Enable creating Tools from any Runnable (#11177)

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pull/11218/head
Nuno Campos 11 months ago committed by GitHub
commit ca5293bf54
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@ -734,7 +734,7 @@ class StructuredTool(BaseTool):
def tool(
*args: Union[str, Callable],
*args: Union[str, Callable, Runnable],
return_direct: bool = False,
args_schema: Optional[Type[BaseModel]] = None,
infer_schema: bool = True,
@ -769,21 +769,46 @@ def tool(
"""
def _make_with_name(tool_name: str) -> Callable:
def _make_tool(dec_func: Callable) -> BaseTool:
if inspect.iscoroutinefunction(dec_func):
def _make_tool(dec_func: Union[Callable, Runnable]) -> BaseTool:
if isinstance(dec_func, Runnable):
runnable = dec_func
if runnable.input_schema.schema().get("type") != "object":
raise ValueError("Runnable must have an object schema.")
async def ainvoke_wrapper(
callbacks: Optional[Callbacks] = None, **kwargs: Any
) -> Any:
return await runnable.ainvoke(kwargs, {"callbacks": callbacks})
def invoke_wrapper(
callbacks: Optional[Callbacks] = None, **kwargs: Any
) -> Any:
return runnable.invoke(kwargs, {"callbacks": callbacks})
coroutine = ainvoke_wrapper
func = invoke_wrapper
schema: Optional[Type[BaseModel]] = runnable.input_schema
description = repr(runnable)
elif inspect.iscoroutinefunction(dec_func):
coroutine = dec_func
func = None
schema = args_schema
description = None
else:
coroutine = None
func = dec_func
schema = args_schema
description = None
if infer_schema or args_schema is not None:
return StructuredTool.from_function(
func,
coroutine,
name=tool_name,
description=description,
return_direct=return_direct,
args_schema=args_schema,
args_schema=schema,
infer_schema=infer_schema,
)
# If someone doesn't want a schema applied, we must treat it as
@ -803,7 +828,9 @@ def tool(
return _make_tool
if len(args) == 1 and isinstance(args[0], str):
if len(args) == 2 and isinstance(args[0], str) and isinstance(args[1], Runnable):
return _make_with_name(args[0])(args[1])
elif len(args) == 1 and isinstance(args[0], str):
# if the argument is a string, then we use the string as the tool name
# Example usage: @tool("search", return_direct=True)
return _make_with_name(args[0])

@ -46,6 +46,7 @@ from langchain.schema.runnable import (
RunnableSequence,
RunnableWithFallbacks,
)
from langchain.tools.base import BaseTool, tool
from langchain.tools.json.tool import JsonListKeysTool, JsonSpec
@ -2779,3 +2780,32 @@ def test_representation_of_runnables() -> None:
" b: RunnableLambda(...)\n"
" }"
), "repr where code string contains multiple lambdas gives up"
@pytest.mark.asyncio
async def test_tool_from_runnable() -> None:
prompt = (
SystemMessagePromptTemplate.from_template("You are a nice assistant.")
+ "{question}"
)
llm = FakeStreamingListLLM(responses=["foo-lish"])
chain = prompt | llm | StrOutputParser()
chain_tool = tool("chain_tool", chain)
assert isinstance(chain_tool, BaseTool)
assert chain_tool.name == "chain_tool"
assert chain_tool.run({"question": "What up"}) == chain.invoke(
{"question": "What up"}
)
assert await chain_tool.arun({"question": "What up"}) == await chain.ainvoke(
{"question": "What up"}
)
assert chain_tool.description.endswith(repr(chain))
assert chain_tool.args_schema.schema() == chain.input_schema.schema()
assert chain_tool.args_schema.schema() == {
"properties": {"question": {"title": "Question"}},
"title": "PromptInput",
"type": "object",
}

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