Update app.py

app.py

@@ -11,13 +11,6 @@ from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
 logging.basicConfig(level=logging.DEBUG)
 
 def load_faiss_index(index_path):
-    """
-    Load a FAISS index from a specified path.
-    Parameters:
-    - index_path (str): Path to the FAISS index file.
-    Returns:
-    - faiss.Index: Loaded FAISS index object.
-    """
     if not os.path.exists(index_path):
         logging.error(f"FAISS index not found at {index_path}. Please create the index first.")
         st.error(f"FAISS index not found at {index_path}. Please create the index first.")
@@ -34,9 +27,6 @@ def load_faiss_index(index_path):
         raise
 
 def load_llm():
-    """
-    Load the HuggingFace model for generating responses.
-    """
     checkpoint = "LaMini-T5-738M"
     tokenizer = AutoTokenizer.from_pretrained(checkpoint)
     model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint)
@@ -52,13 +42,6 @@ def load_llm():
     return pipe
 
 def process_answer(question):
-    """
-    Process the user's question using the FAISS index and LLM.
-    Parameters:
-    - question (str): User's question to be processed.
-    Returns:
-    - str: The answer generated by the LLM.
-    """
     index_path = 'faiss_index/index.faiss'
     embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
     try: