chore: upgrade to new vLLM schema

Signed-off-by: paperspace <29749331+aarnphm@users.noreply.github.com>
This commit is contained in:
paperspace
2024-06-02 15:52:45 +00:00
parent 2e7592cd45
commit a93da12084
90 changed files with 34 additions and 1391 deletions

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@@ -7,9 +7,6 @@ charset = utf-8
indent_style = space indent_style = space
indent_size = 2 indent_size = 2
[openllm-client/src/openllm_client/pb/v1/*]
indent_size = unset
[/node_modules/*] [/node_modules/*]
indent_size = unset indent_size = unset
indent_style = unset indent_style = unset

1
.gitattributes vendored
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@@ -3,7 +3,6 @@
*_pb2*.pyi linguist-generated=true *_pb2*.pyi linguist-generated=true
# Python sdk # Python sdk
openllm-python/tests/models/__snapshots__/* linguist-generated=true
openllm-python/README.md linguist-generated=true openllm-python/README.md linguist-generated=true
openllm-python/CHANGELOG.md linguist-generated=true openllm-python/CHANGELOG.md linguist-generated=true
openllm-core/src/openllm_core/config/__init__.py linguist-generated=true openllm-core/src/openllm_core/config/__init__.py linguist-generated=true

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@@ -7,7 +7,6 @@ on:
branches: [main] branches: [main]
paths-ignore: paths-ignore:
- '*.md' - '*.md'
- 'docs/**'
- 'changelog.d/**' - 'changelog.d/**'
- 'assets/**' - 'assets/**'
- 'openllm-node/**' - 'openllm-node/**'
@@ -16,7 +15,6 @@ on:
branches: [main] branches: [main]
paths-ignore: paths-ignore:
- '*.md' - '*.md'
- 'docs/**'
- 'changelog.d/**' - 'changelog.d/**'
- 'assets/**' - 'assets/**'
- 'openllm-node/**' - 'openllm-node/**'

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@@ -18,18 +18,12 @@ on:
push: push:
branches: [main] branches: [main]
paths-ignore: paths-ignore:
- 'docs/**'
- 'bazel/**'
- 'typings/**'
- '*.md' - '*.md'
- 'changelog.d/**' - 'changelog.d/**'
- 'assets/**' - 'assets/**'
pull_request: pull_request:
branches: [main] branches: [main]
paths-ignore: paths-ignore:
- 'docs/**'
- 'bazel/**'
- 'typings/**'
- '*.md' - '*.md'
- 'changelog.d/**' - 'changelog.d/**'
- 'assets/**' - 'assets/**'

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@@ -760,11 +760,8 @@ Quantization is a technique to reduce the storage and computation requirements f
OpenLLM supports the following quantization techniques OpenLLM supports the following quantization techniques
- [LLM.int8(): 8-bit Matrix Multiplication](https://arxiv.org/abs/2208.07339) through [bitsandbytes](https://github.com/TimDettmers/bitsandbytes) - [AWQ: Activation-aware Weight Quantization](https://arxiv.org/abs/2306.00978).
- [SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression - [GPTQ: Accurate Post-Training Quantization](https://arxiv.org/abs/2210.17323).
](https://arxiv.org/abs/2306.03078) through [bitsandbytes](https://github.com/TimDettmers/bitsandbytes)
- [AWQ: Activation-aware Weight Quantization](https://arxiv.org/abs/2306.00978),
- [GPTQ: Accurate Post-Training Quantization](https://arxiv.org/abs/2210.17323)
- [SqueezeLLM: Dense-and-Sparse Quantization](https://arxiv.org/abs/2306.07629). - [SqueezeLLM: Dense-and-Sparse Quantization](https://arxiv.org/abs/2306.07629).
> [!NOTE] > [!NOTE]
@@ -816,10 +813,21 @@ from llama_index.llms.openllm import OpenLLMAPI
Spin up an OpenLLM server, and connect to it by specifying its URL: Spin up an OpenLLM server, and connect to it by specifying its URL:
```python ```python
from langchain.llms import OpenLLM from langchain.llms import OpenLLMAPI
llm = OpenLLM(server_url='http://44.23.123.1:3000', server_type='http') llm = OpenLLMAPI(server_url='http://44.23.123.1:3000')
llm('What is the difference between a duck and a goose? And why there are so many Goose in Canada?') llm.invoke('What is the difference between a duck and a goose? And why there are so many Goose in Canada?')
# streaming
for it in llm.stream('What is the difference between a duck and a goose? And why there are so many Goose in Canada?'):
print(it, flush=True, end='')
# async context
await llm.ainvoke('What is the difference between a duck and a goose? And why there are so many Goose in Canada?')
# async streaming
async for it in llm.astream('What is the difference between a duck and a goose? And why there are so many Goose in Canada?'):
print(it, flush=True, end='')
``` ```
<!-- hatch-fancy-pypi-readme interim stop --> <!-- hatch-fancy-pypi-readme interim stop -->

