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