epochs-demos commited on
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a2b8dec
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1 Parent(s): b30f27a

Update app.py

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  1. app.py +29 -20
app.py CHANGED
@@ -127,14 +127,13 @@ def make_frontend(
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  """Creates a gradio.Interface frontend for text to image search function."""
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  allow_flagging = "never"
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-
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  # Build a customized browser interface to a Python function
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  frontend = gr.Interface(
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  fn=fn,
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  outputs=gr.Gallery(label="Relevant Items", show_labels=True, label_position="below"),
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  inputs=gr.inputs.Textbox(label="Item Description", placeholder="Enter item description here"),
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- title="Fashion Aggregator", # Title
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- thumbnail="./1001epochs.png", # Company logo image
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  description="Discover your perfect apparel effortlessly. Simply describe what you're looking for!",
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  cache_examples=False,
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  allow_flagging=allow_flagging,
@@ -144,31 +143,41 @@ def make_frontend(
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  # Apply custom CSS styles to enhance the design and layout
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  frontend.styles(
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  # Modify the styles according to your preferences
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- title="color: #333333; font-size: 28px; font-weight: bold; margin-bottom: 10px;",
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- description="color: #666666; font-size: 16px; margin-bottom: 20px;",
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- input="padding: 10px; border-radius: 5px; border: 1px solid #dddddd; font-size: 16px; width: 80%;",
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  output_gallery="margin-top: 20px;",
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  output_image="border-radius: 10px; box-shadow: 0px 2px 10px rgba(0, 0, 0, 0.1);",
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  flag_button="background-color: #ff5555;",
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  flag_options="color: #333333;",
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  )
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-
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- return frontend
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-
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- # # build a basic browser interface to a Python function
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  # frontend = gr.Interface(
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- # fn=fn, # which Python function are we interacting with?
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  # outputs=gr.Gallery(label="Relevant Items", show_labels=True, label_position="below"),
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- # # what input widgets does it need? we configure an image widget
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- # inputs=gr.components.Textbox(label="Item Description", placeholder="Enter item description here"),
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- # title="Fashion Aggregator", # what should we display at the top of the page?
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- # thumbnail="1001epochs.png", # what should we display when the link is shared, e.g. on social media?
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- # description="Discover your perfect apparel effortlessly. Simply describe what you're looking for!", # what should we display just above the interface?
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- # cache_examples=False, # should we cache those inputs for faster inference? slows down start
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- # allow_flagging=allow_flagging, # should we show users the option to "flag" outputs?
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- # flagging_options=["incorrect", "offensive", "other"], # what options do users have for feedback?
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  # )
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- # return frontend
 
 
 
 
 
 
 
 
 
 
 
 
 
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  class PredictorBackend:
 
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  """Creates a gradio.Interface frontend for text to image search function."""
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  allow_flagging = "never"
 
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  # Build a customized browser interface to a Python function
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  frontend = gr.Interface(
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  fn=fn,
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  outputs=gr.Gallery(label="Relevant Items", show_labels=True, label_position="below"),
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  inputs=gr.inputs.Textbox(label="Item Description", placeholder="Enter item description here"),
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+ title="Fashion Aggregator", # Update the title to a more descriptive name
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+ thumbnail="path/to/company-logo.png", # Replace with the path to your company logo image
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  description="Discover your perfect apparel effortlessly. Simply describe what you're looking for!",
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  cache_examples=False,
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  allow_flagging=allow_flagging,
 
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  # Apply custom CSS styles to enhance the design and layout
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  frontend.styles(
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  # Modify the styles according to your preferences
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+ title="color: #333333; font-size: 28px; font-weight: bold; margin-bottom: 10px; text-align: center;",
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+ description="color: #666666; font-size: 16px; margin-bottom: 20px; text-align: center;",
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+ input="padding: 10px; border-radius: 5px; border: 1px solid #dddddd; font-size: 16px; width: 80%; margin: 0 auto;",
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  output_gallery="margin-top: 20px;",
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  output_image="border-radius: 10px; box-shadow: 0px 2px 10px rgba(0, 0, 0, 0.1);",
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  flag_button="background-color: #ff5555;",
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  flag_options="color: #333333;",
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  )
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+
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+ # # Build a customized browser interface to a Python function
 
 
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  # frontend = gr.Interface(
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+ # fn=fn,
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  # outputs=gr.Gallery(label="Relevant Items", show_labels=True, label_position="below"),
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+ # inputs=gr.inputs.Textbox(label="Item Description", placeholder="Enter item description here"),
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+ # title="Fashion Aggregator", # Title
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+ # thumbnail="./1001epochs.png", # Company logo image
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+ # description="Discover your perfect apparel effortlessly. Simply describe what you're looking for!",
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+ # cache_examples=False,
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+ # allow_flagging=allow_flagging,
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+ # flagging_options=["incorrect", "offensive", "other"],
 
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  # )
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+
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+ # # Apply custom CSS styles to enhance the design and layout
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+ # frontend.styles(
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+ # # Modify the styles according to your preferences
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+ # title="color: #333333; font-size: 28px; font-weight: bold; margin-bottom: 10px;",
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+ # description="color: #666666; font-size: 16px; margin-bottom: 20px;",
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+ # input="padding: 10px; border-radius: 5px; border: 1px solid #dddddd; font-size: 16px; width: 80%;",
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+ # output_gallery="margin-top: 20px;",
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+ # output_image="border-radius: 10px; box-shadow: 0px 2px 10px rgba(0, 0, 0, 0.1);",
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+ # flag_button="background-color: #ff5555;",
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+ # flag_options="color: #333333;",
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+ # )
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+
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+ return frontend
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  class PredictorBackend: