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app.py

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+import gradio as gr
+
+def chatbot(input_text, history=[]):
+    if not input_text:
+        return history, ""
+    history = history + [f"User: {input_text}"]
+    response = f"You said: {input_text}"  # Simple response
+    history = history + [f"Bot: {response}"]
+    return history, ""
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Simple Chatbot\nBuilt with anycoder")
+    chatbot_ui = gr.Chatbot()
+    input_box = gr.Textbox(placeholder="Type your message...", label="Message")
+    with gr.Row():
+        send_btn = gr.Button("Send", variant="primary")
+        clear_btn = gr.Button("Clear")
+
+    send_btn.click(chatbot, [input_box, chatbot_ui], [chatbot_ui, input_box])
+    clear_btn.click(lambda: ("", []), [], [chatbot_ui, input_box])
+
+if __name__ == "__main__":
+    demo.launch()
+This chatbot application includes:
+- **Modern Interface**: Clean chat UI with chatbot component
+- **Interactive Controls**: Send and clear buttons
+- **State Management**: Maintains conversation history
+- **User-Friendly**: Clear labels and placeholder text
+- **Attribution**: "Built with anycoder" link as requested
+
+The chatbot currently echoes user messages. You can easily extend the `chatbot` function to integrate with any LLM API or language model for more sophisticated responses.

requirements.txt

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+gradio
+requests
+Pillow
+numpy
+pandas
+matplotlib
+plotly