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• And.java

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// Generated by the protocol buffer compiler.  DO NOT EDIT!
// source: proto/clarifai/api/resources.proto

package com.clarifai.grpc.api;

/**
 * 
 * This is the common building block of a query which is a sequence of And messages ANDed together.
 * Note that some fields are used too RANK results (affect the scores) and some are used to FILTER
 * results (unordered subset of your app's contents). In general, FILTER operations are more
 * efficient queries at scale and when combined with RANK operations can speed up search performance
 * as you effectively operate on a smaller sub-set of your entire app.
 * 
 *
 * Protobuf type {@code clarifai.api.And}
 */
public final class And extends
    com.google.protobuf.GeneratedMessageV3 implements
    // @@protoc_insertion_point(message_implements:clarifai.api.And)
    AndOrBuilder {
private static final long serialVersionUID = 0L;
  // Use And.newBuilder() to construct.
  private And(com.google.protobuf.GeneratedMessageV3.Builder builder) {
    super(builder);
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  public static final int INPUT_FIELD_NUMBER = 1;
  private com.clarifai.grpc.api.Input input_;
  /**
   * 
   * FILTER by input.data... information.
   * This can include human provided concepts, geo location info, metadata, etc.
   * This is effectively searching over only the trusted annotation attached to an input in your
   * app. To search by more specific annotation fields use the Annotation object here.
   * ########## Supported fields ##########
   *  - data.concepts[].id
   *  - data.concepts[].name
   *  - data.concepts[].value
   *  - data.geo.geo_box[].geo_point.latitude
   *  - data.geo.geo_box[].geo_point.longitude
   *  - data.geo.geo_limit.type
   *  - data.geo.geo_limit.value
   *  - data.geo.geo_point.latitude
   *  - data.geo.geo_point.longitude
   *  - data.image.url
   *  - data.metadata - allow search with empty metadata
   *    note that searching by empty metadata will actually not influence the search results.
   *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
   *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
   *  - dataset_ids[] - filter by dataset IDs
   *  - id - filter by input ID
   *  - status.code - filter by input status
   * 
   *
   * .clarifai.api.Input input = 1;
   * @return Whether the input field is set.
   */
  @java.lang.Override
  public boolean hasInput() {
    return input_ != null;
  }
  /**
   * 
   * FILTER by input.data... information.
   * This can include human provided concepts, geo location info, metadata, etc.
   * This is effectively searching over only the trusted annotation attached to an input in your
   * app. To search by more specific annotation fields use the Annotation object here.
   * ########## Supported fields ##########
   *  - data.concepts[].id
   *  - data.concepts[].name
   *  - data.concepts[].value
   *  - data.geo.geo_box[].geo_point.latitude
   *  - data.geo.geo_box[].geo_point.longitude
   *  - data.geo.geo_limit.type
   *  - data.geo.geo_limit.value
   *  - data.geo.geo_point.latitude
   *  - data.geo.geo_point.longitude
   *  - data.image.url
   *  - data.metadata - allow search with empty metadata
   *    note that searching by empty metadata will actually not influence the search results.
   *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
   *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
   *  - dataset_ids[] - filter by dataset IDs
   *  - id - filter by input ID
   *  - status.code - filter by input status
   * 
   *
   * .clarifai.api.Input input = 1;
   * @return The input.
   */
  @java.lang.Override
  public com.clarifai.grpc.api.Input getInput() {
    return input_ == null ? com.clarifai.grpc.api.Input.getDefaultInstance() : input_;
  }
  /**
   * 
   * FILTER by input.data... information.
   * This can include human provided concepts, geo location info, metadata, etc.
   * This is effectively searching over only the trusted annotation attached to an input in your
   * app. To search by more specific annotation fields use the Annotation object here.
   * ########## Supported fields ##########
   *  - data.concepts[].id
   *  - data.concepts[].name
   *  - data.concepts[].value
   *  - data.geo.geo_box[].geo_point.latitude
   *  - data.geo.geo_box[].geo_point.longitude
   *  - data.geo.geo_limit.type
   *  - data.geo.geo_limit.value
   *  - data.geo.geo_point.latitude
   *  - data.geo.geo_point.longitude
   *  - data.image.url
   *  - data.metadata - allow search with empty metadata
   *    note that searching by empty metadata will actually not influence the search results.
   *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
   *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
   *  - dataset_ids[] - filter by dataset IDs
   *  - id - filter by input ID
   *  - status.code - filter by input status
   * 
   *
   * .clarifai.api.Input input = 1;
   */
  @java.lang.Override
  public com.clarifai.grpc.api.InputOrBuilder getInputOrBuilder() {
    return getInput();
  }

