Update app.py

app.py

@@ -74,7 +74,7 @@ def retrieve(query,index,doc_name):
     sparse = bm25.encode_queries(query)
     res = client.embeddings.create(input=[query],model=dense_model)
     dense = res.data[0].embedding
-    hdense, hsparse = hybrid_scale(dense, sparse, alpha=0.5)
+    hdense, hsparse = hybrid_scale(dense, sparse, alpha=0)
     result = index.query(top_k=30,vector=hdense,sparse_vector=hsparse,include_metadata=True, filter = {'doc' :f'{doc_name}'})
     contexts = [(item['metadata']['content'], item['metadata']['source'],item['metadata']['pathTitle']) for item in result['matches']]
     return contexts