Awesome
TabbyAPI
<p align="left"> <img src="https://img.shields.io/badge/Python-3.10%20|%203.11%20|%203.12-blue" alt="Python 3.10, 3.11, and 3.12"> <a href="/LICENSE"> <img src="https://img.shields.io/badge/License-AGPLv3-blue.svg" alt="License: AGPL v3"/> </a> <a href="https://discord.gg/sYQxnuD7Fj"> <img src="https://img.shields.io/discord/545740643247456267.svg?logo=discord&color=blue" alt="Discord Server"/> </a> </p> <p align="left"> <a href="https://theroyallab.github.io/tabbyAPI"> <img src="https://img.shields.io/badge/Documentation-API-orange" alt="Developer facing API documentation"> </a> </p> <p align="left"> <a href="https://ko-fi.com/I2I3BDTSW"> <img src="https://img.shields.io/badge/Support_on_Ko--fi-FF5E5B?logo=ko-fi&style=for-the-badge&logoColor=white" alt="Support on Ko-Fi"> </a> </p>[!IMPORTANT]
In addition to the README, please read the Wiki page for information about getting started!
[!NOTE]
Need help? Join the Discord Server and get the
Tabbyrole. Please be nice when asking questions.
A FastAPI based application that allows for generating text using an LLM (large language model) using the Exllamav2 backend
TabbyAPI is also the official API backend server for ExllamaV2.
Disclaimer
This project is marked as rolling release. There may be bugs and changes down the line. Please be aware that you might need to reinstall dependencies if needed.
TabbyAPI is a hobby project made for a small amount of users. It is not meant to run on production servers. For that, please look at other solutions that support those workloads.
Getting Started
[!IMPORTANT]
This README does not have instructions for setting up. Please read the Wiki.
Read the Wiki for more information. It contains user-facing documentation for installation, configuration, sampling, API usage, and so much more.
Features
- OpenAI compatible API
- Loading/unloading models
- HuggingFace model downloading
- Embedding model support
- JSON schema + Regex + EBNF support
- AI Horde support
- Speculative decoding via draft models
- Multi-lora with independent scaling (ex. a weight of 0.9)
- Inbuilt proxy to override client request parameters/samplers
- Flexible Jinja2 template engine for chat completions that conforms to HuggingFace
- Concurrent inference with asyncio
- Utilizes modern python paradigms
- Continuous batching engine using paged attention
- Fast classifer-free guidance
- OAI style tool/function calling
And much more. If something is missing here, PR it in!
Supported Model Types
TabbyAPI uses Exllamav2 as a powerful and fast backend for model inference, loading, etc. Therefore, the following types of models are supported:
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Exl2 (Highly recommended)
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GPTQ
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FP16 (using Exllamav2's loader)
In addition, TabbyAPI supports parallel batching using paged attention for Nvidia Ampere GPUs and higher.
Contributing
Use the template when creating issues or pull requests, otherwise the developers may not look at your post.
If you have issues with the project:
-
Describe the issue in detail
-
If you have a feature request, please indicate it as such.
If you have a Pull Request
- Describe the pull request in detail, what, and why you are changing something
Acknowldgements
TabbyAPI would not exist without the work of other contributors and FOSS projects:
Developers and Permissions
Creators/Developers: