(f"Installing model dependencies({venv})...", style="green") + try: + run_command(["python", "-m", "venv", venv], silent=VERBOSE_LEVEL.get() < 1) + pyver = next(venv.glob("lib/python*")).name + if parrent_venv is not None: + with open( + venv / "lib" / pyver / "site-packages" / f"{parrent_venv.name}.pth", + "w+", + ) as f: + f.write(str(parrent_venv / "lib" / pyver / "site-packages")) + with open(venv / "requirements.txt", "w") as f: + f.write("\n".join(sorted(env_spec.python_packages.values()))) + run_command( + [ + venv / "bin" / "pip", + "install", + "-r", + venv / "requirements.txt", + "--upgrade-strategy", + "only-if-needed", + ], + silent=VERBOSE_LEVEL.get() < 1, + ) + run_command( + [ + venv / "bin" / "pip", + "install", + "bentoml", + "--upgrade-strategy", + "only-if-needed", + "--upgrade", + ], + silent=VERBOSE_LEVEL.get() < 1, + ) + except Exception: + shutil.rmtree(venv, ignore_errors=True) + questionary.print( + f"Failed to install dependencies to {venv}. Cleaned up.", + style="red", + ) + raise typer.Exit(1) + questionary.print( + f"Successfully installed dependencies to {venv}.", style="green" + ) + return venv + else: + return venv + + +def _ensure_venvs(env_spec_list: Iterable[EnvSpec]) -> pathlib.Path: + last_venv = None + for env_spec in env_spec_list: + last_venv = _ensure_venv(env_spec, last_venv) + assert last_venv is not None + return last_venv + + +def ensure_venv(bento: BentoInfo) -> pathlib.Path: + return _ensure_venvs(_resolve_bento_env_specs(bento)) diff --git a/pyproject.toml b/pyproject.toml index 78a484d3..2ad37831 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -16,7 +16,6 @@ dependencies = [ "psutil", "pathlib", "pip_requirements_parser", - "venv", ] [tool.typer] From 5520d6b554e516f3bddd68eec44779a3003de8f0 Mon Sep 17 00:00:00 2001 From: bojiang Date: Mon, 27 May 2024 15:44:29 +0800 Subject: [PATCH 034/125] chore: add script --- openllm_next/__main__.py | 19 ++++++++++++------- pyproject.toml | 3 +++ 2 files changed, 15 insertions(+), 7 deletions(-) diff --git a/openllm_next/__main__.py b/openllm_next/__main__.py index c7d0083c..b51f07ab 100644 --- a/openllm_next/__main__.py +++ b/openllm_next/__main__.py @@ -1,10 +1,11 @@ import typer -from openllm_next.model import app as model_app -from openllm_next.repo import app as repo_app -from openllm_next.serve import serve as local_serve, run as local_run + from openllm_next.cloud import app as cloud_app from openllm_next.common import VERBOSE_LEVEL - +from openllm_next.model import app as model_app +from openllm_next.repo import app as repo_app +from openllm_next.serve import run as local_run +from openllm_next.serve import serve as local_serve app = typer.Typer() @@ -23,11 +24,15 @@ def run(model: str): local_run(model) -def main_callback(verbose: int = 0): +def typer_callback(verbose: int = 0): if verbose: VERBOSE_LEVEL.set(verbose) -if __name__ == "__main__": - app.callback()(main_callback) +def main(): + app.callback()(typer_callback) app() + + +if __name__ == "__main__": + main() diff --git a/pyproject.toml b/pyproject.toml index 2ad37831..e58a3ce3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -18,5 +18,8 @@ dependencies = [ "pip_requirements_parser", ] +[project.scripts] +openllm = "openllm_next.__main__:main" + [tool.typer] src-dir = "openllm_next" From 1f1059b74914c4ef7695bc23ba1f251ef9307ebc Mon Sep 17 00:00:00 2001 From: bojiang Date: Mon, 27 May 2024 16:04:38 +0800 Subject: [PATCH 035/125] fix: venv ignore python version --- openllm_next/venv.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/openllm_next/venv.py b/openllm_next/venv.py index a715036e..50683c60 100644 --- a/openllm_next/venv.py +++ b/openllm_next/venv.py @@ -43,7 +43,7 @@ class EnvSpec(SimpleNamespace): def __hash__(self): return md5( - self.python_version, + # self.python_version, *sorted(self.python_packages.values()), ) From c1fb00c4bdf6c4216551618378a686abc231f755 Mon Sep 17 00:00:00 2001 From: bojiang Date: Mon, 27 May 2024 16:40:31 +0800 Subject: [PATCH 036/125] chore: add more alias --- recipe.yaml | 69 ++++++++++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 68 insertions(+), 1 deletion(-) diff --git a/recipe.yaml b/recipe.yaml index 687c83a3..da0aa53c 100644 --- a/recipe.yaml +++ b/recipe.yaml @@ -36,6 +36,7 @@ chat_template: llama-2-chat "llama2:7b-chat-awq-4bit": alias: + - 7b-4bit - 7b-chat-4bit project: vllm-chat service_config: @@ -52,7 +53,9 @@ enforce_eager: true chat_template: llama-2-chat "mistral:7b-instruct-awq-4bit": - alias: [] + alias: + - 7b-4bit + - 7b-instruct-4bit project: vllm-chat service_config: name: mistral @@ -87,3 +90,67 @@ enforce_eager: true dtype: half chat_template: mistral-instruct +"llama3:8b-instruct-awq-4bit": + alias: + - 8b-4bit + - 8b-instruct-4bit + project: vllm-chat + service_config: + name: llama3 + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-rtx-3060 + engine_config: + model: casperhansen/llama-3-8b-instruct-awq + max_model_len: 2048 + quantization: awq +"llama3:70b-instruct-awq-4bit": + alias: + - 70b-4bit + - 70b-instruct-4bit + project: vllm-chat + service_config: + name: llama3 + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-a100-80g + engine_config: + model: meta-llama/Meta-Llama-3-8B + max_model_len: 2048 + quantization: awq +"llama3:8b-instruct-fp16": + alias: + - latest + - 8b + - 8b-instruct + project: vllm-chat + service_config: + name: llama3 + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-tesla-l4 + engine_config: + model: meta-llama/Meta-Llama-3-8B-Instruct + max_model_len: 2048 +"llama3:70b-instruct-fp16": + alias: + - latest + - 70b + - 70b-instruct + project: vllm-chat + service_config: + name: llama3 + traffic: + timeout: 300 + resources: + gpu: 2 + gpu_type: nvidia-a100-80g + engine_config: + model: meta-llama/Meta-Llama-3-70B-Instruct + max_model_len: 2048 From 609af2e1f00bc180e65b8c289c56504c65adaa3a Mon Sep 17 00:00:00 2001 From: bojiang Date: Mon, 27 May 2024 18:02:22 +0800 Subject: [PATCH 037/125] feat: add gemma --- recipe.yaml | 48 ++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 48 insertions(+) diff --git a/recipe.yaml b/recipe.yaml index da0aa53c..0c96714b 100644 --- a/recipe.yaml +++ b/recipe.yaml @@ -154,3 +154,51 @@ engine_config: model: meta-llama/Meta-Llama-3-70B-Instruct max_model_len: 2048 +"gemma:2b-instruct-fp16": + alias: + - latest + - 2b + - 2b-instruct + project: vllm-chat + service_config: + name: gemma + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-rtx-3060 + engine_config: + model: google/gemma-2b-it + max_model_len: 2048 +"gemma:7b-instruct-fp16": + alias: + - latest + - 7b + - 7b-instruct + project: vllm-chat + service_config: + name: gemma + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-tesla-l4 + engine_config: + model: google/gemma-7b-it + max_model_len: 2048 +"gemma:7b-instruct-awq-4bit": + alias: + - 7b-4bit + - 7b-instruct-4bit + project: vllm-chat + service_config: + name: gemma + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-rtx-3060 + engine_config: + model: casperhansen/gemma-7b-it-awq + max_model_len: 2048 + quantization: awq From a385e3262f52efbef2e82edd6c2584a1feb8bb8e Mon Sep 17 00:00:00 2001 From: bojiang Date: Mon, 27 May 2024 18:16:52 +0800 Subject: [PATCH 038/125] fix: replace gemma 7b awq chat_template --- recipe.yaml | 1 + 1 file changed, 1 insertion(+) diff --git a/recipe.yaml b/recipe.yaml index 0c96714b..6c6c451f 100644 --- a/recipe.yaml +++ b/recipe.yaml @@ -202,3 +202,4 @@ model: casperhansen/gemma-7b-it-awq max_model_len: 2048 quantization: awq + chat_template: gemma-it From 43439f77845f1faa66abdabe4ad6c1067f4f6a9e Mon Sep 17 00:00:00 2001 From: bojiang Date: Mon, 27 May 2024 18:23:40 +0800 Subject: [PATCH 039/125] chore: list models in tree view --- openllm_next/common.py | 8 ++++++++ openllm_next/model.py | 12 ++++++++---- 2 files changed, 16 insertions(+), 4 deletions(-) diff --git a/openllm_next/common.py b/openllm_next/common.py index c9c49568..e3210c23 100644 --- a/openllm_next/common.py +++ b/openllm_next/common.py @@ -116,6 +116,14 @@ class BentoInfo(SimpleNamespace): def tag(self) -> str: return f"{self.path.parent.name}:{self.path.name}" + @property + def name(self) -> str: + return self.path.parent.name + + @property + def version(self) -> str: + return self.path.name + @functools.cached_property def bento_yaml(self) -> dict: import yaml diff --git a/openllm_next/model.py b/openllm_next/model.py index cebcc4ee..a8c96a9b 100644 --- a/openllm_next/model.py +++ b/openllm_next/model.py @@ -1,3 +1,4 @@ +import collections import os import typing @@ -7,7 +8,6 @@ import typer from openllm_next.common import ERROR_STYLE, VERBOSE_LEVEL, BentoInfo, load_config from openllm_next.repo import parse_repo_url -from openllm_next.venv import ensure_venv app = typer.Typer() @@ -24,10 +24,14 @@ def get(tag: str): ) -@app.command() -def list(): +@app.command(name="list") +def list_(): + bentos = list_bento() + output: dict[str, list[str]] = collections.defaultdict(list) + for bento in bentos: + output[bento.name].append(bento.version) pyaml.pprint( - list_bento(), + output, sort_dicts=False, sort_keys=False, ) From c94a2e0cb0c1a974f915fa2d830111f85a86d0e5 Mon Sep 17 00:00:00 2001 From: bojiang Date: Wed, 29 May 2024 09:54:09 +0800 Subject: [PATCH 040/125] clean --- recipe.yaml | 20 +------------------- 1 file changed, 1 insertion(+), 19 deletions(-) diff --git a/recipe.yaml b/recipe.yaml index 6c6c451f..888e7008 100644 --- a/recipe.yaml +++ b/recipe.yaml @@ -1,8 +1,6 @@ "phi3:3.8b-mini-instruct-4k-fp16": alias: - - latest - 3.8b - - instruct - mini project: vllm-chat service_config: @@ -11,7 +9,7 @@ timeout: 300 resources: gpu: 1 - gpu_type: nvidia-tesla-t4 + gpu_type: nvidia-rtx-3060 engine_config: model: microsoft/Phi-3-mini-4k-instruct max_model_len: 4096 @@ -19,9 +17,7 @@ chat_template: phi-3 "llama2:7b-chat-fp16": alias: - - latest - 7b - - 7b-chat project: vllm-chat service_config: name: llama2 @@ -37,7 +33,6 @@ "llama2:7b-chat-awq-4bit": alias: - 7b-4bit - - 7b-chat-4bit project: vllm-chat service_config: name: llama2 @@ -55,7 +50,6 @@ "mistral:7b-instruct-awq-4bit": alias: - 7b-4bit - - 7b-instruct-4bit project: vllm-chat service_config: name: mistral @@ -75,7 +69,6 @@ alias: - 7b - 7b-instruct - - 7b-instruct-v0.1 project: vllm-chat service_config: name: mistral @@ -93,7 +86,6 @@ "llama3:8b-instruct-awq-4bit": alias: - 8b-4bit - - 8b-instruct-4bit project: vllm-chat service_config: name: llama3 @@ -109,7 +101,6 @@ "llama3:70b-instruct-awq-4bit": alias: - 70b-4bit - - 70b-instruct-4bit project: vllm-chat service_config: name: llama3 @@ -124,9 +115,7 @@ quantization: awq "llama3:8b-instruct-fp16": alias: - - latest - 8b - - 8b-instruct project: vllm-chat service_config: name: llama3 @@ -140,9 +129,7 @@ max_model_len: 2048 "llama3:70b-instruct-fp16": alias: - - latest - 70b - - 70b-instruct project: vllm-chat service_config: name: llama3 @@ -156,9 +143,7 @@ max_model_len: 2048 "gemma:2b-instruct-fp16": alias: - - latest - 2b - - 2b-instruct project: vllm-chat service_config: name: gemma @@ -172,9 +157,7 @@ max_model_len: 2048 "gemma:7b-instruct-fp16": alias: - - latest - 7b - - 7b-instruct project: vllm-chat service_config: name: gemma @@ -189,7 +172,6 @@ "gemma:7b-instruct-awq-4bit": alias: - 7b-4bit - - 7b-instruct-4bit project: vllm-chat service_config: name: gemma From 6be3377c831161b05730bad912c8da83e1837961 Mon Sep 17 00:00:00 2001 From: bojiang Date: Thu, 30 May 2024 11:55:06 +0800 Subject: [PATCH 041/125] use pure python git --- openllm_next/__main__.py | 4 +- openllm_next/accelerator_spec.py | 99 +++++++++++++++++++++++++++++++- openllm_next/common.py | 12 ++-- openllm_next/repo.py | 43 ++++++++------ openllm_next/serve.py | 22 ++++++- pyproject.toml | 6 ++ 6 files changed, 158 insertions(+), 28 deletions(-) diff --git a/openllm_next/__main__.py b/openllm_next/__main__.py index b51f07ab..5fcdb654 100644 --- a/openllm_next/__main__.py +++ b/openllm_next/__main__.py @@ -1,3 +1,5 @@ +from typing import Annotated + import typer from openllm_next.cloud import app as cloud_app @@ -20,7 +22,7 @@ def serve(model: str): @app.command() -def run(model: str): +def run(model: Annotated[str, typer.Argument()] = ""): local_run(model) diff --git a/openllm_next/accelerator_spec.py b/openllm_next/accelerator_spec.py index 798b4c31..904a3bba 100644 --- a/openllm_next/accelerator_spec.py +++ b/openllm_next/accelerator_spec.py @@ -1,4 +1,27 @@ -ACCELERATOR_SPEC = { +import math +import typing +from types import SimpleNamespace + + +class ACC_SPEC(SimpleNamespace): + model: str + memory_size: float + + def __gt__(self, other): + return self.memory_size > other.memory_size + + def __eq__(self, other): + return self.memory_size == other.memory_size + + +class Resource(SimpleNamespace): + cpu: int + memory: float + gpu: int + gpu_type: str + + +ACCELERATOR_SPEC_DICT: dict[str, dict] = { "nvidia-gtx-1650": {"model": "GTX 1650", "memory_size": 4.0}, "nvidia-gtx-1060": {"model": "GTX 1060", "memory_size": 6.0}, "nvidia-gtx-1080-ti": {"model": "GTX 1080 Ti", "memory_size": 11.0}, @@ -8,13 +31,85 @@ ACCELERATOR_SPEC = { "nvidia-rtx-3080": {"model": "RTX 3080", "memory_size": 10.0}, "nvidia-rtx-3080-ti": {"model": "RTX 3080 Ti", "memory_size": 12.0}, "nvidia-rtx-3090": {"model": "RTX 3090", "memory_size": 24.0}, + "nvidia-rtx-4070-ti": {"model": "RTX 4070 Ti", "memory_size": 12.0}, "nvidia-tesla-p4": {"model": "P4", "memory_size": 8.0}, "nvidia-tesla-p100": {"model": "P100", "memory_size": 16.0}, "nvidia-tesla-k80": {"model": "K80", "memory_size": 12.0}, "nvidia-tesla-t4": {"model": "T4", "memory_size": 16.0}, "nvidia-tesla-v100": {"model": "V100", "memory_size": 16.0}, "nvidia-l4": {"model": "L4", "memory_size": 24.0}, + "nvidia-tesla-l4": {"model": "L4", "memory_size": 24.0}, "nvidia-tesla-a10g": {"model": "A10G", "memory_size": 24.0}, - "nvidia-a100-80gb": {"model": "A100", "memory_size": 80.0}, + "nvidia-a100-80g": {"model": "A100", "memory_size": 80.0}, "nvidia-tesla-a100": {"model": "A100", "memory_size": 40.0}, } + + +ACCELERATOR_SPECS: dict[str, ACC_SPEC] = { + key: ACC_SPEC(**value) for key, value in ACCELERATOR_SPEC_DICT.items() +} + + +class MACHINE_SPEC(SimpleNamespace): + source: str = "local" + accelerators: list[ACC_SPEC] + + +def get_local_machine_spec(): + from pynvml import ( + nvmlDeviceGetCount, + nvmlDeviceGetHandleByIndex, + nvmlDeviceGetMemoryInfo, + nvmlDeviceGetName, + nvmlInit, + nvmlShutdown, + ) + + nvmlInit() + device_count = nvmlDeviceGetCount() + accelerators: list[ACC_SPEC] = [] + for i in range(device_count): + handle = nvmlDeviceGetHandleByIndex(i) + name = nvmlDeviceGetName(handle) + memory_info = nvmlDeviceGetMemoryInfo(handle) + accelerators.append( + ACC_SPEC(name=name, memory_size=math.ceil(int(memory_info.total) / 1024**3)) + ) + nvmlShutdown() + return MACHINE_SPEC(accelerators=accelerators, source="local") + + +def _machine_match_score(resource_spec: Resource, machine: MACHINE_SPEC) -> float: + if resource_spec.gpu > 0: + required_gpu = ACCELERATOR_SPECS[resource_spec.gpu_type] + filtered_accelerators = [ + ac + for ac in machine.accelerators + if ac.memory_size >= required_gpu.memory_size + ] + if resource_spec.gpu > len(filtered_accelerators): + return 0.0 + return ( + required_gpu.memory_size + * resource_spec.gpu + / sum(ac.memory_size for ac in machine.accelerators) + ) + if machine.accelerators: + return 0.01 / sum(ac.memory_size for ac in machine.accelerators) + return 1.0 + + +def match_machines( + resource_specs: list[Resource | dict], + machines: list[MACHINE_SPEC] | None = None, +): + if resource_specs and isinstance(resource_specs[0], dict): + resource_specs = [Resource(**spec) for spec in resource_specs] + if machines is None: + machines = [get_local_machine_spec()] + + return [ + (resource_spec, machine, _machine_match_score(resource_spec, machine)) + for machine in machines + for resource_spec in resource_specs + ] diff --git a/openllm_next/common.py b/openllm_next/common.py index e3210c23..38af008a 100644 --- a/openllm_next/common.py +++ b/openllm_next/common.py @@ -109,6 +109,12 @@ class BentoInfo(SimpleNamespace): repo: RepoInfo path: pathlib.Path + def __str__(self): + if self.repo.name == "default": + return f"{self.tag}" + else: + return f"{self.tag} ({self.repo.name})" + def __hash__(self): return md5(str(self.path)) @@ -153,12 +159,6 @@ class BentoInfo(SimpleNamespace): return pretty_yaml return self.bento_yaml - def __str__(self): - if self.repo.name == "default": - return f"{self.tag}" - else: - return f"{self.tag} ({self.repo.name})" - def tolist(self): verbose = VERBOSE_LEVEL.get() if verbose <= 0: diff --git a/openllm_next/repo.py b/openllm_next/repo.py index 2c93201d..f61b504d 100644 --- a/openllm_next/repo.py +++ b/openllm_next/repo.py @@ -1,6 +1,6 @@ import re import shutil -import subprocess +import time import pyaml import questionary @@ -12,7 +12,6 @@ from openllm_next.common import ( SUCCESS_STYLE, RepoInfo, load_config, - run_command, save_config, ) @@ -43,36 +42,47 @@ def remove(name: str): @app.command() def update(): + import dulwich + import dulwich.errors + import dulwich.porcelain + config = load_config() repos_in_use = set() for repo_name, repo in config.repos.items(): repo = parse_repo_url(repo, repo_name) repos_in_use.add((repo.server, repo.owner, repo.repo)) + if repo.path.exists(): # TODO: use update instead of remove and clone + shutil.rmtree(repo.path, ignore_errors=True) if not repo.path.exists(): repo.path.parent.mkdir(parents=True, exist_ok=True) try: - cmd = [ - "git", - "clone", - "--branch", - repo.branch, + dulwich.porcelain.clone( f"https://{repo.server}/{repo.owner}/{repo.repo}.git", str(repo.path), - ] - run_command(cmd) - except subprocess.CalledProcessError: + checkout=True, + depth=1, + branch=repo.branch, + ) + questionary.print("") + questionary.print(f"Repo `{repo.name}` updated", style=SUCCESS_STYLE) + except: shutil.rmtree(repo.path, ignore_errors=True) questionary.print( f"Failed to clone repo {repo.name}", style=ERROR_STYLE ) else: try: - cmd = ["git", "fetch", "origin", repo.branch] - run_command(cmd, cwd=repo.path) - cmd = ["git", "reset", "--hard", f"origin/{repo.branch}"] - run_command(cmd, cwd=repo.path) - cmd = ["git", "clean", "-fdx"] - run_command(cmd, cwd=repo.path) + import dulwich.porcelain + + dulwich.porcelain.pull( + str(repo.path), + f"https://{repo.server}/{repo.owner}/{repo.repo}.git", + refspecs=repo.branch, + force=True, + ) + dulwich.porcelain.clean(str(repo.path), str(repo.path)) + questionary.print("") + questionary.print(f"Repo `{repo.name}` updated", style=SUCCESS_STYLE) except: shutil.rmtree(repo.path, ignore_errors=True) questionary.print( @@ -82,7 +92,6 @@ def update(): if tuple(c.parts[-3:]) not in repos_in_use: shutil.rmtree(c, ignore_errors=True) questionary.print(f"Removed unused repo cache {c}") - questionary.print("Repos updated", style=SUCCESS_STYLE) GIT_REPO_RE = re.compile( diff --git a/openllm_next/serve.py b/openllm_next/serve.py index 17124455..82ec4b38 100644 --- a/openllm_next/serve.py +++ b/openllm_next/serve.py @@ -3,8 +3,9 @@ import asyncio import questionary import typer +from openllm_next.accelerator_spec import match_machines from openllm_next.common import run_command -from openllm_next.model import get_serve_cmd, pick_bento +from openllm_next.model import get_serve_cmd, list_bento, pick_bento from openllm_next.venv import ensure_venv app = typer.Typer() @@ -78,5 +79,22 @@ async def _run_model(model: str, timeout: int = 600): @app.command() -def run(model: str): +def run(model: str = ""): + if not model: + models = list_bento() + matchs = match_machines( + [b.bento_yaml["services"][0]["config"]["resources"] for b in models] + ) + selected = questionary.select( + "Select a model to run", + choices=[ + questionary.Choice( + f"{model.name}:{model.version} ({'local' if match[2] > 0 else 'cloud'})", + model, + ) + for model, match in zip(models, matchs) + if match[2] > 0 + ], + ).ask() + return asyncio.run(_run_model(model)) diff --git a/pyproject.toml b/pyproject.toml index e58a3ce3..a7adce3d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -16,6 +16,8 @@ dependencies = [ "psutil", "pathlib", "pip_requirements_parser", + "nvidia-ml-py", + "dulwich", ] [project.scripts] @@ -23,3 +25,7 @@ openllm = "openllm_next.__main__:main" [tool.typer] src-dir = "openllm_next" + +[tool.isort] +multi_line_output = 3 +include_trailing_comma = true From 2099f3a6f20511f9cfef151e25d3a2366afd48a1 Mon Sep 17 00:00:00 2001 From: bojiang Date: Thu, 30 May 2024 14:03:22 +0800 Subject: [PATCH 042/125] pre select bento --- openllm_next/__main__.py | 57 +++++++++++++++++++++++++++-- openllm_next/accelerator_spec.py | 53 ++++++++++++++++----------- openllm_next/cloud.py | 54 +++++++++++++++++++++------ openllm_next/common.py | 2 +- openllm_next/{serve.py => local.py} | 51 ++++++++------------------ openllm_next/model.py | 54 ++++----------------------- openllm_next/repo.py | 1 - 7 files changed, 152 insertions(+), 120 deletions(-) rename openllm_next/{serve.py => local.py} (59%) diff --git a/openllm_next/__main__.py b/openllm_next/__main__.py index 5fcdb654..3d702cfa 100644 --- a/openllm_next/__main__.py +++ b/openllm_next/__main__.py @@ -1,13 +1,16 @@ from typing import Annotated +import questionary import typer +from openllm_next.accelerator_spec import match_deployment_target from openllm_next.cloud import app as cloud_app from openllm_next.common import VERBOSE_LEVEL +from openllm_next.local import run as local_run +from openllm_next.local import serve as local_serve from openllm_next.model import app as model_app +from openllm_next.model import list_bento from openllm_next.repo import app as repo_app -from openllm_next.serve import run as local_run -from openllm_next.serve import serve as local_serve app = typer.Typer() @@ -16,14 +19,60 @@ app.add_typer(model_app, name="model") app.add_typer(cloud_app, name="cloud") +def _pre_select(model: str): + bentos = list_bento(model) + if len(bentos) == 0: + typer.echo(f"No model found for {model}", err=True) + raise typer.Exit(1) + matchs = match_deployment_target(bentos) + if len(bentos) == 1: + bento = bentos[0] + else: + choices = [] + # bentos that can be run locally + choices += [questionary.Separator("Local available models")] + choices += [ + questionary.Choice( + f" {bento.name}:{bento.version}", + bento, + ) + for bento, targets in matchs.items() + if targets + ] + choices += [questionary.Separator("Cloud available models")] + choices += [ + questionary.Choice( + f" {bento.name}:{bento.version}", + bento, + ) + for bento, targets in matchs.items() + if not targets + ] + + bento = questionary.select( + "Select a model to run", + choices=choices, + ).ask() + if not bento: + questionary.print("No model selected", style="red") + raise typer.Exit(1) + return bento, matchs[bento] + + @app.command() def serve(model: str): - local_serve(model) + bento, targets = _pre_select(model) + local_serve(bento) @app.command() def run(model: Annotated[str, typer.Argument()] = ""): - local_run(model) + bento, targets = _pre_select(model) + if targets: + local_run(bento) + else: + typer.echo("No local available deployment target found", err=True) + raise typer.Exit(1) def typer_callback(verbose: int = 0): diff --git a/openllm_next/accelerator_spec.py b/openllm_next/accelerator_spec.py index 904a3bba..c9aa852c 100644 --- a/openllm_next/accelerator_spec.py +++ b/openllm_next/accelerator_spec.py @@ -1,7 +1,10 @@ +from __future__ import annotations + import math -import typing from types import SimpleNamespace +from openllm_next.common import BentoInfo + class ACC_SPEC(SimpleNamespace): model: str @@ -50,7 +53,7 @@ ACCELERATOR_SPECS: dict[str, ACC_SPEC] = { } -class MACHINE_SPEC(SimpleNamespace): +class DeploymentTarget(SimpleNamespace): source: str = "local" accelerators: list[ACC_SPEC] @@ -76,15 +79,15 @@ def get_local_machine_spec(): ACC_SPEC(name=name, memory_size=math.ceil(int(memory_info.total) / 1024**3)) ) nvmlShutdown() - return MACHINE_SPEC(accelerators=accelerators, source="local") + return DeploymentTarget(accelerators=accelerators, source="local") -def _machine_match_score(resource_spec: Resource, machine: MACHINE_SPEC) -> float: +def _score(resource_spec: Resource, target: DeploymentTarget) -> float: if resource_spec.gpu > 0: required_gpu = ACCELERATOR_SPECS[resource_spec.gpu_type] filtered_accelerators = [ ac - for ac in machine.accelerators + for ac in target.accelerators if ac.memory_size >= required_gpu.memory_size ] if resource_spec.gpu > len(filtered_accelerators): @@ -92,24 +95,32 @@ def _machine_match_score(resource_spec: Resource, machine: MACHINE_SPEC) -> floa return ( required_gpu.memory_size * resource_spec.gpu - / sum(ac.memory_size for ac in machine.accelerators) + / sum(ac.memory_size for ac in target.accelerators) ) - if machine.accelerators: - return 0.01 / sum(ac.memory_size for ac in machine.accelerators) + if target.accelerators: + return 0.01 / sum(ac.memory_size for ac in target.accelerators) return 1.0 -def match_machines( - resource_specs: list[Resource | dict], - machines: list[MACHINE_SPEC] | None = None, -): - if resource_specs and isinstance(resource_specs[0], dict): - resource_specs = [Resource(**spec) for spec in resource_specs] - if machines is None: - machines = [get_local_machine_spec()] +def _multi_score( + resource_spec: Resource, + targets: list[DeploymentTarget], +) -> list[tuple[DeploymentTarget, float]]: + results = [(target, _score(resource_spec, target)) for target in targets] + return [(target, score) for target, score in results if score > 0.0] - return [ - (resource_spec, machine, _machine_match_score(resource_spec, machine)) - for machine in machines - for resource_spec in resource_specs - ] + +def match_deployment_target( + bentos: list[BentoInfo], + targets: list[DeploymentTarget] | None = None, +): + if targets is None: + targets = [get_local_machine_spec()] + + return { + bento: _multi_score( + Resource(**(bento.bento_yaml["services"][0]["config"]["resources"])), + targets, + ) + for bento in bentos + } diff --git a/openllm_next/cloud.py b/openllm_next/cloud.py index 56168b42..b346b578 100644 --- a/openllm_next/cloud.py +++ b/openllm_next/cloud.py @@ -1,16 +1,50 @@ import asyncio import json +import os import subprocess import questionary import typer -from openllm_next.common import ERROR_STYLE, run_command -from openllm_next.model import get_deploy_cmd +from openllm_next.common import ERROR_STYLE, BentoInfo, run_command +from openllm_next.model import pick_bento app = typer.Typer() +def _get_deploy_cmd(bento: BentoInfo): + cmd = ["bentoml", "deploy", bento.tag] + env = { + "BENTOML_HOME": f"{bento.repo.path}/bentoml", + } + + required_envs = bento.bento_yaml.get("envs", []) + required_env_names = [env["name"] for env in required_envs if "name" in env] + if required_env_names: + questionary.print( + f"This model requires the following environment variables to run: {repr(required_env_names)}", + style="yellow", + ) + + for env_info in bento.bento_yaml.get("envs", []): + if "name" not in env_info: + continue + if os.environ.get(env_info["name"]): + default = os.environ[env_info["name"]] + elif "value" in env_info: + default = env_info["value"] + else: + default = "" + value = questionary.text( + f"{env_info['name']}:", + default=default, + ).ask() + if value is None: + raise typer.Exit(1) + cmd += ["--env", f"{env_info['name']}={value}"] + return cmd, env, None + + def _ensure_cloud_context(): cmd = ["bentoml", "cloud", "current-context"] try: @@ -60,16 +94,15 @@ def _ensure_cloud_context(): raise typer.Exit(1) -@app.command() -def serve(model: str): +def serve(bento: BentoInfo): _ensure_cloud_context() - cmd, env, cwd = get_deploy_cmd(model) + cmd, env, cwd = _get_deploy_cmd(bento) run_command(cmd, env=env, cwd=cwd) -async def _run_model(model: str, timeout: int = 600): +async def _run_model(bento: BentoInfo, timeout: int = 600): _ensure_cloud_context() - cmd, env, cwd = get_deploy_cmd(model) + cmd, env, cwd = _get_deploy_cmd(bento) server_proc = subprocess.Popen( cmd, env=env, @@ -103,7 +136,7 @@ async def _run_model(model: str, timeout: int = 600): messages = [] while True: try: - message = input("uesr: ") + message = input("user: ") messages.append(dict(role="user", content=message)) print("assistant: ", end="") assistant_message = "" @@ -121,6 +154,5 @@ async def _run_model(model: str, timeout: int = 600): questionary.print("Stopped model server", style="green") -@app.command() -def run(model: str): - asyncio.run(_run_model(model)) +def run(bento: BentoInfo): + asyncio.run(_run_model(bento)) diff --git a/openllm_next/common.py b/openllm_next/common.py index 38af008a..92c5dc72 100644 --- a/openllm_next/common.py +++ b/openllm_next/common.py @@ -113,7 +113,7 @@ class BentoInfo(SimpleNamespace): if self.repo.name == "default": return f"{self.tag}" else: - return f"{self.tag} ({self.repo.name})" + return f"{self.repo.name}/{self.tag}" def __hash__(self): return md5(str(self.path)) diff --git a/openllm_next/serve.py b/openllm_next/local.py similarity index 59% rename from openllm_next/serve.py rename to openllm_next/local.py index 82ec4b38..5cb8c281 100644 --- a/openllm_next/serve.py +++ b/openllm_next/local.py @@ -3,30 +3,29 @@ import asyncio import questionary import typer -from openllm_next.accelerator_spec import match_machines -from openllm_next.common import run_command -from openllm_next.model import get_serve_cmd, list_bento, pick_bento +from openllm_next.common import BentoInfo, run_command from openllm_next.venv import ensure_venv app = typer.Typer() -@app.command() -def serve(model: str): - if ":" not in model: - model = f"{model}:latest" - bento = pick_bento(model) +def _get_serve_cmd(bento: BentoInfo): + cmd = ["bentoml", "serve", bento.tag] + env = { + "BENTOML_HOME": f"{bento.repo.path}/bentoml", + } + return cmd, env, None + + +def serve(bento: BentoInfo): venv = ensure_venv(bento) - cmd, env, cwd = get_serve_cmd(bento) + cmd, env, cwd = _get_serve_cmd(bento) run_command(cmd, env=env, cwd=cwd, venv=venv) -async def _run_model(model: str, timeout: int = 600): - if ":" not in model: - model = f"{model}:latest" - bento = pick_bento(model) +async def _run_model(bento: BentoInfo, timeout: int = 600): venv = ensure_venv(bento) - cmd, env, cwd = get_serve_cmd(bento) + cmd, env, cwd = _get_serve_cmd(bento) server_proc = run_command( cmd, env=env, @@ -58,7 +57,7 @@ async def _run_model(model: str, timeout: int = 600): messages = [] while True: try: - message = input("uesr: ") + message = input("user: ") messages.append(dict(role="user", content=message)) print("assistant: ", end="") assistant_message = "" @@ -78,23 +77,5 @@ async def _run_model(model: str, timeout: int = 600): questionary.print("Stopped model server", style="green") -@app.command() -def run(model: str = ""): - if not model: - models = list_bento() - matchs = match_machines( - [b.bento_yaml["services"][0]["config"]["resources"] for b in models] - ) - selected = questionary.select( - "Select a model to run", - choices=[ - questionary.Choice( - f"{model.name}:{model.version} ({'local' if match[2] > 0 else 'cloud'})", - model, - ) - for model, match in zip(models, matchs) - if match[2] > 0 - ], - ).ask() - return - asyncio.run(_run_model(model)) +def run(bento: BentoInfo): + asyncio.run(_run_model(bento)) diff --git a/openllm_next/model.py b/openllm_next/model.py index a8c96a9b..f8c07088 100644 --- a/openllm_next/model.py +++ b/openllm_next/model.py @@ -6,7 +6,12 @@ import pyaml import questionary import typer -from openllm_next.common import ERROR_STYLE, VERBOSE_LEVEL, BentoInfo, load_config +from openllm_next.common import ( + ERROR_STYLE, + VERBOSE_LEVEL, + BentoInfo, + load_config, +) from openllm_next.repo import parse_repo_url app = typer.Typer() @@ -38,7 +43,7 @@ def list_(): def list_bento(tag: str | None = None) -> typing.List[BentoInfo]: - if tag is None: + if not tag: glob_pattern = "bentoml/bentos/*/*" elif ":" in tag: repo_name, version = tag.split(":") @@ -86,48 +91,3 @@ def pick_bento(tag) -> BentoInfo: if model is None: raise typer.Exit(1) return model - - -def get_serve_cmd(bento: BentoInfo): - cmd = ["bentoml", "serve", bento.tag] - env = { - "BENTOML_HOME": f"{bento.repo.path}/bentoml", - } - return cmd, env, None - - -def get_deploy_cmd(tag: str): - if ":" not in tag: - tag = f"{tag}:latest" - bento = pick_bento(tag) - - cmd = ["bentoml", "deploy", bento.tag] - env = { - "BENTOML_HOME": f"{bento.repo.path}/bentoml", - } - - required_envs = bento.bento_yaml.get("envs", []) - required_env_names = [env["name"] for env in required_envs if "name" in env] - if required_env_names: - questionary.print( - f"This model requires the following environment variables to run: {repr(required_env_names)}", - style="yellow", - ) - - for env_info in bento.bento_yaml.get("envs", []): - if "name" not in env_info: - continue - if os.environ.get(env_info["name"]): - default = os.environ[env_info["name"]] - elif "value" in env_info: - default = env_info["value"] - else: - default = "" - value = questionary.text( - f"{env_info['name']}:", - default=default, - ).ask() - if value is None: - raise typer.Exit(1) - cmd += ["--env", f"{env_info['name']}={value}"] - return cmd, env, None diff --git a/openllm_next/repo.py b/openllm_next/repo.py index f61b504d..f74d2116 100644 --- a/openllm_next/repo.py +++ b/openllm_next/repo.py @@ -1,6 +1,5 @@ import re import shutil -import time import pyaml import questionary From a3cc7544d8e4a10e30d1819904f4d18e103f53f5 Mon Sep 17 00:00:00 2001 From: bojiang Date: Fri, 31 May 2024 21:19:16 +0800 Subject: [PATCH 043/125] add chattts --- chattts/.bentoignore | 6 ++ chattts/ChatTTS | 1 + chattts/README.md | 141 +++++++++++++++++++++++++++++++++++++ chattts/bento_constants.py | 9 +++ chattts/bentofile.yaml | 13 ++++ chattts/requirements.txt | 13 ++++ chattts/service.py | 55 +++++++++++++++ 7 files changed, 238 insertions(+) create mode 100644 chattts/.bentoignore create mode 160000 chattts/ChatTTS create mode 100644 chattts/README.md create mode 100644 chattts/bento_constants.py create mode 100644 chattts/bentofile.yaml create mode 100644 chattts/requirements.txt create mode 100644 chattts/service.py diff --git a/chattts/.bentoignore b/chattts/.bentoignore new file mode 100644 index 00000000..fc8bfa41 --- /dev/null +++ b/chattts/.bentoignore @@ -0,0 +1,6 @@ +__pycache__/ +*.py[cod] +*$py.class +.ipynb_checkpoints +venv/ +ChatTTS/ diff --git a/chattts/ChatTTS b/chattts/ChatTTS new file mode 160000 index 00000000..a80439e2 --- /dev/null +++ b/chattts/ChatTTS @@ -0,0 +1 @@ +Subproject commit a80439e2a45a0b76e03b0e2cabe667c763d7ec97 diff --git a/chattts/README.md b/chattts/README.md new file mode 100644 index 00000000..8796f668 --- /dev/null +++ b/chattts/README.md @@ -0,0 +1,141 @@ +
