Flight Query Application

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  Layout Plan

Inspiration

Inspired by the challenge of quickly searching flight options across airlines and dates.

What it does

Allows users to search for flights using natural language, returning flight options ranked by price, duration, etc.

How we built it

Built with Python, AWS Sagemaker, and Pinecone. Integrates data from multiple flight APIs and airline databases. Uses vector search for efficient querying.

Challenges we ran into

• Integrating disparate data sources
• Scaling vector search to large datasets
• Query understanding and result ranking

Accomplishments that we're proud of

• Functional text search interface
• Fast and relevant results from across many airlines (given proper csv data)
• Vector search scaling to millions of flights

What we learned

• Techniques for aggregating travel data
• Optimizing vector search for speed and accuracy
• Query parsing and result ranking algorithms

What's next for Flight Query Application

• Expanding databases to more airlines and routes
• Adding user personalization for improved recommendations
• Integrating booking and travel planning features Let me know if you would like me to elaborate on any section!

Built With

• amadeus
• databricks
• gideon
• jupiter
• pinecone
• python