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// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: proto/clarifai/api/resources.proto
package com.clarifai.grpc.api;
public interface CollectorOrBuilder extends
// @@protoc_insertion_point(interface_extends:clarifai.api.Collector)
com.google.protobuf.MessageOrBuilder {
/**
*
* Unique ID for the collector.
*
*
* string id = 1;
* @return The id.
*/
java.lang.String getId();
/**
*
* Unique ID for the collector.
*
*
* string id = 1;
* @return The bytes for id.
*/
com.google.protobuf.ByteString
getIdBytes();
/**
*
* Human readable description for the collector.
*
*
* string description = 2;
* @return The description.
*/
java.lang.String getDescription();
/**
*
* Human readable description for the collector.
*
*
* string description = 2;
* @return The bytes for description.
*/
com.google.protobuf.ByteString
getDescriptionBytes();
/**
*
* When the collector is created. We follow the XXXX timestamp
* format. We use https://www.ietf.org/rfc/rfc3339.txt format:
* "2006-01-02T15:04:05.999999Z" so you can expect results like
* the following from the API:
* "2017-04-11T21:50:50.223962Z"
*
*
* .google.protobuf.Timestamp created_at = 3;
* @return Whether the createdAt field is set.
*/
boolean hasCreatedAt();
/**
*
* When the collector is created. We follow the XXXX timestamp
* format. We use https://www.ietf.org/rfc/rfc3339.txt format:
* "2006-01-02T15:04:05.999999Z" so you can expect results like
* the following from the API:
* "2017-04-11T21:50:50.223962Z"
*
*
* .google.protobuf.Timestamp created_at = 3;
* @return The createdAt.
*/
com.google.protobuf.Timestamp getCreatedAt();
/**
*
* When the collector is created. We follow the XXXX timestamp
* format. We use https://www.ietf.org/rfc/rfc3339.txt format:
* "2006-01-02T15:04:05.999999Z" so you can expect results like
* the following from the API:
* "2017-04-11T21:50:50.223962Z"
*
*
* .google.protobuf.Timestamp created_at = 3;
*/
com.google.protobuf.TimestampOrBuilder getCreatedAtOrBuilder();
/**
*
* This is a workflow to run inline in model predict calls. It should ONLY have very fast and
* light-weight models in it as it will effect the speed of the predictions being made.
* This workflow's purpose is to filter down the inputs to queue for the collector to process.
* The input to this workflow is going to be the OUTPUT of the model, not the input to the model
* since we want to encourage having fast workflows that can also take advantage of the model
* outputs to make deciions (for example: thresholding based on concepts). If the workflow
* output has any field that is non-empty then the input will be queued for the collector
* to process with the post_queue_workflow_id.
* As a simpler alternative, pre_queue_random_sample can be set to just use random sampling instead.
*
*
* string pre_queue_workflow_id = 4;
* @return The preQueueWorkflowId.
*/
java.lang.String getPreQueueWorkflowId();
/**
*
* This is a workflow to run inline in model predict calls. It should ONLY have very fast and
* light-weight models in it as it will effect the speed of the predictions being made.
* This workflow's purpose is to filter down the inputs to queue for the collector to process.
* The input to this workflow is going to be the OUTPUT of the model, not the input to the model
* since we want to encourage having fast workflows that can also take advantage of the model
* outputs to make deciions (for example: thresholding based on concepts). If the workflow
* output has any field that is non-empty then the input will be queued for the collector
* to process with the post_queue_workflow_id.
* As a simpler alternative, pre_queue_random_sample can be set to just use random sampling instead.
*
*
* string pre_queue_workflow_id = 4;
* @return The bytes for preQueueWorkflowId.
*/
com.google.protobuf.ByteString
getPreQueueWorkflowIdBytes();
/**
*
* Instead of needing to create a new workflow for pre_queue_workflow_id, if just random sampling
* of the model inputs is required, then pre_queue_random_sample can be set to a value from (0-1]
* to denote the fraction of inputs to collect.
*
*
* float pre_queue_random_sample = 8;
* @return The preQueueRandomSample.
*/
float getPreQueueRandomSample();
/**
*
* A workflow to run to after the collector is processing the queued input. This workflow
* uses the original input to the model as input to the workflow so that you can run additional
* models as well on that input to decide whether to queue the model or not. If the workflow
* output has any field that is non-empty then it will be passed on to POST /inputs to
* the destination app.
*
*
* string post_queue_workflow_id = 5;
* @return The postQueueWorkflowId.
*/
java.lang.String getPostQueueWorkflowId();
/**
*
* A workflow to run to after the collector is processing the queued input. This workflow
* uses the original input to the model as input to the workflow so that you can run additional
* models as well on that input to decide whether to queue the model or not. If the workflow
* output has any field that is non-empty then it will be passed on to POST /inputs to
* the destination app.
*
*
* string post_queue_workflow_id = 5;
* @return The bytes for postQueueWorkflowId.
*/
com.google.protobuf.ByteString
getPostQueueWorkflowIdBytes();
/**
*
* The source of the collector to feed data into this app.
* Note(zeiler): if we wanted more than one source per collector we could make this it's own
* object and introduce /collectors/{collector_id}/sources
* We will keep it simple for now and have just one source per collector since a user can make
* more than one collector in the same app anyways.
*
*
* .clarifai.api.CollectorSource collector_source = 6;
* @return Whether the collectorSource field is set.
*/
boolean hasCollectorSource();
/**
*
* The source of the collector to feed data into this app.
* Note(zeiler): if we wanted more than one source per collector we could make this it's own
* object and introduce /collectors/{collector_id}/sources
* We will keep it simple for now and have just one source per collector since a user can make
* more than one collector in the same app anyways.
*
*
* .clarifai.api.CollectorSource collector_source = 6;
* @return The collectorSource.
*/
com.clarifai.grpc.api.CollectorSource getCollectorSource();
/**
*
* The source of the collector to feed data into this app.
* Note(zeiler): if we wanted more than one source per collector we could make this it's own
* object and introduce /collectors/{collector_id}/sources
* We will keep it simple for now and have just one source per collector since a user can make
* more than one collector in the same app anyways.
*
*
* .clarifai.api.CollectorSource collector_source = 6;
*/
com.clarifai.grpc.api.CollectorSourceOrBuilder getCollectorSourceOrBuilder();
/**
*
* Status for the collector. This allows you to pause a collector without having to delete it as
* an example.
*
*
* .clarifai.api.status.Status status = 7;
* @return Whether the status field is set.
*/
boolean hasStatus();
/**
*
* Status for the collector. This allows you to pause a collector without having to delete it as
* an example.
*
*
* .clarifai.api.status.Status status = 7;
* @return The status.
*/
com.clarifai.grpc.api.status.Status getStatus();
/**
*
* Status for the collector. This allows you to pause a collector without having to delete it as
* an example.
*
*
* .clarifai.api.status.Status status = 7;
*/
com.clarifai.grpc.api.status.StatusOrBuilder getStatusOrBuilder();
/**
*
* Whether to collect outputs or not. Default is false. If selected, outputs from the
* original model predict call will be posted as annotations along with the input with success status.
*
*
* bool collect_outputs = 9;
* @return The collectOutputs.
*/
boolean getCollectOutputs();
}