feat(qdrant): Use Qdrant's built-in MMR search (#32302)

Author: Anush008

libs/partners/qdrant/langchain_qdrant/qdrant.py

@@ -10,14 +10,11 @@
     Any,
 )
 
-import numpy as np
 from langchain_core.documents import Document
 from langchain_core.embeddings import Embeddings
 from langchain_core.vectorstores import VectorStore
 from qdrant_client import QdrantClient, models
 
-from langchain_qdrant._utils import maximal_marginal_relevance
-
 if TYPE_CHECKING:
     from collections.abc import Generator, Iterable, Sequence
 
@@ -828,10 +825,13 @@ def max_marginal_relevance_search_with_score_by_vector(
         """
         results = self.client.query_points(
             collection_name=self.collection_name,
-            query=embedding,
+            query=models.NearestQuery(
+                nearest=embedding,
+                mmr=models.Mmr(diversity=lambda_mult, candidates_limit=fetch_k),
+            ),
             query_filter=filter,
             search_params=search_params,
-            limit=fetch_k,
+            limit=k,
             with_payload=True,
             with_vectors=True,
             score_threshold=score_threshold,
@@ -840,26 +840,17 @@ def max_marginal_relevance_search_with_score_by_vector(
             **kwargs,
         ).points
 
-        embeddings = [
-            result.vector
-            if isinstance(result.vector, list)
-            else result.vector.get(self.vector_name)  # type: ignore[union-attr]
-            for result in results
-        ]
-        mmr_selected = maximal_marginal_relevance(
-            np.array(embedding), embeddings, k=k, lambda_mult=lambda_mult
-        )
         return [
             (
                 self._document_from_point(
-                    results[i],
+                    result,
                     self.collection_name,
                     self.content_payload_key,
                     self.metadata_payload_key,
                 ),
-                results[i].score,
+                result.score,
             )
-            for i in mmr_selected
+            for result in results
         ]
 
     def delete(  # type: ignore[override]

libs/partners/qdrant/pyproject.toml

@@ -7,7 +7,7 @@ authors = []
 license = { text = "MIT" }
 requires-python = ">=3.10.0,<4.0.0"
 dependencies = [
-    "qdrant-client>=1.10.1,<2.0.0",
+    "qdrant-client>=1.15.1,<2.0.0",
     "pydantic>=2.7.4,<3.0.0",
     "langchain-core>=1.0.0,<2.0.0",
 ]

libs/partners/qdrant/tests/integration_tests/qdrant_vector_store/test_mmr.py

@@ -63,7 +63,7 @@ def test_qdrant_mmr_search(
         output,
         [
             Document(page_content="foo", metadata={"page": 0}),
-            Document(page_content="baz", metadata={"page": 2}),
+            Document(page_content="bar", metadata={"page": 1}),
         ],
     )