+

Self-host Llama 2 7B with vLLM and BentoML

+
+ +This is a BentoML example project, showing you how to serve and deploy Llama 2 7B using [vLLM](https://vllm.ai), a high-throughput and memory-efficient inference engine. + +See [here](https://github.com/bentoml/BentoML?tab=readme-ov-file#%EF%B8%8F-what-you-can-build-with-bentoml) for a full list of BentoML example projects. + +💡 This example is served as a basis for advanced code customization, such as custom model, inference logic or vLLM options. For simple LLM hosting with OpenAI compatible endpoint without writing any code, see [OpenLLM](https://github.com/bentoml/OpenLLM). + + +## Prerequisites + +- You have installed Python 3.8+ and `pip`. See the [Python downloads page](https://www.python.org/downloads/) to learn more. +- You have a basic understanding of key concepts in BentoML, such as Services. We recommend you read [Quickstart](https://docs.bentoml.com/en/1.2/get-started/quickstart.html) first. +- You have gained access to Llama 2 7B on [its official website](https://llama.meta.com/) and [Hugging Face](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf). +- If you want to test the Service locally, you need a Nvidia GPU with at least 16G VRAM. +- (Optional) We recommend you create a virtual environment for dependency isolation for this project. See the [Conda documentation](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) or the [Python documentation](https://docs.python.org/3/library/venv.html) for details. + +## Install dependencies + +```bash +git clone https://github.com/bentoml/BentoVLLM.git +cd BentoVLLM/llama2-7b-chat +pip install -r requirements.txt && pip install -f -U "pydantic>=2.0" +``` + +## Download the model + +```bash +python import_model.py +``` + +## Run the BentoML Service + +We have defined a BentoML Service in `service.py`. Run `bentoml serve` in your project directory to start the Service. + +```python +$ bentoml serve . + +2024-01-18T07:51:30+0800 [INFO] [cli] Starting production HTTP BentoServer from "service:VLLM" listening on http://localhost:3000 (Press CTRL+C to quit) +INFO 01-18 07:51:40 model_runner.py:501] Capturing the model for CUDA graphs. This may lead to unexpected consequences if the model is not static. To run the model in eager mode, set 'enforce_eager=True' or use '--enforce-eager' in the CLI. +INFO 01-18 07:51:40 model_runner.py:505] CUDA graphs can take additional 1~3 GiB memory per GPU. If you are running out of memory, consider decreasing `gpu_memory_utilization` or enforcing eager mode. +INFO 01-18 07:51:46 model_runner.py:547] Graph capturing finished in 6 secs. +``` + +The server is now active at [http://localhost:3000](http://localhost:3000/). You can interact with it using the Swagger UI or in other different ways. + +
+ +CURL + +```bash +curl -X 'POST' \ + 'http://localhost:3000/generate' \ + -H 'accept: text/event-stream' \ + -H 'Content-Type: application/json' \ + -d '{ + "prompt": "Explain superconductors like I'\''m five years old", + "tokens": null +}' +``` + +
+ +
+ +Python client + +```python +import bentoml + +with bentoml.SyncHTTPClient("http://localhost:3000") as client: + response_generator = client.generate( + prompt="Explain superconductors like I'm five years old", + tokens=None + ) + for response in response_generator: + print(response) +``` + +
+ +
+ +OpenAI-compatible endpoints + +This Service uses the `@openai_endpoints` decorator to set up OpenAI-compatible endpoints (`chat/completions` and `completions`). This means your client can interact with the backend Service (in this case, the VLLM class) as if they were communicating directly with OpenAI's API. This [utility](bentovllm_openai/) does not affect your BentoML Service code, and you can use it for other LLMs as well. + +```python +from openai import OpenAI + +client = OpenAI(base_url='http://localhost:3000/v1', api_key='na') + +# Use the following func to get the available models +client.models.list() + +chat_completion = client.chat.completions.create( + model="meta-llama/Llama-2-7b-chat-hf", + messages=[ + { + "role": "user", + "content": "Explain superconductors like I'm five years old" + } + ], + stream=True, +) +for chunk in chat_completion: + # Extract and print the content of the model's reply + print(chunk.choices[0].delta.content or "", end="") +``` + +**Note**: If your Service is deployed with [protected endpoints on BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html#access-protected-deployments), you need to set the environment variable `OPENAI_API_KEY` to your BentoCloud API key first. + +```bash +export OPENAI_API_KEY={YOUR_BENTOCLOUD_API_TOKEN} +``` + +You can then use the following line to replace the client in the above code snippet. Refer to [Obtain the endpoint URL](https://docs.bentoml.com/en/latest/bentocloud/how-tos/call-deployment-endpoints.html#obtain-the-endpoint-url) to retrieve the endpoint URL. + +```python +client = OpenAI(base_url='your_bentocloud_deployment_endpoint_url/v1') +``` + +
+ +For detailed explanations of the Service code, see [vLLM inference](https://docs.bentoml.org/en/latest/use-cases/large-language-models/vllm.html). + +## Deploy to BentoCloud + +After the Service is ready, you can deploy the application to BentoCloud for better management and scalability. [Sign up](https://www.bentoml.com/) if you haven't got a BentoCloud account. + +Make sure you have [logged in to BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html), then run the following command to deploy it. + +```bash +bentoml deploy . +``` + +Once the application is up and running on BentoCloud, you can access it via the exposed URL. + +**Note**: For custom deployment in your own infrastructure, use [BentoML to generate an OCI-compliant image](https://docs.bentoml.com/en/latest/guides/containerization.html). diff --git a/chattts/bento_constants.py b/chattts/bento_constants.py new file mode 100644 index 00000000..6c20a8f9 --- /dev/null +++ b/chattts/bento_constants.py @@ -0,0 +1,9 @@ +CONSTANT_YAML = """ +project: chattts +service_config: + name: chattts + traffic: + timeout: 300 + resources: + gpu: 1 +""" diff --git a/chattts/bentofile.yaml b/chattts/bentofile.yaml new file mode 100644 index 00000000..dc082756 --- /dev/null +++ b/chattts/bentofile.yaml @@ -0,0 +1,13 @@ +service: "service:Main" +labels: + owner: bentoml-team + stage: demo + platforms: linux, macos +include: +- "*.py" +python: + requirements_txt: "./requirements.txt" + lock_packages: true +envs: + - name: CHAT_TTS_REPO + value: https://github.com/2noise/ChatTTS.git diff --git a/chattts/requirements.txt b/chattts/requirements.txt new file mode 100644 index 00000000..75025bd9 --- /dev/null +++ b/chattts/requirements.txt @@ -0,0 +1,13 @@ +torch==2.3.0 +torchaudio +transformers==4.41.0 +omegaconf~=2.3.0 +tqdm +einops +vector_quantize_pytorch +vocos +pyyaml +nemo-text-processing +WeTextProcessing +pysoundfile +dulwich diff --git a/chattts/service.py b/chattts/service.py new file mode 100644 index 00000000..1f24c813 --- /dev/null +++ b/chattts/service.py @@ -0,0 +1,55 @@ +import os +import yaml +from typing import Annotated +import sys +import shutil +import io + +import bentoml +from bentoml.validators import ContentType +from bento_constants import CONSTANT_YAML + + +CONSTANTS = yaml.safe_load(CONSTANT_YAML) + + +@bentoml.service(**CONSTANTS["service_config"]) +class Main: + + @bentoml.on_deployment + @staticmethod + def on_deployment(): + CHAT_TTS_REPO = os.environ.get("CHAT_TTS_REPO") + assert CHAT_TTS_REPO, "CHAT_TTS_REPO environment variable is not set" + + import dulwich + import dulwich.errors + import dulwich.porcelain + + if os.path.exists("ChatTTS"): + shutil.rmtree("ChatTTS") + + dulwich.porcelain.clone( + CHAT_TTS_REPO, + "ChatTTS", + checkout=True, + depth=1, + ) + + def __init__(self) -> None: + sys.path.append(os.path.join(os.path.dirname(__file__), "ChatTTS")) + + import ChatTTS + + self.chat = ChatTTS.Chat() + self.chat.load_models(compile=False) # Set to True for better performance + + @bentoml.api + def tts(self, text: str = "PUT YOUR TEXT HERE") -> Annotated[bytes, ContentType("audio/wav")]: + import torch + import torchaudio + + wavs = self.chat.infer([text]) + output_io = io.BytesIO() + torchaudio.save(output_io, torch.from_numpy(wavs[0]), 24000, format="wav") + return output_io.getvalue() From b8467aa09eaf90f51990e7591ea4090741f9b0e1 Mon Sep 17 00:00:00 2001 From: bojiang Date: Fri, 31 May 2024 21:44:47 +0800 Subject: [PATCH 044/125] use absolute path --- chattts/service.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/chattts/service.py b/chattts/service.py index 1f24c813..67e5d279 100644 --- a/chattts/service.py +++ b/chattts/service.py @@ -12,6 +12,7 @@ from bento_constants import CONSTANT_YAML CONSTANTS = yaml.safe_load(CONSTANT_YAML) +CHATTTS_PATH = os.path.join(os.path.dirname(__file__), "ChatTTS") @bentoml.service(**CONSTANTS["service_config"]) class Main: @@ -26,18 +27,18 @@ class Main: import dulwich.errors import dulwich.porcelain - if os.path.exists("ChatTTS"): - shutil.rmtree("ChatTTS") + if os.path.exists(CHATTTS_PATH): + shutil.rmtree(CHATTTS_PATH) dulwich.porcelain.clone( CHAT_TTS_REPO, - "ChatTTS", + CHATTTS_PATH, checkout=True, depth=1, ) def __init__(self) -> None: - sys.path.append(os.path.join(os.path.dirname(__file__), "ChatTTS")) + sys.path.append(CHATTTS_PATH) import ChatTTS From 5e67ca4dcf4b0e6b341d4e008a181ceda9da1393 Mon Sep 17 00:00:00 2001 From: bojiang Date: Fri, 31 May 2024 22:48:13 +0800 Subject: [PATCH 045/125] fix chattts --- chattts/bentofile.yaml | 3 +++ chattts/service.py | 3 ++- 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/chattts/bentofile.yaml b/chattts/bentofile.yaml index dc082756..843e8bca 100644 --- a/chattts/bentofile.yaml +++ b/chattts/bentofile.yaml @@ -8,6 +8,9 @@ include: python: requirements_txt: "./requirements.txt" lock_packages: true +docker: + system_packages: + - libsox-dev envs: - name: CHAT_TTS_REPO value: https://github.com/2noise/ChatTTS.git diff --git a/chattts/service.py b/chattts/service.py index 67e5d279..74d765a6 100644 --- a/chattts/service.py +++ b/chattts/service.py @@ -4,6 +4,7 @@ from typing import Annotated import sys import shutil import io +import pathlib import bentoml from bentoml.validators import ContentType @@ -46,7 +47,7 @@ class Main: self.chat.load_models(compile=False) # Set to True for better performance @bentoml.api - def tts(self, text: str = "PUT YOUR TEXT HERE") -> Annotated[bytes, ContentType("audio/wav")]: + def tts(self, text: str = "PUT YOUR TEXT HERE") -> Annotated[pathlib.Path, ContentType("audio/wav")]: import torch import torchaudio From 5df10f7ea1400c8d1efc0cec64653fda2bd10e9a Mon Sep 17 00:00:00 2001 From: bojiang Date: Fri, 31 May 2024 22:49:40 +0800 Subject: [PATCH 046/125] ignore ChatTTS --- .gitignore | 2 ++ chattts/ChatTTS | 1 - 2 files changed, 2 insertions(+), 1 deletion(-) delete mode 160000 chattts/ChatTTS diff --git a/.gitignore b/.gitignore index 796b0eb8..d5629589 100644 --- a/.gitignore +++ b/.gitignore @@ -8,3 +8,5 @@ venv/ # BentoML bentoml/client_id + +chattts/ChatTTS/ diff --git a/chattts/ChatTTS b/chattts/ChatTTS deleted file mode 160000 index a80439e2..00000000 --- a/chattts/ChatTTS +++ /dev/null @@ -1 +0,0 @@ -Subproject commit a80439e2a45a0b76e03b0e2cabe667c763d7ec97 From 91cdc6641a10778f6276bfcee3ac463600290a31 Mon Sep 17 00:00:00 2001 From: bojiang Date: Fri, 31 May 2024 22:50:08 +0800 Subject: [PATCH 047/125] rm README --- chattts/README.md | 141 ---------------------------------------------- 1 file changed, 141 deletions(-) delete mode 100644 chattts/README.md diff --git a/chattts/README.md b/chattts/README.md deleted file mode 100644 index 8796f668..00000000 --- a/chattts/README.md +++ /dev/null @@ -1,141 +0,0 @@ -
-

Self-host Llama 2 7B with vLLM and BentoML

-
- -This is a BentoML example project, showing you how to serve and deploy Llama 2 7B using [vLLM](https://vllm.ai), a high-throughput and memory-efficient inference engine. - -See [here](https://github.com/bentoml/BentoML?tab=readme-ov-file#%EF%B8%8F-what-you-can-build-with-bentoml) for a full list of BentoML example projects. - -💡 This example is served as a basis for advanced code customization, such as custom model, inference logic or vLLM options. For simple LLM hosting with OpenAI compatible endpoint without writing any code, see [OpenLLM](https://github.com/bentoml/OpenLLM). - - -## Prerequisites - -- You have installed Python 3.8+ and `pip`. See the [Python downloads page](https://www.python.org/downloads/) to learn more. -- You have a basic understanding of key concepts in BentoML, such as Services. We recommend you read [Quickstart](https://docs.bentoml.com/en/1.2/get-started/quickstart.html) first. -- You have gained access to Llama 2 7B on [its official website](https://llama.meta.com/) and [Hugging Face](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf). -- If you want to test the Service locally, you need a Nvidia GPU with at least 16G VRAM. -- (Optional) We recommend you create a virtual environment for dependency isolation for this project. See the [Conda documentation](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) or the [Python documentation](https://docs.python.org/3/library/venv.html) for details. - -## Install dependencies - -```bash -git clone https://github.com/bentoml/BentoVLLM.git -cd BentoVLLM/llama2-7b-chat -pip install -r requirements.txt && pip install -f -U "pydantic>=2.0" -``` - -## Download the model - -```bash -python import_model.py -``` - -## Run the BentoML Service - -We have defined a BentoML Service in `service.py`. Run `bentoml serve` in your project directory to start the Service. - -```python -$ bentoml serve . - -2024-01-18T07:51:30+0800 [INFO] [cli] Starting production HTTP BentoServer from "service:VLLM" listening on http://localhost:3000 (Press CTRL+C to quit) -INFO 01-18 07:51:40 model_runner.py:501] Capturing the model for CUDA graphs. This may lead to unexpected consequences if the model is not static. To run the model in eager mode, set 'enforce_eager=True' or use '--enforce-eager' in the CLI. -INFO 01-18 07:51:40 model_runner.py:505] CUDA graphs can take additional 1~3 GiB memory per GPU. If you are running out of memory, consider decreasing `gpu_memory_utilization` or enforcing eager mode. -INFO 01-18 07:51:46 model_runner.py:547] Graph capturing finished in 6 secs. -``` - -The server is now active at [http://localhost:3000](http://localhost:3000/). You can interact with it using the Swagger UI or in other different ways. - -
- -CURL - -```bash -curl -X 'POST' \ - 'http://localhost:3000/generate' \ - -H 'accept: text/event-stream' \ - -H 'Content-Type: application/json' \ - -d '{ - "prompt": "Explain superconductors like I'\''m five years old", - "tokens": null -}' -``` - -
- -
- -Python client - -```python -import bentoml - -with bentoml.SyncHTTPClient("http://localhost:3000") as client: - response_generator = client.generate( - prompt="Explain superconductors like I'm five years old", - tokens=None - ) - for response in response_generator: - print(response) -``` - -
- -
- -OpenAI-compatible endpoints - -This Service uses the `@openai_endpoints` decorator to set up OpenAI-compatible endpoints (`chat/completions` and `completions`). This means your client can interact with the backend Service (in this case, the VLLM class) as if they were communicating directly with OpenAI's API. This [utility](bentovllm_openai/) does not affect your BentoML Service code, and you can use it for other LLMs as well. - -```python -from openai import OpenAI - -client = OpenAI(base_url='http://localhost:3000/v1', api_key='na') - -# Use the following func to get the available models -client.models.list() - -chat_completion = client.chat.completions.create( - model="meta-llama/Llama-2-7b-chat-hf", - messages=[ - { - "role": "user", - "content": "Explain superconductors like I'm five years old" - } - ], - stream=True, -) -for chunk in chat_completion: - # Extract and print the content of the model's reply - print(chunk.choices[0].delta.content or "", end="") -``` - -**Note**: If your Service is deployed with [protected endpoints on BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html#access-protected-deployments), you need to set the environment variable `OPENAI_API_KEY` to your BentoCloud API key first. - -```bash -export OPENAI_API_KEY={YOUR_BENTOCLOUD_API_TOKEN} -``` - -You can then use the following line to replace the client in the above code snippet. Refer to [Obtain the endpoint URL](https://docs.bentoml.com/en/latest/bentocloud/how-tos/call-deployment-endpoints.html#obtain-the-endpoint-url) to retrieve the endpoint URL. - -```python -client = OpenAI(base_url='your_bentocloud_deployment_endpoint_url/v1') -``` - -
- -For detailed explanations of the Service code, see [vLLM inference](https://docs.bentoml.org/en/latest/use-cases/large-language-models/vllm.html). - -## Deploy to BentoCloud - -After the Service is ready, you can deploy the application to BentoCloud for better management and scalability. [Sign up](https://www.bentoml.com/) if you haven't got a BentoCloud account. - -Make sure you have [logged in to BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html), then run the following command to deploy it. - -```bash -bentoml deploy . -``` - -Once the application is up and running on BentoCloud, you can access it via the exposed URL. - -**Note**: For custom deployment in your own infrastructure, use [BentoML to generate an OCI-compliant image](https://docs.bentoml.com/en/latest/guides/containerization.html). From b165d94fbb61f08ca6c3ebb43a946fd4e4d4ae3d Mon Sep 17 00:00:00 2001 From: bojiang <5886138+bojiang@users.noreply.github.com> Date: Fri, 31 May 2024 23:04:18 +0800 Subject: [PATCH 048/125] Create README.md --- chattts/README.md | 15 +++++++++++++++ 1 file changed, 15 insertions(+) create mode 100644 chattts/README.md diff --git a/chattts/README.md b/chattts/README.md new file mode 100644 index 00000000..3de3a675 --- /dev/null +++ b/chattts/README.md @@ -0,0 +1,15 @@ +## Local Run & development + +``` +pip install bentoml +pip install -r requirements.txt + +export CHAT_TTS_REPO=https://github.com/2noise/ChatTTS.git +bentoml serve +``` + +(You may need to install `libsox-dev` with your package manager first) + +## Get your own server + +Get your token at: https://cloud.bentoml.com/ From 8f27daa058e5051dc7aac7523ca9b73a0336c6d7 Mon Sep 17 00:00:00 2001 From: Rick Zhou Date: Mon, 3 Jun 2024 08:15:22 +0000 Subject: [PATCH 049/125] Update openvllm protocol to be compatible with 0.4.2 --- vllm-chat/bentovllm_openai/protocol.py | 310 ++++++++++++++++++------- 1 file changed, 223 insertions(+), 87 deletions(-) diff --git a/vllm-chat/bentovllm_openai/protocol.py b/vllm-chat/bentovllm_openai/protocol.py index 7de4d1da..9b7a5680 100644 --- a/vllm-chat/bentovllm_openai/protocol.py +++ b/vllm-chat/bentovllm_openai/protocol.py @@ -4,12 +4,15 @@ from __future__ import annotations # https://github.com/lm-sys/FastChat/blob/168ccc29d3f7edc50823016105c024fe2282732a/fastchat/protocol/openai_api_protocol.py import time import uuid -from typing import TYPE_CHECKING, Dict, List, Literal, Optional, Union +from typing import Any, Dict, List, Literal, Optional, Union, TYPE_CHECKING -from pydantic import BaseModel, Field, model_validator +import openai.types.chat +import torch +from pydantic import BaseModel, ConfigDict, Field, model_validator +from typing_extensions import Annotated, Required, TypedDict if TYPE_CHECKING: - import torch + from vllm.pooling_params import PoolingParams from vllm.sampling_params import SamplingParams @@ -17,7 +20,45 @@ def random_uuid() -> str: return str(uuid.uuid4().hex) -class ErrorResponse(BaseModel): +class CustomChatCompletionContentPartParam(TypedDict, total=False): + __pydantic_config__ = ConfigDict(extra="allow") # type: ignore + + type: Required[str] + """The type of the content part.""" + + +ChatCompletionContentPartParam = Union[ + openai.types.chat.ChatCompletionContentPartParam, + CustomChatCompletionContentPartParam] + + +class CustomChatCompletionMessageParam(TypedDict, total=False): + """Enables custom roles in the Chat Completion API.""" + role: Required[str] + """The role of the message's author.""" + + content: Union[str, List[ChatCompletionContentPartParam]] + """The contents of the message.""" + + name: str + """An optional name for the participant. + + Provides the model information to differentiate between participants of the + same role. + """ + + +ChatCompletionMessageParam = Union[ + openai.types.chat.ChatCompletionMessageParam, + CustomChatCompletionMessageParam] + + +class OpenAIBaseModel(BaseModel): + # OpenAI API does not allow extra fields + model_config = ConfigDict(extra="forbid") + + +class ErrorResponse(OpenAIBaseModel): object: str = "error" message: str type: str @@ -25,7 +66,7 @@ class ErrorResponse(BaseModel): code: int -class ModelPermission(BaseModel): +class ModelPermission(OpenAIBaseModel): id: str = Field(default_factory=lambda: f"modelperm-{random_uuid()}") object: str = "model_permission" created: int = Field(default_factory=lambda: int(time.time())) @@ -37,10 +78,10 @@ class ModelPermission(BaseModel): allow_fine_tuning: bool = False organization: str = "*" group: Optional[str] = None - is_blocking: str = False + is_blocking: bool = False -class ModelCard(BaseModel): +class ModelCard(OpenAIBaseModel): id: str object: str = "model" created: int = Field(default_factory=lambda: int(time.time())) @@ -50,26 +91,26 @@ class ModelCard(BaseModel): permission: List[ModelPermission] = Field(default_factory=list) -class ModelList(BaseModel): +class ModelList(OpenAIBaseModel): object: str = "list" data: List[ModelCard] = Field(default_factory=list) -class UsageInfo(BaseModel): +class UsageInfo(OpenAIBaseModel): prompt_tokens: int = 0 total_tokens: int = 0 completion_tokens: Optional[int] = 0 -class ResponseFormat(BaseModel): +class ResponseFormat(OpenAIBaseModel): # type must be "json_object" or "text" - type: str = Literal["text", "json_object"] + type: Literal["text", "json_object"] -class ChatCompletionRequest(BaseModel): +class ChatCompletionRequest(OpenAIBaseModel): # Ordered by official OpenAI API documentation # https://platform.openai.com/docs/api-reference/chat/create - messages: List[Dict[str, str]] + messages: List[ChatCompletionMessageParam] model: str frequency_penalty: Optional[float] = 0.0 logit_bias: Optional[Dict[str, float]] = None @@ -79,7 +120,9 @@ class ChatCompletionRequest(BaseModel): n: Optional[int] = 1 presence_penalty: Optional[float] = 0.0 response_format: Optional[ResponseFormat] = None - seed: Optional[int] = None + seed: Optional[int] = Field(None, + ge=torch.iinfo(torch.long).min, + le=torch.iinfo(torch.long).max) stop: Optional[Union[str, List[str]]] = Field(default_factory=list) stream: Optional[bool] = False temperature: Optional[float] = 0.7 @@ -106,23 +149,20 @@ class ChatCompletionRequest(BaseModel): default=False, description=( "If true, the new message will be prepended with the last message " - "if they belong to the same role." - ), + "if they belong to the same role."), ) add_generation_prompt: Optional[bool] = Field( default=True, - description=( - "If true, the generation prompt will be added to the chat template. " - "This is a parameter used by chat template in tokenizer config of the " - "model." - ), + description= + ("If true, the generation prompt will be added to the chat template. " + "This is a parameter used by chat template in tokenizer config of the " + "model."), ) include_stop_str_in_output: Optional[bool] = Field( default=False, description=( "Whether to include the stop string in the output. " - "This is only applied when the stop or stop_token_ids is set." - ), + "This is only applied when the stop or stop_token_ids is set."), ) guided_json: Optional[Union[str, dict, BaseModel]] = Field( default=None, @@ -130,16 +170,30 @@ class ChatCompletionRequest(BaseModel): ) guided_regex: Optional[str] = Field( default=None, - description=("If specified, the output will follow the regex pattern."), + description=( + "If specified, the output will follow the regex pattern."), ) guided_choice: Optional[List[str]] = Field( default=None, - description=("If specified, the output will be exactly one of the choices."), + description=( + "If specified, the output will be exactly one of the choices."), ) guided_grammar: Optional[str] = Field( default=None, - description=("If specified, the output will follow the context free grammar."), + description=( + "If specified, the output will follow the context free grammar."), ) + guided_decoding_backend: Optional[str] = Field( + default=None, + description=( + "If specified, will override the default guided decoding backend " + "of the server for this specific request. If set, must be either " + "'outlines' / 'lm-format-enforcer'")) + guided_whitespace_pattern: Optional[str] = Field( + default=None, + description=( + "If specified, will override the default whitespace pattern " + "for guided json decoding.")) # doc: end-chat-completion-extra-params @@ -151,8 +205,9 @@ class ChatCompletionRequest(BaseModel): if self.logit_bias: def logit_bias_logits_processor( - token_ids: List[int], logits: torch.Tensor - ) -> torch.Tensor: + token_ids: List[int], + logits: torch.Tensor) -> torch.Tensor: + assert self.logit_bias is not None for token_id, bias in self.logit_bias.items(): # Clamp the bias between -100 and 100 per OpenAI API spec bias = min(100, max(-100, bias)) @@ -162,7 +217,6 @@ class ChatCompletionRequest(BaseModel): logits_processors = [logit_bias_logits_processor] from vllm.sampling_params import SamplingParams - return SamplingParams( n=self.n, presence_penalty=self.presence_penalty, @@ -193,22 +247,19 @@ class ChatCompletionRequest(BaseModel): @model_validator(mode="before") @classmethod def check_guided_decoding_count(cls, data): - guide_count = sum( - [ - "guided_json" in data and data["guided_json"] is not None, - "guided_regex" in data and data["guided_regex"] is not None, - "guided_choice" in data and data["guided_choice"] is not None, - ] - ) + guide_count = sum([ + "guided_json" in data and data["guided_json"] is not None, + "guided_regex" in data and data["guided_regex"] is not None, + "guided_choice" in data and data["guided_choice"] is not None + ]) if guide_count > 1: raise ValueError( "You can only use one kind of guided decoding " - "('guided_json', 'guided_regex' or 'guided_choice')." - ) + "('guided_json', 'guided_regex' or 'guided_choice').") return data -class CompletionRequest(BaseModel): +class CompletionRequest(OpenAIBaseModel): # Ordered by official OpenAI API documentation # https://platform.openai.com/docs/api-reference/completions/create model: str @@ -219,9 +270,11 @@ class CompletionRequest(BaseModel): logit_bias: Optional[Dict[str, float]] = None logprobs: Optional[int] = None max_tokens: Optional[int] = 16 - n: Optional[int] = 1 + n: int = 1 presence_penalty: Optional[float] = 0.0 - seed: Optional[int] = None + seed: Optional[int] = Field(None, + ge=torch.iinfo(torch.long).min, + le=torch.iinfo(torch.long).max) stop: Optional[Union[str, List[str]]] = Field(default_factory=list) stream: Optional[bool] = False suffix: Optional[str] = None @@ -241,6 +294,7 @@ class CompletionRequest(BaseModel): min_tokens: Optional[int] = 0 skip_special_tokens: Optional[bool] = True spaces_between_special_tokens: Optional[bool] = True + truncate_prompt_tokens: Optional[Annotated[int, Field(ge=1)]] = None # doc: end-completion-sampling-params # doc: begin-completion-extra-params @@ -248,16 +302,14 @@ class CompletionRequest(BaseModel): default=False, description=( "Whether to include the stop string in the output. " - "This is only applied when the stop or stop_token_ids is set." - ), + "This is only applied when the stop or stop_token_ids is set."), ) response_format: Optional[ResponseFormat] = Field( default=None, - description=( - "Similar to chat completion, this parameter specifies the format of " - "output. Only {'type': 'json_object'} or {'type': 'text' } is " - "supported." - ), + description= + ("Similar to chat completion, this parameter specifies the format of " + "output. Only {'type': 'json_object'} or {'type': 'text' } is " + "supported."), ) guided_json: Optional[Union[str, dict, BaseModel]] = Field( default=None, @@ -265,16 +317,30 @@ class CompletionRequest(BaseModel): ) guided_regex: Optional[str] = Field( default=None, - description=("If specified, the output will follow the regex pattern."), + description=( + "If specified, the output will follow the regex pattern."), ) guided_choice: Optional[List[str]] = Field( default=None, - description=("If specified, the output will be exactly one of the choices."), + description=( + "If specified, the output will be exactly one of the choices."), ) guided_grammar: Optional[str] = Field( default=None, - description=("If specified, the output will follow the context free grammar."), + description=( + "If specified, the output will follow the context free grammar."), ) + guided_decoding_backend: Optional[str] = Field( + default=None, + description=( + "If specified, will override the default guided decoding backend " + "of the server for this specific request. If set, must be one of " + "'outlines' / 'lm-format-enforcer'")) + guided_whitespace_pattern: Optional[str] = Field( + default=None, + description=( + "If specified, will override the default whitespace pattern " + "for guided json decoding.")) # doc: end-completion-extra-params @@ -282,11 +348,12 @@ class CompletionRequest(BaseModel): echo_without_generation = self.echo and self.max_tokens == 0 logits_processors = None - if self.logit_bias is not None: + if self.logit_bias: def logit_bias_logits_processor( - token_ids: List[int], logits: torch.Tensor - ) -> torch.Tensor: + token_ids: List[int], + logits: torch.Tensor) -> torch.Tensor: + assert self.logit_bias is not None for token_id, bias in self.logit_bias.items(): # Clamp the bias between -100 and 100 per OpenAI API spec bias = min(100, max(-100, bias)) @@ -296,7 +363,6 @@ class CompletionRequest(BaseModel): logits_processors = [logit_bias_logits_processor] from vllm.sampling_params import SamplingParams - return SamplingParams( n=self.n, best_of=self.best_of, @@ -322,49 +388,64 @@ class CompletionRequest(BaseModel): include_stop_str_in_output=self.include_stop_str_in_output, length_penalty=self.length_penalty, logits_processors=logits_processors, + truncate_prompt_tokens=self.truncate_prompt_tokens, ) @model_validator(mode="before") @classmethod def check_guided_decoding_count(cls, data): - guide_count = sum( - [ - "guided_json" in data and data["guided_json"] is not None, - "guided_regex" in data and data["guided_regex"] is not None, - "guided_choice" in data and data["guided_choice"] is not None, - ] - ) + guide_count = sum([ + "guided_json" in data and data["guided_json"] is not None, + "guided_regex" in data and data["guided_regex"] is not None, + "guided_choice" in data and data["guided_choice"] is not None + ]) if guide_count > 1: raise ValueError( "You can only use one kind of guided decoding " - "('guided_json', 'guided_regex' or 'guided_choice')." - ) + "('guided_json', 