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import gradio as gr
import pandas as pd
import requests
from pathlib import Path
from datetime import datetime, timezone
import time
import logging
logging.basicConfig(level=logging.INFO)
BACKEND_URL = "http://127.0.0.1:8000"
LAST_UPDATED = "Dec 4th 2024"
def load_static_leaderboard():
# read fake_queue/leaderboard.json
return pd.read_json(Path("fake_queue/leaderboard.json"))
def load_leaderboard_data():
try:
response = requests.get(f"{BACKEND_URL}/leaderboard")
response.raise_for_status()
return pd.DataFrame(response.json())
except requests.RequestException as e:
logging.error(f"Error loading leaderboard: {e}")
return pd.DataFrame()
def format_leaderboard_df(df):
if df.empty:
return df
display_df = pd.DataFrame({
"Model": df["model"],
"Average PER β¬οΈ": df["average_per"].apply(lambda x: f"{x:.4f}"),
"Average PWED β¬οΈ": df["average_pwed"].apply(lambda x: f"{x:.4f}"),
"GitHub": df["github_url"].apply(lambda x: f'<a href="{x}" target="_blank">Repository</a>' if x else "N/A"),
"Submission Date": pd.to_datetime(df["submission_date"]).dt.strftime("%Y-%m-%d")
})
return display_df.sort_values("Average PER β¬οΈ")
# def submit_evaluation(model_name, submission_name, github_url):
# if not model_name or not submission_name:
# return "β οΈ Please provide both model name and submission name."
# request_data = {
# "transcription_model": model_name,
# "subset": "test",
# "submission_name": submission_name,
# "github_url": github_url if github_url else None
# }
# try:
# response = requests.post(f"{BACKEND_URL}/evaluate", json=request_data)
# response.raise_for_status()
# task_id = response.json()["task_id"]
# return f"β
Evaluation submitted successfully! Task ID: {task_id}"
# except requests.RequestException as e:
# return f"β Error: {str(e)}"
# def check_task_status(task_id):
# if not task_id:
# return "Please enter a task ID"
# try:
# response = requests.get(f"{BACKEND_URL}/tasks/{task_id}")
# response.raise_for_status()
# return response.json()
# except requests.RequestException as e:
# return f"Error checking status: {str(e)}"
def create_html_table(df):
return df.to_html(escape=False, index=False, classes="styled-table")
with gr.Blocks(css="""
.styled-table {
width: 100%;
border-collapse: collapse;
margin: 25px 0;
font-size: 0.9em;
font-family: sans-serif;
box-shadow: 0 0 20px rgba(0, 0, 0, 0.15);
}
.styled-table thead tr {
background-color: #009879;
color: #ffffff;
text-align: left;
}
.styled-table th,
.styled-table td {
padding: 12px 15px;
}
.styled-table tbody tr {
border-bottom: 1px solid #dddddd;
}
""") as demo:
gr.Markdown("# π― Phonemic Transcription Model Evaluation Leaderboard")
with gr.Tabs():
with gr.TabItem("π Leaderboard"):
leaderboard_html = gr.HTML(create_html_table(format_leaderboard_df(load_static_leaderboard())))
refresh_btn = gr.Button("π Refresh")
refresh_btn.click(
lambda: create_html_table(format_leaderboard_df(load_static_leaderboard())),
outputs=leaderboard_html
)
with gr.TabItem("π Submit Model"):
model_name = gr.Textbox(label="Model Name", placeholder="facebook/wav2vec2-lv-60-espeak-cv-ft")
submission_name = gr.Textbox(label="Submission Name", placeholder="My Model v1.0")
github_url = gr.Textbox(label="GitHub URL (optional)", placeholder="https://github.com/username/repo")
submit_btn = gr.Button("Submit")
result = gr.Textbox(label="Submission Status")
# submit_btn.click(
# submit_evaluation,
# inputs=[model_name, submission_name, github_url],
# outputs=result
# )
with gr.TabItem("π Task Status"):
task_id = gr.Textbox(label="Task ID")
status_btn = gr.Button("Check Status")
status_output = gr.JSON(label="Status")
# status_btn.click(
# check_task_status,
# inputs=task_id,
# outputs=status_output
# )
if __name__ == "__main__":
demo.launch() |