AI Travel Studio: Multi-Agent Orchestration 🌟

AI Travel Studio is a professional-grade Multi-Agent AI Travel Planner built using LangChain, LangGraph, and Groq (Llama 3.3). It orchestrates a team of specialized AI agents to transform simple natural language requests into comprehensive, high-quality travel itineraries.

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🚀 Features

• Multi-Agent Collaboration: 4 specialized agents (Coordinator, Activity Specialist, Logistics Expert, Lead Curator) working in sync.
• Shared State Management: Agents communicate via a shared context passed through a LangGraph workflow.
• Premium UI: Modern, glassmorphism-inspired React frontend with real-time progress tracking.
• Lightning Fast: Powered by Groq's high-speed Llama-3 inference engine.
• Structured Output: Sophisticated parsing of natural language into structured JSON data.

🏗️ Architecture

The system uses a Directed Acyclic Graph (DAG) to manage agent execution:

1. Coordinator Agent: Parses the user's intent, destination, and duration into structured JSON.
2. Activity Specialist: Research and suggests high-quality tours and attractions based on user interests.
3. Logistics Expert: Handles neighborhood recommendations and local transport methods.
4. Lead Curator: Compiles all research into an elegant, master Markdown itinerary.

🛠️ Tech Stack

• Framework: LangChain & LangGraph
• LLM: Groq (Llama 3.3 70B)
• Backend: FastAPI (Python)
• Frontend: React (Vanilla JS/Tailwind CSS)
• State Management: Python TypedDict

⚙️ Setup & Installation

Prerequisites

• Python 3.9+
• A Groq API Key (Get one at console.groq.com)

Installation

1. Clone the repository:

   git clone https://github.com/ANUPAM4545/Multi--Agent-System.git
   cd Multi--Agent-System

2. Set up a virtual environment:

   python3 -m venv venv
   source venv/bin/activate

3. Install dependencies:

   pip install -r requirements.txt

4. Configure Environment Variables: Create a .env file in the root directory:

   GROQ_API_KEY=your_api_key_here

🏃 Running the Application

Option 1: Full-Stack (Web UI)

1. Start the FastAPI server:

   python backend.py

2. Open your browser to http://localhost:8000.

Option 2: Terminal Only

Run the agent orchestration directly in your terminal:

python multi_agent_system.py

🎥 Project Walkthrough

A detailed presentation script and walkthrough guide can be found in walkthrough.md.

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Built with ❤️ for the AI Agentic Coding Assignment.