Update app.py

app.py

@@ -4,102 +4,27 @@ import requests
 from streamlit.components.v1 import html
 import os
 
-# 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 (used elsewhere)
     return pipeline("conversational", model="facebook/blenderbot-400M-distill")
 
-# Custom CSS for professional look (fixed text color) with speech recognition
 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;
-        }
-        
-        .mic-btn {
-            margin-top: 29px;
-            border: none;
-            background: none;
-            cursor: pointer;
-            font-size: 1.5em;
-            padding: 0;
-        }
+        * { 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; }
+        .mic-btn { margin-top: 29px; border: none; background: none; cursor: pointer; font-size: 1.5em; padding: 0; }
     </style>
     <script>
     function startSpeechRecognition(inputId) {
@@ -107,28 +32,23 @@ def inject_custom_css():
         recognition.lang = 'en-US';
         recognition.interimResults = false;
         recognition.maxAlternatives = 1;
-
         recognition.onresult = function(event) {
             const transcript = event.results[0][0].transcript.toLowerCase();
             const inputElement = document.getElementById(inputId);
             if (inputElement) {
                 inputElement.value = transcript;
-                // Trigger Streamlit's input change detection
                 const event = new Event('input', { bubbles: true });
                 inputElement.dispatchEvent(event);
             }
         };
-
         recognition.onerror = function(event) {
             console.error('Speech recognition error', event.error);
         };
-
         recognition.start();
     }
     </script>
     """, unsafe_allow_html=True)
 
-# Confetti animation
 def show_confetti():
     html("""
     <canvas id="confetti-canvas" class="confetti"></canvas>
@@ -136,16 +56,11 @@ def show_confetti():
     <script>
     const canvas = document.getElementById('confetti-canvas');
     const confetti = confetti.create(canvas, { resize: true });
-    confetti({
-        particleCount: 150,
-        spread: 70,
-        origin: { y: 0.6 }
-    });
+    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 = {
@@ -189,45 +104,28 @@ def ask_llama(conversation_history, category, is_final_guess=False):
         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
 def ask_help_agent(query):
     try:
         from huggingface_hub import InferenceClient
-        # Initialize the client with the provided model
         client = InferenceClient("HuggingFaceH4/zephyr-7b-beta", token=os.environ.get("HF_HUB_TOKEN"))
         system_message = "You are a friendly Chatbot."
-        
-        # Build history from session state (if any)
         history = []
         if "help_conversation" in st.session_state:
             for msg in st.session_state.help_conversation:
-                # Each history entry is a tuple: (user query, assistant response)
                 history.append((msg.get("query", ""), msg.get("response", "")))
-        
         messages = [{"role": "system", "content": system_message}]
         for user_msg, bot_msg in history:
-            if user_msg:
-                messages.append({"role": "user", "content": user_msg})
-            if bot_msg:
-                messages.append({"role": "assistant", "content": bot_msg})
+            if user_msg: messages.append({"role": "user", "content": user_msg})
+            if bot_msg: messages.append({"role": "assistant", "content": bot_msg})
         messages.append({"role": "user", "content": query})
-        
         response_text = ""
-        # Using streaming to collect the entire response from the model
-        for message in client.chat_completion(
-            messages,
-            max_tokens=150,
-            stream=True,
-            temperature=0.7,
-            top_p=0.95,
-        ):
+        for message in client.chat_completion(messages, max_tokens=150, stream=True, temperature=0.7, top_p=0.95):
             token = message.choices[0].delta.content
             response_text += token
         return response_text
     except Exception as e:
         return f"Error in help agent: {str(e)}"
 
-# Main game logic
 def main():
     inject_custom_css()
 
@@ -242,9 +140,8 @@ def main():
         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
+        st.session_state.help_conversation = []
 
-    # Start screen
     if st.session_state.game_state == "start":
         st.markdown("""
         <div class="question-box">
@@ -261,25 +158,13 @@ def main():
         """, unsafe_allow_html=True)
 
         with st.form("start_form"):
-            # Create columns for input and microphone button
             col1, col2 = st.columns([4, 1])
             with col1:
-                category_input = st.text_input(
-                    "Enter category (person/place/object):",
-                    key="category_input"
-                ).strip().lower()
-            
+                category_input = st.text_input("Enter category (person/place/object):", key="category_input").strip().lower()
             with col2:
-                st.markdown(
-                    """
-                    <button type="button" onclick="startSpeechRecognition('text_input-category_input')" 
-                            class="mic-btn">
-                        🎤
-                    </button>
-                    """,
-                    unsafe_allow_html=True
-                )
-            
+                st.markdown("""
+                <button type="button" onclick="startSpeechRecognition('text_input-category_input')" class="mic-btn">🎤</button>
+                """, unsafe_allow_html=True)
             if st.form_submit_button("Start Game"):
                 if not category_input:
                     st.error("Please enter a category!")
@@ -287,176 +172,10 @@ def main():
                     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)
+                    first_question = ask_llama([], 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.experimental_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.experimental_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_key = f"answer_{st.session_state.current_q}"
-            
-            # Create columns for input and microphone button
-            col1, col2 = st.columns([4, 1])
-            with col1:
-                answer_input = st.text_input(
-                    "Your answer (yes/no/both) - speak or type:",
-                    key=answer_key
-                ).strip().lower()
-            
-            with col2:
-                st.markdown(
-                    f"""
-                    <button type="button" onclick="startSpeechRecognition('text_input-{answer_key}')" 
-                            class="mic-btn">
-                        🎤
-                    </button>
-                    """,
-                    unsafe_allow_html=True
-                )
-            
-            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.experimental_rerun()
-
-        # Side Help Option: independent chat with an AI help assistant using 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"):
-            # Create columns for input and microphone button
-            col1, col2 = st.columns([4, 1])
-            with col1:
-                confirm_input = st.text_input(
-                    "Type or speak your answer (yes/no/both):",
-                    key="confirm_input"
-                ).strip().lower()
-            
-            with col2:
-                st.markdown(
-                    """
-                    <button type="button" onclick="startSpeechRecognition('text_input-confirm_input')" 
-                            class="mic-btn">
-                        🎤
-                    </button>
-                    """,
-                    unsafe_allow_html=True
-                )
-            
-            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.experimental_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.experimental_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.experimental_rerun()
+                    st.session_state.conversation_history = [{"role": "assistant", "content": first_question}]
+                    st.session_state.game_state = "playing"
 
 if __name__ == "__main__":
-    main()
+    main()