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Update app.py
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app.py
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import gradio as gr
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import logging
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# Omdurman National Bank-specific guidelines
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ONB_GUIDELINES = {
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"الاتصال بالبنك": "contact"
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}
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# Set up logging for analytics
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logging.basicConfig(filename='chatbot_queries.log', level=logging.INFO)
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def
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#
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#
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# Return the corresponding response
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if key:
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return ONB_GUIDELINES.get(key, "عذرًا، لم يتم التعرف على الخيار المحدد.")
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else:
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# Omdurman National Bank-specific interface
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with gr.Blocks(css=".gradio-container {direction: rtl;}") as demo:
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gr.Markdown("# <center>بنك أم درمان الوطني - المساعد المصرفي</center>")
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with gr.Tab("المحادثة"):
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gr.Markdown("## اختر أحد الخيارات
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# Dropdown menu for questions
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dropdown = gr.Dropdown(
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interactive=True
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)
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# Submit button
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submit_btn = gr.Button("إرسال")
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# Output textbox for responses
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output = gr.Textbox(label="الرد", interactive=False)
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#
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submit_btn.click(
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fn=respond,
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inputs=dropdown,
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outputs=output
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)
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with gr.Tab("الإرشادات المصرفية"):
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gr.Markdown("## إرشادات بنك أم درمان الوطني")
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for key, value in ONB_GUIDELINES.items():
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gr.Markdown(f"**{key.capitalize()}**: {value}")
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if __name__ == "__main__":
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demo.launch(
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import gradio as gr
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import logging
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from transformers import pipeline
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# Omdurman National Bank-specific guidelines
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ONB_GUIDELINES = {
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"الاتصال بالبنك": "contact"
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}
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# Load Arabic intent classification model
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intent_classifier = pipeline("text-classification", model="aubmindlab/bert-base-arabertv02")
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# Map intents to menu options
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INTENT_TO_OPTION = {
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"balance": "التحقق من الرصيد",
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"lost_card": "الإبلاغ عن فقدان البطاقة",
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"loan": "شروط الحصول على قرض",
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"transfer": "تحويل الأموال",
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"new_account": "فتح حساب جديد",
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"interest_rates": "أسعار الفائدة",
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"branches": "فروع البنك",
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"working_hours": "ساعات العمل",
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"contact": "الاتصال بالبنك"
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}
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# Set up logging for analytics
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logging.basicConfig(filename='chatbot_queries.log', level=logging.INFO)
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def classify_intent(message: str):
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# Classify the user's intent
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result = intent_classifier(message)
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intent = result[0]['label']
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return INTENT_TO_OPTION.get(intent, "عذرًا، لم أفهم سؤالك. الرجاء اختيار أحد الخيارات التالية.")
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def respond(option: str, message: str, history: list):
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# If the user selects from the dropdown
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if option:
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key = OPTION_TO_KEY.get(option)
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response = ONB_GUIDELINES.get(key, "عذرًا، لم يتم التعرف على الخيار المحدد.")
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# If the user types a message
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elif message:
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option = classify_intent(message)
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key = OPTION_TO_KEY.get(option)
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response = ONB_GUIDELINES.get(key, "عذرًا، لم أفهم سؤالك. الرجاء اختيار أحد الخيارات التالية.")
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else:
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response = "عذرًا، لم يتم تحديد سؤال."
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# Add follow-up questions based on intent
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if key == "loan":
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response += "\n\nما هو نوع القرض الذي تبحث عنه؟"
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elif key == "new_account":
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response += "\n\nهل تريد فتح حساب شخصي أو حساب تجاري؟"
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# Add feedback buttons
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feedback_buttons = gr.Row([
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gr.Button("👍", variant="secondary"),
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gr.Button("👎", variant="secondary")
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])
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return response, feedback_buttons
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# Omdurman National Bank-specific interface
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with gr.Blocks(css=".gradio-container {direction: rtl;}") as demo:
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gr.Markdown("# <center>بنك أم درمان الوطني - المساعد المصرفي</center>")
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with gr.Tab("المحادثة"):
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gr.Markdown("## اختر أحد الخيارات التالية أو اكتب سؤالك:")
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# Dropdown menu for questions
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dropdown = gr.Dropdown(
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interactive=True
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)
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# Free-text input
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text_input = gr.Textbox(label="أو اكتب سؤالك هنا")
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# Submit button
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submit_btn = gr.Button("إرسال")
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# Output textbox for responses
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output = gr.Textbox(label="الرد", interactive=False)
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# Feedback buttons
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feedback_buttons = gr.Row([
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gr.Button("👍", variant="secondary"),
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gr.Button("👎", variant="secondary")
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])
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# Link inputs and button to response function
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submit_btn.click(
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fn=respond,
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inputs=[dropdown, text_input],
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outputs=[output, feedback_buttons]
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)
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if __name__ == "__main__":
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demo.launch(
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