Sharing model parameters with monitoring
You would like to add a health check endpoint that provides model parameters to your penguin classification API.
The required packages (FastAPI and joblib) have been already imported.
Latihan ini adalah bagian dari kursus
Deploying AI into Production with FastAPI
Petunjuk latihan
- Add a GET endpoint at the typical location for health checks.
- Capture the model parameters from the sklearn model using the
get_paramsmethod. - Include the model parameters in the response as the value to key
params.
Latihan interaktif praktis
Cobalah latihan ini dengan menyelesaikan kode contoh berikut.
model = joblib.load(
'penguin_classifier.pkl'
)
app = FastAPI()
# Create health check endpoint
@app.get("____")
async def get_health():
# Capture the model params
params = ____.get_params()
return {"status": "OK",
# Include model params in response
"params": ____}