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101 lines
3.4 KiB
Text
101 lines
3.4 KiB
Text
---
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title: sampling_tool
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sidebarTitle: sampling_tool
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---
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# `fastmcp.server.sampling.sampling_tool`
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SamplingTool for use during LLM sampling requests.
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## Classes
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### `SamplingTool` <sup><a href="https://github.com/PrefectHQ/fastmcp/blob/main/src/fastmcp/server/sampling/sampling_tool.py#L23" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>
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A tool that can be used during LLM sampling.
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SamplingTools bundle a tool's schema (name, description, parameters) with
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an executor function, enabling servers to execute agentic workflows where
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the LLM can request tool calls during sampling.
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In most cases, pass functions directly to ctx.sample():
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def search(query: str) -> str:
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'''Search the web.'''
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return web_search(query)
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result = await context.sample(
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messages="Find info about Python",
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tools=[search], # Plain functions work directly
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)
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Create a SamplingTool explicitly when you need custom name/description:
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tool = SamplingTool.from_function(search, name="web_search")
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**Methods:**
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#### `run` <sup><a href="https://github.com/PrefectHQ/fastmcp/blob/main/src/fastmcp/server/sampling/sampling_tool.py#L54" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>
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```python
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run(self, arguments: dict[str, Any] | None = None) -> Any
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```
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Execute the tool with the given arguments.
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**Args:**
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- `arguments`: Dictionary of arguments to pass to the tool function.
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**Returns:**
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- The result of executing the tool function.
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#### `from_function` <sup><a href="https://github.com/PrefectHQ/fastmcp/blob/main/src/fastmcp/server/sampling/sampling_tool.py#L84" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>
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```python
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from_function(cls, fn: Callable[..., Any]) -> SamplingTool
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```
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Create a SamplingTool from a function.
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The function's signature is analyzed to generate a JSON schema for
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the tool's parameters. Type hints are used to determine parameter types.
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**Args:**
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- `fn`: The function to create a tool from.
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- `name`: Optional name override. Defaults to the function's name.
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- `description`: Optional description override. Defaults to the function's docstring.
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- `sequential`: If True, this tool requires sequential execution and prevents
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parallel execution of all tools in the batch. Set to True for tools
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with shared state, file writes, or other operations that cannot run
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concurrently. Defaults to False.
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**Returns:**
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- A SamplingTool wrapping the function.
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**Raises:**
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- `ValueError`: If the function is a lambda without a name override.
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#### `from_callable_tool` <sup><a href="https://github.com/PrefectHQ/fastmcp/blob/main/src/fastmcp/server/sampling/sampling_tool.py#L126" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>
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```python
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from_callable_tool(cls, tool: FunctionTool | TransformedTool) -> SamplingTool
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```
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Create a SamplingTool from a FunctionTool or TransformedTool.
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Reuses existing server tools in sampling contexts. For TransformedTool,
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the tool's .run() method is used to ensure proper argument transformation,
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and the ToolResult is automatically unwrapped.
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**Args:**
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- `tool`: A FunctionTool or TransformedTool to convert.
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- `name`: Optional name override. Defaults to tool.name.
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- `description`: Optional description override. Defaults to tool.description.
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**Raises:**
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- `TypeError`: If the tool is not a FunctionTool or TransformedTool.
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