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import glob
import os
import logging
import pandas as pd
import gradio as gr
from gradio.themes.utils.sizes import text_md
from content import (HEADER_MARKDOWN, LEADERBOARD_TAB_TITLE_MARKDOWN, SUBMISSION_TAB_TITLE_MARKDOWN,
)
import json
from datetime import datetime
from pathlib import Path
from uuid import uuid4
import time
import gradio as gr
from huggingface_hub import HfApi, snapshot_download
JSON_DATASET_DIR = Path("../json_dataset")
JSON_DATASET_DIR.mkdir(parents=True, exist_ok=True)
JSON_DATASET_PATH = JSON_DATASET_DIR / f"train-{uuid4()}.json"
api = HfApi()
ORG= "CZLC"
REPO = f"{ORG}/LLM_benchmark_data"
def greet(name: str) -> str:
return "Hello " + name + "!"
DATASET_VERSIONS = ['dev-set-1', 'dev-set-2']
HF_TOKEN = os.environ.get("HF_TOKEN")
class LeaderboardServer:
def __init__(self, server_address):
self.server_address = server_address
self.repo_type = "dataset"
self.local_leaderboard = snapshot_download(self.server_address,repo_type=self.repo_type, token=HF_TOKEN)
def on_submit(self):
self.local_leaderboard = snapshot_download(self.server_address,repo_type=self.repo_type, token=HF_TOKEN)
def get_leaderboard(self):
results = []
for submission in glob.glob(os.path.join(self.local_leaderboard, "../data") + "/*.json"):
data = json.load(open(submission))
submission_id = data["metadata"]["model_description"]
local_results = {group: data["results"][group]['acc'] for group in data['results']}
local_results["submission_id"] = submission_id
results.append(local_results)
dataframe = pd.DataFrame.from_records(results)
return dataframe
def save_json(self,file) -> None:
filename = os.path.basename(file)
api.upload_file(
path_or_fileobj=file,
path_in_repo=f"data/{filename}",
repo_id=self.server_address,
repo_type=self.repo_type,
token=HF_TOKEN,
)
leaderboard_server = LeaderboardServer(REPO)
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
LEADERBOARD_TYPES = ['LLM',]
MAX_SUBMISSIONS_PER_24H = 2
# DATASET_VERSIONS = ['dev-set-1', 'dev-set-2']
# CHALLENGE_NAME = 'NOTSOFAR1'
if __name__ == '__main__':
with (gr.Blocks(theme=gr.themes.Soft(text_size=text_md), css="footer {visibility: hidden}") as main):
app_state = gr.State({})
# with gr.Row():
# greet_name = gr.Textbox(label="Name")
# greet_output = gr.Textbox(label="Greetings")
# greet_btn = gr.Button("Greet")
# greet_btn.click(fn=greet, inputs=greet_name, outputs=greet_output).success(
# fn=save_json,
# inputs=[greet_name, greet_output],
# outputs=None,
# )
with gr.Row():
with gr.Row():
gr.Markdown(HEADER_MARKDOWN)
with gr.Row():
# Leaderboards Tab #
####################
def populate_leaderboard(leaderboard_type, dataset_version):
gr.Info('Loading leaderboard...')
time.sleep(1)
leaderboard_df = leaderboard_server.get_leaderboard()
# leaderboard_df = lb_server.get_leaderboard(
# submission_type=leaderboard_type, dataset_version=dataset_version)
# if leaderboard_df.empty:
return leaderboard_df
# return leaderboard_df
def create_leaderboard_tab(tab_name: str, idx: int, dataset_version_dropdown: gr.Dropdown):
# dataset_version = dataset_version_dropdown.value
print(f'Creating tab for {tab_name}, idx={idx}, dataset_version={dataset_version_dropdown}')
with gr.Tab(id=tab_name, label=tab_name) as leaderboard_tab:
leaderboard_table = gr.DataFrame(populate_leaderboard(tab_name, None)) if idx == 0 \
else gr.DataFrame(pd.DataFrame(columns=['No submissions yet']))
leaderboard_tab.select(fn=populate_leaderboard,
inputs=[gr.Text(tab_name, visible=False)],
outputs=[leaderboard_table])
return leaderboard_table
def on_dropdown_change():
first_tab_name = LEADERBOARD_TYPES[0]
leaderboard_server.on_submit()
return gr.Tabs(selected=first_tab_name), populate_leaderboard(first_tab_name, None)
with gr.Tab('Leaderboards') as leaderboards_tab:
with gr.Row():
gr.Markdown(LEADERBOARD_TAB_TITLE_MARKDOWN)
# with gr.Row():
# with gr.Column():
# dataset_version_drop = gr.Dropdown(choices=DATASET_VERSIONS, multiselect=False,
# value=DATASET_VERSIONS[-1], label="Dataset",
# interactive=True)
# with gr.Column():
# gr.Markdown('') # Empty column for spacing
# with gr.Column():
# gr.Markdown('') # Empty column for spacing
# with gr.Column():
# gr.Markdown('') # Empty column for spacing
with gr.Row():
with gr.Tabs() as leaderboards_tabs:
leaderboard_tables_list = []
for leaderboard_idx, leaderboard_type in enumerate(LEADERBOARD_TYPES):
l_tab = create_leaderboard_tab(leaderboard_type, leaderboard_idx, None)
leaderboard_tables_list.append(l_tab)
# dataset_version_drop.select(fn=on_dropdown_change, inputs=[dataset_version_drop],
# outputs=[leaderboards_tabs, leaderboard_tables_list[0]])
# Submission Tab #
##################
with gr.Tab('Submission'):
with gr.Column():
def on_submit_pressed():
return gr.update(value='Processing submission...', interactive=False)
def validate_submission_inputs(team_name, submission_zip, submission_type, token):
if not team_name or not submission_zip or not submission_type:
raise ValueError('Please fill in all fields')
if not os.path.exists(submission_zip):
raise ValueError('File does not exist')
# if not submission_zip.endswith('.zip'):
# raise ValueError('File must be a zip')
# if not token:
# raise ValueError('Please insert a valid Hugging Face token')
def process_submission(team_name, submission, submission_type, description,
app_state, request: gr.Request):
logging.info(f'{team_name}: new submission for track: {submission_type}')
try:
token = app_state.get('hf_token')
validate_submission_inputs(team_name, submission, submission_type, token)
except ValueError as err:
gr.Warning(str(err))
return
# metadata = {'challenge_name': CHALLENGE_NAME,
# "dataset_version": DATASET_VERSIONS[-1],
# 'team_name': team_name,
# 'submission_type': submission_type,
# 'description': description,
# 'token': token,
# 'file_name': os.path.basename(submission_zip),
# 'file_size_mb': os.path.getsize(submission_zip) / 1024 / 1024,
# 'ip': request.client.host}
leaderboard_server.save_json(submission)
try:
gr.Info('Processing submission...')
# response = lb_server.add_submission(token=token, file_path=submission_zip, metadata=metadata)
# if 'error' in response:
# gr.Warning(f'Failed to process submission - {response["error"]}')
# else:
gr.Info('Done processing submission')
except Exception as e:
gr.Warning(f'Submission failed to upload - {e}')
def on_submit_done():
on_dropdown_change()
leaderboard_server.on_submit()
# leaderboard_tab.children[0] = gr.DataFrame(populate_leaderboard(None, None))
# leaderboard_tab.render()
return gr.update(value='Submit', interactive=True)
gr.Markdown(SUBMISSION_TAB_TITLE_MARKDOWN)
submission_team_name_tb = gr.Textbox(label='Team Name')
submission_file_path = gr.File(label='Upload your results', type='filepath')
submission_type_radio = gr.Radio(label='Submission Track', choices=LEADERBOARD_TYPES)
with gr.Row():
hf_token_tb = gr.Textbox(label='Token', type='password')
submissions_24h_txt = gr.Textbox(label='Submissions 24h', value='')
description_tb = gr.Textbox(label='Description', type='text')
submission_btn = gr.Button(value='Submit', interactive=True)
gr.Markdown('### * Please make sure you are using NOTSOFAR dev-set-2 for your submissions')
submission_btn.click(
fn=on_submit_pressed,
outputs=[submission_btn]
).then(
fn=process_submission,
inputs=[submission_team_name_tb, submission_file_path,
submission_type_radio, description_tb, app_state]
).then(
fn=on_submit_done,
outputs=[submission_btn]
).then(
fn=on_dropdown_change,
outputs=[leaderboards_tabs, leaderboard_tables_list[0]]
)
# # My Submissions Tab #
# ######################
# with gr.Tab('My Submissions') as my_submissions_tab:
# def on_my_submissions_tab_select(app_state):
# hf_token = app_state.get('hf_token')
# if not hf_token:
# return pd.DataFrame(columns=['Please insert your Hugging Face token'])
# # submissions = lb_server.get_submissions_by_hf_token(hf_token=hf_token)
# # if submissions.empty:
# # submissions = pd.DataFrame(columns=['No submissions yet'])
# # return submissions
#
# gr.Markdown(MY_SUBMISSIONS_TAB_TITLE_MARKDOWN)
# my_submissions_table = gr.DataFrame()
#
# my_submissions_tab.select(fn=on_my_submissions_tab_select, inputs=[app_state],
# outputs=[my_submissions_table])
# my_submissions_token_tb = gr.Textbox(label='Token', type='password')
def on_token_insert(hf_token, app_state):
gr.Info(f'Verifying token...')
submission_count = None
# if hf_token:
# submission_count = lb_server.get_submission_count_last_24_hours(hf_token=hf_token)
if submission_count is None:
# Invalid token
app_state['hf_token'] = None
submissions_24h_str = ''
team_submissions_df = pd.DataFrame(columns=['Invalid Token'])
gr.Warning('Invalid token')
# else:
# app_state['hf_token'] = hf_token
# submissions_24h_str = f'{submission_count}/{MAX_SUBMISSIONS_PER_24H}'
# team_submissions_df = lb_server.get_submissions_by_hf_token(hf_token=hf_token)
# if team_submissions_df.empty:
# team_submissions_df = pd.DataFrame(columns=['No submissions yet'])
# gr.Info('Token verified!')
return app_state, team_submissions_df, submissions_24h_str
hf_token_tb.change(fn=on_token_insert, inputs=[hf_token_tb, app_state],
outputs=[app_state, submissions_24h_txt])
# my_submissions_token_tb.change(fn=on_token_insert, inputs=[my_submissions_token_tb, app_state],
# outputs=[app_state, my_submissions_table, submissions_24h_txt])
main.launch()
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