China Unicom's Yuanjing Wanwu Agent Platform is an enterprise-grade, multi-tenant AI agent development platform. It helps users build applications such as intelligent agents, workflows, and rag, and also supports model management. The platform features a developer-friendly license, and we welcome all developers to build upon the platform.

Open-source AI Agent Customer Service Platform. Build AI agent teams with LLM orchestration, RAG knowledge base, multi-channel support, and human collaboration.

Open-source RAG platform with multi-LLM support. Build AI agents that connect to your data, tools, and workflows - no code required.

本项目实现了一个基于多智能体（Multi-Agent）和检索增强生成（Retrieval-Augmented Generation, RAG）技术的客户支持系统。它利用 Python、LangChain 和 LangGraph 构建了一个能够处理各种旅行相关查询的对话式 AI，包括航班预订、租车、酒店预订和行程推荐。还有对接了woocommerce商城进行商品查询，文章查询，表单提交，订单查询等商城功能。

🌊 The leading agent orchestration platform for Claude. Deploy intelligent multi-agent swarms, coordinate autonomous workflows, and build conversational AI systems. Features enterprise-grade architecture, distributed swarm intelligence, RAG integration, and native Claude Code support via MCP protocol. Ranked #1 in agent-based frameworks.

Multi-Agent Retrieval-Augmented Generation (RAG) Customer Support System using Python, LangChain, and LangGraph.

On premise enterprise-grade RAG-powered agentic workflow chatbot platform with multi-provider support

Production-grade multi-agent orchestration engine. Compose agentic workflows from a pluggable catalog of Agents, LLMs, tools, and retrievers. Execute locally with LangGraph or distributed with Temporal. Built-in RAG pipeline for enterprise knowledge retrieval. A2A and MCP protocol support. Visual drag-and-drop blueprint builder.

🎩 AIfred - Multi-Agent AI Assistant with TTS, RAG, Web Research & Voice capabilities. Supports Ollama, vLLM, TabbyAPI. Features AIfred/Sokrates/Salomo debate system.

OpenClaw reimagined in pure Python — autonomous AI agent with memory, RAG, skills, web dashboard, voice input, daemon, and multi-channel support.

A Retrieval-Augmented Generation (RAG) Model-Controller-Provider (MCP) server designed to assist AI agents and developers in understanding and navigating codebases.. It supports incremental indexing and multi-language parsing, enabling LLMs to understand and interact with code.

Powerful Asynchronous Multi agent framework built from scratch in python supporting RAG and MCP compatibilities.

Langflow Customer Support Agent: An LLM-powered, multi-agent chatbot using Langflow, Streamlit, and OpenAI GPT-4o mini, with RAG-based retrieval via AstraDB. It dynamically routes queries to specialized agents (FAQAgent, OrderLookupAgent) for accurate, context-aware responses. Includes vector search and file upload for knowledge expansion.

AI-powered deep research agent running locally via Ollama. Multi-agent pipeline with persistent memory, RAG, and GraalVM native image support.

The MCP-RAG project is an AI agent framework based on the Multi-Context Protocol that connects various data sources (MySQL, documents, RAG search) with LLMs. It supports HTTP API, SSE chat, an MCP router, batch workers, and a React + Tailwind frontend.

🤖 Agentic RAG - An intelligent document assistant with semantic chunking, hybrid search (vector + BM25), multi-format support (PDF, Word, CSV, Excel), and multi-channel bots (Telegram, WhatsApp). Built with FastAPI, React, PostgreSQL/pgvector, and LangChain.

Dynamic Agent is a Rust-based framework for building Retrieval-Augmented Generation (RAG) AI agents with multi-LLM and multi-vector store support, featuring WebSocket communication, caching, and flexible configuration.

AIxAI V3 is an intelligent agent generator with MCP server support, integrating seamlessly with AI IDEs. It uses RAG and multi-agent reasoning to build and manage Pydantic AI agents using local or cloud LLMs.

Agent4GoMicroservice: A Go-based multi-agent microservice solution. Combines LLM tool-calling, Eino workflow orchestration, and Milvus-powered RAG for cross-domain automation (business tasks + knowledge queries). Supports dynamic agent registration & MCP integration.

A RAG styled chatbot with AI Search and Multi-LLM Support, including Agents, Web Scraping and a Vector Database for Text Embedding. Built on a ViteJS + React frontend with 2 NodeJS Servers

This is an AI agent application platform built based on the ReAct pattern, integrating multiple AI capabilities including Retrieval-Augmented Generation (RAG), multi-model dialogue, multi-turn conversation memory, and autonomous planning. The platform provides a user-friendly frontend interface, supporting services such as AI Travel Advisor and all

Enterprise LangChain platform with multi-agent collaboration, advanced RAG, local LLM support, and modern web interface. Production-ready AI orchestration for research, coding, and data analysis.

This project implements a multi-agent system (Agent Swarm) that processes user requests through specialized agents working together. The system includes a Router Agent, Knowledge Agent with RAG capabilities, Customer Support Agent with custom tools, and a Personality Layer for human-like responses.

🤖 Production-ready multi-agent AI system orchestrating specialized agents (Planner, Coder, Reviewer, Debugger, Optimizer) with RAG, function calling, and multi-LLM support. Built with FastAPI, React, ChromaDB, GPT-4 & Claude.

User-Centered Banking Assistant: A cooperative multi-agent system that enhances customer experience through behavior analysis, personalized recommendations, and RAG-based conversational support. Agents share insights and adapt to user preferences in a continuous feedback loop.

Automated AI calling agent for businesses with multi-language support, human-like real-time voice interaction, RAG-powered knowledge, and intelligent call management with automated Plivo-powered outbound calling

An AI-powered customer support agent using RAG, LangFlow, and Multi-Agent systems. Handles order management, FAQs, and advanced interactions with a Streamlit interface and LangFlow editor.

An AI-powered Multi-Agent Research Assistant built with Generative AI, Agentic AI, LangGraph, RAG, Persistent Memory, FAISS, and FastAPI. It supports multi-format uploads, intelligent PDF analysis, and expert-like Q&A via Researcher, Summarizer, Critic, and Editor agents—offering deep, contextual, and interactive research insights.

The first of a kind "AGENT AS A BACKEND" : Advanced AI/ML Agent Framework with TypeScript support, multi-model capabilities, vision controls, and comprehensive AI/ML model support including LLM, SLM, MLM, Vision, ASR, TTS, RL, GNN, RNN, CNN, GAN, Diffusion, Transformer, MLP, Autoencoder, BERT, RAG, Hybrid, Foundation, and fine-tuning

AI Customer Support Agent with RAG + Voice A fully local, privacy-focused AI customer support system powered by open-source models. It supports multi-turn conversations, PDF/manual search (RAG), product recommendations, FAQ reasoning, and voice input/output using local STT + TTS. Built with Mistral 7B GGUF, FAISS, Whisper Tiny, Coqui TTS, FastAPI.