Updated app with custom button

app.py

@@ -1,10 +1,10 @@
 # -*- coding: utf-8 -*-
-"""20221027_Generate_Beatles_with_Gradio_faster_version.ipynb
+"""20221027_Generate_Beatles_with_Gradio_faster_version (2).ipynb
 
 Automatically generated by Colaboratory.
 
 Original file is located at
-    https://colab.research.google.com/drive/1spCrOvhSvByMN8J-4iGZ9wk3I8U-9elU
+    https://colab.research.google.com/drive/1B2KVLt04uBMgr2ejW19FYaEgk9lnNS0E
 
 # Build a demo
 
@@ -30,13 +30,17 @@ import gradio as gr
 import re
 import torch
 from torch import autocast
-#from diffusers import StableDiffusionPipeline
 from PIL import Image
 import os
 
-image_input_styles = ["Random", "Beatles style", "Pencil sketch", "Oil painting", "Pop art", "Piet Mondriaan"]
+# Array with song cover art styles
+image_input_styles = ["Random", "The Beatles", "Pencil sketch", "Oil painting", "Pop art", "Piet Mondriaan"]
 
-# Function to get random image type for image input
+# Get image type for image input
+"""
+The default setting for the art style dropdown is "Random". The below function determines which style is chosen
+If set to "Random", copy the art style array and remove "Random" to prevent "Random" from being a chosen art style
+"""
 def get_image_input(title, given_input_style):
     if given_input_style == 'Random':
       image_input_styles_new = image_input_styles.copy()
@@ -45,7 +49,7 @@ def get_image_input(title, given_input_style):
       final_style = image_input_styles_new[random_choice]
     else:
       final_style = given_input_style
-    image_input = final_style + ' for ' + title
+    image_input = 'Cover for ' + title + ' in style of ' + final_style 
     return image_input, final_style
 
 # Available models for generate lyrics pipeline
@@ -56,17 +60,17 @@ checkpoint = 'wvangils/GPT-Medium-Beatles-Lyrics-finetuned-newlyrics'
 # Setup all the pipelines we need
 title_generator = pipeline('summarization', model='czearing/story-to-title')
 lyrics_generator = pipeline("text-generation", model=checkpoint)
-# Image generator: stable diffusion from an existing HuggingFace space
+# For the image generator we use stable diffusion from an existing HuggingFace space
 stable_diffusion = gr.Blocks.load(name="spaces/stabilityai/stable-diffusion")
 
 # Create 4 images for the given prompt and receive the first one
- # This function uses an existing HuggingFace space where the number of created images cannot be modified
+# This function uses an existing HuggingFace space where the number of created images cannot be modified
 def get_image(prompt):
     gallery_dir = stable_diffusion(prompt, fn_index=2)
     images = [os.path.join(gallery_dir, img) for img in os.listdir(gallery_dir)]
     return [images[0]]
 
-# Create function for lyrics generation
+# Lyrics generation
 def generate_beatles(input_prompt, temperature, top_p, given_input_style):
     # Create generator for different models
     generated_lyrics = lyrics_generator(input_prompt
@@ -92,18 +96,18 @@ def generate_beatles(input_prompt, temperature, top_p, given_input_style):
     # Create an image based on the generated title
     image_input, image_style = get_image_input(title, given_input_style)
 
-    # Generate the image, [PIL format](https://pillow.readthedocs.io/en/stable/)
+    # Generate the image
     image = get_image(image_input)
     return (title, generated_lyrics, image, image_style)
 
 # Create textboxes for input and output
 input_box = gr.Textbox(label="Write the start of a song here", placeholder="Write the start of a song here", value="Looking beyond the Broad Horizon", lines=2, max_lines=5)
-gen_lyrics = gr.Textbox(label="Lyrics by The Beatles and chosen language model", lines=15)
+gen_lyrics = gr.Textbox(label="Lyrics", lines=15)
 gen_title = gr.Textbox(label="Proposed songtitle", lines=1)
 gen_image = gr.Gallery(label="Proposed song cover").style(grid=1, height="auto")
 gen_image_style = gr.Textbox(label="Image style", lines=1)
 
-# Layout and text above the App
+# Layout and text around the app
 title='Beatles lyrics generator'
 description="<p style='text-align: center'>We've fine-tuned multiple language models on lyrics from The Beatles to generate Beatles-like text. Below are the results we obtained fine-tuning a GPT Neo model. After generation a title is generated using <a href='https://huggingface.co/czearing/story-to-title' target='_blank'>this model</a>. On top we use the generated title to suggest an album cover using <a href='https://huggingface.co/CompVis/stable-diffusion-v1-4' target='_blank'>Stable Diffusion 1.4</a>. Give it a try!</p>"
 article="""<p style='text-align: left'>These text generation models that output Beatles-like text were created by data scientists working for <a href='https://cmotions.nl/' target="_blank">Cmotions.</a>  
@@ -112,12 +116,20 @@ article="""<p style='text-align: left'>These text generation models that output
         The default output contains 100 tokens and has a repetition penalty of 1.0. 
          </p>"""
 css = """
-        button:lang(en-US) {
+        .gr-button-primary {
+          text-indent: -9999px;
+          line-height: 0;
         }  
+        .gr-button-primary:after {
+          content: "Beatlify!";
+          text-indent: 0;
+          display: block;
+          line-height: initial;
+        }
 """ 
 
 # Let users select their own temperature and top-p
-temperature = gr.Slider(minimum=0.1, maximum=1.0, step=0.1, label="Change the temperature \n (higher temperature = more creative in lyrics generation, but posibbly less Beatly)", value=0.5, show_label=True)  #high = sensitive for low probability tokens
+temperature = gr.Slider(minimum=0.1, maximum=1.0, step=0.1, label="Change the temperature \r\n (higher temperature = more creative in lyrics generation, but posibbly less Beatly)", value=0.5, show_label=True)  #high = sensitive for low probability tokens
 top_p = gr.Slider(minimum=0.1, maximum=1.0, step=0.1, label="Change top probability of the next word \n (higher top probability = more words to choose from for the next word, but possibly less Beatly)", value=0.5, show_label=True)
 given_input_style = gr.Dropdown(choices=image_input_styles, value="Random", label="Choose the art style for the lyrics cover", show_label=True)
 #checkpoint = gr.Radio(checkpoint_choices, value='wvangils/GPT-Medium-Beatles-Lyrics-finetuned-newlyrics', interactive=True, label = 'Select fine-tuned model', show_label=True)
@@ -133,5 +145,5 @@ gr.Interface(fn=generate_beatles
              , allow_flagging='never'
              ).launch()
 
-#generate_beatles(input_prompt="When I look out my window", temperature=0.7, top_p=0.5)
-
+# Uncomment the line below for testing
+#generate_beatles(input_prompt="When I look out my window", temperature=0.7, top_p=0.5)