mirror of
https://github.com/hwchase17/langchain.git
synced 2025-05-28 18:48:50 +00:00
Enable creating Tools from any Runnable (#11177)
<!-- Thank you for contributing to LangChain! Replace this entire comment with: - **Description:** a description of the change, - **Issue:** the issue # it fixes (if applicable), - **Dependencies:** any dependencies required for this change, - **Tag maintainer:** for a quicker response, tag the relevant maintainer (see below), - **Twitter handle:** we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. -->
This commit is contained in:
commit
ca5293bf54
@ -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",
|
||||
}
|
||||
|
Loading…
Reference in New Issue
Block a user