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import streamlit as st
import time
import requests
from streamlit.components.v1 import html
# Cache the help agent
@st.cache_resource
def get_help_agent():
from transformers import pipeline
return pipeline("conversational", model="facebook/blenderbot-400M-distill")
# Custom CSS
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; color: #6C63FF !important; text-align: center; }
.subtitle { font-size: 1.2rem !important; text-align: center; color: #666 !important; }
.question-box { background: #F8F9FA; border-radius: 15px; padding: 2rem; margin: 1.5rem 0; box-shadow: 0 4px 6px rgba(0,0,0,0.1); }
.answer-btn { border-radius: 12px !important; padding: 0.5rem 1.5rem !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; }
</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>
""")
# Improved question generation
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 STRICT rules:
1. FIRST determine category specifics:
- Person: Start with real/fictional, alive/dead, gender, profession
- Place: Start with continent, urban/rural, famous landmarks
- Object: Start with purpose, size, material, location used
2. Ask SPECIFIC yes/no questions that eliminate possibilities
3. Only guess when 95% confident using "Final Guess: [answer]"
4. After guessing, immediately stop and verify
5. Never repeat questions
6. For objects: ask about usage, parts, location, materials
7. For people: clarify fictional status early
8. For places: ask about geography early"""
messages = [
{"role": "system", "content": system_prompt},
*conversation_history,
{"role": "user", "content": "Ask your next question:" if not is_final_guess else "Make your final guess:"}
]
data = {
"model": "llama-3.3-70b-versatile",
"messages": messages,
"temperature": 0.3 if is_final_guess else 0.7,
"max_tokens": 100,
"top_p": 0.9,
"frequency_penalty": 0.5
}
try:
response = requests.post(api_url, headers=headers, json=data)
return response.json()["choices"][0]["message"]["content"]
except Exception as e:
st.error(f"API Error: {str(e)}")
return "Could not generate question"
# Help assistant
def ask_help_agent(query):
from transformers import Conversation
return get_help_agent()(Conversation(query)).generated_responses[-1]
# Main app
def main():
inject_custom_css()
st.markdown('<div class="title">KASOTI</div><div class="subtitle">The Smart Guessing Game</div>', unsafe_allow_html=True)
if 'game_state' not in st.session_state:
st.session_state.update({
'game_state': "start",
'questions': [],
'current_q': 0,
'answers': [],
'conversation_history': [],
'category': None,
'final_guess': None,
'help_conversation': []
})
# Start screen
if st.session_state.game_state == "start":
st.markdown("""
<div class="question-box">
<h3>Welcome to KASOTI ๐ฏ</h3>
<p>Think of something and I'll guess it in 20 questions or less!</p>
<p>Choose category:</p>
<ul>
<li><strong>Person</strong> - real or fictional</li>
<li><strong>Place</strong> - any geographical location</li>
<li><strong>Object</strong> - any physical item</li>
</ul>
</div>
""", unsafe_allow_html=True)
with st.form("start_form"):
category = st.selectbox("Select category:", ["person", "place", "object"])
if st.form_submit_button("Start Game"):
st.session_state.category = category
first_question = ask_llama([], category)
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[-1]
# Check for final 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><strong>{current_question}</strong></div>', unsafe_allow_html=True)
with st.form("answer_form"):
answer = st.radio("Your answer:", ["Yes", "No", "Both"], horizontal=True)
if st.form_submit_button("Submit"):
detailed_answer = {
"Yes": "Yes, that's correct.",
"No": "No, that's not correct.",
"Both": "It can be both depending on context."
}[answer]
st.session_state.answers.append(detailed_answer)
st.session_state.conversation_history.append({"role": "user", "content": detailed_answer})
# Generate next question
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
# Max 20 questions
if st.session_state.current_q >= 19:
st.session_state.game_state = "result"
st.rerun()
# Help section
with st.expander("๐ก Need Help?"):
help_query = st.text_input("Ask the AI Assistant:")
if st.button("Send"):
if help_query:
help_response = ask_help_agent(help_query)
st.session_state.help_conversation.append(f"You: {help_query}\nAssistant: {help_response}")
for msg in st.session_state.help_conversation[-3:]:
st.markdown(f"`{msg}`")
# Guess confirmation screen
elif st.session_state.game_state == "confirm_guess":
st.markdown(f'<div class="question-box">๐ฏ My Final Guess:<br><br><strong>Is it {st.session_state.final_guess}?</strong></div>', unsafe_allow_html=True)
col1, col2 = st.columns(2)
with col1:
if st.button("Yes! Correct!", key="correct", use_container_width=True):
st.session_state.game_state = "result"
st.rerun()
with col2:
if st.button("No, Keep Trying", key="wrong", use_container_width=True):
st.session_state.conversation_history.append({"role": "user", "content": "No, that's incorrect."})
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.session_state.game_state = "gameplay"
st.rerun()
# Result screen
elif st.session_state.game_state == "result":
if not st.session_state.final_guess:
# Fixed list comprehension with proper bracket closure
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">๐ It\'s...</div>', unsafe_allow_html=True)
time.sleep(1)
st.markdown(f'<div class="final-reveal" style="font-size:3.5rem;">{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()
if __name__ == "__main__":
main() |