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Polong Lin
42 lines
2.0 KiB
Markdown
42 lines
2.0 KiB
Markdown
# Built-in tools
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These are ready-to-use functionalities, like Google Search, Code Executors, that provide agents with common capabilities immediately. For instance, an agent needing to retrieve information from the web can directly use the **built\_in\_google\_search** tool without any additional setup.
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## How to Use
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1. **Import:** Import the desired tool from the `agents.tools` module.
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2. **Configure:** Initialize the tool, providing required parameters if any.
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3. **Register:** Add the initialized tool to the **tools** list of your Agent.
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Once added to an agent, the agent can decide to use the tool based on the **user prompt** and its **instructions**. The framework handles the execution of the tool when the agent calls it.
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## Available Built-in tools
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### Google Search
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`google_search`: Allows the agent to perform web searches using Google Search. You simply add this tool to the agent's tools list. It is compatible with Gemini 2 models.
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```py
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--8<-- "examples/python/snippets/tools/built-in-tools/google_search.py"
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```
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### Code Execution
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`built_in_code_execution`: Enables the agent to execute code, specifically when using Gemini 2 models. This allows the model to perform tasks like calculations, data manipulation, or running small scripts. This capability is built-in and automatically activated for compatible models, requiring no explicit configuration.
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````py
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--8<-- "examples/python/snippets/tools/built-in-tools/code_execution.py"
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````
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### Retrieval tools
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This is a category of tools designed to fetch information from various sources. Examples include:
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#### Vertex AI Search
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`built_in_vertexai_search`: Leverages Google Cloud's Vertex AI Search, enabling the agent to search across your private, configured data stores (e.g., internal documents, company policies, knowledge bases). This built-in tool requires you to provide the specific data store ID during configuration.
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```py
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--8<-- "examples/python/snippets/tools/built-in-tools/vertexai_search.py"
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```
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