Update app.py
Browse files
app.py
CHANGED
@@ -193,23 +193,49 @@ def SwarmyTime(data: List[Dict]) -> Dict:
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aggregated["unique_authors"] = len(aggregated["unique_authors"])
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return aggregated
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with gr.Blocks() as demo:
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gr.Markdown("
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with gr.Row():
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with gr.Row():
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download_area = gr.HTML("", label="Download Link")
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metadata_output = gr.Textbox(label="Metadata", lines=10)
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aggregated_output = gr.JSON(label="Aggregated Content")
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search_type_state = gr.State("")
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current_results = gr.State([])
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@@ -219,12 +245,9 @@ with gr.Blocks() as demo:
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data = df.to_dict('records')
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aggregated = SwarmyTime(data)
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html_results = display_results(df)
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show_download = len(data) > 0
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return [
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html_results, # results_html
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show_download, # download_repo_button visible
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"", # download_status
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"", # download_area
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aggregated, # aggregated_output
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search_type, # search_type_state
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@@ -233,23 +256,21 @@ with gr.Blocks() as demo:
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async def handle_readme_download(data):
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if not data:
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return ["No results to download", ""]
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download_link, status = await download_all_readmes(data)
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return [status, download_link]
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def handle_repo_download(data, search_type):
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if not data:
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return ["No results to download", ""]
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download_link, status = create_repo_zip(data, search_type)
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return [status, download_link]
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search_button.click(
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search_and_aggregate,
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inputs=[search_query, search_type],
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outputs=[
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results_html,
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download_readme_button,
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download_repo_button,
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download_status,
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download_area,
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aggregated_output,
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aggregated["unique_authors"] = len(aggregated["unique_authors"])
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return aggregated
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown("""
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# Search the Hugging Face Hub
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Search and download models, datasets, and spaces from Hugging Face.
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""")
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with gr.Row():
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with gr.Column(scale=3):
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search_query = gr.Textbox(
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label="Search Query",
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value="awacke1",
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placeholder="Enter search term..."
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)
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with gr.Column(scale=2):
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search_type = gr.Radio(
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["Models", "Datasets", "Spaces"],
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label="Search Type",
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value="Models",
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container=True
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)
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with gr.Column(scale=1):
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search_button = gr.Button("🔍 Search", variant="primary", scale=1)
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with gr.Row(variant="panel"):
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with gr.Column(scale=1):
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gr.Markdown("### Download Options")
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with gr.Row():
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download_readme_button = gr.Button(
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"📚 Download READMEs",
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variant="secondary",
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)
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download_repo_button = gr.Button(
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"📦 Download Repositories",
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variant="secondary",
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)
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download_status = gr.Markdown("Status: Ready to download", label="Status")
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download_area = gr.HTML("", label="Download Link")
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with gr.Row():
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with gr.Column(scale=2):
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results_html = gr.HTML(label="Search Results")
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with gr.Column(scale=1):
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aggregated_output = gr.JSON(label="Search Statistics")
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search_type_state = gr.State("")
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current_results = gr.State([])
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data = df.to_dict('records')
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aggregated = SwarmyTime(data)
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html_results = display_results(df)
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return [
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html_results, # results_html
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"Status: Ready to download", # download_status
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"", # download_area
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aggregated, # aggregated_output
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search_type, # search_type_state
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async def handle_readme_download(data):
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if not data:
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return ["Status: No results to download", ""]
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download_link, status = await download_all_readmes(data)
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return [f"Status: {status}", download_link]
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def handle_repo_download(data, search_type):
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if not data:
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return ["Status: No results to download", ""]
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download_link, status = create_repo_zip(data, search_type)
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return [f"Status: {status}", download_link]
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search_button.click(
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search_and_aggregate,
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inputs=[search_query, search_type],
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outputs=[
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results_html,
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download_status,
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download_area,
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aggregated_output,
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