Update app.py

app.py

@@ -122,6 +122,35 @@ def load_document_store():
     else:
         print("Error: knowledgebase.txt not found!")
      
+
+def load_document_store_once(file_path):
+    """Loads knowledgebase.txt into a dictionary where FAISS IDs map to text and embeddings"""
+    global document_store
+    document_store = {}  # Reset document store
+    all_texts = []
+    file_location = os.path.join(UPLOAD_DIR, os.path.basename(file_path))
+    if os.path.exists(file_location):
+        with open(file_location, "r", encoding="utf-8") as f:
+            lines = f.readlines()
+        
+        for i, line in enumerate(lines):
+            text = line.strip()
+            if text:
+                document_store[i] = {"text": text}  # Store text mapped to FAISS ID
+                all_texts.append(text)  # Collect all texts for embedding
+
+        print(f"Loaded {len(document_store)} documents into document_store.")
+    else:
+        print("Error: knowledgebase.txt not found!")
+    
+    # Generate embeddings for all documents
+    embeddings = bertmodel.encode(all_texts)
+    embeddings = embeddings.astype("float32")
+    
+    # Add embeddings to FAISS index
+    index.add_with_ids(embeddings, np.array(list(document_store.keys()), dtype=np.int64))
+    print(f"Added {len(all_texts)} document embeddings to FAISS index.")
+
  
 # Function to upload document
 def upload_document(file_path, embed_model):
@@ -222,7 +251,8 @@ def handle_upload():
     
     # Process the document using the upload_document function
     try:
-        upload_document(file_path, bertmodel)  # Assuming 'bertmodel' is defined elsewhere
+        load_document_store_once(file_path)
+    #    upload_document(file_path, bertmodel)  # Assuming 'bertmodel' is defined elsewhere
     except Exception as e:
         return jsonify({"error": f"Error processing file: {e}"}), 503