app.py

# app.py
import streamlit as st
from groq import Groq
import os
import requests
from bs4 import BeautifulSoup
import re
from urllib.parse import quote_plus
from langdetect import detect

# Groq API setup
client = Groq(api_key=os.environ.get("GROQ_API_KEY"))

# Web scraping functions
def google_search(query):
    headers = {
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
    }
    encoded_query = quote_plus(query)
    url = f"https://www.google.com/search?q={encoded_query}&gl=us&hl=en"
    
    try:
        response = requests.get(url, headers=headers)
        soup = BeautifulSoup(response.text, 'html.parser')
        results = []
        
        for g in soup.find_all('div', class_='tF2Cxc'):
            link = g.find('a')['href']
            title = g.find('h3').text
            snippet = g.find('div', class_='VwiC3b')
            if snippet:
                results.append({
                    'title': title,
                    'link': link,
                    'snippet': snippet.text
                })
        return results[:3]
    except Exception as e:
        st.error(f"Search Error: {str(e)}")
        return []

# Chatbot processing
def multilingual_chatbot(user_input):
    try:
        # Detect input language
        lang = detect(user_input)
        
        # Step 1: Symptom extraction (English for searching)
        symptom_prompt = f"""Extract medical symptoms from this text in English comma-separated format:
        {user_input}
        Example Output: headache, dry cough, fever"""
        
        symptom_response = client.chat.completions.create(
            messages=[{"role": "user", "content": symptom_prompt}],
            model="llama3-70b-8192",
            temperature=0.2
        )
        symptoms = symptom_response.choices[0].message.content.split(", ")
        
        # Step 2: Web search
        search_query = f"homeopathic remedies for {' '.join(symptoms)} site:.edu OR site:.gov"
        results = google_search(search_query)
        
        # Step 3: Generate multilingual response
        response_prompt = f"""Translate this medical advice to {lang} while keeping medicine names in English:
        Suggested remedies for {', '.join(symptoms)}:
        {[r['snippet'] for r in results]}
        Include dosage instructions and administration method."""
        
        final_response = client.chat.completions.create(
            messages=[{"role": "user", "content": response_prompt}],
            model="llama3-70b-8192",
            temperature=0.3
        )
        
        return final_response.choices[0].message.content
        
    except Exception as e:
        return f"Error: {str(e)}"

# Streamlit UI
st.set_page_config(page_title="Homeo Assistant", page_icon="🌿")
st.title("🌐 Multilingual Homeopathy Advisor")

# Initialize chat history
if "messages" not in st.session_state:
    st.session_state.messages = [{"role": "assistant", "content": "Describe your symptoms in any language"}]

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

# Chat input
if prompt := st.chat_input("Type your symptoms..."):
    st.session_state.messages.append({"role": "user", "content": prompt})
    
    with st.chat_message("assistant"):
        with st.spinner("Analyzing symptoms..."):
            response = multilingual_chatbot(prompt)
            st.markdown(response)
    st.session_state.messages.append({"role": "assistant", "content": response})

# Disclaimer
st.markdown("""
---
**⚠️ Disclaimer:**  
This is not medical advice. Always consult a qualified practitioner.
""")