Update app.py

app.py

@@ -8,9 +8,11 @@ intent_classifier_ar = pipeline("text-classification", model="aubmindlab/bert-ba
 # Load English NLP model for zero-shot classification
 intent_classifier_en = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
 
-# Load language detection model
+# Load language detection model only (smaller model)
+from transformers import pipeline
 language_detector = pipeline("text-classification", model="papluca/xlm-roberta-base-language-detection")
 
+
 # Omdurman National Bank-specific guidelines in Arabic
 ONB_GUIDELINES_AR = {
     "balance": "يمكنك التحقق من رصيدك عبر الإنترنت أو عبر تطبيق الهاتف الخاص ببنك الوطني.",
@@ -37,17 +39,17 @@ ONB_GUIDELINES_EN = {
     "contact": "Contact us at 249-123-456-789 or via email at [email protected]."
 }
 
-# Map intents to responses
+# Map intents to keywords (enhanced)
 INTENT_KEYWORDS = {
-    "balance": ["balance", "رصيد", "حساب"],
-    "lost_card": ["lost", "card", "stolen", "فقدت", "بطاقة", "مسروقة"],
-    "loan": ["loan", "borrow", "قرض", "استدانة"],
-    "transfer": ["transfer", "send money", "تحويل", "ارسال"],
-    "new_account": ["account", "open", "حساب", "فتح"],
-    "interest_rates": ["interest", "rate", "فائدة", "نسبة"],
-    "branches": ["branch", "location", "فرع", "موقع"],
-    "working_hours": ["hours", "time", "ساعات", "وقت"],
-    "contact": ["contact", "phone", "email", "اتصال", "هاتف", "بريد"]
+    "balance": ["balance", "check balance", "account balance", "how much", "رصيد", "حساب", "كم المبلغ"],
+    "lost_card": ["lost", "card", "stolen", "missing", "فقدت", "بطاقة", "مسروقة", "ضائعة"],
+    "loan": ["loan", "borrow", "borrowing", "credit", "قرض", "استدانة", "إئتمان"],
+    "transfer": ["transfer", "send money", "payment", "تحويل", "ارسال", "دفع"],
+    "new_account": ["account", "open", "create", "new", "حساب", "فتح", "جديد", "إنشاء"],
+    "interest_rates": ["interest", "rate", "rates", "return", "فائدة", "نسبة", "عائد"],
+    "branches": ["branch", "location", "where", "office", "فرع", "موقع", "أين", "مكتب"],
+    "working_hours": ["hours", "time", "open", "close", "ساعات", "وقت", "مفتوح", "مغلق"],
+    "contact": ["contact", "phone", "email", "call", "اتصال", "هاتف", "بريد", "اتصل"]
 }
 
 def detect_language(text):
@@ -56,26 +58,14 @@ def detect_language(text):
     language = result[0]['label']
     return language
 
-def classify_intent(message: str, language: str):
-    # Use appropriate classifier based on language
-    if language == "ar":
-        # For Arabic
-        result = intent_classifier_ar(message)
-        intent = result[0]['label']
-    else:
-        # For English - using zero-shot classification correctly
-        result = intent_classifier_en(message, candidate_labels=list(INTENT_KEYWORDS.keys()))
-        intent = result["labels"][0]
-    
-    # Fallback to keyword matching
-    if intent not in INTENT_KEYWORDS:
-        for intent_key, keywords in INTENT_KEYWORDS.items():
-            for keyword in keywords:
-                if re.search(r'\b' + re.escape(keyword.lower()) + r'\b', message.lower()):
-                    return intent_key
-        return "unknown"
-    
-    return intent
+def classify_intent(message: str):
+    # Use keyword matching for all languages
+    message = message.lower()
+    for intent_key, keywords in INTENT_KEYWORDS.items():
+        for keyword in keywords:
+            if keyword.lower() in message:
+                return intent_key
+    return "unknown"
 
 def respond(message: str):
     if not message.strip():
@@ -91,9 +81,9 @@ def respond(message: str):
     if language != "ar" and language != "en":
         language = "en"
     
-    # Classify the user's intent
-    intent = classify_intent(message, language)
-    
+    # Classify the user's intent using keyword matching
+    intent = classify_intent(message)
+       
     # Prepare responses in both languages
     responses = {
         "ar": "",
@@ -147,7 +137,7 @@ custom_css = """
 
 .header-section {
     background-color: #1a5276;
-    color: white;
+    font-color: white;
     padding: 1rem;
     border-radius: 10px;
     margin-bottom: 1rem;