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Update app.py
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app.py
CHANGED
@@ -75,10 +75,9 @@ def predict_chat(message: str, history: list):
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yield "Error: Model or tokenizer failed to load. Please check the Space logs for details."
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return
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messages.append({"role": "assistant", "content": ai_msg})
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messages.append({"role": "user", "content": message})
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generated_text = ""
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@@ -131,18 +130,16 @@ def predict_chat(message: str, history: list):
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if __name__ == "__main__":
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load_model_for_zerocpu()
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"Hello! I'm an AI assistant. I'm currently running in a CPU-only "
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"environment for efficient demonstration. How can I help you today?"
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# Use gr.ChatInterface directly without gr.Blocks wrapper for simplicity
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# This often works better when ChatInterface is the sole component
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demo = gr.ChatInterface(
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fn=predict_chat,
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# Define the chatbot here, with type='messages'
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chatbot=gr.Chatbot(height=500, type='messages',
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value=[[None, initial_chatbot_message]]), # Set initial message directly here
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textbox=gr.Textbox(
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placeholder="Ask me a question...",
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container=False,
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@@ -162,9 +159,7 @@ if __name__ == "__main__":
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["What's the best way to stay motivated?"],
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],
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cache_examples=False,
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# but if this causes issues, you might need to revert to a gr.ClearButton() below
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clear_btn="Clear Chat" # Re-added clear_btn as it seems to be supported again in latest Gradio versions
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)
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demo.launch()
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yield "Error: Model or tokenizer failed to load. Please check the Space logs for details."
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return
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# history is already in the 'messages' format if type='messages' is set on chatbot
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# It contains dictionaries with 'role' and 'content'
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messages = [{"role": "system", "content": "You are a friendly chatbot."}] + history
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messages.append({"role": "user", "content": message})
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generated_text = ""
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if __name__ == "__main__":
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load_model_for_zerocpu()
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# Initial message for the chatbot in the 'messages' format
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initial_messages = [{"role": "assistant", "content":
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"Hello! I'm an AI assistant. I'm currently running in a CPU-only "
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"environment for efficient demonstration. How can I help you today?"
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}]
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demo = gr.ChatInterface(
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fn=predict_chat,
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# Define the chatbot here, with type='messages' and initial value in the correct format
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chatbot=gr.Chatbot(height=500, type='messages', value=initial_messages),
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textbox=gr.Textbox(
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placeholder="Ask me a question...",
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container=False,
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["What's the best way to stay motivated?"],
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],
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cache_examples=False,
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clear_btn="Clear Chat"
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)
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demo.launch()
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