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Yuxi

A multi-tenant agent platform combining RAG and knowledge graphs
Make enterprise knowledge retrievable, reasoned over, and deliverable by agents

License DeepWiki zread demo

xerrors%2FYuxi | Trendshift

[Docs] · [中文]

arch

*Image generated by GPT-Image-2.

Introduction

Yuxi is an LLM-powered platform for building knowledge-base and knowledge-graph agents. It unifies RAG retrieval, LightRAG knowledge graphs, and LangGraph multi-agent orchestration into a single multi-tenant workspace: administrators configure knowledge bases, models, and permissions, while users chat — in a ChatGPT-like interface — with agents that can mount Skills, MCPs, sub-agents, and sandbox tools, and receive answers with cited sources, graph-based reasoning, and deliverable artifacts.

Core Features

  • 🤖 Agent development — Built on LangGraph, with sub-agents (SubAgents), Skills, MCPs, Tools, and middleware; long-running tasks run asynchronously on a background worker, backed by a sandbox file system for persisting, previewing, and downloading tool artifacts.
  • 📚 Knowledge base (RAG) — Multi-format document parsing (MinerU / PaddleX / OCR), configurable Embedding and Rerank models, knowledge base evaluation, in-app PDF / image preview, and retrieval sources backfilled as chat citations.
  • 🕸️ Knowledge graph — Graph construction and visualization based on LightRAG, with property graph support that feeds directly into agent reasoning.
  • 🏢 Multi-tenancy & permissions — User / department-level access control, unified model provider configuration, and API Key authentication for external system integration.
  • ⚙️ Platform & engineering — Vue + FastAPI architecture, ready-to-run Docker Compose deployment, dark mode, a lightweight LITE startup mode, and production-grade orchestration.

Tech Stack

Layer Technologies
Frontend Vue 3 · Vite · Pinia
Backend FastAPI · LangGraph · ARQ (async worker)
Storage PostgreSQL · Redis · MinIO · Milvus · Neo4j
Doc parsing MinerU · PaddleX · RapidOCR
Deployment Docker Compose

Quick Start

Prerequisites: Docker and Docker Compose installed, plus at least one OpenAI-compatible LLM API.

1. Clone and initialize

git clone --branch v0.7.0.dev0 --depth 1 https://github.com/xerrors/Yuxi.git
cd Yuxi

# Linux/macOS
./scripts/init.sh

# Windows PowerShell
.\scripts\init.ps1

2. Start with Docker

docker compose up --build

3. Open the platform

Once the services are ready, open http://localhost:5173 in your browser and sign in with the admin account generated during initialization.

💡 If you don't need heavy dependencies like knowledge bases / graphs, run make up-lite for a lightweight LITE mode with faster cold starts. See the docs for more deployment details.

Examples and Demo

Home
Home
Dashboard statistics
Dashboard Statistics
Agent configuration
Agent Configuration
Knowledge base invocation
Knowledge Base Invocation
Create knowledge base
Create Knowledge Base
Knowledge base management
Knowledge Base Management
Knowledge graph
Knowledge Graph Visualization
Project docs
Project Documentation
Skills management
Extension Management (Skills)
MCPs management
Extension Management (MCPs)
User and department permissions
User / Department Permission Management
Model provider configuration
Model Provider Configuration

Acknowledgements

Yuxi references and builds on the following excellent open-source projects:

  • LightRAG - Used as the foundation for graph construction and retrieval.
  • DeepAgents - Used as the deep agent framework.
  • DeerFlow - Referenced for Sandbox agent architecture ideas.
  • RAGflow - Referenced for document text chunking strategies.
  • LangGraph - Multi-agent orchestration framework and the core architectural foundation of this project.
  • QwenPaw - Referenced for model configuration and personal file area design.

Contributing

Thanks to all contributors for supporting this project!

Star History

Star History Chart

📄 License

This project is licensed under the MIT License. See LICENSE for details.


If this project helps you, please give us a .