Update app.py

app.py

@@ -1,5 +1,5 @@
-# streamlit_app.py
 import os
+import json
 import streamlit as st
 from huggingface_hub import InferenceClient
 from dotenv import load_dotenv
@@ -17,64 +17,99 @@ st.set_page_config(
     page_icon="🧠",
     layout="centered"
 )
-
 st.title("🎓 Interview Preparation Chatbot")
 
-# Session state for conversation history and selected topic
-if "history" not in st.session_state:
-    st.session_state.history = []
+# Session state initialization
+if "questions" not in st.session_state:
+    st.session_state.questions = []
 if "topic" not in st.session_state:
     st.session_state.topic = "Machine Learning"
+if "score" not in st.session_state:
+    st.session_state.score = 0
+if "correct_count" not in st.session_state:
+    st.session_state.correct_count = 0
+if "incorrect_count" not in st.session_state:
+    st.session_state.incorrect_count = 0
 
-# Sidebar: Topic selection
+# Sidebar: Topic and Score display
 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",
-    ],
+    ["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)
 )
+st.sidebar.markdown("---")
+st.sidebar.header("Your Score")
+st.sidebar.markdown(f"**Total:** {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}")
 
-# Display existing chat history
-for sender, message in st.session_state.history:
-    role = "user" if sender == "You" else "assistant"
-    st.chat_message(role).write(message)
-
-# User input
-user_input = st.chat_input("Ask me anything about " + st.session_state.topic + "…")
+# Function to fetch a new MCQ question via HF Inference API
 
-if user_input:
-    # Append user message
-    st.session_state.history.append(("You", user_input))
-    st.chat_message("user").write(user_input)
+def fetch_question(topic):
+    prompt = {
+        "role": "system",
+        "content": (
+            "You are an expert interviewer. "
+            "Generate a multiple-choice question on the topic of {topic}. "
+            "Respond with a JSON object: {\"question\": str, \"options\": [str, ...], \"correct_index\": int}"
+        ).format(topic=topic)
+    }
+    response = client.chat.completions.create(
+        model="mistralai/Mistral-7B-Instruct-v0.1",
+        messages=[prompt]
+    )
+    content = response.choices[0].message["content"].strip()
+    try:
+        data = json.loads(content)
+        return data
+    except json.JSONDecodeError:
+        st.error("Failed to parse question. Please try again.")
+        return None
 
-    # Placeholder for bot response
-    placeholder = st.chat_message("assistant")
-    placeholder.write("⏳ Thinking...")
+# Buttons for initial and next 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})
+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})
 
-    # Build messages for the API call
-    messages = []
-    for role, text in [("user", msg) if s == "You" else ("assistant", msg)
-                       for s, msg in st.session_state.history]:
-        messages.append({"role": role, "content": text})
+# Display questions and capture answers
+for idx, q in enumerate(st.session_state.questions):
+    st.markdown(f"### Question {idx+1}")
+    st.write(q["question"])
 
-    # Call the Inference API
-    try:
-        response = client.chat.completions.create(
-            model="mistralai/Mistral-7B-Instruct-v0.1",
-            messages=messages
-        )
-        bot_reply = response.choices[0].message["content"].strip()
-    except Exception as e:
-        bot_reply = f"❌ API Error: {e}"
+    # Radio options
+    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}",
+        disabled=q["submitted"]
+    )
+    st.session_state.questions[idx]["selected"] = sel
 
-    # Display and store bot reply
-    placeholder.write(bot_reply)
-    st.session_state.history.append(("Bot", bot_reply))
+    # Submit button
+    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!")
+                st.session_state.score += 10
+                st.session_state.correct_count += 1
+            else:
+                st.error(f"Incorrect! Correct answer: {opts[q['correct_index']]}.")
+                st.session_state.score -= 10
+                st.session_state.incorrect_count += 1
 
+# Footer info
+st.markdown("---")
+st.markdown("*Points: +10 for correct, -10 for incorrect.*")