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| from fastapi import FastAPI | |
| from pydantic import BaseModel | |
| from models.transformer.text_generator import TextGenerator | |
| app = FastAPI() | |
| generator = TextGenerator( | |
| model_name='fine_tuned_model_gpt_2', | |
| ) | |
| class Message(BaseModel): | |
| author: str | |
| content: str | |
| def generate_response(message: Message): | |
| response = generator.generate_text( | |
| author=message.author, | |
| input_str=message.content, | |
| max_length=100, | |
| num_return_sequences=1, | |
| do_sample=True, | |
| temperature=0.8, # Слегка уменьшаем уверенность | |
| top_k=100, # Уменьшаем количество рассматриваемых верхних k слов | |
| top_p=0.95 # Уменьшаем "ядерность" распределения | |
| )["generated_texts"][0] | |
| response = response[:response.find("</s>")] | |
| return { "response": response } | |