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import gradio as gr
import nltk
import string
from transformers import GPT2LMHeadModel, GPT2Tokenizer, GenerationConfig, set_seed
import random
nltk.download('punkt')
response_length = 200
sentence_detector = nltk.data.load('tokenizers/punkt/english.pickle')
tokenizer = GPT2Tokenizer.from_pretrained("gpt2-medium")
tokenizer.truncation_side = 'right'
model = GPT2LMHeadModel.from_pretrained('checkpoint-10000')
generation_config = GenerationConfig.from_pretrained('gpt2-medium')
generation_config.max_new_tokens = response_length
generation_config.pad_token_id = generation_config.eos_token_id
def generate_response(story_so_far, new_prompt):
truncated_story = story_so_far[:1024 - response_length]
set_seed(random.randint(0, 4000000000))
inputs = tokenizer.encode(story_so_far + '\n' + new_prompt if story_so_far else new_prompt,
return_tensors='pt', truncation=True,
max_length=1024 - response_length)
output = model.generate(inputs, do_sample=True, generation_config=generation_config)
response = clean_paragraph(tokenizer.batch_decode(output)[0][((len(truncated_story) + 1) if truncated_story else 0):])
return ((story_so_far + '\n' if story_so_far else '') + response).replace('\n', '\n\n')
def clean_paragraph(entry):
paragraphs = entry.split('\n')
for i in range(len(paragraphs)):
split_sentences = nltk.tokenize.sent_tokenize(paragraphs[i], language='english')
if i == len(paragraphs) - 1 and split_sentences[:1][-1] not in string.punctuation:
paragraphs[i] = " ".join(split_sentences[:-1])
return capitalize_first_char("\n".join(paragraphs))
def reset():
# global outputs
# outputs = []
return None
def capitalize_first_char(entry):
for i in range(len(entry)):
if entry[i].isalpha():
return entry[:i] + entry[i].upper() + entry[i + 1:]
return entry
with gr.Blocks() as demo:
story = gr.Textbox(interactive=False, lines=20)
story.style(show_copy_button=True)
prompt = gr.Textbox(placeholder="Continue the story here!", lines=3, max_lines=3)
with gr.Row():
gen_button = gr.Button('Generate')
# undo_button = gr.Button("Undo")
res_button = gr.Button("Reset")
prompt.submit(generate_response, prompt, story, scroll_to_output=True)
gen_button.click(generate_response, [story, prompt], story, scroll_to_output=True)
# undo_button.click(undo, [], story, scroll_to_output=True)
res_button.click(reset, [], story, scroll_to_output=True)
demo.launch(inbrowser=True)
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