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| # Install necessary libraries | |
| !pip install streamlit groq deep-translator | |
| import streamlit as st | |
| from groq import Groq | |
| from deep_translator import GoogleTranslator | |
| import subprocess | |
| import threading | |
| # Insert your Groq API key here | |
| API_KEY = "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" | |
| # Initialize Groq client | |
| client = Groq(api_key=API_KEY) | |
| st.set_page_config(page_title="Krishna", page_icon="https://res.cloudinary.com/dvlgixtg8/image/upload/v1739472351/Krishna-avatar.png") | |
| # Define a system prompt for fine-tuning responses | |
| system_prompt = """ | |
| Bot Identity | |
| Namaste! I am Neetu, your celestial guide to Hindu astrology and mythology. My purpose is to illuminate the divine wisdom of the cosmos, revealing how planetary movements and ancient scriptures shape our destiny, karma, and dharma. | |
| """ | |
| # Initialize session state for chat history | |
| if "messages" not in st.session_state: | |
| st.session_state.messages = [ | |
| {"role": "system", "content": system_prompt} # Add system prompt at the start | |
| ] | |
| # Translate text function | |
| def translate_text(text, lang='en'): | |
| """Translate text to the desired language.""" | |
| try: | |
| if lang == 'hi': # Translate to Hinglish (Hindi + English) | |
| translated = GoogleTranslator(source='auto', target='hi').translate(text) | |
| else: # Default to English | |
| translated = GoogleTranslator(source='auto', target='en').translate(text) | |
| return translated | |
| except Exception as e: | |
| st.error(f"Error in translation: {e}") | |
| return text | |
| # Display chat messages from session | |
| st.title("Neetu – Unlock the Secrets of Hindu Astrology & Mythology ✨🔱") | |
| # Description | |
| st.write( | |
| "Namaste! I am your celestial guide to **Hindu astrology (Jyotish) and ancient mythology**. " | |
| "Ask me anything about **planetary influences, zodiac signs, karmic lessons, and divine stories from sacred texts**.\n\n" | |
| "Let us explore the cosmic dance of planets and the wisdom of the Vedas, Puranas, and epics – speak to me as a seeker of truth! 🔮✨" | |
| ) | |
| # Language selector | |
| language = st.radio("Choose your language", ('English', 'Hinglish')) | |
| # User input field | |
| user_input = st.chat_input("Type your message...") | |
| if user_input: | |
| # Translate user input to the selected language (English or Hinglish) | |
| translated_input = translate_text(user_input, lang='hi' if language == 'Hinglish' else 'en') | |
| # Append translated user message to session | |
| st.session_state.messages.append({"role": "user", "content": translated_input}) | |
| with st.chat_message("user", avatar="🔮"): | |
| st.write(translated_input) | |
| # Get AI response (in the same language as input) | |
| with st.chat_message("assistant", avatar="https://static.vecteezy.com/system/resources/previews/050/754/028/non_2x/om-ohm-buddhist-and-hindu-religions-symbol-of-god-creation-black-icon-isolated-on-white-background-eps10-graphic-design-element-vector.jpg"): | |
| message_placeholder = st.empty() | |
| response = "" | |
| completion = client.chat.completions.create( | |
| model="llama-3.3-70b-versatile", | |
| messages=st.session_state.messages, # Send full chat history, including system prompt | |
| temperature=1, | |
| max_completion_tokens=1024, | |
| top_p=1, | |
| stream=True, | |
| stop=None, | |
| ) | |
| for chunk in completion: | |
| response_chunk = chunk.choices[0].delta.content or "" | |
| response += response_chunk | |
| message_placeholder.write(response) | |
| # Translate the assistant response back to the selected language | |
| translated_response = translate_text(response, lang='hi' if language == 'Hinglish' else 'en') | |
| # Append assistant response to session | |
| st.session_state.messages.append({"role": "assistant", "content": translated_response}) | |
| with st.chat_message("assistant", avatar="https://static.vecteezy.com/system/resources/previews/050/754/028/non_2x/om-ohm-buddhist-and-hindu-religions-symbol-of-god-creation-black-icon-isolated-on-white-background-eps10-graphic-design-element-vector.jpg"): | |
| st.write(translated_response) | |
| # Start Streamlit app using subprocess | |
| def start_streamlit(): | |
| subprocess.run(["streamlit", "run", "your_streamlit_file.py", "--server.headless=true", "--server.port=8501"]) | |
| # Start Streamlit app in background | |
| streamlit_thread = threading.Thread(target=start_streamlit) | |
| streamlit_thread.start() |