Spaces:
Sleeping
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•
02be4dc
1
Parent(s):
7c1b028
Update app.py
Browse files
app.py
CHANGED
@@ -1,19 +1,218 @@
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import os
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import
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import gradio as gr
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import argilla as rg
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import
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import plotly.colors as colors
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client = rg.Argilla(
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api_url=os.getenv("ARGILLA_API_URL"),
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)
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def
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def get_progress(dataset: rg.Dataset) -> dict:
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dataset_progress = dataset.progress(with_users_distribution=True)
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"total": total,
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"annotated": completed,
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"progress": progress,
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"users": {
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username: user_progress["completed"].get("submitted")
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for username, user_progress in dataset_progress["users"].items()
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}
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}
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def create_gauge_chart(progress):
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fig = go.Figure(
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go.Indicator(
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@@ -135,17 +335,25 @@ def create_treemap(user_annotations, total_records):
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return fig
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dataset = fetch_data(os.getenv("DATASET_NAME"), os.getenv("WORKSPACE"))
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progress = get_progress(dataset)
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gauge_chart = create_gauge_chart(progress)
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treemap = create_treemap(progress["users"], progress["total"])
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leaderboard_df = pd.DataFrame(
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list(progress["users"].items()), columns=["User", "Annotations"]
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)
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leaderboard_df = leaderboard_df.sort_values(
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"Annotations", ascending=False
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).reset_index(drop=True)
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@@ -153,9 +361,20 @@ def update_dashboard():
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return gauge_chart, treemap, leaderboard_df
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with gr.Blocks() as demo:
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gr.Markdown("# Argilla Dataset Dashboard")
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with gr.Row():
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gauge_output = gr.Plot(label="Overall Progress")
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treemap_output = gr.Plot(label="User contributions")
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@@ -167,15 +386,17 @@ with gr.Blocks() as demo:
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demo.load(
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update_dashboard,
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inputs=
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outputs=[gauge_output, treemap_output, leaderboard_output],
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every=5,
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)
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-
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if __name__ == "__main__":
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demo.launch()
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# app dashboard from https://huggingface.co/spaces/davanstrien/argilla-progress/blob/main/app.py
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import os
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from typing import List
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import argilla as rg
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import gradio as gr
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import pandas as pd
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import plotly.colors as colors
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import plotly.graph_objects as go
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client = rg.Argilla(
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api_url=os.getenv("ARGILLA_API_URL"),
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api_key=os.getenv("ARGILLA_API_KEY"),
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)
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def get_progress(dataset: rg.Dataset) -> dict:
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dataset_progress = dataset.progress(with_users_distribution=True)
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total, completed = dataset_progress["total"], dataset_progress["completed"]
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progress = (completed / total) * 100 if total > 0 else 0
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return {
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"total": total,
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"annotated": completed,
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"progress": progress,
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"users": {
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username: user_progress["completed"].get("submitted")
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for username, user_progress in dataset_progress["users"].items()
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}
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}
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def create_gauge_chart(progress):
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fig = go.Figure(
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go.Indicator(
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mode="gauge+number+delta",
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value=progress["progress"],
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title={"text": "Dataset Annotation Progress", "font": {"size": 24}},
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delta={"reference": 100, "increasing": {"color": "RebeccaPurple"}},
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number={"font": {"size": 40}, "valueformat": ".1f", "suffix": "%"},
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gauge={
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"axis": {"range": [None, 100], "tickwidth": 1, "tickcolor": "darkblue"},
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"bar": {"color": "deepskyblue"},
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"bgcolor": "white",
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"borderwidth": 2,
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"bordercolor": "gray",
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"steps": [
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{"range": [0, progress["progress"]], "color": "royalblue"},
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{"range": [progress["progress"], 100], "color": "lightgray"},
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],
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"threshold": {
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"line": {"color": "red", "width": 4},
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"thickness": 0.75,
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"value": 100,
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},
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},
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)
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)
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fig.update_layout(
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annotations=[
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dict(
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text=(
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f"Total records: {progress['total']}<br>"
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f"Annotated: {progress['annotated']} ({progress['progress']:.1f}%)<br>"
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f"Remaining: {progress['total'] - progress['annotated']} ({100 - progress['progress']:.1f}%)"
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),
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# x=0.5,
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# y=-0.2,
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showarrow=False,
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xref="paper",
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yref="paper",
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font=dict(size=16),
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)
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],
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)
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fig.add_annotation(
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text=(
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f"Current Progress: {progress['progress']:.1f}% complete<br>"
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f"({progress['annotated']} out of {progress['total']} records annotated)"
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),
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xref="paper",
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yref="paper",
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x=0.5,
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y=1.1,
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showarrow=False,
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font=dict(size=18),
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align="center",
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)
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return fig
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def create_treemap(user_annotations, total_records):
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sorted_users = sorted(user_annotations.items(), key=lambda x: x[1], reverse=True)
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color_scale = colors.qualitative.Pastel + colors.qualitative.Set3
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labels, parents, values, text, user_colors = [], [], [], [], []
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for i, (user, contribution) in enumerate(sorted_users):
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percentage = (contribution / total_records) * 100
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labels.append(user)
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parents.append("Annotations")
