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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=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 = "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, | |
| examples=examples, | |
| title=title, | |
| article=article, | |
| allow_flagging='never', | |
| cache_examples=False, | |
| theme="default").launch(enable_queue=True, debug=True) | |