Replace reciprocal_rank_stage

Author: aclark4life

libs/langchain-mongodb/langchain_mongodb/pipelines.py

@@ -12,6 +12,7 @@
 from pymongo_search_utils import (
     combine_pipelines,  # noqa: F401
     final_hybrid_stage,  # noqa: F401
+    reciprocal_rank_stage,  # noqa: F401
 )
 
 
@@ -94,41 +95,3 @@ def vector_search_stage(
     if filter:
         stage["filter"] = filter
     return {"$vectorSearch": stage}
-
-
-def reciprocal_rank_stage(
-    score_field: str, penalty: float = 0, weight: float = 1, **kwargs: Any
-) -> List[Dict[str, Any]]:
-    """
-    Stage adds Weighted Reciprocal Rank Fusion (WRRF) scoring.
-
-    First, it groups documents into an array, assigns rank by array index,
-    and then computes a weighted RRF score.
-
-    Args:
-        score_field: A unique string to identify the search being ranked.
-        penalty: A non-negative float (e.g., 60 for RRF-60). Controls the denominator.
-        weight: A float multiplier for this source's importance.
-        **kwargs: Ignored; allows future extensions or passthrough args.
-
-    Returns:
-        Aggregation pipeline stage for weighted RRF scoring.
-    """
-
-    return [
-        {"$group": {"_id": None, "docs": {"$push": "$$ROOT"}}},
-        {"$unwind": {"path": "$docs", "includeArrayIndex": "rank"}},
-        {
-            "$addFields": {
-                f"docs.{score_field}": {
-                    "$multiply": [
-                        weight,
-                        {"$divide": [1.0, {"$add": ["$rank", penalty, 1]}]},
-                    ]
-                },
-                "docs.rank": "$rank",
-                "_id": "$docs._id",
-            }
-        },
-        {"$replaceRoot": {"newRoot": "$docs"}},
-    ]