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@@ -1,105 +0,0 @@
const TAILWIND_CONFIG = {
extends: ['plugin:tailwindcss/recommended'],
rules: {
'tailwindcss/classnames-order': 'off', // conflicts with prettier-plugin-tailwindcss
'tailwindcss/enforces-negative-arbitrary-values': 'error',
'tailwindcss/enforces-shorthand': 'error',
'tailwindcss/migration-from-tailwind-2': 'error',
'tailwindcss/no-custom-classname': 'error'
}
}
/** @type {import('eslint').Linter.Config} */
module.exports = {
root: true,
reportUnusedDisableDirectives: true,
ignorePatterns: ['next-env.d.ts'],
overrides: [
// Rules for all files
{
files: '**/*.{js,jsx,cjs,mjs,ts,tsx,cts,mts}',
extends: ['eslint:recommended', 'plugin:@typescript-eslint/recommended', 'plugin:import/typescript', 'prettier'],
plugins: ['import', 'unicorn'],
rules: {
'prefer-object-has-own': 'error',
'logical-assignment-operators': ['error', 'always', { enforceForIfStatements: true }],
'no-else-return': ['error', { allowElseIf: false }],
'no-lonely-if': 'error',
'prefer-destructuring': ['error', { VariableDeclarator: { object: true } }],
'import/no-duplicates': 'error',
'no-negated-condition': 'off',
'unicorn/no-negated-condition': 'error',
'prefer-regex-literals': ['error', { disallowRedundantWrapping: true }],
'object-shorthand': ['error', 'always'],
'unicorn/prefer-regexp-test': 'error',
'unicorn/no-array-for-each': 'error',
'@typescript-eslint/prefer-for-of': 'error',
// todo: enable
'@typescript-eslint/no-explicit-any': 'off',
'@typescript-eslint/no-non-null-assertion': 'off',
'@typescript-eslint/no-var-requires': 'off',
'@typescript-eslint/ban-ts-comment': 'off'
}
},
// Rules for React files
{
files: '{docs}/**',
extends: ['plugin:react/recommended', 'plugin:react/jsx-runtime', 'plugin:react-hooks/recommended', 'plugin:@next/next/recommended'],
rules: {
'react/prop-types': 'off',
'react/no-unknown-property': ['error', { ignore: ['jsx'] }],
'react-hooks/exhaustive-deps': 'error',
'react/self-closing-comp': 'error',
'no-restricted-syntax': [
'error',
{
// ❌ useMemo(…, [])
selector: 'CallExpression[callee.name=useMemo][arguments.1.type=ArrayExpression][arguments.1.elements.length=0]',
message: "`useMemo` with an empty dependency array can't provide a stable reference, use `useRef` instead."
},
{
// ❌ z.object(…)
selector: 'MemberExpression[object.name=z] > .property[name=object]',
message: 'Use z.strictObject is more safe.'
}
],
'react/jsx-filename-extension': ['error', { extensions: ['.tsx', '.jsx'], allow: 'as-needed' }],
'react/jsx-curly-brace-presence': 'error',
'react/jsx-boolean-value': 'error'
},
settings: {
react: { version: 'detect' }
}
},
// Rules for TypeScript files
{
files: '**/*.{ts,tsx,cts,mts}',
extends: [
// TODO: fix errors
// 'plugin:@typescript-eslint/recommended-requiring-type-checking'
],
parserOptions: {
project: ['docs/tsconfig.json', 'tsconfig.json']
},
rules: {
'@typescript-eslint/no-unnecessary-type-assertion': 'error',
'@typescript-eslint/consistent-type-imports': 'error',
'@typescript-eslint/non-nullable-type-assertion-style': 'error',
'@typescript-eslint/prefer-optional-chain': 'error'
}
},
// ⚙️ Docs
{
...TAILWIND_CONFIG,
files: 'docs/**',
settings: {
tailwindcss: {
config: 'docs/tailwind.config.js',
callees: ['cn'],
whitelist: ['dash-ring', 'theme-1', 'theme-2', 'theme-3', 'theme-4']
},
next: { rootDir: 'docs' }
}
}
]
}

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@@ -1,9 +0,0 @@
# OpenLLM Documentation
Powered by [Nextra](https://nextra.site)
## Development
```bash
pnpm i && pnpm dev
```

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@@ -1,30 +0,0 @@
import { ArrowRightIcon } from '@components/icons'
import cn from 'clsx'
import { motion } from 'framer-motion'
import Link from 'next/link'
import type { ReactNode } from 'react'
import styles from './style.module.css'
export function Feature({ large, centered, children, lightOnly, className, href, index, ...props }) {
return (
<motion.div
initial={{ opacity: 0 }}
whileInView={{ opacity: 1 }}
viewport={{ once: true, margin: '-20px' }}
transition={{ duration: Math.min(0.25 + index * 0.2, 0.8) }}
className={cn(styles.feature, large && styles.large, centered && styles.centered, lightOnly && styles['light-only'], className)}
{...props}
>
{children}
{href ? (
<Link className={styles.link} href={href} target="_blank">
<ArrowRightIcon width="1.5em" />
</Link>
) : null}
</motion.div>
)
}
export function Features({ children }: { children: ReactNode }) {
return <div className={styles.features}>{children}</div>
}

