Update app.py

app.py

@@ -1,349 +1,43 @@
-import streamlit as st
-import time
-import requests
-from streamlit.components.v1 import html
-
-# Import transformers and cache the help agent for performance
-@st.cache_resource
-def get_help_agent():
-    from transformers import pipeline
-    # Using BlenderBot 400M Distill as the public conversational model
-    return pipeline("conversational", model="facebook/blenderbot-400M-distill")
-
-# Custom CSS for professional look (fixed text color)
-def inject_custom_css():
-    st.markdown("""
-    <style>
-        @import url('https://fonts.googleapis.com/css2?family=Poppins:wght@400;600;700&display=swap');
-
-        * {
-            font-family: 'Poppins', sans-serif;
-        }
-
-        .title {
-            font-size: 3rem !important;
-            font-weight: 700 !important;
-            color: #6C63FF !important;
-            text-align: center;
-            margin-bottom: 0.5rem;
-        }
-
-        .subtitle {
-            font-size: 1.2rem !important;
-            text-align: center;
-            color: #666 !important;
-            margin-bottom: 2rem;
-        }
-
-        .question-box {
-            background: #F8F9FA;
-            border-radius: 15px;
-            padding: 2rem;
-            margin: 1.5rem 0;
-            box-shadow: 0 4px 6px rgba(0,0,0,0.1);
-            color: black !important;
-        }
-
-        .answer-btn {
-            border-radius: 12px !important;
-            padding: 0.5rem 1.5rem !important;
-            font-weight: 600 !important;
-            margin: 0.5rem !important;
-        }
-
-        .yes-btn {
-            background: #6C63FF !important;
-            color: white !important;
-        }
-
-        .no-btn {
-            background: #FF6B6B !important;
-            color: white !important;
-        }
-
-        .final-reveal {
-            animation: fadeIn 2s;
-            font-size: 2.5rem;
-            color: #6C63FF;
-            text-align: center;
-            margin: 2rem 0;
-        }
-
-        @keyframes fadeIn {
-            from { opacity: 0; }
-            to { opacity: 1; }
-        }
-
-        .confetti {
-            position: fixed;
-            top: 0;
-            left: 0;
-            width: 100%;
-            height: 100%;
-            pointer-events: none;
-            z-index: 1000;
-        }
-        
-        .confidence-meter {
-            height: 10px;
-            background: linear-gradient(90deg, #FF6B6B 0%, #6C63FF 100%);
-            border-radius: 5px;
-            margin: 10px 0;
-        }
-    </style>
-    """, unsafe_allow_html=True)
-
-# Confetti animation
-def show_confetti():
-    html("""
-    <canvas id="confetti-canvas" class="confetti"></canvas>
-    <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/confetti.browser.min.js"></script>
-    <script>
-    const canvas = document.getElementById('confetti-canvas');
-    const confetti = confetti.create(canvas, { resize: true });
-    confetti({
-        particleCount: 150,
-        spread: 70,
-        origin: { y: 0.6 }
-    });
-    setTimeout(() => { canvas.remove(); }, 5000);
-    </script>
-    """)
-
-# Enhanced AI question generation for guessing game using Llama model
-def ask_llama(conversation_history, category, is_final_guess=False):
-    api_url = "https://api.groq.com/openai/v1/chat/completions"
-    headers = {
-        "Authorization": "Bearer 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",
-        "Content-Type": "application/json"
-    }
-
-    system_prompt = f"""You're playing 20 questions to guess a {category}. Follow these rules:
-1. Ask strategic, non-repeating yes/no questions that narrow down possibilities
-2. Consider all previous answers carefully before asking next question
-3. If you're very confident (80%+ sure), respond with "Final Guess: [your guess]"
-4. For places: ask about continent, climate, famous landmarks, country, city or population
-5. For people: ask about fictional or real, profession, gender, alive/dead, nationality, or fame
-6. For objects: ask about size, color, usage, material, or where it's found
-7. Never repeat questions and always make progress toward guessing"""
-
-    if is_final_guess:
-        prompt = f"""Based on these answers about a {category}, provide ONLY your final guess with no extra text:
-{conversation_history}"""
-    else:
-        prompt = "Ask your next strategic yes/no question that will best narrow down the possibilities."
