app.py

from fastapi import FastAPI, Request
from pydantic import BaseModel
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

app = FastAPI()

# Ladda modellen
model_id = "AI-Sweden/gpt-sw3-126m"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

# Om du kör på CPU – lägg till detta
device = torch.device("cpu")
model.to(device)

# Input-modell
class Prompt(BaseModel):
    text: str
    max_new_tokens: int = 50

@app.post("/generate")
async def generate_text(prompt: Prompt):
    inputs = tokenizer(prompt.text, return_tensors="pt").to(device)
    outputs = model.generate(**inputs, max_new_tokens=prompt.max_new_tokens)
    generated = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return {"response": generated}