Update app.py
Browse files
app.py
CHANGED
@@ -3,52 +3,112 @@ import time
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import requests
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from streamlit.components.v1 import html
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import os
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@st.cache_resource
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def get_help_agent():
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from transformers import pipeline
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return pipeline("conversational", model="facebook/blenderbot-400M-distill")
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def inject_custom_css():
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st.markdown("""
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<style>
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@import url('https://fonts.googleapis.com/css2?family=Poppins:wght@400;600;700&display=swap');
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</style>
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<script>
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function startSpeechRecognition(inputId) {
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const recognition = new (window.SpeechRecognition || window.webkitSpeechRecognition)();
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recognition.lang = 'en-US';
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recognition.interimResults = false;
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recognition.maxAlternatives = 1;
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recognition.onresult = function(event) {
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const transcript = event.results[0][0].transcript.toLowerCase();
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const inputElement = document.getElementById(inputId);
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if (inputElement) {
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inputElement.value = transcript;
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const event = new Event('input', { bubbles: true });
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inputElement.dispatchEvent(event);
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}
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};
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recognition.onerror = function(event) {
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console.error('Speech recognition error', event.error);
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};
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recognition.start();
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}
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</script>
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""", unsafe_allow_html=True)
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def show_confetti():
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html("""
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<canvas id="confetti-canvas" class="confetti"></canvas>
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<script>
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const canvas = document.getElementById('confetti-canvas');
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const confetti = confetti.create(canvas, { resize: true });
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confetti({
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setTimeout(() => { canvas.remove(); }, 5000);
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</script>
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""")
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def ask_llama(conversation_history, category, is_final_guess=False):
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api_url = "https://api.groq.com/openai/v1/chat/completions"
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headers = {
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st.error(f"Error calling Llama API: {str(e)}")
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return "Could not generate question"
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def ask_help_agent(query):
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try:
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from huggingface_hub import InferenceClient
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta", token=os.environ.get("HF_HUB_TOKEN"))
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system_message = "You are a friendly Chatbot."
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history = []
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if "help_conversation" in st.session_state:
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for msg in st.session_state.help_conversation:
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history.append((msg.get("query", ""), msg.get("response", "")))
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messages = [{"role": "system", "content": system_message}]
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for user_msg, bot_msg in history:
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if user_msg:
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-
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messages.append({"role": "user", "content": query})
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response_text = ""
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-
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token = message.choices[0].delta.content
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response_text += token
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return response_text
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except Exception as e:
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return f"Error in help agent: {str(e)}"
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def main():
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inject_custom_css()
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@@ -140,8 +266,9 @@ def main():
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st.session_state.conversation_history = []
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st.session_state.category = None
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st.session_state.final_guess = None
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st.session_state.help_conversation = []
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if st.session_state.game_state == "start":
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st.markdown("""
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<div class="question-box">
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<li><strong>Place</strong> - city, country, landmark, geographical location</li>
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<li><strong>Object</strong> - everyday item, tool, vehicle, etc.</li>
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</ul>
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<p>Type
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</div>
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""", unsafe_allow_html=True)
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with col1:
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category_input = st.text_input("Enter category (person/place/object):", key="category_input").strip().lower()
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with col2:
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st.
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""
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if st.form_submit_button("Start Game"):
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if not category_input:
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st.error("Please enter a category!")
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elif category_input not in ["person", "place", "object"]:
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st.error("Please enter either 'person', 'place', or 'object'!")