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@@ -1,135 +0,0 @@
.feature {
position: relative;
padding: 1.5rem 1.75rem;
color: #000;
background-color: white;
overflow: hidden;
border-radius: 1.78em;
}
.feature.large {
grid-column: span 2;
}
.feature.centered {
text-align: center;
}
.feature h3 {
position: relative;
font-size: 34px;
font-size: min(34px, max(4vw, 24px));
font-weight: 600;
line-height: 1.25;
letter-spacing: -0.02rem;
z-index: 2;
}
:global(.dark) .feature:not(.light-only) {
color: #fff;
background-color: #202020;
}
.feature {
box-shadow:
0 8px 16px rgb(0 0 0 / 8%),
0 1px 2px rgb(0 0 0 / 4%),
0 0 0 1px rgb(0 0 0 / 3%);
transition: box-shadow 0.3s ease;
}
:global(.dark) .feature {
box-shadow: 0 0 0 1px rgb(82 82 82 / 60%);
}
.feature .link {
position: absolute;
right: 1em;
bottom: 1em;
z-index: 2;
width: 2.5em;
height: 2.5em;
background-color: rgb(0 0 0 / 39%);
backdrop-filter: blur(10px);
border-radius: 50%;
display: flex;
justify-content: center;
align-items: center;
color: rgba(255, 255, 255, 0.9);
box-shadow:
0 0 0 2px rgb(154 154 154 / 56%),
0 0 30px rgb(0 0 0 / 10%);
transition: all 0.2s ease;
-webkit-user-drag: none;
}
@media (hover: hover) {
.feature .link {
opacity: 0;
}
.feature:hover .link {
opacity: 1;
}
.feature .link:hover {
transform: scale(1.05);
color: rgba(255, 255, 255, 1);
background-color: rgba(64, 64, 64, 0.39);
box-shadow:
0 0 0 2px rgba(220, 220, 220, 0.56),
0 0 30px rgb(0 0 0 / 10%);
}
.feature .link:active {
transform: scale(1);
color: rgba(255, 255, 255, 0.8);
background-color: rgba(22, 22, 22, 0.39);
box-shadow:
0 0 0 2px rgba(178, 178, 178, 0.56),
0 0 30px rgb(0 0 0 / 10%);
}
}
.features {
display: grid;
grid-template-columns: repeat(3, 1fr);
grid-gap: 2em;
font-feature-settings: initial;
}
.feature :global(.show-on-mobile) {
display: none;
}
@media screen and (max-width: 1024px) {
.feature {
max-width: 80vw;
width: 100%;
}
.feature.large {
grid-column: span 1;
}
.features {
grid-template-columns: 1fr;
grid-gap: 3em;
justify-items: center;
}
.feature h3 {
font-size: 28px;
font-size: min(28px, max(4vw, 22px));
text-align: center;
}
}
@media screen and (max-width: 640px) {
.feature {
max-width: 460px;
width: 100%;
}
.feature.large {
grid-column: span 1;
}
.features {
grid-template-columns: 1fr;
grid-gap: 3em;
justify-items: center;
}
.feature h3 {
font-size: 34px;
font-size: min(34px, max(4vw, 22px));
text-align: center;
}
.feature :global(.show-on-mobile) {
display: block;
}
}

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fill="none"
viewBox="0 0 24 24"
stroke-width="1.5"
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clip-rule="evenodd"
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export { default as FilesIcon } from './files.svg'
export { default as MarkdownIcon } from './markdown.svg'
export { default as TailwindIcon } from './tailwind.svg'
export { default as LinkIcon } from './link.svg'
export { default as LightningIcon } from './lightning.svg'
export { default as GlobeIcon } from './globe.svg'
export { default as PictureIcon } from './picture.svg'
export { default as CodeIcon } from './code.svg'
export { default as BrushIcon } from './brush.svg'
export { default as DropperIcon } from './dropper.svg'
export { default as StarsIcon } from './stars.svg'
export { default as FormulaIcon } from './formula.svg'
export { default as WarningIcon } from './warning.svg'
export { default as ChevronRightIcon } from './chevron-right.svg'
export { default as BoxIcon } from './box.svg'
export { default as GearIcon } from './gear.svg'
export { default as RowsIcon } from './rows.svg'
export { default as CardsIcon } from './cards.svg'
export { default as OneIcon } from './one.svg'
export { default as CloudIcon } from './cloud.svg'
export { default as TableIcon } from './table.svg'
export { default as FileIcon } from './file.svg'
export { default as NewsletterIcon } from './newsletter.svg'
export { default as ArrowRightIcon } from './arrow-right.svg'
export { default as SwitchIcon } from './switch.svg'
export { default as TerminalIcon } from './terminal.svg'
export { default as DiagramIcon } from './diagram.svg'
export { default as FolderTreeIcon } from './folder-tree.svg'
export { default as IdCardIcon } from './id-card.svg'

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points="80 96 120 128 80 160"
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@tailwind base;
@tailwind components;
@tailwind utilities;
body {
font-feature-settings:
'rlig' 1,
'calt' 1,
'kern' 1;
}
.home-content p {
margin-top: 1.5em;
line-height: 1.75em;
}
.home-content a {
--tw-ring-color: hsl(var(--nextra-primary-hue) 100% 50%/0.3);
--tw-text-opacity: 1;
text-underline-position: under;
text-decoration-line: underline;
text-decoration-thickness: from-font;
color: hsl(var(--nextra-primary-hue) 100% 50% / var(--tw-text-opacity));
}
figcaption {
font-size: 0.85rem;
line-height: 1.5rem;
display: block;
text-align: center;
margin-top: 0.5rem;
}
code.text-\[\.9em\] {
font-size: 14px;
}
@media screen and (max-width: 1200px) {
.home-content .hide-medium {
display: none;
}
}
@media screen and (max-width: 720px) {
.home-content p {
font-size: 0.9rem;
}
.home-content .hide-small {
display: none;
}
}

5
docs/next-env.d.ts vendored
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/// <reference types="next" />
/// <reference types="next/image-types/global" />
// NOTE: This file should not be edited
// see https://nextjs.org/docs/basic-features/typescript for more information.

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import nextra from 'nextra'
const withNextra = nextra({
theme: 'nextra-theme-docs',
themeConfig: './theme.config.tsx',
latex: true,
defaultShowCopyCode: true
})
export default withNextra({
reactStrictMode: true,
webpack(config) {
const allowedSvgRegex = /components\/icons\/.+\.svg$/
const fileLoaderRule = config.module.rules.find((rule) => rule.test?.test('.svg'))
fileLoaderRule.exclude = allowedSvgRegex
config.module.rules.push({
test: allowedSvgRegex,
use: ['@svgr/webpack']
})
return config
}
})

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{
"name": "@bentoml/openllm-docs",
"description": "📚 OpenLLM Documentation",
"license": "Apache-2.0",
"private": true,
"scripts": {
"dev": "next dev",
"build": "next build",
"start": "next start"
},
"repository": {
"type": "git",
"url": "git+https://github.com/bentoml/OpenLLM.git"
},
"author": "Aaron Pham <aarnphm@bentoml.com>",
"bugs": {
"url": "https://github.com/bentoml/OpenLLM/issues"
},
"homepage": "https://github.com/bentoml/OpenLLM#readme",
"dependencies": {
"@mdx-js/react": "*",
"@vercel/analytics": "*",
"@vercel/og": "0.5.20",
"clsx": "^2.0.0",
"next": "*",
"next-themes": "^0.2.1",
"nextra": "2.13.2",
"nextra-theme-docs": "2.13.2",
"react": "*",
"react-dom": "*"
},
"devDependencies": {
"@svgr/webpack": "*",
"@types/dedent": "^0.7.1",
"@types/node": "*",
"@types/react": "*",
"@types/react-dom": "*",
"autoprefixer": "^10.4.16",
"eslint": "*",
"postcss": "^8.4.31",
"tailwindcss": "^3.3.3",
"typescript": "*"
}
}

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import { NotFoundPage } from 'nextra-theme-docs'
# 404: Oops, page not found
<NotFoundPage />

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import '../globals.css'
export default function App({ Component, pageProps }) {
return <Component {...pageProps} />
}

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{
"index": {
"type": "page",
"title": "Introduction",
"display": "hidden"
},
"docs": {
"type": "page",
"title": "Documentation"
},
"about": {
"type": "page",
"title": "About",
"theme": {
"typesetting": "article"
}
},
"changelog": {
"type": "page",
"title": "Changelog",
"href": "https://github.com/bentoml/OpenLLM/blob/main/CHANGELOG.md",
"newWindow": true
},
"404": {
"type": "page",
"theme": {
"timestamp": false,
"typesetting": "article"
}
}
}

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# About
OpenLLM was started at [BentoML](https://bentoml.com) to provide a simple
and easy to use interface for serving and deploying large language models (LLMs)
in production. With OpenLLM, you can run inference with any open-source LLMs, deploy models to the
cloud or on-premises, and build powerful AI applications. It supports a wide range of open-source LLMs and
offers flexible APIs with first-class support for BentoML and LangChain.
## Team
The project is currently maintained by [Aaron Pham](https://twitter.com/aarnphm_). You can check out
the full list of contributors on [GitHub](https://github.com/bentoml/OpenLLM/graphs/contributors).
## Credits
OpenLLM is powered by these incredible open-source projects:
- https://bentoml.com/
- https://huggingface.co/docs/transformers/index
- https://github.com/PanQiWei/AutoGPTQ
- https://github.com/huggingface/peft
The documentation is powered by [Nextra](https://nextra.site/).
## Design assets
Feel free to use any of the assets in your project. But please modify
the logo and don't use these logo to represent your product or project.
| Name | Description | Preview |
| :---------: | :----------------------------------------------: | :-----------------------------------: |
| Icon | Useful for favicons, app icons, link icons, etc. | ![OpenLLM icon](/favicon/favicon.svg) |
| Logo | Full OpenLLM logo | ![OpenLLM logo](/logo.svg) |
| Social Card | The OpenLLM social card | ![OpenLLM card](/og.png) |
## License
The OpenLLM project is licensed under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0)

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Fine-tune, serve and deploy LLMs in production.
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{
"index": "Introduction",
"installation": "Installation",
"getting-started": "Getting Started",
"about-link": {
"title": "About OpenLLM",
"href": "/about"
},
"-- Models": {
"type": "separator",
"title": "Supported Models"
},
"supported-models": "Supported Models",
"add-new-model": "Adding a New Model",
"-- Advanced": {
"type": "separator",
"title": "Advanced"
},
"features": {
"display": "hidden",
"title": "Features"
},
"-- API Reference": {
"type": "separator",
"title": "API Reference"
},
"api": {
"display": "hidden"
},
"-- Ecosystem": {
"type": "separator",
"title": "More"
},
"bentocloud": {
"title": "☁️ BentoCloud ↗",
"href": "https://l.bentoml.com/bento-cloud",
"newWindow": true
},
"bentoml": {
"title": "🍱 BentoML ↗",
"href": "https://docs.bentoml.com/en/latest/",
"newWindow": true
}
}

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{
"configuration": "openllm.LLMConfig"
}

