Update app.py

app.py

@@ -1,14 +1,38 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+from googletrans import Translator
+from langdetect import detect
 
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+translator = Translator()
+
+def detect_and_translate(text: str, target_lang='en') -> tuple[str, str]:
+    """
+    Detect language and translate to target language if needed.
+    Returns tuple of (translated_text, detected_language)
+    """
+    try:
+        detected_lang = detect(text)
+        if detected_lang != target_lang:
+            translation = translator.translate(text, dest=target_lang)
+            return translation.text, detected_lang
+        return text, detected_lang
+    except:
+        return text, 'en'  # Fallback to original text if translation fails
+
+def translate_to_original(text: str, original_lang: str) -> str:
+    """Translate response back to original language if needed"""
+    if original_lang != 'en':
+        try:
+            translation = translator.translate(text, dest=original_lang)
+            return translation.text
+        except:
+            return text
+    return text
 
 def check_custom_responses(message: str) -> str:
     """Check for specific patterns and return custom responses."""
-    # Convert message to lowercase for case-insensitive matching
     message_lower = message.lower()
-    
-    # Dictionary of custom responses
     custom_responses = {
         "what is ur name?": "xylaria",
         "what is your name?": "xylaria",
@@ -19,15 +43,11 @@ def check_custom_responses(message: str) -> str:
         "how many r is in strawberry": "3",
         "who is ur dev": "sk md saad amin",
         "who is ur developer": "sk md saad amin",
- 
-        
     }
     
-    # Check if message matches any custom patterns
     for pattern, response in custom_responses.items():
         if pattern in message_lower:
             return response
-    
     return None
 
 def respond(
@@ -44,17 +64,22 @@ def respond(
         yield custom_response
         return
 
-    # If no custom response, proceed with normal chat completion
-    messages = [{"role": "system", "content": system_message}]
+    # Detect language and translate to English if needed
+    translated_msg, detected_lang = detect_and_translate(message)
     
+    # Prepare conversation history
+    messages = [{"role": "system", "content": system_message}]
     for val in history:
         if val[0]:
-            messages.append({"role": "user", "content": val[0]})
+            # Translate user message from history if needed
+            trans_user_msg, _ = detect_and_translate(val[0])
+            messages.append({"role": "user", "content": trans_user_msg})
         if val[1]:
             messages.append({"role": "assistant", "content": val[1]})
     
-    messages.append({"role": "user", "content": message})
+    messages.append({"role": "user", "content": translated_msg})
     
+    # Get response from model
     response = ""
     for message in client.chat_completion(
         messages,
@@ -65,7 +90,13 @@ def respond(
     ):
         token = message.choices[0].delta.content
         response += token
-        yield response
+        
+        # Translate accumulated response if original message wasn't in English
+        if detected_lang != 'en':
+            translated_response = translate_to_original(response, detected_lang)
+            yield translated_response
+        else:
+            yield response
 
 demo = gr.ChatInterface(
     respond,