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Build error
Build error
fix try sample button and description
Browse files
app.py
CHANGED
@@ -365,40 +365,43 @@ def generate_channel(input_desc, n_beams_discover):
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###
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demo = gr.Blocks()
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with demo:
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gr.Markdown("<h1><center>RecipeGen
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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 event-driven rules used to automate smart devices and/or internet services.
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satisfied then execute an
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system to business workflow automation.
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""")
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gr.Markdown("<h3>What is RecipeGen
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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.
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will generate the TAP candidates based on the given description.
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""")
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gr.Markdown("<h3>Working Mode</h3>")
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gr.Markdown("""
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- Interactive: generate a TAP using step-by-step wizard
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- One
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-
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""")
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with gr.Tabs():
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with gr.TabItem("Interactive"):
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gr.Markdown("<h3><center>Instructions for Interactive Mode</center></h3>")
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gr.Markdown("""1. There are 5 generation steps, i.e., generating trigger channel, trigger function, action channel, action function, and the final TAP.
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2. **[STEP 1]** Describe the functionality in the `Functionality Description` text box. Click `Generate Trigger Channel` button. The channel candidates and their descriptions will show up in the `Trigger Channel Results` table.
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3. **[STEP 2]** Select a trigger channel from the dropdown `Select the Trigger Channel`. Click `Generate Trigger Function` button. The function candidates and their descriptions will show up in the `Trigger Function Results` table.
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4. **[STEP 3]** Select a trigger function from the dropdown `Select the Trigger Function`. Click `Generate Action Channel` button. The channel candidates and their descriptions will show up in the `Action Channel Results` table.
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5. **[STEP 4]** Select an action channel from the dropdown `Select the Action Channel`. Click `Generate Action Function` button. The function candidates and their descriptions will show up in the `Action Function Results` table.
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6. **[STEP 5]** Select an action function
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gr.Markdown(""" NOTE: You can control how many sequences are returned by tuning the `Beam Width` slider.
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""")
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with gr.Box():
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with gr.Column():
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-
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button_use_example = gr.Button("Try this sample")
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with gr.Box():
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@@ -455,6 +458,7 @@ with demo:
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table_final = gr.Dataframe(headers=["Trigger","Action"], row_count=1)
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button_use_example.click(return_same, inputs=[dropdown_example], outputs=[textbox_input])
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button_generate_tc.click(generate_preds_tc, inputs=[textbox_input, n_beams_interactive], outputs=[table_tc])
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table_tc.change(fn=update_dropdown_trig_ch, inputs=[table_tc], outputs=[dropdown_tc])
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@@ -472,18 +476,20 @@ with demo:
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table_af.change(fn=update_dropdown_action_func, inputs=[table_af], outputs=[dropdown_af])
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dropdown_af.change(fn=set_final_result, inputs=[textbox_selected_tf, table_af, dropdown_af], outputs=[table_final])
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with gr.TabItem("One
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gr.Markdown("<h3><center>Instructions for One
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gr.Markdown("""
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1. Describe the functionality in the `Functionality Description` text box
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2. Click `Generate TAP` button. The TAP candidates will show up in the `TAP Results` table. The table consists of 4 columns: Trigger, Action, Trigger Description, and Action Description. You can scroll the table
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""")
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gr.Markdown(""" NOTE: You can control how many sequences are returned by tuning the `Beam Width` slider.
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with gr.Box():
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with gr.Column():
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gr.Markdown("You can try
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dropdown_example = gr.Dropdown(type ="value",
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button_use_example = gr.Button("Try this sample")
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with gr.Box():
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@@ -496,21 +502,24 @@ with demo:
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gr.Markdown("<h4><center>TAP Results</center></h4>")
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table_oneshot = gr.Dataframe(headers=["Trigger", "Action", "Trigger Description", "Action Description"], row_count=1)
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button_use_example.click(return_same, inputs=[dropdown_example], outputs=[textbox_input])
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button_generate_oneshot.click(generate_oneshot, inputs=[textbox_input, n_beams_oneshot], outputs=[table_oneshot])
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with gr.TabItem("
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gr.Markdown("<h3><center>Instructions for
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gr.Markdown("""
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1. Describe the functionality in the `Functionality Description` text box.
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2. Click `Discover
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""")
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gr.Markdown(""" NOTE: You can control how many sequences are returned by tuning the `Beam Width` slider.
