Update app.py
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app.py
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import gradio as gr
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from huggingface_hub import InferenceClient
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# ✅ Connect to Hugging Face API (Replace with your model or API key)
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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# ✅
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titles = {
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"en": {
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"header": "🧠 Bandar AI - Your Smart Assistant",
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"subtitle": "💬 Talk to me! I'm here to help you with anything you need.",
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"chat_label": "Bandar AI",
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"input_label": "Type your message here",
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"placeholder": "Hello! How can I help you?",
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"send_button": "Send",
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"clear_button": "Clear Chat",
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"toggle_button": "Switch to Arabic"
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},
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"ar": {
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"header": "🧠 بندر AI - مساعدك الذكي",
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"subtitle": "💬 تحدث معي! أنا هنا لمساعدتك في أي موضوع تحتاجه.",
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"chat_label": "بندر AI",
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"input_label": "اكتب رسالتك هنا",
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"placeholder": "مرحبًا! كيف يمكنني مساعدتك؟",
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"send_button": "إرسال",
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"clear_button": "مسح المحادثة",
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"toggle_button": "التبديل إلى الإنجليزية"
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}
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}
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# ✅ System Prompt
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BANDAR_AI_PROMPT = "أنت مساعد ذكاء اصطناعي يدعى باندر AI."
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# ✅ Initialize Conversation History
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def initialize_history():
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return []
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# ✅ Convert history into tuples for Gradio Chatbot
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def format_history(history):
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return history[-10:] # Keep only the last 10 exchanges
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# ✅ Chat Response Function (
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def respond(message, history):
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history.append((message, "")) # Append user message
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response = ""
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for msg in client.chat_completion(
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token = msg.choices[0].delta.content
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if token:
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response += token
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history[-1] = (message, response) # Update
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yield
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history[-1] = (message, response) # Ensure
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# ✅ Clear Conversation History
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def clear_history():
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return [], [] # Reset chatbot and history
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# ✅ Toggle Language Function
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def toggle_language(current_language):
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return "ar" if current_language == "en" else "en"
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# ✅ Gradio UI
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with gr.Blocks(
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header = gr.Markdown(titles["en"]["header"])
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subtitle = gr.Markdown(titles["en"]["subtitle"])
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history = gr.State(initialize_history())
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chatbot = gr.Chatbot(
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with gr.Row():
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user_input = gr.Textbox(
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send_button = gr.Button(
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with gr.Row():
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clear_button = gr.Button(
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toggle_button = gr.Button(titles["en"]["toggle_button"], variant="secondary")
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# Event Handlers
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send_button.click(respond, inputs=[user_input, history], outputs=[chatbot, history])
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user_input.submit(respond, inputs=[user_input, history], outputs=[chatbot, history])
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clear_button.click(clear_history, outputs=[chatbot, history])
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def update_ui(lang):
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return (
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titles[lang]["header"],
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titles[lang]["subtitle"],
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titles[lang]["chat_label"],
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titles[lang]["input_label"],
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titles[lang]["placeholder"],
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titles[lang]["send_button"],
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titles[lang]["clear_button"],
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titles[lang]["toggle_button"]
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)
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toggle_button.click(toggle_language, inputs=[language], outputs=[language])
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toggle_button.click(
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update_ui, inputs=[language],
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outputs=[header, subtitle, chatbot, user_input, user_input, send_button, clear_button, toggle_button]
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)
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# ✅ Run the Chatbot
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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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from huggingface_hub import InferenceClient
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# ✅ Connect to Hugging Face API (Replace with your model or API key)
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client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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# ✅ System Prompt for AI Behavior
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BANDAR_AI_PROMPT = "أنت مساعد ذكاء اصطناعي يدعى باندر AI."
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# ✅ Initialize Conversation History
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def initialize_history():
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return [] # Start with an empty conversation history
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# ✅ Chat Response Function (Fixed)
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def respond(message, history):
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history.append((message, "")) # Append user message with empty response
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response = ""
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for msg in client.chat_completion(
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token = msg.choices[0].delta.content
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if token:
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response += token
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history[-1] = (message, response) # Update last response
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yield history # Send updated conversation history
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history[-1] = (message, response) # Ensure full response is saved
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# ✅ Clear Conversation History
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def clear_history():
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return [], [] # Reset chatbot and history
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# ✅ Gradio UI
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with gr.Blocks() as demo:
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gr.Markdown("# 🧠 Bandar AI - Chatbot")
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history = gr.State(initialize_history())
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chatbot = gr.Chatbot()
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with gr.Row():
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user_input = gr.Textbox(placeholder="Type your message here...", scale=8)
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send_button = gr.Button("Send", variant="primary", scale=2)
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with gr.Row():
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clear_button = gr.Button("Clear Chat")
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# Event Handlers
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send_button.click(respond, inputs=[user_input, history], outputs=[chatbot, history])
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user_input.submit(respond, inputs=[user_input, history], outputs=[chatbot, history])
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clear_button.click(clear_history, outputs=[chatbot, history])
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# ✅ Run the Chatbot
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if __name__ == "__main__":
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demo.launch()
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