Update app.py

app.py

@@ -10,6 +10,7 @@ from audio_recorder_streamlit import audio_recorder
 import torch
 from io import BytesIO
 import hashlib
+from transformers import pipeline
 
 # Load Whisper model (cached)
 @st.cache_resource
@@ -59,6 +60,271 @@ def voice_input(key, prompt_text, default_text=""):
     
     return text_input
 
+# Enhanced Custom CSS with modern design
+def inject_custom_css():
+    st.markdown("""
+    <style>
+        @import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&display=swap');
+        @import url('https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.0.0/css/all.min.css');
+
+        * {
+            font-family: 'Inter', sans-serif;
+        }
+
+        body {
+            background: linear-gradient(135deg, #f8f9fa 0%, #e9ecef 100%);
+        }
+
+        .title {
+            font-size: 2.8rem !important;
+            font-weight: 800 !important;
+            background: linear-gradient(45deg, #6C63FF, #3B82F6);
+            -webkit-background-clip: text;
+            -webkit-text-fill-color: transparent;
+            text-align: center;
+            margin: 1rem 0;
+            letter-spacing: -1px;
+        }
+
+        .subtitle {
+            font-size: 1.1rem !important;
+            text-align: center;
+            color: #64748B !important;
+            margin-bottom: 2.5rem;
+            animation: fadeInSlide 1s ease;
+        }
+
+        .question-box {
+            background: white;
+            border-radius: 20px;
+            padding: 2rem;
+            margin: 1.5rem 0;
+            box-shadow: 0 10px 25px rgba(0,0,0,0.08);
+            border: 1px solid #e2e8f0;
+            position: relative;
+            transition: transform 0.2s ease;
+            color: black;
+        }
+
+        .question-box:hover {
+            transform: translateY(-3px);
+        }
+
+        .question-box::before {
+            content: "🕹️";
+            position: absolute;
+            left: -15px;
+            top: -15px;
+            background: white;
+            border-radius: 50%;
+            padding: 8px;
+            box-shadow: 0 4px 6px rgba(0,0,0,0.1);
+            font-size: 1.2rem;
+        }
+
+        .input-box {
+            background: white;
+            border-radius: 12px;
+            padding: 1.5rem;
+            margin: 1rem 0;
+            box-shadow: 0 4px 6px rgba(0,0,0,0.05);
+        }
+
+        .stTextInput input {
+            border: 2px solid #e2e8f0 !important;
+            border-radius: 10px !important;
+            padding: 12px 16px !important;
+            transition: all 0.3s ease !important;
+        }
+
+        .stTextInput input:focus {
+            border-color: #6C63FF !important;
+            box-shadow: 0 0 0 3px rgba(108, 99, 255, 0.2) !important;
+        }
+
+        button {
+            background: linear-gradient(45deg, #6C63FF, #3B82F6) !important;
+            color: white !important;
+            border: none !important;
+            border-radius: 10px !important;
+            padding: 12px 24px !important;
+            font-weight: 600 !important;
+            transition: all 0.3s ease !important;
+        }
+
+        button:hover {
+            transform: translateY(-2px);
+            box-shadow: 0 5px 15px rgba(108, 99, 255, 0.3) !important;
+        }
+
+        .final-reveal {
+            animation: fadeInUp 1s ease;
+            font-size: 2.8rem;
+            background: linear-gradient(45deg, #6C63FF, #3B82F6);
+            -webkit-background-clip: text;
+            -webkit-text-fill-color: transparent;
+            text-align: center;
+            margin: 2rem 0;
+            font-weight: 800;
+        }
+
+        .help-chat {
+            background: rgba(255,255,255,0.9);
+            backdrop-filter: blur(10px);
+            border-radius: 15px;
+            padding: 1rem;
+            margin: 1rem 0;
+            box-shadow: 0 8px 30px rgba(0,0,0,0.12);
+        }
+
+        @keyframes fadeInSlide {
+            0% { opacity: 0; transform: translateY(20px); }
+            100% { opacity: 1; transform: translateY(0); }
