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| import gradio as gr | |
| from transformers import GPT2LMHeadModel | |
| from tokenizers import IndoNLGTokenizer | |
| gpt_tokenizer = IndoNLGTokenizer.from_pretrained("indobenchmark/indogpt") | |
| gpt_tokenizer.pad_token = gpt_tokenizer.eos_token | |
| kancilgpt = GPT2LMHeadModel.from_pretrained("abdiharyadi/kancilgpt") | |
| def generate_story(judul: str): | |
| yield "...", "..." | |
| stop = False | |
| while not stop: | |
| gpt_input = gpt_tokenizer('<s> awal cerita | judul:', return_tensors='pt') | |
| gpt_out = kancilgpt.generate(**gpt_input, do_sample=True, max_length=512, pad_token_id=gpt_tokenizer.eos_token_id) | |
| result = gpt_tokenizer.decode(gpt_out[0]) | |
| _, judul_prompt, isi, *end_part = result.split(" | ") | |
| end_part = "".join(end_part) | |
| _, *judul_words = judul_prompt.split() | |
| judul = " ".join(judul_words) | |
| if "</s>" in judul or "</s>" in isi or "|" in isi or (not any(end_part.startswith(x) for x in ["bersambung", "tamat"])): | |
| print("Invalid output! Regenerating ....") | |
| continue | |
| quote_count = 0 | |
| for c in isi: | |
| if c == "\"": | |
| quote_count += 1 | |
| if quote_count % 2 != 0: | |
| print("Invalid output! Regenerating ....") | |
| continue | |
| stop = True | |
| yield judul, isi + " ..." | |
| total_isi = isi | |
| while not end_part.startswith("tamat"): | |
| yield judul, total_isi + " ..." | |
| i = 0 | |
| in_quote = False | |
| end_sentence = False | |
| limit = 1750 | |
| while i < len(isi) and not (end_sentence and (not in_quote) and isi[i] == " " and (len(isi) - i) < limit): | |
| if isi[i] == "\"": | |
| in_quote = not in_quote | |
| if end_sentence: | |
| end_sentence = isi[i] not in "abcdefghijklmnopqrstuvwxyz" | |
| else: | |
| end_sentence = isi[i] in ".?!" | |
| i += 1 | |
| # i == len(isi) or end_sentence or (not in_quote) or isi[i] == " " | |
| while i < len(isi) and not (isi[i] in "abcdefghijklmnopqrstuvwxyz\""): | |
| i += 1 | |
| # i == len(isi) or isi[i] in "abcdefghijklmnopqrstuvwxyz\"" | |
| if i == len(isi): | |
| raise ValueError("What???") | |
| next_isi = isi[i:] | |
| stop = False | |
| while not stop: | |
| gpt_input = gpt_tokenizer(f'<s> pertengahan cerita | judul: {judul} | {next_isi}', return_tensors='pt') | |
| gpt_out = kancilgpt.generate(**gpt_input, do_sample=True, max_length=512, pad_token_id=gpt_tokenizer.eos_token_id) | |
| result = gpt_tokenizer.decode(gpt_out[0]) | |
| _, judul_prompt, isi, *end_part = result.split(" | ") | |
| end_part = "".join(end_part) | |
| _, *judul_words = judul_prompt.split() | |
| judul = " ".join(judul_words) | |
| if isi[len(next_isi) + 1:].strip() != "": | |
| print(isi[len(next_isi) + 1:]) | |
| if "</s>" in isi or "|" in isi or (not any(end_part.startswith(x) for x in ["bersambung", "tamat"])): | |
| print("Invalid output! Regenerating ....") | |
| continue | |
| quote_count = 0 | |
| for c in isi: | |
| if c == "\"": | |
| quote_count += 1 | |
| if quote_count % 2 != 0: | |
| print("Invalid output! Regenerating ....") | |
| continue | |
| stop = True | |
| total_isi += " " + isi[len(next_isi) + 1:] | |
| yield judul, total_isi + "\n\ntamat." | |
| demo = gr.Interface( | |
| fn=generate_story, | |
| inputs=None, | |
| outputs=[ | |
| gr.Textbox(label="judul", lines=1), | |
| gr.Textbox(label="cerita", lines=7) | |
| ] | |
| ) | |
| demo.launch() | |