2023-05-05 03:31:16 +00:00
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"""Test the base tool implementation."""
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2023-05-08 16:13:05 +00:00
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import json
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2023-05-05 03:31:16 +00:00
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from datetime import datetime
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2023-05-08 16:13:05 +00:00
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from enum import Enum
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2023-05-05 03:31:16 +00:00
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from functools import partial
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from typing import Any, Optional, Type, Union
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import pytest
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from pydantic import BaseModel
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from langchain.agents.tools import Tool, tool
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from langchain.callbacks.manager import (
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AsyncCallbackManagerForToolRun,
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CallbackManagerForToolRun,
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)
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Add ToolException that a tool can throw. (#5050)
# Add ToolException that a tool can throw
This is an optional exception that tool throws when execution error
occurs.
When this exception is thrown, the agent will not stop working,but will
handle the exception according to the handle_tool_error variable of the
tool,and the processing result will be returned to the agent as
observation,and printed in pink on the console.It can be used like this:
```python
from langchain.schema import ToolException
from langchain import LLMMathChain, SerpAPIWrapper, OpenAI
from langchain.agents import AgentType, initialize_agent
from langchain.chat_models import ChatOpenAI
from langchain.tools import BaseTool, StructuredTool, Tool, tool
from langchain.chat_models import ChatOpenAI
llm = ChatOpenAI(temperature=0)
llm_math_chain = LLMMathChain(llm=llm, verbose=True)
class Error_tool:
def run(self, s: str):
raise ToolException('The current search tool is not available.')
def handle_tool_error(error) -> str:
return "The following errors occurred during tool execution:"+str(error)
search_tool1 = Error_tool()
search_tool2 = SerpAPIWrapper()
tools = [
Tool.from_function(
func=search_tool1.run,
name="Search_tool1",
description="useful for when you need to answer questions about current events.You should give priority to using it.",
handle_tool_error=handle_tool_error,
),
Tool.from_function(
func=search_tool2.run,
name="Search_tool2",
description="useful for when you need to answer questions about current events",
return_direct=True,
)
]
agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True,
handle_tool_errors=handle_tool_error)
agent.run("Who is Leo DiCaprio's girlfriend? What is her current age raised to the 0.43 power?")
```
![image](https://github.com/hwchase17/langchain/assets/32786500/51930410-b26e-4f85-a1e1-e6a6fb450ada)
## Who can review?
- @vowelparrot
---------
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
2023-05-29 20:05:58 +00:00
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from langchain.tools.base import (
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BaseTool,
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SchemaAnnotationError,
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StructuredTool,
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ToolException,
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)
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2023-05-05 03:31:16 +00:00
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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_args_kwargs_filtered() -> None:
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class _SingleArgToolWithKwargs(BaseTool):
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name = "single_arg_tool"
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description = "A single arged tool with kwargs"
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def _run(
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self,
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some_arg: str,
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run_manager: Optional[CallbackManagerForToolRun] = None,
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**kwargs: Any,
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) -> str:
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return "foo"
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async def _arun(
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self,
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some_arg: str,
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run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
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**kwargs: Any,
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) -> str:
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raise NotImplementedError
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tool = _SingleArgToolWithKwargs()
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assert tool.is_single_input
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class _VarArgToolWithKwargs(BaseTool):
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name = "single_arg_tool"
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description = "A single arged tool with kwargs"
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def _run(
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self,
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*args: Any,
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run_manager: Optional[CallbackManagerForToolRun] = None,
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**kwargs: Any,
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) -> str:
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return "foo"
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async def _arun(
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self,
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*args: Any,
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run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
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**kwargs: Any,
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) -> str:
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raise NotImplementedError
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tool2 = _VarArgToolWithKwargs()
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assert tool2.is_single_input
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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(infer_schema=False)
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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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with pytest.raises(ValueError):
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2023-05-08 16:13:05 +00:00
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assert structured_tool_input.run(args)
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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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assert isinstance(tool_input, str)
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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_structured_tool_types_parsed() -> None:
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"""Test the non-primitive types are correctly passed to structured tools."""
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class SomeEnum(Enum):
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A = "a"
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B = "b"
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class SomeBaseModel(BaseModel):
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foo: str
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@tool
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def structured_tool(
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some_enum: SomeEnum,
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some_base_model: SomeBaseModel,
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) -> dict:
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"""Return the arguments directly."""
