forked from Archives/langchain
da7b51455c
I think the logic of https://github.com/hwchase17/langchain/pull/3684#pullrequestreview-1405358565 is too confusing. I prefer this alternative because: - All `Tool()` implementations by default will be treated the same as before. No breaking changes. - Less reliance on pydantic magic - The decorator (which only is typed as returning a callable) can infer schema and generate a structured tool - Either way, the recommended way to create a custom tool is through inheriting from the base tool
447 lines
14 KiB
Python
447 lines
14 KiB
Python
"""Test tool utils."""
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from datetime import datetime
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from functools import partial
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from typing import Any, Optional, Type, Union
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from unittest.mock import MagicMock
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import pydantic
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import pytest
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from pydantic import BaseModel
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from langchain.agents.agent import Agent
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from langchain.agents.chat.base import ChatAgent
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from langchain.agents.conversational.base import ConversationalAgent
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from langchain.agents.conversational_chat.base import ConversationalChatAgent
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from langchain.agents.mrkl.base import ZeroShotAgent
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from langchain.agents.react.base import ReActDocstoreAgent, ReActTextWorldAgent
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from langchain.agents.self_ask_with_search.base import SelfAskWithSearchAgent
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from langchain.agents.tools import Tool, tool
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from langchain.tools.base import BaseTool, SchemaAnnotationError, StructuredTool
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def test_unnamed_decorator() -> None:
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"""Test functionality with unnamed decorator."""
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@tool
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def search_api(query: str) -> str:
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"""Search the API for the query."""
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return "API result"
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assert isinstance(search_api, BaseTool)
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assert search_api.name == "search_api"
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assert not search_api.return_direct
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assert search_api("test") == "API result"
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class _MockSchema(BaseModel):
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arg1: int
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arg2: bool
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arg3: Optional[dict] = None
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class _MockStructuredTool(BaseTool):
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name = "structured_api"
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args_schema: Type[BaseModel] = _MockSchema
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description = "A Structured Tool"
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def _run(self, arg1: int, arg2: bool, arg3: Optional[dict] = None) -> str:
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return f"{arg1} {arg2} {arg3}"
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async def _arun(self, arg1: int, arg2: bool, arg3: Optional[dict] = None) -> str:
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raise NotImplementedError
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def test_structured_args() -> None:
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"""Test functionality with structured arguments."""
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structured_api = _MockStructuredTool()
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assert isinstance(structured_api, BaseTool)
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assert structured_api.name == "structured_api"
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expected_result = "1 True {'foo': 'bar'}"
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args = {"arg1": 1, "arg2": True, "arg3": {"foo": "bar"}}
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assert structured_api.run(args) == expected_result
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def test_unannotated_base_tool_raises_error() -> None:
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"""Test that a BaseTool without type hints raises an exception.""" ""
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with pytest.raises(SchemaAnnotationError):
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class _UnAnnotatedTool(BaseTool):
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name = "structured_api"
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# This would silently be ignored without the custom metaclass
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args_schema = _MockSchema
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description = "A Structured Tool"
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def _run(self, arg1: int, arg2: bool, arg3: Optional[dict] = None) -> str:
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return f"{arg1} {arg2} {arg3}"
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async def _arun(
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self, arg1: int, arg2: bool, arg3: Optional[dict] = None
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) -> str:
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raise NotImplementedError
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def test_misannotated_base_tool_raises_error() -> None:
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"""Test that a BaseTool with the incorrrect typehint raises an exception.""" ""
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with pytest.raises(SchemaAnnotationError):
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class _MisAnnotatedTool(BaseTool):
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name = "structured_api"
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# This would silently be ignored without the custom metaclass
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args_schema: BaseModel = _MockSchema # type: ignore
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description = "A Structured Tool"
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def _run(self, arg1: int, arg2: bool, arg3: Optional[dict] = None) -> str:
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return f"{arg1} {arg2} {arg3}"
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async def _arun(
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self, arg1: int, arg2: bool, arg3: Optional[dict] = None
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) -> str:
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raise NotImplementedError
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def test_forward_ref_annotated_base_tool_accepted() -> None:
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"""Test that a using forward ref annotation syntax is accepted.""" ""
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class _ForwardRefAnnotatedTool(BaseTool):
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name = "structured_api"
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args_schema: "Type[BaseModel]" = _MockSchema
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description = "A Structured Tool"
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def _run(self, arg1: int, arg2: bool, arg3: Optional[dict] = None) -> str:
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return f"{arg1} {arg2} {arg3}"
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async def _arun(
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self, arg1: int, arg2: bool, arg3: Optional[dict] = None
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) -> str:
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raise NotImplementedError
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def test_subclass_annotated_base_tool_accepted() -> None:
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"""Test BaseTool child w/ custom schema isn't overwritten."""