  public static final int OUTPUT_FIELD_NUMBER = 2;
  private com.clarifai.grpc.api.Output output_;
  /**
   * 
   * RANK based predicted outputs from models such as custom trained models, pre-trained models,
   * etc. This is also where you enter the image url for a visual search because what we're asking
   * the system to do is find output embedding most visually similar to the provided input (that
   * input being in And.output.input.data.image.url for example). This will return the Hits
   * sorted by visual similarity (1.0 being very similar or exact match and 0.0 being very
   * dissimlar). For a search by Output concept, this means we're asking the system to rank
   * the Hits by confidence of our model's predicted Outputs. So for example if the model
   * predicts an image is 0.95 likely there is a "dog" present, that should related directly
   * to the score returned if you search for Output concept "dog" in your query. This provides
   * a natural ranking to search results based on confidence of predictions from the models and
   * is used when ANDing multiple of these types of RANK by Output queries together as well.
   * ########## Supported fields ##########
   *  - data.clusters[].id
   *  - data.concepts[].id
   *  - data.concepts[].name
   *  - data.concepts[].value
   *  - input.data.image - empty image is required when searching by input ID
   *  - input.data.image.base64[]
   *  - input.data.image.url
   *  - input.id
   * 
   *
   * .clarifai.api.Output output = 2;
   * @return Whether the output field is set.
   */
  @java.lang.Override
  public boolean hasOutput() {
    return output_ != null;
  }
  /**
   * 
   * RANK based predicted outputs from models such as custom trained models, pre-trained models,
   * etc. This is also where you enter the image url for a visual search because what we're asking
   * the system to do is find output embedding most visually similar to the provided input (that
   * input being in And.output.input.data.image.url for example). This will return the Hits
   * sorted by visual similarity (1.0 being very similar or exact match and 0.0 being very
   * dissimlar). For a search by Output concept, this means we're asking the system to rank
   * the Hits by confidence of our model's predicted Outputs. So for example if the model
   * predicts an image is 0.95 likely there is a "dog" present, that should related directly
   * to the score returned if you search for Output concept "dog" in your query. This provides
   * a natural ranking to search results based on confidence of predictions from the models and
   * is used when ANDing multiple of these types of RANK by Output queries together as well.
   * ########## Supported fields ##########
   *  - data.clusters[].id
   *  - data.concepts[].id
   *  - data.concepts[].name
   *  - data.concepts[].value
   *  - input.data.image - empty image is required when searching by input ID
   *  - input.data.image.base64[]
   *  - input.data.image.url
   *  - input.id
   * 
   *
   * .clarifai.api.Output output = 2;
   * @return The output.
   */
  @java.lang.Override
  public com.clarifai.grpc.api.Output getOutput() {
    return output_ == null ? com.clarifai.grpc.api.Output.getDefaultInstance() : output_;
  }
  /**
   * 
   * RANK based predicted outputs from models such as custom trained models, pre-trained models,
   * etc. This is also where you enter the image url for a visual search because what we're asking
   * the system to do is find output embedding most visually similar to the provided input (that
   * input being in And.output.input.data.image.url for example). This will return the Hits
   * sorted by visual similarity (1.0 being very similar or exact match and 0.0 being very
   * dissimlar). For a search by Output concept, this means we're asking the system to rank
   * the Hits by confidence of our model's predicted Outputs. So for example if the model
   * predicts an image is 0.95 likely there is a "dog" present, that should related directly
   * to the score returned if you search for Output concept "dog" in your query. This provides
   * a natural ranking to search results based on confidence of predictions from the models and
   * is used when ANDing multiple of these types of RANK by Output queries together as well.
   * ########## Supported fields ##########
   *  - data.clusters[].id
   *  - data.concepts[].id
   *  - data.concepts[].name
   *  - data.concepts[].value
   *  - input.data.image - empty image is required when searching by input ID
   *  - input.data.image.base64[]
   *  - input.data.image.url
   *  - input.id
   * 
   *
   * .clarifai.api.Output output = 2;
   */
  @java.lang.Override
  public com.clarifai.grpc.api.OutputOrBuilder getOutputOrBuilder() {
    return getOutput();
  }

