# LlamaIndex destination brief

- **Agent pattern:** `FunctionAgent` comparison
- **Search surfaces:** Travel explore, web, and maps
- **Saved artifact:** `llamaindex-destination-brief.md`


# What you'll build

A LlamaIndex `FunctionAgent` that discovers reachable cities for a short remote-work trip, researches practical context, checks local coworking access, and recommends one destination with explicit tradeoffs.

**Default brief:** Starting from JFK, find three promising destinations for a four-day remote-work trip and recommend one with evidence and source URLs.


# How the agent works

1.  **Explore reachable cities.** Travel explore search supplies indicative flight options from the origin airport.
2.  **Test practical fit.** Web search checks remote-work facts and maps search verifies nearby coworking access.
3.  **Compare explicitly.** The `FunctionAgent` gathers evidence from every relevant tool before choosing one destination.


# Core agent setup

This excerpt shows the LlamaIndex `FunctionAgent` and its required first tool call. The complete script also configures the model, validates credentials, sets timeouts, and saves the destination brief.

``` python
agent = FunctionAgent(
    tools=[
        travel_explore_search(provider="llamaindex", api_key=api_key),
        web_search(
            provider="llamaindex",
            allowed_engines=["google_light", "bing"],
            api_key=api_key,
        ),
        maps_search(provider="llamaindex", api_key=api_key),
    ],
    llm=llm,
    initial_tool_choice="required",
    streaming=False,
    system_prompt=(
        "Gather evidence from each relevant tool, make the comparison explicit, "
        "and include source URLs."
    ),
)
result = await agent.run(PROMPT)
```

[View the complete `main.py` →](https://github.com/serpapi/serpapi-search-tools-python/blob/main/cookbook/llamaindex/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[llamaindex]' --with python-dotenv --with llama-index-llms-openai \
  cookbook/llamaindex/main.py
```

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

**Tool use starts immediately:** The agent sets `initial_tool_choice="required"`, preventing a plausible-sounding destination answer before live travel evidence is collected.


# Inspect the result

The recipe writes `cookbook-output/llamaindex-destination-brief.md`. Expect three candidate destinations, indicative travel evidence, practical remote-work context, coworking access, tradeoffs, one recommendation, and source URLs.

Replace the origin, trip length, or decision criteria through `COOKBOOK_PROMPT`.


# SerpApi tools used

[travel_explore_search](../../reference/travel_explore_search.md#serpapi_search_tools.travel_explore_search) identifies reachable destination candidates, [web_search](../../reference/web_search.md#serpapi_search_tools.web_search) checks practical remote-work facts, and [maps_search](../../reference/maps_search.md#serpapi_search_tools.maps_search) verifies local coworking access. Together they help the agent compare reachability, practical fit, and nearby facilities as separate decision criteria.

**Framework pattern:** The `FunctionAgent` workflow follows LlamaIndex's basic agent example and uses three complementary SerpApi tools.

- [Open the runnable recipe](https://github.com/serpapi/serpapi-search-tools-python/tree/main/cookbook/llamaindex)
- [View LlamaIndex's source example](https://github.com/run-llama/llama_index/blob/main/docs/examples/agent/agent_workflow_basic.ipynb)