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else:
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st.session_state.category = category_input
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first_question = ask_llama([
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st.session_state.questions = [first_question]
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st.session_state.conversation_history = [
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if __name__ == "__main__":
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main()
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import requests
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from streamlit.components.v1 import html
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import os
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import speech_recognition as sr
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from audio_recorder_streamlit import audio_recorder
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# Import transformers and cache the help agent for performance
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@st.cache_resource
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def get_help_agent():
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from transformers import pipeline
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# Using BlenderBot 400M Distill as the public conversational model (used elsewhere)
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return pipeline("conversational", model="facebook/blenderbot-400M-distill")
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# Custom CSS for professional look (fixed text color)
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def inject_custom_css():
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st.markdown("""
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<style>
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@import url('https://fonts.googleapis.com/css2?family=Poppins:wght@400;600;700&display=swap');
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* {
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font-family: 'Poppins', sans-serif;
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}
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.title {
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font-size: 3rem !important;
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font-weight: 700 !important;
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color: #6C63FF !important;
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text-align: center;
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margin-bottom: 0.5rem;
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}
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.subtitle {
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font-size: 1.2rem !important;
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text-align: center;
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color: #666 !important;
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margin-bottom: 2rem;
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}
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.question-box {
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background: #F8F9FA;
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border-radius: 15px;
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padding: 2rem;
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margin: 1.5rem 0;
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box-shadow: 0 4px 6px rgba(0,0,0,0.1);
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color: black !important;
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}
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.answer-btn {
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border-radius: 12px !important;
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padding: 0.5rem 1.5rem !important;
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font-weight: 600 !important;
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margin: 0.5rem !important;
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}
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.yes-btn {
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background: #6C63FF !important;
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color: white !important;
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}
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.no-btn {
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background: #FF6B6B !important;
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color: white !important;
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}
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.final-reveal {
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animation: fadeIn 2s;
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font-size: 2.5rem;
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color: #6C63FF;
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text-align: center;
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margin: 2rem 0;
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}
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@keyframes fadeIn {
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from { opacity: 0; }
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to { opacity: 1; }
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}
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.confetti {
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position: fixed;
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top: 0;
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left: 0;
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width: 100%;
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height: 100%;
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pointer-events: none;
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z-index: 1000;
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}
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.confidence-meter {
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height: 10px;
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background: linear-gradient(90deg, #FF6B6B 0%, #6C63FF 100%);
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border-radius: 5px;
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margin: 10px 0;
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}
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.mic-btn {
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background: #6C63FF !important;
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color: white !important;
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border-radius: 50% !important;
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width: 40px !important;
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height: 40px !important;
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padding: 0 !important;
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display: flex !important;
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align-items: center !important;
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justify-content: center !important;
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}
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</style>
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""", unsafe_allow_html=True)
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# Confetti animation
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def show_confetti():
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html("""
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<canvas id="confetti-canvas" class="confetti"></canvas>
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<script>
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const canvas = document.getElementById('confetti-canvas');
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const confetti = confetti.create(canvas, { resize: true });
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confetti({
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particleCount: 150,
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spread: 70,
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origin: { y: 0.6 }
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});
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setTimeout(() => { canvas.remove(); }, 5000);
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</script>
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""")
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# Enhanced AI question generation for guessing game using Llama model
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def ask_llama(conversation_history, category, is_final_guess=False):
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api_url = "https://api.groq.com/openai/v1/chat/completions"
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headers = {
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st.error(f"Error calling Llama API: {str(e)}")
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return "Could not generate question"
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# New function for the help AI assistant using the Hugging Face InferenceClient
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def ask_help_agent(query):
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try:
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from huggingface_hub import InferenceClient
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# Initialize the client with the provided model
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta", token=os.environ.get("HF_HUB_TOKEN"))
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system_message = "You are a friendly Chatbot."
