wehub-resource-sync
63 lines
2.1 KiB
Python
63 lines
2.1 KiB
Python
import pytest
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from ragas import MultiTurnSample
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from ragas.messages import AIMessage, HumanMessage, ToolCall
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from ragas.metrics import ToolCallF1
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metric = ToolCallF1()
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def make_sample(expected, predicted):
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return MultiTurnSample(
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user_input=[
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HumanMessage(content="What is the weather in Paris?"),
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AIMessage(
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content="Let me check the weather forecast", tool_calls=predicted
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),
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],
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reference_tool_calls=expected,
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reference="Expected correct weather tool call",
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)
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@pytest.mark.asyncio
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async def test_tool_call_f1_full_match():
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expected = [ToolCall(name="WeatherForecast", args={"location": "Paris"})]
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predicted = [ToolCall(name="WeatherForecast", args={"location": "Paris"})]
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sample = make_sample(expected, predicted)
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score = await metric._multi_turn_ascore(sample)
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assert score == 1.0
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@pytest.mark.asyncio
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async def test_tool_call_f1_partial_match():
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expected = [
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ToolCall(name="WeatherForecast", args={"location": "Paris"}),
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ToolCall(name="UVIndex", args={"location": "Paris"}),
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]
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predicted = [ToolCall(name="WeatherForecast", args={"location": "Paris"})]
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sample = make_sample(expected, predicted)
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score = await metric._multi_turn_ascore(sample)
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assert round(score, 2) == 0.67
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@pytest.mark.asyncio
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async def test_tool_call_f1_no_match():
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expected = [ToolCall(name="WeatherForecast", args={"location": "Paris"})]
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predicted = [ToolCall(name="AirQuality", args={"location": "Paris"})]
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sample = make_sample(expected, predicted)
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score = await metric._multi_turn_ascore(sample)
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assert score == 0.0
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@pytest.mark.asyncio
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async def test_tool_call_f1_extra_call():
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expected = [ToolCall(name="WeatherForecast", args={"location": "Paris"})]
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predicted = [
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ToolCall(name="WeatherForecast", args={"location": "Paris"}),
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ToolCall(name="AirQuality", args={"location": "Paris"}),
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]
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sample = make_sample(expected, predicted)
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score = await metric._multi_turn_ascore(sample)
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assert round(score, 2) == 0.67
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