  public static final int NEGATE_FIELD_NUMBER = 3;
  private boolean negate_;
  /**
   * 
   * If True then this will flip the meaning of this part of the
   * query. This allow for queries such as dog AND ! metadata=={"blah":"value"}
   * 
   *
   * bool negate = 3;
   * @return The negate.
   */
  @java.lang.Override
  public boolean getNegate() {
    return negate_;
  }

  public static final int ANNOTATION_FIELD_NUMBER = 4;
  private com.clarifai.grpc.api.Annotation annotation_;
  /**
   * 
   * FILTER by annotation information. This is more flexible than just filtering by
   * Input information because in the general case each input can have several annotations.
   * Some example use cases for filtering by annotations:
   * 1) find all the inputs annotated "dog" by worker_id = "XYZ"
   * 2) find all the annotations associated with embed_model_version_id = "123"
   * 3) find all the annotations that are trusted, etc.
   * Since all the annotations under the hood are joined to the embedding model's annotation
   * using worker_id's of other models like cluster models or concept models should be
   * combinable with queries like visual search (a query with Output filled in).
   * ########## Supported fields ##########
   *  - annotation_info - allows searching by empty annotation info
   *    note that searching by empty annotation info will actually not influence the search results.
   *    however, in order to be user-friendly, we are still supporting searching by empty annotation info.
   *  - annotation_info.fields - filter by annotation info
   *  - data.concepts[].id
   *  - data.concepts[].name
   *  - data.concepts[].value
   *  - data.geo.geo_box[].geo_point.latitude
   *  - data.geo.geo_box[].geo_point.longitude
   *  - data.geo.geo_limit.type
   *  - data.geo.geo_limit.value
   *  - data.geo.geo_point.latitude
   *  - data.geo.geo_point.longitude
   *  - data.image.url
   *  - data.metadata - allow search with empty metadata
   *    note that searching by empty metadata will actually not influence the search results.
   *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
   *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
   *  - input_id
   *  - input_level
   *  - model_version_id
   *  - status.code
   *  - task_id
   *  - trusted
   *  - user_id
   * 
   *
   * .clarifai.api.Annotation annotation = 4;
   * @return Whether the annotation field is set.
   */
  @java.lang.Override
  public boolean hasAnnotation() {
    return annotation_ != null;
  }
  /**
   * 
   * FILTER by annotation information. This is more flexible than just filtering by
   * Input information because in the general case each input can have several annotations.
   * Some example use cases for filtering by annotations:
   * 1) find all the inputs annotated "dog" by worker_id = "XYZ"
   * 2) find all the annotations associated with embed_model_version_id = "123"
   * 3) find all the annotations that are trusted, etc.
   * Since all the annotations under the hood are joined to the embedding model's annotation
   * using worker_id's of other models like cluster models or concept models should be
   * combinable with queries like visual search (a query with Output filled in).
   * ########## Supported fields ##########
   *  - annotation_info - allows searching by empty annotation info
   *    note that searching by empty annotation info will actually not influence the search results.
   *    however, in order to be user-friendly, we are still supporting searching by empty annotation info.
   *  - annotation_info.fields - filter by annotation info
   *  - data.concepts[].id
   *  - data.concepts[].name
   *  - data.concepts[].value
   *  - data.geo.geo_box[].geo_point.latitude
   *  - data.geo.geo_box[].geo_point.longitude
   *  - data.geo.geo_limit.type
   *  - data.geo.geo_limit.value
   *  - data.geo.geo_point.latitude
   *  - data.geo.geo_point.longitude
   *  - data.image.url
   *  - data.metadata - allow search with empty metadata
   *    note that searching by empty metadata will actually not influence the search results.
   *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
   *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
   *  - input_id
   *  - input_level
   *  - model_version_id
   *  - status.code
   *  - task_id
   *  - trusted
   *  - user_id
   * 
   *
   * .clarifai.api.Annotation annotation = 4;
   * @return The annotation.
   */
  @java.lang.Override
  public com.clarifai.grpc.api.Annotation getAnnotation() {
    return annotation_ == null ? com.clarifai.grpc.api.Annotation.getDefaultInstance() : annotation_;
  }
  /**
   * 
   * FILTER by annotation information. This is more flexible than just filtering by
   * Input information because in the general case each input can have several annotations.
   * Some example use cases for filtering by annotations:
   * 1) find all the inputs annotated "dog" by worker_id = "XYZ"
   * 2) find all the annotations associated with embed_model_version_id = "123"
   * 3) find all the annotations that are trusted, etc.
   * Since all the annotations under the hood are joined to the embedding model's annotation
   * using worker_id's of other models like cluster models or concept models should be
   * combinable with queries like visual search (a query with Output filled in).
   * ########## Supported fields ##########
   *  - annotation_info - allows searching by empty annotation info
   *    note that searching by empty annotation info will actually not influence the search results.
   *    however, in order to be user-friendly, we are still supporting searching by empty annotation info.
   *  - annotation_info.fields - filter by annotation info
   *  - data.concepts[].id
   *  - data.concepts[].name
   *  - data.concepts[].value
   *  - data.geo.geo_box[].geo_point.latitude
   *  - data.geo.geo_box[].geo_point.longitude
   *  - data.geo.geo_limit.type
   *  - data.geo.geo_limit.value
   *  - data.geo.geo_point.latitude
   *  - data.geo.geo_point.longitude
   *  - data.image.url
   *  - data.metadata - allow search with empty metadata
   *    note that searching by empty metadata will actually not influence the search results.
   *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
   *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
   *  - input_id
   *  - input_level
   *  - model_version_id
   *  - status.code
   *  - task_id
   *  - trusted
   *  - user_id
   * 
   *
   * .clarifai.api.Annotation annotation = 4;
   */
  @java.lang.Override
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    if (output_ != null) {
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    if (negate_ != false) {
      output.writeBool(3, negate_);
    }
    if (annotation_ != null) {
      output.writeMessage(4, getAnnotation());
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  @java.lang.Override
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  @java.lang.Override
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        != other.getNegate()) return false;
    if (hasAnnotation() != other.hasAnnotation()) return false;
    if (hasAnnotation()) {
      if (!getAnnotation()
          .equals(other.getAnnotation())) return false;
    }
    if (!unknownFields.equals(other.unknownFields)) return false;
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  }

