Final: Updated app.py

app.py

@@ -151,21 +151,23 @@ def ask_question(question):
 
     context = "\n".join([doc.page_content for doc in docs])
     prompt = generate_prompt(context, question)
-    raw_output = reasoning_pipeline(prompt)[0]['generated_text']
+    response = reasoning_pipeline(prompt)[0]['generated_text']
 
-    # 🧠 Smart cleanup: remove prompt leakage or echoed instructions
-    for section in ["Context:", "Question:", "Instructions:", "Use structured academic language"]:
-        raw_output = raw_output.replace(section, "").strip()
+    # Clean out prompt leakage
+    for token in ["Context:", "Question:", "Instructions:", "Use structured academic language"]:
+        response = response.replace(token, "").strip()
 
-    # Remove anything before answer starts if needed
-    if "Answer:" in raw_output:
-        raw_output = raw_output.split("Answer:")[-1].strip()
+    # Remove leading/trailing junk
+    if "Answer:" in response:
+        response = response.split("Answer:")[-1].strip()
+    if "." in response:
+        response = response.rsplit(".", 1)[0] + "."
 
-    # Trim trailing junk
-    if "." in raw_output:
-        raw_output = raw_output.rsplit(".", 1)[0] + "."
+    # ❗ Fallback if answer is empty or nonsense
+    if len(response.strip()) < 10:
+        return "❌ The model could not generate a meaningful answer based on the provided context."
 
-    return post_process_output(raw_output.strip(), question)
+    return post_process_output(response.strip(), question)
 
 
 # Gradio UI