LangGraph Agentic AI Chatbot

This project is a modular AI chatbot framework that allows dynamic interaction with multiple LLM providers using LangGraph, LangChain, Streamlit, and FastAPI. It also optionally integrates search tools such as Tavily for online augmentation.

The system consists of:

• Streamlit Frontend for user interaction
• FastAPI Backend to serve AI agent responses via REST API
• LangGraph-powered React Agent with support for Groq, OpenAI models, and Tavily search integration

Features

• Dynamically select LLM Provider (Groq or OpenAI)
• Dynamically select available LLM models
• Optional web search augmentation using Tavily
• Custom system prompts per user session
• Stateless API endpoint for easy integration
• Fully interactive Streamlit user interface
• Modular backend logic via reusable agent creation functions

Supported Models

• Groq: llama-3.3-70b-versatile, mixtral-8x7b-32768
• OpenAI: gpt-4o-mini

Project Structure

File/Folder	Description
main.py	FastAPI Backend
frontend.py	Streamlit Frontend
ai_agent.py	Agent Creation Logic
backend.py	Pydantic Schema Validation
.env	Environment variables (API Keys)
requirements.txt	Python dependencies list
README.md	Project documentation

Setup Instructions

1. Clone the repository

git clone https://github.com/your-username/langgraph-agentic-chatbot.git
cd langgraph-agentic-chatbot

2. Setup virtual environment

python -m venv venv
source venv/bin/activate  # Linux/Mac
venv\Scripts\activate     # Windows

3. Install dependencies

pip install -r requirements.txt

4. Setup environment variables

Create a .env file in the project root:

GROQ_API_KEY=your_groq_api_key
OPENAI_API_KEY=your_openai_api_key
TAVILY_API_KEY=your_tavily_api_key

5. Run Backend Server

python backend.py

6. Run Streamlit Frontend

streamlit run frontend.py

7. Test API (Swagger UI)

Visit:

http://127.0.0.1:9999/docs

Dependencies

• Python 3.10+
• LangChain
• LangGraph
• LangChain-Groq
• LangChain-OpenAI
• LangChain-Tavily
• FastAPI
• Pydantic
• Streamlit
• Uvicorn
• Requests
• python-dotenv

Notes

• Make sure you have valid API keys for all providers you want to use.
• Tavily is optional and only used when web search is enabled.
• Backend and frontend communicate over HTTP (localhost).