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# `openllm.LLM`
This page entails the API documentation for the `openllm.LLM` class.
```python title="play.py"
import openllm, asyncio, typing as t
llm = openllm.LLM('meta-llama/Llama-2-13b-chat-hf')
async def main(prompt:str, stream: bool=True,**kwargs: t.Any) -> str|t.Iterator[str]:
if not stream: return await llm.generate(prompt,**kwargs).outputs[0].text
async for output in llm.generate_iterator(prompt,**kwargs): yield output.text
if __name__ == '__main__': asyncio.run(main('What is the meaning of life?'))
```
## `openllm.LLM.__init__()`
Initialize the LLM with given pretrained model.
> [!NOTE]
> - *args to be passed to the model.
> - **attrs will first be parsed to the AutoConfig, then the rest will be parsed to the `import_model`
> - For any specific tokenizer kwargs, it should be prefixed with _tokenizer_*
For custom pretrained path, it is recommended to pass in `model_version` alongside with the path
to ensure that it won't be loaded multiple times.
Internally, if a pretrained is given as a HuggingFace repository path, OpenLLM will use the `commit_hash`
to generate the model version.
For better consistency, we recommend users to also push the fine-tuned model to HuggingFace repository.
If you need to overwrite the default ``import_model``, implement the following in your subclass:
```python
def import_model(
self,
*args: t.Any,
trust_remote_code: bool,
**attrs: t.Any,
):
_, tokenizer_attrs = self.llm_parameters
return bentoml.transformers.save_model(
tag,
transformers.AutoModelForCausalLM.from_pretrained(self.model_id, device_map="auto", torch_dtype=torch.bfloat16, **attrs),
custom_objects={"tokenizer": transformers.AutoTokenizer.from_pretrained(self.model_id, padding_side="left", **tokenizer_attrs)},
)
```
If your import model doesn't require specific customisation, but you still want to control how the model is imported to `llm.model`,
you can simply pass in `import_kwargs` at class level that will be then passed into The default `import_model` implementation.
See ``openllm.DollyV2`` for example.
```python
dolly_v2_runner = openllm.Runner("dolly-v2", _tokenizer_padding_side="left", torch_dtype=torch.bfloat16, device_map="cuda")
```
Note: If you implement your own `import_model`, then `import_kwargs` will be the
base kwargs. You can still override those via ``openllm.Runner``.
Note that this tag will be generated based on `self.default_id`.
passed from the __init__ constructor.
``llm_post_init`` can also be implemented if you need to do any additional
initialization after everything is setup.
> [!NOTE]
> If you need to implement a custom `load_model`, the following is an example from Falcon implementation:
>
> ```python
> def load_model(self, tag: bentoml.Tag, *args: t.Any, **attrs: t.Any) -> t.Any:
> torch_dtype = attrs.pop("torch_dtype", torch.bfloat16)
> device_map = attrs.pop("device_map", "auto")
>
> _ref = bentoml.transformers.get(tag)
>
> model = bentoml.transformers.load_model(_ref, device_map=device_map, torch_dtype=torch_dtype, **attrs)
> return transformers.pipeline("text-generation", model=model, tokenizer=_ref.custom_objects["tokenizer"])
> ```
Args:
model_id: The pretrained model to use. Defaults to None. If None, 'self.default_id' will be used.
llm_config: The config to use for this LLM. Defaults to None. If not passed, OpenLLM
will use `config_class` to construct default configuration.
quantization_config: ``transformers.BitsAndBytesConfig`` configuration, or 'gptq' denoting this model to be loaded with GPTQ.
*args: The args to be passed to the model.
**attrs: The kwargs to be passed to the model.

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{
"fine-tune": ""
}

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## Fine-tuning weights

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## Getting Started

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## OpenLLM
Hello world

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## Integrations

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---
title: 'OpenLLM - Fine-tune, serve, deploy LLMs in production'
---

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// If you want to use other PostCSS plugins, see the following:
// https://tailwindcss.com/docs/using-with-preprocessors
/** @type {import('postcss').Postcss} */
module.exports = {
plugins: {
tailwindcss: {},
autoprefixer: {}
}
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/** @type {import('tailwindcss').Config} */
module.exports = {
content: ['./pages/**/*.{js,ts,jsx,tsx,mdx}', './components/**/*.{js,ts,jsx,tsx}', './theme.config.tsx'],
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import React from 'react'
import { useRouter } from 'next/router'
import { useConfig } from 'nextra-theme-docs'
import type { DocsThemeConfig } from 'nextra-theme-docs'
const openllmUrl = 'https://openllm.community'
const logo = (
<span>
<svg height="20" viewBox="0 0 373 60" xmlns="http://www.w3.org/2000/svg" fill="currentColor">
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<circle cx="40.54" cy="24.66" r="2.74" />
<circle cx="29.67" cy="24.66" r="2.74" />
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<path
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vectorEffect="non-scaling-stroke"
stroke="currentColor"
strokeWidth="0.25"
transform="translate(80, 2.5)"
/>
</svg>
</span>
)
const theme: DocsThemeConfig = {
project: {
link: 'https://github.com/bentoml/OpenLLM'
},
editLink: { text: 'Edit this page on GitHub →' },
feedback: { content: 'Question? Send us your feedback →', labels: 'feedback' },
docsRepositoryBase: 'https://github.com/bentoml/OpenLLM/tree/main/docs',
chat: {
link: 'https://l.bentoml.com/join-openllm-discord'
},
logo,
head: function useHead() {
const { frontMatter, title } = useConfig()
// TODO: support locale
// https://nextjs.org/docs/pages/api-reference/functions/use-router
const { route } = useRouter()
const socialCard = route === '/' || !title ? `${openllmUrl}/og.png` : `${openllmUrl}/api/og?title=${title}`
const ogDescription = frontMatter.description || 'Fine-tune, serve and deploy LLMs in production'
return (
<>
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<meta httpEquiv="Content-Language" content="en" />
<meta name="description" content={ogDescription} />
<meta name="twitter:card" content="summary_large_image" />
<meta name="twitter:image" content={socialCard} />
<meta name="twitter:site:domain" content="openllm.community" />
<meta name="twitter:url" content="https://openllm.community" />
<meta name="og:title" content={title ? title + ' | OpenLLM' : 'OpenLLM'} />
<meta name="og:image" content={socialCard} />
<meta name="og:description" content={ogDescription} />
<meta name="apple-mobile-web-app-title" content="OpenLLM" />
<link rel="apple-touch-icon" sizes="180x180" href="/favicon/apple-touch-icon.png" />
<link rel="icon" type="image/png" sizes="32x32" href="/favicon/favicon-32x32.png" />
<link rel="icon" type="image/png" sizes="16x16" href="/favicon/favicon-16x16.png" />
<link rel="icon" type="image/svg+xml" href="/favicon/favicon.svg" />
<link rel="icon" type="image/x-icon" href="/favicon/favicon.ico" />
<link rel="icon" href="/favicon/favicon-dark.svg" type="image/svg+xml" media="(prefers-color-scheme: dark)" />
<link rel="icon" href="/favicon/favicon-dark.ico" type="image/x-icon" media="(prefers-color-scheme: dark)" />
<link rel="android-chrome" type="image/png" sizes="192x192" href="/favicon/android-chrome-192x192.png" />
<link rel="android-chrome" type="image/png" sizes="512x512" href="/favicon/android-chrome-512x512.png" />
<link rel="manifest" href="/favicon/site.webmanifest" />
<link rel="mask-icon" href="/favicon/safari-pinned-tab.svg" color="#000000" />
<meta name="msapplication-config" content="/favicon/browserconfig.xml" />
<meta name="msapplication-square150x150logo" content="/favicon/mstile-150x150.png" />
<meta name="msapplication-TileColor" content="#ffffff" />
</>
)
},
search: {
placeholder: 'Search website...'
},
toc: {
float: true
},
sidebar: {
titleComponent({ title, type }) {
if (type === 'separator') {
return <span className="cursor-default">{title}</span>
}
return <>{title}</>
},
defaultMenuCollapseLevel: 1,
toggleButton: true
},
gitTimestamp({ timestamp }) {
const { locale } = useRouter()
return (
<>
'last updated on '
<time dateTime={timestamp.toISOString()}>
{timestamp.toLocaleDateString(locale, {
day: 'numeric',
month: 'long',
year: 'numeric'
})}
</time>
</>
)
},
useNextSeoProps() {
const { asPath } = useRouter()
if (['/', '/docs'].includes(asPath)) {
return { titleTemplate: 'OpenLLM' }
}
return { titleTemplate: `%s | OpenLLM` }
},
footer: {
text: (
<div className="flex w-full items-center justify-between">
<div>© {new Date().getFullYear()} OpenLLM project</div>
<a href="https://vercel.com?utm_source=openllm" target="_blank" rel="noopener noreferrer">
<svg xmlns="http://www.w3.org/2000/svg" fill="none" viewBox="0 0 212 44" className="h-8" width="212">
<rect width="212" height="44" fill="#000" rx="8"></rect>
<path
fill="#fff"
d="M60.438 15.227V26.5h1.406v-4.023h2.836c2.117 0 3.625-1.493 3.625-3.602 0-2.148-1.477-3.648-3.61-3.648h-4.257zm1.406 1.25h2.484c1.633 0 2.531.851 2.531 2.398 0 1.492-.93 2.352-2.53 2.352h-2.485v-4.75zm11.5 10.171c2.399 0 3.883-1.656 3.883-4.359 0-2.71-1.484-4.36-3.883-4.36-2.398 0-3.883 1.65-3.883 4.36 0 2.703 1.485 4.36 3.883 4.36zm0-1.21c-1.594 0-2.492-1.157-2.492-3.149 0-2 .898-3.148 2.492-3.148 1.594 0 2.492 1.148 2.492 3.148 0 1.992-.898 3.148-2.492 3.148zm15.954-7.36h-1.352l-1.656 6.735h-.125l-1.883-6.735h-1.29l-1.882 6.735h-.125l-1.656-6.735h-1.36l2.36 8.422h1.36l1.874-6.516h.125l1.883 6.516h1.367l2.36-8.422zm4.523 1.04c1.336 0 2.227.984 2.258 2.476h-4.64c.101-1.492 1.039-2.477 2.382-2.477zm2.219 5.202c-.352.742-1.086 1.14-2.172 1.14-1.43 0-2.36-1.054-2.43-2.718v-.062h6.055v-.516c0-2.617-1.383-4.234-3.656-4.234-2.313 0-3.797 1.718-3.797 4.367 0 2.664 1.46 4.351 3.797 4.351 1.844 0 3.156-.89 3.547-2.328H96.04zm3.242 2.18h1.344v-5.219c0-1.187.93-2.047 2.211-2.047.266 0 .75.047.86.078V17.97a5.77 5.77 0 00-.672-.04c-1.117 0-2.086.579-2.336 1.4h-.125v-1.25h-1.281V26.5zm8.899-7.383c1.336 0 2.227.985 2.258 2.477h-4.641c.102-1.492 1.04-2.477 2.383-2.477zm2.219 5.203c-.352.742-1.086 1.14-2.172 1.14-1.43 0-2.359-1.054-2.43-2.718v-.062h6.055v-.516c0-2.617-1.383-4.234-3.656-4.234-2.313 0-3.797 1.718-3.797 4.367 0 2.664 1.461 4.351 3.797 4.351 1.844 0 3.156-.89 3.547-2.328H110.4zm6.36 2.328c1.164 0 2.164-.554 2.695-1.492h.125V26.5h1.281V14.734h-1.343v4.672h-.118c-.476-.922-1.468-1.476-2.64-1.476-2.141 0-3.539 1.718-3.539 4.36 0 2.648 1.382 4.358 3.539 4.358zm.312-7.507c1.524 0 2.477 1.218 2.477 3.148 0 1.945-.946 3.148-2.477 3.148-1.539 0-2.461-1.18-2.461-3.148 0-1.96.93-3.148 2.461-3.148zm14.462 7.507c2.133 0 3.531-1.726 3.531-4.359 0-2.648-1.391-4.36-3.531-4.36-1.156 0-2.18.571-2.641 1.477h-.125v-4.672h-1.344V26.5h1.282v-1.344h.125c.531.938 1.531 1.492 2.703 1.492zm-.313-7.507c1.539 0 2.453 1.18 2.453 3.148 0 1.969-.914 3.148-2.453 3.148-1.531 0-2.484-1.203-2.484-3.148s.953-3.148 2.484-3.148zm6.04 10.406c1.492 0 2.164-.578 2.882-2.531l3.29-8.938h-1.43l-2.305 6.93h-.125l-2.312-6.93h-1.453l3.117 8.43-.157.5c-.351 1.015-.773 1.383-1.546 1.383-.188 0-.399-.008-.563-.04V29.5c.188.031.422.047.602.047zm17.391-3.047l3.898-11.273h-2.148l-2.813 8.921h-.132l-2.836-8.921h-2.227l3.938 11.273h2.32zm8.016-7.18c1.164 0 1.93.813 1.969 2.078h-4.024c.086-1.25.899-2.078 2.055-2.078zm1.984 4.828c-.281.633-.945.985-1.906.985-1.273 0-2.094-.89-2.141-2.313v-.101h5.969v-.625c0-2.696-1.461-4.313-3.898-4.313-2.477 0-4.016 1.727-4.016 4.477s1.516 4.414 4.031 4.414c2.016 0 3.446-.969 3.797-2.524h-1.836zm3.547 2.352h1.938v-4.938c0-1.195.875-1.976 2.133-1.976.328 0 .843.055.992.11v-1.798c-.18-.054-.524-.085-.805-.085-1.101 0-2.023.625-2.258 1.468h-.132v-1.328h-1.868V26.5zm13.501-5.672c-.203-1.797-1.532-3.047-3.727-3.047-2.57 0-4.078 1.649-4.078 4.422 0 2.813 1.516 4.469 4.086 4.469 2.164 0 3.508-1.203 3.719-2.992h-1.844c-.203.89-.875 1.367-1.883 1.367-1.32 0-2.117-1.047-2.117-2.844 0-1.773.789-2.797 2.117-2.797 1.063 0 1.703.594 1.883 1.422h1.844zm5.117-1.508c1.164 0 1.93.813 1.969 2.078h-4.024c.086-1.25.899-2.078 2.055-2.078zm1.985 4.828c-.282.633-.946.985-1.907.985-1.273 0-2.093-.89-2.14-2.313v-.101h5.968v-.625c0-2.696-1.461-4.313-3.898-4.313-2.477 0-4.016 1.727-4.016 4.477s1.516 4.414 4.032 4.414c2.015 0 3.445-.969 3.796-2.524h-1.835zm3.625 2.352h1.937V14.648h-1.937V26.5zM23.325 13l9.325 16H14l9.325-16z"
></path>
<path stroke="#5E5E5E" d="M43.5 0v44"></path>
</svg>
</a>
</div>
)
}
}
export default theme

