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Browse files- app.py +58 -0
- requirements.txt +3 -0
app.py
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import gradio as gr
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import pandas
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import PIL
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# Dummy function for Workflow A
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def workflow_a(image, text):
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# Here you might process the image/text in a specific way.
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return "Workflow A executed!"
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# Dummy function for Workflow B
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def workflow_b(image, text):
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# Here you might process the image/text in a different way.
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return "Workflow B executed!"
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# Main function triggered by the Start button.
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# It uses an if statement to decide which workflow to call.
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def main(image, text):
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# Example condition: if the text (after stripping whitespace) equals "a" (case-insensitive), call workflow_a.
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if text.strip().lower() == "a":
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result_text = workflow_a(image, text)
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else:
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result_text = workflow_b(image, text)
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# Forward the input image to both image outputs.
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return image, image,
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# Build the Gradio interface using Blocks for a custom layout.
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with gr.Blocks() as demo:
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gr.Markdown("## Gradio Demo: Workflow Selector")
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# Input components in a row.
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with gr.Row():
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image_input = gr.Image(label="Input Image")
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text_input = gr.Textbox(label="Input Text", placeholder='Type "a" for workflow A or anything else for workflow B')
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# Start button to trigger the main function.
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start_button = gr.Button("Start")
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gr.Markdown("### Outputs")
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# Output images in a row.
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with gr.Row():
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output_image1 = gr.Image(label="Output Image 1")
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output_image2 = gr.Image(label="Output Image 2")
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output_text = gr.Textbox(label="Output Text")
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# Connect the Start button to the main function.
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start_button.click(
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fn=main,
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inputs=[image_input, text_input],
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outputs=[output_image1, output_image2, output_text]
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)
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# Launch the Gradio app.
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demo.launch(share=True)
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requirements.txt
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@@ -0,0 +1,3 @@
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gradio
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pandas
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PIL
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