LangChain - Evaluation and Testing
How can you efficiently compute the average evaluation score for multiple predictions against their references using LangSmith evaluators?
How can you efficiently compute the average evaluation score for multiple predictions against their references using LangSmith evaluators?
hard📝 Application Q8 of 15
Step-by-Step Solution
Solution:
Step 1: Understand evaluator usage
evaluate() typically processes one prediction and one reference at a time.Step 2: Compute scores for each pair
Loop through each prediction-reference pair, call evaluate(), and collect scores.Step 3: Calculate average
Sum all scores and divide by number of pairs to get average.Step 4: Eliminate other options
evaluate() does not accept lists; evaluating only one prediction is inaccurate; references are required.Final Answer:
Iterate over each prediction-reference pair, evaluate individually, then average the results -> Option BQuick Check:
Evaluate pairs individually, then average [OK]
Quick Trick: Evaluate pairs one by one, then average scores [OK]
Common Mistakes:
MISTAKES- Passing lists directly to evaluate()
- Assuming one evaluation covers all predictions
- Ignoring references in evaluation
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