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/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()