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from transformers import pipeline, set_seed
import gradio as grad
import random
import re
gpt2_pipe = pipeline('text-generation', model='succinctly/text2image-prompt-generator')
with open("name.txt", "r") as f:
line = f.readlines()
def generate(starting_text):
seed = random.randint(1, 100000)
set_seed(seed)
# If the text field is empty
if starting_text == "":
starting_text: str = line[random.randrange(0, len(line))].replace("\n", "").lower().capitalize()
starting_text: str = re.sub(r"[,:\-–.!;?_]", '', starting_text)
print(starting_text)
response = gpt2_pipe(starting_text, max_length=random.randint(20, 45), num_return_sequences=random.randint(5, 15))
response_list = []
for x in response:
resp = x['generated_text'].strip()
if resp != starting_text and len(resp) > (len(starting_text) + 4) and resp.endswith((":", "-", "—")) is False:
response_list.append(resp)
response_end = "\n".join(response_list)
return response_end
txt = grad.Textbox(lines=1, label="English", placeholder="English Text here")
out = grad.Textbox(lines=5, label="Generated Text")
title = "Prompt Generator"
article = "<div><center><img src='https://visitor-badge.glitch.me/badge?page_id=max_skobeev_prompt_generator_public' alt='visitor badge'></center></div>"
grad.Interface(fn=generate,
inputs=txt,
outputs=out,
title=title,
article=article,
allow_flagging='never',
cache_examples=False,
theme="default").launch(enable_queue=True, debug=True)
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