Update app.py

app.py

@@ -86,26 +86,28 @@ def query_hybrid_search(query: str, client: QdrantClient, collection_name: str,
     
     return client.query_batch_points(
         collection_name=collection_name,
-        requests=QueryRequest(
-            prefetch=Prefetch(query=sparse_embeddings.as_object(), using="text-sparse", limit=10),
-            with_vector=False,
-            with_payload=True,
-            query=FusionQuery(fusion=Fusion.DSBF),
-            limit=3
-            #filter=Filter(must_not=[
-            #    HasIdCondition(has_id=[])
-            #])
-        ),
-        QueryRequest(
-            prefetch=Prefetch(query=dense_embeddings, using="text-dense", limit=10),
-            with_vector=False,
-            with_payload=True,
-            query=FusionQuery(fusion=Fusion.DSBF),
-            limit=3
-            #filter=Filter(must_not=[
-            #    HasIdCondition(has_id=[])
-            #])
-        )
+        requests=[
+            QueryRequest(
+                prefetch=Prefetch(query=sparse_embeddings.as_object(), using="text-sparse", limit=10),
+                with_vector=False,
+                with_payload=True,
+                query=FusionQuery(fusion=Fusion.DSBF),
+                limit=3
+                #filter=Filter(must_not=[
+                #    HasIdCondition(has_id=[])
+                #])
+            ),
+            QueryRequest(
+                prefetch=Prefetch(query=dense_embeddings, using="text-dense", limit=10),
+                with_vector=False,
+                with_payload=True,
+                query=FusionQuery(fusion=Fusion.DSBF),
+                limit=3
+                #filter=Filter(must_not=[
+                #    HasIdCondition(has_id=[])
+                #])
+            )
+        ]
     )
 
 def main(query: str, client: QdrantClient, collection_name: str, tokenizer: AutoTokenizer, llm: vllm.LLM, dense_model: OptimumEncoder, sparse_model: SparseTextEmbedding):