RAG et connaissances
llmware
Unified framework for enterprise RAG pipelines with small, specialized models - local, private and secure.
★ 14,8 k étoilesApache-2.0
Voir le guide →private-gpt est un projet de RAG et connaissances open source, créé par zylon-ai (zylon-ai/private-gpt sur GitHub). Il compte 57 562 étoiles sur GitHub et 7 620 forks, il est publié sous la licence Apache-2.0 et a été mis à jour pour la dernière fois sur GitHub le 8 octobre 2026.
Complete API layer for private AI apps on local models: RAG, skills, tools, MCP and text-to-SQL
Decide what you want from private-gpt and check the README and requirements to confirm it fits your setup and Python environment.
Clone the repository from GitHub (github.com/zylon-ai/private-gpt) or use the documented install channel if you do not need the source.
Follow the README quickstart to install dependencies and set any required configuration or credentials.
Work through the README's first example end to end, then adapt it to your own project or data.
A complete API layer for retrieval-augmented generation over your documents, fully private.
Supports skills, tools and MCP on top of local models.
Includes text-to-SQL capabilities for querying structured data in natural language.
Works with any OpenAI-compatible inference server, not one locked backend.
Offers a Claude-compatible API surface, per the README.
Designed for on-premise deployment so documents never leave your infrastructure.
Start by getting the source and entering the project directory.
git clone https://github.com/zylon-ai/private-gpt.git
cd private-gptOn macOS use Homebrew, or install as a uv tool with the project's wheel index.
brew install private-gptLaunch PrivateGPT and ingest documents through its API or UI.
private-gpt # see README for the exact commandThe RAG & Knowledge shelf also holds nano-graphrag — a small, hackable GraphRAG implementation in about 1,100 lines — no Microsoft GraphRAG bulk. The RAG & Knowledge shelf also holds libratory — In TypeScript — built for your free book and audiobook laboratory. turn the... Readers working through the RAG & Knowledge shelf also stop at deeplake, Deep Lake — a multimodal datalake and vector store for AI, with version control and training streaming.
It is maintained by zylon-ai and contributors on GitHub, where the repository github.com/zylon-ai/private-gpt is the canonical home for code, issues and releases.
Yes — it is open source under the Apache-2.0 license. Read the license in the repository for what is permitted, including any conditions on redistribution or commercial use.
No paid key required — it runs local models through your chosen inference server.
Compared with Ollama or LM Studio alone: PrivateGPT adds the application API layer — RAG, tools, MCP and text-to-SQL — on top of a local inference server.
Clone github.com/zylon-ai/private-gpt, follow the README quickstart to install it, and run the documented first example before adapting it to your own work.
Unified framework for enterprise RAG pipelines with small, specialized models - local, private and secure.
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Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.