Spaces:
Sleeping
Sleeping
only fetching from the API once at load
Browse files
app.py
CHANGED
@@ -30,10 +30,10 @@ def obtain_source_target_datasets() -> (
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filtered_source_dataset = source_dataset.filter_by(response_status=["pending"])
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# Obtain a list of users from the private workspace
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#target_dataset = rg.FeedbackDataset.from_argilla(
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# os.getenv("RESULTS_DATASET"), workspace=os.getenv("RESULTS_WORKSPACE")
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#)
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target_dataset = source_dataset.filter_by(response_status=["submitted"])
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return filtered_source_dataset, target_dataset
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@@ -64,18 +64,21 @@ def get_user_annotations_dictionary(
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return output
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def donut_chart() -> alt.Chart:
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# Load your data
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annotated_records = len(results)
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pending_records = int(os.getenv("TARGET_RECORDS")) - annotated_records
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# Prepare data for the donut chart
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source = pd.DataFrame(
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base = alt.Chart(source).encode(
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theta=alt.Theta("values:Q", stack=True),
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@@ -93,6 +96,7 @@ def donut_chart() -> alt.Chart:
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return chart
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def kpi_chart_remaining() -> alt.Chart:
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"""
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This function returns a KPI chart with the total amount of annotators.
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@@ -100,8 +104,7 @@ def kpi_chart_remaining() -> alt.Chart:
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An altair chart with the KPI chart.
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"""
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pending_records = int(os.getenv("TARGET_RECORDS")) - len(results)
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# Assuming you have a DataFrame with user data, create a sample DataFrame
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data = pd.DataFrame({"Category": ["Total remaining"], "Value": [pending_records]})
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@@ -115,6 +118,7 @@ def kpi_chart_remaining() -> alt.Chart:
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return chart
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def kpi_chart_submitted() -> alt.Chart:
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"""
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This function returns a KPI chart with the total amount of annotators.
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@@ -122,9 +126,6 @@ def kpi_chart_submitted() -> alt.Chart:
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An altair chart with the KPI chart.
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"""
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# Obtain the total amount of annotators
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_, target_dataset = obtain_source_target_datasets()
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total = len(target_dataset)
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# Assuming you have a DataFrame with user data, create a sample DataFrame
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@@ -150,12 +151,12 @@ def kpi_chart() -> alt.Chart:
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"""
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# Obtain the total amount of annotators
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_, target_dataset = obtain_source_target_datasets()
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user_ids_annotations = get_user_annotations_dictionary(target_dataset)
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total_annotators = len(user_ids_annotations)
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# Assuming you have a DataFrame with user data, create a sample DataFrame
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data = pd.DataFrame(
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# Create Altair chart
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chart = (
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@@ -195,15 +196,17 @@ def main() -> None:
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extra_headers={"Authorization": f"Bearer {os.getenv('HF_TOKEN')}"},
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)
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source_dataset, target_dataset = obtain_source_target_datasets()
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user_ids_annotations = get_user_annotations_dictionary(target_dataset)
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top5_dataframe = obtain_top_5_users(user_ids_annotations)
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annotated = len(target_dataset)
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remaining = int(os.getenv("TARGET_RECORDS")) - annotated
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percentage_completed = round(
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with gr.Blocks() as demo:
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gr.Markdown(
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@@ -236,7 +239,6 @@ def main() -> None:
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outputs=[plot],
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)
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plot2 = gr.Plot(label="Plot")
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demo.load(
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donut_chart,
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outputs=[plot2],
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)
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gr.Markdown(
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"""
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## πΎ Contributors Hall of Fame
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filtered_source_dataset = source_dataset.filter_by(response_status=["pending"])
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# Obtain a list of users from the private workspace
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# target_dataset = rg.FeedbackDataset.from_argilla(
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# os.getenv("RESULTS_DATASET"), workspace=os.getenv("RESULTS_WORKSPACE")
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# )
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target_dataset = source_dataset.filter_by(response_status=["submitted"])
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return filtered_source_dataset, target_dataset
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return output
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def donut_chart() -> alt.Chart:
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# Load your data
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annotated_records = len(target_dataset)
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pending_records = int(os.getenv("TARGET_RECORDS")) - annotated_records
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# Prepare data for the donut chart
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source = pd.DataFrame(
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{
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"values": [annotated_records, pending_records],
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"category": ["Completed", "Remaining"],
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"colors": ["#4CAF50", "#757575"], # Green for Completed, Grey for Remaining
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}
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)
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base = alt.Chart(source).encode(
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theta=alt.Theta("values:Q", stack=True),
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return chart
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def kpi_chart_remaining() -> alt.Chart:
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"""
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This function returns a KPI chart with the total amount of annotators.
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An altair chart with the KPI chart.
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"""
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pending_records = int(os.getenv("TARGET_RECORDS")) - len(target_dataset)
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# Assuming you have a DataFrame with user data, create a sample DataFrame
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data = pd.DataFrame({"Category": ["Total remaining"], "Value": [pending_records]})
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return chart
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def kpi_chart_submitted() -> alt.Chart:
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"""
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This function returns a KPI chart with the total amount of annotators.
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An altair chart with the KPI chart.
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"""
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total = len(target_dataset)
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# Assuming you have a DataFrame with user data, create a sample DataFrame
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"""
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# Obtain the total amount of annotators
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total_annotators = len(user_ids_annotations)
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# Assuming you have a DataFrame with user data, create a sample DataFrame
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data = pd.DataFrame(
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{"Category": ["Total Contributors"], "Value": [total_annotators]}
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)
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# Create Altair chart
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chart = (
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extra_headers={"Authorization": f"Bearer {os.getenv('HF_TOKEN')}"},
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)
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global source_dataset, target_dataset, user_ids_annotations
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source_dataset, target_dataset = obtain_source_target_datasets()
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user_ids_annotations = get_user_annotations_dictionary(target_dataset)
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top5_dataframe = obtain_top_5_users(user_ids_annotations)
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annotated = len(target_dataset)
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remaining = int(os.getenv("TARGET_RECORDS")) - annotated
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percentage_completed = round(
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(annotated / int(os.getenv("TARGET_RECORDS"))) * 100, 1
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)
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with gr.Blocks() as demo:
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gr.Markdown(
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outputs=[plot],
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)
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plot2 = gr.Plot(label="Plot")
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demo.load(
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donut_chart,
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outputs=[plot2],
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)
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gr.Markdown(
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"""
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## πΎ Contributors Hall of Fame
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