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Update app.py
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app.py
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@@ -88,9 +88,23 @@ def generate_preds_field(desc_field, num_beams_field, num_returned_seqs_field):
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demo = gr.Blocks()
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with demo:
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gr.Markdown("<h1><center>RecipeGen: Automated TAPs Generation Tool</center></h1>")
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gr.Markdown("
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gr.Markdown("<h3>
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gr.Markdown("""
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1. Select the generation granularity (i.e., Channel, Function, or Field)
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2. Describe your intended functionality
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demo = gr.Blocks()
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with demo:
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gr.Markdown("<h1><center>RecipeGen: Automated Trigger Action Programs (TAPs) Generation Tool</center></h1>")
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# gr.Markdown("This demo allows you to generate TAPs using functionality description described in English. You can learn the working detail of our tool from our paper")
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gr.Markdown("<h3>What is TAP?</h3>")
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gr.Markdown("""
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TAPs or Trigger Action Programs are an event-driven rules used to automate smart devices and/or internet services. TAPs are written in the form of "IF <trigger> then execute <action>,
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where <trigger> and <action> refer to API calls. TAPs has been used in various use cases, ranging from home monitoring system to business workflow automation.
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""")
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gr.Markdown("<h3>Why generating TAPs can be challenging?</h3>")
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gr.Markdown("""
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Generating TAP is challenging mainly because of the large search space of the API calls that can be used as the trigger and action.
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""")
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gr.Markdown("<h3>RecipeGen</h3?>")
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gr.Markdown("""
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RecipeGen is a deep learning-based tool that can assist end-users to generate TAPs using natural language description. End-users can describe the functionality of the intended TAP, then RecipeGen
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will generate the candidate TAPs based those descriptions.
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""")
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gr.Markdown("<h3>Instructions</h3>")
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gr.Markdown("""
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1. Select the generation granularity (i.e., Channel, Function, or Field)
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2. Describe your intended functionality
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