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autorestart
#4
by
ignacioct
- opened
app.py
CHANGED
@@ -8,6 +8,7 @@ import altair as alt
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import argilla as rg
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from argilla.feedback import FeedbackDataset
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from argilla.client.feedback.dataset.remote.dataset import RemoteFeedbackDataset
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import gradio as gr
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import pandas as pd
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@@ -17,6 +18,7 @@ It's designed as a template to recreate the dashboard for the prompt translation
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To create a new dashboard, you need several environment variables, that you can easily set in the HuggingFace Space that you are using to host the dashboard:
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- SOURCE_DATASET: The dataset id of the source dataset
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- SOURCE_WORKSPACE: The workspace id of the source dataset
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- TARGET_RECORDS: The number of records that you have as a target to annotate. We usually set this to 500.
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@@ -25,15 +27,30 @@ To create a new dashboard, you need several environment variables, that you can
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"""
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# Translation of legends and titles
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ANNOTATED =
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NUMBER_ANNOTATED =
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PENDING =
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NUMBER_ANNOTATORS = "Number of annotators"
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NAME =
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NUMBER_ANNOTATIONS =
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CATEGORY = 'Category'
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def obtain_source_target_datasets() -> (
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Tuple[
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@@ -186,9 +203,7 @@ def kpi_chart_total_annotators() -> alt.Chart:
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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": [NUMBER_ANNOTATORS], "Value": [total_annotators]}
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)
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# Create Altair chart
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chart = (
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@@ -201,14 +216,14 @@ def kpi_chart_total_annotators() -> alt.Chart:
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return chart
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def render_hub_user_link(hub_id:str) -> str:
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"""
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This function returns a link to the user's profile on Hugging Face.
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Args:
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hub_id: The user's id on Hugging Face.
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Returns:
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A string with the link to the user's profile on Hugging Face.
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"""
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link = f"https://huggingface.co/{hub_id}"
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@@ -255,7 +270,7 @@ def fetch_data() -> None:
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print(f"Data fetched: {datetime.datetime.now()}")
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def get_top(N
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"""
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This function returns the top N users with the most annotations.
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@@ -287,7 +302,7 @@ def main() -> None:
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}
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"""
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with gr.Blocks(css=css) as demo:
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gr.Markdown(
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"""
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# π [YOUR LANGUAGE] - Multilingual Prompt Evaluation Project
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with gr.Row():
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kpi_hall_plot = gr.Plot(label="Plot")
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demo.load(
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kpi_chart_total_annotators, inputs=[], outputs=[kpi_hall_plot]
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)
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top_df_plot = gr.Dataframe(
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headers=[NAME, NUMBER_ANNOTATIONS],
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)
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demo.load(get_top, None, [top_df_plot])
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# Launch the Gradio interface
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demo.launch()
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if __name__ == "__main__":
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main()
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import argilla as rg
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from argilla.feedback import FeedbackDataset
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from argilla.client.feedback.dataset.remote.dataset import RemoteFeedbackDataset
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from huggingface_hub import restart_space
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import gradio as gr
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import pandas as pd
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To create a new dashboard, you need several environment variables, that you can easily set in the HuggingFace Space that you are using to host the dashboard:
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- HF_TOKEN: Token with write access from your Hugging Face account: https://huggingface.co/settings/tokens
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- SOURCE_DATASET: The dataset id of the source dataset
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- SOURCE_WORKSPACE: The workspace id of the source dataset
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- TARGET_RECORDS: The number of records that you have as a target to annotate. We usually set this to 500.
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"""
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# Translation of legends and titles
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ANNOTATED = "Annotations"
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NUMBER_ANNOTATED = "Total Annotations"
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PENDING = "Pending"
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NUMBER_ANNOTATORS = "Number of annotators"
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NAME = "Username"
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NUMBER_ANNOTATIONS = "Number of annotations"
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CATEGORY = "Category"
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def restart() -> None:
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"""
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This function restarts the space where the dashboard is hosted.
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"""
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# Update Space name with your Space information
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gr.Info("Restarting space at " + str(datetime.datetime.now()))
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restart_space(
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"ignacioct/TryingRestartDashboard",
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token=os.getenv("HF_TOKEN"),
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# factory_reboot=True,
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)
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def obtain_source_target_datasets() -> (
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Tuple[
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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({"Category": [NUMBER_ANNOTATORS], "Value": [total_annotators]})
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# Create Altair chart
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chart = (
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return chart
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def render_hub_user_link(hub_id: str) -> str:
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"""
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This function returns a link to the user's profile on Hugging Face.
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Args:
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hub_id: The user's id on Hugging Face.
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Returns:
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A string with the link to the user's profile on Hugging Face.
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"""
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link = f"https://huggingface.co/{hub_id}"
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print(f"Data fetched: {datetime.datetime.now()}")
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def get_top(N=50) -> pd.DataFrame:
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"""
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This function returns the top N users with the most annotations.
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}
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"""
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with gr.Blocks(css=css, delete_cache=(300, 300)) as demo:
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gr.Markdown(
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"""
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# π [YOUR LANGUAGE] - Multilingual Prompt Evaluation Project
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with gr.Row():
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kpi_hall_plot = gr.Plot(label="Plot")
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demo.load(kpi_chart_total_annotators, inputs=[], outputs=[kpi_hall_plot])
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top_df_plot = gr.Dataframe(
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headers=[NAME, NUMBER_ANNOTATIONS],
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)
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demo.load(get_top, None, [top_df_plot])
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# Manage background refresh
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scheduler = BackgroundScheduler()
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_ = scheduler.add_job(restart, "interval", minutes=30)
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scheduler.start()
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# Launch the Gradio interface
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demo.launch()
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if __name__ == "__main__":
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main()
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