text: from fast_dash import FastDash, Fastify
  from fast_dash.Components import Text, Image, Upload, UploadImage, Slider, html, dcc
  from fast_dash.utils import pil_to_b64
  
  
  def example_1_simple_text_to_text():
      "Fast Dash example 1. Simple text to text Fast Dash app"
      ## Define callback functions
      def simple_text_to_text_function(input_text):
          return input_text
  
      app = FastDash(
          callback_fn=simple_text_to_text_function,
          inputs=Text,
          outputs=Text,
          title="Fast Dash example 1",
      )
  
      return app
  
  
  def example_2_text_with_slider():
      "Fast Dash example 2"
  
      # Step 1: Define your model inference
      def text_to_text_function(input_text, slider_value):
          processed_text = f'{input_text}. Slider value is {slider_value}.'
          return processed_text
  
      # Step 2: Specify the input and output components
      app = FastDash(callback_fn=text_to_text_function, 
                      inputs=[Text, Slider], 
                      outputs=Text,
                      title='Fast Dash example 2')
  
      return app
  
  
  def example_3_image_to_image():
      "Fast Dash example 3"
  
      # Step 1: Define your model inference
      def callback_fn(image):
          return image
  
      # Step 2: Specify the input and output components
      app = FastDash(callback_fn=callback_fn, 
                      inputs=Upload, 
                      outputs=Image,
                      title='Fast Dash example 3')
  
      return app
  
  
  def example_4_image_slider_to_image_text():
      "Fast Dash example 4. Input is Upload (with ack) and slider. Output is Image and Text."
  
      def callback_fn(input_text, slider_value):
          return input_text, f"Slider value is {slider_value}"
  
      ack_image = Fastify(html.Img(width='100%'), 'src')
      fast_upload = Fastify(dcc.Upload(children=["Click to upload"], style={'borderStyle': 'dashed', 'padding-bottom':'20px'}), 'contents', ack=ack_image)
  
      app = FastDash(callback_fn=callback_fn, 
                          inputs=[fast_upload, Slider],
                          outputs=[Image, Text], 
                          title='Fast Dash example 4',
                          theme='SKETCHY')
  
      return app
  
  
  def example_5_uploadimage_to_image():
      "Fast Dash example 5. Input is UploadImage. Output is Image."
  
      def image_to_image(image):
  
          from PIL import Image
          import io
          import base64
          _, image_contents = image.split(',')
          processed_image = Image.open(io.BytesIO(base64.b64decode(image_contents.encode())))
  
          return pil_to_b64(processed_image)
  
      app = FastDash(callback_fn=image_to_image, 
                  inputs=UploadImage, 
                  outputs=Image,
                  title='Fast Dash example 5',
                  title_image_path='https://tinyurl.com/mr44nn5y',
                  subheader='Build ML prototypes lightning fast!',
                  github_url='https://github.com/dkedar7/fast_dash/',
                  linkedin_url='https://linkedin.com/in/dkedar7/',
                  twitter_url='https://twitter.com/dkedar7/',
                  theme='FLATLY')
  
      return app