Update app.py

app.py

@@ -83,7 +83,7 @@ Settings.llm = HuggingFaceInferenceAPI(model_name=LLM_NAME,
 #                              task="None"
                              )
 # "BAAI/bge-m3"
-Settings.embed_model = HuggingFaceEmbedding(model_name="sentence-transformers/all-MiniLM-L6-v2")
+Settings.embed_model = HuggingFaceEmbedding(model_name=EMBED_MODEL) # "sentence-transformers/all-MiniLM-L6-v2"
 #documents = [Document(text="Indian parliament elections happened in April-May 2024. BJP Party won."),
 #            ]
 #index = VectorStoreIndex.from_documents(
@@ -133,17 +133,17 @@ def rag(input_text, history, jezik, file):
 #    )
 ##    else:
 ###    query_results = collection.query(
-    query_engine = index.as_query_engine(
-        similarity_top_k=3,
-        vector_store_query_mode="default",
-        filters=MetadataFilters(
-            filters=[
-                 ExactMatchFilter(key="lang", value=jezik),
-            ]
-        ),
-        alpha=None,
-        doc_ids=None,
-    )
+    #query_engine = index.as_query_engine(
+    #    similarity_top_k=3,
+    #    vector_store_query_mode="default",
+    #    filters=MetadataFilters(
+    #         filters=[
+    #             ExactMatchFilter(key="lang", value=jezik),
+    #        ]
+    #    ),
+    #    alpha=None,
+    #    doc_ids=None,
+    #)
     #query_results = index.query(
     #    query_texts = [ input_text ],
     #    n_results = max_results,