Update app.py

app.py

@@ -1,16 +1,29 @@
 import streamlit as st
 import os
 from transformers import pipeline
-from langdetect import detect
+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.")
+    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)
+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 = {
@@ -23,25 +36,86 @@ LANG_CODE_MAP = {
 }
 
 def translate_text(text, target_lang='eng_Latn'):
-    """Translate text using NLLB-200"""
+    """Translate text using NLLB-200 model."""
     try:
         source_lang = detect(text)
-        source_code = LANG_CODE_MAP.get(source_lang, 'eng_Latn')  # Detect source language
+        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
-
-# Test function
-if __name__ == "__main__":
-    test_text = "یہ ایک آزمائشی جملہ ہے۔"  # Urdu sample text
-    translated = translate_text(test_text, "eng_Latn")
-    print("Translated:", translated)
+        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.")