import logging import os import gradio as gr # type: ignore[import] from src.content import ( INTRODUCTION_TEXT, INTRODUCTION_TITLE, LEADERBOARD_TEXT, LEADERBOARD_TITLE, SUBMISSION_TEXT_FILES, SUBMISSION_TEXT_INTRO, SUBMISSION_TEXT_METADATA, SUBMISSION_TEXT_SUBMIT, SUBMISSION_TEXT_TASK, SUBMISSION_TITLE, ) from src.get_results_for_task import get_results_for_task from src.leaderboard_formatting import get_types_per_task from src.submission_uploader import SubmissionUploader from src.tasks_content import ( TASKS_DESCRIPTIONS, TASKS_PRETTY, TASKS_PRETTY_REVERSE, get_submission_text_files_for_task, ) logging.basicConfig( level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s", handlers=[logging.StreamHandler()], ) submission_uploader = SubmissionUploader( dataset_id=os.environ["DATASET_ID"], private_dataset_id=os.environ["PRIVATE_DATASET_ID"] ) def get_leaderboard_for_task(task_pretty: str) -> gr.components.Dataframe: return gr.components.Dataframe( value=get_results_for_task(task_pretty), interactive=False, datatype=get_types_per_task(TASKS_PRETTY_REVERSE[task_pretty]), ) def get_leaderboard_for_completion_task(dataset_name: str | None): df = get_results_for_task(TASKS_PRETTY['project_code_completion']) code_completion_dataset_names = df['Dataset'].unique() if dataset_name is None: dataset_name = code_completion_dataset_names[0] filtered_df = df[df['Dataset']==dataset_name] return gr.components.Dataframe( value=filtered_df, interactive=False, datatype=get_types_per_task('project_code_completion'), ) with gr.Blocks() as demo: # intro gr.HTML(INTRODUCTION_TITLE) gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text") # leaderboard gr.HTML(LEADERBOARD_TITLE) gr.Markdown(LEADERBOARD_TEXT, elem_classes="markdown-text") with gr.Tabs(): for task_pretty in TASKS_PRETTY_REVERSE: with gr.TabItem(task_pretty): with gr.Row(): gr.Markdown(TASKS_DESCRIPTIONS[TASKS_PRETTY_REVERSE[task_pretty]]) if task_pretty == TASKS_PRETTY['project_code_completion']: leaderboard_table = get_leaderboard_for_completion_task(dataset_name=None) code_completion_dataset_names = get_results_for_task(TASKS_PRETTY['project_code_completion'])['Dataset'].unique().tolist() else: leaderboard_table = get_leaderboard_for_task(task_pretty) task_input = gr.Text(value=task_pretty, visible=False) if task_pretty == TASKS_PRETTY['project_code_completion']: dataset_dropdown = gr.Dropdown(choices=code_completion_dataset_names, label="Select the Dataset") dataset_dropdown.change( fn=get_leaderboard_for_completion_task, inputs=dataset_dropdown, outputs=leaderboard_table ) refresh_button = gr.Button("🔄 Refresh", variant="secondary") refresh_button.click( fn=get_leaderboard_for_completion_task, inputs=dataset_dropdown, outputs=leaderboard_table, ) else: refresh_button = gr.Button("🔄 Refresh", variant="secondary") refresh_button.click( fn=get_leaderboard_for_task, inputs=task_input, outputs=leaderboard_table, ) # submission gr.HTML(SUBMISSION_TITLE) gr.Markdown(SUBMISSION_TEXT_INTRO, elem_classes="markdown-text") with gr.Accordion("🚀 Submit new results", open=False): gr.Markdown(SUBMISSION_TEXT_TASK, elem_classes="markdown-text") task_selection = gr.Radio(TASKS_PRETTY_REVERSE.keys(), label="Task") gr.Markdown(SUBMISSION_TEXT_METADATA, elem_classes="markdown-text") with gr.Row(): with gr.Column(): model_folder_textbox = gr.Textbox( label="Model Folder", placeholder="How to call a folder related to this submission in our results dataset (should be unique).", ) model_name_textbox = gr.Textbox( label="Model Name", placeholder="How to display model's name on the leaderboard.", ) model_url_textbox = gr.Textbox( label="Model URL", placeholder="Link to a model's page - will be clickable on a leaderboard (optional).", ) with gr.Column(): url_textbox = gr.Textbox( label="Relevant URLs", placeholder='URLs to relevant resources with additional details about your submission (optional). Use the following format: "[text1](link1), [text2](link2)".', ) model_availability_textbox = gr.Textbox( label="Availability", placeholder="Information about the model's availability and licensing.", ) context_size_textbox = gr.Textbox( label="Context Size", placeholder="Context size in tokens used for the submission (should be an integer).", ) with gr.Column(): submitted_by_textbox = gr.Textbox( label="Submitted By", placeholder="How to display on the leaderboard who submitted the model.", ) contact_textbox = gr.Textbox( label="Contact Information", placeholder="How Long Code Arena team can contact you (won't go to public dataset).", ) comment_textbox = gr.Textbox( label="Comment", placeholder="Any comments you have for Long Code Arena team (optional, won't go to public dataset).", ) gr.Markdown(SUBMISSION_TEXT_FILES, elem_classes="markdown-text") with gr.Row(): with gr.Column(variant="panel"): task_specific_instructions = gr.Markdown(get_submission_text_files_for_task(None)) task_selection.select(get_submission_text_files_for_task, [task_selection], task_specific_instructions) with gr.Column(): file_output = gr.File(file_count="multiple") gr.Markdown(SUBMISSION_TEXT_SUBMIT, elem_classes="markdown-text") submit_button = gr.Button("Submit") submission_result = gr.Markdown() submit_button.click( submission_uploader.upload_files, [ task_selection, model_folder_textbox, model_name_textbox, model_availability_textbox, model_url_textbox, url_textbox, context_size_textbox, submitted_by_textbox, contact_textbox, comment_textbox, file_output, ], submission_result, ) if __name__ == "__main__": demo.queue() demo.launch()