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| from fastapi import FastAPI, HTTPException | |
| from pydantic import BaseModel | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| import torch | |
| import requests | |
| app = FastAPI(title="LuxAI GPT-2 Backend") | |
| # ===== GPT-2 ===== | |
| MODEL_NAME = "distilgpt2" | |
| tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME) | |
| model = AutoModelForCausalLM.from_pretrained(MODEL_NAME) | |
| model.eval() | |
| # ===== Request ===== | |
| class GenerateRequest(BaseModel): | |
| user_input: str | |
| model: str = "gpt2" | |
| def generate(req: GenerateRequest): | |
| if req.model != "gpt2": | |
| raise HTTPException(400, "Tento backend podporuje pouze gpt2") | |
| prompt = f"User: {req.user_input}\nBot:" | |
| inputs = tokenizer(prompt, return_tensors="pt") | |
| with torch.no_grad(): | |
| output = model.generate( | |
| **inputs, | |
| max_new_tokens=120, | |
| temperature=0.8, | |
| do_sample=True, | |
| top_p=0.95, | |
| pad_token_id=tokenizer.eos_token_id | |
| ) | |
| text = tokenizer.decode(output[0], skip_special_tokens=True) | |
| response = text[len(prompt):].strip() | |
| return {"response": response} | |