# Pydantic AI visual location scout

- **Agent pattern:** Typed cross-verification
- **Search surfaces:** Images, maps, and web
- **Saved artifact:** `pydantic-ai-location-scout.md`


# What you'll build

A Pydantic AI location scout that finds visually distinct campaign locations, verifies the actual places, and checks practical access or restriction details before it makes a recommendation.

**Default brief:** Scout three Portland, Oregon locations for an outdoor lifestyle campaign. Return visual motifs, logistics, risks, and source URLs.


# How the agent works

1.  **Find visual directions.** Image search supplies candidate locations and the visual motifs that make them distinct.
2.  **Verify the place.** Maps search confirms location details, access context, and nearby landmarks.
3.  **Check practical claims.** Web search validates restrictions or logistics so the agent never infers permission from an image.


# Core agent setup

This excerpt shows Pydantic AI's typed, cross-verification tool set. The full script also configures the OpenAI model, validates keys, handles the result, and saves the scouting brief.

``` python
agent = Agent(
    model,
    instructions=(
        "Use image search for visual evidence, maps for place facts, "
        "and web search for practical verification."
    ),
    tools=[
        images_search(provider="pydantic-ai"),
        maps_search(provider="pydantic-ai"),
        web_search(
            provider="pydantic-ai",
            allowed_engines=["google_light", "bing"],
        ),
    ],
)
result = agent.run_sync(PROMPT)
```

[View the complete `main.py` →](https://github.com/serpapi/serpapi-search-tools-python/blob/main/cookbook/pydantic-ai/main.py)


# Run the recipe

Set `SERPAPI_API_KEY` and `OPENAI_API_KEY` in the repository-root `.env`, then run:

``` bash
uv run --isolated --no-project --with 'serpapi-search-tools[pydantic-ai]' --with python-dotenv cookbook/pydantic-ai/main.py
```

Optional controls: `OPENAI_MODEL`, `COOKBOOK_PROMPT`, and `COOKBOOK_OUTPUT_DIR`.

**Typed tools do different jobs:** The instructions prevent visual search from becoming a proxy for place facts or access permission; every important claim must cross the appropriate tool boundary.


# Inspect the result

The recipe writes `cookbook-output/pydantic-ai-location-scout.md`. Expect three candidate locations with visual motifs, verified place details, nearby landmarks, logistics, restrictions or risks, and source URLs.

Set `COOKBOOK_PROMPT` to scout a different city, campaign, or creative brief.


# SerpApi tools used

[images_search](../../reference/images_search.md#serpapi_search_tools.images_search) finds visual directions, [maps_search](../../reference/maps_search.md#serpapi_search_tools.maps_search) verifies place details and nearby landmarks, and [web_search](../../reference/web_search.md#serpapi_search_tools.web_search) checks restrictions or practical context. Using the tools together helps the agent avoid treating an image as proof of access, dimensions, or permission.

**Framework pattern:** The focused typed-tool setup follows Pydantic AI's weather agent example and uses SerpApi image, maps, and web search.

- [Open the runnable recipe](https://github.com/serpapi/serpapi-search-tools-python/tree/main/cookbook/pydantic-ai)
- [View Pydantic AI's source example](https://github.com/pydantic/pydantic-ai/blob/main/docs/examples/weather-agent.md)