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predictions_request.go
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predictions_request.go
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//
// Copyright © 2021 Uncharted Software Inc.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package compute
import (
"time"
"github.com/pkg/errors"
"github.com/uncharted-distil/distil/api/util/json"
)
// PredictRequest defines a request to generate new predictions from a fitted model and input data.
type PredictRequest struct {
DatasetID string
DatasetPath string
FittedSolutionID string
TimestampField string
MaxTime int
IntervalCount int
IntervalLength float64
ExistingDataset bool
requestChannel chan PredictStatus
finished chan error
}
// PredictStatus defines a prediction status update from a downstream autoML system
type PredictStatus struct {
Progress string `json:"progress"`
RequestID string `json:"requestId"`
ResultID string `json:"resultId"`
Error error `json:"error"`
Timestamp time.Time `json:"timestamp"`
}
// NewPredictRequest instantiates a predict request from a raw byte stream.
func NewPredictRequest(data []byte) (*PredictRequest, error) {
req := &PredictRequest{
finished: make(chan error),
requestChannel: make(chan PredictStatus),
}
jsonMap, err := json.Unmarshal(data)
if err != nil {
return nil, err
}
var ok bool
// the fitted pipeline to use for the predictions
req.FittedSolutionID, ok = json.String(jsonMap, "fittedSolutionId")
if !ok {
return nil, errors.Errorf("no `fittedSolutionId` in predict request")
}
// the name of the input prediction dataset
req.DatasetID, ok = json.String(jsonMap, "datasetId")
if !ok {
return nil, errors.Errorf("no `datasetId` in predict request")
}
// the dataset contents as a base 64 encded string
req.DatasetPath, ok = json.String(jsonMap, "datasetPath")
if !ok {
req.DatasetPath = ""
}
// timeseries prediction fields
req.IntervalCount, ok = json.Int(jsonMap, "intervalCount")
if !ok {
req.IntervalCount = 0
}
req.IntervalLength, ok = json.Float(jsonMap, "intervalLength")
if !ok {
req.IntervalLength = 0
}
req.ExistingDataset, ok = json.Bool(jsonMap, "existingDataset")
if !ok {
req.ExistingDataset = false
}
return req, nil
}