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return {
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"some_enum": some_enum,
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"some_base_model": some_base_model,
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}
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assert isinstance(structured_tool, StructuredTool)
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args = {
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"some_enum": SomeEnum.A.value,
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"some_base_model": SomeBaseModel(foo="bar").dict(),
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}
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result = structured_tool.run(json.loads(json.dumps(args)))
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expected = {
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"some_enum": SomeEnum.A,
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"some_base_model": SomeBaseModel(foo="bar"),
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}
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assert result == expected
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2023-05-05 03:31:16 +00:00
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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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assert isinstance(tool_input, str)
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assert isinstance(other_arg, str)
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2023-05-05 03:31:16 +00:00
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return tool_input + other_arg
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tool = 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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|
|
|
)
|
|
|
|
assert tool.run("bar") == "barfoo"
|
|
|
|
|
|
|
|
|
|
|
|
def test_empty_args_decorator() -> None:
|
|
|
|
"""Test inferred schema of decorated fn with no args."""
|
|
|
|
|
|
|
|
@tool
|
|
|
|
def empty_tool_input() -> str:
|
|
|
|
"""Return a constant."""
|
|
|
|
return "the empty result"
|
|
|
|
|
|
|
|
assert isinstance(empty_tool_input, BaseTool)
|
|
|
|
assert empty_tool_input.name == "empty_tool_input"
|
|
|
|
assert empty_tool_input.args == {}
|
|
|
|
assert empty_tool_input.run({}) == "the empty result"
|
|
|
|
|
|
|
|
|
|
|
|
def test_named_tool_decorator() -> None:
|
|
|
|
"""Test functionality when arguments are provided as input to decorator."""
|
|
|
|
|
|
|
|
@tool("search")
|
|
|
|
def search_api(query: str) -> str:
|
|
|
|
"""Search the API for the query."""
|
2023-05-08 16:13:05 +00:00
|
|
|
assert isinstance(query, str)
|
|
|
|
return f"API result - {query}"
|
2023-05-05 03:31:16 +00:00
|
|
|
|
|
|
|
assert isinstance(search_api, BaseTool)
|
|
|
|
assert search_api.name == "search"
|
|
|
|
assert not search_api.return_direct
|
2023-05-08 16:13:05 +00:00
|
|
|
assert search_api.run({"query": "foo"}) == "API result - foo"
|
2023-05-05 03:31:16 +00:00
|
|
|
|
|
|
|
|
|
|
|
def test_named_tool_decorator_return_direct() -> None:
|
|
|
|
"""Test functionality when arguments and return direct are provided as input."""
|
|
|
|
|
|
|
|
@tool("search", return_direct=True)
|
2023-05-08 16:13:05 +00:00
|
|
|
def search_api(query: str, *args: Any) -> str:
|
2023-05-05 03:31:16 +00:00
|
|
|
"""Search the API for the query."""
|
|
|
|
return "API result"
|
|
|
|
|
|
|
|
assert isinstance(search_api, BaseTool)
|
|
|
|
assert search_api.name == "search"
|
|
|
|
assert search_api.return_direct
|
2023-05-08 16:13:05 +00:00
|
|
|
assert search_api.run({"query": "foo"}) == "API result"
|
2023-05-05 03:31:16 +00:00
|
|
|
|
|
|
|
|
|
|
|
def test_unnamed_tool_decorator_return_direct() -> None:
|
|
|
|
"""Test functionality when only return direct is provided."""
|
|
|
|
|
|
|
|
@tool(return_direct=True)
|
|
|
|
def search_api(query: str) -> str:
|
|
|
|
"""Search the API for the query."""
|
2023-05-08 16:13:05 +00:00
|
|
|
assert isinstance(query, str)
|
2023-05-05 03:31:16 +00:00
|
|
|
return "API result"
|
|
|
|
|
|
|
|
assert isinstance(search_api, BaseTool)
|
|
|
|
assert search_api.name == "search_api"
|
|
|
|
assert search_api.return_direct
|
2023-05-08 16:13:05 +00:00
|
|
|
assert search_api.run({"query": "foo"}) == "API result"
|
2023-05-05 03:31:16 +00:00
|
|
|
|
|
|
|
|
|
|
|
def test_tool_with_kwargs() -> None:
|
|
|
|
"""Test functionality when only return direct is provided."""
|
|
|
|
|
|
|
|
@tool(return_direct=True)
|
|
|
|
def search_api(
|
|
|
|
arg_0: str,
|
|
|
|
arg_1: float = 4.3,
|
|
|
|
ping: str = "hi",
|
|
|
|
) -> str:
|
|
|
|
"""Search the API for the query."""
|
|
|
|
return f"arg_0={arg_0}, arg_1={arg_1}, ping={ping}"
|
|
|
|
|
|
|
|
assert isinstance(search_api, BaseTool)
|
|
|
|
result = search_api.run(
|
|
|
|
tool_input={
|
|
|
|
"arg_0": "foo",
|
|
|
|
"arg_1": 3.2,
|
|
|
|
"ping": "pong",
|
|
|
|
}
|
|
|
|
)
|
|
|
|
assert result == "arg_0=foo, arg_1=3.2, ping=pong"
|
|
|
|
|
|
|
|
result = search_api.run(
|
|
|
|
tool_input={
|
|
|
|
"arg_0": "foo",
|
|
|
|
}
|
|
|
|
)
|
|
|
|
assert result == "arg_0=foo, arg_1=4.3, ping=hi"
|
|
|
|
# For backwards compatibility, we still accept a single str arg
|
|
|
|
result = search_api.run("foobar")
|
|
|
|
assert result == "arg_0=foobar, arg_1=4.3, ping=hi"
|
|
|
|
|
|
|
|
|
|
|
|
def test_missing_docstring() -> None:
|
|
|
|
"""Test error is raised when docstring is missing."""
|
|
|
|
# expect to throw a value error if theres no docstring
|
|
|
|
with pytest.raises(AssertionError, match="Function must have a docstring"):
|
|
|
|
|
|
|
|
@tool
|
|
|
|
def search_api(query: str) -> str:
|
|
|
|
return "API result"
|
|
|
|
|
|
|
|
|
|
|
|
def test_create_tool_positional_args() -> None:
|
|
|
|
"""Test that positional arguments are allowed."""
|
|
|
|
test_tool = Tool("test_name", lambda x: x, "test_description")
|
|
|
|
assert test_tool("foo") == "foo"
|
|
|
|
assert test_tool.name == "test_name"
|
|
|
|
assert test_tool.description == "test_description"
|
|
|
|
assert test_tool.is_single_input
|
|
|
|
|
|
|
|
|
|
|
|
def test_create_tool_keyword_args() -> None:
|
|
|
|
"""Test that keyword arguments are allowed."""
|
|
|
|
test_tool = Tool(name="test_name", func=lambda x: x, description="test_description")
|
|
|
|
assert test_tool.is_single_input
|
|
|
|
assert test_tool("foo") == "foo"
|
|
|
|
assert test_tool.name == "test_name"
|
|
|
|
assert test_tool.description == "test_description"
|
|
|
|
|
|
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
|
|
async def test_create_async_tool() -> None:
|
|
|
|
"""Test that async tools are allowed."""
|
|
|
|
|
|
|
|
async def _test_func(x: str) -> str:
|
|
|
|
return x
|
|
|
|
|
|
|
|
test_tool = Tool(
|
|
|
|
name="test_name",
|
|
|
|
func=lambda x: x,
|
|
|
|
description="test_description",
|
|
|
|
coroutine=_test_func,
|
|
|
|
)
|
|
|
|
assert test_tool.is_single_input
|
|
|
|
assert test_tool("foo") == "foo"
|
|
|
|
assert test_tool.name == "test_name"
|
|
|
|
assert test_tool.description == "test_description"
|
|
|
|
assert test_tool.coroutine is not None
|
|
|
|
assert await test_tool.arun("foo") == "foo"
|
Add ToolException that a tool can throw. (#5050)
# Add ToolException that a tool can throw
This is an optional exception that tool throws when execution error
occurs.
