//     Those cannot be well described when embedded.
//  3. Inconsistent validation.  Because the usages are different, the validation rules are different by usage, which makes it hard for users to predict what will happen.
//  4. The fields are both imprecise and overly precise.  Kind is not a precise mapping to a URL. This can produce ambiguity

    yield
    # Clean up the ML models and release the resources
    ml_models.clear()


app = FastAPI(lifespan=lifespan)


@app.get("/predict")
async def predict(x: float):
    result = ml_models["answer_to_everything"](x)
    return {"result": result}
```

**Note**: This is the recommended way going forward, instead of using `startup` and `shutdown` events.

    <glob pattern="*.ppj"/>
    <root-XML localName="PremiereData"/>
    <sub-class-of type="application/xml"/>
  </mime-type>

  <mime-type type="image/vnd.cns.inf2"/>

  <!-- credit: peeveen's tika-dgn-detector https://github.com/peeveen/tika-dgn-detector/ -->
  <mime-type type="image/vnd.dgn">
    <glob pattern="*.dgn" />
    <glob pattern="*.dgnlib" />
    <glob pattern="*.cel" />