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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): | |
for count in range(6): | |
seed = random.randint(100, 1000000) | |
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(60, 90), num_return_sequences=8) | |
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) | |
response_end = re.sub('[^ ]+\.[^ ]+','', response_end) | |
response_end = response_end.replace("<", "").replace(">", "") | |
if response_end != "": | |
return response_end | |
if count == 5: | |
return response_end | |
txt = grad.Textbox(lines=1, label="English", placeholder="English Text here") | |
out = grad.Textbox(lines=6, label="Generated Text") | |
examples = [["mythology of the Slavs"], ["All-seeing eye monitors these world"], ["astronaut dog"], | |
["A monochrome forest of ebony trees"], ["sad view of worker in office,"], | |
["Headshot photo portrait of John Lennon"], ["wide field with thousands of blue nemophila,"]] | |
title = "Magic Prompt Generator 🪄" | |
description = ' To use it, simply submit your text or click on one of the examples.' | |
grad.Interface(fn=generate, | |
inputs=txt, | |
outputs=out, | |
examples=examples, | |
title=title, | |
description=description, | |
allow_flagging='never', | |
cache_examples=False).queue(concurrency_count=1, api_open=False).launch(show_api=False, show_error=True) | |