Update src/app.py

Added quiz component

src/app.py

@@ -11,6 +11,7 @@ import doc_loader
 from openai import OpenAI
 from datetime import datetime
 from test_integration import run_tests
+from core.QuizEngine import QuizEngine
 
 # --- CONFIGURATION ---
 st.set_page_config(page_title="Navy AI Toolkit", page_icon="⚓", layout="wide")
@@ -22,6 +23,15 @@ OPENAI_KEY = os.getenv("OPENAI_API_KEY")
 if "roles" not in st.session_state:
     st.session_state.roles = []
 
+if "quiz_state" not in st.session_state:
+    st.session_state.quiz_state = {
+        "active": False,        # Is a question currently displayed?
+        "question_data": None,  # The current acronym object
+        "user_answer": "",      # What the user typed
+        "feedback": None,       # The LLM's grading response
+        "streak": 0             # Fun gamification metric
+    }
+
 # --- FLATTENER LOGIC (Integrated) ---
 class OutlineProcessor:
     """Parses text outlines for the Flattener tool."""
@@ -239,7 +249,7 @@ update_sidebar_metrics()
 
 # --- MAIN APP ---
 st.title("⚓ Navy AI Toolkit")
-tab1, tab2 = st.tabs(["💬 Chat Playground", "📂 Knowledge & Tools"])
+tab1, tab2, tab3 = st.tabs(["💬 Chat Playground", "📂 Knowledge & Tools", "⚡ Quiz Mode"])
 
 # === TAB 1: CHAT ===
 with tab1:
@@ -456,6 +466,92 @@ with tab2:
                             st.error(msg)
 
     st.divider()
+
+# === TAB 3: QUIZ MODE ===
+with tab3:
+    st.header("⚡ Acronym Lightning Round")
+    st.caption("Test your knowledge against your own Acronym Dictionary.")
+
+    # Initialize Engine
+    quiz = QuizEngine()
+    qs = st.session_state.quiz_state
+
+    # METRICS ROW
+    m1, m2, m3 = st.columns(3)
+    m1.metric("Streak", qs["streak"])
+    
+    # 1. START / NEXT QUESTION BUTTON
+    if not qs["active"]:
+        if st.button("🚀 Start New Question", type="primary"):
+            q_data = quiz.get_random_acronym()
+            if q_data:
+                qs["active"] = True
+                qs["question_data"] = q_data
+                qs["feedback"] = None
+                qs["user_answer"] = ""
+                st.rerun()
+            else:
+                st.warning("Acronym Dictionary is empty! Please upload 'acronyms.json' or run the local extractor.")
+
+    # 2. QUESTION DISPLAY
+    if qs["active"] and qs["question_data"]:
+        st.divider()
+        st.markdown(f"### {qs['question_data']['question']}")
+        
+        # User Input
+        # We use a form so hitting 'Enter' submits the answer
+        with st.form(key="quiz_form"):
+            user_input = st.text_input("Your Definition:", value=qs.get("user_answer_temp", ""))
+            submit_btn = st.form_submit_button("Submit Answer")
+        
+        if submit_btn and user_input:
+            qs["user_answer"] = user_input
+            
+            # 3. GRADING LOGIC
+            with st.spinner("The Board is deliberating..."):
+                # Construct Prompt
+                term = qs["question_data"]["term"]
+                correct_def = qs["question_data"]["correct_definition"]
+                prompt = quiz.construct_grading_prompt(term, correct_def, user_input)
+                
+                # Call LLM (Reusing your existing query helper)
+                msgs = [{"role": "user", "content": prompt}]
+                grade, usage = query_model_universal(
+                    msgs, 300, model_choice, st.session_state.get("user_openai_key")
+                )
+                
+                qs["feedback"] = grade
+                
+                # Simple Streak Logic (If LLM says PASS)
+                if "GRADE:** PASS" in grade or "GRADE:** Pass" in grade:
+                    qs["streak"] += 1
+                elif "GRADE:** FAIL" in grade:
+                    qs["streak"] = 0
+                    
+                # Log usage
+                if usage:
+                    m_name = "GPT-4o" if "GPT-4o" in model_choice else model_choice.split()[0]
+                    tracker.log_usage(m_name, usage["input"], usage["output"])
+                    update_sidebar_metrics()
+            
+            st.rerun()
+
+    # 4. FEEDBACK DISPLAY
+    if qs["feedback"]:
+        st.divider()
+        if "PASS" in qs["feedback"]:
+            st.success("✅ CORRECT")
+        else:
+            st.error("❌ INCORRECT")
+            
+        st.markdown(qs["feedback"])
+        st.info(f"**Official Definition:** {qs['question_data']['correct_definition']}")
+        
+        if st.button("Next Question ➡️"):
+            qs["active"] = False
+            qs["question_data"] = None
+            qs["feedback"] = None
+            st.rerun()
     
     # DB MANAGER
     st.subheader("Database Management")