When this exception is thrown, the agent will not stop working,but will
handle the exception according to the handle_tool_error variable of the
tool,and the processing result will be returned to the agent as
observation,and printed in pink on the console.It can be used like this:
```python
from langchain.schema import ToolException
from langchain import LLMMathChain, SerpAPIWrapper, OpenAI
from langchain.agents import AgentType, initialize_agent
from langchain.chat_models import ChatOpenAI
from langchain.tools import BaseTool, StructuredTool, Tool, tool
from langchain.chat_models import ChatOpenAI
llm = ChatOpenAI(temperature=0)
llm_math_chain = LLMMathChain(llm=llm, verbose=True)
class Error_tool:
def run(self, s: str):
raise ToolException('The current search tool is not available.')
def handle_tool_error(error) -> str:
return "The following errors occurred during tool execution:"+str(error)
search_tool1 = Error_tool()
search_tool2 = SerpAPIWrapper()
tools = [
Tool.from_function(
func=search_tool1.run,
name="Search_tool1",
description="useful for when you need to answer questions about current events.You should give priority to using it.",
handle_tool_error=handle_tool_error,
),
Tool.from_function(
func=search_tool2.run,
name="Search_tool2",
description="useful for when you need to answer questions about current events",
return_direct=True,
)
]
agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True,
handle_tool_errors=handle_tool_error)
agent.run("Who is Leo DiCaprio's girlfriend? What is her current age raised to the 0.43 power?")
```
![image](https://github.com/hwchase17/langchain/assets/32786500/51930410-b26e-4f85-a1e1-e6a6fb450ada)
## Who can review?
- @vowelparrot
---------
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
2023-05-29 20:05:58 +00:00
|
|
|
|
|
|
|
|
|
|
|
class _FakeExceptionTool(BaseTool):
|
|
|
|
name = "exception"
|
|
|
|
description = "an exception-throwing tool"
|
|
|
|
exception: Exception = ToolException()
|
|
|
|
|
|
|
|
def _run(self) -> str:
|
|
|
|
raise self.exception
|
|
|
|
|
|
|
|
async def _arun(self) -> str:
|
|
|
|
raise self.exception
|
|
|
|
|
|
|
|
|
|
|
|
def test_exception_handling_bool() -> None:
|
|
|
|
_tool = _FakeExceptionTool(handle_tool_error=True)
|
|
|
|
expected = "Tool execution error"
|
|
|
|
actual = _tool.run({})
|
|
|
|
assert expected == actual
|
|
|
|
|
|
|
|
|
|
|
|
def test_exception_handling_str() -> None:
|
|
|
|
expected = "foo bar"
|
|
|
|
_tool = _FakeExceptionTool(handle_tool_error=expected)
|
|
|
|
actual = _tool.run({})
|
|
|
|
assert expected == actual
|
|
|
|
|
|
|
|
|
|
|
|
def test_exception_handling_callable() -> None:
|
|
|
|
expected = "foo bar"
|
|
|
|
handling = lambda _: expected # noqa: E731
|
|
|
|
_tool = _FakeExceptionTool(handle_tool_error=handling)
|
|
|
|
actual = _tool.run({})
|
|
|
|
assert expected == actual
|
|
|
|
|
|
|
|
|
|
|
|
def test_exception_handling_non_tool_exception() -> None:
|
|
|
|
_tool = _FakeExceptionTool(exception=ValueError())
|
|
|
|
with pytest.raises(ValueError):
|
|
|
|
_tool.run({})
|
|
|
|
|
|
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
|
|
async def test_async_exception_handling_bool() -> None:
|
|
|
|
_tool = _FakeExceptionTool(handle_tool_error=True)
|
|
|
|
expected = "Tool execution error"
|
|
|
|
actual = await _tool.arun({})
|
|
|
|
assert expected == actual
|
|
|
|
|
|
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
|
|
async def test_async_exception_handling_str() -> None:
|
|
|
|
expected = "foo bar"
|
|
|
|
_tool = _FakeExceptionTool(handle_tool_error=expected)
|
|
|
|
actual = await _tool.arun({})
|
|
|
|
assert expected == actual
|
|
|
|
|
|
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
|
|
async def test_async_exception_handling_callable() -> None:
|
|
|
|
expected = "foo bar"
|
|
|
|
handling = lambda _: expected # noqa: E731
|
|
|
|
_tool = _FakeExceptionTool(handle_tool_error=handling)
|
|
|
|
actual = await _tool.arun({})
|
|
|
|
assert expected == actual
|
|
|
|
|
|
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
|
|
async def test_async_exception_handling_non_tool_exception() -> None:
|
|
|
|
_tool = _FakeExceptionTool(exception=ValueError())
|
|
|
|
with pytest.raises(ValueError):
|
|
|
|
await _tool.arun({})
|