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class _ForwardRefAnnotatedTool(BaseTool):
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name = "structured_api"
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args_schema: Type[_MockSchema] = _MockSchema
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description = "A Structured Tool"
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def _run(self, arg1: int, arg2: bool, arg3: Optional[dict] = None) -> str:
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return f"{arg1} {arg2} {arg3}"
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async def _arun(
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self, arg1: int, arg2: bool, arg3: Optional[dict] = None
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) -> str:
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raise NotImplementedError
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assert issubclass(_ForwardRefAnnotatedTool, BaseTool)
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tool = _ForwardRefAnnotatedTool()
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assert tool.args_schema == _MockSchema
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def test_decorator_with_specified_schema() -> None:
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"""Test that manually specified schemata are passed through to the tool."""
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@tool(args_schema=_MockSchema)
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def tool_func(arg1: int, arg2: bool, arg3: Optional[dict] = None) -> str:
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"""Return the arguments directly."""
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return f"{arg1} {arg2} {arg3}"
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assert isinstance(tool_func, BaseTool)
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assert tool_func.args_schema == _MockSchema
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def test_decorated_function_schema_equivalent() -> None:
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"""Test that a BaseTool without a schema meets expectations."""
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@tool
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def structured_tool_input(
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arg1: int, arg2: bool, arg3: Optional[dict] = None
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) -> str:
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"""Return the arguments directly."""
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return f"{arg1} {arg2} {arg3}"
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assert isinstance(structured_tool_input, BaseTool)
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assert structured_tool_input.args_schema is not None
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assert (
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structured_tool_input.args_schema.schema()["properties"]
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== _MockSchema.schema()["properties"]
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== structured_tool_input.args
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)
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def test_structured_args_decorator_no_infer_schema() -> None:
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"""Test functionality with structured arguments parsed as a decorator."""
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@tool
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def structured_tool_input(
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arg1: int, arg2: Union[float, datetime], opt_arg: Optional[dict] = None
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) -> str:
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"""Return the arguments directly."""
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return f"{arg1}, {arg2}, {opt_arg}"
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assert isinstance(structured_tool_input, BaseTool)
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assert structured_tool_input.name == "structured_tool_input"
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args = {"arg1": 1, "arg2": 0.001, "opt_arg": {"foo": "bar"}}
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expected_result = "1, 0.001, {'foo': 'bar'}"
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assert structured_tool_input.run(args) == expected_result
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def test_structured_single_str_decorator_no_infer_schema() -> None:
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"""Test functionality with structured arguments parsed as a decorator."""
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@tool(infer_schema=False)
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def unstructured_tool_input(tool_input: str) -> str:
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"""Return the arguments directly."""
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return f"{tool_input}"
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assert isinstance(unstructured_tool_input, BaseTool)
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assert unstructured_tool_input.args_schema is None
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assert unstructured_tool_input.run("foo") == "foo"
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def test_base_tool_inheritance_base_schema() -> None:
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"""Test schema is correctly inferred when inheriting from BaseTool."""
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class _MockSimpleTool(BaseTool):
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name = "simple_tool"
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description = "A Simple Tool"
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def _run(self, tool_input: str) -> str:
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return f"{tool_input}"
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async def _arun(self, tool_input: str) -> str:
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raise NotImplementedError
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simple_tool = _MockSimpleTool()
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assert simple_tool.args_schema is None
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expected_args = {"tool_input": {"title": "Tool Input", "type": "string"}}
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assert simple_tool.args == expected_args
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def test_tool_lambda_args_schema() -> None:
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"""Test args schema inference when the tool argument is a lambda function."""
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tool = Tool(
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name="tool",
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description="A tool",
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func=lambda tool_input: tool_input,
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)
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assert tool.args_schema is None
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expected_args = {"tool_input": {"type": "string"}}
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assert tool.args == expected_args
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def test_structured_tool_lambda_multi_args_schema() -> None:
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"""Test args schema inference when the tool argument is a lambda function."""
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tool = StructuredTool.from_function(
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name="tool",
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description="A tool",
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func=lambda tool_input, other_arg: f"{tool_input}{other_arg}", # type: ignore
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)
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assert tool.args_schema is not None
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expected_args = {
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"tool_input": {"title": "Tool Input"},
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"other_arg": {"title": "Other Arg"},
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}
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assert tool.args == expected_args
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def test_tool_partial_function_args_schema() -> None:
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"""Test args schema inference when the tool argument is a partial function."""
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def func(tool_input: str, other_arg: str) -> str:
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return tool_input + other_arg
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with pytest.raises(pydantic.error_wrappers.ValidationError):
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# We don't yet support args_schema inference for partial functions
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# so want to make sure we proactively raise an error
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Tool(
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name="tool",
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description="A tool",
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func=partial(func, other_arg="foo"),
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)
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def test_empty_args_decorator() -> None:
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"""Test inferred schema of decorated fn with no args."""
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@tool
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def empty_tool_input() -> str:
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"""Return a constant."""
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return "the empty result"
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assert isinstance(empty_tool_input, BaseTool)
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assert empty_tool_input.name == "empty_tool_input"
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assert empty_tool_input.args == {}
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assert empty_tool_input.run({}) == "the empty result"
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def test_named_tool_decorator() -> None:
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"""Test functionality when arguments are provided as input to decorator."""
