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295 | class FunctionTool(AsyncBaseTool):
"""Function Tool.
A tool that takes in a function, optionally handles workflow context,
and allows the use of callbacks. The callback can return a new ToolOutput
to override the default one or a string that will be used as the final content.
"""
def __init__(
self,
fn: Optional[Callable[..., Any]] = None,
metadata: Optional[ToolMetadata] = None,
async_fn: Optional[Callable[..., Any]] = None,
callback: Optional[Callable[..., Any]] = None,
async_callback: Optional[Callable[..., Any]] = None,
) -> None:
if fn is None and async_fn is None:
raise ValueError("fn or async_fn must be provided.")
# Handle function (sync and async)
if async_fn is not None:
self._async_fn = async_fn
self._fn = fn or async_to_sync(async_fn)
else:
assert fn is not None
if inspect.iscoroutinefunction(fn):
self._async_fn = fn
self._fn = async_to_sync(fn)
else:
self._fn = fn
self._async_fn = sync_to_async(fn)
# Determine if the function requires context by inspecting its signature
fn_to_inspect = fn or async_fn
assert fn_to_inspect is not None
sig = inspect.signature(fn_to_inspect)
self.requires_context = any(
param.annotation == Context for param in sig.parameters.values()
)
if metadata is None:
raise ValueError("metadata must be provided")
self._metadata = metadata
# Handle callback (sync and async)
self._callback = None
if callback is not None:
self._callback = callback
elif async_callback is not None:
self._callback = async_to_sync(async_callback)
self._async_callback = None
if async_callback is not None:
self._async_callback = async_callback
elif self._callback is not None:
self._async_callback = sync_to_async(self._callback)
def _run_sync_callback(self, result: Any) -> CallbackReturn:
"""Runs the sync callback, if provided, and returns either a ToolOutput
to override the default output or a string to override the content.
"""
if self._callback:
ret: CallbackReturn = self._callback(result)
return ret
return None
async def _run_async_callback(self, result: Any) -> CallbackReturn:
"""Runs the async callback, if provided, and returns either a ToolOutput
to override the default output or a string to override the content.
"""
if self._async_callback:
ret: CallbackReturn = await self._async_callback(result)
return ret
return None
@classmethod
def from_defaults(
cls,
fn: Optional[Callable[..., Any]] = None,
name: Optional[str] = None,
description: Optional[str] = None,
return_direct: bool = False,
fn_schema: Optional[Type[BaseModel]] = None,
async_fn: Optional[AsyncCallable] = None,
tool_metadata: Optional[ToolMetadata] = None,
callback: Optional[Callable[[Any], Any]] = None,
async_callback: Optional[AsyncCallable] = None,
) -> "FunctionTool":
if tool_metadata is None:
fn_to_parse = fn or async_fn
assert fn_to_parse is not None, "fn must be provided"
name = name or fn_to_parse.__name__
docstring = fn_to_parse.__doc__
# Get function signature
fn_sig = inspect.signature(fn_to_parse)
# Remove ctx parameter from schema if present
has_ctx = any(
param.annotation == Context for param in fn_sig.parameters.values()
)
ctx_param_name = None
if has_ctx:
ctx_param_name = next(
param.name
for param in fn_sig.parameters.values()
if param.annotation == Context
)
fn_sig = fn_sig.replace(
parameters=[
param
for param in fn_sig.parameters.values()
if param.annotation != Context
]
)
# Handle FieldInfo defaults
fn_sig = fn_sig.replace(
parameters=[
param.replace(default=inspect.Parameter.empty)
if isinstance(param.default, FieldInfo)
else param
for param in fn_sig.parameters.values()
]
)
description = description or f"{name}{fn_sig}\n{docstring}"
if fn_schema is None:
fn_schema = create_schema_from_function(
f"{name}",
fn_to_parse,
additional_fields=None,
ignore_fields=[ctx_param_name]
if ctx_param_name is not None
else None,
)
tool_metadata = ToolMetadata(
name=name,
description=description,
fn_schema=fn_schema,
return_direct=return_direct,
)
return cls(
fn=fn,
metadata=tool_metadata,
async_fn=async_fn,
callback=callback,
async_callback=async_callback,
)
@property
def metadata(self) -> ToolMetadata:
"""Metadata."""
return self._metadata
@property
def fn(self) -> Callable[..., Any]:
"""Function."""
return self._fn
@property
def async_fn(self) -> AsyncCallable:
"""Async function."""
return self._async_fn
def call(
self, *args: Any, ctx: Optional[Context] = None, **kwargs: Any
) -> ToolOutput:
"""Sync Call."""
if self.requires_context:
if ctx is None:
raise ValueError("Context is required for this tool")
raw_output = self._fn(ctx, *args, **kwargs)
else:
raw_output = self._fn(*args, **kwargs)
# Default ToolOutput based on the raw output
default_output = ToolOutput(
content=str(raw_output),
tool_name=self.metadata.name,
raw_input={"args": args, "kwargs": kwargs},
raw_output=raw_output,
)
# Check for a sync callback override
callback_result = self._run_sync_callback(raw_output)
if callback_result is not None:
if isinstance(callback_result, ToolOutput):
return callback_result
else:
# Assume callback_result is a string to override the content.
return ToolOutput(
content=str(callback_result),
tool_name=self.metadata.name,
raw_input={"args": args, "kwargs": kwargs},
raw_output=raw_output,
)
return default_output
async def acall(
self, *args: Any, ctx: Optional[Context] = None, **kwargs: Any
) -> ToolOutput:
"""Async Call."""
if self.requires_context:
if ctx is None:
raise ValueError("Context is required for this tool")
raw_output = await self._async_fn(ctx, *args, **kwargs)
else:
raw_output = await self._async_fn(*args, **kwargs)
# Default ToolOutput based on the raw output
default_output = ToolOutput(
content=str(raw_output),
tool_name=self.metadata.name,
raw_input={"args": args, "kwargs": kwargs},
raw_output=raw_output,
)
# Check for an async callback override
callback_result = await self._run_async_callback(raw_output)
if callback_result is not None:
if isinstance(callback_result, ToolOutput):
return callback_result
else:
# Assume callback_result is a string to override the content.
return ToolOutput(
content=str(callback_result),
tool_name=self.metadata.name,
raw_input={"args": args, "kwargs": kwargs},
raw_output=raw_output,
)
return default_output
def to_langchain_tool(self, **langchain_tool_kwargs: Any) -> "Tool":
"""To langchain tool."""
from llama_index.core.bridge.langchain import Tool
langchain_tool_kwargs = self._process_langchain_tool_kwargs(
langchain_tool_kwargs
)
return Tool.from_function(
func=self.fn,
coroutine=self.async_fn,
**langchain_tool_kwargs,
)
def to_langchain_structured_tool(
self, **langchain_tool_kwargs: Any
) -> "StructuredTool":
"""To langchain structured tool."""
from llama_index.core.bridge.langchain import StructuredTool
langchain_tool_kwargs = self._process_langchain_tool_kwargs(
langchain_tool_kwargs
)
return StructuredTool.from_function(
func=self.fn,
coroutine=self.async_fn,
**langchain_tool_kwargs,
)
|
