evaluate() method is used to evaluate the performance of a RAG app. You can find the signature below:

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Parameters

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question
Union[str, list[str]]
A question or a list of questions to evaluate your app on.
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metrics
Optional[list[Union[BaseMetric, str]]]
The metrics to evaluate your app on. Defaults to all metrics: ["context_relevancy", "answer_relevancy", "groundedness"]
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num_workers
int
Specify the number of threads to use for parallel processing.

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Returns

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metrics
dict
Returns the metrics you have chosen to evaluate your app on as a dictionary.

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Usage

from embedchain import App

app = App()

# add data source
app.add("https://www.forbes.com/profile/elon-musk")

# run evaluation
app.evaluate("what is the net worth of Elon Musk?")
# {'answer_relevancy': 0.958019958036268, 'context_relevancy': 0.12903225806451613}

# or
# app.evaluate(["what is the net worth of Elon Musk?", "which companies does Elon Musk own?"])