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PRIVATEGPT
Build private AI applications with local models and RAG
Apache-2.0
ABOUT
Organizations that need AI capabilities but cannot send data to third-party APIs face a difficult choice: sacrifice privacy or build a custom on-premise AI stack from scratch. PrivateGPT solves this by providing a comprehensive, production-ready API layer that runs entirely on your own infrastructure with local models. It handles document ingestion, RAG retrieval, multi-model chat, tool execution, MCP server integration, and even text-to-SQL — all behind your firewall. The OpenAI-compatible API means existing tooling works without modification. Teams get the full power of LLMs without compromising on data sovereignty.
INSTALL
pip install private-gptINTEGRATION GUIDE
1. Deploy a fully private document Q&A system for sensitive HR, legal, and financial documents that cannot be sent to external APIs
2. Build an on-premise AI assistant that accesses internal databases via text-to-SQL without exposing query logic to third parties
3. Create a private coding assistant with local LLMs and MCP tool integration for air-gapped development environments
4. Power a customer-facing AI chatbot for regulated industries (healthcare, finance, government) with guaranteed data residency
TAGS
ragpythonon-premiselocalprivacyapimcptext-to-sql