🤖 Conversation Agent using Langgraph

📋 Overview

This project implements a conversational agent (chatbot) using Langgraph, a library built on top of LangChain for creating robust and stateful multi-turn applications. The agent maintains context across conversations and demonstrates core principles for building interactive AI assistants.

📋 Prerequisites

• 🐍 Python 3.12+
• 🔑 OpenAI API key (or compatible API provider)
• 📦 Git

🚀 Quick Start

1️⃣ Clone the Repository

git clone https://github.com/arnabd64/Chatbot-Langgraph.git
cd Chatbot-Langgraph

2️⃣ Environment Setup

Create a .env file in the project root:

# Required
OPENAI_API_KEY="your-openai-api-key-here"
MODEL_NAME="gpt-4o-mini"

# Optional - for OpenAI compatible providers
OPENAI_API_BASE=""

# Optional - for Langsmith tracing
LANGSMITH_TRACING=true
LANGSMITH_PROJECT="Langgraph"
LANGSMITH_ENDPOINT="https://api.smith.langchain.com"
LANGSMITH_API_KEY="your-langsmith-api-key-here"

3️⃣ Installation Options

Choose one of the following methods:

🐍 Option A: Using pip (Standard)

# Create and activate virtual environment
python -m venv .venv

# Activate environment
source .venv/bin/activate     # Linux/macOS
# OR
.venv\Scripts\activate        # Windows

# Install dependencies
pip install -e .

# Run the server
python main.py

⚡ Option B: Using uv (Recommended)

# Install dependencies
uv sync

# Run the server
uv run python main.py

🐳 Option C: Using Dev Container

Requires Visual Studio Code with Dev Containers extension:

1. Open VS Code: code .
2. Press F1 and search for "Dev Containers: Rebuild and Reopen in Dev Containers"
3. Run: uv run python main.py

4️⃣ Access the Application

• 🌐 Web Interface: Visit http://localhost:8000/app
• 📖 API Documentation: Visit http://localhost:8000/docs

🔧 API Usage

🆔 Generate Session ID

Each chat session requires a unique session ID:

curl -X GET "http://localhost:8000/chat/id" -H "accept: text/plain"

Response:

dbaed28e-cf61-457a-b034-2bd48ab5424a

💬 Send Messages

Send messages using the session ID:

curl -X POST "http://localhost:8000/chat/dbaed28e-cf61-457a-b034-2bd48ab5424a" \
  -H "accept: application/json" \
  -H "Content-Type: application/json" \
  -d '[
    {
      "role": "human",
      "content": "Hi"
    }
  ]'

Response:

{
  "error": "false",
  "data": [
    {
      "role": "human",
      "content": "Hi"
    },
    {
      "role": "ai",
      "content": "Hello! How can I assist you today?"
    }
  ]
}

📝 Message Format

Each message is a JSON object with:

• role: Message sender ("system", "human", or "ai")
• content: Message text

✨ Features

• 🔄 Stateful Conversations: Maintains context across multiple turns
• 🛠️ FastAPI Integration: REST API for easy integration
• 🌐 Web Interface: Built-in chat interface
• 🔒 Session Management: Isolated chat sessions using UUIDs
• 🔧 OpenAI Compatible: Works with OpenAI and compatible providers
• 📊 Langsmith Integration: Optional tracing and monitoring