RAG et connaissances
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The semantic intelligence layer for ontologies — governed, traceable knowledge for AI agents
★ 2,8 k étoilesApache-2.0
Voir le guide →pipeshub-ai est un projet de RAG et connaissances open source, créé par pipeshub-ai (pipeshub-ai/pipeshub-ai sur GitHub). Il compte 3 820 étoiles sur GitHub et 595 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.
The open-source, permission-aware context layer that lets agents search all your company knowledge.
Decide the first concrete outcome you want from it, so you can pick the right example, template or mode instead of exploring everything at once.
Clone the repository (or install the published package) and skim its README quick start for the requirements for your platform.
Run the documented install step and set any required configuration — such as provider keys, data sources or local services — before the first run.
Execute the smallest documented example end to end, confirm the output is what you expected, then adapt it to your real data or workflow.
Slack, Drive, Jira, GitHub, Microsoft 365 and many more sources synced and indexed automatically.
Results respect source permissions, with hybrid search, knowledge-graph retrieval and citations.
Agents can search, navigate and cite company knowledge through the Model Context Protocol.
Official Python, TypeScript and Go SDKs for building on the context layer.
Ready agents for tasks such as deep research on top of your workspace knowledge.
Run it on your own infrastructure with the one-line installer; your data stays under your control.
Get the source so you can inspect, configure and run it locally.
git clone https://github.com/pipeshub-ai/pipeshub-ai.git
cd pipeshub-aiRun the official installer on your server (review the script first if you prefer).
curl -fsSL https://get.pipeshub.com/install | bashClone the repo and run the same installer from the repo root, then connect your first sources in the web app.
git clone https://github.com/pipeshub-ai/pipeshub-ai.git
cd pipeshub-ai
./install.shIt is maintained by pipeshub-ai on GitHub (pipeshub-ai/pipeshub-ai), where the source, issues and releases live.
Yes — it is free and open source under Apache-2.0, which permits use, modification and commercial redistribution, with licence/notice retention.
The software is free and self-hosted; you configure your own LLM provider (cloud key or a local model via Ollama) for answer generation.
Compared with Glean or hosted enterprise search, pipeshub-ai's distinguishing focus is: the open-source, permission-aware context layer that lets agents search all your company knowledge. Pick it when that focus matches your need; the alternative may suit you better if its broader or different scope is the priority.
Clone https://github.com/pipeshub-ai/pipeshub-ai (or install its published package), follow the README quick start to install and configure it, then run the smallest documented example — the Run section on this page mirrors those steps.
The semantic intelligence layer for ontologies — governed, traceable knowledge for AI agents
All-in-one AI framework for semantic search, LLM orchestration and language model workflows.
Utopia — an open-source enterprise world model: a bitemporal knowledge substrate that learns from your documents and gives agents a governed, auditable memory
A trilingual e-commerce knowledge base agents can install.
Skills that let coding agents search and read your local documents.
A new state of the art for RAG: an open knowledge base for humans and agents.
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Projets de la catégorie RAG et connaissances proches dans le catalogue, les plus proches en étoiles de pipeshub-ai — continuez à explorer de part et d'autre.
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A personal knowledge base that builds itself — drop in sources, get a persistent interlinked wiki.
RAGApp: deploy a RAG app over your documents with Docker — configure it like a custom GPT
VideoRAG — chat with your videos, even hundreds of hours of them, with graph-driven retrieval.
Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.