Update app.py

app.py

@@ -1,27 +1,46 @@
 import gradio as gr
-import re
+import spacy
 import json
-import time
 from datetime import datetime
 
-# Corrected Simple language detection function
-def simple_detect_language(text):
-    arabic_pattern = re.compile(r'[Ø€-Û¿]+')  # Fixed Arabic character range
-    return "ar" if arabic_pattern.search(text) else "en"
+# Load spaCy language models
+try:
+    nlp_ar = spacy.blank("ar")  # Arabic
+    nlp_en = spacy.blank("en")  # English
+except Exception as e:
+    print(f"Error loading spaCy models: {e}")
+    nlp_ar = None
+    nlp_en = None
+
+# Function to detect language using spaCy
+def detect_language(text):
+    if not text.strip():
+        return "unknown"
+    
+    # Check if the text contains Arabic characters using spaCy
+    if nlp_ar and any(token.is_alpha for token in nlp_ar(text)):
+        return "ar"
+    
+    # Check for English
+    if nlp_en and any(token.is_alpha for token in nlp_en(text)):
+        return "en"
+    
+    return "unknown"
 
 # Placeholder customer service functions
-def get_enhanced_response(intent, lang, name=""):
+def get_enhanced_response(intent, lang):
     responses = {
         "balance": {"ar": "رصيدك هو 1000 جنيه سوداني.", "en": "Your balance is 1000 SDG."},
         "lost_card": {"ar": "يرجى الاتصال بالبنك فورًا للإبلاغ عن بطاقة مفقودة.", "en": "Please contact the bank immediately to report a lost card."}
     }
     return responses.get(intent, {}).get(lang, "I'm not sure how to answer that.")
 
+# Log interactions
 def log_interaction(user_message, bot_response, intent, language):
     timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
     log_entry = {"timestamp": timestamp, "user_message": user_message, "bot_response": bot_response, "intent": intent, "language": language}
-    with open("/mnt/data/chat_logs.jsonl", "a") as f:
-        f.write(json.dumps(log_entry) + "\n")
+    with open("/mnt/data/chat_logs.jsonl", "a", encoding="utf-8") as f:
+        f.write(json.dumps(log_entry, ensure_ascii=False) + "\n")
 
 # Intent classification function
 def classify_intent(message):
@@ -36,13 +55,13 @@ def classify_intent(message):
 
 # Response function
 def respond(message):
-    language = simple_detect_language(message)
+    language = detect_language(message)
     intent = classify_intent(message)
     response = get_enhanced_response(intent, language)
     log_interaction(message, response, intent, language)
     return response
 
-# Chat interface with Gradio
+# Chatbot interface with Gradio
 def chatbot_interface(user_input, chat_history):
     if not user_input.strip():
         return "", chat_history
@@ -55,7 +74,7 @@ def chatbot_interface(user_input, chat_history):
 
 # Gradio UI
 with gr.Blocks() as demo:
-    gr.Markdown("# Banking Chatbot")
+    gr.Markdown("# Banking Chatbot - Now with spaCy")
     chat_history = gr.State([])
     chatbot = gr.Chatbot()
     user_input = gr.Textbox(placeholder="Type your message...")