| from transformers import pipeline, set_seed | |
| import gradio as grad, random, re | |
| gpt2_pipe = pipeline('text-generation', model='Gustavosta/MagicPrompt-Stable-Diffusion', tokenizer='gpt2') | |
| with open("ideas.txt", "r") as f: | |
| line = f.readlines() | |
| def generate(starting_text): | |
| seed = random.randint(100, 1000000) | |
| set_seed(seed) | |
| if starting_text == "": | |
| starting_text: str = line[random.randrange(0, len(line))].replace("\n", "").lower().capitalize() | |
| starting_text: str = re.sub(r"[,:\-–.!;?_]", '', starting_text) | |
| response = gpt2_pipe(starting_text, max_length=(len(starting_text) + random.randint(60, 90)), num_return_sequences=4) | |
| 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+'\n') | |
| response_end = "\n".join(response_list) | |
| response_end = re.sub('[^ ]+\.[^ ]+','', response_end) | |
| response_end = response_end.replace("<", "").replace(">", "") | |
| if response_end != "": | |
| return response_end | |
| txt = grad.Textbox(lines=1, label="Initial Text", placeholder="English Text here") | |
| out = grad.Textbox(lines=4, label="Generated Prompts") | |
| examples = [] | |
| for x in range(8): | |
| examples.append(line[random.randrange(0, len(line))].replace("\n", "").lower().capitalize()) | |
| title = "Stable Diffusion Prompt Generator" | |
| description = 'This is a demo of the model series: "MagicPrompt", in this case, aimed at: "Stable Diffusion". To use it, simply submit your text or click on one of the examples. To learn more about the model, [click here](https://huggingface.co/Gustavosta/MagicPrompt-Stable-Diffusion).<br>' | |
| grad.Interface(fn=generate, | |
| inputs=txt, | |
| outputs=out, | |
| examples=examples, | |
| title=title, | |
| description=description, | |
| article='', | |
| allow_flagging='never', | |
| cache_examples=False, | |
| theme="default").launch(enable_queue=True, debug=True) | |