from fastapi import FastAPI
import os

app = FastAPI()

MODEL_PATH = "model.tflite"


# ===== تحويل من .h =====
def convert():
    from mrk_model_data import mrk_model_data, mrk_model_data_len

    with open(MODEL_PATH, "wb") as f:
        f.write(bytes(mrk_model_data[:mrk_model_data_len]))


# ===== init =====
if not os.path.exists(MODEL_PATH):
    convert()


@app.get("/")
def home():
    return {"status": "ok", "model": os.path.exists(MODEL_PATH)}


# ===== AI RESPONSE (placeholder inference) =====
@app.post("/predict")
def predict(data: dict):
    return {
        "input": data,
        "output": "MODEL_LOADED_SUCCESSFULLY",
        "note": "No runtime engine yet (tflite-runtime missing)"
    }