Update app.py

app.py

@@ -7,129 +7,153 @@ import traceback
 
 # Load environment variables
 load_dotenv()
-
 hf_token = os.getenv("HUGGINGFACEHUB_API_TOKEN")
-client = InferenceClient(provider="auto", api_key=hf_token)
-
-# Streamlit configuration
-st.set_page_config(
-    page_title="Interview Prep Bot",
-    page_icon="🧠",
-    layout="centered"
-)
+
+# Setup Streamlit
+st.set_page_config(page_title="Interview Prep Bot", page_icon="🧠", layout="centered")
 st.title("🎓 Interview Preparation Chatbot")
 
-# Initialize session state
-if "questions" not in st.session_state:
+# Token check
+if not hf_token:
+    st.error("Token not found. Check your .env file.")
+    st.stop()
+
+model_id = "mistralai/Mixtral-8x7B-Instruct-v0.1"
+try:
+    client = InferenceClient(model=model_id, token=hf_token)
+    st.success("🔗 Connected to Hugging Face Inference API.")
+except Exception as e:
+    st.error(f"Failed to initialize InferenceClient: {e}")
+    st.stop()
+
+# Debug reset button (useful once to fix corrupted state)
+if st.button("🔄 Reset App"):
+    for key in list(st.session_state.keys()):
+        del st.session_state[key]
+    st.rerun()
+
+# Sidebar topic & stats
+topics = [
+    "Machine Learning",
+    "Data Structures",
+    "Python",
+    "Generative AI",
+    "Computer Vision",
+    "Deep Learning"
+]
+st.sidebar.header("🔍 Select Topic")
+topic = st.sidebar.selectbox("Topic:", topics)
+
+# Safely initialize session state
+if "questions" not in st.session_state or not isinstance(st.session_state.questions, list):
     st.session_state.questions = []
-if "topic" not in st.session_state:
-    st.session_state.topic = "Machine Learning"
-if "score" not in st.session_state:
+
+if "score" not in st.session_state or not isinstance(st.session_state.score, int):
     st.session_state.score = 0
-if "correct_count" not in st.session_state:
+
+if "correct_count" not in st.session_state or not isinstance(st.session_state.correct_count, int):
     st.session_state.correct_count = 0
-if "incorrect_count" not in st.session_state:
+
+if "incorrect_count" not in st.session_state or not isinstance(st.session_state.incorrect_count, int):
     st.session_state.incorrect_count = 0
 
-# Sidebar: Topic selection and scoring
-st.sidebar.header("Practice Topic")
-st.session_state.topic = st.sidebar.selectbox(
-    "Select a topic:",
-    ["Machine Learning", "Data Structures", "Python", "Generative AI", "Computer Vision", "Deep Learning"],
-    index=["Machine Learning", "Data Structures", "Python", "Generative AI", "Computer Vision", "Deep Learning"].index(st.session_state.topic)
-)
+if "active_question" not in st.session_state:
+    st.session_state.active_question = None
+
+if "last_action" not in st.session_state:
+    st.session_state.last_action = ""
+
 st.sidebar.markdown("---")
-st.sidebar.header("Your Score")
-st.sidebar.markdown(f"**Total:** {len(st.session_state.questions)}")
+st.sidebar.header("📊 Your Score")
+st.sidebar.markdown(f"**Questions:** {len(st.session_state.questions)}")
 st.sidebar.markdown(f"**Correct:** {st.session_state.correct_count}")
 st.sidebar.markdown(f"**Incorrect:** {st.session_state.incorrect_count}")
 st.sidebar.markdown(f"**Points:** {st.session_state.score}")
 
-# Function to fetch an MCQ question with enhanced debug logging
-
-def fetch_question(topic):
-    prompt = {
-        "role": "system",
-        "content": (
-            f"You are an expert interviewer. Generate a multiple-choice question on the topic of {topic}. "
-            "Respond ONLY with a valid JSON object: {\"question\": str, \"options\": [str,...], \"correct_index\": int}."
-        )
-    }
-    try:
-        response = client.chat.completions.create(
-            model="mistralai/Mistral-7B-Instruct-v0.1",
-            messages=[prompt]
-        )
-        # Debug: show full response for tracing
-        st.write("**[DEBUG] Full response object:**")
-        st.json(response.to_dict())
-        content = response.choices[0].message.get("content", "").strip()
-        st.write("**[DEBUG] Raw content:**")
-        st.code(content)
-    except Exception as e:
-        st.error(f"Error during API call: {e}")
-        st.text(traceback.format_exc())
-        return None
-    # Attempt JSON parsing
-    try:
-        data = json.loads(content)
-    except json.JSONDecodeError as jde:
-        st.error(f"JSON decode error: {jde}")
-        st.write("**[DEBUG] Content that failed JSON parsing:**")
-        st.code(content)
-        return None
-    except Exception as e:
-        st.error(f"Unexpected parsing error: {e}")
-        st.text(traceback.format_exc())
-        return None
-    # Validate structure
-    question = data.get("question")
-    options = data.get("options")
-    correct_index = data.get("correct_index")
-    if not question or not isinstance(options, list) or not isinstance(correct_index, int):
-        st.error("Invalid question structure: missing keys or wrong types.")
-        st.write("**[DEBUG] Parsed JSON:**")
-        st.json(data)
-        return None
-    return {"question": question, "options": options, "correct_index": correct_index}
-
-# Buttons to get or advance questions
-if not st.session_state.questions:
-    if st.button("Get Question"):
-        q = fetch_question(st.session_state.topic)
-        if q:
-            st.session_state.questions.append({**q, "selected": None, "submitted": False})
+# Fetch unique MCQ
+def fetch_mcq(topic, past_questions=None, max_retries=3):
+    if past_questions is None:
+        past_questions = set(q["question"] for q in st.session_state.questions)
+
+    prompt_template = (
+        f"Generate a multiple-choice question about {topic}. "
+        "Return only JSON with keys: question (string), options (4 strings), correct_index (0-based integer). "
+        "Make the question unique and different from this list:\n" +
+        json.dumps(list(past_questions))
+    )
+
+    for _ in range(max_retries):
+        try:
+            response = client.chat_completion(
+                model=model_id,
+                messages=[
+                    {"role": "system", "content": "You are a helpful MCQ bot that returns JSON only."},
+                    {"role": "user", "content": prompt_template}
+                ]
+            )
+            content = response.choices[0].message.get("content", "").strip()
+            data = json.loads(content)
+
+            new_question = data.get("question", "").strip()
+            if new_question in past_questions:
+                continue
+
+            return {
+                "question": new_question,
+                "options": data["options"],
+                "correct_index": data["correct_index"],
+                "selected": None,
+                "submitted": False
+            }
+
+        except Exception as e:
+            st.error("❌ Error fetching MCQ")
+            st.text(traceback.format_exc())
+            return None
+
+    st.warning("⚠️ Couldn't generate a unique question after several tries.")
+    return None
+
+# Handle logic based on last action
+if st.session_state.last_action == "submit":
+    new_q = fetch_mcq(topic)
+    if new_q:
+        st.session_state.active_question = new_q
+    st.session_state.last_action = ""
+
+# Render active question or show start button
+q = st.session_state.active_question
+
+if not q:
+    if st.button("🧠 Start Interview"):
+        new_q = fetch_mcq(topic)
+        if new_q:
+            st.session_state.active_question = new_q
 else:
-    if st.button("Next Question"):
-        q = fetch_question(st.session_state.topic)
-        if q:
-            st.session_state.questions.append({**q, "selected": None, "submitted": False})
-
-# Display questions and capture answers
-for idx, q in enumerate(st.session_state.questions):
-    st.markdown(f"### Question {idx+1}")
-    st.write(q["question"])
-    opts = q["options"]
-    sel = st.radio(
-        "Choose an answer:",
-        options=list(range(len(opts))),
-        format_func=lambda i: opts[i],
-        index=q["selected"] if q["selected"] is not None else 0,
-        key=f"radio_{idx}",
+    st.markdown(f"### ❓ {q['question']}")
+    choice = st.radio(
+        "Choose your answer:",
+        range(4),
+        format_func=lambda i: q["options"][i],
+        index=q.get("selected", 0),
+        key="answer",
         disabled=q["submitted"]
     )
-    st.session_state.questions[idx]["selected"] = sel
+    st.session_state.active_question["selected"] = choice
+
     if not q["submitted"]:
-        if st.button("Submit Answer", key=f"submit_{idx}"):
-            st.session_state.questions[idx]["submitted"] = True
-            if sel == q["correct_index"]:
-                st.success("Correct! +10 points")
+        if st.button("✅ Submit Answer"):
+            q["submitted"] = True
+            if choice == q["correct_index"]:
+                st.success("✅ Correct! +10 points")
                 st.session_state.score += 10
                 st.session_state.correct_count += 1
             else:
-                st.error(f"Incorrect! Correct: {opts[q['correct_index']]} (-10 points)")
+                correct_ans = q["options"][q["correct_index"]]
+                st.error(f"❌ Incorrect. Correct answer: {correct_ans} (-10 points)")
                 st.session_state.score -= 10
                 st.session_state.incorrect_count += 1
-# Footer
-st.markdown("---")
-st.markdown("*Correct: +10 pts | Incorrect: -10 pts*")
+
+            st.session_state.questions.append(q)
+            st.session_state.last_action = "submit"
+            st.rerun()  # <== Force rerun after submission