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OpenPipe

> AI 编程
开源

将昂贵的提示转换为便宜的微调模型

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工具介绍

将昂贵的提示转换为便宜的微调模型

## **Note:** we’ve temporarily stopped development on the open-source version of OpenPipe to integrate some proprietary third-party code. We hope to make the non-proprietary parts of the repository open again under an open core model once we have the bandwidth to do so!

OpenPipe

Open-source fine-tuning and model-hosting platform.

Demo - Running Locally - Docs


Use powerful but expensive LLMs to fine-tune smaller and cheaper models suited to your exact needs. Query your past requests and evaluate models against one another. Switch between OpenAI and fine-tuned models with one line of code.
## Features - Easy integration with OpenAI's SDK in both Python and TypeScript. - [Python SDK](https://pypi.org/project/openpipe/) - [TypeScript SDK](https://www.npmjs.com/package/openpipe) - OpenAI-compatible chat completions endpoint. - Fine-tune GPT 3.5, Mistral, and Llama 2 models. Host on-platform or download the weights. - Model output is OpenAI-compatible. - Switching from GPT 4 to a fine-tuned Mistral model only requires changing the model name. - Query logs using powerful built-in filters. - Import datasets in OpenAI-compatible JSONL files. - Prune large chunks of duplicate text like system prompts. - Compare output accuracy against base models like gpt-3.5-turbo. ## Supported Base Models - [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) - [OpenPipe/mistral-ft-optimized-1227](https://huggingface.co/OpenPipe/mistral-ft-optimized-1227) - [meta-llama/Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) - [meta-llama/Llama-3-70B](https://huggingface.co/meta-llama/Meta-Llama-3-70B) - [gpt-3.5-turbo-0613](https://openai.com/blog/gpt-3-5-turbo-fine-tuning-and-api-updates) - [gpt-3.5-turbo-1106](https://openai.com/blog/gpt-3-5-turbo-fine-tuning-and-api-updates) - [gpt-3.5-turbo-0125](https://openai.com/blog/gpt-3-5-turbo-fine-tuning-and-api-updates) ## Documentation - See [docs](https://docs.openpipe.ai/introduction) ## Running Locally 1. Install [Postgresql](https://www.postgresql.org/download/). 2. Install [NodeJS 20](https://nodejs.org/en/download/current) (earlier versions will very likely work but aren't tested). 3. Install `pnpm`: `npm i -g pnpm` 4. Clone this repository: `git clone https://github.com/openpipe/openpipe` 5. Install the dependencies: `cd openpipe && pnpm install` 6. Create a `.env` file (`cd app && cp .env.example .env`) and enter your `OPENAI_API_KEY`. 7. If you just installed postgres and wish to use the default `DATABASE_URL` run the following commands: ```sh psql postgres CREATE ROLE postgres WITH LOGIN PASSWORD 'postgres'; ALTER ROLE postgres SUPERUSER; ``` 8. Update `DATABASE_URL` if necessary to point to your Postgres instance and run `pnpm prisma migrate dev` in the `app` directory to create the database. 9. Create a [GitHub OAuth App](https://docs.github.com/en/apps/oauth-apps/building-oauth-apps/creating-an-oauth-app), set the callback URL to `/api/auth/callback/github`, e.g. `http://localhost:3000/api/auth/callback/github`. 10. Update the `GITHUB_CLIENT_ID` and `GITHUB_CLIENT_SECRET` values from the Github OAuth app (Note: a PR to make auth optional when running locally would be a great contribution!). 11. To start the app run `pnpm dev` in the `app` directory. 12. Navigate to [http://localhost:3000](http://localhost:3000) ## Using Locally ```sh import os from openpipe import OpenAI client = OpenAI( api_key="Your API Key", openpipe={ "api_key": "Your OpenPipe API Key", "base_url": "http://localhost:3000/api/v1", # Local OpenPipe instance } ) completion = client.chat.completions.create( model="gpt-3.5-turbo", messages=[{"role": "system", "content": "count to 10"}], openpipe={ "tags": {"prompt_id": "counting"}, "log_request": True }, ) ``` ## Testing Locally 1. Copy your `.env` file to `.env.test`. 2. Update the `DATABASE_URL` to have a different database name than your development one 3. Run `DATABASE_URL=[your new datatase url] pnpm prisma migrate dev --skip-seed --skip-generate` 4. Run `pnpm test`

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核心特点

  • •Easy integration with OpenAI's SDK in both Python and TypeScript.
  • •Python SDK
  • •TypeScript SDK
  • •OpenAI-compatible chat completions endpoint.
  • •Fine-tune GPT 3.5, Mistral, and Llama 2 models. Host on-platform or download the weights.
  • •Model output is OpenAI-compatible.
  • •Switching from GPT 4 to a fine-tuned Mistral model only requires changing the model name.
  • •Query logs using powerful built-in filters.
  • •Import datasets in OpenAI-compatible JSONL files.
  • •Prune large chunks of duplicate text like system prompts.

> 标签

TypeScriptaillmllmopsprompt-engineering

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> 工具信息

发布日期2026年8月1日
最后更新2026年9月17日
分类AI 编程
定价开源

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