ИИ-агенты
TaskingAI
An open-source platform for AI-native application development — assistants, tools, RAG and models in one API.
★ 5,4 тыс. звёздApache-2.0
Смотреть руководство →RAG-Anything — проект с открытым исходным кодом из категории «ИИ-агенты» от HKUDS (HKUDS/RAG-Anything на GitHub). У него 23 495 звёзд на GitHub и 2 735 форков, он распространяется по лицензии MIT и последний раз обновлялся на GitHub 6 октября 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.
An open-source platform for AI-native application development — assistants, tools, RAG and models in one API.
An open agent framework with a native terminal TUI, ReAct and Agent Team modes — one command to run.
A low-code tool for building multi-agent LLM apps — chatbots, RAG and fine-tuning in one flow.
The Ruby-native AI framework. Chats, agents, tools, images, audio, and video through one consistent API, in plain Ruby or Rails.
Enterprise-grade AI agent framework with multi-provider LLM management, secure knowledge bases and high-precision RAG, visual workflow orchestration, and mul…
Open Source framework for voice agents, multimodal apps, and realtime AI. Maintained by Daily and the community
Другие проекты из категории «ИИ-агенты» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если RAG-Anything вам не подходит.
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
Соседние проекты из категории «ИИ-агенты» в каталоге, ближайшие по числу звёзд к RAG-Anything — продолжайте изучать полку по обе стороны от него.
Jev Ultrafast — the fastest browser agent from browser-use: one decision-model request per action cycle drives a real browser, MIT
A framework for building agents and services
The official Python SDK for Model Context Protocol servers and clients.
An MCP server that lets Claude, Cursor and Windsurf build n8n workflows for you
Stateful AI agents with memory that learns and improves.
NVIDIA's reference stack for running AI agents more securely inside OpenShell sandboxes
Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.