from fastapi import FastAPI
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
import os

app = FastAPI()

# Set the cache directory environment variable
os.environ["TRANSFORMERS_CACHE"] = "/tmp/cache"

# Load the model and tokenizer
model_name = "unsloth/llama-3-8b-bnb-4bit"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

@app.get("/")
def read_root():
    return {"Hello": "World"}

@app.post("/generate/")
def generate(prompt: str):
    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(inputs["input_ids"], max_length=50)
    text = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return {"generated_text": text}