-
-    messages = [
-        {"role": "system", "content": system_prompt},
-        *conversation_history,
-        {"role": "user", "content": prompt}
-    ]
-
-    data = {
-        "model": "llama-3.3-70b-versatile",
-        "messages": messages,
-        "temperature": 0.7 if is_final_guess else 0.8,
-        "max_tokens": 100
-    }
-
-    try:
-        response = requests.post(api_url, headers=headers, json=data)
-        response.raise_for_status()
-        return response.json()["choices"][0]["message"]["content"]
-    except Exception as e:
-        st.error(f"Error calling Llama API: {str(e)}")
-        return "Could not generate question"
-
-# New function for the help AI assistant using a Hugging Face chatbot model
-def ask_help_agent(query):
-    # Use a try/except block to import Conversation from the correct module,
-    # accommodating different versions of transformers
-    try:
-        from transformers import Conversation
-    except ImportError:
-        from transformers.pipelines.conversational import Conversation
-    # Get the cached help agent (BlenderBot)
-    help_agent = get_help_agent()
-    conversation = Conversation(query)
-    result = help_agent(conversation)
-    # The generated response is stored in generated_responses list
-    return result.generated_responses[-1]
-
-# Main game logic
-def main():
-    inject_custom_css()
-
-    st.markdown('<div class="title">KASOTI</div>', unsafe_allow_html=True)
-    st.markdown('<div class="subtitle">The Smart Guessing Game</div>', unsafe_allow_html=True)
-
-    if 'game_state' not in st.session_state:
-        st.session_state.game_state = "start"
-        st.session_state.questions = []
-        st.session_state.current_q = 0
-        st.session_state.answers = []
-        st.session_state.conversation_history = []
-        st.session_state.category = None
-        st.session_state.final_guess = None
-        st.session_state.help_conversation = []  # separate history for help agent
-
-    # Start screen
-    if st.session_state.game_state == "start":
-        st.markdown("""
-        <div class="question-box">
-            <h3>Welcome to <span style='color:#6C63FF;'>KASOTI 🎯</span></h3>
-            <p>Think of something and I'll try to guess it in 20 questions or less!</p>
-            <p>Choose a category:</p>
-            <ul>
-                <li><strong>Person</strong> - celebrity, fictional character, historical figure</li>
-                <li><strong>Place</strong> - city, country, landmark, geographical location</li>
-                <li><strong>Object</strong> - everyday item, tool, vehicle, etc.</li>
-            </ul>
-            <p>Type your category below to begin:</p>
-        </div>
-        """, unsafe_allow_html=True)
-
-        with st.form("start_form"):
-            category_input = st.text_input("Enter category (person/place/object):").strip().lower()
-            if st.form_submit_button("Start Game"):
-                if not category_input:
-                    st.error("Please enter a category!")
-                elif category_input not in ["person", "place", "object"]:
-                    st.error("Please enter either 'person', 'place', or 'object'!")
-                else:
-                    st.session_state.category = category_input
-                    first_question = ask_llama([
-                        {"role": "user", "content": "Ask your first strategic yes/no question."}
-                    ], category_input)
-                    st.session_state.questions = [first_question]
-                    st.session_state.conversation_history = [
-                        {"role": "assistant", "content": first_question}
-                    ]
-                    st.session_state.game_state = "gameplay"
-                    st.rerun()
-
-    # Gameplay screen
-    elif st.session_state.game_state == "gameplay":
-        current_question = st.session_state.questions[st.session_state.current_q]
-        
-        # Check if AI made a guess
-        if "Final Guess:" in current_question:
-            st.session_state.final_guess = current_question.split("Final Guess:")[1].strip()
-            st.session_state.game_state = "confirm_guess"
-            st.rerun()
-        
-        st.markdown(f'<div class="question-box">Question {st.session_state.current_q + 1}/20:<br><br>'
-                    f'<strong>{current_question}</strong></div>',
-                    unsafe_allow_html=True)
-        
-        with st.form("answer_form"):
-            answer_input = st.text_input("Your answer (yes/no/both):", 
-                                       key=f"answer_{st.session_state.current_q}").strip().lower()
-            if st.form_submit_button("Submit"):
-                if answer_input not in ["yes", "no", "both"]:
-                    st.error("Please answer with 'yes', 'no', or 'both'!")
-                else:
-                    st.session_state.answers.append(answer_input)
-                    st.session_state.conversation_history.append(
-                        {"role": "user", "content": answer_input}
-                    )
-
-                    # Generate next response
-                    next_response = ask_llama(
-                        st.session_state.conversation_history,
-                        st.session_state.category
-                    )
-                    
-                    # Check if AI made a guess
-                    if "Final Guess:" in next_response:
-                        st.session_state.final_guess = next_response.split("Final Guess:")[1].strip()
-                        st.session_state.game_state = "confirm_guess"
-                    else:
-                        st.session_state.questions.append(next_response)
-                        st.session_state.conversation_history.append(
-                            {"role": "assistant", "content": next_response}
-                        )
-                        st.session_state.current_q += 1
-
-                        # Stop after 20 questions max
-                        if st.session_state.current_q >= 20:
-                            st.session_state.game_state = "result"
-                    
-                    st.rerun()
-
-        # Side Help Option: independent chat with an AI help assistant (Hugging Face model)
-        with st.expander("Need Help? Chat with AI Assistant"):
-            help_query = st.text_input("Enter your help query:", key="help_query")
-            if st.button("Send", key="send_help"):
-                if help_query:
-                    help_response = ask_help_agent(help_query)
-                    st.session_state.help_conversation.append({"query": help_query, "response": help_response})
-                else:
-                    st.error("Please enter a query!")
