mirror of
https://github.com/bentoml/OpenLLM.git
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119 lines
4.3 KiB
Python
Executable File
119 lines
4.3 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright 2023 BentoML Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import annotations
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import os
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import typing as t
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import inflection
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import tomlkit
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import openllm
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START_COMMENT = f"<!-- {os.path.basename(__file__)}: start -->\n"
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END_COMMENT = f"<!-- {os.path.basename(__file__)}: stop -->\n"
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ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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def main() -> int:
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with open(os.path.join(ROOT, "pyproject.toml"), "r") as f:
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deps = tomlkit.parse(f.read()).value["project"]["optional-dependencies"]
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with open(os.path.join(ROOT, "README.md"), "r") as f:
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readme = f.readlines()
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start_index, stop_index = readme.index(START_COMMENT), readme.index(END_COMMENT)
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formatted: dict[
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t.Literal["Model", "Architecture", "CPU", "GPU", "URL", "Installation", "Model Ids"], list[str | list[str]]
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] = {
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"Model": [],
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"Architecture": [],
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"URL": [],
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"CPU": [],
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"GPU": [],
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"Model Ids": [],
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"Installation": [],
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}
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max_install_len_div = 0
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for name, config_cls in openllm.CONFIG_MAPPING.items():
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dashed = inflection.dasherize(name)
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formatted["Model"].append(dashed)
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formatted["Architecture"].append(config_cls.__openllm_architecture__)
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formatted["URL"].append(config_cls.__openllm_url__)
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formatted["GPU"].append("✅")
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formatted["CPU"].append("✅" if not config_cls.__openllm_requires_gpu__ else "❌")
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formatted["Model Ids"].append(config_cls.__openllm_model_ids__)
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if dashed in deps:
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instruction = f'```bash\npip install "openllm[{dashed}]"\n```'
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else:
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instruction = "```bash\npip install openllm\n```"
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if len(instruction) > max_install_len_div:
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max_install_len_div = len(instruction)
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formatted["Installation"].append(instruction)
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meta: list[str] = ["\n", "<table align='center'>\n"]
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# NOTE: headers
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meta += ["<tr>\n"]
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meta.extend([f"<th>{header}</th>\n" for header in formatted.keys() if header not in ("URL",)])
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meta += ["</tr>\n"]
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# NOTE: rows
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for name, architecture, url, cpu, gpu, model_ids, installation in t.cast(
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t.Iterable[t.Tuple[str, str, str, str, str, t.List[str], str]], zip(*formatted.values())
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):
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meta += "<tr>\n"
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# configure architecture URL
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cfg_cls = openllm.CONFIG_MAPPING[name]
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if cfg_cls.__openllm_trust_remote_code__:
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arch = f"<td><a href={url}><code>{architecture}</code></a></td>\n"
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else:
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model_name = {
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"dolly_v2": "gpt_neox",
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"stablelm": "gpt_neox",
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"starcoder": "gpt_bigcode",
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"flan_t5": "t5",
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}.get(cfg_cls.__openllm_model_name__, cfg_cls.__openllm_model_name__)
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arch = f"<td><a href=https://huggingface.co/docs/transformers/main/model_doc/{model_name}#transformers.{architecture}><code>{architecture}</code></a></td>\n"
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meta.extend(
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[
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f"\n<td><a href={url}>{name}</a></td>\n",
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arch,
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f"<td>{cpu}</td>\n",
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f"<td>{gpu}</td>\n",
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]
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)
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format_with_links: list[str] = []
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for lid in model_ids:
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format_with_links.append(f"<li><a href=https://huggingface.co/{lid}><code>{lid}</code></a></li>")
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meta.append("<td>\n\n<ul>" + "\n".join(format_with_links) + "</ul>\n\n</td>\n")
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meta.append(f"<td>\n\n{installation}\n\n</td>\n")
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meta += "</tr>\n"
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meta.extend(["</table>\n", "\n"])
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readme = readme[:start_index] + [START_COMMENT] + meta + [END_COMMENT] + readme[stop_index + 1 :]
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with open(os.path.join(ROOT, "README.md"), "w") as f:
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f.writelines(readme)
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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