Langchain-Chatchat（原Langchain-ChatGLM）基于 Langchain 与 ChatGLM, Qwen 与 Llama 等语言模型的 RAG 与 Agent 应用 | Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM, Qwen and Llama) RAG and Agent app with langchain

A project-based course repository for developing AI agents using LangChain v1+ and LangGraph: search agents, RAG systems, reflection agents, and code interpreters.

Flock is a workflow-based low-code platform for rapidly building chatbots, RAG, and coordinating multi-agent teams, powered by LangGraph, Langchain, FastAPI, and NextJS.（Flock 是一个基于workflow工作流的低代码平台，用于快速构建聊天机器人、RAG、Agent和Muti-Agent应用，采用 LangGraph、Langchain、FastAPI 和 NextJS 构建。）

This repository contains advanced LLM-based chatbots for Q&A using LLM agents, and Retrieval Augmented Generation (RAG) and with different databases. (VectorDB, GraphDB, SQLite, CSV, XLSX, etc.)

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

JRVS AI Agent with JARCORE autonomous coding engine - RAG knowledge base, web scraping, calendar, code generation. Powered by whatever local AI you choose.

Launching the "Agent Creation Toolkit", providing developers with an intuitive and efficient Development Environment, supporting the rapid construction of intelligent agents. The toolkit will integrate RAG (Retrieval-Augmented Generation) Knowledge Base and LLMOps toolchain.

A modular, skill-based autonomous Security Operations Center (SOC) agent that monitors OpenSearch/Elasticsearch data, builds RAG-based behavioral memory, and validates real-time anomalies using LLMs.

RAFT, or Retrieval-Augmented Fine-Tuning, is a method comprising of a fine-tuning and a RAG-based retrieval phase. It is particularly suited for the creation of agents that realistically emulate a specific human target.

A fully custom chatbot built with Agentic RAG (Retrieval-Augmented Generation), combining Gemini models with a local knowledge base for accurate, context-aware, and explainable responses. Features a lightweight, dependency-free frontend and a streamlined FastAPI backend for complete control and simplicity.

RAGElo is a set of tools that helps you selecting the best RAG-based LLM agents by using an Elo ranker

🌊 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.

An agent based LLM assistant that extends RAG with batch entity extraction and SQL querying to improve performance on multi-step and analytical questions.

MCP server for AI agent for cybersecurity: automate assessment of documents, questionnaires & reports. Multi-format parsing, RAG knowledge base,Risks, compliance gaps, remediations.

A full-stack ai agent chat project, built with langgraph+fastapi+nextjs, supporting tool invocation and RAG knowledge base

The GPT-RAG Orchestrator service is an agentic orchestration layer built on Microsoft Foundry Agent Service and the Microsoft Agent framework. It enables agent-based RAG workflows by coordinating multiple specialized agents to collaboratively generate accurate, context-aware responses for complex user queries.

Bedrock Knowledge Base and Agents for Retrieval Augmented Generation (RAG)

A travel agent based on Qwen2.5, fine-tuned by SFT + DPO/PPO/GRPO using traveling question-answer dataset, a mindmap can be output using the response. A RAG system is build upon the tuned qwen2, using Prompt-Template + Tool-Use + Chroma embedding database + LangChain

WebRAgent is a retrieval-augmented generation (RAG) web application featuring agent-based query decomposition, vector search with Qdrant, and integration with leading LLM providers for context-rich, dynamic responses.

An agentic AI for tech career coaching 程序员技术学习AI智能体 (based on JoyAgent-JDGenie with local RAG and code analyzing)

Sample for context-aware Agentic RaG, Q&A with multi-source verification, and self-curating knowledge base. Powered by Azure AI Foundry Agent Service, Azure AI Search with agentic retrieval and query rewrite, Semantic Kernel and LangGraph agents running in Azure Container Apps, and ready for Copilot Studio

Confidence-Weighted Multi-Agent Retrieval-Augmented Generation (CW-MARAG) — a contradiction-aware RAG system that uses multiple retrieval agents with confidence-based arbitration to generate grounded, non-hallucinated answers from PDFs.

An interactive RAG agent built with LangChain and MongoDB Atlas. Manage your knowledge base, switch embedding models, and tune retrieval parameters on-the-fly through a conversational interface.

📚 AI-powered research reading workbench. Project-based paper Q&A with Hybrid RAG, multi-agent workflows (ReAct/Plan-Act/RePlan), long-term memory, and traceable evidence. Built with LangChain + LangGraph + Streamlit.

这是一个结合了RAG（Retrieval-Augmented Generation）和网络搜索功能的Agent项目，能够同时检索本地知识库和进行网络搜索，为用户提供全面的信息服务。项目通过API调用大语言模型进行推理，同时使用本地的bce-embedding-base_v1嵌入模型和Chroma向量数据库处理本地知识库检索，并采用ms-marco-MiniLM-L-6-v2交叉编码模型进行结果重排序。支持多角度查询和抽象查询等高级检索策略，提升检索准确性和回答质量。

A complete, driver based RAG pipeline for Laravel with pgvector & sqlite-vec, streaming, agentic retrieval, hybrid search, evals, MCP server, Filament admin.

Retrieval Augmented Generation-based Agentic CrewAI

A Tavily-based agent generating evaluation datasets for web search RAG systems.

ArXiv Agent is a terminal-based intelligent assistant designed for researchers and engineers who want to stay on top of the latest AI trends without drowning in PDFs. It combines daily digests, RAG-powered chat, and automated implementation into a single, cohesive workflow.

A sophisticated Retrieval-Augmented Generation (RAG) system that combines advanced document processing with intelligent retrieval mechanisms to deliver accurate, context-aware responses from multimodal data sources.