  @java.lang.Override
  public int hashCode() {
    if (memoizedHashCode != 0) {
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    hash = (19 * hash) + getDescriptor().hashCode();
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      hash = (53 * hash) + getAnnotation().hashCode();
    }
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  public static com.clarifai.grpc.api.And parseFrom(
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  public static com.clarifai.grpc.api.And parseFrom(
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  public static com.clarifai.grpc.api.And parseFrom(
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   * efficient queries at scale and when combined with RANK operations can speed up search performance
   * as you effectively operate on a smaller sub-set of your entire app.
   * 
   *
   * Protobuf type {@code clarifai.api.And}
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    private com.google.protobuf.SingleFieldBuilderV3<
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    /**
     * 
     * FILTER by input.data... information.
     * This can include human provided concepts, geo location info, metadata, etc.
     * This is effectively searching over only the trusted annotation attached to an input in your
     * app. To search by more specific annotation fields use the Annotation object here.
     * ########## Supported fields ##########
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - dataset_ids[] - filter by dataset IDs
     *  - id - filter by input ID
     *  - status.code - filter by input status
     * 
     *
     * .clarifai.api.Input input = 1;
     * @return Whether the input field is set.
     */
    public boolean hasInput() {
      return inputBuilder_ != null || input_ != null;
    }
    /**
     * 
     * FILTER by input.data... information.
     * This can include human provided concepts, geo location info, metadata, etc.
     * This is effectively searching over only the trusted annotation attached to an input in your
     * app. To search by more specific annotation fields use the Annotation object here.
     * ########## Supported fields ##########
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - dataset_ids[] - filter by dataset IDs
     *  - id - filter by input ID
     *  - status.code - filter by input status
     * 
     *
     * .clarifai.api.Input input = 1;
     * @return The input.
     */
    public com.clarifai.grpc.api.Input getInput() {
      if (inputBuilder_ == null) {
        return input_ == null ? com.clarifai.grpc.api.Input.getDefaultInstance() : input_;
      } else {
        return inputBuilder_.getMessage();
      }
    }
    /**
     * 
     * FILTER by input.data... information.
     * This can include human provided concepts, geo location info, metadata, etc.
     * This is effectively searching over only the trusted annotation attached to an input in your
     * app. To search by more specific annotation fields use the Annotation object here.
     * ########## Supported fields ##########
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - dataset_ids[] - filter by dataset IDs
     *  - id - filter by input ID
     *  - status.code - filter by input status
     * 
     *
     * .clarifai.api.Input input = 1;
     */
    public Builder setInput(com.clarifai.grpc.api.Input value) {
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        if (value == null) {
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        }
        input_ = value;
        onChanged();
      } else {
        inputBuilder_.setMessage(value);
      }

      return this;
    }
    /**
     * 
     * FILTER by input.data... information.
     * This can include human provided concepts, geo location info, metadata, etc.
     * This is effectively searching over only the trusted annotation attached to an input in your
     * app. To search by more specific annotation fields use the Annotation object here.
     * ########## Supported fields ##########
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - dataset_ids[] - filter by dataset IDs
     *  - id - filter by input ID
     *  - status.code - filter by input status
     * 
     *
     * .clarifai.api.Input input = 1;
     */
    public Builder setInput(
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        onChanged();
      } else {
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      }