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# Build history from session state (if any)
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history = []
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if "help_conversation" in st.session_state:
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for msg in st.session_state.help_conversation:
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# Each history entry is a tuple: (user query, assistant response)
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history.append((msg.get("query", ""), msg.get("response", "")))
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messages = [{"role": "system", "content": system_message}]
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for user_msg, bot_msg in history:
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if user_msg:
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messages.append({"role": "user", "content": user_msg})
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if bot_msg:
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messages.append({"role": "assistant", "content": bot_msg})
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messages.append({"role": "user", "content": query})
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response_text = ""
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# Using streaming to collect the entire response from the model
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for message in client.chat_completion(
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messages,
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max_tokens=150,
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stream=True,
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temperature=0.7,
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top_p=0.95,
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):
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token = message.choices[0].delta.content
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response_text += token
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return response_text
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except Exception as e:
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return f"Error in help agent: {str(e)}"
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# Audio processing functions
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def transcribe_audio(audio_bytes):
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"""Convert audio bytes to text using SpeechRecognition"""
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recognizer = sr.Recognizer()
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try:
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# Create a temporary WAV file
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with open("temp_audio.wav", "wb") as f:
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f.write(audio_bytes)
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with sr.AudioFile("temp_audio.wav") as source:
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audio_data = recognizer.record(source)
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text = recognizer.recognize_google(audio_data)
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os.remove("temp_audio.wav")
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return text.lower()
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except sr.UnknownValueError:
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st.error("Could not understand audio")
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except sr.RequestError as e:
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st.error(f"Speech recognition error: {e}")
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except Exception as e:
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st.error(f"Error processing audio: {e}")
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finally:
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if os.path.exists("temp_audio.wav"):
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os.remove("temp_audio.wav")
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return ""
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def record_audio(key):
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"""Record audio and return transcribed text"""
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audio_bytes = audio_recorder(
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pause_threshold=2.0,
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text="",
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recording_color="#6C63FF",
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neutral_color="#6C63FF",
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icon_name="microphone",
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icon_size="2x",
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key=key
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)
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if audio_bytes:
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248 |
+
with st.spinner("Processing audio..."):
|
249 |
+
text = transcribe_audio(audio_bytes)
|
250 |
+
if text:
|
251 |
+
return text
|
252 |
+
return None
|
253 |
+
|
254 |
+
# Main game logic
|
255 |
def main():
|
256 |
inject_custom_css()
|
257 |
|
|
|
266 |
st.session_state.conversation_history = []
|
267 |
st.session_state.category = None
|
268 |
st.session_state.final_guess = None
|
269 |
+
st.session_state.help_conversation = [] # separate history for help agent
|
270 |
|
271 |
+
# Start screen
|
272 |
if st.session_state.game_state == "start":
|
273 |
st.markdown("""
|
274 |
<div class="question-box">
|
|
|
280 |
<li><strong>Place</strong> - city, country, landmark, geographical location</li>
|
281 |
<li><strong>Object</strong> - everyday item, tool, vehicle, etc.</li>
|
282 |
</ul>
|
283 |
+
<p>Type your category below to begin:</p>
|
284 |
</div>
|
285 |
""", unsafe_allow_html=True)
|
286 |
|
|
|
289 |
with col1:
|
290 |
category_input = st.text_input("Enter category (person/place/object):", key="category_input").strip().lower()
|
291 |
with col2:
|
292 |
+
st.write("")
|
293 |
+
st.write("")
|
294 |
+
if st.form_submit_button("🎤", key="start_mic"):
|
295 |
+
audio_text = record_audio("start_mic")
|
296 |
+
if audio_text:
|
297 |
+
st.session_state.category_input = audio_text
|
298 |
+
st.experimental_rerun()
|
299 |
+
|
300 |
if st.form_submit_button("Start Game"):
|
301 |
+
category_input = st.session_state.get("category_input", category_input)
|
302 |
if not category_input:
|
303 |
st.error("Please enter a category!")
|
304 |
elif category_input not in ["person", "place", "object"]:
|
305 |
st.error("Please enter either 'person', 'place', or 'object'!")
