Create app.py

app.py

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+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()