      return this;
    }
    /**
     * 
     * FILTER by input.data... information.
     * This can include human provided concepts, geo location info, metadata, etc.
     * This is effectively searching over only the trusted annotation attached to an input in your
     * app. To search by more specific annotation fields use the Annotation object here.
     * ########## Supported fields ##########
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - dataset_ids[] - filter by dataset IDs
     *  - id - filter by input ID
     *  - status.code - filter by input status
     * 
     *
     * .clarifai.api.Input input = 1;
     */
    public Builder mergeInput(com.clarifai.grpc.api.Input value) {
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        } else {
          input_ = value;
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        onChanged();
      } else {
        inputBuilder_.mergeFrom(value);
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      return this;
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    /**
     * 
     * FILTER by input.data... information.
     * This can include human provided concepts, geo location info, metadata, etc.
     * This is effectively searching over only the trusted annotation attached to an input in your
     * app. To search by more specific annotation fields use the Annotation object here.
     * ########## Supported fields ##########
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - dataset_ids[] - filter by dataset IDs
     *  - id - filter by input ID
     *  - status.code - filter by input status
     * 
     *
     * .clarifai.api.Input input = 1;
     */
    public Builder clearInput() {
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        onChanged();
      } else {
        input_ = null;
        inputBuilder_ = null;
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    /**
     * 
     * FILTER by input.data... information.
     * This can include human provided concepts, geo location info, metadata, etc.
     * This is effectively searching over only the trusted annotation attached to an input in your
     * app. To search by more specific annotation fields use the Annotation object here.
     * ########## Supported fields ##########
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - dataset_ids[] - filter by dataset IDs
     *  - id - filter by input ID
     *  - status.code - filter by input status
     * 
     *
     * .clarifai.api.Input input = 1;
     */
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      return getInputFieldBuilder().getBuilder();
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    /**
     * 
     * FILTER by input.data... information.
     * This can include human provided concepts, geo location info, metadata, etc.
     * This is effectively searching over only the trusted annotation attached to an input in your
     * app. To search by more specific annotation fields use the Annotation object here.
     * ########## Supported fields ##########
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - dataset_ids[] - filter by dataset IDs
     *  - id - filter by input ID
     *  - status.code - filter by input status
     * 
     *
     * .clarifai.api.Input input = 1;
     */
    public com.clarifai.grpc.api.InputOrBuilder getInputOrBuilder() {
      if (inputBuilder_ != null) {
        return inputBuilder_.getMessageOrBuilder();
      } else {
        return input_ == null ?
            com.clarifai.grpc.api.Input.getDefaultInstance() : input_;
      }
    }
    /**
     * 
     * FILTER by input.data... information.
     * This can include human provided concepts, geo location info, metadata, etc.
     * This is effectively searching over only the trusted annotation attached to an input in your
     * app. To search by more specific annotation fields use the Annotation object here.
     * ########## Supported fields ##########
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - dataset_ids[] - filter by dataset IDs
     *  - id - filter by input ID
     *  - status.code - filter by input status
     * 
     *
     * .clarifai.api.Input input = 1;
     */
    private com.google.protobuf.SingleFieldBuilderV3<
        com.clarifai.grpc.api.Input, com.clarifai.grpc.api.Input.Builder, com.clarifai.grpc.api.InputOrBuilder> 
        getInputFieldBuilder() {
      if (inputBuilder_ == null) {
        inputBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
            com.clarifai.grpc.api.Input, com.clarifai.grpc.api.Input.Builder, com.clarifai.grpc.api.InputOrBuilder>(
                getInput(),
                getParentForChildren(),
                isClean());
        input_ = null;
      }
      return inputBuilder_;
    }

    private com.clarifai.grpc.api.Output output_;
    private com.google.protobuf.SingleFieldBuilderV3<
        com.clarifai.grpc.api.Output, com.clarifai.grpc.api.Output.Builder, com.clarifai.grpc.api.OutputOrBuilder> outputBuilder_;
    /**
     * 
     * RANK based predicted outputs from models such as custom trained models, pre-trained models,
     * etc. This is also where you enter the image url for a visual search because what we're asking
     * the system to do is find output embedding most visually similar to the provided input (that
     * input being in And.output.input.data.image.url for example). This will return the Hits
     * sorted by visual similarity (1.0 being very similar or exact match and 0.0 being very
     * dissimlar). For a search by Output concept, this means we're asking the system to rank
     * the Hits by confidence of our model's predicted Outputs. So for example if the model
     * predicts an image is 0.95 likely there is a "dog" present, that should related directly
     * to the score returned if you search for Output concept "dog" in your query. This provides
     * a natural ranking to search results based on confidence of predictions from the models and
     * is used when ANDing multiple of these types of RANK by Output queries together as well.
     * ########## Supported fields ##########
     *  - data.clusters[].id
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - input.data.image - empty image is required when searching by input ID
     *  - input.data.image.base64[]
     *  - input.data.image.url
     *  - input.id
     * 
     *
     * .clarifai.api.Output output = 2;
     * @return Whether the output field is set.
     */
    public boolean hasOutput() {
      return outputBuilder_ != null || output_ != null;
    }
    /**
     * 
     * RANK based predicted outputs from models such as custom trained models, pre-trained models,
     * etc. This is also where you enter the image url for a visual search because what we're asking
     * the system to do is find output embedding most visually similar to the provided input (that
     * input being in And.output.input.data.image.url for example). This will return the Hits
     * sorted by visual similarity (1.0 being very similar or exact match and 0.0 being very
     * dissimlar). For a search by Output concept, this means we're asking the system to rank
     * the Hits by confidence of our model's predicted Outputs. So for example if the model
     * predicts an image is 0.95 likely there is a "dog" present, that should related directly
     * to the score returned if you search for Output concept "dog" in your query. This provides
     * a natural ranking to search results based on confidence of predictions from the models and
     * is used when ANDing multiple of these types of RANK by Output queries together as well.
     * ########## Supported fields ##########
     *  - data.clusters[].id
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - input.data.image - empty image is required when searching by input ID
     *  - input.data.image.base64[]
     *  - input.data.image.url
     *  - input.id
     * 
     *
     * .clarifai.api.Output output = 2;
     * @return The output.
     */
    public com.clarifai.grpc.api.Output getOutput() {
      if (outputBuilder_ == null) {
        return output_ == null ? com.clarifai.grpc.api.Output.getDefaultInstance() : output_;
      } else {
        return outputBuilder_.getMessage();
      }
    }
    /**
     * 
     * RANK based predicted outputs from models such as custom trained models, pre-trained models,
     * etc. This is also where you enter the image url for a visual search because what we're asking
     * the system to do is find output embedding most visually similar to the provided input (that
     * input being in And.output.input.data.image.url for example). This will return the Hits
     * sorted by visual similarity (1.0 being very similar or exact match and 0.0 being very
     * dissimlar). For a search by Output concept, this means we're asking the system to rank
     * the Hits by confidence of our model's predicted Outputs. So for example if the model
     * predicts an image is 0.95 likely there is a "dog" present, that should related directly
     * to the score returned if you search for Output concept "dog" in your query. This provides
     * a natural ranking to search results based on confidence of predictions from the models and
     * is used when ANDing multiple of these types of RANK by Output queries together as well.
     * ########## Supported fields ##########
     *  - data.clusters[].id
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - input.data.image - empty image is required when searching by input ID
     *  - input.data.image.base64[]
     *  - input.data.image.url
     *  - input.id
     * 
     *
     * .clarifai.api.Output output = 2;
     */
    public Builder setOutput(com.clarifai.grpc.api.Output value) {
      if (outputBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        output_ = value;
        onChanged();
      } else {
        outputBuilder_.setMessage(value);
      }

      return this;
    }
    /**
     * 
     * RANK based predicted outputs from models such as custom trained models, pre-trained models,
     * etc. This is also where you enter the image url for a visual search because what we're asking
     * the system to do is find output embedding most visually similar to the provided input (that
     * input being in And.output.input.data.image.url for example). This will return the Hits
     * sorted by visual similarity (1.0 being very similar or exact match and 0.0 being very
     * dissimlar). For a search by Output concept, this means we're asking the system to rank
     * the Hits by confidence of our model's predicted Outputs. So for example if the model
     * predicts an image is 0.95 likely there is a "dog" present, that should related directly
     * to the score returned if you search for Output concept "dog" in your query. This provides
     * a natural ranking to search results based on confidence of predictions from the models and
     * is used when ANDing multiple of these types of RANK by Output queries together as well.
     * ########## Supported fields ##########
     *  - data.clusters[].id
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - input.data.image - empty image is required when searching by input ID
     *  - input.data.image.base64[]
     *  - input.data.image.url
     *  - input.id
     * 
     *
     * .clarifai.api.Output output = 2;
     */
    public Builder setOutput(
        com.clarifai.grpc.api.Output.Builder builderForValue) {
      if (outputBuilder_ == null) {
        output_ = builderForValue.build();
        onChanged();
      } else {
        outputBuilder_.setMessage(builderForValue.build());
      }

