Update app.py

app.py

@@ -1,363 +1,99 @@
 import gradio as gr
-import re
-import json
-import time
-from datetime import datetime
+from transformers import pipeline
 
-# Simple language detection function
-def simple_detect_language(text):
-    arabic_pattern = re.compile(r'[\u0600-\u06FF\u0750-\u077F\u08A0-\u08FF]+')
-    if arabic_pattern.search(text):
-        return "ar"
-    return "en"
+# Load Arabic NLP model for intent classification
+intent_classifier = pipeline("text-classification", model="aubmindlab/bert-base-arabertv02")
 
-# Try to import transformers for Arabic NLP
-try:
-    from transformers import pipeline
-    arabic_nlp = pipeline("text-classification", model="papluca/xlm-roberta-base-language-detection")
-    ARABIC_NLP_AVAILABLE = True
-    
-    def detect_language_with_nlp(text):
-        result = arabic_nlp(text)
-        return result[0]['label']
-except ImportError:
-    ARABIC_NLP_AVAILABLE = False
-
-# Import customer service enhancements
-try:
-    from customer_service_enhancements import (
-        ENHANCED_CUSTOMER_SERVICE_PHRASES_AR,
-        ENHANCED_CUSTOMER_SERVICE_PHRASES_EN,
-        BANKING_FAQS_AR,
-        BANKING_FAQS_EN,
-        BANKING_GLOSSARY_AR,
-        BANKING_GLOSSARY_EN,
-        get_enhanced_response,
-        handle_banking_faq,
-        offer_satisfaction_survey,
-        get_banking_term_definition
-    )
-    CUSTOMER_SERVICE_ENHANCEMENTS_AVAILABLE = True
-except ImportError:
-    CUSTOMER_SERVICE_ENHANCEMENTS_AVAILABLE = False
-    ENHANCED_CUSTOMER_SERVICE_PHRASES_AR = {
-        "greeting": ["مرحبًا بك في بنك أم درمان الوطني! كيف يمكنني مساعدتك اليوم؟"],
-        "thanks": ["شكرًا لتواصلك مع بنك أم درمان الوطني!"],
-        "follow_up": ["هل هناك خدمة أخرى يمكنني مساعدتك بها؟"]
-    }
-    ENHANCED_CUSTOMER_SERVICE_PHRASES_EN = {
-        "greeting": ["Welcome to Omdurman National Bank! How may I assist you today?"],
-        "thanks": ["Thank you for contacting Omdurman National Bank!"],
-        "follow_up": ["Is there anything else I can help you with?"]
-    }
+# Load language detection model
+language_detector = pipeline("text-classification", model="papluca/xlm-roberta-base-language-detection")
 
 # Omdurman National Bank-specific guidelines
-ONB_GUIDELINES_AR = {
+ONB_GUIDELINES = {
     "balance": "يمكنك التحقق من رصيدك عبر الإنترنت أو عبر تطبيق الهاتف الخاص ببنك أم درمان الوطني.",
     "lost_card": "في حالة فقدان البطاقة، اتصل بالرقم 249-123-456-789 فورًا.",
     "loan": "شروط القرض تشمل الحد الأدنى للدخل (5000 جنيه سوداني) وتاريخ ائتماني جيد.",
     "transfer": "لتحويل الأموال، استخدم تطبيق الهاتف أو الخدمة المصرفية عبر الإنترنت.",
     "new_account": "لفتح حساب جديد، قم بزيارة أقرب فرع مع جواز سفرك أو هويتك الوطنية.",
     "interest_rates": "أسعار الفائدة على الودائع تتراوح بين 5% إلى 10% سنويًا.",
-    "branches": "فروعنا موجودة في أم درمان، الخرطوم، وبورتسودان.",
+    "branches": "فروعنا موجودة في أم درمان، الخرطوم، وبورتسودان. زيارة موقعنا للتفاصيل.",
     "working_hours": "ساعات العمل من 8 صباحًا إلى 3 مساءً من الأحد إلى الخميس.",
     "contact": "الاتصال بنا على الرقم 249-123-456-789 أو عبر البريد الإلكتروني [email protected]."
 }
 
-ONB_GUIDELINES_EN = {
-    "balance": "You can check your balance online or via the ONB mobile app.",
-    "lost_card": "In case of a lost card, call 249-123-456-789 immediately.",
-    "loan": "Loan requirements include minimum income (5000 SDG) and good credit history.",
-    "transfer": "To transfer funds, use the mobile app or online banking service.",
-    "new_account": "To open a new account, visit your nearest branch with your passport or national ID.",
-    "interest_rates": "Interest rates on deposits range from 5% to 10% annually.",
-    "branches": "Our branches are located in Omdurman, Khartoum, and Port Sudan.",
-    "working_hours": "Working hours are from 8 AM to 3 PM, Sunday to Thursday.",
-    "contact": "Contact us at 249-123-456-789 or via email at [email protected]."
+# Map intents to responses
+INTENT_TO_RESPONSE = {
+    "balance": "balance",
+    "lost_card": "lost_card",
+    "loan": "loan",
+    "transfer": "transfer",
+    "new_account": "new_account",
+    "interest_rates": "interest_rates",
+    "branches": "branches",
+    "working_hours": "working_hours",
+    "contact": "contact"
 }
 
-# Quick action buttons
-QUICK_ACTIONS_AR = [
-    {"text": "تحقق من الرصيد", "intent": "balance"},
-    {"text": "الإبلاغ عن بطاقة مفقودة", "intent": "lost_card"},
-    {"text": "معلومات القرض", "intent": "loan"},
-    {"text": "تحويل الأموال", "intent": "transfer"},
-    {"text": "فتح حساب جديد", "intent": "new_account"},
-    {"text": "أسعار الفائدة", "intent": "interest_rates"},
-    {"text": "مواقع الفروع", "intent": "branches"},
-    {"text": "ساعات العمل", "intent": "working_hours"},
-    {"text": "اتصل بنا", "intent": "contact"}
-]
-
-QUICK_ACTIONS_EN = [
-    {"text": "Check Balance", "intent": "balance"},
-    {"text": "Report Lost Card", "intent": "lost_card"},
-    {"text": "Loan Information", "intent": "loan"},
-    {"text": "Transfer Funds", "intent": "transfer"},
-    {"text": "Open New Account", "intent": "new_account"},
-    {"text": "Interest Rates", "intent": "interest_rates"},
-    {"text": "Branch Locations", "intent": "branches"},
-    {"text": "Working Hours", "intent": "working_hours"},
-    {"text": "Contact Us", "intent": "contact"}
-]
-
-# Function to get a random phrase
-def get_random_phrase(category, language):
-    import random
-    if language == "ar":
-        return random.choice(ENHANCED_CUSTOMER_SERVICE_PHRASES_AR[category])
-    else:
-        return random.choice(ENHANCED_CUSTOMER_SERVICE_PHRASES_EN[category])
+def detect_language(text):
+    # Use Hugging Face language detection model
+    result = language_detector(text)
+    language = result[0]['label']
+    return language
 
 def classify_intent(message: str):
-    menu_keywords = ["menu", "options", "help", "قائمة", "خيارات", "مساعدة"]
-    message_lower = message.lower()
-    
-    for keyword in menu_keywords:
-        if keyword in message_lower:
-            return "menu"
-    
-    for intent_key, keywords in INTENT_KEYWORDS.items():
-        for keyword in keywords:
-            if keyword.lower() in message_lower:
-                return intent_key
-                
-    return "unknown"
+    # Use NLP model to classify the user's intent
+    result = intent_classifier(message)
+    intent = result[0]['label']
+    return INTENT_TO_RESPONSE.get(intent, "unknown")
 
-# Function to log customer 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
-    }
-    
-    try:
-        with open("interaction_logs.jsonl", "a") as f:
-            f.write(json.dumps(log_entry) + "\n")
-    except Exception as e:
-        print(f"Error logging interaction: {e}")
-
-# Function to generate responses
 def respond(message: str):
-    if not message.strip():
-        return {
-            "ar": "الرجاء كتابة سؤالك.",
-            "en": "Please type your question."
-        }
-    
     # Detect language
-    if ARABIC_NLP_AVAILABLE:
-        language = detect_language_with_nlp(message)
-        if language != "ar" and language != "en":
-            language = "en"
-    else:
-        language = simple_detect_language(message)
-    
-    # Classify intent
-    intent = classify_intent(message)
-    
-    # Prepare responses
-    responses = {
-        "ar": "",
-        "en": ""
-    }
+    language = detect_language(message)
     
-    # Handle menu request
-    if intent == "menu":
-        responses["ar"] = MENU_AR
-        responses["en"] = MENU_EN
-        log_interaction(message, responses[language], "menu", language)
-        return responses
+    # If the language is not Arabic, return a default response
+    if language != "ar":
+        return "عذرًا، هذا المساعد يدعم اللغة العربية فقط. الرجاء إعادة الصياغة بالعربية."
     
