BaseTool

The unique name of the tool that clearly communicates its purpose.

Used to tell the model how/when/why to use the tool.

You can provide few-shot examples as a part of the description.

Pydantic model class to validate and parse the tool's input arguments.

Args schema should be either:

• A subclass of pydantic.BaseModel.
• A subclass of pydantic.v1.BaseModel if accessing v1 namespace in pydantic 2
• A JSON schema dict

Whether to return the tool's output directly.

Setting this to True means that after the tool is called, the AgentExecutor will stop looping.

Whether to log the tool's progress.

Callbacks to be called during tool execution.

Optional list of tags associated with the tool.

These tags will be associated with each call to this tool, and passed as arguments to the handlers defined in callbacks.

You can use these to, e.g., identify a specific instance of a tool with its use case.

Optional metadata associated with the tool.

This metadata will be associated with each call to this tool, and passed as arguments to the handlers defined in callbacks.

You can use these to, e.g., identify a specific instance of a tool with its usecase.

Handle the content of the ToolException thrown.

Handle the content of the ValidationError thrown.

The tool response format.

If 'content' then the output of the tool is interpreted as the contents of a ToolMessage. If 'content_and_artifact' then the output is expected to be a two-tuple corresponding to the (content, artifact) of a ToolMessage.

Optional provider-specific extra fields for the tool.

This is used to pass provider-specific configuration that doesn't fit into standard tool fields.

Check if the tool accepts only a single input argument.

Get the tool's input arguments schema.

Get the schema for tool calls, excluding injected arguments.

The tool's input schema.

Run the tool.

Run the tool asynchronously.