app.py

import os

# Set writable cache directory inside the container
os.environ['SENTENCE_TRANSFORMERS_HOME'] = '/app/hf_home'
os.environ['TRANSFORMERS_CACHE'] = '/app/hf_home'

from fastapi import FastAPI
from transformers import AutoModelForCausalLM, AutoTokenizer

# Ensure the directory exists
os.makedirs(os.environ['TRANSFORMERS_CACHE'], exist_ok=True)

# Load model
model_name = "mynuddin/chatbot"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name).to("cpu")

app = FastAPI()

@app.post("/generate")
def generate_text(prompt: str):
    inputs = tokenizer(prompt, return_tensors="pt")
    output = model.generate(**inputs, max_length=128)
    generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
    return {"generated_query": generated_text}