A sophisticated travel planning assistant powered by multi-agent collaboration and vector search capabilities. This project demonstrates the power of specialized AI agents working together to provide comprehensive travel planning assistance.
- 🚀 Multi-Agent Collaboration – Specialized agents work together, seamlessly passing context to one another
- 🔧 Customizable Handoff Tools – Built-in mechanisms for smooth communication between agents
- 📂 LanceDB for Data Retrieval – High-performance vector search and full-text search for accurate and fast information retrieval
- 🌍 Travel Agent Use Case – Agents collaborate to handle different aspects of travel planning, ensuring efficient and context-aware responses
The Swarm Style Travel Planner uses a sophisticated multi-agent system where different specialized agents handle various aspects of travel planning:
- Flight Search Agent: Handles flight-related queries and searches
- Hotel Search Agent: Manages hotel and accommodation searches
- Coordination Agent: Orchestrates communication between agents and maintains context
The system uses LanceDB for efficient vector search capabilities, allowing for semantic understanding of user queries and fast retrieval of relevant travel information.
- Launch the application using
streamlit run app.py - Enter your travel-related query in the chat interface
- The system will automatically:
- Parse your requirements
- Route queries to appropriate specialized agents
- Provide comprehensive travel suggestions
- Maintain context throughout the conversation
Example queries:
- "Find me flights from New York to London next month"
- "I need a hotel in Paris near the Eiffel Tower"
- "Plan a week-long trip to Tokyo with flights and hotels"
Experience the Swarm Style Travel Planner directly on Google Colab:
