Agentic AI Application

A sophisticated AI application built using LangGraph framework for creating autonomous AI agents with complex workflows.

Overview

This project demonstrates the implementation of agentic AI using the LangGraph framework, enabling the creation of autonomous agents that can perform complex tasks through structured workflows and decision-making processes.

Features

• Task-oriented AI agents
• Dynamic workflow management
• Multi-step reasoning capabilities
• State management and persistence
• Event-driven agent interactions

Prerequisites

• Python 3.8+
• LangGraph
• LangChain
• OpenAI API key (or alternative LLM provider)

Installation

# Clone the repository
git clone https://github.com/yourusername/agentic-ai-app.git

# Install dependencies
pip install -r requirements.txt

# Set up environment variables
cp .env.example .env

Configuration

1. Add your API keys to .env:

OPENAI_API_KEY=your_api_key_here

2. Configure agent parameters in config.yaml

Usage

from agentic_ai_app import AgentWorkflow

# Initialize workflow
workflow = AgentWorkflow()

# Execute agent tasks
result = workflow.run("your task description")

Architecture

src/
├── agents/         # Agent definitions
├── workflows/      # Workflow configurations
├── utils/         # Helper functions
└── config/        # Configuration files

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

MIT License - See LICENSE for details

Contact

Your Name - @ShamserulAwsGeek

Project Link: https://github.com/yourusername/agentic-ai-app