Update rag_engine.py

rag_engine.py

@@ -29,7 +29,7 @@ def setup_gcp_client():
         
         # Get bucket name from secrets - required
         try:
-            bucket_name_gcs = st.secrets["bucket_name_gcs"]
+            bucket_name_gcs = st.secrets["BUCKET_NAME_GCS"]
         except KeyError:
             print("❌ Error: GCS bucket name not found in secrets")
             return None
@@ -67,9 +67,9 @@ def load_model():
         
         # Get embedding model path from secrets
         try:
-            embedding_model = st.secrets["embedding_model"]
+            embedding_model = st.secrets["EMBEDDING_MODEL"]
         except KeyError:
-            print("❌ Error: Embedding model not found in secrets")
+            print("❌ Error: Embedding model path not found in secrets")
             return None, None
             
         # Load tokenizer and model
@@ -131,10 +131,10 @@ def load_data_files():
     
     # Get GCS paths from secrets - required
     try:
-        metadata_file_gcs = st.secrets["metadata_file_gcs"]
-        embeddings_file_gcs = st.secrets["embeddings_file_gcs"]
-        faiss_index_file_gcs = st.secrets["faiss_index_file_gcs"]
-        text_chunks_file_gcs = st.secrets["text_chunks_file_gcs"]
+        metadata_file_gcs = st.secrets["METADATA_PATH_GCS"]
+        embeddings_file_gcs = st.secrets["EMBEDDINGS_PATH_GCS"]
+        faiss_index_file_gcs = st.secrets["INDICES_PATH_GCS"]
+        text_chunks_file_gcs = st.secrets["CHUNKS_PATH_GCS"]
     except KeyError as e:
         print(f"❌ Error: Required GCS path not found in secrets: {e}")
         return None, None, None
@@ -338,7 +338,7 @@ def answer_with_llm(query, context=None, word_limit=100):
 
         # Get LLM model from secrets
         try:
-            llm_model = st.secrets["llm_model"]
+            llm_model = st.secrets["LLM_MODEL"]
         except KeyError:
             print("❌ Error: LLM model not found in secrets")
             return "I apologize, but I'm unable to answer at the moment."