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import streamlit as st
import os
from transformers import pipeline
from langdetect import detect, DetectorFactory
from groq import Groq
# Ensure consistent language detection
DetectorFactory.seed = 0
# 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
try:
translator = pipeline("translation", model="facebook/nllb-200-distilled-600M", token=HF_TOKEN)
except Exception as e:
st.error(f"❌ Error initializing translation model: {e}")
# Initialize Groq client for AI-based homeopathic advice
GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
if not GROQ_API_KEY:
st.error("❌ Missing GROQ API Key. Set 'GROQ_API_KEY' in environment variables.")
groq_client = Groq(api_key=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 model."""
try:
source_lang = detect(text)
source_code = LANG_CODE_MAP.get(source_lang, 'eng_Latn') # Default to English if unknown
st.write(f"🔄 Detected source: {source_code}, Target: {target_lang}") # Debugging log
translation = translator(
text,
src_lang=source_code, # Pass source language
tgt_lang=target_lang # Pass target language
)
return translation[0]['translation_text']
except Exception as e:
st.error(f"⚠️ Translation error: {str(e)}")
return text # Return original text if translation fails
def get_homeopathic_advice(symptoms):
"""Get medical advice using Groq AI 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 fetching homeopathic advice: {str(e)}"
# 🎨 Streamlit UI
st.set_page_config(page_title="Homeo Advisor", page_icon="🌿")
st.title("🌍 Multilingual Homeopathic Advisor")
# Chat interface (Persistent session)
if "messages" not in st.session_state:
st.session_state.messages = []
# Display previous chat messages
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
# User input box
if prompt := st.chat_input("Describe symptoms in any language..."):
st.session_state.messages.append({"role": "user", "content": prompt})
with st.spinner("🔍 Analyzing..."):
# Translate user input to English
english_input = translate_text(prompt, "eng_Latn")
# Get homeopathic advice in English
english_advice = get_homeopathic_advice(english_input)
# Detect original language
source_lang = detect(prompt)
source_code = LANG_CODE_MAP.get(source_lang, 'eng_Latn')
# Translate advice back to original language
translated_advice = translate_text(english_advice, source_code)
# 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)
# Save response in session history
st.session_state.messages.append({"role": "assistant", "content": final_response})
# Disclaimer
st.caption("⚠️ This is not medical advice. Consult a professional.")
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