app.py

import json
import numpy as np
import gradio as gr
import onnxruntime as ort

# Load vocab
with open("vocab.json") as f:
    vocab = json.load(f)
token2id = vocab
id2token = {v:k for k,v in vocab.items()}

# Load ONNX model
session = ort.InferenceSession("chat_model.onnx")

def tokenize(text):
    return [token2id.get(ch, 0) for ch in text]  # contoh simpel

def detokenize(ids):
    return "".join([id2token.get(i, "?") for i in ids])

def predict(text):
    ids = tokenize(text)
    x = np.array([ids], dtype=np.int64)  # biasanya int64

    # Input sesuai nama model
    input_name = session.get_inputs()[0].name
    output_name = session.get_outputs()[0].name

    # Run inference
    output = session.run([output_name], {input_name: x})[0][0]

    # Convert ke teks
    return detokenize(output.tolist())

# Gradio UI
demo = gr.Interface(fn=predict, inputs="text", outputs="text")
demo.launch()