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 This project demonstrates a Python CLI that leverages the LFM2.5-1.2B-Thinking model to help users find and book plane tickets through multi-step reasoning and tool calling. Flight Search Assistant Demo

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Quickstart

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1. Verify uv installation

Check that you have uv available on your system: 
uv --version
If this fails, install uv following these instructions.

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2. Clone and build the project

Clone the repository and install dependencies: 
git clone https://github.com/Liquid4All/cookbook.git
cd cookbook/examples/flight-search-assistant
uv sync

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3. Run example queries

The assistant accepts natural language requests through the command-line interface: Simple flight availability search: 
uv run flight_search.py --query "What flights are available from New York to Paris on 2026-01-19?"
Direct booking request: 
uv run flight_search.py --query "Book flight AA495 for 2026-02-04"
Multi-step workflow (search then book): 
uv run flight_search.py --query "Book the cheapest flight from Barcelona to Belgrade on 2026-01-31"
Complex reasoning task: 
uv run flight_search.py --query "Book the cheapest flight from Barcelona to a US city on the East Coast that is not NYC on 2026-02-14"
The implementation uses mocked flight data for demonstration purposes, though it supports integration with real APIs like Amadeus, Skyscanner, or Kiwi for production deployment.

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Future Development

The roadmap includes:
  • Adding evaluation datasets
  • Implementing performance improvements through GRPO fine-tuning with verifiable rewards

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