app.py

import streamlit as st
import pandas as pd
from groq import Groq
import os

# --------------------------
# 1. Dataset Setup (Updated with Urdu)
# --------------------------
data = {
    "symptoms_en": ["headache", "fever", "insomnia", "anxiety", "cough"],
    "symptoms_es": ["dolor de cabeza", "fiebre", "insomnio", "ansiedad", "tos"],
    "symptoms_hi": ["सिरदर्द", "बुखार", "अनिद्रा", "चिंता", "खांसी"],
    "symptoms_ur": ["سر درد", "بخار", "بے خوابی", "اضطراب", "کھانسی"],
    "remedy": ["Belladonna", "Aconitum", "Coffea", "Argentum nitricum", "Drosera"],
    "potency": ["30C"]*5,
    "usage": ["3 times daily"]*5
}

df = pd.DataFrame(data)

# --------------------------
# 2. Groq Setup (Multilingual Processing)
# --------------------------
client = Groq(api_key=os.environ.get("GROQ_API_KEY"))

def analyze_symptoms(text, language):
    """Use Groq's Llama 3 for symptom analysis"""
    lang_map = {
        'en': 'English',
        'es': 'Spanish', 
        'hi': 'Hindi',
        'ur': 'Urdu'
    }
    
    prompt = f"""Task: Extract medical symptoms from this {lang_map[language]} text.
    Text: {text}
    Output format: Comma-separated symptoms in {lang_map[language]}.
    Example: headache, muscle pain, dry cough"""
    
    try:
        chat_completion = client.chat.completions.create(
            messages=[{"role": "user", "content": prompt}],
            model="llama3-70b-8192",
            temperature=0.1
        )
        return [s.strip() for s in chat_completion.choices[0].message.content.split(",")]
    except Exception as e:
        st.error(f"Error in Groq API: {str(e)}")
        return []

# --------------------------
# 3. Streamlit UI (Multilingual Interface)
# --------------------------
st.set_page_config(page_title="Homeo Doctor", page_icon="🌿")

# Language selection
language = st.sidebar.selectbox("भाषा चुनें/Select Language", 
                              ['English', 'Español', 'हिन्दी', 'اردو'],
                              format_func=lambda x: x)

lang_code = {
    'English': 'en',
    'Español': 'es', 
    'हिन्दी': 'hi',
    'اردو': 'ur'
}[language]

# Header with dynamic language
headers = {
    'en': "🌿 Homeopathic Doctor",
    'es': "🌿 Doctor Homeopático", 
    'hi': "🌿 होम्योपैथिक डॉक्टर",
    'ur': "🌿 ہومیوپیتھک ڈاکٹر"
}
st.header(headers[lang_code])

# MCQ Symptoms
symptom_col = f"symptoms_{lang_code}"
symptoms = df[symptom_col].tolist()
selected = st.multiselect(
    label={
        'en': "Select your symptoms:",
        'es': "Seleccione sus síntomas:",
        'hi': "अपने लक्षण चुनें:",
        'ur': "اپنی علامات منتخب کریں:"
    }[lang_code],
    options=symptoms
)

# Chat Input
chat_input = st.text_input(
    label={
        'en': "Describe other symptoms:",
        'es': "Describa otros síntomas:",
        'hi': "अन्य लक्षण बताएं:",
        'ur': "دیگر علامات بیان کریں:"
    }[lang_code],
    placeholder={
        'en': "Type symptoms not listed above...",
        'ur': "اوپر درج نہ کی گئی علامات ٹائپ کریں..."
    }[lang_code] if lang_code == 'ur' else ""
)

# Diagnosis Logic
if st.button({
    'en': "Get Recommendation", 
    'es': "Obtener Recomendación",
    'hi': "सिफारिश प्राप्त करें",
    'ur': "تجویز حاصل کریں"
}[lang_code]):
    # Process chat input
    if chat_input:
        analyzed_symptoms = analyze_symptoms(chat_input, lang_code)
        selected += [s for s in analyzed_symptoms if s in symptoms]
    
    # Find best remedy
    if not selected:
        st.warning({
            'en': "Please select or describe symptoms!",
            'ur': "براہ کرم علامات منتخب کریں یا بیان کریں!"
        }[lang_code] if lang_code == 'ur' else "")
    else:
        matches = df[df[symptom_col].isin(selected)]
        if not matches.empty:
            remedy = matches.iloc[0]
            st.success(f"""
                **{remedy['remedy']}**  
                {{
                    'en': "Potency: {remedy['potency']}",
                    'ur': "طاقت: {remedy['potency']}"
                }}[lang_code]  
                {{
                    'en': "Usage: {remedy['usage']}",
                    'ur': "استعمال: {remedy['usage']}"
                }}[lang_code]
            """)
        else:
            st.error({
                'en': "No matching remedy found. Consult a professional.",
                'ur': "کوئی مماثل دوا نہیں ملی۔ پیشہ ور سے مشورہ کریں۔"
            }[lang_code])

# Disclaimer
st.markdown("""
---
**⚠️ Notice/نوٹس:**  
This is not medical advice. Always consult a qualified homeopath.  
यह चिकित्सीय सलाह नहीं है। हमेशा योग्य होम्योपैथ से सलाह लें۔  
Esto no es un consejo médico. Siempre consulte a un homeópata calificado.  
یہ طبی مشورہ نہیں ہے۔ ہمیشہ کوالیفائڈ ہومیوپیتھک ڈاکٹر سے مشورہ کریں۔
""")