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Open-source API layer for private AI applications on local models

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Type
Open Source
Company
Zylon
Visit Website GitHub (40 stars)

About GitHub

PrivateGPT is an open-source API layer that transforms local AI models into production-ready applications. It provides higher-level building blocks—such as a standard messages API, file and artifact ingestion, retrieval-augmented generation (RAG) with citations, built-in tools (web search, web fetch, code execution), custom tools and MCP connectors, structured access to databases and CSVs, embeddings, and orchestration—all exposed through a Claude-compatible API. PrivateGPT does not run models itself; it connects to any OpenAI-compatible inference server (e.g., Ollama, llama.cpp, vLLM). It ships a built-in workbench UI for testing and is production-tested, powering the on-premise AI platform Zylon.

Key Features

Standard messages API with streaming, async, and token counting
File and artifact ingestion
Retrieval with citations and agentic RAG
Built-in tools: web search, web fetch, code execution
Custom tools and MCP connectors
Structured access to databases and CSVs
Embeddings and orchestration
Works with any OpenAI-compatible inference server (Ollama, llama.cpp, vLLM, etc.)
Built-in workbench UI for testing and demos

Pros & Cons

Pros
  • Fully open-source and free to use
  • Enables private, on-premise AI without cloud dependency
  • Production-tested and powers a commercial enterprise platform (Zylon)
  • Rich API supporting RAG, tool use, and multi-modal inputs
  • Compatible with any OpenAI-compatible inference server, providing flexibility
  • Built-in UI for quick testing and demos
Cons
  • Requires a separate, running OpenAI-compatible inference server to function
  • Not a standalone solution; needs technical setup for deployment
  • Documentation and community support may be less extensive than larger projects

Best For

Building private AI applications that run entirely on local modelsDeploying on-premise AI solutions for enterprises requiring data privacyCreating RAG pipelines with citation supportDeveloping AI agents with tool use (web search, code execution, database queries)Prototyping and testing AI workflows with a built-in UI

FAQ

What is PrivateGPT?
PrivateGPT is an open-source API layer that sits on top of local AI models, providing higher-level building blocks like RAG, tool calling, and file ingestion so you can build production AI applications without relying on cloud APIs.
Does PrivateGPT run models itself?
No. PrivateGPT connects to any OpenAI-compatible inference server (e.g., Ollama, llama.cpp, vLLM) via the OPENAI_API_BASE setting. It uses the /v1/chat/completions and /v1/models endpoints.
What features does the PrivateGPT API provide?
It includes a standard messages API with streaming and async support, file and artifact ingestion, retrieval with citations (RAG), built-in tools (web search, web fetch, code execution), custom tools and MCP connectors, structured access to databases and CSVs, and embeddings and orchestration.