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import os
import argparse
# from typing import Literal
import gradio as gr # type: ignore
# from sotopia_space.chat import chat_introduction, chat_tab, get_sotopia_profiles
from sotopia_space import benchmark
from ui_constants import CITATION_TEXT, BANNER
# OPENAI_KEY_FILE="./openai_api.key"
# if os.path.exists(OPENAI_KEY_FILE):
# with open(OPENAI_KEY_FILE, "r") as f:
# os.environ["OPENAI_API_KEY"] = f.read().strip()
# with open("./sotopia_space/_header.md", "r") as f:
# HEADER_MD = f.read()
def navigation_bar():
with gr.Column(scale=2):
toggle_dark = gr.Button(value="Toggle Dark")
toggle_dark.click(
None,
js="""
() => {
if (document.body.classList.contains('dark')) {
document.body.classList.remove('dark');
document.querySelector('gradio-app').style.backgroundColor = 'var(--color-background-primary-light)';
} else {
document.body.classList.add('dark');
document.querySelector('gradio-app').style.backgroundColor = 'var(--color-background-primary-dark)';
}
}
""",
)
with gr.Blocks(
css="""#chat_container {height: 820px; width: 1000px; margin-left: auto; margin-right: auto;}
#chatbot {height: 600px; overflow: auto;}
#create_container {height: 750px; margin-left: 0px; margin-right: 0px;}
#tokenizer_renderer span {white-space: pre-wrap}
""",
theme="gradio/monochrome",
) as demo:
# with gr.Row():
# navigation_bar()
# gr.Image(
# "images/banner.jpg", elem_id="banner-image", show_label=False
# )
# gr.Markdown(HEADER_MD, elem_classes="markdown-text")
with gr.Tabs(elem_classes="tab-buttons") as tabs:
with gr.TabItem("🏅 Leaderboard", elem_id="benchmark-tab-table", id=0):
benchmark.benchmark_table()
# with gr.TabItem("💬 Chat", elem_id="chat-tab-interface", id=1):
# with gr.Row():
# chat_introduction()
# with gr.Row():
# chat_tab()
with gr.Row():
with gr.Accordion("📙 Citation", open=False, elem_classes="accordion-label"):
gr.Textbox(
value=CITATION_TEXT,
lines=7,
label="Copy the BibTeX snippet to cite this source",
elem_id="citation-button",
show_copy_button=True)
# def start_demo():
# demo = main()
# if DEPLOYED:
# demo.queue(api_open=False).launch(show_api=False)
# else:
# demo.queue()
# demo.launch(share=False, server_name="0.0.0.0")
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--result_file", help="Path to results table", default="data_dir\\bartscore_100_results.jsonl")
#benchmark.original_df = pd.read_json(args.result_file, lines=True)
# get_sotopia_profiles()
# prepare_model(DEFAULT_MODEL_SELECTION)
demo.launch() |