Update app.py

app.py

@@ -37,19 +37,19 @@ def extract_text_from_docx(docx_path):
     return text
 
 
-# Initialize the embedding model (same as before)
+# Initialize the embedding model 
 embedding_model = SentenceTransformer('all-MiniLM-L6-v2')
 
 
-# Hugging Face API token (same as before)
+# Hugging Face API token 
 api_token = os.getenv('HUGGINGFACEHUB_API_TOKEN')
 if not api_token:
     raise ValueError("HUGGINGFACEHUB_API_TOKEN environment variable is not set")
 
 
-# Define RAG models (replace with your chosen models)
+# Define RAG models 
 generator_model_name = "facebook/bart-base"
-retriever_model_name = "facebook/bart-base"  # Can be the same as generator
+retriever_model_name = "facebook/bart-base"  
 
 generator = AutoModelForSeq2SeqLM.from_pretrained(generator_model_name)
 generator_tokenizer = AutoTokenizer.from_pretrained(generator_model_name)
@@ -103,8 +103,8 @@ def upload_files(files):
             embeddings = embedding_model.encode(sentences)
             index.add(np.array(embeddings))
 
-        # Save the updated index and documents (same as before)
-        # ...
+        # Save the updated index and documents 
+    
         return "Files processed successfully"
     except Exception as e:
         print(f"Error processing files: {e}")