Agents IA
TaskingAI
An open-source platform for AI-native application development — assistants, tools, RAG and models in one API.
★ 5,4 k étoilesApache-2.0
Voir le guide →RAG-Anything est un projet de agents IA open source, créé par HKUDS (HKUDS/RAG-Anything sur GitHub). Il compte 23 495 étoiles sur GitHub et 2 735 forks, il est publié sous la licence MIT et a été mis à jour pour la dernière fois sur GitHub le 6 octobre 2026.
One RAG framework for everything — including multimodal documents.
Decide what you want the project to do before installing anything.
Grab the source and skim the README for setup requirements.
Install dependencies and add any API keys or settings it needs.
Launch it and follow the example workflow from the docs.
Parsing through generation in one toolkit.
Text, images, tables — the messy reality.
From HKU with a published paper.
One interface across document types.
Fits the standard ML stack.
Free for commercial use.
Download the source and move into the project folder.
git clone https://github.com/HKUDS/RAG-Anything.git
cd RAG-AnythingIsolate dependencies, then install requirements.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtLaunch using the entry point shown in the README.
python -m rag_anything # check README for the exact commandIt is an open-source project at HKUDS/RAG-Anything with 2735 forks. Check the contributors tab and recent commits to judge how active maintenance is.
Yes — it's MIT licensed: free to use, modify, and ship commercially. Just keep the license notice in copies.
Documents mixing text, images, tables, and more — the full messy reality of enterprise files. See the paper for details.
Yes — the design is described in an arXiv paper linked from the repo homepage field.
Clone the repo and follow the README quickstart — the README is the best starting point.
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Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.