sotopia-space / app.py
Wonderplex
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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="bethecloud/storj_theme",
) 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("πŸ’¬ Chat", elem_id="chat-tab-interface", id=1):
with gr.Row():
chat_introduction()
with gr.Row():
chat_tab()
with gr.TabItem("πŸ… Leaderboard", elem_id="benchmark-tab-table", id=0):
benchmark.benchmark_table()
with gr.Row():
with gr.Accordion("πŸ“™ 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/models_vs_gpt35.jsonl")
#benchmark.original_df = pd.read_json(args.result_file, lines=True)
get_sotopia_profiles()
# prepare_model(DEFAULT_MODEL_SELECTION)
demo.launch()