Update app.py

app.py

@@ -13,12 +13,18 @@ import pickle
 model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
 index = faiss.read_index('IPC_index.faiss')
 index2 = faiss.read_index('CrpC_index.faiss')
-flattened_data = pickle.load('IPC_F')
-pdf_filenames = pickle.load('IPC_N')
-chunk_indices = pickle.load('IPC_C')
-flattened_data2 = pickle.load('CrPC_F')
-pdf_filenames2 = pickle.load('CrPC_N')
-chunk_indices2 = pickle.load('CrPC_C')
+with open('IPC_N.pkl', 'rb') as f:
+    flattened_data = pickle.load(f)
+with open('IPC_F.pkl', 'rb') as f:
+    pdf_filenames = pickle.load(f)
+with open('IPC_C.pkl', 'rb') as f:
+    chunk_indices = pickle.load(f)
+with open('CrPC_N.pkl', 'rb') as f:
+    flattened_data2 = pickle.load(f)
+with open('CrPC_F.pkl', 'rb') as f:
+    pdf_filenames2 = pickle.load(f)
+with open('CrPC_C.pkl', 'rb') as f:
+    chunk_indices2 = pickle.load(f)
 # Step 3: Retrieval with Citations using PDF filename
 def retrieve_info_with_citation(query, top_k=5):
     query_embedding = model.encode([query])