Extract shared build_metric_registry factory (DRY)

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

webapp/services/inline_scorer.py

@@ -13,35 +13,17 @@ import threading
 from typing import Any
 
 from rag_eval.compat import ensure_ragas_import_compat
-from rag_eval.metrics.factory import build_models
+from rag_eval.metrics.factory import build_metric_registry, build_models
 from rag_eval.metrics.pipeline import MetricPipeline
 from rag_eval.settings import EvaluationSettings
 from rag_eval.shared.models import NormalizedSample
 
 ensure_ragas_import_compat()
 
-from ragas.metrics.collections import (  # noqa: E402
-    AnswerRelevancy,
-    ContextPrecision,
-    ContextRecall,
-    FactualCorrectness,
-    Faithfulness,
-    NoiseSensitivity,
-    SemanticSimilarity,
-)
-
 
 def _build_metric_instances(metrics: list[str], llm: Any, embeddings: Any) -> dict[str, Any]:
     """Instantiate only the RAGAS metric objects requested."""
-    registry: dict[str, Any] = {
-        "faithfulness": Faithfulness(llm=llm),
-        "answer_relevancy": AnswerRelevancy(llm=llm, embeddings=embeddings),
-        "context_recall": ContextRecall(llm=llm),
-        "context_precision": ContextPrecision(llm=llm),
-        "noise_sensitivity": NoiseSensitivity(llm=llm),
-        "factual_correctness": FactualCorrectness(llm=llm),
-        "semantic_similarity": SemanticSimilarity(embeddings=embeddings),
-    }
+    registry = build_metric_registry(llm, embeddings)
     return {name: registry[name] for name in metrics if name in registry}