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@tool("search")
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def search_api(query: str) -> str:
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"""Search the API for the query."""
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return "API result"
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assert isinstance(search_api, BaseTool)
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assert search_api.name == "search"
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assert not search_api.return_direct
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def test_named_tool_decorator_return_direct() -> None:
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"""Test functionality when arguments and return direct are provided as input."""
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@tool("search", return_direct=True)
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def search_api(query: str) -> str:
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"""Search the API for the query."""
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return "API result"
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assert isinstance(search_api, BaseTool)
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assert search_api.name == "search"
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assert search_api.return_direct
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def test_unnamed_tool_decorator_return_direct() -> None:
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"""Test functionality when only return direct is provided."""
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@tool(return_direct=True)
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def search_api(query: str) -> str:
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"""Search the API for the query."""
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return "API result"
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assert isinstance(search_api, BaseTool)
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assert search_api.name == "search_api"
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assert search_api.return_direct
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def test_tool_with_kwargs() -> None:
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"""Test functionality when only return direct is provided."""
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@tool(return_direct=True)
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def search_api(
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arg_0: str,
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arg_1: float = 4.3,
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ping: str = "hi",
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) -> str:
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"""Search the API for the query."""
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return f"arg_0={arg_0}, arg_1={arg_1}, ping={ping}"
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assert isinstance(search_api, BaseTool)
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result = search_api.run(
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tool_input={
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"arg_0": "foo",
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"arg_1": 3.2,
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"ping": "pong",
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}
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)
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assert result == "arg_0=foo, arg_1=3.2, ping=pong"
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result = search_api.run(
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tool_input={
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"arg_0": "foo",
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}
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)
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assert result == "arg_0=foo, arg_1=4.3, ping=hi"
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# For backwards compatibility, we still accept a single str arg
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result = search_api.run("foobar")
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assert result == "arg_0=foobar, arg_1=4.3, ping=hi"
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def test_missing_docstring() -> None:
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"""Test error is raised when docstring is missing."""
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# expect to throw a value error if theres no docstring
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with pytest.raises(AssertionError, match="Function must have a docstring"):
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@tool
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def search_api(query: str) -> str:
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return "API result"
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def test_create_tool_positional_args() -> None:
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"""Test that positional arguments are allowed."""
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test_tool = Tool("test_name", lambda x: x, "test_description")
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assert test_tool("foo") == "foo"
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assert test_tool.name == "test_name"
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assert test_tool.description == "test_description"
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assert test_tool.is_single_input
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def test_create_tool_keyword_args() -> None:
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"""Test that keyword arguments are allowed."""
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test_tool = Tool(name="test_name", func=lambda x: x, description="test_description")
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assert test_tool.is_single_input
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assert test_tool("foo") == "foo"
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assert test_tool.name == "test_name"
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assert test_tool.description == "test_description"
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@pytest.mark.asyncio
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async def test_create_async_tool() -> None:
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"""Test that async tools are allowed."""
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async def _test_func(x: str) -> str:
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return x
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test_tool = Tool(
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name="test_name",
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func=lambda x: x,
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description="test_description",
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coroutine=_test_func,
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)
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assert test_tool.is_single_input
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assert test_tool("foo") == "foo"
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assert test_tool.name == "test_name"
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assert test_tool.description == "test_description"
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assert test_tool.coroutine is not None
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assert await test_tool.arun("foo") == "foo"
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@pytest.mark.parametrize(
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"agent_cls",
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[
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ChatAgent,
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ZeroShotAgent,
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ConversationalChatAgent,
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ConversationalAgent,
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ReActDocstoreAgent,
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ReActTextWorldAgent,
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SelfAskWithSearchAgent,
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],
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)
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def test_single_input_agent_raises_error_on_structured_tool(
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agent_cls: Type[Agent],
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) -> None:
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"""Test that older agents raise errors on older tools."""
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@tool
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def the_tool(foo: str, bar: str) -> str:
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"""Return the concat of foo and bar."""
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return foo + bar
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with pytest.raises(
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ValueError,
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match=f"{agent_cls.__name__} does not support" # type: ignore
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f" multi-input tool {the_tool.name}.",
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):
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agent_cls.from_llm_and_tools(MagicMock(), [the_tool]) # type: ignore
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def test_tool_no_args_specified_assumes_str() -> None:
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"""Older tools could assume *args and **kwargs were passed in."""
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def ambiguous_function(*args: Any, **kwargs: Any) -> str:
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"""An ambiguously defined function."""
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return args[0]
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some_tool = Tool(
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name="chain_run",
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description="Run the chain",
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func=ambiguous_function,
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)
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expected_args = {"tool_input": {"type": "string"}}
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assert some_tool.args == expected_args
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assert some_tool.run("foobar") == "foobar"
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assert some_tool.run({"tool_input": "foobar"}) == "foobar"
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with pytest.raises(ValueError, match="Too many arguments to single-input tool"):
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some_tool.run({"tool_input": "foobar", "other_input": "bar"})
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