Update app/retriever.py

app/retriever.py

@@ -222,13 +222,13 @@ def get_context(
         search_kwargs = {
             "model_name": config.get("embeddings", "MODEL_NAME")
         }
-        model = SentenceTransformer(config.get("embeddings", "MODEL_NAME"))
-        query_vector = model.encode(query).tolist()
-        retrieved_docs = vectorstore.search(
-                      collection_name="EUDR",
-                      query_vector=query_vector,
-                      limit=top_k,
-                      with_payload=True)
+        #model = SentenceTransformer(config.get("embeddings", "MODEL_NAME"))
+        #query_vector = model.encode(query).tolist()
+        #retrieved_docs = vectorstore.search(
+        ##              collection_name="EUDR",
+        #              query_vector=query_vector,
+        #              limit=top_k,
+        #              with_payload=True)
         # filter support for QdrantVectorStore
         #if isinstance(vectorstore, QdrantVectorStore):
         #    filter_obj = create_filter(reports, sources, subtype, year)
@@ -236,7 +236,7 @@ def get_context(
         #        search_kwargs["filter"] = filter_obj
         
         # Perform initial retrieval
-        #retrieved_docs = vectorstore.search(query, top_k,)
+        retrieved_docs = vectorstore.search(query, top_k)
         
         logging.info(f"Retrieved {len(retrieved_docs)} documents for query: {query[:50]}...")