feat(contextual-precision): add RetrievedContextData source grouping and fix weighted precision score#2743
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- Add _group_retrieval_contexts() to merge RetrievedContextData chunks by source - Update _calculate_score() to use correct weighted cumulative precision formula - Add import warnings
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Summary
This PR improves
ContextualPrecisionMetricwith two changes:1.
RetrievedContextDatasource groupingAdds a new
_group_retrieval_contexts()method that merges multipleRetrievedContextDatachunks sharing the samesourceinto a single context string. This prevents redundant per-chunk LLM calls and gives the judge model better context by presenting all chunks from the same document together.Before: Each chunk is evaluated independently, even if from the same source.
After: Chunks from the same source are combined under a
Source: <name>header, separated by---.2. Weighted cumulative precision formula fix
Updates
_calculate_score()to correctly implement the WCP formula:1foryes,0otherwise)precision_at_konly for relevant nodesrelevant_nodes_count(not total verdicts)This aligns the implementation with the documented formula in the DeepEval docs.
Changes
deepeval/metrics/contextual_precision/contextual_precision.py_group_retrieval_contexts()method_calculate_score()with correct WCP formulaimport warnings