This project is an AI-powered travel planning assistant. It uses an agentic workflow, a local vector database (FAISS), and a Streamlit-based UI to generate detailed travel itineraries based on user inputs like destination, travel dates, interests, and budget.
- 🧠 Agentic AI workflow with tool usage
- 🔍 Retrieval-Augmented Generation (RAG) via FAISS-based local knowledge
- 📅 Personalized itineraries based on dynamic user input
- 💻 Streamlit UI frontend for a smooth experience
- 🌍 Works offline with local city datasets under
/data
Agentic_AI/ │ ├── data/ # Local city knowledgebase (Milan, Tokyo, etc.) ├── .env # API keys & environment config ├── build_vector_store.py # Builds FAISS vector store from data ├── sample_db_creation.py # Initializes sample RAG database ├── travel_agent_task.py # Core agentic planning logic ├── travel_plan_utils.py # Utilities for plan formatting and structure ├── travel_requirements.txt # Text file of required user input fields ├── planner_app.py # Streamlit UI runner ├── requirements.txt # Python dependencies └── README.md # You’re here!
You can try the live version here:
👉 Agentic Travel Planner on Streamlit