# google-aistudio-tools (Google AI Studio Tools)

This example demonstrates how to use Google AI Studio's function calling, search capabilities, code execution, and URL context features with promptfoo.

You can run this example with:

```bash
npx promptfoo@latest init --example google-aistudio-tools
cd google-aistudio-tools
```

## Prerequisites

- Google AI Studio API key set as `GOOGLE_API_KEY` in your environment

## Overview

This example shows how to:

1. **Function Calling**: Use Gemini to invoke predefined functions based on user queries
2. **Google Search Integration**: Get up-to-date information from the web using Gemini models with search grounding
3. **Code Execution**: Execute Python code to solve computational problems
4. **URL Context**: Extract and analyze content from web URLs

## Function Calling Example

The function calling configuration (`promptfooconfig.yaml`) demonstrates:

- Defining a weather function in `tools.json`
- Validating that Gemini models correctly produce structured function calls
- Testing that the location parameter matches the user's query

Run with:

```bash
promptfoo eval -c promptfooconfig.yaml
```

## Search Grounding Example

The search grounding configuration (`promptfooconfig.search.yaml`) demonstrates:

- Using Gemini 2.5 Flash with Google Search as a tool
- Using Gemini 2.5 Pro with thinking capabilities and Search grounding
- Using Gemini 1.5 Flash with dynamic retrieval configuration
- Testing queries that benefit from real-time web information
- Verifying responses include relevant information

Run with:

```bash
promptfoo eval -c promptfooconfig.search.yaml
```

## Code Execution Example

The code execution configuration (`promptfooconfig.codeexecution.yaml`) demonstrates:

- Testing computational problems that require code to solve
- Verifying that the answer is correct from the code execution

Run with:

```bash
promptfoo eval -c promptfooconfig.codeexecution.yaml
```

## URL Context Example

The URL context configuration (`promptfooconfig.urlcontext.yaml`) demonstrates:

- Using Gemini to extract and analyze content from web URLs
- Combining URL context with search capabilities

Run with:

```bash
promptfoo eval -c promptfooconfig.urlcontext.yaml
```

## Example Files

- `promptfooconfig.yaml`: Function calling configuration
- `promptfooconfig.search.yaml`: Search grounding configuration
- `promptfooconfig.codeexecution.yaml`: Code execution configuration
- `promptfooconfig.urlcontext.yaml`: URL context configuration
- `tools.json`: Function definition for the weather example

## Notes on Google Search Integration

When using Search grounding in your own applications:

- The API response includes search metadata and sources
- Google requires displaying "Google Search Suggestions" in user-facing apps
- Models can retrieve current information about events, prices, and technical updates

### Search Methods

This example demonstrates three approaches to search:

1. **Search as a tool** (Gemini 2.5): Allows the model to decide when to use search

   ```yaml
   tools:
     - googleSearch: {}
   ```

2. **Search with thinking** (Gemini 2.5): Adds thinking capabilities for better reasoning

   ```yaml
   generationConfig:
     thinkingConfig:
       thinkingBudget: 1024
   tools:
     - googleSearch: {}
   ```

3. **Dynamic retrieval** (Gemini 1.5): Controls when to use search with threshold settings
   ```yaml
   tools:
     - googleSearchRetrieval:
         dynamicRetrievalConfig:
           mode: 'MODE_DYNAMIC'
           dynamicThreshold: 0 # 0 = always use search, 1 = never use search
   ```

## Further Resources

- [Google AI Studio Function Calling documentation](https://ai.google.dev/docs/function_calling)
- [Google AI Studio Search Grounding documentation](https://ai.google.dev/docs/gemini_api/grounding)
- [promptfoo Google Provider documentation](/docs/providers/google)