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with gr.Box():
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with gr.Column():
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gr.Markdown("You can try
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dropdown_example = gr.Dropdown(type ="value",
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button_use_example = gr.Button("Try this sample")
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with gr.Box():
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@@ -520,14 +529,15 @@ with demo:
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button_discover_function = gr.Button("Discover Functions!")
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gr.Markdown("<br>")
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gr.Markdown("<h4><center>Relevant Trigger Channels</center></h4>")
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table_discover_tc = gr.Dataframe(headers=["Trigger", "Available Functions", "Trigger Description"], row_count=1)
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gr.Markdown("<br>")
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gr.Markdown("<h4><center>Relevant Action Channels</center></h4>")
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table_discover_ac = gr.Dataframe(headers=["Action", "Available Functions", "Action Description"], row_count=1)
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button_use_example.click(return_same, inputs=[dropdown_example], outputs=[textbox_input])
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button_discover_function.click(generate_channel, inputs=[textbox_input, n_beams_discover], outputs=[table_discover_tc, table_discover_ac])
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demo.launch()
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###
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demo = gr.Blocks()
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with demo:
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gr.Markdown("<h1><center><em>RecipeGen++</em> | an 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 event-driven rules used to automate smart devices and/or internet services.
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TAPs are written in the form of "IF a {trigger} is satisfied then execute an {action}, where the {trigger} and the {action} correspond to API calls.
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TAPs have been used in various use cases, ranging from the home monitoring system to business workflow automation.
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""")
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gr.Markdown("<h3>What is <em>RecipeGen++</em>?</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.
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End-users can describe the functionality of the intended TAP, then *RecipeGen++* will generate the TAP candidates based on the given description.
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""")
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gr.Markdown("<h3>Working Mode</h3>")
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gr.Markdown("""
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- Interactive: generate a TAP using a step-by-step wizard
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- One-Click: generate a TAP using the one-click button
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- Functionality Discovery: discover relevant functionalities from channels with similar functionalities
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""")
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with gr.Tabs():
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with gr.TabItem("Interactive"):
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gr.Markdown("<h3><center>Instructions for Interactive Mode</center></h3>")
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gr.Markdown("""1. There are 5 generation steps, i.e., generating trigger channel, trigger function, action channel, action function, and the final TAP.
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2. **[STEP 1]** Describe the functionality in the `Functionality Description` text box. Click the `Generate Trigger Channel` button. The channel candidates and their descriptions will show up in the `Trigger Channel Results` table.
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3. **[STEP 2]** Select a trigger channel from the dropdown `Select the Trigger Channel`. Click the `Generate Trigger Function` button. The function candidates and their descriptions will show up in the `Trigger Function Results` table.
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4. **[STEP 3]** Select a trigger function from the dropdown `Select the Trigger Function`. Click the `Generate Action Channel` button. The channel candidates and their descriptions will show up in the `Action Channel Results` table.
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5. **[STEP 4]** Select an action channel from the dropdown `Select the Action Channel`. Click the `Generate Action Function` button. The function candidates and their descriptions will show up in the `Action Function Results` table.
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6. **[STEP 5]** Select an action function from the `Select the Action Function` to generate the final TAP.""")
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gr.Markdown(""" NOTE: You can control how many sequences are returned by tuning the `Beam Width` slider. A larger value will cause a longer generation time.
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""")
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with gr.Box():
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with gr.Column():
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gr.Markdown("You can describe your own functionality directly in the `Functionality Description` text box or try a description sample from the dropdown below:")
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dropdown_example = gr.Dropdown(type ="value",
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choices = ["Log to my spreadsheet if motion is detected in the living room","When I am not home, let me know when any motion is detected in my house", "Turn on my Philips lamp every sunset","Update my picture in Twitter when I change my profile picture in Facebook","Save in notes when I create a new bookmark"],
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label = "Select a sample functionality descriptions")
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button_use_example = gr.Button("Try this sample")
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with gr.Box():
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table_final = gr.Dataframe(headers=["Trigger","Action"], row_count=1)
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button_use_example.click(return_same, inputs=[dropdown_example], outputs=[textbox_input])
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button_use_example.click(generate_preds_tc, inputs=[dropdown_example, n_beams_interactive], outputs=[table_tc])
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button_generate_tc.click(generate_preds_tc, inputs=[textbox_input, n_beams_interactive], outputs=[table_tc])
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table_tc.change(fn=update_dropdown_trig_ch, inputs=[table_tc], outputs=[dropdown_tc])
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table_af.change(fn=update_dropdown_action_func, inputs=[table_af], outputs=[dropdown_af])
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dropdown_af.change(fn=set_final_result, inputs=[textbox_selected_tf, table_af, dropdown_af], outputs=[table_final])
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with gr.TabItem("One-Click"):
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gr.Markdown("<h3><center>Instructions for One-Click Mode</center></h3>")
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gr.Markdown("""
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1. Describe the functionality by yourself in the `Functionality Description` text box
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2. Click `Generate TAP` button. The TAP candidates will show up in the `TAP Results` table. The table consists of 4 columns: Trigger, Action, Trigger Description, and Action Description. You can scroll the table horizontally.