|
306 |
else:
|
307 |
st.session_state.category = category_input
|
308 |
+
first_question = ask_llama([
|
309 |
+
{"role": "user", "content": "Ask your first strategic yes/no question."}
|
310 |
+
], category_input)
|
311 |
st.session_state.questions = [first_question]
|
312 |
+
st.session_state.conversation_history = [
|
313 |
+
{"role": "assistant", "content": first_question}
|
314 |
+
]
|
315 |
+
st.session_state.game_state = "gameplay"
|
316 |
+
st.experimental_rerun()
|
317 |
+
|
318 |
+
# Gameplay screen
|
319 |
+
elif st.session_state.game_state == "gameplay":
|
320 |
+
current_question = st.session_state.questions[st.session_state.current_q]
|
321 |
+
|
322 |
+
# Check if AI made a guess
|
323 |
+
if "Final Guess:" in current_question:
|
324 |
+
st.session_state.final_guess = current_question.split("Final Guess:")[1].strip()
|
325 |
+
st.session_state.game_state = "confirm_guess"
|
326 |
+
st.experimental_rerun()
|
327 |
+
|
328 |
+
st.markdown(f'<div class="question-box">Question {st.session_state.current_q + 1}/20:<br><br>'
|
329 |
+
f'<strong>{current_question}</strong></div>',
|
330 |
+
unsafe_allow_html=True)
|
331 |
+
|
332 |
+
with st.form("answer_form"):
|
333 |
+
col1, col2 = st.columns([4, 1])
|
334 |
+
with col1:
|
335 |
+
answer_input = st.text_input("Your answer (yes/no/both):",
|
336 |
+
key=f"answer_{st.session_state.current_q}").strip().lower()
|
337 |
+
with col2:
|
338 |
+
st.write("")
|
339 |
+
st.write("")
|
340 |
+
if st.form_submit_button("🎤", key=f"mic_{st.session_state.current_q}"):
|
341 |
+
audio_text = record_audio(f"mic_{st.session_state.current_q}")
|
342 |
+
if audio_text:
|
343 |
+
st.session_state[f"answer_{st.session_state.current_q}"] = audio_text
|
344 |
+
st.experimental_rerun()
|
345 |
+
|
346 |
+
if st.form_submit_button("Submit"):
|
347 |
+
answer_input = st.session_state.get(f"answer_{st.session_state.current_q}", answer_input)
|
348 |
+
if answer_input not in ["yes", "no", "both"]:
|
349 |
+
st.error("Please answer with 'yes', 'no', or 'both'!")
|
350 |
+
else:
|
351 |
+
st.session_state.answers.append(answer_input)
|
352 |
+
st.session_state.conversation_history.append(
|
353 |
+
{"role": "user", "content": answer_input}
|
354 |
+
)
|
355 |
+
|
356 |
+
# Generate next response
|
357 |
+
next_response = ask_llama(
|
358 |
+
st.session_state.conversation_history,
|
359 |
+
st.session_state.category
|
360 |
+
)
|
361 |
+
|
362 |
+
# Check if AI made a guess
|
363 |
+
if "Final Guess:" in next_response:
|
364 |
+
st.session_state.final_guess = next_response.split("Final Guess:")[1].strip()
|
365 |
+
st.session_state.game_state = "confirm_guess"
|
366 |
+
else:
|
367 |
+
st.session_state.questions.append(next_response)
|
368 |
+
st.session_state.conversation_history.append(
|
369 |
+
{"role": "assistant", "content": next_response}
|
370 |
+
)
|
371 |
+
st.session_state.current_q += 1
|
372 |
+
|
373 |
+
# Stop after 20 questions max
|
374 |
+
if st.session_state.current_q >= 20:
|
375 |
+
st.session_state.game_state = "result"
|
376 |
+
|
377 |
+
st.experimental_rerun()
|
378 |
+
|
379 |
+
# Side Help Option: independent chat with an AI help assistant using Hugging Face model
|
380 |
+
with st.expander("Need Help? Chat with AI Assistant"):
|
381 |
+
col1, col2 = st.columns([4, 1])
|
382 |
+
with col1:
|
383 |
+
help_query = st.text_input("Enter your help query:", key="help_query")
|
384 |
+
with col2:
|
385 |
+
st.write("")
|
386 |
+
st.write("")
|
387 |
+
if st.button("🎤", key="help_mic"):
|
388 |
+
audio_text = record_audio("help_mic")
|
389 |
+
if audio_text:
|
390 |
+
st.session_state.help_query = audio_text
|
391 |
+
st.experimental_rerun()
|
392 |
+
|
393 |
+
if st.button("Send", key="send_help"):
|
394 |
+
help_query = st.session_state.get("help_query", help_query)
|
395 |
+
if help_query:
|
396 |
+
help_response = ask_help_agent(help_query)
|
397 |
+
st.session_state.help_conversation.append({"query": help_query, "response": help_response})
|
398 |
+
st.session_state.help_query = "" # Clear the input after sending
|
399 |
+
st.experimental_rerun()
|
400 |
+
else:
|
401 |
+
st.error("Please enter a query!")
