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| """Composite RAG metrics combining retrieval + generation (single‐mapping version).""" | |
| from __future__ import annotations | |
| from typing import Mapping | |
| import math | |
| def harmonic_mean(scores: Mapping[str, float]) -> float: | |
| """Compute the harmonic mean of positive scores.""" | |
| if not scores: | |
| return 0.0 | |
| if any(v <= 0 for v in scores.values()): | |
| return 0.0 | |
| else: | |
| inv_sum = sum(1.0 / (v) for v in scores.values()) | |
| return len(scores) / inv_sum if inv_sum and inv_sum != 0 else 0.0 | |
| def rag_score( | |
| scores: Mapping[str, float], | |
| *, | |
| alpha: float = 0.5, | |
| ) -> float: | |
| """ | |
| Combine retrieval & generation sub-scores (0-1) via weighted HM. | |
| """ | |
| # Split the incoming flat mapping into two maps: retrieval vs generation | |
| retr_map: dict[str, float] = {} | |
| gen_map: dict[str, float] = {} | |
| for k, v in scores.items(): | |
| if k.startswith("retrieval_"): | |
| retr_map[k[len("retrieval_"):]] = v | |
| elif k.startswith("generation_"): | |
| gen_map[k[len("generation_"):]] = v | |
| else: | |
| # ignore any key that doesn't start with 'retrieval_' or 'generation_' | |
| pass | |
| # If either side is empty, we cannot score | |
| if not retr_map or not gen_map: | |
| return 0.0 | |
| retr_score = harmonic_mean(retr_map) | |
| gen_score = harmonic_mean(gen_map) | |
| if retr_score == 0 or gen_score == 0: | |
| return 0.0 | |
| return 1.0 / (alpha / retr_score + (1 - alpha) / gen_score) |