Update utils.py

utils.py

@@ -8,7 +8,7 @@ import numpy as np
 #Load .env file
 load_dotenv()
 
-#Get model name from environment (default if not found)
+#Getting the model name from environment (default if not found)
 MODEL_NAME = os.getenv("MODEL_NAME", "google/flan-t5-small")
 
 def load_handbook_text(pdf_path):
@@ -33,14 +33,14 @@ def answer_question(query, pdf_path="STUDENT-HANDBOOK-2021-EDITION.pdf"):
     chunks = split_text(text)
     context = find_relevant_chunk(query, chunks)
 
-    # Load the model (cached automatically by Hugging Face)
+    #Loading the model, which is cached automatically by Hugging Face.
     qa = pipeline(
         "text2text-generation",
         model=MODEL_NAME,
         tokenizer=MODEL_NAME
     )
 
-    # Improved prompt for more precise answers
+    #Improved prompts for more precise answers.
     prompt = (
         f"Use only the context below to answer concisely and clearly.\n\n"
         f"Question: {query}\n\n"
@@ -50,6 +50,6 @@ def answer_question(query, pdf_path="STUDENT-HANDBOOK-2021-EDITION.pdf"):
 
     result = qa(prompt, max_new_tokens=100, temperature=0.3, num_beams=4)
 
-    # Clean up output (trim redundant text)
+    #Cleaning up the output by trimming the redundant text
     answer = result[0]["generated_text"].strip()
     return answer