Update src/app.py

src/app.py

@@ -510,24 +510,32 @@ with tab3:
 
                 # MODE B: DOCUMENTS
                 else:
-                    q_ctx = quiz.get_document_context(st.session_state.username)
-                    if q_ctx:
-                        # We have the text, now we need the LLM to write the question
-                        prompt = quiz.construct_question_generation_prompt(q_ctx["context_text"])
-                        
-                        # Generate Question using your existing query helper
-                        msgs = [{"role": "user", "content": prompt}]
-                        question_text, usage = query_model_universal(
-                            msgs, 300, model_choice, st.session_state.get("user_openai_key")
-                        )
+                    # Retry logic for the LLM's "SKIP" response
+                    valid_question_found = False
+                    attempts = 0
+                    
+                    while not valid_question_found and attempts < 3:
+                        attempts += 1
+                        q_ctx = quiz.get_document_context(st.session_state.username)
                         
-                        qs["active"] = True
-                        qs["question_data"] = q_ctx
-                        qs["generated_question_text"] = question_text # Store the LLM-generated question
-                        qs["feedback"] = None
-                        st.rerun()
-                    else:
-                        st.error("No documents found! Upload some .txt or .md files first.")
+                        if q_ctx:
+                            prompt = quiz.construct_question_generation_prompt(q_ctx["context_text"])
+                            question_text, usage = query_model_universal(
+                                [{"role": "user", "content": prompt}], 
+                                300, model_choice, st.session_state.get("user_openai_key")
+                            )
+                            
+                            # If LLM liked the chunk, it gave us a question. If not, it said "SKIP".
+                            if "SKIP" not in question_text and len(question_text) > 10:
+                                valid_question_found = True
+                                qs["active"] = True
+                                qs["question_data"] = q_ctx
+                                qs["generated_question_text"] = question_text
+                                qs["feedback"] = None
+                                st.rerun()
+                    
+                    if not valid_question_found:
+                        st.warning("Tried to find a good engineering question but the available text was too administrative. Try uploading denser technical notes!")
 
     # 3. QUIZ INTERFACE
     if qs["active"]: