app.py

import streamlit as st
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

st.title("AI Accountant - Prompt-Based ERP Entry")

model_path = "google/flan-t5-large"  # load directly from Hugging Face hub

tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForSeq2SeqLM.from_pretrained(model_path)

user_input = st.text_area("Enter accounting transaction:")

if st.button("Generate Entry"):
    inputs = tokenizer(user_input, return_tensors="pt")
    outputs = model.generate(**inputs, max_new_tokens=128)
    result = tokenizer.decode(outputs[0], skip_special_tokens=True)
    st.json(eval(result))