|
402 |
+
|
403 |
+
if st.session_state.help_conversation:
|
404 |
+
for msg in st.session_state.help_conversation:
|
405 |
+
st.markdown(f"**You:** {msg['query']}")
|
406 |
+
st.markdown(f"**Help Assistant:** {msg['response']}")
|
407 |
+
|
408 |
+
# Guess confirmation screen using text input response
|
409 |
+
elif st.session_state.game_state == "confirm_guess":
|
410 |
+
st.markdown(f'<div class="question-box">🤖 My Final Guess:<br><br>'
|
411 |
+
f'<strong>Is it {st.session_state.final_guess}?</strong></div>',
|
412 |
+
unsafe_allow_html=True)
|
413 |
+
|
414 |
+
with st.form("confirm_form"):
|
415 |
+
col1, col2 = st.columns([4, 1])
|
416 |
+
with col1:
|
417 |
+
confirm_input = st.text_input("Type your answer (yes/no/both):", key="confirm_input").strip().lower()
|
418 |
+
with col2:
|
419 |
+
st.write("")
|
420 |
+
st.write("")
|
421 |
+
if st.form_submit_button("🎤", key="confirm_mic"):
|
422 |
+
audio_text = record_audio("confirm_mic")
|
423 |
+
if audio_text:
|
424 |
+
st.session_state.confirm_input = audio_text
|
425 |
+
st.experimental_rerun()
|
426 |
+
|
427 |
+
if st.form_submit_button("Submit"):
|
428 |
+
confirm_input = st.session_state.get("confirm_input", confirm_input)
|
429 |
+
if confirm_input not in ["yes", "no", "both"]:
|
430 |
+
st.error("Please answer with 'yes', 'no', or 'both'!")
|
431 |
+
else:
|
432 |
+
if confirm_input == "yes":
|
433 |
+
st.session_state.game_state = "result"
|
434 |
+
st.experimental_rerun()
|
435 |
+
else:
|
436 |
+
# Add negative response to history and continue gameplay
|
437 |
+
st.session_state.conversation_history.append(
|
438 |
+
{"role": "user", "content": "no"}
|
439 |
+
)
|
440 |
+
st.session_state.game_state = "gameplay"
|
441 |
+
next_response = ask_llama(
|
442 |
+
st.session_state.conversation_history,
|
443 |
+
st.session_state.category
|
444 |
+
)
|
445 |
+
st.session_state.questions.append(next_response)
|
446 |
+
st.session_state.conversation_history.append(
|
447 |
+
{"role": "assistant", "content": next_response}
|
448 |
+
)
|
449 |
+
st.session_state.current_q += 1
|
450 |
+
st.experimental_rerun()
|
451 |
+
|
452 |
+
# Result screen
|
453 |
+
elif st.session_state.game_state == "result":
|
454 |
+
if not st.session_state.final_guess:
|
455 |
+
# Generate final guess if not already made
|
456 |
+
qa_history = "\n".join(
|
457 |
+
[f"Q{i+1}: {q}\nA: {a}"
|
458 |
+
for i, (q, a) in enumerate(zip(st.session_state.questions, st.session_state.answers))]
|
459 |
+
)
|
460 |
+
|
461 |
+
final_guess = ask_llama(
|
462 |
+
[{"role": "user", "content": qa_history}],
|
463 |
+
st.session_state.category,
|
464 |
+
is_final_guess=True
|
465 |
+
)
|
466 |
+
st.session_state.final_guess = final_guess.split("Final Guess:")[-1].strip()
|
467 |
+
|
468 |
+
show_confetti()
|
469 |
+
st.markdown(f'<div class="final-reveal">🎉 It\'s...</div>', unsafe_allow_html=True)
|
470 |
+
time.sleep(1)
|
471 |
+
st.markdown(f'<div class="final-reveal" style="font-size:3.5rem;color:#6C63FF;">{st.session_state.final_guess}</div>',
|
472 |
+
unsafe_allow_html=True)
|
473 |
+
st.markdown(f"<p style='text-align:center'>Guessed in {len(st.session_state.questions)} questions</p>",
|
474 |
+
unsafe_allow_html=True)
|
475 |
+
|
476 |
+
if st.button("Play Again", key="play_again"):
|
477 |
+
st.session_state.clear()
|
478 |
+
st.experimental_rerun()
|
479 |
|
480 |
if __name__ == "__main__":
|
481 |
+
main()
|