fix metadata mappings issue

Author: maxjakob

elasticsearch/helpers/vectorstore/_async/vectorstore.py

@@ -302,15 +302,14 @@ async def _create_index_if_not_exists(self) -> None:
             vector_field=self.vector_field,
             num_dimensions=self.num_dimensions,
         )
-
         if self.metadata_mappings:
             metadata = mappings["properties"].get("metadata", {"properties": {}})
             for key in self.metadata_mappings.keys():
                 if key in metadata:
                     raise ValueError(f"metadata key {key} already exists in mappings")
 
             metadata = dict(**metadata["properties"], **self.metadata_mappings)
-            mappings["properties"] = {"metadata": {"properties": metadata}}
+            mappings["properties"]["metadata"] = {"properties": metadata}
 
         await self.retrieval_strategy.before_index_creation(
             self.es_client, self.text_field, self.vector_field

elasticsearch/helpers/vectorstore/_sync/vectorstore.py

@@ -300,15 +300,14 @@ def _create_index_if_not_exists(self) -> None:
             vector_field=self.vector_field,
             num_dimensions=self.num_dimensions,
         )
-
         if self.metadata_mappings:
             metadata = mappings["properties"].get("metadata", {"properties": {}})
             for key in self.metadata_mappings.keys():
                 if key in metadata:
                     raise ValueError(f"metadata key {key} already exists in mappings")
 
             metadata = dict(**metadata["properties"], **self.metadata_mappings)
-            mappings["properties"] = {"metadata": {"properties": metadata}}
+            mappings["properties"]["metadata"] = {"properties": metadata}
 
         self.retrieval_strategy.before_index_creation(
             self.es_client, self.text_field, self.vector_field

test_elasticsearch/test_server/test_helpers_vectorstore/test_vectorstore.py

@@ -896,18 +896,26 @@ def test_metadata_mapping(
         }
         store = VectorStore(
             index_name=index_name,
-            retrieval_strategy=DenseVectorStrategy(),
+            retrieval_strategy=DenseVectorStrategy(distance=DistanceMetric.COSINE),
             embedding_service=FakeEmbeddings(),
+            num_dimensions=10,
             es_client=sync_client,
             metadata_mappings=test_mappings,
         )
 
         texts = ["foo", "foo", "foo"]
-        metadatas = [{"page": i} for i in range(len(texts))]
+        metadatas = [{"my_field": str(i)} for i in range(len(texts))]
         store.add_texts(texts=texts, metadatas=metadatas)
 
         mapping_response = sync_client.indices.get_mapping(index=index_name)
         mapping_properties = mapping_response[index_name]["mappings"]["properties"]
+        assert mapping_properties["vector_field"] == {
+            "type": "dense_vector",
+            "dims": 10,
+            "index": True,
+            "similarity": "cosine",
+        }
+
         assert "metadata" in mapping_properties
         for key, val in test_mappings.items():
             assert mapping_properties["metadata"]["properties"][key] == val