+        }
+
+        @keyframes fadeInUp {
+            0% { opacity: 0; transform: translateY(30px); }
+            100% { opacity: 1; transform: translateY(0); }
+        }
+
+        .progress-bar {
+            height: 6px;
+            background: #e2e8f0;
+            border-radius: 3px;
+            margin: 1.5rem 0;
+            overflow: hidden;
+        }
+
+        .progress-fill {
+            height: 100%;
+            background: linear-gradient(90deg, #6C63FF, #3B82F6);
+            transition: width 0.5s ease;
+        }
+
+        .question-count {
+            color: #6C63FF;
+            font-weight: 600;
+            font-size: 0.9rem;
+            margin-bottom: 0.5rem;
+        }
+    </style>
+    """, unsafe_allow_html=True)
+
+# Confetti animation (enhanced)
+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 count = 200;
+    const defaults = {
+        origin: { y: 0.7 },
+        zIndex: 1050
+    };
+
+    function fire(particleRatio, opts) {
+        confetti(Object.assign({}, defaults, opts, {
+            particleCount: Math.floor(count * particleRatio)
+        }));
+    }
+
+    fire(0.25, { spread: 26, startVelocity: 55 });
+    fire(0.2, { spread: 60 });
+    fire(0.35, { spread: 100, decay: 0.91, scalar: 0.8 });
+    fire(0.1, { spread: 120, startVelocity: 25, decay: 0.92, scalar: 1.2 });
+    fire(0.1, { spread: 120, startVelocity: 45 });
+    </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 the Hugging Face InferenceClient
+MISTRAL_API_KEY = "wm5eLl09b9I9cOxR3E9n5rrRr1CRQQjn"
+def ask_help_agent(query):
+    try:
+        # Prepare Mistral API request
+        url = "https://api.mistral.ai/v1/chat/completions"
+        headers = {
+            "Authorization": f"Bearer {MISTRAL_API_KEY}",
+            "Content-Type": "application/json"
+        }
+
+        system_message = "You are a friendly Chatbot."
+        
+        # Build message history
+        messages = [{"role": "system", "content": system_message}]
+        if "help_conversation" in st.session_state:
+            for msg in st.session_state.help_conversation:
+                if msg.get("query"):
+                    messages.append({"role": "user", "content": msg["query"]})
+                if msg.get("response"):
+                    messages.append({"role": "assistant", "content": msg["response"]})
+        
+        # Add current user query
+        messages.append({"role": "user", "content": query})
+
+        # API payload
+        payload = {
+            "model": "mistral-tiny",
+            "messages": messages,
+            "temperature": 0.7,
+            "top_p": 0.95
+        }
+
+        # Send POST request
+        response = requests.post(url, headers=headers, json=payload)
+
+        if response.status_code == 200:
+            result = response.json()
+            return result["choices"][0]["message"]["content"]
+        else:
+            return f"API Error {response.status_code}: {response.text}"
+
+    except Exception as e:
+        return f"Error in help agent: {str(e)}"
+
 # Import transformers and cache the help agent for performance
 @st.cache_resource
 def get_help_agent():
@@ -66,12 +332,7 @@ def get_help_agent():
     # Using BlenderBot 400M Distill as the public conversational model (used elsewhere)
     return pipeline("conversational", model="facebook/blenderbot-400M-distill")
 
-# [Rest of your existing functions remain exactly the same...]
-# inject_custom_css()
-# show_confetti()
-# ask_llama()
-# ask_help_agent()
-
+# Main game logic with enhanced UI
 def main():
     inject_custom_css()
 
@@ -86,9 +347,9 @@ def main():
         st.session_state.conversation_history = []
         st.session_state.category = None
         st.session_state.final_guess = None
-        st.session_state.help_conversation = []
+        st.session_state.help_conversation = []  # separate history for help agent
 
-    # Start screen with voice input
+    # Start screen with enhanced layout
     if st.session_state.game_state == "start":
         with st.container():
             st.markdown("""