Update app.py

app.py

@@ -156,7 +156,7 @@ uuids = [str(uuid4()) for _ in range(len(documents))]
 docs = documents
 
 
-# sparse_embeddings = FastEmbedSparse(model_name="Qdrant/bm25")
+sparse_embeddings = FastEmbedSparse(model_name="Qdrant/bm25")
 embeddings = FastEmbedEmbeddings(model_name="sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2")
 
 client = QdrantClient(path="tmp/langchain_qdrant")
@@ -165,18 +165,20 @@ client = QdrantClient(path="tmp/langchain_qdrant")
 client.create_collection(
     collection_name="my_documents",
     vectors_config={"dense": VectorParams(size=3072, distance=Distance.COSINE)},
-    # sparse_vectors_config={
-    #     "sparse": SparseVectorParams(index=models.SparseIndexParams(on_disk=False))
-    # },
+    sparse_vectors_config={
+        "sparse": SparseVectorParams(index=models.SparseIndexParams(on_disk=False))
+    },
 )
 
 qdrant = QdrantVectorStore(
     client=client,
     collection_name="my_documents",
     embedding=embeddings,
-    # sparse_embedding=sparse_embeddings,
+    sparse_embedding=sparse_embeddings,
     # retrieval_mode=RetrievalMode.SPARSE,
-    # sparse_vector_name="sparse",
+    retrieval_mode=RetrievalMode.HYBRID,
+    vector_name="dense",
+    sparse_vector_name="sparse",
     
 )