aurora

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import gradio as gr
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from typing import TYPE_CHECKING, Dict, Optional, Tuple
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if TYPE_CHECKING:
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    from gradio.blocks import Block
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    from gradio.components import Component
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    from llmtuner.webui.engine import Engine
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def create_chat_box(
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    engine: "Engine",
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    visible: Optional[bool] = False
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) -> Tuple["Block", "Component", "Component", Dict[str, "Component"]]:
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    with gr.Box(visible=visible) as chat_box:
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        chatbot = gr.Chatbot()
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        history = gr.State([])
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        with gr.Row():
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            with gr.Column(scale=4):
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                system = gr.Textbox(show_label=False)
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                query = gr.Textbox(show_label=False, lines=8)
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                submit_btn = gr.Button(variant="primary")
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            with gr.Column(scale=1):
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                clear_btn = gr.Button()
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                gen_kwargs = engine.chatter.generating_args
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                max_new_tokens = gr.Slider(10, 2048, value=gen_kwargs.max_new_tokens, step=1)
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                top_p = gr.Slider(0.01, 1, value=gen_kwargs.top_p, step=0.01)
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                temperature = gr.Slider(0.01, 1.5, value=gen_kwargs.temperature, step=0.01)
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    submit_btn.click(
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        engine.chatter.predict,
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        [chatbot, query, history, system, max_new_tokens, top_p, temperature],
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        [chatbot, history],
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        show_progress=True
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    ).then(
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        lambda: gr.update(value=""), outputs=[query]
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    )
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    clear_btn.click(lambda: ([], []), outputs=[chatbot, history], show_progress=True)
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    return chat_box, chatbot, history, dict(
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        system=system,
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        query=query,
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        submit_btn=submit_btn,
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        clear_btn=clear_btn,
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        max_new_tokens=max_new_tokens,
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        top_p=top_p,
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        temperature=temperature
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    )
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