RAG et connaissances
OpenKB
OpenKB compiles your documents into a persistent, interlinked wiki knowledge base — no vector DB
★ 4,8 k étoilesApache-2.0
Voir le guide →FastGPT est un projet de RAG et connaissances open source, créé par labring (labring/FastGPT sur GitHub). Il compte 29 789 étoiles sur GitHub et 7 327 forks, il est publié sous la licence NOASSERTION et a été mis à jour pour la dernière fois sur GitHub le 8 octobre 2026.
A knowledge-base platform with visual AI workflows — build Q&A systems on your own documents
Decide what you want to achieve with FastGPT and check the README on GitHub for requirements before installing.
Clone the repository from GitHub (or take the packaged install route in step 3 if the README offers one).
Follow the project's documented install commands — the Run section below lists the exact ones — and add any required API keys or models.
Work through the README's quickstart example end to end, then adapt it to your own project or data.
Import documents, let FastGPT process and index them, and answer questions from your data.
Build complex Q&A and agent flows by dragging nodes instead of writing code.
Built-in handling for cleaning and chunking imported knowledge.
Works with OpenAI, Claude, DeepSeek, Qwen and other LLM providers.
Can call tools through the Model Context Protocol from within workflows.
An official install script pulls the deployment config and starts the full stack with Docker Compose.
Get the FastGPT source if you plan to develop it; deployment uses the official install script below.
git clone https://github.com/labring/FastGPT.git
cd FastGPTRun the official install script to fetch the deployment configuration.
bash <(curl -fsSL https://doc.fastgpt.io/deploy/install.sh)Bring the services up with Docker Compose, then open the web app (the README notes default account root / 1234 — change it immediately).
docker compose up -d
# open http://localhost:3000 and change the default passwordFastGPT is maintained by the labring organization/account on GitHub, together with open-source contributors, in the public repository labring/FastGPT.
Yes — the code is open source under the NOASSERTION license. Check the repository's LICENSE file for the exact terms before commercial use.
FastGPT is open source, but answering questions needs an LLM — you supply your own provider API key (OpenAI, DeepSeek, Qwen and others are supported).
All three offer visual LLM app building; FastGPT's center of gravity is knowledge-base Q&A with strong RAG tooling and a large Chinese community.
Clone the repository from GitHub, follow the install commands in the Run section (taken from the project's README), and complete the documented quickstart example before adapting it to your own use case.
OpenKB compiles your documents into a persistent, interlinked wiki knowledge base — no vector DB
Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.
Build a ChatGPT over your own data using natural language and LlamaIndex.
Utopia — an open-source enterprise world model: a bitemporal knowledge substrate that learns from your documents and gives agents a governed, auditable memory
A private AI platform for agents, assistants and enterprise search over your documents
Internal Q&A and knowledge base for Backstage.
Les autres projets de la catégorie RAG et connaissances avec le plus d'étoiles du catalogue LibreAI — la sélection réaliste d'alternatives si FastGPT ne vous convient pas.
Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or…
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context…
Lightweight OCR toolkit turning PDFs and images into structured, LLM-ready data in 100+ languages
MinerU — turns PDFs and Office documents into LLM-ready Markdown and JSON for agents and RAG pipelines, Apache-2.0 plus terms
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience
Projets de la catégorie RAG et connaissances proches dans le catalogue, les plus proches en étoiles de FastGPT — continuez à explorer de part et d'autre.
Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.
Turn PDFs into AI-ready data: extract Markdown, JSON and tables — and auto-tag for accessibility
Microsoft's graph-based RAG: index a corpus into a knowledge graph, then query it with an LLM
Vector similarity search inside Postgres - store embeddings next to your data
Local knowledge-base RAG and agent app built on LangChain with ChatGLM, Qwen and Llama models
An agentic AI data assistant - chat with your databases, run SQL and code, get reports
Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.