✈️ Way-wise-AI — A Multi-Agent Travel Planner with LangGraph

An open-source AI travel planner that turns a natural-language trip request into a practical travel plan with flight suggestions, hotel ideas, and a day-by-day itinerary. The project uses a multi-agent workflow built with LangGraph, LangChain, and FastAPI.

Planning a trip usually means jumping between multiple websites, tools, and spreadsheets. This project brings that flow into one experience by combining:

• a flight-search agent,
• a hotel-research agent,
• an itinerary-planning agent, and
• a final response agent,

all coordinated through a LangGraph workflow.

• ✈️ Flight research using AviationStack
• 🏨 Hotel suggestions using Tavily search
• 🧠 Multi-agent orchestration with LangGraph
• 📝 Structured travel itinerary generation
• 🌐 FastAPI backend with a simple web interface
• 💾 Conversation state persistence using PostgreSQL
• ⚡ LLM-powered responses with Groq

• Python 3.10+
• FastAPI
• Jinja2 + HTML/CSS/JavaScript frontend
• LangGraph
• LangChain
• Groq LLMs
• PostgreSQL
• Tavily API
• AviationStack API

.
├── app.py                # FastAPI app entry point
├── backend.py            # LangGraph travel workflow
├── requirements.txt      # Python dependencies
├── static/               # Static frontend assets
├── templates/            # HTML templates
└── tools/                # Flight and web search integrations

Before running the project locally, make sure you have:

• Python 3.10 or newer installed
• PostgreSQL running and accessible
• API keys for:
  • Groq
  • Tavily
  • AviationStack

Create a .env file in the project root with the following variables:

DATABASE_URL=postgresql://user:password@localhost:5432/travel_db
GROQ_API_KEY=your_groq_api_key
AVIATIONSTACK_API_KEY=your_aviationstack_api_key
TAVILY_API_KEY=your_tavily_api_key
DEFAULT_ORIGIN_IATA=DAC

python -m venv .venv
source .venv/bin/activate   # On Windows: .venv\Scripts\activate
pip install -r requirements.txt

Start the FastAPI server:

python app.py

Then open your browser at:

http://127.0.0.1:8000/

• GET /health - Health check
• POST /api/travel - Submit a travel request

Example request:

curl -X POST http://127.0.0.1:8000/api/travel \
  -H "Content-Type: application/json" \
  -d '{"message":"Plan a 3-day trip to Tokyo with a budget of $1200"}'

1. The user submits a travel request.
2. The flight agent gathers flight-related information.
3. The hotel agent searches for accommodation suggestions.
4. The itinerary agent creates a practical travel plan.
5. The final agent formats the result into a polished response.

Contributions are welcome. If you want to improve the app, add new travel features, or fix issues:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Open a pull request

This project is built with the help of modern LLM tooling and travel APIs, and it is intended as a practical example of combining LangGraph agents with real-world applications.