'guided_regex' or 'guided_choice').") return data -class LogProbs(BaseModel): +class EmbeddingRequest(BaseModel): + # Ordered by official OpenAI API documentation + # https://platform.openai.com/docs/api-reference/embeddings + model: str + input: Union[List[int], List[List[int]], str, List[str]] + encoding_format: Optional[str] = Field('float', pattern='^(float|base64)$') + dimensions: Optional[int] = None + user: Optional[str] = None + + # doc: begin-embedding-pooling-params + additional_data: Optional[Any] = None + + # doc: end-embedding-pooling-params + + def to_pooling_params(self): + return PoolingParams(additional_data=self.additional_data) + + +class LogProbs(OpenAIBaseModel): text_offset: List[int] = Field(default_factory=list) token_logprobs: List[Optional[float]] = Field(default_factory=list) tokens: List[str] = Field(default_factory=list) top_logprobs: Optional[List[Optional[Dict[str, float]]]] = None -class CompletionResponseChoice(BaseModel): +class CompletionResponseChoice(OpenAIBaseModel): index: int text: str logprobs: Optional[LogProbs] = None - finish_reason: Optional[Literal["stop", "length"]] = None - stop_reason: Union[None, int, str] = Field( + finish_reason: Optional[str] = None + stop_reason: Optional[Union[int, str]] = Field( default=None, description=( "The stop string or token id that caused the completion " "to stop, None if the completion finished for some other reason " - "including encountering the EOS token" - ), + "including encountering the EOS token"), ) -class CompletionResponse(BaseModel): +class CompletionResponse(OpenAIBaseModel): id: str = Field(default_factory=lambda: f"cmpl-{random_uuid()}") object: str = "text_completion" created: int = Field(default_factory=lambda: int(time.time())) @@ -373,22 +454,21 @@ class CompletionResponse(BaseModel): usage: UsageInfo -class CompletionResponseStreamChoice(BaseModel): +class CompletionResponseStreamChoice(OpenAIBaseModel): index: int text: str logprobs: Optional[LogProbs] = None - finish_reason: Optional[Literal["stop", "length"]] = None - stop_reason: Union[None, int, str] = Field( + finish_reason: Optional[str] = None + stop_reason: Optional[Union[int, str]] = Field( default=None, description=( "The stop string or token id that caused the completion " "to stop, None if the completion finished for some other reason " - "including encountering the EOS token" - ), + "including encountering the EOS token"), ) -class CompletionStreamResponse(BaseModel): +class CompletionStreamResponse(OpenAIBaseModel): id: str = Field(default_factory=lambda: f"cmpl-{random_uuid()}") object: str = "text_completion" created: int = Field(default_factory=lambda: int(time.time())) @@ -397,20 +477,35 @@ class CompletionStreamResponse(BaseModel): usage: Optional[UsageInfo] = Field(default=None) -class ChatMessage(BaseModel): +class EmbeddingResponseData(BaseModel): + index: int + object: str = "embedding" + embedding: List[float] + + +class EmbeddingResponse(BaseModel): + id: str = Field(default_factory=lambda: f"cmpl-{random_uuid()}") + object: str = "list" + created: int = Field(default_factory=lambda: int(time.time())) + model: str + data: List[EmbeddingResponseData] + usage: UsageInfo + + +class ChatMessage(OpenAIBaseModel): role: str content: str -class ChatCompletionResponseChoice(BaseModel): +class ChatCompletionResponseChoice(OpenAIBaseModel): index: int message: ChatMessage logprobs: Optional[LogProbs] = None - finish_reason: Optional[Literal["stop", "length"]] = None - stop_reason: Union[None, int, str] = None + finish_reason: Optional[str] = None + stop_reason: Optional[Union[int, str]] = None -class ChatCompletionResponse(BaseModel): +class ChatCompletionResponse(OpenAIBaseModel): id: str = Field(default_factory=lambda: f"chatcmpl-{random_uuid()}") object: str = "chat.completion" created: int = Field(default_factory=lambda: int(time.time())) @@ -419,23 +514,64 @@ class ChatCompletionResponse(BaseModel): usage: UsageInfo -class DeltaMessage(BaseModel): +class DeltaMessage(OpenAIBaseModel): role: Optional[str] = None content: Optional[str] = None -class ChatCompletionResponseStreamChoice(BaseModel): +class ChatCompletionResponseStreamChoice(OpenAIBaseModel): index: int delta: DeltaMessage logprobs: Optional[LogProbs] = None - finish_reason: Optional[Literal["stop", "length"]] = None - stop_reason: Union[None, int, str] = None + finish_reason: Optional[str] = None + stop_reason: Optional[Union[int, str]] = None -class ChatCompletionStreamResponse(BaseModel): +class ChatCompletionStreamResponse(OpenAIBaseModel): id: str = Field(default_factory=lambda: f"chatcmpl-{random_uuid()}") object: str = "chat.completion.chunk" created: int = Field(default_factory=lambda: int(time.time())) model: str choices: List[ChatCompletionResponseStreamChoice] usage: Optional[UsageInfo] = Field(default=None) + + +class BatchRequestInput(OpenAIBaseModel): + """ + The per-line object of the batch input file. + + NOTE: Currently only the `/v1/chat/completions` endpoint is supported. + """ + + # A developer-provided per-request id that will be used to match outputs to + # inputs. Must be unique for each request in a batch. + custom_id: str + + # The HTTP method to be used for the request. Currently only POST is + # supported. + method: str + + # The OpenAI API relative URL to be used for the request. Currently + # /v1/chat/completions is supported. + url: str + + # The parameteters of the request. + body: Union[ChatCompletionRequest, ] + + +class BatchRequestOutput(OpenAIBaseModel): + """ + The per-line object of the batch output and error files + """ + + id: str + + # A developer-provided per-request id that will be used to match outputs to + # inputs. + custom_id: str + + response: Optional[ChatCompletionResponse] + + # For requests that failed with a non-HTTP error, this will contain more + # information on the cause of the failure. + error: Optional[Any] From cd7c0e2c2042032201d1afb25ab93ff81d7c5b88 Mon Sep 17 00:00:00 2001 From: bojiang Date: Thu, 30 May 2024 20:26:56 +0800 Subject: [PATCH 050/125] deployment target --- openllm_next/__main__.py | 115 ++++++++++++++++++++----------- openllm_next/accelerator_spec.py | 63 ++++++++--------- openllm_next/cloud.py | 110 +++++++++++++---------------- openllm_next/common.py | 27 +++++++- openllm_next/local.py | 3 - 5 files changed, 177 insertions(+), 141 deletions(-) diff --git a/openllm_next/__main__.py b/openllm_next/__main__.py index 3d702cfa..c8d2dba4 100644 --- a/openllm_next/__main__.py +++ b/openllm_next/__main__.py @@ -3,9 +3,17 @@ from typing import Annotated import questionary import typer -from openllm_next.accelerator_spec import match_deployment_target +from openllm_next.accelerator_spec import ( + ACCELERATOR_SPECS, + DeploymentTarget, + can_run, + get_local_machine_spec, +) from openllm_next.cloud import app as cloud_app -from openllm_next.common import VERBOSE_LEVEL +from openllm_next.cloud import get_cloud_machine_spec +from openllm_next.cloud import run as cloud_run +from openllm_next.cloud import serve as cloud_serve +from openllm_next.common import VERBOSE_LEVEL, BentoInfo from openllm_next.local import run as local_run from openllm_next.local import serve as local_serve from openllm_next.model import app as model_app @@ -19,60 +27,89 @@ app.add_typer(model_app, name="model") app.add_typer(cloud_app, name="cloud") -def _pre_select(model: str): +def _pre_select(model: str) -> tuple[BentoInfo, DeploymentTarget]: bentos = list_bento(model) if len(bentos) == 0: typer.echo(f"No model found for {model}", err=True) raise typer.Exit(1) - matchs = match_deployment_target(bentos) + + local = get_local_machine_spec() + if len(bentos) == 1: bento = bentos[0] - else: - choices = [] - # bentos that can be run locally - choices += [questionary.Separator("Local available models")] - choices += [ - questionary.Choice( - f" {bento.name}:{bento.version}", - bento, + if can_run(bento, local) <= 0: + questionary.print( + f"No deployment target found for {bento.name}:{bento.version}", + style="red", ) - for bento, targets in matchs.items() - if targets - ] - choices += [questionary.Separator("Cloud available models")] - choices += [ - questionary.Choice( - f" {bento.name}:{bento.version}", - bento, - ) - for bento, targets in matchs.items() - if not targets - ] - - bento = questionary.select( - "Select a model to run", - choices=choices, - ).ask() - if not bento: - questionary.print("No model selected", style="red") raise typer.Exit(1) - return bento, matchs[bento] + return bento, local + + choices = [] + choices += [questionary.Separator("Local available models")] + choices += [ + questionary.Choice( + f" {bento.name}:{bento.version}", + (bento, local), + ) + for bento in bentos + if can_run(bento) > 0 + ] + choices += [questionary.Separator("Cloud available models")] + choices += [ + questionary.Choice( + f" {bento.name}:{bento.version}", + (bento, None), + ) + for bento in bentos + ] + + choosen: tuple[BentoInfo, DeploymentTarget] = questionary.select( + "Select a model to run", + choices=choices, + ).ask() + + if not choosen: + questionary.print("No model selected", style="red") + raise typer.Exit(1) + + bento, target = choosen + if target is None: + cloud_targets = get_cloud_machine_spec() + target = questionary.select( + "Select a cloud target", + choices=[ + questionary.Choice( + f" {target.name}", + target, + ) + for target in cloud_targets + if can_run(bento, target) > 0 + ], + ).ask() + if not target: + questionary.print("No target selected", style="red") + raise typer.Exit(1) + + return bento, target @app.command() -def serve(model: str): - bento, targets = _pre_select(model) - local_serve(bento) +def serve(model: Annotated[str, typer.Argument()] = ""): + bento, target = _pre_select(model) + if target and target.source == "local": + local_serve(bento) + else: + cloud_serve(bento, target) @app.command() def run(model: Annotated[str, typer.Argument()] = ""): - bento, targets = _pre_select(model) - if targets: + bento, target = _pre_select(model) + if target and target.source == "local": local_run(bento) else: - typer.echo("No local available deployment target found", err=True) - raise typer.Exit(1) + cloud_run(bento, target) def typer_callback(verbose: int = 0): diff --git a/openllm_next/accelerator_spec.py b/openllm_next/accelerator_spec.py index c9aa852c..3021e301 100644 --- a/openllm_next/accelerator_spec.py +++ b/openllm_next/accelerator_spec.py @@ -1,12 +1,13 @@ from __future__ import annotations +import functools import math from types import SimpleNamespace -from openllm_next.common import BentoInfo +from openllm_next.common import BentoInfo, DeploymentTarget -class ACC_SPEC(SimpleNamespace): +class Accelerator(SimpleNamespace): model: str memory_size: float @@ -23,6 +24,9 @@ class Resource(SimpleNamespace): gpu: int gpu_type: str + def __hash__(self): + return hash((self.cpu, self.memory, self.gpu, self.gpu_type)) + ACCELERATOR_SPEC_DICT: dict[str, dict] = { "nvidia-gtx-1650": {"model": "GTX 1650", "memory_size": 4.0}, @@ -48,16 +52,12 @@ ACCELERATOR_SPEC_DICT: dict[str, dict] = { } -ACCELERATOR_SPECS: dict[str, ACC_SPEC] = { - key: ACC_SPEC(**value) for key, value in ACCELERATOR_SPEC_DICT.items() +ACCELERATOR_SPECS: dict[str, Accelerator] = { + key: Accelerator(**value) for key, value in ACCELERATOR_SPEC_DICT.items() } -class DeploymentTarget(SimpleNamespace): - source: str = "local" - accelerators: list[ACC_SPEC] - - +@functools.lru_cache def get_local_machine_spec(): from pynvml import ( nvmlDeviceGetCount, @@ -70,19 +70,34 @@ def get_local_machine_spec(): nvmlInit() device_count = nvmlDeviceGetCount() - accelerators: list[ACC_SPEC] = [] + accelerators: list[Accelerator] = [] for i in range(device_count): handle = nvmlDeviceGetHandleByIndex(i) name = nvmlDeviceGetName(handle) memory_info = nvmlDeviceGetMemoryInfo(handle) accelerators.append( - ACC_SPEC(name=name, memory_size=math.ceil(int(memory_info.total) / 1024**3)) + Accelerator( + name=name, memory_size=math.ceil(int(memory_info.total) / 1024**3) + ) ) nvmlShutdown() return DeploymentTarget(accelerators=accelerators, source="local") -def _score(resource_spec: Resource, target: DeploymentTarget) -> float: +@functools.lru_cache() +def can_run( + resource_spec: Resource | BentoInfo, + target: DeploymentTarget | None = None, +) -> float: + """ + Calculate if the resource_spec can be deployed on the target. + """ + if isinstance(resource_spec, BentoInfo): + resource_spec = Resource( + **(resource_spec.bento_yaml["services"][0]["config"]["resources"]) + ) + if target is None: + target = get_local_machine_spec() if resource_spec.gpu > 0: required_gpu = ACCELERATOR_SPECS[resource_spec.gpu_type] filtered_accelerators = [ @@ -100,27 +115,3 @@ def _score(resource_spec: Resource, target: DeploymentTarget) -> float: if target.accelerators: return 0.01 / sum(ac.memory_size for ac in target.accelerators) return 1.0 - - -def _multi_score( - resource_spec: Resource, - targets: list[DeploymentTarget], -) -> list[tuple[DeploymentTarget, float]]: - results = [(target, _score(resource_spec, target)) for target in targets] - return [(target, score) for target, score in results if score > 0.0] - - -def match_deployment_target( - bentos: list[BentoInfo], - targets: list[DeploymentTarget] | None = None, -): - if targets is None: - targets = [get_local_machine_spec()] - - return { - bento: _multi_score( - Resource(**(bento.bento_yaml["services"][0]["config"]["resources"])), - targets, - ) - for bento in bentos - } diff --git a/openllm_next/cloud.py b/openllm_next/cloud.py index b346b578..db51b638 100644 --- a/openllm_next/cloud.py +++ b/openllm_next/cloud.py @@ -1,18 +1,24 @@ -import asyncio import json import os +import pathlib +import shutil import subprocess import questionary import typer -from openllm_next.common import ERROR_STYLE, BentoInfo, run_command -from openllm_next.model import pick_bento +from openllm_next.accelerator_spec import ACCELERATOR_SPECS +from openllm_next.common import ( + ERROR_STYLE, + BentoInfo, + DeploymentTarget, + run_command, +) app = typer.Typer() -def _get_deploy_cmd(bento: BentoInfo): +def _get_deploy_cmd(bento: BentoInfo, target: DeploymentTarget | None = None): cmd = ["bentoml", "deploy", bento.tag] env = { "BENTOML_HOME": f"{bento.repo.path}/bentoml", @@ -42,6 +48,16 @@ def _get_deploy_cmd(bento: BentoInfo): if value is None: raise typer.Exit(1) cmd += ["--env", f"{env_info['name']}={value}"] + + if target: + cmd += ["--instance-type", target.name] + + assert (pathlib.Path.home() / "bentoml" / ".yatai.yaml").exists() + shutil.copy( + pathlib.Path.home() / "bentoml" / ".yatai.yaml", + bento.repo.path / "bentoml" / ".yatai.yaml", + ) + return cmd, env, None @@ -94,65 +110,35 @@ def _ensure_cloud_context(): raise typer.Exit(1) -def serve(bento: BentoInfo): +def get_cloud_machine_spec(): _ensure_cloud_context() - cmd, env, cwd = _get_deploy_cmd(bento) + cmd = ["bentoml", "deployment", "list-instance-types", "-o", "json"] + try: + result = subprocess.check_output(cmd, stderr=subprocess.DEVNULL) + instance_types = json.loads(result) + return [ + DeploymentTarget( + source="cloud", + name=it["name"], + price=it["price"], + accelerators=( + [ACCELERATOR_SPECS[it["gpu_type"]] for _ in range(int(it["gpu"]))] + if it.get("gpu") + else [] + ), + ) + for it in instance_types + ] + except (subprocess.CalledProcessError, json.JSONDecodeError, KeyError, ValueError): + questionary.print("Failed to get cloud instance types", style=ERROR_STYLE) + return [] + + +def serve(bento: BentoInfo, target: DeploymentTarget): + _ensure_cloud_context() + cmd, env, cwd = _get_deploy_cmd(bento, target) run_command(cmd, env=env, cwd=cwd) -async def _run_model(bento: BentoInfo, timeout: int = 600): - _ensure_cloud_context() - cmd, env, cwd = _get_deploy_cmd(bento) - server_proc = subprocess.Popen( - cmd, - env=env, - cwd=cwd, - stdout=subprocess.DEVNULL, - stderr=subprocess.DEVNULL, - ) - - import bentoml - from httpx import ReadError - - try: - questionary.print("Model loading...", style="green") - for _ in range(timeout): - try: - client = bentoml.AsyncHTTPClient( - "http://localhost:3000", timeout=timeout - ) - resp = await client.request("GET", "/readyz") - if resp.status_code == 200: - break - except bentoml.exceptions.BentoMLException: - await asyncio.sleep(1) - except ReadError: - await asyncio.sleep(1) - else: - questionary.print("Model failed to load", style="red") - return - - questionary.print("Model is ready", style="green") - messages = [] - while True: - try: - message = input("user: ") - messages.append(dict(role="user", content=message)) - print("assistant: ", end="") - assistant_message = "" - async for text in client.chat(messages=messages): # type: ignore - assistant_message += text - print(text, end="") - messages.append(dict(role="assistant", content=assistant_message)) - print() - - except KeyboardInterrupt: - break - finally: - questionary.print("\nStopping model server...", style="green") - server_proc.terminate() - questionary.print("Stopped model server", style="green") - - -def run(bento: BentoInfo): - asyncio.run(_run_model(bento)) +def run(bento: BentoInfo, target: DeploymentTarget): + pass diff --git a/openllm_next/common.py b/openllm_next/common.py index 92c5dc72..69cdf6e2 100644 --- a/openllm_next/common.py +++ b/openllm_next/common.py @@ -179,6 +179,27 @@ class BentoInfo(SimpleNamespace): ) +class Accelerator(SimpleNamespace): + model: str + memory_size: float + + def __gt__(self, other): + return self.memory_size > other.memory_size + + def __eq__(self, other): + return self.memory_size == other.memory_size + + +class DeploymentTarget(SimpleNamespace): + source: str = "local" + name: str = "local" + price: str = "" + accelerators: list[Accelerator] + + def __hash__(self): + return hash(self.source) + + @typing.overload def run_command( cmd, @@ -254,7 +275,11 @@ def run_command( stderr=subprocess.DEVNULL, ) else: - return run_func(cmd, cwd=cwd, env=env) + return run_func( + cmd, + cwd=cwd, + env=env, + ) except subprocess.CalledProcessError: questionary.print("Command failed", style=ERROR_STYLE) raise typer.Exit(1) diff --git a/openllm_next/local.py b/openllm_next/local.py index 5cb8c281..626cc74b 100644 --- a/openllm_next/local.py +++ b/openllm_next/local.py @@ -1,13 +1,10 @@ import asyncio import questionary -import typer from openllm_next.common import BentoInfo, run_command from openllm_next.venv import ensure_venv -app = typer.Typer() - def _get_serve_cmd(bento: BentoInfo): cmd = ["bentoml", "serve", bento.tag] From 47fefe30ed3513cafc454588dedd513d9b62d62c Mon Sep 17 00:00:00 2001 From: bojiang Date: Mon, 3 Jun 2024 17:25:32 +0800 Subject: [PATCH 051/125] chattts --- chattts/.gitignore | 12 ++++++++++++ chattts/README.md | 34 ++++++++++++++++++++++++++++++---- chattts/service.py | 40 +++++++++++++++++++++++++++++++++++++--- 3 files changed, 79 insertions(+), 7 deletions(-) create mode 100644 chattts/.gitignore diff --git a/chattts/.gitignore b/chattts/.gitignore new file mode 100644 index 00000000..c6c5b0cc --- /dev/null +++ b/chattts/.gitignore @@ -0,0 +1,12 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# Environments +venv/ + +# BentoML +bentoml/client_id + +ChatTTS/ diff --git a/chattts/README.md b/chattts/README.md index 3de3a675..b4de51e2 100644 --- a/chattts/README.md +++ b/chattts/README.md @@ -1,15 +1,41 @@ -## Local Run & development +# BentoChatTTS + +[ChatTTS](https://github.com/2noise/ChatTTS) is a text-to-speech model designed specifically for dialogue scenario such as LLM assistant. + +## Prerequisites + +- You have installed Python 3.9+ and `pip`. See the [Python downloads page](https://www.python.org/downloads/) to learn more. +- You have a basic understanding of key concepts in BentoML, such as Services. We recommend you read [Quickstart](https://docs.bentoml.com/en/latest/get-started/quickstart.html) first. +- (Optional) We recommend you create a virtual environment for dependency isolation for this project. See the [Conda documentation](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) or the [Python documentation](https://docs.python.org/3/library/venv.html) for details. + +## Install Dependencies ``` pip install bentoml pip install -r requirements.txt +``` +If not already present, you need to install `libsox-dev` with your package manager first. + +## Run + +Start a Bento server with ChatTTS. + +``` export CHAT_TTS_REPO=https://github.com/2noise/ChatTTS.git bentoml serve ``` -(You may need to install `libsox-dev` with your package manager first) +The server is now active at [http://localhost:3000](http://localhost:3000/). You can interact with it using the Swagger UI. -## Get your own server +## Deploy -Get your token at: https://cloud.bentoml.com/ +You can deploy the ChatTTS Bento service to BentoCloud. + +[Sign up](https://www.bentoml.com/) if you haven't got a BentoCloud account. + +Make sure you have [logged in to BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html), then run the following command to deploy it. + +```bash +bentoml deploy . +``` diff --git a/chattts/service.py b/chattts/service.py index 74d765a6..6dfc6dba 100644 --- a/chattts/service.py +++ b/chattts/service.py @@ -15,6 +15,7 @@ CONSTANTS = yaml.safe_load(CONSTANT_YAML) CHATTTS_PATH = os.path.join(os.path.dirname(__file__), "ChatTTS") + @bentoml.service(**CONSTANTS["service_config"]) class Main: @@ -44,14 +45,47 @@ class Main: import ChatTTS self.chat = ChatTTS.Chat() - self.chat.load_models(compile=False) # Set to True for better performance + self.chat.load_models(compile=False) # Set to True for better performance @bentoml.api - def tts(self, text: str = "PUT YOUR TEXT HERE") -> Annotated[pathlib.Path, ContentType("audio/wav")]: + def tts( + self, + text: str = "PUT YOUR TEXT HERE", + speaker: str = "2", + ) -> Annotated[pathlib.Path, ContentType("audio/wav")]: + rhythm: bool = True + temperature: float = 0.3 + top_P: float = 0.7 + top_K: int = 20 + import torch import torchaudio - wavs = self.chat.infer([text]) + if speaker: + seed = int(speaker, 16) + torch.manual_seed(seed) + + if torch.cuda.is_available(): + torch.cuda.manual_seed(seed) + torch.cuda.manual_seed_all(seed) + + dim = self.chat.pretrain_models["gpt"].gpt.layers[0].mlp.gate_proj.in_features + std, mean = self.chat.pretrain_models["spk_stat"].chunk(2) + rand_spk = torch.randn(dim, device=std.device) * std + mean + + params_infer_code = { + "spk_emb": rand_spk, + "temperature": temperature, + "top_P": top_P, + "top_K": top_K, + } + + wavs = self.chat.infer( + [text], + skip_refine_text=rhythm, + params_infer_code=params_infer_code, + ) + output_io = io.BytesIO() torchaudio.save(output_io, torch.from_numpy(wavs[0]), 24000, format="wav") return output_io.getvalue() From 9d667bb46a2b7462be0c012e79dfbe3123fbab76 Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 4 Jun 2024 19:54:26 +0800 Subject: [PATCH 052/125] add more version of llama --- recipe.yaml | 34 +++++++++++++++++++++++++++++++--- vllm-chat/.gitignore | 12 ++++++++++++ 2 files changed, 43 insertions(+), 3 deletions(-) create mode 100644 vllm-chat/.gitignore diff --git a/recipe.yaml b/recipe.yaml index 888e7008..29e9d5eb 100644 --- a/recipe.yaml +++ b/recipe.yaml @@ -1,7 +1,6 @@ "phi3:3.8b-mini-instruct-4k-fp16": alias: - 3.8b - - mini project: vllm-chat service_config: name: phi3 @@ -30,6 +29,36 @@ model: meta-llama/Llama-2-7b-chat-hf max_model_len: 1024 chat_template: llama-2-chat +"llama2:13b-chat-fp16": + alias: + - 13b + project: vllm-chat + service_config: + name: llama2 + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-tesla-a100 + engine_config: + model: meta-llama/Llama-2-13b-chat-hf + max_model_len: 1024 + chat_template: llama-2-chat +"llama2:70b-chat-fp16": + alias: + - 70b + project: vllm-chat + service_config: + name: llama2 + traffic: + timeout: 300 + resources: + gpu: 2 + gpu_type: nvidia-a100-80g + engine_config: + model: meta-llama/Llama-2-70b-chat-hf + max_model_len: 1024 + chat_template: llama-2-chat "llama2:7b-chat-awq-4bit": alias: - 7b-4bit @@ -68,7 +97,6 @@ "mistral:7b-instruct-fp16": alias: - 7b - - 7b-instruct project: vllm-chat service_config: name: mistral @@ -110,7 +138,7 @@ gpu: 1 gpu_type: nvidia-a100-80g engine_config: - model: meta-llama/Meta-Llama-3-8B + model: casperhansen/llama-3-70b-instruct-awq max_model_len: 2048 quantization: awq "llama3:8b-instruct-fp16": diff --git a/vllm-chat/.gitignore b/vllm-chat/.gitignore new file mode 100644 index 00000000..d5629589 --- /dev/null +++ b/vllm-chat/.gitignore @@ -0,0 +1,12 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# Environments +venv/ + +# BentoML +bentoml/client_id + +chattts/ChatTTS/ From 810ba167033f394276a30090107b141067721416 Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 4 Jun 2024 20:17:45 +0800 Subject: [PATCH 053/125] match instance type --- openllm_next/__main__.py | 10 +++++++++- openllm_next/accelerator_spec.py | 1 + openllm_next/cloud.py | 4 ++-- 3 files changed, 12 insertions(+), 3 deletions(-) diff --git a/openllm_next/__main__.py b/openllm_next/__main__.py index c8d2dba4..71b424b8 100644 --- a/openllm_next/__main__.py +++ b/openllm_next/__main__.py @@ -76,6 +76,15 @@ def _pre_select(model: str) -> tuple[BentoInfo, DeploymentTarget]: bento, target = choosen if target is None: cloud_targets = get_cloud_machine_spec() + cloud_targets = [ + target for target in cloud_targets if can_run(bento, target) > 0 + ] + if len(cloud_targets) == 0: + questionary.print( + f"No suitable instance type found for {bento.name}:{bento.version}", + style="red", + ) + raise typer.Exit(1) target = questionary.select( "Select a cloud target", choices=[ @@ -84,7 +93,6 @@ def _pre_select(model: str) -> tuple[BentoInfo, DeploymentTarget]: target, ) for target in cloud_targets - if can_run(bento, target) > 0 ], ).ask() if not target: diff --git a/openllm_next/accelerator_spec.py b/openllm_next/accelerator_spec.py index 3021e301..d32bf9eb 100644 --- a/openllm_next/accelerator_spec.py +++ b/openllm_next/accelerator_spec.py @@ -48,6 +48,7 @@ ACCELERATOR_SPEC_DICT: dict[str, dict] = { "nvidia-tesla-l4": {"model": "L4", "memory_size": 24.0}, "nvidia-tesla-a10g": {"model": "A10G", "memory_size": 24.0}, "nvidia-a100-80g": {"model": "A100", "memory_size": 80.0}, + "nvidia-a100-80gb": {"model": "A100", "memory_size": 80.0}, "nvidia-tesla-a100": {"model": "A100", "memory_size": 40.0}, } diff --git a/openllm_next/cloud.py b/openllm_next/cloud.py index db51b638..71bd92f3 100644 --- a/openllm_next/cloud.py +++ b/openllm_next/cloud.py @@ -123,13 +123,13 @@ def get_cloud_machine_spec(): price=it["price"], accelerators=( [ACCELERATOR_SPECS[it["gpu_type"]] for _ in range(int(it["gpu"]))] - if it.get("gpu") + if it.get("gpu") and it["gpu_type"] in ACCELERATOR_SPECS else [] ), ) for it in instance_types ] - except (subprocess.CalledProcessError, json.JSONDecodeError, KeyError, ValueError): + except (subprocess.CalledProcessError, json.JSONDecodeError): questionary.print("Failed to get cloud instance types", style=ERROR_STYLE) return [] From d58aff9e022996dab2052432dec986675bd05212 Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 4 Jun 2024 20:31:52 +0800 Subject: [PATCH 054/125] only list first alias --- openllm_next/accelerator_spec.py | 2 +- openllm_next/model.py | 11 ++++++++++- 2 files changed, 11 insertions(+), 2 deletions(-) diff --git a/openllm_next/accelerator_spec.py b/openllm_next/accelerator_spec.py index d32bf9eb..43489bee 100644 --- a/openllm_next/accelerator_spec.py +++ b/openllm_next/accelerator_spec.py @@ -91,7 +91,7 @@ def can_run( target: DeploymentTarget | None = None, ) -> float: """ - Calculate if the resource_spec can be deployed on the target. + Calculate if the bento can be deployed on the target. """ if isinstance(resource_spec, BentoInfo): resource_spec = Resource( diff --git a/openllm_next/model.py b/openllm_next/model.py index f8c07088..9ef1baad 100644 --- a/openllm_next/model.py +++ b/openllm_next/model.py @@ -1,5 +1,4 @@ import collections -import os import typing import pyaml @@ -74,6 +73,16 @@ def list_bento(tag: str | None = None) -> typing.List[BentoInfo]: if model: model_list.append(model) model_list.sort(key=lambda x: x.tag) + if VERBOSE_LEVEL.get() <= 0: + seen = set() + model_list = [ + x + for x in model_list + if not ( + f"{x.bento_yaml['name']}:{x.bento_yaml['version']}" in seen + or seen.add(f"{x.bento_yaml['name']}:{x.bento_yaml['version']}") + ) + ] return model_list From 64b22098c7ee09c6f03d2d19c9ac6b82594cc2bb Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 4 Jun 2024 20:50:46 +0800 Subject: [PATCH 055/125] ask for updating repo --- openllm_next/cloud.py | 6 +++++- openllm_next/model.py | 3 ++- openllm_next/repo.py | 23 +++++++++++++++++++++++ 3 files changed, 30 insertions(+), 2 deletions(-) diff --git a/openllm_next/cloud.py b/openllm_next/cloud.py index 71bd92f3..ba3cebf9 100644 --- a/openllm_next/cloud.py +++ b/openllm_next/cloud.py @@ -141,4 +141,8 @@ def serve(bento: BentoInfo, target: DeploymentTarget): def run(bento: BentoInfo, target: DeploymentTarget): - pass + questionary.print( + "`run` with bentocloud is not supported yet, please use `serve` instead", + style=ERROR_STYLE, + ) + raise typer.Exit(1) diff --git a/openllm_next/model.py b/openllm_next/model.py index 9ef1baad..6d6a2f82 100644 --- a/openllm_next/model.py +++ b/openllm_next/model.py @@ -11,7 +11,7 @@ from openllm_next.common import ( BentoInfo, load_config, ) -from openllm_next.repo import parse_repo_url +from openllm_next.repo import ensure_repo_updated, parse_repo_url app = typer.Typer() @@ -42,6 +42,7 @@ def list_(): def list_bento(tag: str | None = None) -> typing.List[BentoInfo]: + ensure_repo_updated() if not tag: glob_pattern = "bentoml/bentos/*/*" elif ":" in tag: diff --git a/openllm_next/repo.py b/openllm_next/repo.py index f74d2116..b60da611 100644 --- a/openllm_next/repo.py +++ b/openllm_next/repo.py @@ -1,3 +1,4 @@ +import datetime import re import shutil @@ -14,6 +15,8 @@ from openllm_next.common import ( save_config, ) +UPDATE_INTERVAL = datetime.timedelta(days=3) + app = typer.Typer() @@ -91,6 +94,26 @@ def update(): if tuple(c.parts[-3:]) not in repos_in_use: shutil.rmtree(c, ignore_errors=True) questionary.print(f"Removed unused repo cache {c}") + with open(REPO_DIR / "last_update", "w") as f: + f.write(datetime.datetime.now().isoformat()) + + +def ensure_repo_updated(): + last_update_file = REPO_DIR / "last_update" + if not last_update_file.exists(): + choice = questionary.confirm( + "The repo cache is never updated, do you want to update it to fetch the latest model list?" + ).ask() + if choice: + update() + return + last_update = datetime.datetime.fromisoformat(last_update_file.read_text().strip()) + if datetime.datetime.now() - last_update > UPDATE_INTERVAL: + choice = questionary.confirm( + "The repo cache is outdated, do you want to update it to fetch the latest model list?" + ).ask() + if choice: + update() GIT_REPO_RE = re.compile( From a1397bb20ba71fec97c38d7c2afc6cb38ca5e79e Mon Sep 17 00:00:00 2001 From: bojiang <5886138+bojiang@users.noreply.github.com> Date: Tue, 4 Jun 2024 20:53:18 +0800 Subject: [PATCH 056/125] Update README.md --- README.md | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 8b137891..08b9a8a4 100644 --- a/README.md +++ b/README.md @@ -1 +1,6 @@ - +``` +pip install . +openllm serve +# or openllm run +``` +To find out what LLM models are already in your hands. From 35e4181d903611a0bdd6c69dcd3d00c745090764 Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 4 Jun 2024 21:22:31 +0800 Subject: [PATCH 057/125] support platforms filter --- openllm_next/accelerator_spec.py | 60 +++++++++++++++++++++++--------- openllm_next/cloud.py | 1 + openllm_next/common.py | 1 + 3 files changed, 45 insertions(+), 17 deletions(-) diff --git a/openllm_next/accelerator_spec.py b/openllm_next/accelerator_spec.py index 43489bee..3fd9ad56 100644 --- a/openllm_next/accelerator_spec.py +++ b/openllm_next/accelerator_spec.py @@ -4,6 +4,9 @@ import functools import math from types import SimpleNamespace +import psutil +import questionary + from openllm_next.common import BentoInfo, DeploymentTarget @@ -60,6 +63,16 @@ ACCELERATOR_SPECS: dict[str, Accelerator] = { @functools.lru_cache def get_local_machine_spec(): + if psutil.MACOS: + return DeploymentTarget(accelerators=[], source="local", platform="macos") + + if psutil.WINDOWS: + platform = "windows" + elif psutil.LINUX: + platform = "linux" + else: + raise NotImplementedError(f"Unsupported platform") + from pynvml import ( nvmlDeviceGetCount, nvmlDeviceGetHandleByIndex, @@ -69,36 +82,49 @@ def get_local_machine_spec(): nvmlShutdown, ) - nvmlInit() - device_count = nvmlDeviceGetCount() - accelerators: list[Accelerator] = [] - for i in range(device_count): - handle = nvmlDeviceGetHandleByIndex(i) - name = nvmlDeviceGetName(handle) - memory_info = nvmlDeviceGetMemoryInfo(handle) - accelerators.append( - Accelerator( - name=name, memory_size=math.ceil(int(memory_info.total) / 1024**3) + try: + nvmlInit() + device_count = nvmlDeviceGetCount() + accelerators: list[Accelerator] = [] + for i in range(device_count): + handle = nvmlDeviceGetHandleByIndex(i) + name = nvmlDeviceGetName(handle) + memory_info = nvmlDeviceGetMemoryInfo(handle) + accelerators.append( + Accelerator( + name=name, memory_size=math.ceil(int(memory_info.total) / 1024**3) + ) ) + nvmlShutdown() + return DeploymentTarget( + accelerators=accelerators, + source="local", + platform=platform, ) - nvmlShutdown() - return DeploymentTarget(accelerators=accelerators, source="local") + except Exception as e: + questionary.print( + f"Failed to get local GPU info. Ensure nvidia driver is installed to enable local GPU deployment", + color="yellow", + ) + return DeploymentTarget(accelerators=[], source="local", platform=platform) @functools.lru_cache() def can_run( - resource_spec: Resource | BentoInfo, + bento: Resource | BentoInfo, target: DeploymentTarget | None = None, ) -> float: """ Calculate if the bento can be deployed on the target. """ - if isinstance(resource_spec, BentoInfo): - resource_spec = Resource( - **(resource_spec.bento_yaml["services"][0]["config"]["resources"]) - ) if target is None: target = get_local_machine_spec() + + resource_spec = Resource(**(bento.bento_yaml["services"][0]["config"]["resources"])) + platforms = bento.bento_yaml["labels"].get("platforms", "linux").split(",") + + if target.platform not in platforms: + return 0.0 if resource_spec.gpu > 0: required_gpu = ACCELERATOR_SPECS[resource_spec.gpu_type] filtered_accelerators = [ diff --git a/openllm_next/cloud.py b/openllm_next/cloud.py index ba3cebf9..132e6c13 100644 --- a/openllm_next/cloud.py +++ b/openllm_next/cloud.py @@ -121,6 +121,7 @@ def get_cloud_machine_spec(): source="cloud", name=it["name"], price=it["price"], + platform="linux", accelerators=( [ACCELERATOR_SPECS[it["gpu_type"]] for _ in range(int(it["gpu"]))] if it.get("gpu") and it["gpu_type"] in ACCELERATOR_SPECS diff --git a/openllm_next/common.py b/openllm_next/common.py index 69cdf6e2..1f6ccc91 100644 --- a/openllm_next/common.py +++ b/openllm_next/common.py @@ -194,6 +194,7 @@ class DeploymentTarget(SimpleNamespace): source: str = "local" name: str = "local" price: str = "" + platform = "linux" accelerators: list[Accelerator] def __hash__(self): From ed55f2901104ec4e17d1a7aaec9a820621a26bc1 Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 4 Jun 2024 22:27:05 +0800 Subject: [PATCH 058/125] support Python 3.9 --- openllm_next/__main__.py | 1 - openllm_next/accelerator_spec.py | 7 ++++--- openllm_next/cloud.py | 3 ++- openllm_next/common.py | 2 +- openllm_next/model.py | 2 +- openllm_next/venv.py | 9 +++++++-- 6 files changed, 15 insertions(+), 9 deletions(-) diff --git a/openllm_next/__main__.py b/openllm_next/__main__.py index 71b424b8..8eedfa02 100644 --- a/openllm_next/__main__.py +++ b/openllm_next/__main__.py @@ -4,7 +4,6 @@ import questionary import typer from openllm_next.accelerator_spec import ( - ACCELERATOR_SPECS, DeploymentTarget, can_run, get_local_machine_spec, diff --git a/openllm_next/accelerator_spec.py b/openllm_next/accelerator_spec.py index 3fd9ad56..3850b680 100644 --- a/openllm_next/accelerator_spec.py +++ b/openllm_next/accelerator_spec.py @@ -1,4 +1,5 @@ from __future__ import annotations +import typing import functools import math @@ -101,7 +102,7 @@ def get_local_machine_spec(): source="local", platform=platform, ) - except Exception as e: + except Exception: questionary.print( f"Failed to get local GPU info. Ensure nvidia driver is installed to enable local GPU deployment", color="yellow", @@ -111,8 +112,8 @@ def get_local_machine_spec(): @functools.lru_cache() def can_run( - bento: Resource | BentoInfo, - target: DeploymentTarget | None = None, + bento: typing.Union[Resource, BentoInfo], + target: typing.Optional[DeploymentTarget] = None, ) -> float: """ Calculate if the bento can be deployed on the target. diff --git a/openllm_next/cloud.py b/openllm_next/cloud.py index 132e6c13..988f9aca 100644 --- a/openllm_next/cloud.py +++ b/openllm_next/cloud.py @@ -4,6 +4,7 @@ import pathlib import shutil import subprocess +import typing import questionary import typer @@ -18,7 +19,7 @@ from openllm_next.common import ( app = typer.Typer() -def _get_deploy_cmd(bento: BentoInfo, target: DeploymentTarget | None = None): +def _get_deploy_cmd(bento: BentoInfo, target: typing.Optional[DeploymentTarget]=None): cmd = ["bentoml", "deploy", bento.tag] env = { "BENTOML_HOME": f"{bento.repo.path}/bentoml", diff --git a/openllm_next/common.py b/openllm_next/common.py index 1f6ccc91..b8f8b6d5 100644 --- a/openllm_next/common.py +++ b/openllm_next/common.py @@ -233,7 +233,7 @@ def run_command( venv=None, silent=False, background=False, -) -> subprocess.CompletedProcess | subprocess.Popen: +) -> typing.Union[subprocess.CompletedProcess, subprocess.Popen]: if background: run_func = subprocess.Popen else: diff --git a/openllm_next/model.py b/openllm_next/model.py index 6d6a2f82..f40e01dc 100644 --- a/openllm_next/model.py +++ b/openllm_next/model.py @@ -41,7 +41,7 @@ def list_(): ) -def list_bento(tag: str | None = None) -> typing.List[BentoInfo]: +def list_bento(tag: typing.Optional[str] = None) -> typing.List[BentoInfo]: ensure_repo_updated() if not tag: glob_pattern = "bentoml/bentos/*/*" diff --git a/openllm_next/venv.py b/openllm_next/venv.py index 50683c60..0ce2ff29 100644 --- a/openllm_next/venv.py +++ b/openllm_next/venv.py @@ -1,4 +1,5 @@ import functools +import typing import pathlib import shutil from types import SimpleNamespace @@ -10,7 +11,7 @@ import typer from openllm_next.common import VENV_DIR, VERBOSE_LEVEL, BentoInfo, md5, run_command -def _resolve_packages(requirement: str | pathlib.Path) -> dict[str, str]: +def _resolve_packages(requirement: typing.Union[pathlib.Path, str]) -> dict[str, str]: from pip_requirements_parser import RequirementsFile requirements_txt = RequirementsFile.from_file( @@ -78,9 +79,11 @@ def _resolve_bento_env_specs(bento: BentoInfo): def _ensure_venv( - env_spec: EnvSpec, parrent_venv: pathlib.Path | None = None + env_spec: EnvSpec, parrent_venv: typing.Optional[pathlib.Path] = None, ) -> pathlib.Path: venv = VENV_DIR / str(hash(env_spec)) + if venv.exists() and not (venv / "DONE").exists(): + shutil.rmtree(venv, ignore_errors=True) if not venv.exists(): questionary.print(f"Installing model dependencies({venv})...", style="green") try: @@ -116,6 +119,8 @@ def _ensure_venv( ], silent=VERBOSE_LEVEL.get() < 1, ) + with open(venv / "DONE", "w") as f: + f.write("DONE") except Exception: shutil.rmtree(venv, ignore_errors=True) questionary.print( From 091829a83018570501a2433cc2f5c5f63f9e71bf Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 4 Jun 2024 22:50:10 +0800 Subject: [PATCH 059/125] support Python>=3.9 --- vllm-chat/bentofile.yaml | 3 +-- vllm-chat/service.py | 6 +++--- 2 files changed, 4 insertions(+), 5 deletions(-) diff --git a/vllm-chat/bentofile.yaml b/vllm-chat/bentofile.yaml index 1ef27b35..8e5bdedc 100644 --- a/vllm-chat/bentofile.yaml +++ b/vllm-chat/bentofile.yaml @@ -1,10 +1,9 @@ service: "service:VLLM" labels: owner: bentoml-team - stage: demo + platforms: linux include: - "*.py" -- "config.yaml" - "bentovllm_openai/*.py" - "chat_templates/chat_templates/*.jinja" - "chat_templates/generation_configs/*.json" diff --git a/vllm-chat/service.py b/vllm-chat/service.py index 44c23626..959ae7dc 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -1,7 +1,7 @@ import uuid import json import os -from typing import AsyncGenerator +from typing import AsyncGenerator, Union from typing_extensions import Annotated import functools @@ -86,8 +86,8 @@ class VLLM: Ge(128), Le(ENGINE_CONFIG["max_model_len"]), ] = ENGINE_CONFIG["max_model_len"], - stop: list[str] | str | None = None, - stop_token_ids: list[int] | None = None, + stop: Union[list[str], str, None] = None, + stop_token_ids: Union[list[int], None] = None, ) -> AsyncGenerator[str, None]: """ light-weight chat API that takes in a list of messages and returns a response From cbde63ab2427ad8c12d5e3dbe20a0c7e92d422e2 Mon Sep 17 00:00:00 2001 From: Rick Zhou Date: Tue, 4 Jun 2024 21:21:12 +0000 Subject: [PATCH 060/125] feat: Use community chat template as the source of truth. Fall back to HF tokenizer template --- vllm-chat/bentovllm_openai/utils.py | 1 + vllm-chat/service.py | 27 +++++++++++++++++---------- 2 files changed, 18 insertions(+), 10 deletions(-) diff --git a/vllm-chat/bentovllm_openai/utils.py b/vllm-chat/bentovllm_openai/utils.py index 88f1dd61..38ab85bd 100644 --- a/vllm-chat/bentovllm_openai/utils.py +++ b/vllm-chat/bentovllm_openai/utils.py @@ -88,6 +88,7 @@ def openai_endpoints( if self.chat_template is None and chat_template_model_id is not None: from transformers import AutoTokenizer + # If no community chat template is provided, use the tokenizer's chat template _tokenizer = AutoTokenizer.from_pretrained(chat_template_model_id) self.chat_template = _tokenizer.chat_template diff --git a/vllm-chat/service.py b/vllm-chat/service.py index 959ae7dc..ed0dccb5 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -1,25 +1,30 @@ -import uuid -import json -import os -from typing import AsyncGenerator, Union -from typing_extensions import Annotated import functools +import json +import logging +import os +import uuid +from typing import AsyncGenerator, Union import bentoml -from annotated_types import Ge, Le -from bentovllm_openai.utils import openai_endpoints import yaml +from annotated_types import Ge, Le from bento_constants import CONSTANT_YAML - +from bentovllm_openai.utils import openai_endpoints +from typing_extensions import Annotated CONSTANTS = yaml.safe_load(CONSTANT_YAML) ENGINE_CONFIG = CONSTANTS["engine_config"] SERVICE_CONFIG = CONSTANTS["service_config"] +CHAT_TEMPLATE = CONSTANTS.get("chat_template") + +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) @functools.lru_cache(maxsize=1) def _get_gen_config(community_chat_template: str) -> dict: + logger.info(f"Load community_chat_template: {community_chat_template}") chat_template_path = os.path.join( os.path.dirname(__file__), "chat_templates", "chat_templates" ) @@ -37,17 +42,19 @@ def _get_gen_config(community_chat_template: str) -> dict: @openai_endpoints( served_model_names=[ENGINE_CONFIG["model"]], + chat_template=_get_gen_config(CHAT_TEMPLATE)["template"] if CHAT_TEMPLATE else None, chat_template_model_id=ENGINE_CONFIG["model"], ) @bentoml.service(**SERVICE_CONFIG) class VLLM: def __init__(self) -> None: - from vllm import AsyncEngineArgs, AsyncLLMEngine from transformers import AutoTokenizer + from vllm import AsyncEngineArgs, AsyncLLMEngine ENGINE_ARGS = AsyncEngineArgs(**ENGINE_CONFIG) self.engine = AsyncLLMEngine.from_engine_args(ENGINE_ARGS) self.tokenizer = AutoTokenizer.from_pretrained(ENGINE_CONFIG["model"]) + logger.info(f"VLLM service initialized with model: {ENGINE_CONFIG['model']}") @bentoml.api async def generate( @@ -94,7 +101,7 @@ class VLLM: """ from vllm import SamplingParams - if CONSTANTS.get("chat_template"): # community chat template + if CHAT_TEMPLATE: # community chat template gen_config = _get_gen_config(CONSTANTS["chat_template"]) if not stop: if gen_config["stop_str"]: From a0bda5229974df7a6e3e6b4be4859ba654e02cf6 Mon Sep 17 00:00:00 2001 From: bojiang Date: Wed, 5 Jun 2024 13:40:43 +0800 Subject: [PATCH 061/125] add source_repo --- vllm-chat/bentofile.yaml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/vllm-chat/bentofile.yaml b/vllm-chat/bentofile.yaml index 8e5bdedc..ab22e759 100644 --- a/vllm-chat/bentofile.yaml +++ b/vllm-chat/bentofile.yaml @@ -2,6 +2,8 @@ service: "service:VLLM" labels: owner: bentoml-team platforms: linux + source_repo: https://github.com/bentoml/openllm-repo-recipe.git + source_directory: vllm-chat include: - "*.py" - "bentovllm_openai/*.py" From ac0eb048673915131f1d68b55f62bbb55b2db55c Mon Sep 17 00:00:00 2001 From: bojiang Date: Thu, 6 Jun 2024 14:42:16 +0800 Subject: [PATCH 062/125] chore: stream output for background commands --- openllm_next/cloud.py | 2 +- openllm_next/common.py | 98 ++++++++++++++++++++++++++++-------------- openllm_next/local.py | 22 +++++----- openllm_next/venv.py | 3 +- 4 files changed, 81 insertions(+), 44 deletions(-) diff --git a/openllm_next/cloud.py b/openllm_next/cloud.py index 988f9aca..d2d85286 100644 --- a/openllm_next/cloud.py +++ b/openllm_next/cloud.py @@ -19,7 +19,7 @@ from openllm_next.common import ( app = typer.Typer() -def _get_deploy_cmd(bento: BentoInfo, target: typing.Optional[DeploymentTarget]=None): +def _get_deploy_cmd(bento: BentoInfo, target: typing.Optional[DeploymentTarget] = None): cmd = ["bentoml", "deploy", bento.tag] env = { "BENTOML_HOME": f"{bento.repo.path}/bentoml", diff --git a/openllm_next/common.py b/openllm_next/common.py index b8f8b6d5..30b35dd4 100644 --- a/openllm_next/common.py +++ b/openllm_next/common.py @@ -1,4 +1,5 @@ import functools +import asyncio import hashlib import json import os @@ -201,7 +202,6 @@ class DeploymentTarget(SimpleNamespace): return hash(self.source) -@typing.overload def run_command( cmd, cwd=None, @@ -209,35 +209,7 @@ def run_command( copy_env=True, venv=None, silent=False, - background: typing.Literal[False] = False, -) -> subprocess.CompletedProcess: ... - - -@typing.overload -def run_command( - cmd, - cwd=None, - env=None, - copy_env=True, - venv=None, - silent=False, - background: typing.Literal[True] = True, -) -> subprocess.Popen: ... - - -def run_command( - cmd, - cwd=None, - env=None, - copy_env=True, - venv=None, - silent=False, - background=False, -) -> typing.Union[subprocess.CompletedProcess, subprocess.Popen]: - if background: - run_func = subprocess.Popen - else: - run_func = subprocess.run +) -> subprocess.CompletedProcess: import shlex env = env or {} @@ -268,7 +240,7 @@ def run_command( try: if silent: - return run_func( # type: ignore + return subprocess.run( # type: ignore cmd, cwd=cwd, env=env, @@ -276,7 +248,7 @@ def run_command( stderr=subprocess.DEVNULL, ) else: - return run_func( + return subprocess.run( cmd, cwd=cwd, env=env, @@ -286,6 +258,68 @@ def run_command( raise typer.Exit(1) +async def _stream_print(stream, style="gray"): + async for line in stream: + questionary.print(line.decode(), style=style, end="") + + +async def async_run_command( + cmd, + cwd=None, + env=None, + copy_env=True, + venv=None, + silent=True, + stream_stdout=False, + stream_stderr=False, +): + import shlex + + env = env or {} + cmd = [str(c) for c in cmd] + + if not silent: + questionary.print("\n") + if cwd: + questionary.print(f"$ cd {cwd}", style="bold") + if env: + for k, v in env.items(): + questionary.print(f"$ export {k}={shlex.quote(v)}", style="bold") + if venv: + questionary.print(f"$ source {venv / 'bin' / 'activate'}", style="bold") + questionary.print(f"$ {' '.join(cmd)}", style="bold") + + if venv: + py = venv / "bin" / "python" + else: + py = sys.executable + + if copy_env: + env = {**os.environ, **env} + + if cmd and cmd[0] == "bentoml": + cmd = [py, "-m", "bentoml"] + cmd[1:] + if cmd and cmd[0] == "python": + cmd = [py] + cmd[1:] + + try: + proc = await asyncio.create_subprocess_shell( + " ".join(map(str, cmd)), + stdout=asyncio.subprocess.PIPE, + stderr=asyncio.subprocess.PIPE, + cwd=cwd, + env=env, + ) + if stream_stdout: + asyncio.create_task(_stream_print(proc.stdout)) + if stream_stderr: + asyncio.create_task(_stream_print(proc.stderr, style="red")) + return proc + except subprocess.CalledProcessError: + questionary.print("Command failed", style=ERROR_STYLE) + raise typer.Exit(1) + + def md5(*strings: str) -> int: m = hashlib.md5() for s in strings: diff --git a/openllm_next/local.py b/openllm_next/local.py index 626cc74b..a118ceda 100644 --- a/openllm_next/local.py +++ b/openllm_next/local.py @@ -1,8 +1,10 @@ import asyncio +import httpx +import typer import questionary -from openllm_next.common import BentoInfo, run_command +from openllm_next.common import BentoInfo, run_command, async_run_command from openllm_next.venv import ensure_venv @@ -23,13 +25,14 @@ def serve(bento: BentoInfo): async def _run_model(bento: BentoInfo, timeout: int = 600): venv = ensure_venv(bento) cmd, env, cwd = _get_serve_cmd(bento) - server_proc = run_command( + server_proc = await async_run_command( cmd, env=env, cwd=cwd, venv=venv, - silent=True, - background=True, + silent=False, + stream_stderr=True, + stream_stdout=True, ) import bentoml @@ -38,20 +41,19 @@ async def _run_model(bento: BentoInfo, timeout: int = 600): questionary.print("Model loading...", style="green") for _ in range(timeout): try: - client = bentoml.AsyncHTTPClient( - "http://localhost:3000", timeout=timeout - ) - resp = await client.request("GET", "/readyz") + resp = httpx.get("http://localhost:3000/readyz", timeout=3) if resp.status_code == 200: break - except bentoml.exceptions.BentoMLException: - await asyncio.sleep(1) + except httpx.RequestError: + await asyncio.sleep(0) else: questionary.print("Model failed to load", style="red") + server_proc.terminate() return questionary.print("Model is ready", style="green") messages = [] + client = bentoml.AsyncHTTPClient("http://localhost:3000", timeout=timeout) while True: try: message = input("user: ") diff --git a/openllm_next/venv.py b/openllm_next/venv.py index 0ce2ff29..8e66cb25 100644 --- a/openllm_next/venv.py +++ b/openllm_next/venv.py @@ -79,7 +79,8 @@ def _resolve_bento_env_specs(bento: BentoInfo): def _ensure_venv( - env_spec: EnvSpec, parrent_venv: typing.Optional[pathlib.Path] = None, + env_spec: EnvSpec, + parrent_venv: typing.Optional[pathlib.Path] = None, ) -> pathlib.Path: venv = VENV_DIR / str(hash(env_spec)) if venv.exists() and not (venv / "DONE").exists(): From acdeafef48956d612051c14fa631e544db763e52 Mon Sep 17 00:00:00 2001 From: bojiang Date: Fri, 7 Jun 2024 09:46:03 +0800 Subject: [PATCH 063/125] stop stream server log when ready --- openllm_next/common.py | 8 +------- openllm_next/local.py | 19 +++++++++++++++---- 2 files changed, 16 insertions(+), 11 deletions(-) diff --git a/openllm_next/common.py b/openllm_next/common.py index 30b35dd4..785d6b26 100644 --- a/openllm_next/common.py +++ b/openllm_next/common.py @@ -258,7 +258,7 @@ def run_command( raise typer.Exit(1) -async def _stream_print(stream, style="gray"): +async def stream_command_output(stream, style="gray"): async for line in stream: questionary.print(line.decode(), style=style, end="") @@ -270,8 +270,6 @@ async def async_run_command( copy_env=True, venv=None, silent=True, - stream_stdout=False, - stream_stderr=False, ): import shlex @@ -310,10 +308,6 @@ async def async_run_command( cwd=cwd, env=env, ) - if stream_stdout: - asyncio.create_task(_stream_print(proc.stdout)) - if stream_stderr: - asyncio.create_task(_stream_print(proc.stderr, style="red")) return proc except subprocess.CalledProcessError: questionary.print("Command failed", style=ERROR_STYLE) diff --git a/openllm_next/local.py b/openllm_next/local.py index a118ceda..d5e8239e 100644 --- a/openllm_next/local.py +++ b/openllm_next/local.py @@ -1,10 +1,14 @@ import asyncio import httpx -import typer import questionary -from openllm_next.common import BentoInfo, run_command, async_run_command +from openllm_next.common import ( + BentoInfo, + run_command, + async_run_command, + stream_command_output, +) from openllm_next.venv import ensure_venv @@ -31,8 +35,12 @@ async def _run_model(bento: BentoInfo, timeout: int = 600): cwd=cwd, venv=venv, silent=False, - stream_stderr=True, - stream_stdout=True, + ) + stdout_streamer = asyncio.create_task( + stream_command_output(server_proc.stdout, style="gray") + ) + stderr_streamer = asyncio.create_task( + stream_command_output(server_proc.stderr, style="#BD2D0F") ) import bentoml @@ -51,6 +59,9 @@ async def _run_model(bento: BentoInfo, timeout: int = 600): server_proc.terminate() return + stdout_streamer.cancel() + stderr_streamer.cancel() + questionary.print("Model is ready", style="green") messages = [] client = bentoml.AsyncHTTPClient("http://localhost:3000", timeout=timeout) From 81c12a42f6523537e1764c8ce576dc20676a6c39 Mon Sep 17 00:00:00 2001 From: bojiang Date: Fri, 7 Jun 2024 11:55:27 +0800 Subject: [PATCH 064/125] add qwen --- recipe.yaml | 28 ++++++++++++++++++++++++++++ 1 file changed, 28 insertions(+) diff --git a/recipe.yaml b/recipe.yaml index 29e9d5eb..b0ec497d 100644 --- a/recipe.yaml +++ b/recipe.yaml @@ -213,3 +213,31 @@ max_model_len: 2048 quantization: awq chat_template: gemma-it +"qwen2:1.5b-instruct-fp16": + alias: + - 1.5b + project: vllm-chat + service_config: + name: qwen2 + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-rtx-3060 + engine_config: + model: Qwen/Qwen2-1.5B-Instruct + max_model_len: 2048 +"qwen2:7b-instruct-fp16": + alias: + - 7b + project: vllm-chat + service_config: + name: qwen2 + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-tesla-l4 + engine_config: + model: Qwen/Qwen2-7B-Instruct + max_model_len: 2048 From 69597378e7505fd5742e5a45ed696cb0b0b28718 Mon Sep 17 00:00:00 2001 From: bojiang <5886138+bojiang@users.noreply.github.com> Date: Fri, 7 Jun 2024 11:59:10 +0800 Subject: [PATCH 065/125] Delete outlines-integration directory --- outlines-integration/.bentoignore | 5 -- outlines-integration/README.md | 88 --------------------------- outlines-integration/bentofile.yaml | 9 --- outlines-integration/requirements.txt | 5 -- outlines-integration/service.py | 82 ------------------------- 5 files changed, 189 deletions(-) delete mode 100644 outlines-integration/.bentoignore delete mode 100644 outlines-integration/README.md delete mode 100644 outlines-integration/bentofile.yaml delete mode 100644 outlines-integration/requirements.txt delete mode 100644 outlines-integration/service.py diff --git a/outlines-integration/.bentoignore b/outlines-integration/.bentoignore deleted file mode 100644 index d9cf1150..00000000 --- a/outlines-integration/.bentoignore +++ /dev/null @@ -1,5 +0,0 @@ -__pycache__/ -*.py[cod] -*$py.class -.ipynb_checkpoints -venv/ diff --git a/outlines-integration/README.md b/outlines-integration/README.md deleted file mode 100644 index d3b4edfe..00000000 --- a/outlines-integration/README.md +++ /dev/null @@ -1,88 +0,0 @@ -
-

Output structured data with Outlines and BentoML

-
- -[Outlines](https://github.com/outlines-dev/outlines) is an open-source Python package for structured text generation, integrating with various models to produce controlled, format-specific outputs​. It offers capabilities like fast regex-structured generation, JSON generation following a JSON schema or a Pydantic model, and grammar-structured generation. - -This is a BentoML example project, demonstrating how to output structured data from an LLM using Outlines and BentoML. See [here](https://github.com/bentoml/BentoML?tab=readme-ov-file#%EF%B8%8F-what-you-can-build-with-bentoml) for a full list of BentoML example projects. - -## Prerequisites - -- You have installed Python 3.8+ and `pip`. See the [Python downloads page](https://www.python.org/downloads/) to learn more. -- You have a basic understanding of key concepts in BentoML, such as Services. We recommend you read [Quickstart](https://docs.bentoml.com/en/1.2/get-started/quickstart.html) first. -- If you want to test the Service locally, you need a Nvidia GPU with at least 16G VRAM. -- (Optional) We recommend you create a virtual environment for dependency isolation for this project. See the [Conda documentation](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) or the [Python documentation](https://docs.python.org/3/library/venv.html) for details. - -## Install dependencies - -```bash -git clone https://github.com/bentoml/BentoVLLM.git -cd BentoVLLM/outlines-integration -pip install -r requirements.txt && pip install -f -U "pydantic>=2.0" -``` - -## Run the BentoML Service - -We have defined a BentoML Service in `service.py`. Run `bentoml serve` in your project directory to start the Service. - -```bash -$ bentoml serve . - -2024-03-27T10:14:50+0000 [INFO] [cli] Starting production HTTP BentoServer from "service:VLLM" listening on http://localhost:3000 (Press CTRL+C to quit) -INFO 03-27 10:14:54 llm_engine.py:87] Initializing an LLM engine with config: model='mistralai/Mistral-7B-Instruct-v0.2', tokenizer='mistralai/Mistral-7B-Instruct-v0.2', tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.bfloat16, max_seq_len=1024, download_dir=None, load_format=auto, tensor_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto, device_config=cuda, seed=0) -``` - -The server is now active at [http://localhost:3000](http://localhost:3000/). You can interact with it using the Swagger UI or in other different ways. - -CURL - -```bash -curl -X 'POST' \ - 'http://localhost:3000/generate' \ - -H 'accept: text/event-stream' \ - -H 'Content-Type: application/json' \ - -d '{ - "prompt": "Create a user profile with the fields name, last_name and id. name should be common English first names. last_name should be common English last names. id should be a random integer", - "max_tokens": 1024, - "json_schema": "\n{\n \"title\": \"User\",\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\"type\": \"string\"},\n \"last_name\": {\"type\": \"string\"},\n \"id\": {\"type\": \"integer\"}\n }\n}\n", - "regex_string": null -}' -``` - -Python client - -```python -import bentoml - -with bentoml.SyncHTTPClient("http://localhost:3000") as client: - result = client.generate( - json_schema="\n{\n \"title\": \"User\",\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\"type\": \"string\"},\n \"last_name\": {\"type\": \"string\"},\n \"id\": {\"type\": \"integer\"}\n }\n}\n", - max_tokens=1024, - prompt="Create a user profile with the fields name, last_name and id. name should be common English first names. last_name should be common English last names. id should be a random integer", - regex_string="", - ) -``` - -Example output: - -```bash -{ - "name": "Oliver", - "last_name": "Johnson", - "id": 123456 -} -``` - -## Deploy to BentoCloud - -After the Service is ready, you can deploy the application to BentoCloud for better management and scalability. [Sign up](https://www.bentoml.com/) if you haven't got a BentoCloud account. - -Make sure you have [logged in to BentoCloud](https://docs.bentoml.com/en/latest/bentocloud/how-tos/manage-access-token.html), then run the following command to deploy it. - -```bash -bentoml deploy . -``` - -Once the application is up and running on BentoCloud, you can access it via the exposed URL. - -**Note**: For custom deployment in your own infrastructure, use [BentoML to generate an OCI-compliant image](https://docs.bentoml.com/en/latest/guides/containerization.html). diff --git a/outlines-integration/bentofile.yaml b/outlines-integration/bentofile.yaml deleted file mode 100644 index 54f2fb0a..00000000 --- a/outlines-integration/bentofile.yaml +++ /dev/null @@ -1,9 +0,0 @@ -service: "service:VLLM" -labels: - owner: bentoml-team - stage: demo -include: -- "*.py" -python: - requirements_txt: "./requirements.txt" - lock_packages: false diff --git a/outlines-integration/requirements.txt b/outlines-integration/requirements.txt deleted file mode 100644 index f706074e..00000000 --- a/outlines-integration/requirements.txt +++ /dev/null @@ -1,5 +0,0 @@ -bentoml>=1.2.4 -torch==2.1.2 -transformers==4.38.2 -vllm==0.3.3 -outlines==0.0.37 diff --git a/outlines-integration/service.py b/outlines-integration/service.py deleted file mode 100644 index f1be8970..00000000 --- a/outlines-integration/service.py +++ /dev/null @@ -1,82 +0,0 @@ -import uuid -import typing as t -from typing import AsyncGenerator - -import bentoml -from annotated_types import Ge, Le -from typing_extensions import Annotated - - -MAX_TOKENS = 1024 -PROMPT_TEMPLATE = """[INST] -Always assist with care, respect, and truth. Respond with utmost utility yet securely. Avoid harmful, unethical, prejudiced, or negative content. Ensure replies promote fairness and positivity. -{user_prompt} [/INST] """ - - -MODEL_ID = "mistralai/Mistral-7B-Instruct-v0.2" - -DEFAULT_SCHEMA = """ -{ - "title": "User", - "type": "object", - "properties": { - "name": {"type": "string"}, - "last_name": {"type": "string"}, - "id": {"type": "integer"} - } -} -""" - -DEFAULT_USER_PROMPT = "Create a user profile with the fields name, last_name and id. name should be common English first names. last_name should be common English last names. id should be a random integer" - - -@bentoml.service( - name="mistral-7b-instruct-outlines-service", - traffic={ - "timeout": 300, - }, - resources={ - "gpu": 1, - "gpu_type": "nvidia-l4", - }, -) -class VLLM: - def __init__(self) -> None: - from vllm import AsyncEngineArgs, AsyncLLMEngine - ENGINE_ARGS = AsyncEngineArgs( - model=MODEL_ID, - max_model_len=MAX_TOKENS - ) - - self.engine = AsyncLLMEngine.from_engine_args(ENGINE_ARGS) - - @bentoml.api - async def generate( - self, - prompt: str = DEFAULT_USER_PROMPT, - max_tokens: Annotated[int, Ge(128), Le(MAX_TOKENS)] = MAX_TOKENS, - json_schema: t.Optional[str] = DEFAULT_SCHEMA, - regex_string: t.Optional[str] = None, - ) -> AsyncGenerator[str, None]: - from vllm import SamplingParams - from outlines.integrations.vllm import JSONLogitsProcessor, RegexLogitsProcessor - - if json_schema is not None: - logits_processors = [JSONLogitsProcessor(json_schema, self.engine.engine)] - elif regex_string is not None: - logits_processors = [RegexLogitsProcessor(regex_string, self.engine.engine)] - else: - logits_processors = [] - - sampling_param = SamplingParams( - max_tokens=max_tokens, - logits_processors=logits_processors, - ) - prompt = PROMPT_TEMPLATE.format(user_prompt=prompt) - stream = await self.engine.add_request(uuid.uuid4().hex, prompt, sampling_param) - - cursor = 0 - async for request_output in stream: - text = request_output.outputs[0].text - yield text[cursor:] - cursor = len(text) From 1545a6ae807093bf63adba3642a982d428b06272 Mon Sep 17 00:00:00 2001 From: bojiang Date: Fri, 7 Jun 2024 14:21:38 +0800 Subject: [PATCH 066/125] fix: terminate subprocess --- openllm_next/local.