-    # Handle banking FAQ
-    if CUSTOMER_SERVICE_ENHANCEMENTS_AVAILABLE:
-        faq_answer = handle_banking_faq(message, language)
-        if faq_answer:
-            responses["ar"] = f"{get_random_phrase('greeting', 'ar')}<br><br>{faq_answer}<br><br>{get_random_phrase('follow_up', 'ar')}"
-            responses["en"] = f"{get_random_phrase('greeting', 'en')}<br><br>{faq_answer}<br><br>{get_random_phrase('follow_up', 'en')}"
-            log_interaction(message, responses[language], "faq", language)
-            return responses
-    
-    # Handle banking term definition
-    if CUSTOMER_SERVICE_ENHANCEMENTS_AVAILABLE:
-        term_definition = get_banking_term_definition(message, language)
-        if term_definition:
-            responses["ar"] = f"{get_random_phrase('greeting', 'ar')}<br><br>{term_definition}<br><br>{get_random_phrase('follow_up', 'ar')}"
-            responses["en"] = f"{get_random_phrase('greeting', 'en')}<br><br>{term_definition}<br><br>{get_random_phrase('follow_up', 'en')}"
-            log_interaction(message, responses[language], "term", language)
-            return responses
+    # Classify the user's intent using NLP
+    intent = classify_intent(message)
     
-    # Handle recognized intents
+    # If intent is recognized, return the corresponding response
     if intent != "unknown":
-        if CUSTOMER_SERVICE_ENHANCEMENTS_AVAILABLE:
-            responses["ar"] = get_enhanced_response(intent, "ar")
-            responses["en"] = get_enhanced_response(intent, "en")
-        else:
-            responses["ar"] = f"{get_random_phrase('greeting', 'ar')}<br><br>{ONB_GUIDELINES_AR.get(intent, 'عذرًا، لم يتم التعرف على الخيار المحدد.')}<br><br>{get_random_phrase('follow_up', 'ar')}"
-            responses["en"] = f"{get_random_phrase('greeting', 'en')}<br><br>{ONB_GUIDELINES_EN.get(intent, 'Sorry, the selected option was not recognized.')}<br><br>{get_random_phrase('follow_up', 'en')}"
-    else:
-        responses["ar"] = "عذرًا، لم أفهم سؤالك. إليك قائمة بالخدمات المتاحة:" + MENU_AR
-        responses["en"] = "Sorry, I didn't understand your question. Here's a menu of available services:" + MENU_EN
-    
-    log_interaction(message, responses[language], intent, language)
-    return responses
-
-# Function to handle message submission
-def on_submit(message, chat_history, lang, name):
-    if not message.strip():
-        return "", chat_history, name
-    
-    # Check if this is a name introduction
-    name_patterns = [
-        r"my name is (\w+)",
-        r"i am (\w+)",
-        r"i'm (\w+)",
-        r"اسمي (\w+)",
-        r"أنا (\w+)"
-    ]
-    
-    for pattern in name_patterns:
-        match = re.search(pattern, message.lower())
-        if match:
-            name = match.group(1)
-            break
-    
-    # Add user message to chat history
-    chat_history = chat_history + [[message, None]]
-    
-    # Get response
-    responses = respond(message)
-    
-    # Select response based on language
-    response = responses[lang]
-    
-    # Personalize response if name is available
-    if name and CUSTOMER_SERVICE_ENHANCEMENTS_AVAILABLE:
-        if lang == "ar":
-            response = response.replace("مرحبًا", f"مرحبًا {name}")
-        else:
-            response = response.replace("Welcome", f"Welcome {name}")
-            response = response.replace("Hello", f"Hello {name}")
-    
-    # Update bot response in chat history
-    chat_history[-1][1] = response
-    
-    return "", chat_history, name
-
-# Function to show menu
-def show_menu(chat_history, lang):
-    menu_responses = {
-        "ar": MENU_AR,
-        "en": MENU_EN
-    }
-    
-    # Get menu text
-    menu_text = menu_responses[lang]
-    
-    # Add system message showing the menu
-    chat_history = chat_history + [[None, menu_text.replace("\n", "<br>")]]
-    
-    return chat_history
-
-# Function to connect to live agent
-def connect_to_live_agent(chat_history, lang):
-    message = "Connecting to a live customer service agent. Please wait a moment..." if lang == "en" else "جاري الاتصال بوكيل خدمة العملاء. يرجى الانتظار لحظة..."
-    chat_history = chat_history + [[None, message]]
-    return chat_history
-
-# Function to show satisfaction survey
-def show_satisfaction_survey(chat_history, lang):
-    if CUSTOMER_SERVICE_ENHANCEMENTS_AVAILABLE:
-        survey_html = offer_satisfaction_survey(lang)
-        chat_history = chat_history + [[None, survey_html]]
-    else:
-        # Simple survey message if enhancements not available
-        title = "استطلاع رضا العملاء" if lang == "ar" else "Customer Satisfaction Survey"
-        message = f"<div class='satisfaction-survey'><h3>{title}</h3><p>{'نشكرك على استخدام المساعد المصرفي الافتراضي!' if lang == 'ar' else 'Thank you for using our virtual banking assistant!'}</p></div>"
-        chat_history = chat_history + [[None, message]]
-    
-    return chat_history
-
-# Function to reset chat
-def reset_chat():
-    return [], None  # Clear chat history and reset user name
-
-# Function to initialize chat with welcome message
-def init_chat():
-    welcome_ar = "مرحبًا بك في المساعد المصرفي الافتراضي لبنك أم درمان الوطني! يمكنك طرح أي سؤال حول خدماتنا المصرفية أو استخدام أزرار الإجراءات السريعة أدناه."
-    welcome_en = "Welcome to Omdurman National Bank Virtual Banking Assistant! You can ask any question about our banking services or use the quick action buttons below."
-    
-    # Initialize chat with welcome messages
-    chat_history = []
-    chat_history.append([None, welcome_ar])
-    chat_history.append([None, welcome_en])
-    
-    return chat_history
-
-# Gradio Interface
-with gr.Blocks() as demo:
-    selected_lang = gr.State(value="ar")
-    user_name = gr.State(value=None)
-    
-    with gr.Row():
-        gr.Markdown("# Omdurman National Bank Virtual Assistant")
-    
-    with gr.Row():
-        language_btn = gr.Radio(["العربية", "English"], value="العربية", label="Language")
-    
-    chatbot = gr.Chatbot(height=400, type="messages")  # Updated to use the new format
-    
-    with gr.Row():
-        text_input = gr.Textbox(placeholder="Type your question here", label="")
-        submit_btn = gr.Button("Send", variant="primary")
-    
-    with gr.Row():
-        menu_btn = gr.Button("Show Menu")
-        live_agent_btn = gr.Button("Connect to Live Agent")
-        survey_btn = gr.Button("Feedback")
-        reset_btn = gr.Button("Reset Chat")
-    
-    # Link inputs and buttons to response functions
-    submit_btn.click(
-        fn=on_submit,
-        inputs=[text_input, chatbot, selected_lang, user_name],
-        outputs=[text_input, chatbot, user_name]
-    )
-    
-    menu_btn.click(
-        fn=show_menu,
-        inputs=[chatbot, selected_lang],
-        outputs=[chatbot]
-    )
-    
-    live_agent_btn.click(
-        fn=connect_to_live_agent,
-        inputs=[chatbot, selected_lang],
-        outputs=[chatbot]
-    )
-    
-    survey_btn.click(
-        fn=show_satisfaction_survey,
-        inputs=[chatbot, selected_lang],
-        outputs=[chatbot]
-    )
-    
-    reset_btn.click(
-        fn=reset_chat,
-        inputs=[],
-        outputs=[chatbot, user_name]
-    )
-    
-    # Initialize chat
-    demo.load(
-        fn=init_chat,
-        inputs=[],
-        outputs=[chatbot]
-    )
+        return ONB_GUIDELINES.get(intent, "عذرًا، لم يتم التعرف على الخيار المحدد.")
+    
+    # Fallback to keyword matching if NLP doesn't recognize the intent
+    for keyword, key in INTENT_TO_RESPONSE.items():
+        if keyword in message:
+            return ONB_GUIDELINES.get(key, "عذرًا، لم يتم التعرف على الخيار المحدد.")
+    
+    # Default response if no intent or keyword is matched
+    return "عذرًا، لم أفهم سؤالك. الرجاء إعادة الصياغة أو اختيار أحد الخيارات التالية: " + ", ".join(INTENT_TO_RESPONSE.keys())
+
+# Chat interface
+with gr.Blocks(css=".gradio-container {direction: rtl;}") as demo:
+    gr.Markdown("# <center>بنك أم درمان الوطني - المساعد المصرفي</center>")
+    
+    with gr.Tab("المحادثة"):
+        gr.Markdown("## اكتب سؤالك هنا:")
+        
+        # Text input
+        text_input = gr.Textbox(label="السؤال")
+        
+        # Submit button
+        submit_btn = gr.Button("إرسال")
+        
+        # Output textbox for responses
+        output = gr.Textbox(label="الرد", interactive=False)
+        
+        # Link inputs and button to response function
+        submit_btn.click(
+            fn=respond,
+            inputs=text_input,
+            outputs=output
+        )
 
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860, share=True)
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=True  # Enable public link
+    )