import os import datetime import pandas as pd import gradio as gr import argilla as rg import plotly.graph_objects as go import plotly.colors as colors client = rg.Argilla( api_url=os.getenv("ARGILLA_API_URL"), api_key=os.getenv("ARGILLA_API_KEY") ) def fetch_data(dataset_name: str, workspace: str): return client.datasets(dataset_name, workspace=workspace) def get_progress(dataset: rg.Dataset) -> dict: dataset_progress = dataset.progress(with_users_distribution=True) total, completed = dataset_progress["total"], dataset_progress["completed"] progress = (completed / total) * 100 if total > 0 else 0 return { "total": total, "annotated": completed, "progress": progress, "users": dataset_progress["users"] } def create_gauge_chart(progress): fig = go.Figure( go.Indicator( mode="gauge+number+delta", value=progress["progress"], title={"text": "Dataset Annotation Progress", "font": {"size": 24}}, delta={"reference": 100, "increasing": {"color": "RebeccaPurple"}}, number={"font": {"size": 40}, "valueformat": ".1f", "suffix": "%"}, gauge={ "axis": {"range": [None, 100], "tickwidth": 1, "tickcolor": "darkblue"}, "bar": {"color": "deepskyblue"}, "bgcolor": "white", "borderwidth": 2, "bordercolor": "gray", "steps": [ {"range": [0, progress["progress"]], "color": "royalblue"}, {"range": [progress["progress"], 100], "color": "lightgray"}, ], "threshold": { "line": {"color": "red", "width": 4}, "thickness": 0.75, "value": 100, }, }, ) ) fig.update_layout( annotations=[ dict( text=( f"Total records: {progress['total']}
" f"Annotated: {progress['annotated']} ({progress['progress']:.1f}%)
" f"Remaining: {progress['total'] - progress['annotated']} ({100 - progress['progress']:.1f}%)" ), # x=0.5, # y=-0.2, showarrow=False, xref="paper", yref="paper", font=dict(size=16), ) ], ) fig.add_annotation( text=( f"Current Progress: {progress['progress']:.1f}% complete
" f"({progress['annotated']} out of {progress['total']} records annotated)" ), xref="paper", yref="paper", x=0.5, y=1.1, showarrow=False, font=dict(size=18), align="center", ) return fig def create_treemap(user_annotations, total_records): sorted_users = sorted(user_annotations.items(), key=lambda x: x[1], reverse=True) color_scale = colors.qualitative.Pastel + colors.qualitative.Set3 labels, parents, values, text, user_colors = [], [], [], [], [] for i, (user, contribution) in enumerate(sorted_users): percentage = (contribution / total_records) * 100 labels.append(user) parents.append("Annotations") values.append(contribution) text.append(f"{contribution} annotations
{percentage:.2f}%") user_colors.append(color_scale[i % len(color_scale)]) labels.append("Annotations") parents.append("") values.append(total_records) text.append(f"Total: {total_records} annotations") user_colors.append("#FFFFFF") fig = go.Figure( go.Treemap( labels=labels, parents=parents, values=values, text=text, textinfo="label+text", hoverinfo="label+text+value", marker=dict(colors=user_colors, line=dict(width=2)), ) ) fig.update_layout( title_text="User contributions to the total end dataset", height=500, margin=dict(l=10, r=10, t=50, b=10), paper_bgcolor="#F0F0F0", # Light gray background plot_bgcolor="#F0F0F0", # Light gray background ) return fig def update_dashboard(): dataset = fetch_data(os.getenv("DATASET_NAME"), os.getenv("WORKSPACE")) progress = get_progress(dataset) gauge_chart = create_gauge_chart(progress) treemap = create_treemap(progress["users"], progress["total"]) leaderboard_df = pd.DataFrame( list(progress["users"].items()), columns=["User", "Annotations"] ) leaderboard_df = leaderboard_df.sort_values( "Annotations", ascending=False ).reset_index(drop=True) return gauge_chart, treemap, leaderboard_df with gr.Blocks() as demo: gr.Markdown("# Argilla Dataset Dashboard") with gr.Row(): gauge_output = gr.Plot(label="Overall Progress") treemap_output = gr.Plot(label="User contributions") with gr.Row(): leaderboard_output = gr.Dataframe( label="Leaderboard", headers=["User", "Annotations"] ) demo.load( update_dashboard, inputs=None, outputs=[gauge_output, treemap_output, leaderboard_output], ) gr.Button("Refresh").click( update_dashboard, inputs=None, outputs=[gauge_output, treemap_output, leaderboard_output], ) if __name__ == "__main__": demo.launch()