Ship reliable, testable agents – not guesses. Better Agents adds simulations, evaluations, and standards on top of any framework. Explore Better Agents
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", 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 use an LLM-as-judge to check if the conversation is related to competitors, without having to name them explicitly
API key for authentication
The input text to evaluate
The output/response text to evaluate
Show child attributes
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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