fix: VectorDB with metadata parameter

Signed-off-by: Varsha Prasad Narsing <varshaprasad96@gmail.com>

llama_stack/distribution/routers/vector_io.py

@@ -97,11 +97,14 @@ class VectorIORouter(VectorIO):
         vector_db_id: str,
         chunks: list[Chunk],
         ttl_seconds: int | None = None,
+        params: dict[str, Any] | None = None,
     ) -> None:
         logger.debug(
             f"VectorIORouter.insert_chunks: {vector_db_id}, {len(chunks)} chunks, ttl_seconds={ttl_seconds}, chunk_ids={[chunk.metadata['document_id'] for chunk in chunks[:3]]}{' and more...' if len(chunks) > 3 else ''}",
         )
-        return await self.routing_table.get_provider_impl(vector_db_id).insert_chunks(vector_db_id, chunks, ttl_seconds)
+        return await self.routing_table.get_provider_impl(vector_db_id).insert_chunks(
+            vector_db_id, chunks, ttl_seconds, params
+        )
 
     async def query_chunks(
         self,

llama_stack/providers/remote/vector_io/chroma/chroma.py

@@ -178,6 +178,7 @@ class ChromaVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
         vector_db_id: str,
         chunks: list[Chunk],
         ttl_seconds: int | None = None,
+        params: dict[str, Any] | None = None,
     ) -> None:
         index = await self._get_and_cache_vector_db_index(vector_db_id)
 

llama_stack/providers/remote/vector_io/milvus/milvus.py

@@ -183,6 +183,7 @@ class MilvusVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
         vector_db_id: str,
         chunks: list[Chunk],
         ttl_seconds: int | None = None,
+        params: dict[str, Any] | None = None,
     ) -> None:
         index = await self._get_and_cache_vector_db_index(vector_db_id)
         if not index:

llama_stack/providers/remote/vector_io/pgvector/pgvector.py

@@ -215,6 +215,7 @@ class PGVectorVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
         vector_db_id: str,
         chunks: list[Chunk],
         ttl_seconds: int | None = None,
+        params: dict[str, Any] | None = None,
     ) -> None:
         index = await self._get_and_cache_vector_db_index(vector_db_id)
         await index.insert_chunks(chunks)

llama_stack/providers/remote/vector_io/qdrant/qdrant.py

@@ -370,12 +370,7 @@ class QdrantVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolP
         if params is not None:
             distance_metric = params.get("distance_metric")
 
-        # Create metadata dict with distance_metric if provided
+        await index.insert_chunks(chunks, distance_metric=distance_metric)
-        metadata = None
-        if distance_metric is not None:
-            metadata = {"distance_metric": distance_metric}
-
-        await index.insert_chunks(chunks, metadata=metadata)
 
     async def query_chunks(
         self,

llama_stack/providers/remote/vector_io/weaviate/weaviate.py

@@ -188,6 +188,7 @@ class WeaviateVectorIOAdapter(
         vector_db_id: str,
         chunks: list[Chunk],
         ttl_seconds: int | None = None,
+        params: dict[str, Any] | None = None,
     ) -> None:
         index = await self._get_and_cache_vector_db_index(vector_db_id)
         if not index: