## Problem I found a bug with `Github.CountStargazers` where a stargazer count of `0` was interpreted as a null result. In other words, 0 wasn't passed back to the Engine correctly. Separately, the tool function was also not authorized correctly. ## Fix - Don't use a falsy comparison when evaluating `result` inside the `ToolOutputFactory` - Add unit tests for `ToolOutputFactory` to give us confidence in the business logic - Added `ToolContext` to pass in the authorization token correctly. Before ``` User (nate@arcade-ai.com): how many stars does the ArcadeAI/Docs repo have on github? Assistant (gpt-4o): I successfully checked the repository, but unfortunately, I cannot provide the number of stars for the ArcadeAI/Docs repository. Please try checking directly on GitHub for the most accurate information. Called tool 'Github_CountStargazers' Parameters:{"owner":"ArcadeAI","name":"Docs"} 'Github_CountStargazers' tool returned:Github.CountStargazers called successfully ``` After ``` User (nate@arcade-ai.com): how many stars does the ArcadeAI/Docs repo have on github? Assistant (gpt-4o): The ArcadeAI/Docs repository on GitHub has 0 stars. Called tool 'Github_CountStargazers' Parameters:{"owner":"ArcadeAI","name":"Docs"} 'Github_CountStargazers' tool returned:0
75 lines
2.1 KiB
Python
75 lines
2.1 KiB
Python
from typing import Any
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import pytest
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from pydantic import BaseModel
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from arcade.core.output import ToolOutputFactory
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@pytest.fixture
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def output_factory():
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return ToolOutputFactory()
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class SampleOutputModel(BaseModel):
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result: Any
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@pytest.mark.parametrize(
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"data, expected_value",
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[
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(None, ""),
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("success", "success"),
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("", ""),
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(None, ""),
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(123, 123),
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(0, 0),
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(123.45, 123.45),
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(True, True),
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(False, False),
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],
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)
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def test_success(output_factory, data, expected_value):
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data_obj = SampleOutputModel(result=data) if data is not None else None
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output = output_factory.success(data=data_obj)
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assert output.value == expected_value
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assert output.error is None
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@pytest.mark.parametrize(
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"message, developer_message",
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[
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("Error occurred", None),
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("Error occurred", "Detailed error message"),
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],
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)
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def test_fail(output_factory, message, developer_message):
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output = output_factory.fail(message=message, developer_message=developer_message)
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assert output.error is not None
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assert output.error.message == message
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assert output.error.developer_message == developer_message
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assert output.error.can_retry is False
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@pytest.mark.parametrize(
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"message, developer_message, additional_prompt_content, retry_after_ms",
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[
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("Retry error", None, None, None),
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("Retry error", "Retrying", "Please try again with this additional data: foobar", 1000),
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],
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)
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def test_fail_retry(
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output_factory, message, developer_message, additional_prompt_content, retry_after_ms
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):
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output = output_factory.fail_retry(
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message=message,
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developer_message=developer_message,
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additional_prompt_content=additional_prompt_content,
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retry_after_ms=retry_after_ms,
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)
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assert output.error is not None
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assert output.error.message == message
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assert output.error.developer_message == developer_message
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assert output.error.can_retry is True
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assert output.error.additional_prompt_content == additional_prompt_content
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assert output.error.retry_after_ms == retry_after_ms
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