View File

@@ -1,13 +0,0 @@
{
"extends": "../tsconfig.json",
"compilerOptions": {
"baseUrl": ".",
"paths": {
"@components/*": ["components/*"],
"react": ["./node_modules/@types/react"],
"react-dom": ["./node_modules/@types/react-dom"]
}
},
"include": ["next-env.d.ts", "**/*.ts", "**/*.tsx"],
"exclude": ["node_modules"]
}

View File

@@ -70,7 +70,6 @@ write-summary-report = "python tools/write-coverage-report.py"
detached = true detached = true
[envs.ui.scripts] [envs.ui.scripts]
server = "openllm start {args:facebook/opt-250m} --working-dir {root:uri} --cors --debug" server = "openllm start {args:facebook/opt-250m} --working-dir {root:uri} --cors --debug"
docs = "cd docs && pnpm dev"
[envs.ci] [envs.ci]
detached = true detached = true
[envs.ci.scripts] [envs.ci.scripts]

View File

@@ -80,9 +80,7 @@ Homepage = "https://bentoml.com"
Tracker = "https://github.com/bentoml/OpenLLM/issues" Tracker = "https://github.com/bentoml/OpenLLM/issues"
Twitter = "https://twitter.com/bentomlai" Twitter = "https://twitter.com/bentomlai"
[project.optional-dependencies] [project.optional-dependencies]
full = ["openllm-core[vllm,bentoml,transformers]"] full = ["openllm-core[bentoml]", "transformers>=4.36.0"]
transformers = ["transformers>=4.36.0"]
vllm = ["vllm>=0.3.0"]
bentoml = ["bentoml>=1.2"] bentoml = ["bentoml>=1.2"]
[tool.hatch.version] [tool.hatch.version]

View File

@@ -42,7 +42,7 @@ dependencies = [
"openllm-client>=0.5.4", "openllm-client>=0.5.4",
"openllm-core>=0.5.4", "openllm-core>=0.5.4",
"safetensors", "safetensors",
"vllm>=0.4.2", "vllm>=0.4.3",
"ghapi", "ghapi",
"einops", "einops",
"sentencepiece", "sentencepiece",

