Create app.py

app.py

@@ -0,0 +1,24 @@
+# main.py
+from fastapi import FastAPI
+from pydantic import BaseModel
+import onnxruntime as ort
+import numpy as np
+
+app = FastAPI()
+
+session = ort.InferenceSession("model.onnx")
+
+class ModelInput(BaseModel):
+    input_ids: list[int]
+    attention_mask: list[int]
+
+@app.post("/predict")
+def predict(data: ModelInput):
+    input_ids = np.array(data.input_ids, dtype=np.int64).reshape(1, -1)
+    attention_mask = np.array(data.attention_mask, dtype=np.int64).reshape(1, -1)
+    inputs = {
+        "input_ids": input_ids,
+        "attention_mask": attention_mask,
+    }
+    outputs = session.run(None, inputs)
+    return {"output": outputs}