PrivateGPT is an open-source API layer that turns local language models into production AI applications.
PrivateGPT solves the problem that running a model locally is only the first step toward building useful AI applications. It provides higher-level building blocks as an API following the Claude API model, allowing developers to build private AI products without rebuilding backend primitives from scratch or depending on cloud APIs. The tool connects to any OpenAI-compatible inference server via a configurable base URL, requiring only that the server implements the standard chat completions and models endpoints. It does not run models itself but orchestrates them alongside retrieval-augmented generation, agentic capabilities, tool execution, and database access.
PrivateGPT suits teams building on-premise AI applications where data privacy is essential and cloud dependencies are unacceptable. It works with any OpenAI-compatible inference server, making it flexible across different local model deployments. The tool includes a built-in workbench UI for testing and demonstrations, though the API is the actual product and developers are expected to build their own applications on top of it. The feature set spans standard messaging with streaming and async support, file and artifact ingestion, retrieval with citations, built-in tools like web search and code execution, custom tools and MCP connectors, and structured database and CSV access through embeddings and orchestration.
The project maintains active development with regular updates to its core API and integrations. The codebase shows consistent refinement of the API surface and expansion of supported inference providers. Documentation is comprehensive and kept current alongside feature additions. The tool is production-tested, powering an on-premise AI platform serving enterprises globally.
