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import gradio as gr |
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from generate import generate_response |
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DESCRIPTION = """ |
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# 🤖 EvoChat |
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A lightweight, self-trained Transformer chatbot based on EvoDecoder architecture. |
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Model trained on 1K dialogue samples. Evolves from your feedback (v1). |
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""" |
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def chat_fn(message, history): |
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response = generate_response(message) |
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history.append((message, response)) |
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return "", history |
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with gr.Blocks() as demo: |
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gr.Markdown(DESCRIPTION) |
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chatbot = gr.Chatbot() |
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with gr.Row(): |
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msg = gr.Textbox(label="Your message") |
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submit = gr.Button("Send") |
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clear = gr.Button("Clear chat") |
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history = gr.State([]) |
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submit.click(chat_fn, [msg, history], [msg, chatbot]) |
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clear.click(lambda: [], None, chatbot) |
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demo.launch() |
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