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""")
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gr.Markdown(""" NOTE: You can control how many sequences are returned by tuning the `Beam Width` slider. A larger value will cause a longer generation time.""")
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with gr.Box():
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with gr.Column():
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gr.Markdown("You can describe your own functionality directly in the `Functionality Description` text box or try a description sample from the dropdown below:")
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dropdown_example = gr.Dropdown(type ="value",
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choices = ["Log to my spreadsheet if motion is detected in the living room","When I am not home, let me know when any motion is detected in my house", "Turn on my Philips lamp every sunset","Update my picture in Twitter when I change my profile picture in Facebook","Save in notes when I create a new bookmark"],
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label = "Select a sample functionality description")
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button_use_example = gr.Button("Try this sample")
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with gr.Box():
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gr.Markdown("<h4><center>TAP Results</center></h4>")
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table_oneshot = gr.Dataframe(headers=["Trigger", "Action", "Trigger Description", "Action Description"], row_count=1)
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button_use_example.click(return_same, inputs=[dropdown_example], outputs=[textbox_input])
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button_use_example.click(generate_oneshot, inputs=[dropdown_example, n_beams_oneshot], outputs=[table_oneshot])
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button_generate_oneshot.click(generate_oneshot, inputs=[textbox_input, n_beams_oneshot], outputs=[table_oneshot])
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with gr.TabItem("Functionality Discovery"):
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gr.Markdown("<h3><center>Instructions for Functionality Discovery Mode</center></h3>")
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gr.Markdown("""
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1. Describe the functionality in the `Functionality Description` text box.
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2. Click `Discover Functionalities` button. The table containing relevant trigger and action channels will show up. Each channel is accompanied by a list of available functionalities. You can scroll the table horizontally.
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""")
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gr.Markdown(""" NOTE: You can control how many sequences are returned by tuning the `Beam Width` slider. A larger value will cause a longer generation time.""")
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with gr.Box():
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with gr.Column():
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gr.Markdown("You can describe your own functionality directly in the `Functionality Description` text box or try a description sample from the dropdown below:")
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dropdown_example = gr.Dropdown(type ="value",
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choices = ["Log to my spreadsheet if motion is detected in the living room","When I am not home, let me know when any motion is detected in my house", "Turn on my Philips lamp every sunset","Update my picture in Twitter when I change my profile picture in Facebook","Save in notes when I create a new bookmark"],
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label = "Select a sample functionality description")
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button_use_example = gr.Button("Try this sample")
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with gr.Box():
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button_discover_function = gr.Button("Discover Functions!")
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gr.Markdown("<br>")
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gr.Markdown("<h4><center>Relevant Trigger Channels and Functionalities</center></h4>")
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table_discover_tc = gr.Dataframe(headers=["Trigger", "Available Functions", "Trigger Description"], row_count=1)
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gr.Markdown("<br>")
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gr.Markdown("<h4><center>Relevant Action Channels and Functionalities</center></h4>")
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table_discover_ac = gr.Dataframe(headers=["Action", "Available Functions", "Action Description"], row_count=1)
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button_use_example.click(return_same, inputs=[dropdown_example], outputs=[textbox_input])
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button_use_example.click(generate_channel, inputs=[dropdown_example, n_beams_discover], outputs=[table_discover_tc, table_discover_ac])
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button_discover_function.click(generate_channel, inputs=[textbox_input, n_beams_discover], outputs=[table_discover_tc, table_discover_ac])
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demo.launch()
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