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/openllm_next/local.py b/openllm_next/local.py index d5e8239e..265006e9 100644 --- a/openllm_next/local.py +++ b/openllm_next/local.py @@ -79,11 +79,13 @@ async def _run_model(bento: BentoInfo, timeout: int = 600): except KeyboardInterrupt: break - except asyncio.CancelledError: + except (asyncio.CancelledError, httpx.RequestError): pass finally: questionary.print("\nStopping model server...", style="green") - server_proc.terminate() + if server_proc.returncode is None: + server_proc.terminate() + await server_proc.wait() questionary.print("Stopped model server", style="green") From 5d97ef604b739aee1c113136fa7ed8dc8f10120b Mon Sep 17 00:00:00 2001 From: bojiang Date: Sat, 8 Jun 2024 01:21:40 +0800 Subject: [PATCH 067/125] fix: ensure process exit --- openllm_next/common.py | 11 ++++++++-- openllm_next/local.py | 46 +++++++++++++++++++++++------------------- 2 files changed, 34 insertions(+), 23 deletions(-) diff --git a/openllm_next/common.py b/openllm_next/common.py index 785d6b26..ef5e348a 100644 --- a/openllm_next/common.py +++ b/openllm_next/common.py @@ -1,4 +1,5 @@ import functools +import signal import asyncio import hashlib import json @@ -7,7 +8,7 @@ import pathlib import subprocess import sys import typing -from contextlib import contextmanager +from contextlib import contextmanager, asynccontextmanager from types import SimpleNamespace import questionary @@ -263,6 +264,7 @@ async def stream_command_output(stream, style="gray"): questionary.print(line.decode(), style=style, end="") +@asynccontextmanager async def async_run_command( cmd, cwd=None, @@ -300,6 +302,7 @@ async def async_run_command( if cmd and cmd[0] == "python": cmd = [py] + cmd[1:] + proc = None try: proc = await asyncio.create_subprocess_shell( " ".join(map(str, cmd)), @@ -308,10 +311,14 @@ async def async_run_command( cwd=cwd, env=env, ) - return proc + yield proc except subprocess.CalledProcessError: questionary.print("Command failed", style=ERROR_STYLE) raise typer.Exit(1) + finally: + if proc: + proc.send_signal(signal.SIGINT) + await proc.wait() def md5(*strings: str) -> int: diff --git a/openllm_next/local.py b/openllm_next/local.py index 265006e9..713f03e4 100644 --- a/openllm_next/local.py +++ b/openllm_next/local.py @@ -1,4 +1,6 @@ import asyncio +import signal +import time import httpx import questionary @@ -29,23 +31,21 @@ def serve(bento: BentoInfo): async def _run_model(bento: BentoInfo, timeout: int = 600): venv = ensure_venv(bento) cmd, env, cwd = _get_serve_cmd(bento) - server_proc = await async_run_command( + async with async_run_command( cmd, env=env, cwd=cwd, venv=venv, silent=False, - ) - stdout_streamer = asyncio.create_task( - stream_command_output(server_proc.stdout, style="gray") - ) - stderr_streamer = asyncio.create_task( - stream_command_output(server_proc.stderr, style="#BD2D0F") - ) + ) as server_proc: + import bentoml - import bentoml + print("Model server started", server_proc.pid) + + stdout_streamer = None + stderr_streamer = None + start_time = time.time() - try: questionary.print("Model loading...", style="green") for _ in range(timeout): try: @@ -53,14 +53,25 @@ async def _run_model(bento: BentoInfo, timeout: int = 600): if resp.status_code == 200: break except httpx.RequestError: - await asyncio.sleep(0) + if time.time() - start_time > 30: + if not stdout_streamer: + stdout_streamer = asyncio.create_task( + stream_command_output(server_proc.stdout, style="gray") + ) + if not stderr_streamer: + stderr_streamer = asyncio.create_task( + stream_command_output(server_proc.stderr, style="#BD2D0F") + ) + await asyncio.sleep(1) else: questionary.print("Model failed to load", style="red") server_proc.terminate() return - stdout_streamer.cancel() - stderr_streamer.cancel() + if stdout_streamer: + stdout_streamer.cancel() + if stderr_streamer: + stderr_streamer.cancel() questionary.print("Model is ready", style="green") messages = [] @@ -76,17 +87,10 @@ async def _run_model(bento: BentoInfo, timeout: int = 600): print(text, end="") messages.append(dict(role="assistant", content=assistant_message)) print() - except KeyboardInterrupt: break - except (asyncio.CancelledError, httpx.RequestError): - pass - finally: questionary.print("\nStopping model server...", style="green") - if server_proc.returncode is None: - server_proc.terminate() - await server_proc.wait() - questionary.print("Stopped model server", style="green") + questionary.print("Stopped model server", style="green") def run(bento: BentoInfo): From bcecbbd91839ac39497e33567b5652848fd69c87 Mon Sep 17 00:00:00 2001 From: Zhao Shenyang Date: Tue, 11 Jun 2024 03:20:20 +0800 Subject: [PATCH 068/125] chore: bump vllm to 0.4.3 --- vllm-chat/bentovllm_openai/utils.py | 136 ++++++++++++---------------- vllm-chat/requirements.txt | 3 +- vllm-chat/service.py | 2 +- 3 files changed, 61 insertions(+), 80 deletions(-) diff --git a/vllm-chat/bentovllm_openai/utils.py b/vllm-chat/bentovllm_openai/utils.py index 38ab85bd..b7fbfb72 100644 --- a/vllm-chat/bentovllm_openai/utils.py +++ b/vllm-chat/bentovllm_openai/utils.py @@ -14,19 +14,37 @@ T = t.TypeVar("T", bound=object) if t.TYPE_CHECKING: from vllm import AsyncLLMEngine - def openai_endpoints( - served_model_names: list[str], - response_role: str = "assistant", - chat_template: t.Optional[str] = None, - chat_template_model_id: t.Optional[str] = None, + model_id: str, + response_role: str = "assistant", + served_model_names: t.Optional[list[str]] = None, + chat_template: t.Optional[str] = None, + chat_template_model_id: t.Optional[str] = None, + default_completion_parameters: t.Optional[t.Dict[str, t.Any]] = None, + default_chat_completion_parameters: t.Optional[t.Dict[str, t.Any]] = None, ): + if served_model_names is None: + served_model_names = [model_id] + def openai_wrapper(svc: Service[T]): cls = svc.inner app = FastAPI() + # make sure default_*_parameters are in valid format + if default_completion_parameters is not None: + assert "prompt" not in default_completion_parameters + assert CompletionRequest( + prompt="", model="", **default_completion_parameters + ) + + if default_chat_completion_parameters is not None: + assert "messages" not in default_chat_completion_parameters + assert ChatCompletionRequest( + messages=[], model="", **default_chat_completion_parameters + ) + class new_cls(cls): def __init__(self): @@ -38,65 +56,32 @@ def openai_endpoints( # That's also why we put these codes inside class's # `__init__` function import bentoml + from vllm.entrypoints.openai.serving_chat import OpenAIServingChat - from vllm.entrypoints.openai.serving_completion import ( - OpenAIServingCompletion, - ) + from vllm.entrypoints.openai.serving_completion import OpenAIServingCompletion - # https://github.com/vllm-project/vllm/issues/2683 - class PatchedOpenAIServingChat(OpenAIServingChat): - def __init__( - self, - engine: AsyncLLMEngine, - served_model_names: list[str], - response_role: str, - chat_template=None, - ): - super(OpenAIServingChat, self).__init__( - engine=engine, - served_model_names=served_model_names, - lora_modules=None, - ) - self.response_role = response_role - try: - event_loop = asyncio.get_running_loop() - except RuntimeError: - event_loop = None - - if event_loop is not None and event_loop.is_running(): - event_loop.create_task( - self._load_chat_template(chat_template) - ) - else: - asyncio.run(self._load_chat_template(chat_template)) - - async def _load_chat_template(self, chat_template): - # Simply making this function async is usually already enough to give the parent - # class time to load the tokenizer (so usually no sleeping happens here) - # However, it feels safer to be explicit about this since asyncio does not - # guarantee the order in which scheduled tasks are run - while self.tokenizer is None: - await asyncio.sleep(0.1) - return super()._load_chat_template(chat_template) + # we can do this because worker/engine_user_ray is always False for us + model_config = self.engine.engine.get_model_config() self.openai_serving_completion = OpenAIServingCompletion( engine=self.engine, served_model_names=served_model_names, + model_config=model_config, + lora_modules=None, ) self.chat_template = chat_template if self.chat_template is None and chat_template_model_id is not None: from transformers import AutoTokenizer - - # If no community chat template is provided, use the tokenizer's chat template _tokenizer = AutoTokenizer.from_pretrained(chat_template_model_id) self.chat_template = _tokenizer.chat_template - self.openai_serving_chat = PatchedOpenAIServingChat( + self.openai_serving_chat = OpenAIServingChat( engine=self.engine, served_model_names=served_model_names, response_role=response_role, chat_template=self.chat_template, + model_config=model_config, ) @app.get("/models") @@ -106,37 +91,38 @@ def openai_endpoints( @app.post("/chat/completions") async def create_chat_completion( - request: ChatCompletionRequest, raw_request: Request + request: ChatCompletionRequest, + raw_request: Request ): + if default_chat_completion_parameters is not None: + for k, v in default_chat_completion_parameters.items(): + if k not in request.__fields_set__: + setattr(request, k, v) generator = await self.openai_serving_chat.create_chat_completion( - request, raw_request - ) + request, raw_request) if isinstance(generator, ErrorResponse): - return JSONResponse( - content=generator.model_dump(), status_code=generator.code - ) + return JSONResponse(content=generator.model_dump(), + status_code=generator.code) if request.stream: - return StreamingResponse( - content=generator, media_type="text/event-stream" - ) + return StreamingResponse(content=generator, + media_type="text/event-stream") else: return JSONResponse(content=generator.model_dump()) @app.post("/completions") - async def create_completion( - request: CompletionRequest, raw_request: Request - ): + async def create_completion(request: CompletionRequest, raw_request: Request): + if default_completion_parameters is not None: + for k, v in default_completion_parameters.items(): + if k not in request.__fields_set__: + setattr(request, k, v) generator = await self.openai_serving_completion.create_completion( - request, raw_request - ) + request, raw_request) if isinstance(generator, ErrorResponse): - return JSONResponse( - content=generator.model_dump(), status_code=generator.code - ) + return JSONResponse(content=generator.model_dump(), + status_code=generator.code) if request.stream: - return StreamingResponse( - content=generator, media_type="text/event-stream" - ) + return StreamingResponse(content=generator, + media_type="text/event-stream") else: return JSONResponse(content=generator.model_dump()) @@ -151,9 +137,8 @@ def openai_endpoints( # helper function to make a httpx client for BentoML service def _make_httpx_client(url, svc): - from urllib.parse import urlparse - import httpx + from urllib.parse import urlparse from bentoml._internal.utils.uri import uri_to_path timeout = svc.config["traffic"]["timeout"] @@ -169,12 +154,9 @@ def _make_httpx_client(url, svc): elif parsed.scheme == "tcp": target_url = f"http://{parsed.netloc}" - return ( - httpx.Client( - transport=transport, - timeout=timeout, - follow_redirects=True, - headers=headers, - ), - target_url, - ) + return httpx.Client( + transport=transport, + timeout=timeout, + follow_redirects=True, + headers=headers, + ), target_url diff --git a/vllm-chat/requirements.txt b/vllm-chat/requirements.txt index 63880cab..1210f56e 100644 --- a/vllm-chat/requirements.txt +++ b/vllm-chat/requirements.txt @@ -1,4 +1,3 @@ -torch==2.3.0 -vllm==0.4.2 +vllm==0.4.3 transformers==4.41.0 pyyaml diff --git a/vllm-chat/service.py b/vllm-chat/service.py index ed0dccb5..701d231f 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -41,7 +41,7 @@ def _get_gen_config(community_chat_template: str) -> dict: @openai_endpoints( - served_model_names=[ENGINE_CONFIG["model"]], + model_id=ENGINE_CONFIG["model"], chat_template=_get_gen_config(CHAT_TEMPLATE)["template"] if CHAT_TEMPLATE else None, chat_template_model_id=ENGINE_CONFIG["model"], ) From 52c625ec2ffb4f628dda532db117e9c240d01037 Mon Sep 17 00:00:00 2001 From: bojiang <5886138+bojiang@users.noreply.github.com> Date: Wed, 12 Jun 2024 20:03:58 +0800 Subject: [PATCH 069/125] Revert "chore: bump vllm to 0.4.3" (#3) --- vllm-chat/bentovllm_openai/utils.py | 138 ++++++++++++++++------------ vllm-chat/requirements.txt | 3 +- vllm-chat/service.py | 2 +- 3 files changed, 81 insertions(+), 62 deletions(-) diff --git a/vllm-chat/bentovllm_openai/utils.py b/vllm-chat/bentovllm_openai/utils.py index b7fbfb72..38ab85bd 100644 --- a/vllm-chat/bentovllm_openai/utils.py +++ b/vllm-chat/bentovllm_openai/utils.py @@ -14,37 +14,19 @@ T = t.TypeVar("T", bound=object) if t.TYPE_CHECKING: from vllm import AsyncLLMEngine -def openai_endpoints( - model_id: str, - response_role: str = "assistant", - served_model_names: t.Optional[list[str]] = None, - chat_template: t.Optional[str] = None, - chat_template_model_id: t.Optional[str] = None, - default_completion_parameters: t.Optional[t.Dict[str, t.Any]] = None, - default_chat_completion_parameters: t.Optional[t.Dict[str, t.Any]] = None, -): - if served_model_names is None: - served_model_names = [model_id] +def openai_endpoints( + served_model_names: list[str], + response_role: str = "assistant", + chat_template: t.Optional[str] = None, + chat_template_model_id: t.Optional[str] = None, +): def openai_wrapper(svc: Service[T]): cls = svc.inner app = FastAPI() - # make sure default_*_parameters are in valid format - if default_completion_parameters is not None: - assert "prompt" not in default_completion_parameters - assert CompletionRequest( - prompt="", model="", **default_completion_parameters - ) - - if default_chat_completion_parameters is not None: - assert "messages" not in default_chat_completion_parameters - assert ChatCompletionRequest( - messages=[], model="", **default_chat_completion_parameters - ) - class new_cls(cls): def __init__(self): @@ -56,32 +38,65 @@ def openai_endpoints( # That's also why we put these codes inside class's # `__init__` function import bentoml - from vllm.entrypoints.openai.serving_chat import OpenAIServingChat - from vllm.entrypoints.openai.serving_completion import OpenAIServingCompletion + from vllm.entrypoints.openai.serving_completion import ( + OpenAIServingCompletion, + ) - # we can do this because worker/engine_user_ray is always False for us - model_config = self.engine.engine.get_model_config() + # https://github.com/vllm-project/vllm/issues/2683 + class PatchedOpenAIServingChat(OpenAIServingChat): + def __init__( + self, + engine: AsyncLLMEngine, + served_model_names: list[str], + response_role: str, + chat_template=None, + ): + super(OpenAIServingChat, self).__init__( + engine=engine, + served_model_names=served_model_names, + lora_modules=None, + ) + self.response_role = response_role + try: + event_loop = asyncio.get_running_loop() + except RuntimeError: + event_loop = None + + if event_loop is not None and event_loop.is_running(): + event_loop.create_task( + self._load_chat_template(chat_template) + ) + else: + asyncio.run(self._load_chat_template(chat_template)) + + async def _load_chat_template(self, chat_template): + # Simply making this function async is usually already enough to give the parent + # class time to load the tokenizer (so usually no sleeping happens here) + # However, it feels safer to be explicit about this since asyncio does not + # guarantee the order in which scheduled tasks are run + while self.tokenizer is None: + await asyncio.sleep(0.1) + return super()._load_chat_template(chat_template) self.openai_serving_completion = OpenAIServingCompletion( engine=self.engine, served_model_names=served_model_names, - model_config=model_config, - lora_modules=None, ) self.chat_template = chat_template if self.chat_template is None and chat_template_model_id is not None: from transformers import AutoTokenizer + + # If no community chat template is provided, use the tokenizer's chat template _tokenizer = AutoTokenizer.from_pretrained(chat_template_model_id) self.chat_template = _tokenizer.chat_template - self.openai_serving_chat = OpenAIServingChat( + self.openai_serving_chat = PatchedOpenAIServingChat( engine=self.engine, served_model_names=served_model_names, response_role=response_role, chat_template=self.chat_template, - model_config=model_config, ) @app.get("/models") @@ -91,38 +106,37 @@ def openai_endpoints( @app.post("/chat/completions") async def create_chat_completion( - request: ChatCompletionRequest, - raw_request: Request + request: ChatCompletionRequest, raw_request: Request ): - if default_chat_completion_parameters is not None: - for k, v in default_chat_completion_parameters.items(): - if k not in request.__fields_set__: - setattr(request, k, v) generator = await self.openai_serving_chat.create_chat_completion( - request, raw_request) + request, raw_request + ) if isinstance(generator, ErrorResponse): - return JSONResponse(content=generator.model_dump(), - status_code=generator.code) + return JSONResponse( + content=generator.model_dump(), status_code=generator.code + ) if request.stream: - return StreamingResponse(content=generator, - media_type="text/event-stream") + return StreamingResponse( + content=generator, media_type="text/event-stream" + ) else: return JSONResponse(content=generator.model_dump()) @app.post("/completions") - async def create_completion(request: CompletionRequest, raw_request: Request): - if default_completion_parameters is not None: - for k, v in default_completion_parameters.items(): - if k not in request.__fields_set__: - setattr(request, k, v) + async def create_completion( + request: CompletionRequest, raw_request: Request + ): generator = await self.openai_serving_completion.create_completion( - request, raw_request) + request, raw_request + ) if isinstance(generator, ErrorResponse): - return JSONResponse(content=generator.model_dump(), - status_code=generator.code) + return JSONResponse( + content=generator.model_dump(), status_code=generator.code + ) if request.stream: - return StreamingResponse(content=generator, - media_type="text/event-stream") + return StreamingResponse( + content=generator, media_type="text/event-stream" + ) else: return JSONResponse(content=generator.model_dump()) @@ -137,8 +151,9 @@ def openai_endpoints( # helper function to make a httpx client for BentoML service def _make_httpx_client(url, svc): - import httpx from urllib.parse import urlparse + + import httpx from bentoml._internal.utils.uri import uri_to_path timeout = svc.config["traffic"]["timeout"] @@ -154,9 +169,12 @@ def _make_httpx_client(url, svc): elif parsed.scheme == "tcp": target_url = f"http://{parsed.netloc}" - return httpx.Client( - transport=transport, - timeout=timeout, - follow_redirects=True, - headers=headers, - ), target_url + return ( + httpx.Client( + transport=transport, + timeout=timeout, + follow_redirects=True, + headers=headers, + ), + target_url, + ) diff --git a/vllm-chat/requirements.txt b/vllm-chat/requirements.txt index 1210f56e..63880cab 100644 --- a/vllm-chat/requirements.txt +++ b/vllm-chat/requirements.txt @@ -1,3 +1,4 @@ -vllm==0.4.3 +torch==2.3.0 +vllm==0.4.2 transformers==4.41.0 pyyaml diff --git a/vllm-chat/service.py b/vllm-chat/service.py index 701d231f..ed0dccb5 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -41,7 +41,7 @@ def _get_gen_config(community_chat_template: str) -> dict: @openai_endpoints( - model_id=ENGINE_CONFIG["model"], + served_model_names=[ENGINE_CONFIG["model"]], chat_template=_get_gen_config(CHAT_TEMPLATE)["template"] if CHAT_TEMPLATE else None, chat_template_model_id=ENGINE_CONFIG["model"], ) From b8d536d4795b418b27c2a134ff1e1212d77bff8c Mon Sep 17 00:00:00 2001 From: bojiang Date: Fri, 7 Jun 2024 13:55:57 +0800 Subject: [PATCH 070/125] add more qwen versions --- recipe.yaml | 73 +++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 73 insertions(+) diff --git a/recipe.yaml b/recipe.yaml index b0ec497d..2050d3b8 100644 --- a/recipe.yaml +++ b/recipe.yaml @@ -213,6 +213,20 @@ max_model_len: 2048 quantization: awq chat_template: gemma-it +"qwen2:0.5b-instruct-fp16": + alias: + - 0.5b + project: vllm-chat + service_config: + name: qwen2 + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-rtx-3060 + engine_config: + model: Qwen/Qwen2-0.5B-Instruct + max_model_len: 2048 "qwen2:1.5b-instruct-fp16": alias: - 1.5b @@ -227,6 +241,22 @@ engine_config: model: Qwen/Qwen2-1.5B-Instruct max_model_len: 2048 +"qwen2:7b-instruct-awq-4bit": + alias: + - 7b-4bit + project: vllm-chat + service_config: + name: qwen2 + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-rtx-3060 + engine_config: + model: Qwen/Qwen2-7B-Instruct-AWQ + max_model_len: 2048 + quantization: awq + chat_template: gemma-it "qwen2:7b-instruct-fp16": alias: - 7b @@ -241,3 +271,46 @@ engine_config: model: Qwen/Qwen2-7B-Instruct max_model_len: 2048 +"qwen2:72b-instruct-awq-4bit": + alias: + - 70b-4bit + project: vllm-chat + service_config: + name: qwen2 + traffic: + timeout: 300 + resources: + gpu: 1 + gpu_type: nvidia-a100-80g + engine_config: + model: Qwen/Qwen2-72B-Instruct-AWQ + max_model_len: 2048 + quantization: awq +"qwen2:57b-a14b-instruct-fp16": + alias: + - 57b-a14b + project: vllm-chat + service_config: + name: qwen2 + traffic: + timeout: 300 + resources: + gpu: 2 + gpu_type: nvidia-a100-80g + engine_config: + model: Qwen/Qwen2-57B-A14B-Instruct + max_model_len: 2048 +"qwen2:72b-instruct-fp16": + alias: + - 72b + project: vllm-chat + service_config: + name: qwen2 + traffic: + timeout: 300 + resources: + gpu: 2 + gpu_type: nvidia-a100-80g + engine_config: + model: Qwen/Qwen2-72B-Instruct + max_model_len: 2048 From c7f9fad285e62df31b18c9a9d2f81206de192b8c Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 11 Jun 2024 02:52:30 +0800 Subject: [PATCH 071/125] fix openai api --- recipe.yaml | 1 - vllm-chat/bentovllm_openai/protocol.py | 8 -------- vllm-chat/bentovllm_openai/utils.py | 26 +++++++++++++++++++------- 3 files changed, 19 insertions(+), 16 deletions(-) diff --git a/recipe.yaml b/recipe.yaml index 2050d3b8..2a2cd00d 100644 --- a/recipe.yaml +++ b/recipe.yaml @@ -256,7 +256,6 @@ model: Qwen/Qwen2-7B-Instruct-AWQ max_model_len: 2048 quantization: awq - chat_template: gemma-it "qwen2:7b-instruct-fp16": alias: - 7b diff --git a/vllm-chat/bentovllm_openai/protocol.py b/vllm-chat/bentovllm_openai/protocol.py index 9b7a5680..d66fa8a9 100644 --- a/vllm-chat/bentovllm_openai/protocol.py +++ b/vllm-chat/bentovllm_openai/protocol.py @@ -58,14 +58,6 @@ class OpenAIBaseModel(BaseModel): model_config = ConfigDict(extra="forbid") -class ErrorResponse(OpenAIBaseModel): - object: str = "error" - message: str - type: str - param: Optional[str] = None - code: int - - class ModelPermission(OpenAIBaseModel): id: str = Field(default_factory=lambda: f"modelperm-{random_uuid()}") object: str = "model_permission" diff --git a/vllm-chat/bentovllm_openai/utils.py b/vllm-chat/bentovllm_openai/utils.py index 38ab85bd..dd06237a 100644 --- a/vllm-chat/bentovllm_openai/utils.py +++ b/vllm-chat/bentovllm_openai/utils.py @@ -4,15 +4,18 @@ import asyncio import typing as t from _bentoml_sdk.service.factory import Service +from bentoml._internal.types import LazyType from fastapi import FastAPI, Request from fastapi.responses import JSONResponse, StreamingResponse -from .protocol import ChatCompletionRequest, CompletionRequest, ErrorResponse +from .protocol import CompletionRequest T = t.TypeVar("T", bound=object) if t.TYPE_CHECKING: from vllm import AsyncLLMEngine + from vllm.entrypoints.openai.protocol import ChatCompletionRequest, ErrorResponse + def openai_endpoints( @@ -28,6 +31,7 @@ def openai_endpoints( app = FastAPI() class new_cls(cls): + engine: AsyncLLMEngine def __init__(self): @@ -37,7 +41,6 @@ def openai_endpoints( # `prometheus_client` won't cause import troubles # That's also why we put these codes inside class's # `__init__` function - import bentoml from vllm.entrypoints.openai.serving_chat import OpenAIServingChat from vllm.entrypoints.openai.serving_completion import ( OpenAIServingCompletion, @@ -77,7 +80,7 @@ def openai_endpoints( # guarantee the order in which scheduled tasks are run while self.tokenizer is None: await asyncio.sleep(0.1) - return super()._load_chat_template(chat_template) + return await super()._load_chat_template(chat_template) self.openai_serving_completion = OpenAIServingCompletion( engine=self.engine, @@ -106,26 +109,35 @@ def openai_endpoints( @app.post("/chat/completions") async def create_chat_completion( - request: ChatCompletionRequest, raw_request: Request + request: 'ChatCompletionRequest', raw_request: Request ): + models = await self.openai_serving_chat.show_available_models() + model_ids = [model['id'] for model in models.model_dump()['data']] + if not request.model or request.model not in model_ids and len(model_ids) == 1: + request.model = model_ids[0] generator = await self.openai_serving_chat.create_chat_completion( request, raw_request ) - if isinstance(generator, ErrorResponse): + if LazyType['ErrorResponse']("vllm.entrypoints.openai.protocol.ErrorResponse").isinstance(generator): return JSONResponse( - content=generator.model_dump(), status_code=generator.code + content=generator.model_dump_json(), status_code=generator.code ) if request.stream: return StreamingResponse( content=generator, media_type="text/event-stream" ) else: - return JSONResponse(content=generator.model_dump()) + return JSONResponse(content=generator.model_dump_json()) @app.post("/completions") async def create_completion( request: CompletionRequest, raw_request: Request ): + from vllm.entrypoints.openai.protocol import ErrorResponse + if not request.model: + models = await self.openai_serving_chat.show_available_models() + if len(models.model_dump()) == 1: + request.model = models.model_dump()['data'][0]['id'] generator = await self.openai_serving_completion.create_completion( request, raw_request ) From 12166897434f258808f46bd94113baddf531e264 Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 11 Jun 2024 05:21:12 +0800 Subject: [PATCH 072/125] refactor(openai): simpler integration --- vllm-chat/bentovllm_openai/__init__.py | 0 vllm-chat/bentovllm_openai/protocol.py | 569 ------------------------- vllm-chat/bentovllm_openai/utils.py | 192 --------- vllm-chat/service.py | 59 ++- 4 files changed, 50 insertions(+), 770 deletions(-) delete mode 100644 vllm-chat/bentovllm_openai/__init__.py delete mode 100644 vllm-chat/bentovllm_openai/protocol.py delete mode 100644 vllm-chat/bentovllm_openai/utils.py diff --git a/vllm-chat/bentovllm_openai/__init__.py b/vllm-chat/bentovllm_openai/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/vllm-chat/bentovllm_openai/protocol.py b/vllm-chat/bentovllm_openai/protocol.py deleted file mode 100644 index d66fa8a9..00000000 --- a/vllm-chat/bentovllm_openai/protocol.py +++ /dev/null @@ -1,569 +0,0 @@ -from __future__ import annotations - -# Adapted from -# https://github.com/lm-sys/FastChat/blob/168ccc29d3f7edc50823016105c024fe2282732a/fastchat/protocol/openai_api_protocol.py -import time -import uuid -from typing import Any, Dict, List, Literal, Optional, Union, TYPE_CHECKING - -import openai.types.chat -import torch -from pydantic import BaseModel, ConfigDict, Field, model_validator -from typing_extensions import Annotated, Required, TypedDict - -if TYPE_CHECKING: - from vllm.pooling_params import PoolingParams - from vllm.sampling_params import SamplingParams - - -def random_uuid() -> str: - return str(uuid.uuid4().hex) - - -class CustomChatCompletionContentPartParam(TypedDict, total=False): - __pydantic_config__ = ConfigDict(extra="allow") # type: ignore - - type: Required[str] - """The type of the content part.""" - - -ChatCompletionContentPartParam = Union[ - openai.types.chat.ChatCompletionContentPartParam, - CustomChatCompletionContentPartParam] - - -class CustomChatCompletionMessageParam(TypedDict, total=False): - """Enables custom roles in the Chat Completion API.""" - role: Required[str] - """The role of the message's author.""" - - content: Union[str, List[ChatCompletionContentPartParam]] - """The contents of the message.""" - - name: str - """An optional name for the participant. - - Provides the model information to differentiate between participants of the - same role. - """ - - -ChatCompletionMessageParam = Union[ - openai.types.chat.ChatCompletionMessageParam, - CustomChatCompletionMessageParam] - - -class OpenAIBaseModel(BaseModel): - # OpenAI API does not allow extra fields - model_config = ConfigDict(extra="forbid") - - -class ModelPermission(OpenAIBaseModel): - id: str = Field(default_factory=lambda: f"modelperm-{random_uuid()}") - object: str = "model_permission" - created: int = Field(default_factory=lambda: int(time.time())) - allow_create_engine: bool = False - allow_sampling: bool = True - allow_logprobs: bool = True - allow_search_indices: bool = False - allow_view: bool = True - allow_fine_tuning: bool = False - organization: str = "*" - group: Optional[str] = None - is_blocking: bool = False - - -class ModelCard(OpenAIBaseModel): - id: str - object: str = "model" - created: int = Field(default_factory=lambda: int(time.time())) - owned_by: str = "vllm" - root: Optional[str] = None - parent: Optional[str] = None - permission: List[ModelPermission] = Field(default_factory=list) - - -class ModelList(OpenAIBaseModel): - object: str = "list" - data: List[ModelCard] = Field(default_factory=list) - - -class UsageInfo(OpenAIBaseModel): - prompt_tokens: int = 0 - total_tokens: int = 0 - completion_tokens: Optional[int] = 0 - - -class ResponseFormat(OpenAIBaseModel): - # type must be "json_object" or "text" - type: Literal["text", "json_object"] - - -class ChatCompletionRequest(OpenAIBaseModel): - # Ordered by official OpenAI API documentation - # https://platform.openai.com/docs/api-reference/chat/create - messages: List[ChatCompletionMessageParam] - model: str - frequency_penalty: Optional[float] = 0.0 - logit_bias: Optional[Dict[str, float]] = None - logprobs: Optional[bool] = False - top_logprobs: Optional[int] = None - max_tokens: Optional[int] = None - n: Optional[int] = 1 - presence_penalty: Optional[float] = 0.0 - response_format: Optional[ResponseFormat] = None - seed: Optional[int] = Field(None, - ge=torch.iinfo(torch.long).min, - le=torch.iinfo(torch.long).max) - stop: Optional[Union[str, List[str]]] = Field(default_factory=list) - stream: Optional[bool] = False - temperature: Optional[float] = 0.7 - top_p: Optional[float] = 1.0 - user: Optional[str] = None - - # doc: begin-chat-completion-sampling-params - best_of: Optional[int] = None - use_beam_search: Optional[bool] = False - top_k: Optional[int] = -1 - min_p: Optional[float] = 0.0 - repetition_penalty: Optional[float] = 1.0 - length_penalty: Optional[float] = 1.0 - early_stopping: Optional[bool] = False - ignore_eos: Optional[bool] = False - min_tokens: Optional[int] = 0 - stop_token_ids: Optional[List[int]] = Field(default_factory=list) - skip_special_tokens: Optional[bool] = True - spaces_between_special_tokens: Optional[bool] = True - # doc: end-chat-completion-sampling-params - - # doc: begin-chat-completion-extra-params - echo: Optional[bool] = Field( - default=False, - description=( - "If true, the new message will be prepended with the last message " - "if they belong to the same role."), - ) - add_generation_prompt: Optional[bool] = Field( - default=True, - description= - ("If true, the generation prompt will be added to the chat template. " - "This is a parameter used by chat template in tokenizer config of the " - "model."), - ) - include_stop_str_in_output: Optional[bool] = Field( - default=False, - description=( - "Whether to include the stop string in the output. " - "This is only applied when the stop or stop_token_ids is set."), - ) - guided_json: Optional[Union[str, dict, BaseModel]] = Field( - default=None, - description=("If specified, the output will follow the JSON schema."), - ) - guided_regex: Optional[str] = Field( - default=None, - description=( - "If specified, the output will follow the regex pattern."), - ) - guided_choice: Optional[List[str]] = Field( - default=None, - description=( - "If specified, the output will be exactly one of the choices."), - ) - guided_grammar: Optional[str] = Field( - default=None, - description=( - "If specified, the output will follow the context free grammar."), - ) - guided_decoding_backend: Optional[str] = Field( - default=None, - description=( - "If specified, will override the default guided decoding backend " - "of the server for this specific request. If set, must be either " - "'outlines' / 'lm-format-enforcer'")) - guided_whitespace_pattern: Optional[str] = Field( - default=None, - description=( - "If specified, will override the default whitespace pattern " - "for guided json decoding.")) - - # doc: end-chat-completion-extra-params - - def to_sampling_params(self) -> SamplingParams: - if self.logprobs and not self.top_logprobs: - raise ValueError("Top logprobs must be set when logprobs is.") - - logits_processors = None - if self.logit_bias: - - def logit_bias_logits_processor( - token_ids: List[int], - logits: torch.Tensor) -> torch.Tensor: - assert self.logit_bias is not None - for token_id, bias in self.logit_bias.items(): - # Clamp the bias between -100 and 100 per OpenAI API spec - bias = min(100, max(-100, bias)) - logits[int(token_id)] += bias - return logits - - logits_processors = [logit_bias_logits_processor] - - from vllm.sampling_params import SamplingParams - return SamplingParams( - n=self.n, - presence_penalty=self.presence_penalty, - frequency_penalty=self.frequency_penalty, - repetition_penalty=self.repetition_penalty, - temperature=self.temperature, - top_p=self.top_p, - min_p=self.min_p, - seed=self.seed, - stop=self.stop, - stop_token_ids=self.stop_token_ids, - max_tokens=self.max_tokens, - min_tokens=self.min_tokens, - logprobs=self.top_logprobs if self.logprobs else None, - prompt_logprobs=self.top_logprobs if self.echo else None, - best_of=self.best_of, - top_k=self.top_k, - ignore_eos=self.ignore_eos, - use_beam_search=self.use_beam_search, - early_stopping=self.early_stopping, - skip_special_tokens=self.skip_special_tokens, - spaces_between_special_tokens=self.spaces_between_special_tokens, - include_stop_str_in_output=self.include_stop_str_in_output, - length_penalty=self.length_penalty, - logits_processors=logits_processors, - ) - - @model_validator(mode="before") - @classmethod - def check_guided_decoding_count(cls, data): - guide_count = sum([ - "guided_json" in data and data["guided_json"] is not None, - "guided_regex" in data and data["guided_regex"] is not None, - "guided_choice" in data and data["guided_choice"] is not None - ]) - if guide_count > 1: - raise ValueError( - "You can only use one kind of guided decoding " - "('guided_json', 'guided_regex' or 'guided_choice').") - return data - - -class CompletionRequest(OpenAIBaseModel): - # Ordered by official OpenAI API documentation - # https://platform.openai.com/docs/api-reference/completions/create - model: str - prompt: Union[List[int], List[List[int]], str, List[str]] - best_of: Optional[int] = None - echo: Optional[bool] = False - frequency_penalty: Optional[float] = 0.0 - logit_bias: Optional[Dict[str, float]] = None - logprobs: Optional[int] = None - max_tokens: Optional[int] = 16 - n: int = 1 - presence_penalty: Optional[float] = 0.0 - seed: Optional[int] = Field(None, - ge=torch.iinfo(torch.long).min, - le=torch.iinfo(torch.long).max) - stop: Optional[Union[str, List[str]]] = Field(default_factory=list) - stream: Optional[bool] = False - suffix: Optional[str] = None - temperature: Optional[float] = 1.0 - top_p: Optional[float] = 1.0 - user: Optional[str] = None - - # doc: begin-completion-sampling-params - use_beam_search: Optional[bool] = False - top_k: Optional[int] = -1 - min_p: Optional[float] = 0.0 - repetition_penalty: Optional[float] = 1.0 - length_penalty: Optional[float] = 1.0 - early_stopping: Optional[bool] = False - stop_token_ids: Optional[List[int]] = Field(default_factory=list) - ignore_eos: Optional[bool] = False - min_tokens: Optional[int] = 0 - skip_special_tokens: Optional[bool] = True - spaces_between_special_tokens: Optional[bool] = True - truncate_prompt_tokens: Optional[Annotated[int, Field(ge=1)]] = None - # doc: end-completion-sampling-params - - # doc: begin-completion-extra-params - include_stop_str_in_output: Optional[bool] = Field( - default=False, - description=( - "Whether to include the stop string in the output. " - "This is only applied when the stop or stop_token_ids is set."), - ) - response_format: Optional[ResponseFormat] = Field( - default=None, - description= - ("Similar to chat completion, this parameter specifies the format of " - "output. Only {'type': 'json_object'} or {'type': 'text' } is " - "supported."), - ) - guided_json: Optional[Union[str, dict, BaseModel]] = Field( - default=None, - description=("If specified, the output will follow the JSON schema."), - ) - guided_regex: Optional[str] = Field( - default=None, - description=( - "If specified, the output will follow the regex pattern."), - ) - guided_choice: Optional[List[str]] = Field( - default=None, - description=( - "If specified, the output will be exactly one of the choices."), - ) - guided_grammar: Optional[str] = Field( - default=None, - description=( - "If specified, the output will follow the context free grammar."), - ) - guided_decoding_backend: Optional[str] = Field( - default=None, - description=( - "If specified, will override the default guided decoding backend " - "of the server for this specific request. If set, must be one of " - "'outlines' / 'lm-format-enforcer'")) - guided_whitespace_pattern: Optional[str] = Field( - default=None, - description=( - "If specified, will override the default whitespace pattern " - "for guided json decoding.")) - - # doc: end-completion-extra-params - - def to_sampling_params(self): - echo_without_generation = self.echo and self.max_tokens == 0 - - logits_processors = None - if self.logit_bias: - - def logit_bias_logits_processor( - token_ids: List[int], - logits: torch.Tensor) -> torch.Tensor: - assert self.logit_bias is not None - for token_id, bias in self.logit_bias.items(): - # Clamp the bias between -100 and 100 per OpenAI API spec - bias = min(100, max(-100, bias)) - logits[int(token_id)] += bias - return logits - - logits_processors = [logit_bias_logits_processor] - - from vllm.sampling_params import SamplingParams - return SamplingParams( - n=self.n, - best_of=self.best_of, - presence_penalty=self.presence_penalty, - frequency_penalty=self.frequency_penalty, - repetition_penalty=self.repetition_penalty, - temperature=self.temperature, - top_p=self.top_p, - top_k=self.top_k, - min_p=self.min_p, - seed=self.seed, - stop=self.stop, - stop_token_ids=self.stop_token_ids, - ignore_eos=self.ignore_eos, - max_tokens=self.max_tokens if not echo_without_generation else 1, - min_tokens=self.min_tokens, - logprobs=self.logprobs, - use_beam_search=self.use_beam_search, - early_stopping=self.early_stopping, - prompt_logprobs=self.logprobs if self.echo else None, - skip_special_tokens=self.skip_special_tokens, - spaces_between_special_tokens=(self.spaces_between_special_tokens), - include_stop_str_in_output=self.include_stop_str_in_output, - length_penalty=self.length_penalty, - logits_processors=logits_processors, - truncate_prompt_tokens=self.truncate_prompt_tokens, - ) - - @model_validator(mode="before") - @classmethod - def check_guided_decoding_count(cls, data): - guide_count = sum([ - "guided_json" in data and data["guided_json"] is not None, - "guided_regex" in data and data["guided_regex"] is not None, - "guided_choice" in data and data["guided_choice"] is not None - ]) - if guide_count > 1: - raise ValueError( - "You can only use one kind of guided decoding " - "('guided_json', 'guided_regex' or 'guided_choice').") - return data - - -class EmbeddingRequest(BaseModel): - # Ordered by official OpenAI API documentation - # https://platform.openai.com/docs/api-reference/embeddings - model: str - input: Union[List[int], List[List[int]], str, List[str]] - encoding_format: Optional[str] = Field('float', pattern='^(float|base64)$') - dimensions: Optional[int] = None - user: Optional[str] = None - - # doc: begin-embedding-pooling-params - additional_data: Optional[Any] = None - - # doc: end-embedding-pooling-params - - def to_pooling_params(self): - return PoolingParams(additional_data=self.additional_data) - - -class LogProbs(OpenAIBaseModel): - text_offset: List[int] = Field(default_factory=list) - token_logprobs: List[Optional[float]] = Field(default_factory=list) - tokens: List[str] = Field(default_factory=list) - top_logprobs: Optional[List[Optional[Dict[str, float]]]] = None - - -class CompletionResponseChoice(OpenAIBaseModel): - index: int - text: str - logprobs: Optional[LogProbs] = None - finish_reason: Optional[str] = None - stop_reason: Optional[Union[int, str]] = Field( - default=None, - description=( - "The stop string or token id that caused the completion " - "to stop, None if the completion finished for some other reason " - "including encountering the EOS token"), - ) - - -class CompletionResponse(OpenAIBaseModel): - id: str = Field(default_factory=lambda: f"cmpl-{random_uuid()}") - object: str = "text_completion" - created: int = Field(default_factory=lambda: int(time.time())) - model: str - choices: List[CompletionResponseChoice] - usage: UsageInfo - - -class CompletionResponseStreamChoice(OpenAIBaseModel): - index: int - text: str - logprobs: Optional[LogProbs] = None - finish_reason: Optional[str] = None - stop_reason: Optional[Union[int, str]] = Field( - default=None, - description=( - "The stop string or token id that caused the completion " - "to stop, None if the completion finished for some other reason " - "including encountering the EOS token"), - ) - - -class CompletionStreamResponse(OpenAIBaseModel): - id: str = Field(default_factory=lambda: f"cmpl-{random_uuid()}") - object: str = "text_completion" - created: int = Field(default_factory=lambda: int(time.time())) - model: str - choices: List[CompletionResponseStreamChoice] - usage: Optional[UsageInfo] = Field(default=None) - - -class EmbeddingResponseData(BaseModel): - index: int - object: str = "embedding" - embedding: List[float] - - -class EmbeddingResponse(BaseModel): - id: str = Field(default_factory=lambda: f"cmpl-{random_uuid()}") - object: str = "list" - created: int = Field(default_factory=lambda: int(time.time())) - model: str - data: List[EmbeddingResponseData] - usage: UsageInfo - - -class ChatMessage(OpenAIBaseModel): - role: str - content: str - - -class ChatCompletionResponseChoice(OpenAIBaseModel): - index: int - message: ChatMessage - logprobs: Optional[LogProbs] = None - finish_reason: Optional[str] = None - stop_reason: Optional[Union[int, str]] = None - - -class ChatCompletionResponse(OpenAIBaseModel): - id: str = Field(default_factory=lambda: f"chatcmpl-{random_uuid()}") - object: str = "chat.completion" - created: int = Field(default_factory=lambda: int(time.time())) - model: str - choices: List[ChatCompletionResponseChoice] - usage: UsageInfo - - -class DeltaMessage(OpenAIBaseModel): - role: Optional[str] = None - content: Optional[str] = None - - -class ChatCompletionResponseStreamChoice(OpenAIBaseModel): - index: int - delta: DeltaMessage - logprobs: Optional[LogProbs] = None - finish_reason: Optional[str] = None - stop_reason: Optional[Union[int, str]] = None - - -class ChatCompletionStreamResponse(OpenAIBaseModel): - id: str = Field(default_factory=lambda: f"chatcmpl-{random_uuid()}") - object: str = "chat.completion.chunk" - created: int = Field(default_factory=lambda: int(time.time())) - model: str - choices: List[ChatCompletionResponseStreamChoice] - usage: Optional[UsageInfo] = Field(default=None) - - -class BatchRequestInput(OpenAIBaseModel): - """ - The per-line object of the batch input file. - - NOTE: Currently only the `/v1/chat/completions` endpoint is supported. - """ - - # A developer-provided per-request id that will be used to match outputs to - # inputs. Must be unique for each request in a batch. - custom_id: str - - # The HTTP method to be used for the request. Currently only POST is - # supported. - method: str - - # The OpenAI API relative URL to be used for the request. Currently - # /v1/chat/completions is supported. - url: str - - # The parameteters of the request. - body: Union[ChatCompletionRequest, ] - - -class BatchRequestOutput(OpenAIBaseModel): - """ - The per-line object of the batch output and error files - """ - - id: str - - # A developer-provided per-request id that will be used to match outputs to - # inputs. - custom_id: str - - response: Optional[ChatCompletionResponse] - - # For requests that failed with a non-HTTP error, this will contain more - # information on the cause of the failure. - error: Optional[Any] diff --git a/vllm-chat/bentovllm_openai/utils.py b/vllm-chat/bentovllm_openai/utils.py deleted file mode 100644 index dd06237a..00000000 --- a/vllm-chat/bentovllm_openai/utils.py +++ /dev/null @@ -1,192 +0,0 @@ -from __future__ import annotations - -import asyncio -import typing as t - -from _bentoml_sdk.service.factory import Service -from bentoml._internal.types import LazyType -from fastapi import FastAPI, Request -from fastapi.responses import JSONResponse, StreamingResponse - -from .protocol import CompletionRequest - -T = t.TypeVar("T", bound=object) - -if t.TYPE_CHECKING: - from vllm import AsyncLLMEngine - from vllm.entrypoints.openai.protocol import ChatCompletionRequest, ErrorResponse - - - -def openai_endpoints( - served_model_names: list[str], - response_role: str = "assistant", - chat_template: t.Optional[str] = None, - chat_template_model_id: t.Optional[str] = None, -): - - def openai_wrapper(svc: Service[T]): - - cls = svc.inner - app = FastAPI() - - class new_cls(cls): - engine: AsyncLLMEngine - - def __init__(self): - - super().__init__() - - # we need to import bentoml before vllm so - # `prometheus_client` won't cause import troubles - # That's also why we put these codes inside class's - # `__init__` function - from vllm.entrypoints.openai.serving_chat import OpenAIServingChat - from vllm.entrypoints.openai.serving_completion import ( - OpenAIServingCompletion, - ) - - # https://github.com/vllm-project/vllm/issues/2683 - class PatchedOpenAIServingChat(OpenAIServingChat): - def __init__( - self, - engine: AsyncLLMEngine, - served_model_names: list[str], - response_role: str, - chat_template=None, - ): - super(OpenAIServingChat, self).__init__( - engine=engine, - served_model_names=served_model_names, - lora_modules=None, - ) - self.response_role = response_role - try: - event_loop = asyncio.get_running_loop() - except RuntimeError: - event_loop = None - - if event_loop is not None and event_loop.is_running(): - event_loop.create_task( - self._load_chat_template(chat_template) - ) - else: - asyncio.run(self._load_chat_template(chat_template)) - - async def _load_chat_template(self, chat_template): - # Simply making this function async is usually already enough to give the parent - # class time to load the tokenizer (so usually no sleeping happens here) - # However, it feels safer to be explicit about this since asyncio does not - # guarantee the order in which scheduled tasks are run - while self.tokenizer is None: - await asyncio.sleep(0.1) - return await super()._load_chat_template(chat_template) - - self.openai_serving_completion = OpenAIServingCompletion( - engine=self.engine, - served_model_names=served_model_names, - ) - - self.chat_template = chat_template - if self.chat_template is None and chat_template_model_id is not None: - from transformers import AutoTokenizer - - # If no community chat template is provided, use the tokenizer's chat template - _tokenizer = AutoTokenizer.from_pretrained(chat_template_model_id) - self.chat_template = _tokenizer.chat_template - - self.openai_serving_chat = PatchedOpenAIServingChat( - engine=self.engine, - served_model_names=served_model_names, - response_role=response_role, - chat_template=self.chat_template, - ) - - @app.get("/models") - async def show_available_models(): - models = await self.openai_serving_chat.show_available_models() - return JSONResponse(content=models.model_dump()) - - @app.post("/chat/completions") - async def create_chat_completion( - request: 'ChatCompletionRequest', raw_request: Request - ): - models = await self.openai_serving_chat.show_available_models() - model_ids = [model['id'] for model in models.model_dump()['data']] - if not request.model or request.model not in model_ids and len(model_ids) == 1: - request.model = model_ids[0] - generator = await self.openai_serving_chat.create_chat_completion( - request, raw_request - ) - if LazyType['ErrorResponse']("vllm.entrypoints.openai.protocol.ErrorResponse").isinstance(generator): - return JSONResponse( - content=generator.model_dump_json(), status_code=generator.code - ) - if request.stream: - return StreamingResponse( - content=generator, media_type="text/event-stream" - ) - else: - return JSONResponse(content=generator.model_dump_json()) - - @app.post("/completions") - async def create_completion( - request: CompletionRequest, raw_request: Request - ): - from vllm.entrypoints.openai.protocol import ErrorResponse - if not request.model: - models = await self.openai_serving_chat.show_available_models() - if len(models.model_dump()) == 1: - request.model = models.model_dump()['data'][0]['id'] - generator = await self.openai_serving_completion.create_completion( - request, raw_request - ) - if isinstance(generator, ErrorResponse): - return JSONResponse( - content=generator.model_dump(), status_code=generator.code - ) - if request.stream: - return StreamingResponse( - content=generator, media_type="text/event-stream" - ) - else: - return JSONResponse(content=generator.model_dump()) - - new_cls.__name__ = "%s_OpenAI" % cls.__name__ - svc.inner = new_cls - svc.mount_asgi_app(app, path="/v1/") - return svc - - return openai_wrapper - - -# helper function to make a httpx client for BentoML service -def _make_httpx_client(url, svc): - - from urllib.parse import urlparse - - import httpx - from bentoml._internal.utils.uri import uri_to_path - - timeout = svc.config["traffic"]["timeout"] - headers = {"Runner-Name": svc.name} - parsed = urlparse(url) - transport = None - target_url = url - - if parsed.scheme == "file": - uds = uri_to_path(url) - transport = httpx.HTTPTransport(uds=uds) - target_url = "http://127.0.0.1:3000" - elif parsed.scheme == "tcp": - target_url = f"http://{parsed.netloc}" - - return ( - httpx.Client( - transport=transport, - timeout=timeout, - follow_redirects=True, - headers=headers, - ), - target_url, - ) diff --git a/vllm-chat/service.py b/vllm-chat/service.py index ed0dccb5..a9a6f188 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -2,21 +2,22 @@ import functools import json import logging import os +import sys import uuid from typing import AsyncGenerator, Union -import bentoml +import fastapi +import vllm.entrypoints.openai.api_server as vllm_api_server import yaml from annotated_types import Ge, Le from bento_constants import CONSTANT_YAML -from bentovllm_openai.utils import openai_endpoints from typing_extensions import Annotated CONSTANTS = yaml.safe_load(CONSTANT_YAML) ENGINE_CONFIG = CONSTANTS["engine_config"] SERVICE_CONFIG = CONSTANTS["service_config"] -CHAT_TEMPLATE = CONSTANTS.get("chat_template") +OVERRIDE_CHAT_TEMPLATE = CONSTANTS.get("chat_template") logger = logging.getLogger(__name__) logger.setLevel(logging.INFO) @@ -40,22 +41,62 @@ def _get_gen_config(community_chat_template: str) -> dict: return gen_config -@openai_endpoints( - served_model_names=[ENGINE_CONFIG["model"]], - chat_template=_get_gen_config(CHAT_TEMPLATE)["template"] if CHAT_TEMPLATE else None, - chat_template_model_id=ENGINE_CONFIG["model"], -) +openai_api_app = fastapi.FastAPI() + + +for route in vllm_api_server.app.routes: + if isinstance(route, fastapi.routing.APIRoute): + if route.path.startswith("/v1"): + openai_api_app.add_api_route( + path=route.path[3:], + endpoint=route.endpoint, + methods=list(route.methods) if route.methods else None, + name=route.name, + include_in_schema=route.include_in_schema, + ) + + +if "prometheus_client" in sys.modules: + sys.modules.pop("prometheus_client") + + +import bentoml + + +@bentoml.mount_asgi_app(openai_api_app, path="/v1") @bentoml.service(**SERVICE_CONFIG) class VLLM: def __init__(self) -> None: from transformers import AutoTokenizer from vllm import AsyncEngineArgs, AsyncLLMEngine + from vllm.entrypoints.openai.serving_chat import OpenAIServingChat + from vllm.entrypoints.openai.serving_completion import OpenAIServingCompletion ENGINE_ARGS = AsyncEngineArgs(**ENGINE_CONFIG) self.engine = AsyncLLMEngine.from_engine_args(ENGINE_ARGS) self.tokenizer = AutoTokenizer.from_pretrained(ENGINE_CONFIG["model"]) logger.info(f"VLLM service initialized with model: {ENGINE_CONFIG['model']}") + if OVERRIDE_CHAT_TEMPLATE: # use community chat template + gen_config = _get_gen_config(CONSTANTS["chat_template"]) + chat_template = gen_config["template"] + else: + chat_template = None + + # inject the engine into the openai serving chat and completion + vllm_api_server.openai_serving_chat = OpenAIServingChat( + engine=self.engine, + served_model_names=[ENGINE_CONFIG["model"]], + response_role="assistant", + chat_template=chat_template, + # args.lora_modules, + ) + vllm_api_server.openai_serving_completion = OpenAIServingCompletion( + engine=self.engine, + served_model_names=[ENGINE_CONFIG["model"]], + # args.lora_modules, + ) + @bentoml.api async def generate( self, @@ -101,7 +142,7 @@ class VLLM: """ from vllm import SamplingParams - if CHAT_TEMPLATE: # community chat template + if OVERRIDE_CHAT_TEMPLATE: # community chat template gen_config = _get_gen_config(CONSTANTS["chat_template"]) if not stop: if gen_config["stop_str"]: From b11140298c63b02a1381ff4bdfefd3e9c55b39d7 Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 11 Jun 2024 18:41:45 +0800 Subject: [PATCH 073/125] add openai apis --- vllm-chat/service.py | 29 ++++++++++++++++------------- 1 file changed, 16 insertions(+), 13 deletions(-) diff --git a/vllm-chat/service.py b/vllm-chat/service.py index a9a6f188..9676ad06 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -6,6 +6,7 @@ import sys import uuid from typing import AsyncGenerator, Union +import bentoml import fastapi import vllm.entrypoints.openai.api_server as vllm_api_server import yaml @@ -44,25 +45,27 @@ def _get_gen_config(community_chat_template: str) -> dict: openai_api_app = fastapi.FastAPI() -for route in vllm_api_server.app.routes: - if isinstance(route, fastapi.routing.APIRoute): - if route.path.startswith("/v1"): - openai_api_app.add_api_route( - path=route.path[3:], - endpoint=route.endpoint, - methods=list(route.methods) if route.methods else None, - name=route.name, - include_in_schema=route.include_in_schema, - ) +OPENAI_ENDPOINTS = [ + ["/v1/chat/completions", vllm_api_server.create_chat_completion, ["POST"]], + ["/v1/completions", vllm_api_server.create_completion, ["POST"]], + ["/v1/models", vllm_api_server.show_available_models, ["GET"]], +] +for route, endpoint, methods in OPENAI_ENDPOINTS: + openai_api_app.add_api_route( + path=route[3:], + endpoint=endpoint, + methods=methods, + include_in_schema=True, + ) + + +# special handling for prometheus_client of bentoml if "prometheus_client" in sys.modules: sys.modules.pop("prometheus_client") -import bentoml - - @bentoml.mount_asgi_app(openai_api_app, path="/v1") @bentoml.service(**SERVICE_CONFIG) class VLLM: From ebed5331e3d5b4e99ae2246385c94a982b134bc1 Mon Sep 17 00:00:00 2001 From: bojiang Date: Tue, 11 Jun 2024 19:30:11 +0800 Subject: [PATCH 074/125] not work --- vllm-chat/service.py | 20 +++++++++-- .../7BT5lwjSKT2H9mkp4WtzL/_buildManifest.js | 1 + .../7BT5lwjSKT2H9mkp4WtzL/_ssgManifest.js | 1 + .../chunks/0e5ce63c-f5957df8d97fa48f.js | 1 + .../chunks/370b0802-87e84e603248538e.js | 1 + .../chunks/3d47b92a-f8bda4b39f1e2d9d.js | 1 + .../chunks/479ba886-0c92f49cb8e74e58.js | 1 + .../static/chunks/553-eb44b2c179677206.js | 13 ++++++++ .../chunks/59650de3-87b10f0662b51900.js | 1 + .../chunks/66ec4792-34336521b476aa45.js | 1 + .../static/chunks/674-461cd92d861f607d.js | 1 + .../static/chunks/69-49041ec9af0205fa.js | 1 + .../static/chunks/700-532b1fe2415e5859.js | 5 +++ .../static/chunks/899-fa939dd99dc7a1df.js | 5 +++ .../chunks/8e1d74a4-a6b9a2554f9153c0.js | 1 + .../chunks/94730671-0f73873f7f5896de.js | 1 + .../app/(site)/page-e098dfc653ddc682.js | 1 + .../chunks/app/chat/page-4ceddc02645cea6a.js | 1 + .../chunks/app/layout-7be00a9f3b4b3b3d.js | 1 + .../chunks/app/not-found-2d03ed3798d6bcd7.js | 1 + .../chunks/d3ac728e-0c798b3b8aa3bf53.js | 1 + .../chunks/fd9d1056-32c33f3919735051.js | 1 + .../chunks/framework-00a8ba1a63cfdc9e.js | 33 +++++++++++++++++++ .../static/chunks/main-2362c5f5fa889423.js | 1 + .../chunks/main-app-b33bb27039dae64b.js | 1 + .../chunks/pages/_app-d21e88acd55d90f1.js | 1 + .../chunks/pages/_error-d6107f1aac0c574c.js | 1 + .../chunks/polyfills-c67a75d1b6f99dc8.js | 1 + .../static/chunks/webpack-d274d3a6100c3631.js | 1 + .../ui/_next/static/css/429544bd3cd8ce3a.css | 1 + .../ui/_next/static/css/5b67f082b31cfc7b.css | 1 + .../ui/_next/static/css/9e63023b20ddb15e.css | 3 ++ vllm-chat/ui/chat.html | 5 +++ 33 files changed, 107 insertions(+), 3 deletions(-) create mode 100644 vllm-chat/ui/_next/static/7BT5lwjSKT2H9mkp4WtzL/_buildManifest.js create mode 100644 vllm-chat/ui/_next/static/7BT5lwjSKT2H9mkp4WtzL/_ssgManifest.js create mode 100644 vllm-chat/ui/_next/static/chunks/0e5ce63c-f5957df8d97fa48f.js create mode 100644 vllm-chat/ui/_next/static/chunks/370b0802-87e84e603248538e.js create mode 100644 vllm-chat/ui/_next/static/chunks/3d47b92a-f8bda4b39f1e2d9d.js create mode 100644 vllm-chat/ui/_next/static/chunks/479ba886-0c92f49cb8e74e58.js create mode 100644 vllm-chat/ui/_next/static/chunks/553-eb44b2c179677206.js create mode 100644 vllm-chat/ui/_next/static/chunks/59650de3-87b10f0662b51900.js create mode 100644 vllm-chat/ui/_next/static/chunks/66ec4792-34336521b476aa45.js create mode 100644 vllm-chat/ui/_next/static/chunks/674-461cd92d861f607d.js create mode 100644 vllm-chat/ui/_next/static/chunks/69-49041ec9af0205fa.js create mode 100644 vllm-chat/ui/_next/static/chunks/700-532b1fe2415e5859.js create mode 100644 vllm-chat/ui/_next/static/chunks/899-fa939dd99dc7a1df.js create mode 100644 vllm-chat/ui/_next/static/chunks/8e1d74a4-a6b9a2554f9153c0.js create mode 100644 vllm-chat/ui/_next/static/chunks/94730671-0f73873f7f5896de.js create mode 100644 vllm-chat/ui/_next/static/chunks/app/(site)/page-e098dfc653ddc682.js create mode 100644 vllm-chat/ui/_next/static/chunks/app/chat/page-4ceddc02645cea6a.js create mode 100644 vllm-chat/ui/_next/static/chunks/app/layout-7be00a9f3b4b3b3d.js create mode 100644 vllm-chat/ui/_next/static/chunks/app/not-found-2d03ed3798d6bcd7.js create mode 100644 vllm-chat/ui/_next/static/chunks/d3ac728e-0c798b3b8aa3bf53.js create mode 100644 vllm-chat/ui/_next/static/chunks/fd9d1056-32c33f3919735051.js create mode 100644 vllm-chat/ui/_next/static/chunks/framework-00a8ba1a63cfdc9e.js create mode 100644 vllm-chat/ui/_next/static/chunks/main-2362c5f5fa889423.js create mode 100644 vllm-chat/ui/_next/static/chunks/main-app-b33bb27039dae64b.js create mode 100644 vllm-chat/ui/_next/static/chunks/pages/_app-d21e88acd55d90f1.js create mode 100644 vllm-chat/ui/_next/static/chunks/pages/_error-d6107f1aac0c574c.js create mode 100644 vllm-chat/ui/_next/static/chunks/polyfills-c67a75d1b6f99dc8.js create mode 100644 vllm-chat/ui/_next/static/chunks/webpack-d274d3a6100c3631.js create mode 100644 vllm-chat/ui/_next/static/css/429544bd3cd8ce3a.css create mode 100644 vllm-chat/ui/_next/static/css/5b67f082b31cfc7b.css create mode 100644 vllm-chat/ui/_next/static/css/9e63023b20ddb15e.css create mode 100644 vllm-chat/ui/chat.html diff --git a/vllm-chat/service.py b/vllm-chat/service.py index 9676ad06..3c6c91fc 100644 --- a/vllm-chat/service.py +++ b/vllm-chat/service.py @@ -8,12 +8,14 @@ from typing import AsyncGenerator, Union import bentoml import fastapi +import fastapi.staticfiles import vllm.entrypoints.openai.api_server as vllm_api_server import yaml from annotated_types import Ge, Le -from bento_constants import CONSTANT_YAML from typing_extensions import Annotated +from bento_constants import CONSTANT_YAML + CONSTANTS = yaml.safe_load(CONSTANT_YAML) ENGINE_CONFIG = CONSTANTS["engine_config"] @@ -54,19 +56,31 @@ OPENAI_ENDPOINTS = [ for route, endpoint, methods in OPENAI_ENDPOINTS: openai_api_app.add_api_route( - path=route[3:], + path=route, endpoint=endpoint, methods=methods, include_in_schema=True, ) +STATIC_DIR = os.path.join(os.path.dirname(__file__), "ui", "_next") +CHAT_HTML = os.path.join(os.path.dirname(__file__), "ui", "chat.html") + +openai_api_app.mount("/_next", fastapi.staticfiles.StaticFiles(directory=STATIC_DIR)) + + +@openai_api_app.get("/chat") +async def chat_ui(): + with open(CHAT_HTML) as f: + return fastapi.responses.HTMLResponse(content=f.read()) + + # special handling for prometheus_client of bentoml if "prometheus_client" in sys.modules: sys.modules.pop("prometheus_client") -@bentoml.mount_asgi_app(openai_api_app, path="/v1") +@bentoml.mount_asgi_app(openai_api_app) @bentoml.service(**SERVICE_CONFIG) class VLLM: def __init__(self) -> None: diff --git a/vllm-chat/ui/_next/static/7BT5lwjSKT2H9mkp4WtzL/_buildManifest.js b/vllm-chat/ui/_next/static/7BT5lwjSKT2H9mkp4WtzL/_buildManifest.js new file mode 100644 index 00000000..f779caa0 --- /dev/null +++ b/vllm-chat/ui/_next/static/7BT5lwjSKT2H9mkp4WtzL/_buildManifest.js @@ -0,0 +1 @@ +self.__BUILD_MANIFEST={__rewrites:{afterFiles:[],beforeFiles:[],fallback:[]},"/_error":["static/chunks/pages/_error-d6107f1aac0c574c.js"],sortedPages:["/_app","/_error"]},self.__BUILD_MANIFEST_CB&&self.__BUILD_MANIFEST_CB(); \ No newline at end of file diff --git a/vllm-chat/ui/_next/static/7BT5lwjSKT2H9mkp4WtzL/_ssgManifest.js 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Uint16Array('ᵁ<\xd5ıʊҝջאٵ۞ޢߖࠏ੊ઑඡ๭༉༦჊ረዡᐕᒝᓃᓟᔥ\x00\x00\x00\x00\x00\x00ᕫᛍᦍᰒᷝ὾⁠↰⊍⏀⏻⑂⠤⤒ⴈ⹈⿎〖㊺㘹㞬㣾㨨㩱㫠㬮ࠀEMabcfglmnoprstu\\bfms\x7f\x84\x8b\x90\x95\x98\xa6\xb3\xb9\xc8\xcflig耻\xc6䃆P耻&䀦cute耻\xc1䃁reve;䄂Āiyx}rc耻\xc2䃂;䐐r;쀀\ud835\udd04rave耻\xc0䃀pha;䎑acr;䄀d;橓Āgp\x9d\xa1on;䄄f;쀀\ud835\udd38plyFunction;恡ing耻\xc5䃅Ācs\xbe\xc3r;쀀\ud835\udc9cign;扔ilde耻\xc3䃃ml耻\xc4䃄Ѐaceforsu\xe5\xfb\xfeėĜĢħĪĀcr\xea\xf2kslash;或Ŷ\xf6\xf8;櫧ed;挆y;䐑ƀcrtąċĔause;戵noullis;愬a;䎒r;쀀\ud835\udd05pf;쀀\ud835\udd39eve;䋘c\xf2ēmpeq;扎܀HOacdefhilorsuōőŖƀƞƢƵƷƺǜȕɳɸɾcy;䐧PY耻\xa9䂩ƀcpyŝŢźute;䄆Ā;iŧŨ拒talDifferentialD;慅leys;愭ȀaeioƉƎƔƘron;䄌dil耻\xc7䃇rc;䄈nint;戰ot;䄊ĀdnƧƭilla;䂸terDot;䂷\xf2ſi;䎧rcleȀDMPTLJNjǑǖot;抙inus;抖lus;投imes;抗oĀcsǢǸkwiseContourIntegral;戲eCurlyĀDQȃȏoubleQuote;思uote;怙ȀlnpuȞȨɇɕonĀ;eȥȦ户;橴ƀgitȯȶȺruent;扡nt;戯ourIntegral;戮ĀfrɌɎ;愂oduct;成nterClockwiseContourIntegral;戳oss;樯cr;쀀\ud835\udc9epĀ;Cʄʅ拓ap;才րDJSZacefiosʠʬʰʴʸˋ˗ˡ˦̳ҍĀ;oŹʥtrahd;椑cy;䐂cy;䐅cy;䐏ƀgrsʿ˄ˇger;怡r;憡hv;櫤Āayː˕ron;䄎;䐔lĀ;t˝˞戇a;䎔r;쀀\ud835\udd07Āaf˫̧Ācm˰̢riticalȀADGT̖̜̀̆cute;䂴oŴ̋̍;䋙bleAcute;䋝rave;䁠ilde;䋜ond;拄ferentialD;慆Ѱ̽\x00\x00\x00͔͂\x00Ѕf;쀀\ud835\udd3bƀ;DE͈͉͍䂨ot;惜qual;扐blèCDLRUVͣͲ΂ϏϢϸontourIntegra\xecȹoɴ͹\x00\x00ͻ\xbb͉nArrow;懓Āeo·ΤftƀARTΐΖΡrrow;懐ightArrow;懔e\xe5ˊngĀLRΫτeftĀARγιrrow;柸ightArrow;柺ightArrow;柹ightĀATϘϞrrow;懒ee;抨pɁϩ\x00\x00ϯrrow;懑ownArrow;懕erticalBar;戥ǹABLRTaВЪаўѿͼrrowƀ;BUНОТ憓ar;椓pArrow;懵reve;䌑eft˒к\x00ц\x00ѐightVector;楐eeVector;楞ectorĀ;Bљњ憽ar;楖ightǔѧ\x00ѱeeVector;楟ectorĀ;BѺѻ懁ar;楗eeĀ;A҆҇护rrow;憧ĀctҒҗr;쀀\ud835\udc9frok;䄐ࠀNTacdfglmopqstuxҽӀӄӋӞӢӧӮӵԡԯԶՒ՝ՠեG;䅊H耻\xd0䃐cute耻\xc9䃉ƀaiyӒӗӜron;䄚rc耻\xca䃊;䐭ot;䄖r;쀀\ud835\udd08rave耻\xc8䃈ement;戈ĀapӺӾcr;䄒tyɓԆ\x00\x00ԒmallSquare;旻erySmallSquare;斫ĀgpԦԪon;䄘f;쀀\ud835\udd3csilon;䎕uĀaiԼՉlĀ;TՂՃ橵ilde;扂librium;懌Āci՗՚r;愰m;橳a;䎗ml耻\xcb䃋Āipժկsts;戃onentialE;慇ʀcfiosօֈ֍ֲ׌y;䐤r;쀀\ud835\udd09lledɓ֗\x00\x00֣mallSquare;旼erySmallSquare;斪Ͱֺ\x00ֿ\x00\x00ׄf;쀀\ud835\udd3dAll;戀riertrf;愱c\xf2׋؀JTabcdfgorstר׬ׯ׺؀ؒؖ؛؝أ٬ٲcy;䐃耻>䀾mmaĀ;d׷׸䎓;䏜reve;䄞ƀeiy؇،ؐdil;䄢rc;䄜;䐓ot;䄠r;쀀\ud835\udd0a;拙pf;쀀\ud835\udd3eeater̀EFGLSTصلَٖٛ٦qualĀ;Lؾؿ扥ess;招ullEqual;执reater;檢ess;扷lantEqual;橾ilde;扳cr;쀀\ud835\udca2;扫ЀAacfiosuڅڋږڛڞڪھۊRDcy;䐪Āctڐڔek;䋇;䁞irc;䄤r;愌lbertSpace;愋ǰگ\x00ڲf;愍izontalLine;攀Āctۃۅ\xf2کrok;䄦mpńېۘownHum\xf0įqual;扏܀EJOacdfgmnostuۺ۾܃܇܎ܚܞܡܨ݄ݸދޏޕcy;䐕lig;䄲cy;䐁cute耻\xcd䃍Āiyܓܘrc耻\xce䃎;䐘ot;䄰r;愑rave耻\xcc䃌ƀ;apܠܯܿĀcgܴܷr;䄪inaryI;慈lie\xf3ϝǴ݉\x00ݢĀ;eݍݎ戬Āgrݓݘral;戫section;拂isibleĀCTݬݲomma;恣imes;恢ƀgptݿރވon;䄮f;쀀\ud835\udd40a;䎙cr;愐ilde;䄨ǫޚ\x00ޞcy;䐆l耻\xcf䃏ʀcfosuެ޷޼߂ߐĀiyޱ޵rc;䄴;䐙r;쀀\ud835\udd0dpf;쀀\ud835\udd41ǣ߇\x00ߌr;쀀\ud835\udca5rcy;䐈kcy;䐄΀HJacfosߤߨ߽߬߱ࠂࠈcy;䐥cy;䐌ppa;䎚Āey߶߻dil;䄶;䐚r;쀀\ud835\udd0epf;쀀\ud835\udd42cr;쀀\ud835\udca6րJTaceflmostࠥࠩࠬࡐࡣ঳সে্਷ੇcy;䐉耻<䀼ʀcmnpr࠷࠼ࡁࡄࡍute;䄹bda;䎛g;柪lacetrf;愒r;憞ƀaeyࡗ࡜ࡡron;䄽dil;䄻;䐛Āfsࡨ॰tԀACDFRTUVarࡾࢩࢱࣦ࣠ࣼयज़ΐ४Ānrࢃ࢏gleBracket;柨rowƀ;BR࢙࢚࢞憐ar;懤ightArrow;懆eiling;挈oǵࢷ\x00ࣃbleBracket;柦nǔࣈ\x00࣒eeVector;楡ectorĀ;Bࣛࣜ懃ar;楙loor;挊ightĀAV࣯ࣵrrow;憔ector;楎Āerँगeƀ;AVउऊऐ抣rrow;憤ector;楚iangleƀ;BEतथऩ抲ar;槏qual;抴pƀDTVषूौownVector;楑eeVector;楠ectorĀ;Bॖॗ憿ar;楘ectorĀ;B॥