-            if st.session_state.help_conversation:
-                for msg in st.session_state.help_conversation:
-                    st.markdown(f"**You:** {msg['query']}")
-                    st.markdown(f"**Help Assistant:** {msg['response']}")
-
-    # Guess confirmation screen using text input response
-    elif st.session_state.game_state == "confirm_guess":
-        st.markdown(f'<div class="question-box">🤖 My Final Guess:<br><br>'
-                    f'<strong>Is it {st.session_state.final_guess}?</strong></div>',
-                    unsafe_allow_html=True)
-        
-        with st.form("confirm_form"):
-            confirm_input = st.text_input("Type your answer (yes/no/both):", key="confirm_input").strip().lower()
-            if st.form_submit_button("Submit"):
-                if confirm_input not in ["yes", "no", "both"]:
-                    st.error("Please answer with 'yes', 'no', or 'both'!")
-                else:
-                    if confirm_input == "yes":
-                        st.session_state.game_state = "result"
-                        st.rerun()
-                        st.stop()  # Immediately halt further execution
-                    else:
-                        # Add negative response to history and continue gameplay
-                        st.session_state.conversation_history.append(
-                            {"role": "user", "content": "no"}
-                        )
-                        st.session_state.game_state = "gameplay"
-                        next_response = ask_llama(
-                            st.session_state.conversation_history,
-                            st.session_state.category
-                        )
-                        st.session_state.questions.append(next_response)
-                        st.session_state.conversation_history.append(
-                            {"role": "assistant", "content": next_response}
-                        )
-                        st.session_state.current_q += 1
-                        st.rerun()
-
-    # Result screen
-    elif st.session_state.game_state == "result":
-        if not st.session_state.final_guess:
-            # Generate final guess if not already made
-            qa_history = "\n".join(
-                [f"Q{i+1}: {q}\nA: {a}" 
-                 for i, (q, a) in enumerate(zip(st.session_state.questions, st.session_state.answers))]
-            )
-            
-            final_guess = ask_llama(
-                [{"role": "user", "content": qa_history}],
-                st.session_state.category,
-                is_final_guess=True
-            )
-            st.session_state.final_guess = final_guess.split("Final Guess:")[-1].strip()
-
-        show_confetti()
-        st.markdown(f'<div class="final-reveal">🎉 It\'s...</div>', unsafe_allow_html=True)
-        time.sleep(1)
-        st.markdown(f'<div class="final-reveal" style="font-size:3.5rem;color:#6C63FF;">{st.session_state.final_guess}</div>',
-                    unsafe_allow_html=True)
-        st.markdown(f"<p style='text-align:center'>Guessed in {len(st.session_state.questions)} questions</p>", 
-                    unsafe_allow_html=True)
-        
-        if st.button("Play Again", key="play_again"):
-            st.session_state.clear()
-            st.rerun()
+from flask import Flask, request, render_template
+from transformers import pipeline, AutoTokenizer
+import torch
+
+app = Flask(__name__)
+
+# Load a lightweight model (e.g., Zephyr-7B, Mistral-7B)
+model_name = "mistralai/Mistral-7B-Instruct-v0.2"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+chatbot = pipeline(
+    "text-generation",
+    model=model_name,
+    tokenizer=tokenizer,
+    torch_dtype=torch.float16,
+    device_map="auto"  # Uses GPU if available
+)
+
+@app.route("/", methods=["GET", "POST"])
+def home():
+    if request.method == "POST":
+        user_input = request.form["user_input"]
+        response = generate_response(user_input)
+        return render_template("index.html", user_input=user_input, bot_response=response)
+    return render_template("index.html")
+
+def generate_response(prompt):
+    # Format prompt for instruction-following models
+    messages = [{"role": "user", "content": prompt}]
+    prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+    
+    # Generate response
+    outputs = chatbot(
+        prompt,
+        max_new_tokens=256,
+        do_sample=True,
+        temperature=0.7,
+        top_k=50,
+        top_p=0.95
+    )
+    return outputs[0]["generated_text"][len(prompt):]  # Extract only the bot's reply
 
 if __name__ == "__main__":
-    main()
+    app.run(host="0.0.0.0", port=5000, debug=True)