> ## Documentation Index
> Fetch the complete documentation index at: https://docs.liquid.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Flight search assistant with tool calling

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  Browse the complete example on GitHub
</Card>

This project demonstrates a Python CLI that leverages the [LFM2.5-1.2B-Thinking](/lfm/models/lfm25-1.2b-thinking) model to help users find and book plane tickets through multi-step reasoning and tool calling.

![Flight Search Assistant Demo](https://raw.githubusercontent.com/Liquid4All/cookbook/main/examples/flight-search-assistant/media/demo.gif)

## Quickstart

### 1. Verify uv installation

Check that you have `uv` available on your system:

```bash theme={"theme":{"light":"github-light","dark":"github-dark"}}
uv --version
```

If this fails, [install `uv` following these instructions](https://docs.astral.sh/uv/getting-started/installation/).

### 2. Clone and build the project

Clone the repository and install dependencies:

```bash theme={"theme":{"light":"github-light","dark":"github-dark"}}
git clone https://github.com/Liquid4All/cookbook.git
cd cookbook/examples/flight-search-assistant
uv sync
```

### 3. Run example queries

The assistant accepts natural language requests through the command-line interface:

**Simple flight availability search:**

```bash theme={"theme":{"light":"github-light","dark":"github-dark"}}
uv run flight_search.py --query "What flights are available from New York to Paris on 2026-01-19?"
```

**Direct booking request:**

```bash theme={"theme":{"light":"github-light","dark":"github-dark"}}
uv run flight_search.py --query "Book flight AA495 for 2026-02-04"
```

**Multi-step workflow (search then book):**

```bash theme={"theme":{"light":"github-light","dark":"github-dark"}}
uv run flight_search.py --query "Book the cheapest flight from Barcelona to Belgrade on 2026-01-31"
```

**Complex reasoning task:**

```bash theme={"theme":{"light":"github-light","dark":"github-dark"}}
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"
```

<Note>
  The implementation uses mocked flight data for demonstration purposes, though it supports integration with real APIs like Amadeus, Skyscanner, or Kiwi for production deployment.
</Note>

## Future Development

The roadmap includes:

* Adding evaluation datasets
* Implementing performance improvements through GRPO fine-tuning with verifiable rewards

## Need help?

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