Create app.py

app.py

@@ -0,0 +1,16 @@
+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+st.title("AI Accountant - Prompt-Based ERP Entry")
+
+model_path = "./finetuned-flan-t5"  # update if different path
+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))  # Convert JSON string to dict