Update app.py

app.py

@@ -3,9 +3,6 @@ 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")
@@ -15,9 +12,6 @@ if not HF_TOKEN:
 # 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
@@ -32,68 +26,22 @@ 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
+        source_code = LANG_CODE_MAP.get(source_lang, 'eng_Latn')  # Detect source language
 
-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
+        translation = translator(
+            text, 
+            src_lang=source_code,   # Pass source language
+            tgt_lang=target_lang    # Pass target language
         )
-        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})
+        return translation[0]['translation_text']
+    
+    except Exception as e:
+        st.error(f"Translation error: {str(e)}")
+        return text
 
-# Disclaimer
-st.caption("⚠️ This is not medical advice. Consult a professional.")
+# 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)