Data-Agent：从 0 到 1 构建 Text2SQL 智能体实战教程，覆盖 StateGraph 编排、双重 RAG、关系图谱、HITL 人工确认、SQL 自动纠错、Python Docker 沙盒执行与 A2A + SSE 流式交互。

This project demonstrates a complete workflow that uses 'LangGraph', a stateful orchestration framework to streamline the coordination and the integration of Large Language Models (LLMs) like OpenAI’s GPT-4o-mini with real-time search APIs like ‘Google Search’.

Langgraph Agentic Chatbot

Project to learn and understand LangGraph basics

This is a simple chatbot project built using LangGraph, a graph-based framework for orchestrating LLMs, and powered by the Groq API with the LLaMA3-8B-8192 model. The chatbot demonstrates how to structure conversational flows using state graphs and message reducers for memory. Ideal for learning how to integrate LLMs into modular applications.

A multi-agent research assistant built using LangGraph

A lightweight, modular LLM agent framework built using LangGraph, powered by Groq's ultra-fast LLaMA3-8B model. This project demonstrates how to create a goal-oriented agent that breaks down a user prompt into sub-tasks, executes each one using LLM reasoning, and summarizes the outcome — all within a structured graph-based flow.

This is simple agentic chatbot with one tool Node and LLM.