import streamlit as st
import os
from transformers import pipeline
from langdetect import detect
from groq import Groq
import torch
print(torch.__version__)
print("CUDA available:", torch.cuda.is_available())  # Check if GPU is available

# Load Hugging Face token from environment
HF_TOKEN = os.environ.get("homeo_doc")
if not HF_TOKEN:
    st.error("Missing Hugging Face API token. Set 'homeo_doc' in environment variables.")

# Initialize translation pipeline
translator = pipeline("translation", model="facebook/nllb-200-distilled-600M", token=HF_TOKEN)

# Initialize Groq client for homeopathic advice
groq_client = Groq(api_key=os.environ.get("GROQ_API_KEY"))

# Language code mapping for NLLB-200
LANG_CODE_MAP = {
    'en': 'eng_Latn',    # English
    'ur': 'urd_Arab',    # Urdu
    'ar': 'arb_Arab',    # Arabic
    'es': 'spa_Latn',    # Spanish
    'hi': 'hin_Deva',    # Hindi
    'fr': 'fra_Latn'     # French
}

def translate_text(text, target_lang='eng_Latn'):
    """Translate text using NLLB-200"""
    try:
        source_lang = detect(text)
        source_code = LANG_CODE_MAP.get(source_lang, 'eng_Latn')
        translation = translator(text)[0]['translation_text']
        return translation
    except Exception as e:
        st.error(f"Translation error: {str(e)}")
        return text

def get_homeopathic_advice(symptoms):
    """Get medical advice using Groq API"""
    try:
        response = groq_client.chat.completions.create(
            model="llama3-70b-8192",
            messages=[{
                "role": "user",
                "content": f"Act as a homeopathic expert. Suggest remedies for: {symptoms}"
            }],
            temperature=0.3
        )
        return response.choices[0].message.content
    except Exception as e:
        return f"Error: {str(e)}"

# Streamlit UI
st.set_page_config(page_title="Homeo Advisor", page_icon="🌿")
st.title("🌍 Multilingual Homeopathic Advisor")

# Chat interface
if "messages" not in st.session_state:
    st.session_state.messages = []

for message in st.session_state.messages:
    with st.chat_message(message["role"]):
        st.markdown(message["content"])

if prompt := st.chat_input("Describe symptoms in any language"):
    st.session_state.messages.append({"role": "user", "content": prompt})

    # Process input
    with st.spinner("Analyzing..."):
        # Translate input to English
        english_input = translate_text(prompt)

        # Get medical advice
        english_advice = get_homeopathic_advice(english_input)

        # Translate back to original language
        source_lang = detect(prompt)
        translated_advice = translate_text(english_advice)

        # Format response
        final_response = f"""
        **English Recommendation:**  
        {english_advice}
        
        **Translated Recommendation ({source_lang.upper()}):**  
        {translated_advice}
        """

    # Display response
    with st.chat_message("assistant"):
        st.markdown(final_response)
    st.session_state.messages.append({"role": "assistant", "content": final_response})

# Disclaimer
st.caption("⚠️ This is not medical advice. Consult a professional.")