| from flask import Flask, jsonify, requestimport mlflow.pyfuncapp = Flask(__name__)# Load the model as a PyFuncModel.model = mlflow.pyfunc.load_model(model_uri="models:/deployed_model/1")@app.route('/predict', methods=['POST'])def predict(): data = request.get_json() predictions = model.predict(data) return jsonify(predictions.tolist())if __name__ == '__main__': app.run(host='0.0.0.0', port=5000) | |