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TABBYAPI

Run local LLMs with an OpenAI-compatible API

AGPL-3.0

ABOUT

Running open-source LLMs locally typically requires complex setup, model format conversion, and custom client code. TabbyAPI provides a drop-in OpenAI API replacement that works with any OpenAI-compatible client. It supports the ExLlamaV2 engine for fast inference, various quantization formats (GPTQ, EXL2, FP16), custom model configurations, and multi-user access with API key management. Deployment is a single Docker command, and it works on consumer GPUs.

INTEGRATION GUIDE

1. Deploy a local OpenAI-compatible endpoint for testing LLM integrations without cloud API costs 2. Run quantized LLMs on consumer GPUs for private inference of sensitive data 3. Set up a multi-user inference server for a team with per-user API keys and rate limits 4. Experiment with different model quantizations (GPTQ, EXL2, FP16) to find the best speed-quality tradeoff 5. Build a local RAG pipeline with embedding models and LLMs all running through one API endpoint

TAGS

llminferencelocal-aiopenai-compatibleapi-serverquantizationself-hosted
TabbyAPI — AI Tool | Agentic AI For Good