def generateStory(theme1, theme2):
openai.api_key = {API_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 = "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"
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(
"""
Infinite Stories
Compute credits are expensive. Please help me keep this experiment running by buying me a coffee here :)
')
gr.HTML('Built with GPT-3, Stable Diffusion, the Diffusers library and Gradio, by Rodolfo Ocampo