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values.append(contribution)
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text.append(f"{contribution} annotations<br>{percentage:.2f}%")
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user_colors.append(color_scale[i % len(color_scale)])
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labels.append("Annotations")
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parents.append("")
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values.append(total_records)
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text.append(f"Total: {total_records} annotations")
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user_colors.append("#FFFFFF")
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fig = go.Figure(
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go.Treemap(
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labels=labels,
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parents=parents,
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values=values,
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text=text,
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textinfo="label+text",
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hoverinfo="label+text+value",
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marker=dict(colors=user_colors, line=dict(width=2)),
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)
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)
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fig.update_layout(
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title_text="User contributions to the total end dataset",
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height=500,
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margin=dict(l=10, r=10, t=50, b=10),
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paper_bgcolor="#F0F0F0", # Light gray background
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plot_bgcolor="#F0F0F0", # Light gray background
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)
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return fig
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def get_datasets(client: rg.Argilla) -> List[rg.Dataset]:
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return client.datasets.list()
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datasets = get_datasets(client)
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def update_dashboard(dataset_idx: int| None = None):
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if dataset_idx is None:
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return [None, None, None]
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dataset = datasets[dataset_idx]
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progress = get_progress(dataset)
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gauge_chart = create_gauge_chart(progress)
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treemap = create_treemap(progress["users"], progress["total"])
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leaderboard_df = pd.DataFrame(
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list(progress["users"].items()), columns=["User", "Annotations"]
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)
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leaderboard_df = leaderboard_df.sort_values(
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"Annotations", ascending=False
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).reset_index(drop=True)
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return gauge_chart, treemap, leaderboard_df
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with gr.Blocks() as demo:
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gr.Markdown("# Argilla Dataset Dashboard")
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datasets_dropdown = gr.Dropdown(label="Select your dataset")
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datasets_dropdown.choices = [(dataset.name, idx) for idx, dataset in enumerate(datasets)]
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def set_selected_dataset(dataset_idx) -> None:
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global selected_dataset
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dataset = datasets[dataset_idx]
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selected_dataset = dataset
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with gr.Row():
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gauge_output = gr.Plot(label="Overall Progress")
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treemap_output = gr.Plot(label="User contributions")
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with gr.Row():
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leaderboard_output = gr.Dataframe(
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label="Leaderboard", headers=["User", "Annotations"]
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)
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demo.load(
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update_dashboard,
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inputs=[datasets_dropdown],
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outputs=[gauge_output, treemap_output, leaderboard_output],
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every=5,
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)
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datasets_dropdown.change(
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update_dashboard,
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inputs=[datasets_dropdown],
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outputs=[gauge_output, treemap_output, leaderboard_output],
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)
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if __name__ == "__main__":
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demo.launch()
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# app dashboard from https://huggingface.co/spaces/davanstrien/argilla-progress/blob/main/app.py
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import os
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from typing import List
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import argilla as rg
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import gradio as gr
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import pandas as pd
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import plotly.colors as colors
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import plotly.graph_objects as go
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client = rg.Argilla(
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api_url=os.getenv("ARGILLA_API_URL"),
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api_key=os.getenv("ARGILLA_API_KEY"),
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)
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def get_progress(dataset: rg.Dataset) -> dict:
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dataset_progress = dataset.progress(with_users_distribution=True)
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"total": total,
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"annotated": completed,
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"progress": progress,
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"users": {
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username: user_progress["completed"].get("submitted")
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for username, user_progress in dataset_progress["users"].items()
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}
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}
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def create_gauge_chart(progress):
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fig = go.Figure(
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go.Indicator(
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return fig
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def get_datasets(client: rg.Argilla) -> List[rg.Dataset]:
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return client.datasets.list()
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datasets = get_datasets(client)
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def update_dashboard(dataset_idx: int| None = None):
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if dataset_idx is None:
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return [None, None, None]
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dataset = datasets[dataset_idx]
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progress = get_progress(dataset)
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gauge_chart = create_gauge_chart(progress)
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treemap = create_treemap(progress["users"], progress["total"])
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leaderboard_df = pd.DataFrame(
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list(progress["users"].items()), columns=["User", "Annotations"]
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)
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leaderboard_df = leaderboard_df.sort_values(
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"Annotations", ascending=False
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).reset_index(drop=True)
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return gauge_chart, treemap, leaderboard_df
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with gr.Blocks() as demo:
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gr.Markdown("# Argilla Dataset Dashboard")
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datasets_dropdown = gr.Dropdown(label="Select your dataset")
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datasets_dropdown.choices = [(dataset.name, idx) for idx, dataset in enumerate(datasets)]
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def set_selected_dataset(dataset_idx) -> None:
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global selected_dataset
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dataset = datasets[dataset_idx]
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selected_dataset = dataset
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with gr.Row():
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gauge_output = gr.Plot(label="Overall Progress")
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treemap_output = gr.Plot(label="User contributions")
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demo.load(
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update_dashboard,
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inputs=[datasets_dropdown],
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outputs=[gauge_output, treemap_output, leaderboard_output],
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every=5,
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)
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datasets_dropdown.change(
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update_dashboard,
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inputs=[datasets_dropdown],
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outputs=[gauge_output, treemap_output, leaderboard_output],
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)
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if __name__ == "__main__":
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demo.launch()
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