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import gradio as gr
import plotly.graph_objects as go
from huggingface_hub import hf_hub_download
from datasets import load_dataset
import pathlib
import json
import pandas as pd
from evaluation import load_boundary, load_boundaries
from constellaration import forward_model, initial_guess
from constellaration.boozer import boozer
from constellaration.utils import (
file_exporter,
visualization,
visualization_utils,
)
organization = 'proxima-fusion'
results_repo = f'{organization}/constellaration-bench-results'
def read_result_from_hub(filename):
local_path = hf_hub_download(
repo_id=results_repo,
repo_type="dataset",
filename=filename,
)
return local_path
def make_visual(boundary):
vis = visualization.plot_surface(boundary)
return vis
def gradio_interface() -> gr.Blocks:
with gr.Blocks() as demo:
gr.Markdown("""
# Welcome to the ConStellaration Boundary Explorer!
### Here, you can visualize submissions to the ConStellaration Leaderboard, generate and visualize new random boundaries, or upload and visualize your own!
""")
ds = load_dataset(results_repo, split='train')
full_df = pd.DataFrame(ds)
filenames = full_df['result_filename'].to_list()
with gr.Row():
with gr.Column():
dropdown = gr.Dropdown(choices=filenames, label="Choose a leaderboard entry", value=filenames[0])
rld_btn = gr.Button(value="Reload")
with gr.Column():
plot = gr.Plot()
def get_boundary_vis(selected_file):
row = full_df[full_df['result_filename'] == selected_file].iloc[0]
if row['problem_type'] == 'mhd_stable':
raise gr.Error("Sorry this isn't implemented for mhd_stable submissions yet!")
else:
boundary = load_boundary(row['boundary_json'])
vis = make_visual(boundary)
return vis
demo.load(get_boundary_vis, dropdown, plot)
rld_btn.click(get_boundary_vis, dropdown, plot)
return demo
if __name__ == "__main__":
gradio_interface().launch()
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