Configuration
Python Handler
Specifying models in API configuration
cortex.yaml
cortex.yamlThe directory s3://cortex-examples/sklearn/mpg-estimator/linreg/ contains 4 different versions of the model.
- name: mpg-estimator
kind: RealtimeAPI
handler:
type: python
path: handler.py
models:
path: s3://cortex-examples/sklearn/mpg-estimator/linreg/handler.py
handler.pyimport mlflow.sklearn
class Handler:
def __init__(self, config, python_client):
self.client = python_client
def load_model(self, model_path):
return mlflow.sklearn.load_model(model_path)
def handle_post(self, payload, query_params):
model_version = query_params.get("version")
# model_input = ...
model = self.client.get_model(model_version=model_version)
result = model.predict(model_input)
return {"prediction": result, "model": {"version": model_version}}Without specifying models in API configuration
cortex.yaml
cortex.yamlhandler.py
handler.pyTensorFlow Handler
cortex.yaml
cortex.yamlhandler.py
handler.pyLast updated