View File

@@ -4,6 +4,8 @@ ARG NVIDIA_DRIVER_CAPABILITIES=compute,utility
ENV NVIDIA_DRIVER_CAPABILITIES=$NVIDIA_DRIVER_CAPABILITIES ENV NVIDIA_DRIVER_CAPABILITIES=$NVIDIA_DRIVER_CAPABILITIES
ARG HF_HUB_DISABLE_PROGRESS_BARS=TRUE ARG HF_HUB_DISABLE_PROGRESS_BARS=TRUE
ENV HF_HUB_DISABLE_PROGRESS_BARS=$HF_HUB_DISABLE_PROGRESS_BARS ENV HF_HUB_DISABLE_PROGRESS_BARS=$HF_HUB_DISABLE_PROGRESS_BARS
{% call common.RUN(__enable_buildkit__) -%} {{ __pip_cache__ }} {% endcall -%} bash -c 'pip install --no-color --progress-bar off "vllm==0.4.2" || true' ARG VLLM_NO_USAGE_STATS=1
ENV VLLM_NO_USAGE_STATS=$VLLM_NO_USAGE_STATS
{% call common.RUN(__enable_buildkit__) -%} {{ __pip_cache__ }} {% endcall -%} bash -c 'pip install --no-color --progress-bar off "vllm==0.4.3" || true'
{{ super() }} {{ super() }}
{% endblock %} {% endblock %}

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@@ -263,6 +263,7 @@ def start_command(
'OPENLLM_CONFIG': llm_config.model_dump_json(), 'OPENLLM_CONFIG': llm_config.model_dump_json(),
'DTYPE': dtype, 'DTYPE': dtype,
'TRUST_REMOTE_CODE': str(trust_remote_code), 'TRUST_REMOTE_CODE': str(trust_remote_code),
'VLLM_NO_USAGE_STATS': str(1),
'GPU_MEMORY_UTILIZATION': orjson.dumps(gpu_memory_utilization).decode(), 'GPU_MEMORY_UTILIZATION': orjson.dumps(gpu_memory_utilization).decode(),
'SERVICES_CONFIG': orjson.dumps( 'SERVICES_CONFIG': orjson.dumps(
# XXX: right now we just enable GPU by default. will revisit this if we decide to support TPU later. # XXX: right now we just enable GPU by default. will revisit this if we decide to support TPU later.

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@@ -202,7 +202,14 @@ class LLM:
"'generate_iterator' is reserved only for online serving. For batch inference use 'LLM.batch' instead." "'generate_iterator' is reserved only for online serving. For batch inference use 'LLM.batch' instead."
) )
from vllm import SamplingParams from vllm import SamplingParams, TextPrompt, TokensPrompt
if prompt_token_ids is not None:
inputs = TokensPrompt(prompt_token_ids=prompt_token_ids)
else:
if prompt is None:
raise ValueError('Either "prompt" or "prompt_token_ids" must be passed.')
inputs = TextPrompt(prompt=prompt)
config = self.config.model_construct_env(**dict_filter_none(attrs)) config = self.config.model_construct_env(**dict_filter_none(attrs))
@@ -229,12 +236,11 @@ class LLM:
try: try:
async for generations in self._model.generate( async for generations in self._model.generate(
prompt, inputs=inputs,
sampling_params=SamplingParams(**{ sampling_params=SamplingParams(**{
k: config.__getitem__(k) for k in set(inspect.signature(SamplingParams).parameters.keys()) k: config.__getitem__(k) for k in set(inspect.signature(SamplingParams).parameters.keys())
}), }),
request_id=request_id, request_id=request_id,
prompt_token_ids=prompt_token_ids if prompt_token_ids else None,
): ):
yield generations yield generations
except Exception as err: except Exception as err:
@@ -277,7 +283,7 @@ class LLM:
"'batch' is reserved for offline batch inference. For online serving use 'LLM.generate' or 'LLM.generate_iterator' instead." "'batch' is reserved for offline batch inference. For online serving use 'LLM.generate' or 'LLM.generate_iterator' instead."
) )
from vllm import SamplingParams from vllm import SamplingParams, TextPrompt
if isinstance(prompts, str): if isinstance(prompts, str):
prompts = [prompts] prompts = [prompts]
@@ -295,11 +301,10 @@ class LLM:
for i in range(num_requests): for i in range(num_requests):
request_id = str(next(self._counter)) request_id = str(next(self._counter))
prompt = prompts[i]
config = configs[i] config = configs[i]
self._model.add_request( self._model.add_request(
request_id, request_id,
prompt, TextPrompt(prompt=prompts[i]),
SamplingParams(**{k: config.__getitem__(k) for k in set(inspect.signature(SamplingParams).parameters.keys())}), SamplingParams(**{k: config.__getitem__(k) for k in set(inspect.signature(SamplingParams).parameters.keys())}),
) )

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@@ -1,3 +1,2 @@
packages: packages:
- docs
- openllm-node - openllm-node

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@@ -2,10 +2,8 @@
from __future__ import annotations from __future__ import annotations
import dataclasses import dataclasses
import os import os
import sys
import typing as t import typing as t
import inflection
import tomlkit import tomlkit
from ghapi.all import GhApi from ghapi.all import GhApi
@@ -13,9 +11,6 @@ if t.TYPE_CHECKING:
from tomlkit.items import Array, Table from tomlkit.items import Array, Table
ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.insert(0, os.path.join(ROOT, 'openllm-core', 'src'))
import openllm_core as core
_OWNER, _REPO = 'bentoml', 'openllm' _OWNER, _REPO = 'bentoml', 'openllm'
@@ -248,7 +243,7 @@ def main(args) -> int:
Dependencies(name='openllm-client', lower_constraint=release_version), Dependencies(name='openllm-client', lower_constraint=release_version),
Dependencies(name='openllm-core', lower_constraint=release_version), Dependencies(name='openllm-core', lower_constraint=release_version),
Dependencies(name='safetensors'), Dependencies(name='safetensors'),
Dependencies(name='vllm', lower_constraint='0.4.2'), Dependencies(name='vllm', lower_constraint='0.4.3'),
Dependencies(name='ghapi'), Dependencies(name='ghapi'),
Dependencies(name='einops'), Dependencies(name='einops'),
Dependencies(name='sentencepiece'), Dependencies(name='sentencepiece'),