app.py

import numpy as np
import gradio as gr
import openai
import os

def generateStory(theme1, theme2):
    openai.api_key = OPENAI_KEY
    prompt_text = "Write a children's story about \"{}\" and \"{}\".".format(theme1,theme2)
    response = openai.Completion.create(
      engine="text-davinci-003",
      prompt=prompt_text,
      temperature=0.7,
      max_tokens=600,
      top_p=1,
      frequency_penalty=0,
      presence_penalty=0
    )
    story = response["choices"][0]["text"]

    content_to_classify = "Your content here"

    response = openai.Completion.create(
          model="content-filter-alpha",
          prompt = "<|endoftext|>"+story+"\n--\nLabel:",
          temperature=0,
          max_tokens=1,
          top_p=0,
          logprobs=10
        )
    
    output_label = response["choices"][0]["text"]

    # This is the probability at which we evaluate that a "2" is likely real
    # vs. should be discarded as a false positive
    toxic_threshold = -0.355

    if output_label == "2":
      story='Please generate again'

    if story.startswith('\n\n'):
      story = story[2:]
    return story


def illustratedStory(story):

    if story != 'Please generate again':

      illustration_response = openai.Completion.create(
        model="text-davinci-002",
        prompt="Write a visual description of an illustration that could accompany the following story: '{}'".format(story),
        temperature=0.7,
        max_tokens=256,
        top_p=1,
        frequency_penalty=0,
        presence_penalty=0
      )

      image_prompt = illustration_response["choices"][0]["text"]
      print(image_prompt)
      response = openai.Image.create(
          
      prompt="A cartoon of: " + image_prompt,
      n=1,
      size="1024x1024"
      )
      image_url = response['data'][0]['url']

    else: 
      image = np.zeros([100,100,3],dtype=np.uint8)
      image.fill(255) # or img[:] = 255

    return image_url

def continueStory(inputStory):
    openai.api_key = OPENAI_KEY
    prompt_text = inputStory
    response = openai.Completion.create(
      engine="text-davinci-002",
      prompt=prompt_text,
      temperature=0.7,
      max_tokens=250,
      top_p=1,
      frequency_penalty=0,
      presence_penalty=0
    )
    story = response["choices"][0]["text"]

    content_to_classify = "Your content here"

    response = openai.Completion.create(
          model="content-filter-alpha",
          prompt = "<|endoftext|>"+story+"\n--\nLabel:",
          temperature=0,
          max_tokens=1,
          top_p=0,
          logprobs=10
        )
    
    output_label = response["choices"][0]["text"]

    # This is the probability at which we evaluate that a "2" is likely real
    # vs. should be discarded as a false positive
    toxic_threshold = -0.355

    if output_label == "2":
      story='Please generate again'

    if story.startswith('\n\n'):
      story = story[2:]
    return inputStory + story

def downloadStory(story):
  with open("output.txt", "a") as f:
    print("Hello stackoverflow!", file=f)
    print("I have a question.", file=f)

'''
demo = gr.Interface(
    fn=themes,

    
    inputs=["text", "text"],
    outputs=["text", "image"],
)

demo.launch()
'''



with gr.Blocks(css='''
.h1 {
    
    font-family: HK Grotesk;
    font-style: normal;
    font-weight: bold;
    font-size: 100px;
    line-height: 105%;
    margin: 0;
  }
  
  ''') as demo:
    title = gr.HTML(
        """
            <div style="text-align: center; margin: 0;">
              <div style="
                  display: inline-flex;
                  align-items: center;
                  gap: 0.8rem;
                  font-size: 1.75rem;
                ">
                
                <h1 style="font-weight: 900; margin-bottom: 7px;">
                  Infinite Stories
                </h1>
              </div>
              <p style="margin-bottom: 10px; font-size: 94%;">
                
              </p>
              <br>
              <p style="font-size: 70%;>Generate the beginning of a story by writing two themes, then edit, add to it, extend it and illustrate it! </p>
              
            </div>
        """)
    with gr.Row():        
      theme1 = gr.Textbox(label='Theme 1', elem_id = 'theme')
      theme2 = gr.Textbox(label='Theme 2', elem_id = 'theme')
    
    b1 = gr.Button("Generate starting paragraph", elem_id="generate-btn")

    story_output = gr.Textbox(label='Story (pro tip: you can edit this! Shift + enter for a new line)')

    with gr.Row():
  
      b3 = gr.Button("Continue Story", elem_id="continue-btn") 
      b2 = gr.Button("Illustrate Story", elem_id="illustrated-btn")
    

    with gr.Row():  
      illustration = gr.Image(label='Illustration')
      
    
    gr.HTML('<div style="text-align: center; max-width: 650px; margin: 0 auto;"><p style="margin-bottom: 10px; font-size: 94%;">Compute credits are expensive. Please help me keep this experiment running by buying me a coffee <a href="https://www.buymeacoffee.com/jrodolfoocG"> <u><b>here</u></b> :) </a></p></div><br>')
    gr.HTML('<div style="text-align: center; max-width: 650px; margin: 0 auto;"><p style="margin-bottom: 10px; font-size: 70%;">Built with GPT-3, Stable Diffusion, the Diffusers library and Gradio, by <a href="https://research.rodolfoocampo.com"><u><b>Rodolfo Ocampo</u></b></a></p></div>')
    
    
    b1.click(generateStory, inputs=[theme1,theme2], outputs=[story_output])
    b2.click(illustratedStory, inputs=[story_output], outputs=[illustration])

    b3.click(continueStory, inputs=[story_output], outputs=[story_output])

    
demo.launch(debug=True, share=True)