०憼ar;楒ight\xe1Μs̀EFGLSTॾঋকঝঢভqualGreater;拚ullEqual;扦reater;扶ess;檡lantEqual;橽ilde;扲r;쀀\ud835\udd0fĀ;eঽা拘ftarrow;懚idot;䄿ƀnpw৔ਖਛgȀLRlr৞৷ਂਐeftĀAR০৬rrow;柵ightArrow;柷ightArrow;柶eftĀarγਊight\xe1οight\xe1ϊf;쀀\ud835\udd43erĀLRਢਬeftArrow;憙ightArrow;憘ƀchtਾੀੂ\xf2ࡌ;憰rok;䅁;扪Ѐacefiosuਗ਼੝੠੷੼અઋ઎p;椅y;䐜Ādl੥੯iumSpace;恟lintrf;愳r;쀀\ud835\udd10nusPlus;戓pf;쀀\ud835\udd44c\xf2੶;䎜ҀJacefostuણધભીଔଙඑ඗ඞcy;䐊cute;䅃ƀaey઴હાron;䅇dil;䅅;䐝ƀgswે૰଎ativeƀMTV૓૟૨ediumSpace;怋hiĀcn૦૘\xeb૙eryThi\xee૙tedĀGL૸ଆreaterGreate\xf2ٳessLes\xf3ੈLine;䀊r;쀀\ud835\udd11ȀBnptଢନଷ଺reak;恠BreakingSpace;䂠f;愕ڀ;CDEGHLNPRSTV୕ୖ୪୼஡௫ఄ౞಄ದ೘ൡඅ櫬Āou୛୤ngruent;扢pCap;扭oubleVerticalBar;戦ƀlqxஃஊ஛ement;戉ualĀ;Tஒஓ扠ilde;쀀≂̸ists;戄reater΀;EFGLSTஶஷ஽௉௓௘௥扯qual;扱ullEqual;쀀≧̸reater;쀀≫̸ess;批lantEqual;쀀⩾̸ilde;扵umpń௲௽ownHump;쀀≎̸qual;쀀≏̸eĀfsఊధtTriangleƀ;BEచఛడ拪ar;쀀⧏̸qual;括s̀;EGLSTవశ఼ౄోౘ扮qual;扰reater;扸ess;쀀≪̸lantEqual;쀀⩽̸ilde;扴estedĀGL౨౹reaterGreater;쀀⪢̸essLess;쀀⪡̸recedesƀ;ESಒಓಛ技qual;쀀⪯̸lantEqual;拠ĀeiಫಹverseElement;戌ghtTriangleƀ;BEೋೌ೒拫ar;쀀⧐̸qual;拭ĀquೝഌuareSuĀbp೨೹setĀ;E೰ೳ쀀⊏̸qual;拢ersetĀ;Eഃആ쀀⊐̸qual;拣ƀbcpഓതൎsetĀ;Eഛഞ쀀⊂⃒qual;抈ceedsȀ;ESTലള഻െ抁qual;쀀⪰̸lantEqual;拡ilde;쀀≿̸ersetĀ;E൘൛쀀⊃⃒qual;抉ildeȀ;EFT൮൯൵ൿ扁qual;扄ullEqual;扇ilde;扉erticalBar;戤cr;쀀\ud835\udca9ilde耻\xd1䃑;䎝܀Eacdfgmoprstuvලෂ෉෕ෛ෠෧෼ขภยา฿ไlig;䅒cute耻\xd3䃓Āiy෎ීrc耻\xd4䃔;䐞blac;䅐r;쀀\ud835\udd12rave耻\xd2䃒ƀaei෮ෲ෶cr;䅌ga;䎩cron;䎟pf;쀀\ud835\udd46enCurlyĀDQฎบoubleQuote;怜uote;怘;橔Āclวฬr;쀀\ud835\udcaaash耻\xd8䃘iŬื฼de耻\xd5䃕es;樷ml耻\xd6䃖erĀBP๋๠Āar๐๓r;怾acĀek๚๜;揞et;掴arenthesis;揜Ҁacfhilors๿ງຊຏຒດຝະ໼rtialD;戂y;䐟r;쀀\ud835\udd13i;䎦;䎠usMinus;䂱Āipຢອncareplan\xe5ڝf;愙Ȁ;eio຺ູ໠໤檻cedesȀ;EST່້໏໚扺qual;檯lantEqual;扼ilde;找me;怳Ādp໩໮uct;戏ortionĀ;aȥ໹l;戝Āci༁༆r;쀀\ud835\udcab;䎨ȀUfos༑༖༛༟OT耻"䀢r;쀀\ud835\udd14pf;愚cr;쀀\ud835\udcac؀BEacefhiorsu༾གྷཇའཱིྦྷྪྭ႖ႩႴႾarr;椐G耻\xae䂮ƀcnrཎནབute;䅔g;柫rĀ;tཛྷཝ憠l;椖ƀaeyཧཬཱron;䅘dil;䅖;䐠Ā;vླྀཹ愜erseĀEUྂྙĀlq྇ྎement;戋uilibrium;懋pEquilibrium;楯r\xbbཹo;䎡ghtЀACDFTUVa࿁࿫࿳ဢဨၛႇϘĀnr࿆࿒gleBracket;柩rowƀ;BL࿜࿝࿡憒ar;懥eftArrow;懄eiling;按oǵ࿹\x00စbleBracket;柧nǔည\x00နeeVector;楝ectorĀ;Bဝသ懂ar;楕loor;挋Āerိ၃eƀ;AVဵံြ抢rrow;憦ector;楛iangleƀ;BEၐၑၕ抳ar;槐qual;抵pƀDTVၣၮၸownVector;楏eeVector;楜ectorĀ;Bႂႃ憾ar;楔ectorĀ;B႑႒懀ar;楓Āpuႛ႞f;愝ndImplies;楰ightarrow;懛ĀchႹႼr;愛;憱leDelayed;槴ڀHOacfhimoqstuფჱჷჽᄙᄞᅑᅖᅡᅧᆵᆻᆿĀCcჩხHcy;䐩y;䐨FTcy;䐬cute;䅚ʀ;aeiyᄈᄉᄎᄓᄗ檼ron;䅠dil;䅞rc;䅜;䐡r;쀀\ud835\udd16ortȀDLRUᄪᄴᄾᅉownArrow\xbbОeftArrow\xbb࢚ightArrow\xbb࿝pArrow;憑gma;䎣allCircle;战pf;쀀\ud835\udd4aɲᅭ\x00\x00ᅰt;戚areȀ;ISUᅻᅼᆉᆯ斡ntersection;抓uĀbpᆏᆞsetĀ;Eᆗᆘ抏qual;抑ersetĀ;Eᆨᆩ抐qual;抒nion;抔cr;쀀\ud835\udcaear;拆ȀbcmpᇈᇛሉላĀ;sᇍᇎ拐etĀ;Eᇍᇕqual;抆ĀchᇠህeedsȀ;ESTᇭᇮᇴᇿ扻qual;檰lantEqual;扽ilde;承Th\xe1ྌ;我ƀ;esሒሓሣ拑rsetĀ;Eሜም抃qual;抇et\xbbሓրHRSacfhiorsሾቄ቉ቕ቞ቱቶኟዂወዑORN耻\xde䃞ADE;愢ĀHc቎ቒcy;䐋y;䐦Ābuቚቜ;䀉;䎤ƀaeyብቪቯron;䅤dil;䅢;䐢r;쀀\ud835\udd17Āeiቻ኉Dzኀ\x00ኇefore;戴a;䎘Ācn኎ኘkSpace;쀀  Space;怉ldeȀ;EFTካኬኲኼ戼qual;扃ullEqual;扅ilde;扈pf;쀀\ud835\udd4bipleDot;惛Āctዖዛr;쀀\ud835\udcafrok;䅦ૡዷጎጚጦ\x00ጬጱ\x00\x00\x00\x00\x00ጸጽ፷ᎅ\x00᏿ᐄᐊᐐĀcrዻጁute耻\xda䃚rĀ;oጇገ憟cir;楉rǣጓ\x00጖y;䐎ve;䅬Āiyጞጣrc耻\xdb䃛;䐣blac;䅰r;쀀\ud835\udd18rave耻\xd9䃙acr;䅪Ādiፁ፩erĀBPፈ፝Āarፍፐr;䁟acĀekፗፙ;揟et;掵arenthesis;揝onĀ;P፰፱拃lus;抎Āgp፻፿on;䅲f;쀀\ud835\udd4cЀADETadps᎕ᎮᎸᏄϨᏒᏗᏳrrowƀ;BDᅐᎠᎤar;椒ownArrow;懅ownArrow;憕quilibrium;楮eeĀ;AᏋᏌ报rrow;憥own\xe1ϳerĀLRᏞᏨeftArrow;憖ightArrow;憗iĀ;lᏹᏺ䏒on;䎥ing;䅮cr;쀀\ud835\udcb0ilde;䅨ml耻\xdc䃜ҀDbcdefosvᐧᐬᐰᐳᐾᒅᒊᒐᒖash;披ar;櫫y;䐒ashĀ;lᐻᐼ抩;櫦Āerᑃᑅ;拁ƀbtyᑌᑐᑺar;怖Ā;iᑏᑕcalȀBLSTᑡᑥᑪᑴar;戣ine;䁼eparator;杘ilde;所ThinSpace;怊r;쀀\ud835\udd19pf;쀀\ud835\udd4dcr;쀀\ud835\udcb1dash;抪ʀcefosᒧᒬᒱᒶᒼirc;䅴dge;拀r;쀀\ud835\udd1apf;쀀\ud835\udd4ecr;쀀\ud835\udcb2Ȁfiosᓋᓐᓒᓘr;쀀\ud835\udd1b;䎞pf;쀀\ud835\udd4fcr;쀀\ud835\udcb3ҀAIUacfosuᓱᓵᓹᓽᔄᔏᔔᔚᔠcy;䐯cy;䐇cy;䐮cute耻\xdd䃝Āiyᔉᔍrc;䅶;䐫r;쀀\ud835\udd1cpf;쀀\ud835\udd50cr;쀀\ud835\udcb4ml;䅸ЀHacdefosᔵᔹᔿᕋᕏᕝᕠᕤcy;䐖cute;䅹Āayᕄᕉron;䅽;䐗ot;䅻Dzᕔ\x00ᕛoWidt\xe8૙a;䎖r;愨pf;愤cr;쀀\ud835\udcb5௡ᖃᖊᖐ\x00ᖰᖶᖿ\x00\x00\x00\x00ᗆᗛᗫᙟ᙭\x00ᚕ᚛ᚲᚹ\x00ᚾcute耻\xe1䃡reve;䄃̀;Ediuyᖜᖝᖡᖣᖨᖭ戾;쀀∾̳;房rc耻\xe2䃢te肻\xb4̆;䐰lig耻\xe6䃦Ā;r\xb2ᖺ;쀀\ud835\udd1erave耻\xe0䃠ĀepᗊᗖĀfpᗏᗔsym;愵\xe8ᗓha;䎱ĀapᗟcĀclᗤᗧr;䄁g;樿ɤᗰ\x00\x00ᘊʀ;adsvᗺᗻᗿᘁᘇ戧nd;橕;橜lope;橘;橚΀;elmrszᘘᘙᘛᘞᘿᙏᙙ戠;榤e\xbbᘙsdĀ;aᘥᘦ戡ѡᘰᘲᘴᘶᘸᘺᘼᘾ;榨;榩;榪;榫;榬;榭;榮;榯tĀ;vᙅᙆ戟bĀ;dᙌᙍ抾;榝Āptᙔᙗh;戢\xbb\xb9arr;捼Āgpᙣᙧon;䄅f;쀀\ud835\udd52΀;Eaeiop዁ᙻᙽᚂᚄᚇᚊ;橰cir;橯;扊d;手s;䀧roxĀ;e዁ᚒ\xf1ᚃing耻\xe5䃥ƀctyᚡᚦᚨr;쀀\ud835\udcb6;䀪mpĀ;e዁ᚯ\xf1ʈilde耻\xe3䃣ml耻\xe4䃤Āciᛂᛈonin\xf4ɲnt;樑ࠀNabcdefiklnoprsu᛭ᛱᜰ᜼ᝃᝈ᝸᝽០៦ᠹᡐᜍ᤽᥈ᥰot;櫭Ācrᛶ᜞kȀcepsᜀᜅᜍᜓong;扌psilon;䏶rime;怵imĀ;e᜚᜛戽q;拍Ŷᜢᜦee;抽edĀ;gᜬᜭ挅e\xbbᜭrkĀ;t፜᜷brk;掶Āoyᜁᝁ;䐱quo;怞ʀcmprtᝓ᝛ᝡᝤᝨausĀ;eĊĉptyv;榰s\xe9ᜌno\xf5ēƀahwᝯ᝱ᝳ;䎲;愶een;扬r;쀀\ud835\udd1fg΀costuvwឍឝឳេ៕៛៞ƀaiuបពរ\xf0ݠrc;旯p\xbb፱ƀdptឤឨឭot;樀lus;樁imes;樂ɱឹ\x00\x00ើcup;樆ar;昅riangleĀdu៍្own;施p;斳plus;樄e\xe5ᑄ\xe5ᒭarow;植ƀako៭ᠦᠵĀcn៲ᠣkƀlst៺֫᠂ozenge;槫riangleȀ;dlr᠒᠓᠘᠝斴own;斾eft;旂ight;斸k;搣Ʊᠫ\x00ᠳƲᠯ\x00ᠱ;斒;斑4;斓ck;斈ĀeoᠾᡍĀ;qᡃᡆ쀀=⃥uiv;쀀≡⃥t;挐Ȁptwxᡙᡞᡧᡬf;쀀\ud835\udd53Ā;tᏋᡣom\xbbᏌtie;拈؀DHUVbdhmptuvᢅᢖᢪᢻᣗᣛᣬ᣿ᤅᤊᤐᤡȀLRlrᢎᢐᢒᢔ;敗;敔;敖;敓ʀ;DUduᢡᢢᢤᢦᢨ敐;敦;敩;敤;敧ȀLRlrᢳᢵᢷᢹ;敝;敚;敜;教΀;HLRhlrᣊᣋᣍᣏᣑᣓᣕ救;敬;散;敠;敫;敢;敟ox;槉ȀLRlrᣤᣦᣨᣪ;敕;敒;攐;攌ʀ;DUduڽ᣷᣹᣻᣽;敥;敨;攬;攴inus;抟lus;択imes;抠ȀLRlrᤙᤛᤝ᤟;敛;敘;攘;攔΀;HLRhlrᤰᤱᤳᤵᤷ᤻᤹攂;敪;敡;敞;攼;攤;攜Āevģ᥂bar耻\xa6䂦Ȁceioᥑᥖᥚᥠr;쀀\ud835\udcb7mi;恏mĀ;e᜚᜜lƀ;bhᥨᥩᥫ䁜;槅sub;柈Ŭᥴ᥾lĀ;e᥹᥺怢t\xbb᥺pƀ;Eeįᦅᦇ;檮Ā;qۜۛೡᦧ\x00᧨ᨑᨕᨲ\x00ᨷᩐ\x00\x00᪴\x00\x00᫁\x00\x00ᬡᬮ᭍᭒\x00᯽\x00ᰌƀcpr᦭ᦲ᧝ute;䄇̀;abcdsᦿᧀᧄ᧊᧕᧙戩nd;橄rcup;橉Āau᧏᧒p;橋p;橇ot;橀;쀀∩︀Āeo᧢᧥t;恁\xeeړȀaeiu᧰᧻ᨁᨅǰ᧵\x00᧸s;橍on;䄍dil耻\xe7䃧rc;䄉psĀ;sᨌᨍ橌m;橐ot;䄋ƀdmnᨛᨠᨦil肻\xb8ƭptyv;榲t脀\xa2;eᨭᨮ䂢r\xe4Ʋr;쀀\ud835\udd20ƀceiᨽᩀᩍy;䑇ckĀ;mᩇᩈ朓ark\xbbᩈ;䏇r΀;Ecefms᩟᩠ᩢᩫ᪤᪪᪮旋;槃ƀ;elᩩᩪᩭ䋆q;扗eɡᩴ\x00\x00᪈rrowĀlr᩼᪁eft;憺ight;憻ʀRSacd᪒᪔᪖᪚᪟\xbbཇ;擈st;抛irc;抚ash;抝nint;樐id;櫯cir;槂ubsĀ;u᪻᪼晣it\xbb᪼ˬ᫇᫔᫺\x00ᬊonĀ;eᫍᫎ䀺Ā;q\xc7\xc6ɭ᫙\x00\x00᫢aĀ;t᫞᫟䀬;䁀ƀ;fl᫨᫩᫫戁\xeeᅠeĀmx᫱᫶ent\xbb᫩e\xf3ɍǧ᫾\x00ᬇĀ;dኻᬂot;橭n\xf4Ɇƀfryᬐᬔᬗ;쀀\ud835\udd54o\xe4ɔ脀\xa9;sŕᬝr;愗Āaoᬥᬩrr;憵ss;朗Ācuᬲᬷr;쀀\ud835\udcb8Ābpᬼ᭄Ā;eᭁᭂ櫏;櫑Ā;eᭉᭊ櫐;櫒dot;拯΀delprvw᭠᭬᭷ᮂᮬᯔ᯹arrĀlr᭨᭪;椸;椵ɰ᭲\x00\x00᭵r;拞c;拟arrĀ;p᭿ᮀ憶;椽̀;bcdosᮏᮐᮖᮡᮥᮨ截rcap;橈Āauᮛᮞp;橆p;橊ot;抍r;橅;쀀∪︀Ȁalrv᮵ᮿᯞᯣrrĀ;mᮼᮽ憷;椼yƀevwᯇᯔᯘqɰᯎ\x00\x00ᯒre\xe3᭳u\xe3᭵ee;拎edge;拏en耻\xa4䂤earrowĀlrᯮ᯳eft\xbbᮀight\xbbᮽe\xe4ᯝĀciᰁᰇonin\xf4Ƿnt;戱lcty;挭ঀAHabcdefhijlorstuwz᰸᰻᰿ᱝᱩᱵᲊᲞᲬᲷ᳻᳿ᴍᵻᶑᶫᶻ᷆᷍r\xf2΁ar;楥Ȁglrs᱈ᱍ᱒᱔ger;怠eth;愸\xf2ᄳhĀ;vᱚᱛ怐\xbbऊūᱡᱧarow;椏a\xe3̕Āayᱮᱳron;䄏;䐴ƀ;ao̲ᱼᲄĀgrʿᲁr;懊tseq;橷ƀglmᲑᲔᲘ耻\xb0䂰ta;䎴ptyv;榱ĀirᲣᲨsht;楿;쀀\ud835\udd21arĀlrᲳᲵ\xbbࣜ\xbbသʀaegsv᳂͸᳖᳜᳠mƀ;oș᳊᳔ndĀ;ș᳑uit;晦amma;䏝in;拲ƀ;io᳧᳨᳸䃷de脀\xf7;o᳧ᳰntimes;拇n\xf8᳷cy;䑒cɯᴆ\x00\x00ᴊrn;挞op;挍ʀlptuwᴘᴝᴢᵉᵕlar;䀤f;쀀\ud835\udd55ʀ;emps̋ᴭᴷᴽᵂqĀ;d͒ᴳot;扑inus;戸lus;戔quare;抡blebarwedg\xe5\xfanƀadhᄮᵝᵧownarrow\xf3ᲃarpoonĀlrᵲᵶef\xf4Ჴigh\xf4ᲶŢᵿᶅkaro\xf7གɯᶊ\x00\x00ᶎrn;挟op;挌ƀcotᶘᶣᶦĀryᶝᶡ;쀀\ud835\udcb9;䑕l;槶rok;䄑Ādrᶰᶴot;拱iĀ;fᶺ᠖斿Āah᷀᷃r\xf2Щa\xf2ྦangle;榦Āci᷒ᷕy;䑟grarr;柿ऀDacdefglmnopqrstuxḁḉḙḸոḼṉṡṾấắẽỡἪἷὄ὎὚ĀDoḆᴴo\xf4ᲉĀcsḎḔute耻\xe9䃩ter;橮ȀaioyḢḧḱḶron;䄛rĀ;cḭḮ扖耻\xea䃪lon;払;䑍ot;䄗ĀDrṁṅot;扒;쀀\ud835\udd22ƀ;rsṐṑṗ檚ave耻\xe8䃨Ā;dṜṝ檖ot;檘Ȁ;ilsṪṫṲṴ檙nters;揧;愓Ā;dṹṺ檕ot;檗ƀapsẅẉẗcr;䄓tyƀ;svẒẓẕ戅et\xbbẓpĀ1;ẝẤijạả;怄;怅怃ĀgsẪẬ;䅋p;怂ĀgpẴẸon;䄙f;쀀\ud835\udd56ƀalsỄỎỒrĀ;sỊị拕l;槣us;橱iƀ;lvỚớở䎵on\xbbớ;䏵ȀcsuvỪỳἋἣĀioữḱrc\xbbḮɩỹ\x00\x00ỻ\xedՈantĀglἂἆtr\xbbṝess\xbbṺƀaeiἒ἖Ἒls;䀽st;扟vĀ;DȵἠD;橸parsl;槥ĀDaἯἳot;打rr;楱ƀcdiἾὁỸr;愯o\xf4͒ĀahὉὋ;䎷耻\xf0䃰Āmrὓὗl耻\xeb䃫o;悬ƀcipὡὤὧl;䀡s\xf4ծĀeoὬὴctatio\xeeՙnential\xe5չৡᾒ\x00ᾞ\x00ᾡᾧ\x00\x00ῆῌ\x00ΐ\x00ῦῪ \x00 ⁚llingdotse\xf1Ṅy;䑄male;晀ƀilrᾭᾳ῁lig;耀ffiɩᾹ\x00\x00᾽g;耀ffig;耀ffl;쀀\ud835\udd23lig;耀filig;쀀fjƀaltῙ῜ῡt;晭ig;耀flns;斱of;䆒ǰ΅\x00ῳf;쀀\ud835\udd57ĀakֿῷĀ;vῼ´拔;櫙artint;樍Āao‌⁕Ācs‑⁒ႉ‸⁅⁈\x00⁐β•‥‧‪‬\x00‮耻\xbd䂽;慓耻\xbc䂼;慕;慙;慛Ƴ‴\x00‶;慔;慖ʴ‾⁁\x00\x00⁃耻\xbe䂾;慗;慜5;慘ƶ⁌\x00⁎;慚;慝8;慞l;恄wn;挢cr;쀀\ud835\udcbbࢀEabcdefgijlnorstv₂₉₟₥₰₴⃰⃵⃺⃿℃ℒℸ̗ℾ⅒↞Ā;lٍ₇;檌ƀcmpₐₕ₝ute;䇵maĀ;dₜ᳚䎳;檆reve;䄟Āiy₪₮rc;䄝;䐳ot;䄡Ȁ;lqsؾق₽⃉ƀ;qsؾٌ⃄lan\xf4٥Ȁ;cdl٥⃒⃥⃕c;檩otĀ;o⃜⃝檀Ā;l⃢⃣檂;檄Ā;e⃪⃭쀀⋛︀s;檔r;쀀\ud835\udd24Ā;gٳ؛mel;愷cy;䑓Ȁ;Eajٚℌℎℐ;檒;檥;檤ȀEaesℛℝ℩ℴ;扩pĀ;p℣ℤ檊rox\xbbℤĀ;q℮ℯ檈Ā;q℮ℛim;拧pf;쀀\ud835\udd58Āci⅃ⅆr;愊mƀ;el٫ⅎ⅐;檎;檐茀>;cdlqr׮ⅠⅪⅮⅳⅹĀciⅥⅧ;檧r;橺ot;拗Par;榕uest;橼ʀadelsↄⅪ←ٖ↛ǰ↉\x00↎pro\xf8₞r;楸qĀlqؿ↖les\xf3₈i\xed٫Āen↣↭rtneqq;쀀≩︀\xc5↪ԀAabcefkosy⇄⇇⇱⇵⇺∘∝∯≨≽r\xf2ΠȀilmr⇐⇔⇗⇛rs\xf0ᒄf\xbb․il\xf4کĀdr⇠⇤cy;䑊ƀ;cwࣴ⇫⇯ir;楈;憭ar;意irc;䄥ƀalr∁∎∓rtsĀ;u∉∊晥it\xbb∊lip;怦con;抹r;쀀\ud835\udd25sĀew∣∩arow;椥arow;椦ʀamopr∺∾≃≞≣rr;懿tht;戻kĀlr≉≓eftarrow;憩ightarrow;憪f;쀀\ud835\udd59bar;怕ƀclt≯≴≸r;쀀\ud835\udcbdas\xe8⇴rok;䄧Ābp⊂⊇ull;恃hen\xbbᱛૡ⊣\x00⊪\x00⊸⋅⋎\x00⋕⋳\x00\x00⋸⌢⍧⍢⍿\x00⎆⎪⎴cute耻\xed䃭ƀ;iyݱ⊰⊵rc耻\xee䃮;䐸Ācx⊼⊿y;䐵cl耻\xa1䂡ĀfrΟ⋉;쀀\ud835\udd26rave耻\xec䃬Ȁ;inoܾ⋝⋩⋮Āin⋢⋦nt;樌t;戭fin;槜ta;愩lig;䄳ƀaop⋾⌚⌝ƀcgt⌅⌈⌗r;䄫ƀelpܟ⌏⌓in\xe5ގar\xf4ܠh;䄱f;抷ed;䆵ʀ;cfotӴ⌬⌱⌽⍁are;愅inĀ;t⌸⌹戞ie;槝do\xf4⌙ʀ;celpݗ⍌⍐⍛⍡al;抺Āgr⍕⍙er\xf3ᕣ\xe3⍍arhk;樗rod;樼Ȁcgpt⍯⍲⍶⍻y;䑑on;䄯f;쀀\ud835\udd5aa;䎹uest耻\xbf䂿Āci⎊⎏r;쀀\ud835\udcbenʀ;EdsvӴ⎛⎝⎡ӳ;拹ot;拵Ā;v⎦⎧拴;拳Ā;iݷ⎮lde;䄩ǫ⎸\x00⎼cy;䑖l耻\xef䃯̀cfmosu⏌⏗⏜⏡⏧⏵Āiy⏑⏕rc;䄵;䐹r;쀀\ud835\udd27ath;䈷pf;쀀\ud835\udd5bǣ⏬\x00⏱r;쀀\ud835\udcbfrcy;䑘kcy;䑔Ѐacfghjos␋␖␢␧␭␱␵␻ppaĀ;v␓␔䎺;䏰Āey␛␠dil;䄷;䐺r;쀀\ud835\udd28reen;䄸cy;䑅cy;䑜pf;쀀\ud835\udd5ccr;쀀\ud835\udcc0஀ABEHabcdefghjlmnoprstuv⑰⒁⒆⒍⒑┎┽╚▀♎♞♥♹♽⚚⚲⛘❝❨➋⟀⠁⠒ƀart⑷⑺⑼r\xf2৆\xf2Εail;椛arr;椎Ā;gঔ⒋;檋ar;楢ॣ⒥\x00⒪\x00⒱\x00\x00\x00\x00\x00⒵Ⓔ\x00ⓆⓈⓍ\x00⓹ute;䄺mptyv;榴ra\xeeࡌbda;䎻gƀ;dlࢎⓁⓃ;榑\xe5ࢎ;檅uo耻\xab䂫rЀ;bfhlpst࢙ⓞⓦⓩ⓫⓮⓱⓵Ā;f࢝ⓣs;椟s;椝\xeb≒p;憫l;椹im;楳l;憢ƀ;ae⓿─┄檫il;椙Ā;s┉┊檭;쀀⪭︀ƀabr┕┙┝rr;椌rk;杲Āak┢┬cĀek┨┪;䁻;䁛Āes┱┳;榋lĀdu┹┻;榏;榍Ȁaeuy╆╋╖╘ron;䄾Ādi═╔il;䄼\xecࢰ\xe2┩;䐻Ȁcqrs╣╦╭╽a;椶uoĀ;rนᝆĀdu╲╷har;楧shar;楋h;憲ʀ;fgqs▋▌উ◳◿扤tʀahlrt▘▤▷◂◨rrowĀ;t࢙□a\xe9⓶arpoonĀdu▯▴own\xbbњp\xbb०eftarrows;懇ightƀahs◍◖◞rrowĀ;sࣴࢧarpoon\xf3྘quigarro\xf7⇰hreetimes;拋ƀ;qs▋ও◺lan\xf4বʀ;cdgsব☊☍☝☨c;檨otĀ;o☔☕橿Ā;r☚☛檁;檃Ā;e☢☥쀀⋚︀s;檓ʀadegs☳☹☽♉♋ppro\xf8Ⓠot;拖qĀgq♃♅\xf4উgt\xf2⒌\xf4ছi\xedলƀilr♕࣡♚sht;楼;쀀\ud835\udd29Ā;Eজ♣;檑š♩♶rĀdu▲♮Ā;l॥♳;楪lk;斄cy;䑙ʀ;achtੈ⚈⚋⚑⚖r\xf2◁orne\xf2ᴈard;楫ri;旺Āio⚟⚤dot;䅀ustĀ;a⚬⚭掰che\xbb⚭ȀEaes⚻⚽⛉⛔;扨pĀ;p⛃⛄檉rox\xbb⛄Ā;q⛎⛏檇Ā;q⛎⚻im;拦Ѐabnoptwz⛩⛴⛷✚✯❁❇❐Ānr⛮⛱g;柬r;懽r\xebࣁgƀlmr⛿✍✔eftĀar০✇ight\xe1৲apsto;柼ight\xe1৽parrowĀlr✥✩ef\xf4⓭ight;憬ƀafl✶✹✽r;榅;쀀\ud835\udd5dus;樭imes;樴š❋❏st;戗\xe1ፎƀ;ef❗❘᠀旊nge\xbb❘arĀ;l❤❥䀨t;榓ʀachmt❳❶❼➅➇r\xf2ࢨorne\xf2ᶌarĀ;d྘➃;業;怎ri;抿̀achiqt➘➝ੀ➢➮➻quo;怹r;쀀\ud835\udcc1mƀ;egল➪➬;檍;檏Ābu┪➳oĀ;rฟ➹;怚rok;䅂萀<;cdhilqrࠫ⟒☹⟜⟠⟥⟪⟰Āci⟗⟙;檦r;橹re\xe5◲mes;拉arr;楶uest;橻ĀPi⟵⟹ar;榖ƀ;ef⠀भ᠛旃rĀdu⠇⠍shar;楊har;楦Āen⠗⠡rtneqq;쀀≨︀\xc5⠞܀Dacdefhilnopsu⡀⡅⢂⢎⢓⢠⢥⢨⣚⣢⣤ઃ⣳⤂Dot;戺Ȁclpr⡎⡒⡣⡽r耻\xaf䂯Āet⡗⡙;時Ā;e⡞⡟朠se\xbb⡟Ā;sျ⡨toȀ;dluျ⡳⡷⡻ow\xeeҌef\xf4ए\xf0Ꮡker;斮Āoy⢇⢌mma;権;䐼ash;怔asuredangle\xbbᘦr;쀀\ud835\udd2ao;愧ƀcdn⢯⢴⣉ro耻\xb5䂵Ȁ;acdᑤ⢽⣀⣄s\xf4ᚧir;櫰ot肻\xb7Ƶusƀ;bd⣒ᤃ⣓戒Ā;uᴼ⣘;横ţ⣞⣡p;櫛\xf2−\xf0ઁĀdp⣩⣮els;抧f;쀀\ud835\udd5eĀct⣸⣽r;쀀\ud835\udcc2pos\xbbᖝƀ;lm⤉⤊⤍䎼timap;抸ఀGLRVabcdefghijlmoprstuvw⥂⥓⥾⦉⦘⧚⧩⨕⨚⩘⩝⪃⪕⪤⪨⬄⬇⭄⭿⮮ⰴⱧⱼ⳩Āgt⥇⥋;쀀⋙̸Ā;v⥐௏쀀≫⃒ƀelt⥚⥲⥶ftĀar⥡⥧rrow;懍ightarrow;懎;쀀⋘̸Ā;v⥻ే쀀≪⃒ightarrow;懏ĀDd⦎⦓ash;抯ash;抮ʀbcnpt⦣⦧⦬⦱⧌la\xbb˞ute;䅄g;쀀∠⃒ʀ;Eiop඄⦼⧀⧅⧈;쀀⩰̸d;쀀≋̸s;䅉ro\xf8඄urĀ;a⧓⧔普lĀ;s⧓ସdz⧟\x00⧣p肻\xa0ଷmpĀ;e௹ఀʀaeouy⧴⧾⨃⨐⨓ǰ⧹\x00⧻;橃on;䅈dil;䅆ngĀ;dൾ⨊ot;쀀⩭̸p;橂;䐽ash;怓΀;Aadqsxஒ⨩⨭⨻⩁⩅⩐rr;懗rĀhr⨳⨶k;椤Ā;oᏲᏰot;쀀≐̸ui\xf6ୣĀei⩊⩎ar;椨\xed஘istĀ;s஠டr;쀀\ud835\udd2bȀEest௅⩦⩹⩼ƀ;qs஼⩭௡ƀ;qs஼௅⩴lan\xf4௢i\xed௪Ā;rஶ⪁\xbbஷƀAap⪊⪍⪑r\xf2⥱rr;憮ar;櫲ƀ;svྍ⪜ྌĀ;d⪡⪢拼;拺cy;䑚΀AEadest⪷⪺⪾⫂⫅⫶⫹r\xf2⥦;쀀≦̸rr;憚r;急Ȁ;fqs఻⫎⫣⫯tĀar⫔⫙rro\xf7⫁ightarro\xf7⪐ƀ;qs఻⪺⫪lan\xf4ౕĀ;sౕ⫴\xbbశi\xedౝĀ;rవ⫾iĀ;eచథi\xe4ඐĀpt⬌⬑f;쀀\ud835\udd5f膀\xac;in⬙⬚⬶䂬nȀ;Edvஉ⬤⬨⬮;쀀⋹̸ot;쀀⋵̸ǡஉ⬳⬵;拷;拶iĀ;vಸ⬼ǡಸ⭁⭃;拾;拽ƀaor⭋⭣⭩rȀ;ast୻⭕⭚⭟lle\xec୻l;쀀⫽⃥;쀀∂̸lint;樔ƀ;ceಒ⭰⭳u\xe5ಥĀ;cಘ⭸Ā;eಒ⭽\xf1ಘȀAait⮈⮋⮝⮧r\xf2⦈rrƀ;cw⮔⮕⮙憛;쀀⤳̸;쀀↝̸ghtarrow\xbb⮕riĀ;eೋೖ΀chimpqu⮽⯍⯙⬄୸⯤⯯Ȁ;cerല⯆ഷ⯉u\xe5൅;쀀\ud835\udcc3ortɭ⬅\x00\x00⯖ar\xe1⭖mĀ;e൮⯟Ā;q൴൳suĀbp⯫⯭\xe5೸\xe5ഋƀbcp⯶ⰑⰙȀ;Ees⯿ⰀഢⰄ抄;쀀⫅̸etĀ;eഛⰋqĀ;qണⰀcĀ;eലⰗ\xf1സȀ;EesⰢⰣൟⰧ抅;쀀⫆̸etĀ;e൘ⰮqĀ;qൠⰣȀgilrⰽⰿⱅⱇ\xecௗlde耻\xf1䃱\xe7ృiangleĀlrⱒⱜeftĀ;eచⱚ\xf1దightĀ;eೋⱥ\xf1೗Ā;mⱬⱭ䎽ƀ;esⱴⱵⱹ䀣ro;愖p;怇ҀDHadgilrsⲏⲔⲙⲞⲣⲰⲶⳓⳣash;抭arr;椄p;쀀≍⃒ash;抬ĀetⲨⲬ;쀀≥⃒;쀀>⃒nfin;槞ƀAetⲽⳁⳅrr;椂;쀀≤⃒Ā;rⳊⳍ쀀<⃒ie;쀀⊴⃒ĀAtⳘⳜrr;椃rie;쀀⊵⃒im;쀀∼⃒ƀAan⳰⳴ⴂrr;懖rĀhr⳺⳽k;椣Ā;oᏧᏥear;椧ቓ᪕\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00ⴭ\x00ⴸⵈⵠⵥ⵲ⶄᬇ\x00\x00ⶍⶫ\x00ⷈⷎ\x00ⷜ⸙⸫⸾⹃Ācsⴱ᪗ute耻\xf3䃳ĀiyⴼⵅrĀ;c᪞ⵂ耻\xf4䃴;䐾ʀabios᪠ⵒⵗLjⵚlac;䅑v;樸old;榼lig;䅓Ācr⵩⵭ir;榿;쀀\ud835\udd2cͯ⵹\x00\x00⵼\x00ⶂn;䋛ave耻\xf2䃲;槁Ābmⶈ෴ar;榵Ȁacitⶕ⶘ⶥⶨr\xf2᪀Āir⶝ⶠr;榾oss;榻n\xe5๒;槀ƀaeiⶱⶵⶹcr;䅍ga;䏉ƀcdnⷀⷅǍron;䎿;榶pf;쀀\ud835\udd60ƀaelⷔ⷗ǒr;榷rp;榹΀;adiosvⷪⷫⷮ⸈⸍⸐⸖戨r\xf2᪆Ȁ;efmⷷⷸ⸂⸅橝rĀ;oⷾⷿ愴f\xbbⷿ耻\xaa䂪耻\xba䂺gof;抶r;橖lope;橗;橛ƀclo⸟⸡⸧\xf2⸁ash耻\xf8䃸l;折iŬⸯ⸴de耻\xf5䃵esĀ;aǛ⸺s;樶ml耻\xf6䃶bar;挽ૡ⹞\x00⹽\x00⺀⺝\x00⺢⺹\x00\x00⻋ຜ\x00⼓\x00\x00⼫⾼\x00⿈rȀ;astЃ⹧⹲຅脀\xb6;l⹭⹮䂶le\xecЃɩ⹸\x00\x00⹻m;櫳;櫽y;䐿rʀcimpt⺋⺏⺓ᡥ⺗nt;䀥od;䀮il;怰enk;怱r;쀀\ud835\udd2dƀimo⺨⺰⺴Ā;v⺭⺮䏆;䏕ma\xf4੶ne;明ƀ;tv⺿⻀⻈䏀chfork\xbb´;䏖Āau⻏⻟nĀck⻕⻝kĀ;h⇴⻛;愎\xf6⇴sҀ;abcdemst⻳⻴ᤈ⻹⻽⼄⼆⼊⼎䀫cir;樣ir;樢Āouᵀ⼂;樥;橲n肻\xb1ຝim;樦wo;樧ƀipu⼙⼠⼥ntint;樕f;쀀\ud835\udd61nd耻\xa3䂣Ԁ;Eaceinosu່⼿⽁⽄⽇⾁⾉⾒⽾⾶;檳p;檷u\xe5໙Ā;c໎⽌̀;acens່⽙⽟⽦⽨⽾ppro\xf8⽃urlye\xf1໙\xf1໎ƀaes⽯⽶⽺pprox;檹qq;檵im;拨i\xedໟmeĀ;s⾈ຮ怲ƀEas⽸⾐⽺\xf0⽵ƀdfp໬⾙⾯ƀals⾠⾥⾪lar;挮ine;挒urf;挓Ā;t໻⾴\xef໻rel;抰Āci⿀⿅r;쀀\ud835\udcc5;䏈ncsp;怈̀fiopsu⿚⋢⿟⿥⿫⿱r;쀀\ud835\udd2epf;쀀\ud835\udd62rime;恗cr;쀀\ud835\udcc6ƀaeo⿸〉〓tĀei⿾々rnion\xf3ڰnt;樖stĀ;e【】䀿\xf1Ἑ\xf4༔઀ABHabcdefhilmnoprstux぀けさすムㄎㄫㅇㅢㅲㆎ㈆㈕㈤㈩㉘㉮㉲㊐㊰㊷ƀartぇおがr\xf2Ⴓ\xf2ϝail;検ar\xf2ᱥar;楤΀cdenqrtとふへみわゔヌĀeuねぱ;쀀∽̱te;䅕i\xe3ᅮmptyv;榳gȀ;del࿑らるろ;榒;榥\xe5࿑uo耻\xbb䂻rր;abcfhlpstw࿜ガクシスゼゾダッデナp;極Ā;f࿠ゴs;椠;椳s;椞\xeb≝\xf0✮l;楅im;楴l;憣;憝Āaiパフil;椚oĀ;nホボ戶al\xf3༞ƀabrョリヮr\xf2៥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Uint16Array("Ȁaglq \x15\x18\x1bɭ\x0f\x00\x00\x12p;䀦os;䀧t;䀾t;䀼uot;䀢".split("").map(e=>e.charCodeAt(0)));let eb=new Map([[0,65533],[128,8364],[130,8218],[131,402],[132,8222],[133,8230],[134,8224],[135,8225],[136,710],[137,8240],[138,352],[139,8249],[140,338],[142,381],[145,8216],[146,8217],[147,8220],[148,8221],[149,8226],[150,8211],[151,8212],[152,732],[153,8482],[154,353],[155,8250],[156,339],[158,382],[159,376]]),eT=null!==(A=String.fromCodePoint)&&void 0!==A?A:function(e){let t="";return e>65535&&(e-=65536,t+=String.fromCharCode(e>>>10&1023|55296),e=56320|1023&e),t+=String.fromCharCode(e)};function eS(e){return e>=y.ZERO&&e<=y.NINE}(o=y||(y={}))[o.NUM=35]="NUM",o[o.SEMI=59]="SEMI",o[o.EQUALS=61]="EQUALS",o[o.ZERO=48]="ZERO",o[o.NINE=57]="NINE",o[o.LOWER_A=97]="LOWER_A",o[o.LOWER_F=102]="LOWER_F",o[o.LOWER_X=120]="LOWER_X",o[o.LOWER_Z=122]="LOWER_Z",o[o.UPPER_A=65]="UPPER_A",o[o.UPPER_F=70]="UPPER_F",o[o.UPPER_Z=90]="UPPER_Z",(s=_||(_={}))[s.VALUE_LENGTH=49152]="VALUE_LENGTH",s[s.BRANCH_LENGTH=16256]="BRANCH_LENGTH",s[s.JUMP_TABLE=127]="JUMP_TABLE",(l=N||(N={}))[l.EntityStart=0]="EntityStart",l[l.NumericStart=1]="NumericStart",l[l.NumericDecimal=2]="NumericDecimal",l[l.NumericHex=3]="NumericHex",l[l.NamedEntity=4]="NamedEntity",(c=I||(I={}))[c.Legacy=0]="Legacy",c[c.Strict=1]="Strict",c[c.Attribute=2]="Attribute";class eA{constructor(e,t,n){this.decodeTree=e,this.emitCodePoint=t,this.errors=n,this.state=N.EntityStart,this.consumed=1,this.result=0,this.treeIndex=0,this.excess=1,this.decodeMode=I.Strict}startEntity(e){this.decodeMode=e,this.state=N.EntityStart,this.result=0,this.treeIndex=0,this.excess=1,this.consumed=1}write(e,t){switch(this.state){case N.EntityStart:if(e.charCodeAt(t)===y.NUM)return this.state=N.NumericStart,this.consumed+=1,this.stateNumericStart(e,t+1);return this.state=N.NamedEntity,this.stateNamedEntity(e,t);case N.NumericStart:return this.stateNumericStart(e,t);case N.NumericDecimal:return this.stateNumericDecimal(e,t);case N.NumericHex:return this.stateNumericHex(e,t);case N.NamedEntity:return this.stateNamedEntity(e,t)}}stateNumericStart(e,t){return t>=e.length?-1:(32|e.charCodeAt(t))===y.LOWER_X?(this.state=N.NumericHex,this.consumed+=1,this.stateNumericHex(e,t+1)):(this.state=N.NumericDecimal,this.stateNumericDecimal(e,t))}addToNumericResult(e,t,n,r){if(t!==n){let a=n-t;this.result=this.result*Math.pow(r,a)+parseInt(e.substr(t,a),r),this.consumed+=a}}stateNumericHex(e,t){let n=t;for(;t=y.UPPER_A)||!(r<=y.UPPER_F))&&(!(r>=y.LOWER_A)||!(r<=y.LOWER_F)))return this.addToNumericResult(e,n,t,16),this.emitNumericEntity(a,3);t+=1}return this.addToNumericResult(e,n,t,16),-1}stateNumericDecimal(e,t){let n=t;for(;t=55296&&r<=57343||r>1114111?65533:null!==(a=eb.get(r))&&void 0!==a?a:r,this.consumed),this.errors&&(e!==y.SEMI&&this.errors.missingSemicolonAfterCharacterReference(),this.errors.validateNumericCharacterReference(this.result)),this.consumed}stateNamedEntity(e,t){let{decodeTree:n}=this,r=n[this.treeIndex],a=(r&_.VALUE_LENGTH)>>14;for(;t=y.UPPER_A&&t<=y.UPPER_Z||t>=y.LOWER_A&&t<=y.LOWER_Z||eS(t)}(i))?0:this.emitNotTerminatedNamedEntity();if(0!=(a=((r=n[this.treeIndex])&_.VALUE_LENGTH)>>14)){if(i===y.SEMI)return this.emitNamedEntityData(this.treeIndex,a,this.consumed+this.excess);this.decodeMode!==I.Strict&&(this.result=this.treeIndex,this.consumed+=this.excess,this.excess=0)}}return -1}emitNotTerminatedNamedEntity(){var e;let{result:t,decodeTree:n}=this,r=(n[t]&_.VALUE_LENGTH)>>14;return this.emitNamedEntityData(t,r,this.consumed),null===(e=this.errors)||void 0===e||e.missingSemicolonAfterCharacterReference(),this.consumed}emitNamedEntityData(e,t,n){let{decodeTree:r}=this;return this.emitCodePoint(1===t?r[e]&~_.VALUE_LENGTH:r[e+1],n),3===t&&this.emitCodePoint(r[e+2],n),n}end(){var e;switch(this.state){case N.NamedEntity:return 0!==this.result&&(this.decodeMode!==I.Attribute||this.result===this.treeIndex)?this.emitNotTerminatedNamedEntity():0;case N.NumericDecimal:return this.emitNumericEntity(0,2);case N.NumericHex:return this.emitNumericEntity(0,3);case N.NumericStart:return null===(e=this.errors)||void 0===e||e.absenceOfDigitsInNumericCharacterReference(this.consumed),0;case N.EntityStart:return 0}}}function ey(e){let t="",n=new eA(e,e=>t+=eT(e));return function(e,r){let a=0,i=0;for(;(i=e.indexOf("&",i))>=0;){t+=e.slice(a,i),n.startEntity(r);let o=n.write(e,i+1);if(o<0){a=i+n.end();break}a=i+o,i=0===o?a+1:a}let o=t+e.slice(a);return t="",o}}function e_(e,t,n,r){let a=(t&_.BRANCH_LENGTH)>>7,i=t&_.JUMP_TABLE;if(0===a)return 0!==i&&r===i?n:-1;if(i){let t=r-i;return t<0||t>=a?-1:e[n+t]-1}let o=n,s=o+a-1;for(;o<=s;){let t=o+s>>>1,n=e[t];if(nr))return e[t+a];s=t-1}}return 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Map([[128,8364],[130,8218],[131,402],[132,8222],[133,8230],[134,8224],[135,8225],[136,710],[137,8240],[138,352],[139,8249],[140,338],[142,381],[145,8216],[146,8217],[147,8220],[148,8221],[149,8226],[150,8211],[151,8212],[152,732],[153,8482],[154,353],[155,8250],[156,339],[158,382],[159,376]]);(g=w||(w={}))[g.DATA=0]="DATA",g[g.RCDATA=1]="RCDATA",g[g.RAWTEXT=2]="RAWTEXT",g[g.SCRIPT_DATA=3]="SCRIPT_DATA",g[g.PLAINTEXT=4]="PLAINTEXT",g[g.TAG_OPEN=5]="TAG_OPEN",g[g.END_TAG_OPEN=6]="END_TAG_OPEN",g[g.TAG_NAME=7]="TAG_NAME",g[g.RCDATA_LESS_THAN_SIGN=8]="RCDATA_LESS_THAN_SIGN",g[g.RCDATA_END_TAG_OPEN=9]="RCDATA_END_TAG_OPEN",g[g.RCDATA_END_TAG_NAME=10]="RCDATA_END_TAG_NAME",g[g.RAWTEXT_LESS_THAN_SIGN=11]="RAWTEXT_LESS_THAN_SIGN",g[g.RAWTEXT_END_TAG_OPEN=12]="RAWTEXT_END_TAG_OPEN",g[g.RAWTEXT_END_TAG_NAME=13]="RAWTEXT_END_TAG_NAME",g[g.SCRIPT_DATA_LESS_THAN_SIGN=14]="SCRIPT_DATA_LESS_THAN_SIGN",g[g.SCRIPT_DATA_END_TAG_OPEN=15]="SCRIPT_DATA_END_TAG_OPEN",g[g.SCRIPT_DATA_END_TAG_NAME=16]="SCRIPT_DATA_END_TAG_NAME",g[g.SCRIPT_DATA_ESCAPE_START=17]="SCRIPT_DATA_ESCAPE_START",g[g.SCRIPT_DATA_ESCAPE_START_DASH=18]="SCRIPT_DATA_ESCAPE_START_DASH",g[g.SCRIPT_DATA_ESCAPED=19]="SCRIPT_DATA_ESCAPED",g[g.SCRIPT_DATA_ESCAPED_DASH=20]="SCRIPT_DATA_ESCAPED_DASH",g[g.SCRIPT_DATA_ESCAPED_DASH_DASH=21]="SCRIPT_DATA_ESCAPED_DASH_DASH",g[g.SCRIPT_DATA_ESCAPED_LESS_THAN_SIGN=22]="SCRIPT_DATA_ESCAPED_LESS_THAN_SIGN",g[g.SCRIPT_DATA_ESCAPED_END_TAG_OPEN=23]="SCRIPT_DATA_ESCAPED_END_TAG_OPEN",g[g.SCRIPT_DATA_ESCAPED_END_TAG_NAME=24]="SCRIPT_DATA_ESCAPED_END_TAG_NAME",g[g.SCRIPT_DATA_DOUBLE_ESCAPE_START=25]="SCRIPT_DATA_DOUBLE_ESCAPE_START",g[g.SCRIPT_DATA_DOUBLE_ESCAPED=26]="SCRIPT_DATA_DOUBLE_ESCAPED",g[g.SCRIPT_DATA_DOUBLE_ESCAPED_DASH=27]="SCRIPT_DATA_DOUBLE_ESCAPED_DASH",g[g.SCRIPT_DATA_DOUBLE_ESCAPED_DASH_DASH=28]="SCRIPT_DATA_DOUBLE_ESCAPED_DASH_DASH",g[g.SCRIPT_DATA_DOUBLE_ESCAPED_LESS_THAN_SIGN=29]="SCRIPT_DATA_DOUBLE_ESCAPED_LESS_THAN_SIGN",g[g.SCRIPT_DATA_DOUBLE_ESCAPE_END=30]="SCRIPT_DATA_DOUBLE_ESCAPE_END",g[g.BEFORE_ATTRIBUTE_NAME=31]="BEFORE_ATTRIBUTE_NAME",g[g.ATTRIBUTE_NAME=32]="ATTRIBUTE_NAME",g[g.AFTER_ATTRIBUTE_NAME=33]="AFTER_ATTRIBUTE_NAME",g[g.BEFORE_ATTRIBUTE_VALUE=34]="BEFORE_ATTRIBUTE_VALUE",g[g.ATTRIBUTE_VALUE_DOUBLE_QUOTED=35]="ATTRIBUTE_VALUE_DOUBLE_QUOTED",g[g.ATTRIBUTE_VALUE_SINGLE_QUOTED=36]="ATTRIBUTE_VALUE_SINGLE_QUOTED",g[g.ATTRIBUTE_VALUE_UNQUOTED=37]="ATTRIBUTE_VALUE_UNQUOTED",g[g.AFTER_ATTRIBUTE_VALUE_QUOTED=38]="AFTER_ATTRIBUTE_VALUE_QUOTED",g[g.SELF_CLOSING_START_TAG=39]="SELF_CLOSING_START_TAG",g[g.BOGUS_COMMENT=40]="BOGUS_COMMENT",g[g.MARKUP_DECLARATION_OPEN=41]="MARKUP_DECLARATION_OPEN",g[g.COMMENT_START=42]="COMMENT_START",g[g.COMMENT_START_DASH=43]="COMMENT_START_DASH",g[g.COMMENT=44]="COMMENT",g[g.COMMENT_LESS_THAN_SIGN=45]="COMMENT_LESS_THAN_SIGN",g[g.COMMENT_LESS_THAN_SIGN_BANG=46]="COMMENT_LESS_THAN_SIGN_BANG",g[g.COMMENT_LESS_THAN_SIGN_BANG_DASH=47]="COMMENT_LESS_THAN_SIGN_BANG_DASH",g[g.COMMENT_LESS_THAN_SIGN_BANG_DASH_DASH=48]="COMMENT_LESS_THAN_SIGN_BANG_DASH_DASH",g[g.COMMENT_END_DASH=49]="COMMENT_END_DASH",g[g.COMMENT_END=50]="COMMENT_END",g[g.COMMENT_END_BANG=51]="COMMENT_END_BANG",g[g.DOCTYPE=52]="DOCTYPE",g[g.BEFORE_DOCTYPE_NAME=53]="BEFORE_DOCTYPE_NAME",g[g.DOCTYPE_NAME=54]="DOCTYPE_NAME",g[g.AFTER_DOCTYPE_NAME=55]="AFTER_DOCTYPE_NAME",g[g.AFTER_DOCTYPE_PUBLIC_KEYWORD=56]="AFTER_DOCTYPE_PUBLIC_KEYWORD",g[g.BEFORE_DOCTYPE_PUBLIC_IDENTIFIER=57]="BEFORE_DOCTYPE_PUBLIC_IDENTIFIER",g[g.DOCTYPE_PUBLIC_IDENTIFIER_DOUBLE_QUOTED=58]="DOCTYPE_PUBLIC_IDENTIFIER_DOUBLE_QUOTED",g[g.DOCTYPE_PUBLIC_IDENTIFIER_SINGLE_QUOTED=59]="DOCTYPE_PUBLIC_IDENTIFIER_SINGLE_QUOTED",g[g.AFTER_DOCTYPE_PUBLIC_IDENTIFIER=60]="AFTER_DOCTYPE_PUBLIC_IDENTIFIER",g[g.BETWEEN_DOCTYPE_PUBLIC_AND_SYSTEM_IDENTIFIERS=61]="BETWEEN_DOCTYPE_PUBLIC_AND_SYSTEM_IDENTIFIERS",g[g.AFTER_DOCTYPE_SYSTEM_KEYWORD=62]="AFTER_DOCTYPE_SYSTEM_KEYWORD",g[g.BEFORE_DOCTYPE_SYSTEM_IDENTIFIER=63]="BEFORE_DOCTYPE_SYSTEM_IDENTIFIER",g[g.DOCTYPE_SYSTEM_IDENTIFIER_DOUBLE_QUOTED=64]="DOCTYPE_SYSTEM_IDENTIFIER_DOUBLE_QUOTED",g[g.DOCTYPE_SYSTEM_IDENTIFIER_SINGLE_QUOTED=65]="DOCTYPE_SYSTEM_IDENTIFIER_SINGLE_QUOTED",g[g.AFTER_DOCTYPE_SYSTEM_IDENTIFIER=66]="AFTER_DOCTYPE_SYSTEM_IDENTIFIER",g[g.BOGUS_DOCTYPE=67]="BOGUS_DOCTYPE",g[g.CDATA_SECTION=68]="CDATA_SECTION",g[g.CDATA_SECTION_BRACKET=69]="CDATA_SECTION_BRACKET",g[g.CDATA_SECTION_END=70]="CDATA_SECTION_END",g[g.CHARACTER_REFERENCE=71]="CHARACTER_REFERENCE",g[g.NAMED_CHARACTER_REFERENCE=72]="NAMED_CHARACTER_REFERENCE",g[g.AMBIGUOUS_AMPERSAND=73]="AMBIGUOUS_AMPERSAND",g[g.NUMERIC_CHARACTER_REFERENCE=74]="NUMERIC_CHARACTER_REFERENCE",g[g.HEXADEMICAL_CHARACTER_REFERENCE_START=75]="HEXADEMICAL_CHARACTER_REFERENCE_START",g[g.HEXADEMICAL_CHARACTER_REFERENCE=76]="HEXADEMICAL_CHARACTER_REFERENCE",g[g.DECIMAL_CHARACTER_REFERENCE=77]="DECIMAL_CHARACTER_REFERENCE",g[g.NUMERIC_CHARACTER_REFERENCE_END=78]="NUMERIC_CHARACTER_REFERENCE_END";let ev={DATA:w.DATA,RCDATA:w.RCDATA,RAWTEXT:w.RAWTEXT,SCRIPT_DATA:w.SCRIPT_DATA,PLAINTEXT:w.PLAINTEXT,CDATA_SECTION:w.CDATA_SECTION};function ew(e){return e>=b.DIGIT_0&&e<=b.DIGIT_9}function eD(e){return e>=b.LATIN_CAPITAL_A&&e<=b.LATIN_CAPITAL_Z}function eL(e){return e>=b.LATIN_SMALL_A&&e<=b.LATIN_SMALL_Z||eD(e)}function ex(e){return eL(e)||ew(e)}function eP(e){return e>=b.LATIN_CAPITAL_A&&e<=b.LATIN_CAPITAL_F}function eM(e){return e>=b.LATIN_SMALL_A&&e<=b.LATIN_SMALL_F}function eF(e){return e===b.SPACE||e===b.LINE_FEED||e===b.TABULATION||e===b.FORM_FEED}function eU(e){return eF(e)||e===b.SOLIDUS||e===b.GREATER_THAN_SIGN}class eB{constructor(e,t){this.options=e,this.handler=t,this.paused=!1,this.inLoop=!1,this.inForeignNode=!1,this.lastStartTagName="",this.active=!1,this.state=w.DATA,this.returnState=w.DATA,this.charRefCode=-1,this.consumedAfterSnapshot=-1,this.currentCharacterToken=null,this.currentToken=null,this.currentAttr={name:"",value:""},this.preprocessor=new ef(t),this.currentLocation=this.getCurrentLocation(-1)}_err(e){var t,n;null===(n=(t=this.handler).onParseError)||void 0===n||n.call(t,this.preprocessor.getError(e))}getCurrentLocation(e){return this.options.sourceCodeLocationInfo?{startLine:this.preprocessor.line,startCol:this.preprocessor.col-e,startOffset:this.preprocessor.offset-e,endLine:-1,endCol:-1,endOffset:-1}:null}_runParsingLoop(){if(!this.inLoop){for(this.inLoop=!0;this.active&&!this.paused;){this.consumedAfterSnapshot=0;let e=this._consume();this._ensureHibernation()||this._callState(e)}this.inLoop=!1}}pause(){this.paused=!0}resume(e){if(!this.paused)throw Error("Parser was already resumed");this.paused=!1,this.inLoop||(this._runParsingLoop(),this.paused||null==e||e())}write(e,t,n){this.active=!0,this.preprocessor.write(e,t),this._runParsingLoop(),this.paused||null==n||n()}insertHtmlAtCurrentPos(e){this.active=!0,this.preprocessor.insertHtmlAtCurrentPos(e),this._runParsingLoop()}_ensureHibernation(){return!!this.preprocessor.endOfChunkHit&&(this._unconsume(this.consumedAfterSnapshot),this.active=!1,!0)}_consume(){return this.consumedAfterSnapshot++,this.preprocessor.advance()}_unconsume(e){this.consumedAfterSnapshot-=e,this.preprocessor.retreat(e)}_reconsumeInState(e,t){this.state=e,this._callState(t)}_advanceBy(e){this.consumedAfterSnapshot+=e;for(let t=0;t0&&this._err(T.endTagWithAttributes),e.selfClosing&&this._err(T.endTagWithTrailingSolidus),this.handler.onEndTag(e)),this.preprocessor.dropParsedChunk()}emitCurrentComment(e){this.prepareToken(e),this.handler.onComment(e),this.preprocessor.dropParsedChunk()}emitCurrentDoctype(e){this.prepareToken(e),this.handler.onDoctype(e),this.preprocessor.dropParsedChunk()}_emitCurrentCharacterToken(e){if(this.currentCharacterToken){switch(e&&this.currentCharacterToken.location&&(this.currentCharacterToken.location.endLine=e.startLine,this.currentCharacterToken.location.endCol=e.startCol,this.currentCharacterToken.location.endOffset=e.startOffset),this.currentCharacterToken.type){case S.CHARACTER:this.handler.onCharacter(this.currentCharacterToken);break;case S.NULL_CHARACTER:this.handler.onNullCharacter(this.currentCharacterToken);break;case S.WHITESPACE_CHARACTER:this.handler.onWhitespaceCharacter(this.currentCharacterToken)}this.currentCharacterToken=null}}_emitEOFToken(){let e=this.getCurrentLocation(0);e&&(e.endLine=e.startLine,e.endCol=e.startCol,e.endOffset=e.startOffset),this._emitCurrentCharacterToken(e),this.handler.onEof({type:S.EOF,location:e}),this.active=!1}_appendCharToCurrentCharacterToken(e,t){if(this.currentCharacterToken){if(this.currentCharacterToken.type!==e)this.currentLocation=this.getCurrentLocation(0),this._emitCurrentCharacterToken(this.currentLocation),this.preprocessor.dropParsedChunk();else{this.currentCharacterToken.chars+=t;return}}this._createCharacterToken(e,t)}_emitCodePoint(e){let t=eF(e)?S.WHITESPACE_CHARACTER:e===b.NULL?S.NULL_CHARACTER:S.CHARACTER;this._appendCharToCurrentCharacterToken(t,String.fromCodePoint(e))}_emitChars(e){this._appendCharToCurrentCharacterToken(S.CHARACTER,e)}_matchNamedCharacterReference(e){let t=null,n=0,r=!1;for(let i=0,o=eh[0];i>=0&&!((i=e_(eh,o,i+1,e))<0);e=this._consume()){n+=1;let s=(o=eh[i])&_.VALUE_LENGTH;if(s){var a;let o=(s>>14)-1;if(e!==b.SEMICOLON&&this._isCharacterReferenceInAttribute()&&((a=this.preprocessor.peek(1))===b.EQUALS_SIGN||ex(a))?(t=[b.AMPERSAND],i+=o):(t=0===o?[eh[i]&~_.VALUE_LENGTH]:1===o?[eh[++i]]:[eh[++i],eh[++i]],n=0,r=e!==b.SEMICOLON),0===o){this._consume();break}}}return this._unconsume(n),r&&!this.preprocessor.endOfChunkHit&&this._err(T.missingSemicolonAfterCharacterReference),this._unconsume(1),t}_isCharacterReferenceInAttribute(){return this.returnState===w.ATTRIBUTE_VALUE_DOUBLE_QUOTED||this.returnState===w.ATTRIBUTE_VALUE_SINGLE_QUOTED||this.returnState===w.ATTRIBUTE_VALUE_UNQUOTED}_flushCodePointConsumedAsCharacterReference(e){this._isCharacterReferenceInAttribute()?this.currentAttr.value+=String.fromCodePoint(e):this._emitCodePoint(e)}_callState(e){switch(this.state){case w.DATA:this._stateData(e);break;case w.RCDATA:this._stateRcdata(e);break;case w.RAWTEXT:this._stateRawtext(e);break;case w.SCRIPT_DATA:this._stateScriptData(e);break;case w.PLAINTEXT:this._statePlaintext(e);break;case w.TAG_OPEN:this._stateTagOpen(e);break;case w.END_TAG_OPEN:this._stateEndTagOpen(e);break;case w.TAG_NAME:this._stateTagName(e);break;case w.RCDATA_LESS_THAN_SIGN:this._stateRcdataLessThanSign(e);break;case w.RCDATA_END_TAG_OPEN:this._stateRcdataEndTagOpen(e);break;case w.RCDATA_END_TAG_NAME:this._stateRcdataEndTagName(e);break;case w.RAWTEXT_LESS_THAN_SIGN:this._stateRawtextLessThanSign(e);break;case w.RAWTEXT_END_TAG_OPEN:this._stateRawtextEndTagOpen(e);break;case w.RAWTEXT_END_TAG_NAME:this._stateRawtextEndTagName(e);break;case w.SCRIPT_DATA_LESS_THAN_SIGN:this._stateScriptDataLessThanSign(e);break;case w.SCRIPT_DATA_END_TAG_OPEN:this._stateScriptDataEndTagOpen(e);break;case w.SCRIPT_DATA_END_TAG_NAME:this._stateScriptDataEndTagName(e);break;case w.SCRIPT_DATA_ESCAPE_START:this._stateScriptDataEscapeStart(e);break;case w.SCRIPT_DATA_ESCAPE_START_DASH:this._stateScriptDataEscapeStartDash(e);break;case w.SCRIPT_DATA_ESCAPED:this._stateScriptDataEscaped(e);break;case w.SCRIPT_DATA_ESCAPED_DASH:this._stateScriptDataEscapedDash(e);break;case w.SCRIPT_DATA_ESCAPED_DASH_DASH:this._stateScriptDataEscapedDashDash(e);break;case w.SCRIPT_DATA_ESCAPED_LESS_THAN_SIGN:this._stateScriptDataEscapedLessThanSign(e);break;case w.SCRIPT_DATA_ESCAPED_END_TAG_OPEN:this._stateScriptDataEscapedEndTagOpen(e);break;case w.SCRIPT_DATA_ESCAPED_END_TAG_NAME:this._stateScriptDataEscapedEndTagName(e);break;case w.SCRIPT_DATA_DOUBLE_ESCAPE_START:this._stateScriptDataDoubleEscapeStart(e);break;case w.SCRIPT_DATA_DOUBLE_ESCAPED:this._stateScriptDataDoubleEscaped(e);break;case w.SCRIPT_DATA_DOUBLE_ESCAPED_DASH:this._stateScriptDataDoubleEscapedDash(e);break;case w.SCRIPT_DATA_DOUBLE_ESCAPED_DASH_DASH:this._stateScriptDataDoubleEscapedDashDash(e);break;case w.SCRIPT_DATA_DOUBLE_ESCAPED_LESS_THAN_SIGN:this._stateScriptDataDoubleEscapedLessThanSign(e);break;case w.SCRIPT_DATA_DOUBLE_ESCAPE_END:this._stateScriptDataDoubleEscapeEnd(e);break;case w.BEFORE_ATTRIBUTE_NAME:this._stateBeforeAttributeName(e);break;case w.ATTRIBUTE_NAME:this._stateAttributeName(e);break;case w.AFTER_ATTRIBUTE_NAME:this._stateAfterAttributeName(e);break;case w.BEFORE_ATTRIBUTE_VALUE:this._stateBeforeAttributeValue(e);break;case w.ATTRIBUTE_VALUE_DOUBLE_QUOTED:this._stateAttributeValueDoubleQuoted(e);break;case w.ATTRIBUTE_VALUE_SINGLE_QUOTED:this._stateAttributeValueSingleQuoted(e);break;case w.ATTRIBUTE_VALUE_UNQUOTED:this._stateAttributeValueUnquoted(e);break;case w.AFTER_ATTRIBUTE_VALUE_QUOTED:this._stateAfterAttributeValueQuoted(e);break;case w.SELF_CLOSING_START_TAG:this._stateSelfClosingStartTag(e);break;case w.BOGUS_COMMENT:this._stateBogusComment(e);break;case w.MARKUP_DECLARATION_OPEN:this._stateMarkupDeclarationOpen(e);break;case w.COMMENT_START:this._stateCommentStart(e);break;case w.COMMENT_START_DASH:this._stateCommentStartDash(e);break;case w.COMMENT:this._stateComment(e);break;case w.COMMENT_LESS_THAN_SIGN:this._stateCommentLessThanSign(e);break;case w.COMMENT_LESS_THAN_SIGN_BANG:this._stateCommentLessThanSignBang(e);break;case w.COMMENT_LESS_THAN_SIGN_BANG_DASH:this._stateCommentLessThanSignBangDash(e);break;case w.COMMENT_LESS_THAN_SIGN_BANG_DASH_DASH:this._stateCommentLessThanSignBangDashDash(e);break;case w.COMMENT_END_DASH:this._stateCommentEndDash(e);break;case w.COMMENT_END:this._stateCommentEnd(e);break;case w.COMMENT_END_BANG:this._stateCommentEndBang(e);break;case w.DOCTYPE:this._stateDoctype(e);break;case w.BEFORE_DOCTYPE_NAME:this._stateBeforeDoctypeName(e);break;case w.DOCTYPE_NAME:this._stateDoctypeName(e);break;case w.AFTER_DOCTYPE_NAME:this._stateAfterDoctypeName(e);break;case w.AFTER_DOCTYPE_PUBLIC_KEYWORD:this._stateAfterDoctypePublicKeyword(e);break;case w.BEFORE_DOCTYPE_PUBLIC_IDENTIFIER:this._stateBeforeDoctypePublicIdentifier(e);break;case w.DOCTYPE_PUBLIC_IDENTIFIER_DOUBLE_QUOTED:this._stateDoctypePublicIdentifierDoubleQuoted(e);break;case w.DOCTYPE_PUBLIC_IDENTIFIER_SINGLE_QUOTED:this._stateDoctypePublicIdentifierSingleQuoted(e);break;case w.AFTER_DOCTYPE_PUBLIC_IDENTIFIER:this._stateAfterDoctypePublicIdentifier(e);break;case w.BETWEEN_DOCTYPE_PUBLIC_AND_SYSTEM_IDENTIFIERS:this._stateBetweenDoctypePublicAndSystemIdentifiers(e);break;case w.AFTER_DOCTYPE_SYSTEM_KEYWORD:this._stateAfterDoctypeSystemKeyword(e);break;case w.BEFORE_DOCTYPE_SYSTEM_IDENTIFIER:this._stateBeforeDoctypeSystemIdentifier(e);break;case w.DOCTYPE_SYSTEM_IDENTIFIER_DOUBLE_QUOTED:this._stateDoctypeSystemIdentifierDoubleQuoted(e);break;case w.DOCTYPE_SYSTEM_IDENTIFIER_SINGLE_QUOTED:this._stateDoctypeSystemIdentifierSingleQuoted(e);break;case w.AFTER_DOCTYPE_SYSTEM_IDENTIFIER:this._stateAfterDoctypeSystemIdentifier(e);break;case w.BOGUS_DOCTYPE:this._stateBogusDoctype(e);break;case w.CDATA_SECTION:this._stateCdataSection(e);break;case w.CDATA_SECTION_BRACKET:this._stateCdataSectionBracket(e);break;case w.CDATA_SECTION_END:this._stateCdataSectionEnd(e);break;case w.CHARACTER_REFERENCE:this._stateCharacterReference(e);break;case w.NAMED_CHARACTER_REFERENCE:this._stateNamedCharacterReference(e);break;case w.AMBIGUOUS_AMPERSAND:this._stateAmbiguousAmpersand(e);break;case w.NUMERIC_CHARACTER_REFERENCE:this._stateNumericCharacterReference(e);break;case w.HEXADEMICAL_CHARACTER_REFERENCE_START:this._stateHexademicalCharacterReferenceStart(e);break;case w.HEXADEMICAL_CHARACTER_REFERENCE:this._stateHexademicalCharacterReference(e);break;case w.DECIMAL_CHARACTER_REFERENCE:this._stateDecimalCharacterReference(e);break;case w.NUMERIC_CHARACTER_REFERENCE_END:this._stateNumericCharacterReferenceEnd(e);break;default:throw Error("Unknown state")}}_stateData(e){switch(e){case b.LESS_THAN_SIGN:this.state=w.TAG_OPEN;break;case b.AMPERSAND:this.returnState=w.DATA,this.state=w.CHARACTER_REFERENCE;break;case b.NULL:this._err(T.unexpectedNullCharacter),this._emitCodePoint(e);break;case b.EOF:this._emitEOFToken();break;default:this._emitCodePoint(e)}}_stateRcdata(e){switch(e){case b.AMPERSAND:this.returnState=w.RCDATA,this.state=w.CHARACTER_REFERENCE;break;case b.LESS_THAN_SIGN:this.state=w.RCDATA_LESS_THAN_SIGN;break;case b.NULL:this._err(T.unexpectedNullCharacter),this._emitChars("�");break;case b.EOF:this._emitEOFToken();break;default:this._emitCodePoint(e)}}_stateRawtext(e){switch(e){case b.LESS_THAN_SIGN:this.state=w.RAWTEXT_LESS_THAN_SIGN;break;case b.NULL:this._err(T.unexpectedNullCharacter),this._emitChars("�");break;case b.EOF:this._emitEOFToken();break;default:this._emitCodePoint(e)}}_stateScriptData(e){switch(e){case b.LESS_THAN_SIGN:this.state=w.SCRIPT_DATA_LESS_THAN_SIGN;break;case b.NULL:this._err(T.unexpectedNullCharacter),this._emitChars("�");break;case b.EOF:this._emitEOFToken();break;default:this._emitCodePoint(e)}}_statePlaintext(e){switch(e){case b.NULL:this._err(T.unexpectedNullCharacter),this._emitChars("�");break;case b.EOF:this._emitEOFToken();break;default:this._emitCodePoint(e)}}_stateTagOpen(e){if(eL(e))this._createStartTagToken(),this.state=w.TAG_NAME,this._stateTagName(e);else switch(e){case b.EXCLAMATION_MARK:this.state=w.MARKUP_DECLARATION_OPEN;break;case b.SOLIDUS:this.state=w.END_TAG_OPEN;break;case b.QUESTION_MARK:this._err(T.unexpectedQuestionMarkInsteadOfTagName),this._createCommentToken(1),this.state=w.BOGUS_COMMENT,this._stateBogusComment(e);break;case b.EOF:this._err(T.eofBeforeTagName),this._emitChars("<"),this._emitEOFToken();break;default:this._err(T.invalidFirstCharacterOfTagName),this._emitChars("<"),this.state=w.DATA,this._stateData(e)}}_stateEndTagOpen(e){if(eL(e))this._createEndTagToken(),this.state=w.TAG_NAME,this._stateTagName(e);else switch(e){case b.GREATER_THAN_SIGN:this._err(T.missingEndTagName),this.state=w.DATA;break;case b.EOF:this._err(T.eofBeforeTagName),this._emitChars("");break;case b.NULL:this._err(T.unexpectedNullCharacter),this.state=w.SCRIPT_DATA_ESCAPED,this._emitChars("�");break;case b.EOF:this._err(T.eofInScriptHtmlCommentLikeText),this._emitEOFToken();break;default:this.state=w.SCRIPT_DATA_ESCAPED,this._emitCodePoint(e)}}_stateScriptDataEscapedLessThanSign(e){e===b.SOLIDUS?this.state=w.SCRIPT_DATA_ESCAPED_END_TAG_OPEN:eL(e)?(this._emitChars("<"),this.state=w.SCRIPT_DATA_DOUBLE_ESCAPE_START,this._stateScriptDataDoubleEscapeStart(e)):(this._emitChars("<"),this.state=w.SCRIPT_DATA_ESCAPED,this._stateScriptDataEscaped(e))}_stateScriptDataEscapedEndTagOpen(e){eL(e)?(this.state=w.SCRIPT_DATA_ESCAPED_END_TAG_NAME,this._stateScriptDataEscapedEndTagName(e)):(this._emitChars("");break;case b.NULL:this._err(T.unexpectedNullCharacter),this.state=w.SCRIPT_DATA_DOUBLE_ESCAPED,this._emitChars("�");break;case b.EOF:this._err(T.eofInScriptHtmlCommentLikeText),this._emitEOFToken();break;default:this.state=w.SCRIPT_DATA_DOUBLE_ESCAPED,this._emitCodePoint(e)}}_stateScriptDataDoubleEscapedLessThanSign(e){e===b.SOLIDUS?(this.state=w.SCRIPT_DATA_DOUBLE_ESCAPE_END,this._emitChars("/")):(this.state=w.SCRIPT_DATA_DOUBLE_ESCAPED,this._stateScriptDataDoubleEscaped(e))}_stateScriptDataDoubleEscapeEnd(e){if(this.preprocessor.startsWith(eu.SCRIPT,!1)&&eU(this.preprocessor.peek(eu.SCRIPT.length))){this._emitCodePoint(e);for(let e=0;e1114111)this._err(T.characterReferenceOutsideUnicodeRange),this.charRefCode=b.REPLACEMENT_CHARACTER;else if(ed(this.charRefCode))this._err(T.surrogateCharacterReference),this.charRefCode=b.REPLACEMENT_CHARACTER;else if(em(this.charRefCode))this._err(T.noncharacterCharacterReference);else if(ep(this.charRefCode)||this.charRefCode===b.CARRIAGE_RETURN){this._err(T.controlCharacterReference);let e=eO.get(this.charRefCode);void 0!==e&&(this.charRefCode=e)}this._flushCodePointConsumedAsCharacterReference(this.charRefCode),this._reconsumeInState(this.returnState,e)}}let eH=new Set([v.DD,v.DT,v.LI,v.OPTGROUP,v.OPTION,v.P,v.RB,v.RP,v.RT,v.RTC]),eG=new Set([...eH,v.CAPTION,v.COLGROUP,v.TBODY,v.TD,v.TFOOT,v.TH,v.THEAD,v.TR]),ez=new Map([[v.APPLET,R.HTML],[v.CAPTION,R.HTML],[v.HTML,R.HTML],[v.MARQUEE,R.HTML],[v.OBJECT,R.HTML],[v.TABLE,R.HTML],[v.TD,R.HTML],[v.TEMPLATE,R.HTML],[v.TH,R.HTML],[v.ANNOTATION_XML,R.MATHML],[v.MI,R.MATHML],[v.MN,R.MATHML],[v.MO,R.MATHML],[v.MS,R.MATHML],[v.MTEXT,R.MATHML],[v.DESC,R.SVG],[v.FOREIGN_OBJECT,R.SVG],[v.TITLE,R.SVG]]),e$=[v.H1,v.H2,v.H3,v.H4,v.H5,v.H6],ej=[v.TR,v.TEMPLATE,v.HTML],eV=[v.TBODY,v.TFOOT,v.THEAD,v.TEMPLATE,v.HTML],eY=[v.TABLE,v.TEMPLATE,v.HTML],eW=[v.TD,v.TH];class eq{get currentTmplContentOrNode(){return this._isInTemplate()?this.treeAdapter.getTemplateContent(this.current):this.current}constructor(e,t,n){this.treeAdapter=t,this.handler=n,this.items=[],this.tagIDs=[],this.stackTop=-1,this.tmplCount=0,this.currentTagId=v.UNKNOWN,this.current=e}_indexOf(e){return this.items.lastIndexOf(e,this.stackTop)}_isInTemplate(){return this.currentTagId===v.TEMPLATE&&this.treeAdapter.getNamespaceURI(this.current)===R.HTML}_updateCurrentElement(){this.current=this.items[this.stackTop],this.currentTagId=this.tagIDs[this.stackTop]}push(e,t){this.stackTop++,this.items[this.stackTop]=e,this.current=e,this.tagIDs[this.stackTop]=t,this.currentTagId=t,this._isInTemplate()&&this.tmplCount++,this.handler.onItemPush(e,t,!0)}pop(){let e=this.current;this.tmplCount>0&&this._isInTemplate()&&this.tmplCount--,this.stackTop--,this._updateCurrentElement(),this.handler.onItemPop(e,!0)}replace(e,t){let n=this._indexOf(e);this.items[n]=t,n===this.stackTop&&(this.current=t)}insertAfter(e,t,n){let r=this._indexOf(e)+1;this.items.splice(r,0,t),this.tagIDs.splice(r,0,n),this.stackTop++,r===this.stackTop&&this._updateCurrentElement(),this.handler.onItemPush(this.current,this.currentTagId,r===this.stackTop)}popUntilTagNamePopped(e){let t=this.stackTop+1;do t=this.tagIDs.lastIndexOf(e,t-1);while(t>0&&this.treeAdapter.getNamespaceURI(this.items[t])!==R.HTML);this.shortenToLength(t<0?0:t)}shortenToLength(e){for(;this.stackTop>=e;){let t=this.current;this.tmplCount>0&&this._isInTemplate()&&(this.tmplCount-=1),this.stackTop--,this._updateCurrentElement(),this.handler.onItemPop(t,this.stackTop=0;n--)if(e.includes(this.tagIDs[n])&&this.treeAdapter.getNamespaceURI(this.items[n])===t)return n;return -1}clearBackTo(e,t){let n=this._indexOfTagNames(e,t);this.shortenToLength(n+1)}clearBackToTableContext(){this.clearBackTo(eY,R.HTML)}clearBackToTableBodyContext(){this.clearBackTo(eV,R.HTML)}clearBackToTableRowContext(){this.clearBackTo(ej,R.HTML)}remove(e){let t=this._indexOf(e);t>=0&&(t===this.stackTop?this.pop():(this.items.splice(t,1),this.tagIDs.splice(t,1),this.stackTop--,this._updateCurrentElement(),this.handler.onItemPop(e,!1)))}tryPeekProperlyNestedBodyElement(){return this.stackTop>=1&&this.tagIDs[1]===v.BODY?this.items[1]:null}contains(e){return this._indexOf(e)>-1}getCommonAncestor(e){let t=this._indexOf(e)-1;return t>=0?this.items[t]:null}isRootHtmlElementCurrent(){return 0===this.stackTop&&this.tagIDs[0]===v.HTML}hasInScope(e){for(let t=this.stackTop;t>=0;t--){let n=this.tagIDs[t],r=this.treeAdapter.getNamespaceURI(this.items[t]);if(n===e&&r===R.HTML)break;if(ez.get(n)===r)return!1}return!0}hasNumberedHeaderInScope(){for(let e=this.stackTop;e>=0;e--){let t=this.tagIDs[e],n=this.treeAdapter.getNamespaceURI(this.items[e]);if(ek(t)&&n===R.HTML)break;if(ez.get(t)===n)return!1}return!0}hasInListItemScope(e){for(let t=this.stackTop;t>=0;t--){let n=this.tagIDs[t],r=this.treeAdapter.getNamespaceURI(this.items[t]);if(n===e&&r===R.HTML)break;if((n===v.UL||n===v.OL)&&r===R.HTML||ez.get(n)===r)return!1}return!0}hasInButtonScope(e){for(let t=this.stackTop;t>=0;t--){let n=this.tagIDs[t],r=this.treeAdapter.getNamespaceURI(this.items[t]);if(n===e&&r===R.HTML)break;if(n===v.BUTTON&&r===R.HTML||ez.get(n)===r)return!1}return!0}hasInTableScope(e){for(let t=this.stackTop;t>=0;t--){let n=this.tagIDs[t];if(this.treeAdapter.getNamespaceURI(this.items[t])===R.HTML){if(n===e)break;if(n===v.TABLE||n===v.TEMPLATE||n===v.HTML)return!1}}return!0}hasTableBodyContextInTableScope(){for(let e=this.stackTop;e>=0;e--){let t=this.tagIDs[e];if(this.treeAdapter.getNamespaceURI(this.items[e])===R.HTML){if(t===v.TBODY||t===v.THEAD||t===v.TFOOT)break;if(t===v.TABLE||t===v.HTML)return!1}}return!0}hasInSelectScope(e){for(let t=this.stackTop;t>=0;t--){let n=this.tagIDs[t];if(this.treeAdapter.getNamespaceURI(this.items[t])===R.HTML){if(n===e)break;if(n!==v.OPTION&&n!==v.OPTGROUP)return!1}}return!0}generateImpliedEndTags(){for(;eH.has(this.currentTagId);)this.pop()}generateImpliedEndTagsThoroughly(){for(;eG.has(this.currentTagId);)this.pop()}generateImpliedEndTagsWithExclusion(e){for(;this.currentTagId!==e&&eG.has(this.currentTagId);)this.pop()}}(h=D=D||(D={}))[h.Marker=0]="Marker",h[h.Element=1]="Element";let eK={type:D.Marker};class eX{constructor(e){this.treeAdapter=e,this.entries=[],this.bookmark=null}_getNoahArkConditionCandidates(e,t){let n=[],r=t.length,a=this.treeAdapter.getTagName(e),i=this.treeAdapter.getNamespaceURI(e);for(let e=0;e[e.name,e.value])),a=0;for(let e=0;er.get(e.name)===e.value)&&(a+=1)>=3&&this.entries.splice(t.idx,1)}}insertMarker(){this.entries.unshift(eK)}pushElement(e,t){this._ensureNoahArkCondition(e),this.entries.unshift({type:D.Element,element:e,token:t})}insertElementAfterBookmark(e,t){let n=this.entries.indexOf(this.bookmark);this.entries.splice(n,0,{type:D.Element,element:e,token:t})}removeEntry(e){let t=this.entries.indexOf(e);t>=0&&this.entries.splice(t,1)}clearToLastMarker(){let e=this.entries.indexOf(eK);e>=0?this.entries.splice(0,e+1):this.entries.length=0}getElementEntryInScopeWithTagName(e){let t=this.entries.find(t=>t.type===D.Marker||this.treeAdapter.getTagName(t.element)===e);return t&&t.type===D.Element?t:null}getElementEntry(e){return this.entries.find(t=>t.type===D.Element&&t.element===e)}}function eZ(e){return{nodeName:"#text",value:e,parentNode:null}}let eQ={createDocument:()=>({nodeName:"#document",mode:k.NO_QUIRKS,childNodes:[]}),createDocumentFragment:()=>({nodeName:"#document-fragment",childNodes:[]}),createElement:(e,t,n)=>({nodeName:e,tagName:e,attrs:n,namespaceURI:t,childNodes:[],parentNode:null}),createCommentNode:e=>({nodeName:"#comment",data:e,parentNode:null}),appendChild(e,t){e.childNodes.push(t),t.parentNode=e},insertBefore(e,t,n){let r=e.childNodes.indexOf(n);e.childNodes.splice(r,0,t),t.parentNode=e},setTemplateContent(e,t){e.content=t},getTemplateContent:e=>e.content,setDocumentType(e,t,n,r){let a=e.childNodes.find(e=>"#documentType"===e.nodeName);a?(a.name=t,a.publicId=n,a.systemId=r):eQ.appendChild(e,{nodeName:"#documentType",name:t,publicId:n,systemId:r,parentNode:null})},setDocumentMode(e,t){e.mode=t},getDocumentMode:e=>e.mode,detachNode(e){if(e.parentNode){let t=e.parentNode.childNodes.indexOf(e);e.parentNode.childNodes.splice(t,1),e.parentNode=null}},insertText(e,t){if(e.childNodes.length>0){let n=e.childNodes[e.childNodes.length-1];if(eQ.isTextNode(n)){n.value+=t;return}}eQ.appendChild(e,eZ(t))},insertTextBefore(e,t,n){let r=e.childNodes[e.childNodes.indexOf(n)-1];r&&eQ.isTextNode(r)?r.value+=t:eQ.insertBefore(e,eZ(t),n)},adoptAttributes(e,t){let n=new Set(e.attrs.map(e=>e.name));for(let r=0;re.childNodes[0],getChildNodes:e=>e.childNodes,getParentNode:e=>e.parentNode,getAttrList:e=>e.attrs,getTagName:e=>e.tagName,getNamespaceURI:e=>e.namespaceURI,getTextNodeContent:e=>e.value,getCommentNodeContent:e=>e.data,getDocumentTypeNodeName:e=>e.name,getDocumentTypeNodePublicId:e=>e.publicId,getDocumentTypeNodeSystemId:e=>e.systemId,isTextNode:e=>"#text"===e.nodeName,isCommentNode:e=>"#comment"===e.nodeName,isDocumentTypeNode:e=>"#documentType"===e.nodeName,isElementNode:e=>Object.prototype.hasOwnProperty.call(e,"tagName"),setNodeSourceCodeLocation(e,t){e.sourceCodeLocation=t},getNodeSourceCodeLocation:e=>e.sourceCodeLocation,updateNodeSourceCodeLocation(e,t){e.sourceCodeLocation={...e.sourceCodeLocation,...t}}},eJ="html",e0=["+//silmaril//dtd html pro v0r11 19970101//","-//as//dtd html 3.0 aswedit + extensions//","-//advasoft ltd//dtd html 3.0 aswedit + extensions//","-//ietf//dtd html 2.0 level 1//","-//ietf//dtd html 2.0 level 2//","-//ietf//dtd html 2.0 strict level 1//","-//ietf//dtd html 2.0 strict level 2//","-//ietf//dtd html 2.0 strict//","-//ietf//dtd html 2.0//","-//ietf//dtd html 2.1e//","-//ietf//dtd html 3.0//","-//ietf//dtd html 3.2 final//","-//ietf//dtd html 3.2//","-//ietf//dtd html 3//","-//ietf//dtd html level 0//","-//ietf//dtd html level 1//","-//ietf//dtd html level 2//","-//ietf//dtd html level 3//","-//ietf//dtd html strict level 0//","-//ietf//dtd html strict level 1//","-//ietf//dtd html strict level 2//","-//ietf//dtd html strict level 3//","-//ietf//dtd html strict//","-//ietf//dtd html//","-//metrius//dtd metrius presentational//","-//microsoft//dtd internet explorer 2.0 html strict//","-//microsoft//dtd internet explorer 2.0 html//","-//microsoft//dtd internet explorer 2.0 tables//","-//microsoft//dtd internet explorer 3.0 html strict//","-//microsoft//dtd internet explorer 3.0 html//","-//microsoft//dtd internet explorer 3.0 tables//","-//netscape comm. corp.//dtd html//","-//netscape comm. corp.//dtd strict 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Map(["attributeName","attributeType","baseFrequency","baseProfile","calcMode","clipPathUnits","diffuseConstant","edgeMode","filterUnits","glyphRef","gradientTransform","gradientUnits","kernelMatrix","kernelUnitLength","keyPoints","keySplines","keyTimes","lengthAdjust","limitingConeAngle","markerHeight","markerUnits","markerWidth","maskContentUnits","maskUnits","numOctaves","pathLength","patternContentUnits","patternTransform","patternUnits","pointsAtX","pointsAtY","pointsAtZ","preserveAlpha","preserveAspectRatio","primitiveUnits","refX","refY","repeatCount","repeatDur","requiredExtensions","requiredFeatures","specularConstant","specularExponent","spreadMethod","startOffset","stdDeviation","stitchTiles","surfaceScale","systemLanguage","tableValues","targetX","targetY","textLength","viewBox","viewTarget","xChannelSelector","yChannelSelector","zoomAndPan"].map(e=>[e.toLowerCase(),e])),e9=new Map([["xlink:actuate",{prefix:"xlink",name:"actuate",namespace:R.XLINK}],["xlink:arcrole",{prefix:"xlink",name:"arcrole",namespace:R.XLINK}],["xlink:href",{prefix:"xlink",name:"href",namespace:R.XLINK}],["xlink:role",{prefix:"xlink",name:"role",namespace:R.XLINK}],["xlink:show",{prefix:"xlink",name:"show",namespace:R.XLINK}],["xlink:title",{prefix:"xlink",name:"title",namespace:R.XLINK}],["xlink:type",{prefix:"xlink",name:"type",namespace:R.XLINK}],["xml:base",{prefix:"xml",name:"base",namespace:R.XML}],["xml:lang",{prefix:"xml",name:"lang",namespace:R.XML}],["xml:space",{prefix:"xml",name:"space",namespace:R.XML}],["xmlns",{prefix:"",name:"xmlns",namespace:R.XMLNS}],["xmlns:xlink",{prefix:"xmlns",name:"xlink",namespace:R.XMLNS}]]),e7=new Map(["altGlyph","altGlyphDef","altGlyphItem","animateColor","animateMotion","animateTransform","clipPath","feBlend","feColorMatrix","feComponentTransfer","feComposite","feConvolveMatrix","feDiffuseLighting","feDisplacementMap","feDistantLight","feFlood","feFuncA","feFuncB","feFuncG","feFuncR","feGaussianBlur","feImage","feMerge","feMergeNode","feMorphology","feOffset","fePointLight","feSpecularLighting","feSpotLight","feTile","feTurbulence","foreignObject","glyphRef","linearGradient","radialGradient","textPath"].map(e=>[e.toLowerCase(),e])),te=new Set([v.B,v.BIG,v.BLOCKQUOTE,v.BODY,v.BR,v.CENTER,v.CODE,v.DD,v.DIV,v.DL,v.DT,v.EM,v.EMBED,v.H1,v.H2,v.H3,v.H4,v.H5,v.H6,v.HEAD,v.HR,v.I,v.IMG,v.LI,v.LISTING,v.MENU,v.META,v.NOBR,v.OL,v.P,v.PRE,v.RUBY,v.S,v.SMALL,v.SPAN,v.STRONG,v.STRIKE,v.SUB,v.SUP,v.TABLE,v.TT,v.U,v.UL,v.VAR]);function tt(e){for(let t=0;t0&&this._setContextModes(e,t)}onItemPop(e,t){var n,r;if(this.options.sourceCodeLocationInfo&&this._setEndLocation(e,this.currentToken),null===(r=(n=this.treeAdapter).onItemPop)||void 0===r||r.call(n,e,this.openElements.current),t){let e,t;0===this.openElements.stackTop&&this.fragmentContext?(e=this.fragmentContext,t=this.fragmentContextID):{current:e,currentTagId:t}=this.openElements,this._setContextModes(e,t)}}_setContextModes(e,t){let n=e===this.document||this.treeAdapter.getNamespaceURI(e)===R.HTML;this.currentNotInHTML=!n,this.tokenizer.inForeignNode=!n&&!this._isIntegrationPoint(t,e)}_switchToTextParsing(e,t){this._insertElement(e,R.HTML),this.tokenizer.state=t,this.originalInsertionMode=this.insertionMode,this.insertionMode=L.TEXT}switchToPlaintextParsing(){this.insertionMode=L.TEXT,this.originalInsertionMode=L.IN_BODY,this.tokenizer.state=ev.PLAINTEXT}_getAdjustedCurrentElement(){return 0===this.openElements.stackTop&&this.fragmentContext?this.fragmentContext:this.openElements.current}_findFormInFragmentContext(){let e=this.fragmentContext;for(;e;){if(this.treeAdapter.getTagName(e)===O.FORM){this.formElement=e;break}e=this.treeAdapter.getParentNode(e)}}_initTokenizerForFragmentParsing(){if(this.fragmentContext&&this.treeAdapter.getNamespaceURI(this.fragmentContext)===R.HTML)switch(this.fragmentContextID){case v.TITLE:case v.TEXTAREA:this.tokenizer.state=ev.RCDATA;break;case v.STYLE:case v.XMP:case v.IFRAME:case v.NOEMBED:case v.NOFRAMES:case v.NOSCRIPT:this.tokenizer.state=ev.RAWTEXT;break;case v.SCRIPT:this.tokenizer.state=ev.SCRIPT_DATA;break;case v.PLAINTEXT:this.tokenizer.state=ev.PLAINTEXT}}_setDocumentType(e){let t=e.name||"",n=e.publicId||"",r=e.systemId||"";if(this.treeAdapter.setDocumentType(this.document,t,n,r),e.location){let t=this.treeAdapter.getChildNodes(this.document).find(e=>this.treeAdapter.isDocumentTypeNode(e));t&&this.treeAdapter.setNodeSourceCodeLocation(t,e.location)}}_attachElementToTree(e,t){if(this.options.sourceCodeLocationInfo){let n=t&&{...t,startTag:t};this.treeAdapter.setNodeSourceCodeLocation(e,n)}if(this._shouldFosterParentOnInsertion())this._fosterParentElement(e);else{let t=this.openElements.currentTmplContentOrNode;this.treeAdapter.appendChild(t,e)}}_appendElement(e,t){let n=this.treeAdapter.createElement(e.tagName,t,e.attrs);this._attachElementToTree(n,e.location)}_insertElement(e,t){let n=this.treeAdapter.createElement(e.tagName,t,e.attrs);this._attachElementToTree(n,e.location),this.openElements.push(n,e.tagID)}_insertFakeElement(e,t){let n=this.treeAdapter.createElement(e,R.HTML,[]);this._attachElementToTree(n,null),this.openElements.push(n,t)}_insertTemplate(e){let t=this.treeAdapter.createElement(e.tagName,R.HTML,e.attrs),n=this.treeAdapter.createDocumentFragment();this.treeAdapter.setTemplateContent(t,n),this._attachElementToTree(t,e.location),this.openElements.push(t,e.tagID),this.options.sourceCodeLocationInfo&&this.treeAdapter.setNodeSourceCodeLocation(n,null)}_insertFakeRootElement(){let e=this.treeAdapter.createElement(O.HTML,R.HTML,[]);this.options.sourceCodeLocationInfo&&this.treeAdapter.setNodeSourceCodeLocation(e,null),this.treeAdapter.appendChild(this.openElements.current,e),this.openElements.push(e,v.HTML)}_appendCommentNode(e,t){let n=this.treeAdapter.createCommentNode(e.data);this.treeAdapter.appendChild(t,n),this.options.sourceCodeLocationInfo&&this.treeAdapter.setNodeSourceCodeLocation(n,e.location)}_insertCharacters(e){let t,n;if(this._shouldFosterParentOnInsertion()?({parent:t,beforeElement:n}=this._findFosterParentingLocation(),n?this.treeAdapter.insertTextBefore(t,e.chars,n):this.treeAdapter.insertText(t,e.chars)):(t=this.openElements.currentTmplContentOrNode,this.treeAdapter.insertText(t,e.chars)),!e.location)return;let r=this.treeAdapter.getChildNodes(t),a=n?r.lastIndexOf(n):r.length,i=r[a-1];if(this.treeAdapter.getNodeSourceCodeLocation(i)){let{endLine:t,endCol:n,endOffset:r}=e.location;this.treeAdapter.updateNodeSourceCodeLocation(i,{endLine:t,endCol:n,endOffset:r})}else this.options.sourceCodeLocationInfo&&this.treeAdapter.setNodeSourceCodeLocation(i,e.location)}_adoptNodes(e,t){for(let n=this.treeAdapter.getFirstChild(e);n;n=this.treeAdapter.getFirstChild(e))this.treeAdapter.detachNode(n),this.treeAdapter.appendChild(t,n)}_setEndLocation(e,t){if(this.treeAdapter.getNodeSourceCodeLocation(e)&&t.location){let n=t.location,r=this.treeAdapter.getTagName(e),a=t.type===S.END_TAG&&r===t.tagName?{endTag:{...n},endLine:n.endLine,endCol:n.endCol,endOffset:n.endOffset}:{endLine:n.startLine,endCol:n.startCol,endOffset:n.startOffset};this.treeAdapter.updateNodeSourceCodeLocation(e,a)}}shouldProcessStartTagTokenInForeignContent(e){let t,n;return!!this.currentNotInHTML&&(0===this.openElements.stackTop&&this.fragmentContext?(t=this.fragmentContext,n=this.fragmentContextID):{current:t,currentTagId:n}=this.openElements,(e.tagID!==v.SVG||this.treeAdapter.getTagName(t)!==O.ANNOTATION_XML||this.treeAdapter.getNamespaceURI(t)!==R.MATHML)&&(this.tokenizer.inForeignNode||(e.tagID===v.MGLYPH||e.tagID===v.MALIGNMARK)&&!this._isIntegrationPoint(n,t,R.HTML)))}_processToken(e){switch(e.type){case S.CHARACTER:this.onCharacter(e);break;case S.NULL_CHARACTER:this.onNullCharacter(e);break;case S.COMMENT:this.onComment(e);break;case S.DOCTYPE:this.onDoctype(e);break;case S.START_TAG:this._processStartTag(e);break;case S.END_TAG:this.onEndTag(e);break;case S.EOF:this.onEof(e);break;case S.WHITESPACE_CHARACTER:this.onWhitespaceCharacter(e)}}_isIntegrationPoint(e,t,n){let r=this.treeAdapter.getNamespaceURI(t),a=this.treeAdapter.getAttrList(t);return(!n||n===R.HTML)&&function(e,t,n){if(t===R.MATHML&&e===v.ANNOTATION_XML){for(let e=0;ee.type===D.Marker||this.openElements.contains(e.element)),n=t<0?e-1:t-1;for(let e=n;e>=0;e--){let t=this.activeFormattingElements.entries[e];this._insertElement(t.token,this.treeAdapter.getNamespaceURI(t.element)),t.element=this.openElements.current}}}_closeTableCell(){this.openElements.generateImpliedEndTags(),this.openElements.popUntilTableCellPopped(),this.activeFormattingElements.clearToLastMarker(),this.insertionMode=L.IN_ROW}_closePElement(){this.openElements.generateImpliedEndTagsWithExclusion(v.P),this.openElements.popUntilTagNamePopped(v.P)}_resetInsertionMode(){for(let e=this.openElements.stackTop;e>=0;e--)switch(0===e&&this.fragmentContext?this.fragmentContextID:this.openElements.tagIDs[e]){case v.TR:this.insertionMode=L.IN_ROW;return;case v.TBODY:case v.THEAD:case v.TFOOT:this.insertionMode=L.IN_TABLE_BODY;return;case v.CAPTION:this.insertionMode=L.IN_CAPTION;return;case v.COLGROUP:this.insertionMode=L.IN_COLUMN_GROUP;return;case v.TABLE:this.insertionMode=L.IN_TABLE;return;case v.BODY:this.insertionMode=L.IN_BODY;return;case v.FRAMESET:this.insertionMode=L.IN_FRAMESET;return;case v.SELECT:this._resetInsertionModeForSelect(e);return;case v.TEMPLATE:this.insertionMode=this.tmplInsertionModeStack[0];return;case v.HTML:this.insertionMode=this.headElement?L.AFTER_HEAD:L.BEFORE_HEAD;return;case v.TD:case v.TH:if(e>0){this.insertionMode=L.IN_CELL;return}break;case v.HEAD:if(e>0){this.insertionMode=L.IN_HEAD;return}}this.insertionMode=L.IN_BODY}_resetInsertionModeForSelect(e){if(e>0)for(let t=e-1;t>0;t--){let e=this.openElements.tagIDs[t];if(e===v.TEMPLATE)break;if(e===v.TABLE){this.insertionMode=L.IN_SELECT_IN_TABLE;return}}this.insertionMode=L.IN_SELECT}_isElementCausesFosterParenting(e){return ti.has(e)}_shouldFosterParentOnInsertion(){return this.fosterParentingEnabled&&this._isElementCausesFosterParenting(this.openElements.currentTagId)}_findFosterParentingLocation(){for(let e=this.openElements.stackTop;e>=0;e--){let t=this.openElements.items[e];switch(this.openElements.tagIDs[e]){case v.TEMPLATE:if(this.treeAdapter.getNamespaceURI(t)===R.HTML)return{parent:this.treeAdapter.getTemplateContent(t),beforeElement:null};break;case v.TABLE:{let n=this.treeAdapter.getParentNode(t);if(n)return{parent:n,beforeElement:t};return{parent:this.openElements.items[e-1],beforeElement:null}}}}return{parent:this.openElements.items[0],beforeElement:null}}_fosterParentElement(e){let t=this._findFosterParentingLocation();t.beforeElement?this.treeAdapter.insertBefore(t.parent,e,t.beforeElement):this.treeAdapter.appendChild(t.parent,e)}_isSpecialElement(e,t){return eC[this.treeAdapter.getNamespaceURI(e)].has(t)}onCharacter(e){if(this.skipNextNewLine=!1,this.tokenizer.inForeignNode){this._insertCharacters(e),this.framesetOk=!1;return}switch(this.insertionMode){case L.INITIAL:td(this,e);break;case L.BEFORE_HTML:tp(this,e);break;case L.BEFORE_HEAD:tm(this,e);break;case L.IN_HEAD:th(this,e);break;case L.IN_HEAD_NO_SCRIPT:tE(this,e);break;case L.AFTER_HEAD:tb(this,e);break;case L.IN_BODY:case L.IN_CAPTION:case L.IN_CELL:case L.IN_TEMPLATE:tA(this,e);break;case L.TEXT:case L.IN_SELECT:case L.IN_SELECT_IN_TABLE:this._insertCharacters(e);break;case L.IN_TABLE:case L.IN_TABLE_BODY:case L.IN_ROW:tv(this,e);break;case L.IN_TABLE_TEXT:tP(this,e);break;case L.IN_COLUMN_GROUP:tB(this,e);break;case L.AFTER_BODY:tq(this,e);break;case L.AFTER_AFTER_BODY:tK(this,e)}}onNullCharacter(e){if(this.skipNextNewLine=!1,this.tokenizer.inForeignNode){e.chars="�",this._insertCharacters(e);return}switch(this.insertionMode){case L.INITIAL:td(this,e);break;case L.BEFORE_HTML:tp(this,e);break;case L.BEFORE_HEAD:tm(this,e);break;case L.IN_HEAD:th(this,e);break;case L.IN_HEAD_NO_SCRIPT:tE(this,e);break;case L.AFTER_HEAD:tb(this,e);break;case L.TEXT:this._insertCharacters(e);break;case L.IN_TABLE:case L.IN_TABLE_BODY:case L.IN_ROW:tv(this,e);break;case L.IN_COLUMN_GROUP:tB(this,e);break;case L.AFTER_BODY:tq(this,e);break;case L.AFTER_AFTER_BODY:tK(this,e)}}onComment(e){if(this.skipNextNewLine=!1,this.currentNotInHTML){tc(this,e);return}switch(this.insertionMode){case L.INITIAL:case L.BEFORE_HTML:case L.BEFORE_HEAD:case L.IN_HEAD:case L.IN_HEAD_NO_SCRIPT:case L.AFTER_HEAD:case L.IN_BODY:case L.IN_TABLE:case L.IN_CAPTION:case L.IN_COLUMN_GROUP:case L.IN_TABLE_BODY:case L.IN_ROW:case L.IN_CELL:case L.IN_SELECT:case L.IN_SELECT_IN_TABLE:case L.IN_TEMPLATE:case L.IN_FRAMESET:case L.AFTER_FRAMESET:tc(this,e);break;case L.IN_TABLE_TEXT:tM(this,e);break;case L.AFTER_BODY:!function(e,t){e._appendCommentNode(t,e.openElements.items[0])}(this,e);break;case L.AFTER_AFTER_BODY:case L.AFTER_AFTER_FRAMESET:!function(e,t){e._appendCommentNode(t,e.document)}(this,e)}}onDoctype(e){switch(this.skipNextNewLine=!1,this.insertionMode){case L.INITIAL:!function(e,t){e._setDocumentType(t);let n=t.forceQuirks?k.QUIRKS:function(e){if(e.name!==eJ)return k.QUIRKS;let{systemId:t}=e;if(t&&"http://www.ibm.com/data/dtd/v11/ibmxhtml1-transitional.dtd"===t.toLowerCase())return k.QUIRKS;let{publicId:n}=e;if(null!==n){if(n=n.toLowerCase(),e2.has(n))return k.QUIRKS;let e=null===t?e1:e0;if(e5(n,e))return k.QUIRKS;if(e5(n,e=null===t?e3:e4))return k.LIMITED_QUIRKS}return k.NO_QUIRKS}(t);t.name===eJ&&null===t.publicId&&(null===t.systemId||"about:legacy-compat"===t.systemId)||e._err(t,T.nonConformingDoctype),e.treeAdapter.setDocumentMode(e.document,n),e.insertionMode=L.BEFORE_HTML}(this,e);break;case L.BEFORE_HEAD:case L.IN_HEAD:case L.IN_HEAD_NO_SCRIPT:case L.AFTER_HEAD:this._err(e,T.misplacedDoctype);break;case L.IN_TABLE_TEXT:tM(this,e)}}onStartTag(e){this.skipNextNewLine=!1,this.currentToken=e,this._processStartTag(e),e.selfClosing&&!e.ackSelfClosing&&this._err(e,T.nonVoidHtmlElementStartTagWithTrailingSolidus)}_processStartTag(e){this.shouldProcessStartTagTokenInForeignContent(e)?function(e,t){if(function(e){let t=e.tagID;return t===v.FONT&&e.attrs.some(({name:e})=>e===C.COLOR||e===C.SIZE||e===C.FACE)||te.has(t)}(t))tX(e),e._startTagOutsideForeignContent(t);else{let n=e._getAdjustedCurrentElement(),r=e.treeAdapter.getNamespaceURI(n);r===R.MATHML?tt(t):r===R.SVG&&(function(e){let t=e7.get(e.tagName);null!=t&&(e.tagName=t,e.tagID=eI(e.tagName))}(t),tn(t)),tr(t),t.selfClosing?e._appendElement(t,r):e._insertElement(t,r),t.ackSelfClosing=!0}}(this,e):this._startTagOutsideForeignContent(e)}_startTagOutsideForeignContent(e){switch(this.insertionMode){case L.INITIAL:td(this,e);break;case L.BEFORE_HTML:e.tagID===v.HTML?(this._insertElement(e,R.HTML),this.insertionMode=L.BEFORE_HEAD):tp(this,e);break;case L.BEFORE_HEAD:!function(e,t){switch(t.tagID){case v.HTML:tR(e,t);break;case v.HEAD:e._insertElement(t,R.HTML),e.headElement=e.openElements.current,e.insertionMode=L.IN_HEAD;break;default:tm(e,t)}}(this,e);break;case L.IN_HEAD:tf(this,e);break;case L.IN_HEAD_NO_SCRIPT:!function(e,t){switch(t.tagID){case v.HTML:tR(e,t);break;case v.BASEFONT:case v.BGSOUND:case v.HEAD:case v.LINK:case v.META:case v.NOFRAMES:case v.STYLE:tf(e,t);break;case v.NOSCRIPT:e._err(t,T.nestedNoscriptInHead);break;default:tE(e,t)}}(this,e);break;case L.AFTER_HEAD:!function(e,t){switch(t.tagID){case v.HTML:tR(e,t);break;case v.BODY:e._insertElement(t,R.HTML),e.framesetOk=!1,e.insertionMode=L.IN_BODY;break;case v.FRAMESET:e._insertElement(t,R.HTML),e.insertionMode=L.IN_FRAMESET;break;case v.BASE:case v.BASEFONT:case v.BGSOUND:case v.LINK:case v.META:case v.NOFRAMES:case v.SCRIPT:case v.STYLE:case v.TEMPLATE:case v.TITLE:e._err(t,T.abandonedHeadElementChild),e.openElements.push(e.headElement,v.HEAD),tf(e,t),e.openElements.remove(e.headElement);break;case v.HEAD:e._err(t,T.misplacedStartTagForHeadElement);break;default:tb(e,t)}}(this,e);break;case L.IN_BODY:tR(this,e);break;case L.IN_TABLE:tw(this,e);break;case L.IN_TABLE_TEXT:tM(this,e);break;case L.IN_CAPTION:!function(e,t){let n=t.tagID;tF.has(n)?e.openElements.hasInTableScope(v.CAPTION)&&(e.openElements.generateImpliedEndTags(),e.openElements.popUntilTagNamePopped(v.CAPTION),e.activeFormattingElements.clearToLastMarker(),e.insertionMode=L.IN_TABLE,tw(e,t)):tR(e,t)}(this,e);break;case L.IN_COLUMN_GROUP:tU(this,e);break;case L.IN_TABLE_BODY:tH(this,e);break;case L.IN_ROW:tz(this,e);break;case L.IN_CELL:!function(e,t){let n=t.tagID;tF.has(n)?(e.openElements.hasInTableScope(v.TD)||e.openElements.hasInTableScope(v.TH))&&(e._closeTableCell(),tz(e,t)):tR(e,t)}(this,e);break;case L.IN_SELECT:tj(this,e);break;case L.IN_SELECT_IN_TABLE:!function(e,t){let n=t.tagID;n===v.CAPTION||n===v.TABLE||n===v.TBODY||n===v.TFOOT||n===v.THEAD||n===v.TR||n===v.TD||n===v.TH?(e.openElements.popUntilTagNamePopped(v.SELECT),e._resetInsertionMode(),e._processStartTag(t)):tj(e,t)}(this,e);break;case L.IN_TEMPLATE:!function(e,t){switch(t.tagID){case v.BASE:case v.BASEFONT:case v.BGSOUND:case v.LINK:case v.META:case v.NOFRAMES:case v.SCRIPT:case v.STYLE:case v.TEMPLATE:case v.TITLE:tf(e,t);break;case v.CAPTION:case v.COLGROUP:case v.TBODY:case v.TFOOT:case v.THEAD:e.tmplInsertionModeStack[0]=L.IN_TABLE,e.insertionMode=L.IN_TABLE,tw(e,t);break;case v.COL:e.tmplInsertionModeStack[0]=L.IN_COLUMN_GROUP,e.insertionMode=L.IN_COLUMN_GROUP,tU(e,t);break;case v.TR:e.tmplInsertionModeStack[0]=L.IN_TABLE_BODY,e.insertionMode=L.IN_TABLE_BODY,tH(e,t);break;case v.TD:case v.TH:e.tmplInsertionModeStack[0]=L.IN_ROW,e.insertionMode=L.IN_ROW,tz(e,t);break;default:e.tmplInsertionModeStack[0]=L.IN_BODY,e.insertionMode=L.IN_BODY,tR(e,t)}}(this,e);break;case L.AFTER_BODY:e.tagID===v.HTML?tR(this,e):tq(this,e);break;case L.IN_FRAMESET:!function(e,t){switch(t.tagID){case v.HTML:tR(e,t);break;case v.FRAMESET:e._insertElement(t,R.HTML);break;case v.FRAME:e._appendElement(t,R.HTML),t.ackSelfClosing=!0;break;case v.NOFRAMES:tf(e,t)}}(this,e);break;case L.AFTER_FRAMESET:!function(e,t){switch(t.tagID){case v.HTML:tR(e,t);break;case v.NOFRAMES:tf(e,t)}}(this,e);break;case L.AFTER_AFTER_BODY:e.tagID===v.HTML?tR(this,e):tK(this,e);break;case L.AFTER_AFTER_FRAMESET:!function(e,t){switch(t.tagID){case v.HTML:tR(e,t);break;case v.NOFRAMES:tf(e,t)}}(this,e)}}onEndTag(e){this.skipNextNewLine=!1,this.currentToken=e,this.currentNotInHTML?function(e,t){if(t.tagID===v.P||t.tagID===v.BR){tX(e),e._endTagOutsideForeignContent(t);return}for(let n=e.openElements.stackTop;n>0;n--){let r=e.openElements.items[n];if(e.treeAdapter.getNamespaceURI(r)===R.HTML){e._endTagOutsideForeignContent(t);break}let a=e.treeAdapter.getTagName(r);if(a.toLowerCase()===t.tagName){t.tagName=a,e.openElements.shortenToLength(n);break}}}(this,e):this._endTagOutsideForeignContent(e)}_endTagOutsideForeignContent(e){var t;switch(this.insertionMode){case L.INITIAL:td(this,e);break;case L.BEFORE_HTML:!function(e,t){let n=t.tagID;(n===v.HTML||n===v.HEAD||n===v.BODY||n===v.BR)&&tp(e,t)}(this,e);break;case L.BEFORE_HEAD:!function(e,t){let n=t.tagID;n===v.HEAD||n===v.BODY||n===v.HTML||n===v.BR?tm(e,t):e._err(t,T.endTagWithoutMatchingOpenElement)}(this,e);break;case L.IN_HEAD:!function(e,t){switch(t.tagID){case v.HEAD:e.openElements.pop(),e.insertionMode=L.AFTER_HEAD;break;case v.BODY:case v.BR:case v.HTML:th(e,t);break;case v.TEMPLATE:tg(e,t);break;default:e._err(t,T.endTagWithoutMatchingOpenElement)}}(this,e);break;case L.IN_HEAD_NO_SCRIPT:!function(e,t){switch(t.tagID){case v.NOSCRIPT:e.openElements.pop(),e.insertionMode=L.IN_HEAD;break;case v.BR:tE(e,t);break;default:e._err(t,T.endTagWithoutMatchingOpenElement)}}(this,e);break;case L.AFTER_HEAD:!function(e,t){switch(t.tagID){case v.BODY:case v.HTML:case v.BR:tb(e,t);break;case v.TEMPLATE:tg(e,t);break;default:e._err(t,T.endTagWithoutMatchingOpenElement)}}(this,e);break;case L.IN_BODY:tk(this,e);break;case L.TEXT:e.tagID===v.SCRIPT&&(null===(t=this.scriptHandler)||void 0===t||t.call(this,this.openElements.current)),this.openElements.pop(),this.insertionMode=this.originalInsertionMode;break;case L.IN_TABLE:tD(this,e);break;case L.IN_TABLE_TEXT:tM(this,e);break;case L.IN_CAPTION:!function(e,t){let n=t.tagID;switch(n){case v.CAPTION:case v.TABLE:e.openElements.hasInTableScope(v.CAPTION)&&(e.openElements.generateImpliedEndTags(),e.openElements.popUntilTagNamePopped(v.CAPTION),e.activeFormattingElements.clearToLastMarker(),e.insertionMode=L.IN_TABLE,n===v.TABLE&&tD(e,t));break;case v.BODY:case v.COL:case v.COLGROUP:case v.HTML:case v.TBODY:case v.TD:case v.TFOOT:case v.TH:case v.THEAD:case v.TR:break;default:tk(e,t)}}(this,e);break;case L.IN_COLUMN_GROUP:!function(e,t){switch(t.tagID){case v.COLGROUP:e.openElements.currentTagId===v.COLGROUP&&(e.openElements.pop(),e.insertionMode=L.IN_TABLE);break;case v.TEMPLATE:tg(e,t);break;case v.COL:break;default:tB(e,t)}}(this,e);break;case L.IN_TABLE_BODY:tG(this,e);break;case L.IN_ROW:t$(this,e);break;case L.IN_CELL:!function(e,t){let n=t.tagID;switch(n){case v.TD:case v.TH:e.openElements.hasInTableScope(n)&&(e.openElements.generateImpliedEndTags(),e.openElements.popUntilTagNamePopped(n),e.activeFormattingElements.clearToLastMarker(),e.insertionMode=L.IN_ROW);break;case v.TABLE:case v.TBODY:case v.TFOOT:case v.THEAD:case v.TR:e.openElements.hasInTableScope(n)&&(e._closeTableCell(),t$(e,t));break;case v.BODY:case v.CAPTION:case v.COL:case v.COLGROUP:case v.HTML:break;default:tk(e,t)}}(this,e);break;case L.IN_SELECT:tV(this,e);break;case L.IN_SELECT_IN_TABLE:!function(e,t){let n=t.tagID;n===v.CAPTION||n===v.TABLE||n===v.TBODY||n===v.TFOOT||n===v.THEAD||n===v.TR||n===v.TD||n===v.TH?e.openElements.hasInTableScope(n)&&(e.openElements.popUntilTagNamePopped(v.SELECT),e._resetInsertionMode(),e.onEndTag(t)):tV(e,t)}(this,e);break;case L.IN_TEMPLATE:e.tagID===v.TEMPLATE&&tg(this,e);break;case L.AFTER_BODY:tW(this,e);break;case L.IN_FRAMESET:e.tagID!==v.FRAMESET||this.openElements.isRootHtmlElementCurrent()||(this.openElements.pop(),this.fragmentContext||this.openElements.currentTagId===v.FRAMESET||(this.insertionMode=L.AFTER_FRAMESET));break;case L.AFTER_FRAMESET:e.tagID===v.HTML&&(this.insertionMode=L.AFTER_AFTER_FRAMESET);break;case L.AFTER_AFTER_BODY:tK(this,e)}}onEof(e){switch(this.insertionMode){case L.INITIAL:td(this,e);break;case L.BEFORE_HTML:tp(this,e);break;case L.BEFORE_HEAD:tm(this,e);break;case L.IN_HEAD:th(this,e);break;case L.IN_HEAD_NO_SCRIPT:tE(this,e);break;case L.AFTER_HEAD:tb(this,e);break;case L.IN_BODY:case L.IN_TABLE:case L.IN_CAPTION:case L.IN_COLUMN_GROUP:case L.IN_TABLE_BODY:case L.IN_ROW:case L.IN_CELL:case L.IN_SELECT:case L.IN_SELECT_IN_TABLE:tO(this,e);break;case L.TEXT:this._err(e,T.eofInElementThatCanContainOnlyText),this.openElements.pop(),this.insertionMode=this.originalInsertionMode,this.onEof(e);break;case L.IN_TABLE_TEXT:tM(this,e);break;case L.IN_TEMPLATE:tY(this,e);break;case L.AFTER_BODY:case L.IN_FRAMESET:case L.AFTER_FRAMESET:case L.AFTER_AFTER_BODY:case L.AFTER_AFTER_FRAMESET:tu(this,e)}}onWhitespaceCharacter(e){if(this.skipNextNewLine&&(this.skipNextNewLine=!1,e.chars.charCodeAt(0)===b.LINE_FEED)){if(1===e.chars.length)return;e.chars=e.chars.substr(1)}if(this.tokenizer.inForeignNode){this._insertCharacters(e);return}switch(this.insertionMode){case L.IN_HEAD:case L.IN_HEAD_NO_SCRIPT:case L.AFTER_HEAD:case L.TEXT:case L.IN_COLUMN_GROUP:case L.IN_SELECT:case L.IN_SELECT_IN_TABLE:case L.IN_FRAMESET:case L.AFTER_FRAMESET:this._insertCharacters(e);break;case L.IN_BODY:case L.IN_CAPTION:case L.IN_CELL:case L.IN_TEMPLATE:case L.AFTER_BODY:case L.AFTER_AFTER_BODY:case L.AFTER_AFTER_FRAMESET:tS(this,e);break;case L.IN_TABLE:case L.IN_TABLE_BODY:case L.IN_ROW:tv(this,e);break;case L.IN_TABLE_TEXT:tx(this,e)}}}function tl(e,t){for(let n=0;n<8;n++){let n=function(e,t){let 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