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Python
Experiment
import langwatchdf = langwatch.datasets.get_dataset("dataset-id").to_pandas()experiment = langwatch.experiment.init("my-experiment")for index, row in experiment.loop(df.iterrows()): # your execution code here experiment.evaluate( "langevals/competitor_llm_function_call", index=index, data={ "output": output, "input": row["input"], }, settings={} )
[ { "status": "processed", "score": 123, "passed": true, "label": "<string>", "details": "<string>", "cost": { "currency": "<string>", "amount": 123 } } ]
This evaluator implements LLM-as-a-judge with a function call approach to check if the message contains a mention of a competitor.
API key for authentication
Show child attributes
Optional trace ID to associate this evaluation with a trace
Successful evaluation
processed
skipped
error
Numeric score from the evaluation
Whether the evaluation passed
Label assigned by the evaluation
Additional details about the evaluation
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