      return this;
    }
    /**
     * 
     * RANK based predicted outputs from models such as custom trained models, pre-trained models,
     * etc. This is also where you enter the image url for a visual search because what we're asking
     * the system to do is find output embedding most visually similar to the provided input (that
     * input being in And.output.input.data.image.url for example). This will return the Hits
     * sorted by visual similarity (1.0 being very similar or exact match and 0.0 being very
     * dissimlar). For a search by Output concept, this means we're asking the system to rank
     * the Hits by confidence of our model's predicted Outputs. So for example if the model
     * predicts an image is 0.95 likely there is a "dog" present, that should related directly
     * to the score returned if you search for Output concept "dog" in your query. This provides
     * a natural ranking to search results based on confidence of predictions from the models and
     * is used when ANDing multiple of these types of RANK by Output queries together as well.
     * ########## Supported fields ##########
     *  - data.clusters[].id
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - input.data.image - empty image is required when searching by input ID
     *  - input.data.image.base64[]
     *  - input.data.image.url
     *  - input.id
     * 
     *
     * .clarifai.api.Output output = 2;
     */
    public Builder mergeOutput(com.clarifai.grpc.api.Output value) {
      if (outputBuilder_ == null) {
        if (output_ != null) {
          output_ =
            com.clarifai.grpc.api.Output.newBuilder(output_).mergeFrom(value).buildPartial();
        } else {
          output_ = value;
        }
        onChanged();
      } else {
        outputBuilder_.mergeFrom(value);
      }

      return this;
    }
    /**
     * 
     * RANK based predicted outputs from models such as custom trained models, pre-trained models,
     * etc. This is also where you enter the image url for a visual search because what we're asking
     * the system to do is find output embedding most visually similar to the provided input (that
     * input being in And.output.input.data.image.url for example). This will return the Hits
     * sorted by visual similarity (1.0 being very similar or exact match and 0.0 being very
     * dissimlar). For a search by Output concept, this means we're asking the system to rank
     * the Hits by confidence of our model's predicted Outputs. So for example if the model
     * predicts an image is 0.95 likely there is a "dog" present, that should related directly
     * to the score returned if you search for Output concept "dog" in your query. This provides
     * a natural ranking to search results based on confidence of predictions from the models and
     * is used when ANDing multiple of these types of RANK by Output queries together as well.
     * ########## Supported fields ##########
     *  - data.clusters[].id
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - input.data.image - empty image is required when searching by input ID
     *  - input.data.image.base64[]
     *  - input.data.image.url
     *  - input.id
     * 
     *
     * .clarifai.api.Output output = 2;
     */
    public Builder clearOutput() {
      if (outputBuilder_ == null) {
        output_ = null;
        onChanged();
      } else {
        output_ = null;
        outputBuilder_ = null;
      }

      return this;
    }
    /**
     * 
     * RANK based predicted outputs from models such as custom trained models, pre-trained models,
     * etc. This is also where you enter the image url for a visual search because what we're asking
     * the system to do is find output embedding most visually similar to the provided input (that
     * input being in And.output.input.data.image.url for example). This will return the Hits
     * sorted by visual similarity (1.0 being very similar or exact match and 0.0 being very
     * dissimlar). For a search by Output concept, this means we're asking the system to rank
     * the Hits by confidence of our model's predicted Outputs. So for example if the model
     * predicts an image is 0.95 likely there is a "dog" present, that should related directly
     * to the score returned if you search for Output concept "dog" in your query. This provides
     * a natural ranking to search results based on confidence of predictions from the models and
     * is used when ANDing multiple of these types of RANK by Output queries together as well.
     * ########## Supported fields ##########
     *  - data.clusters[].id
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - input.data.image - empty image is required when searching by input ID
     *  - input.data.image.base64[]
     *  - input.data.image.url
     *  - input.id
     * 
     *
     * .clarifai.api.Output output = 2;
     */
    public com.clarifai.grpc.api.Output.Builder getOutputBuilder() {
      
      onChanged();
      return getOutputFieldBuilder().getBuilder();
    }
    /**
     * 
     * RANK based predicted outputs from models such as custom trained models, pre-trained models,
     * etc. This is also where you enter the image url for a visual search because what we're asking
     * the system to do is find output embedding most visually similar to the provided input (that
     * input being in And.output.input.data.image.url for example). This will return the Hits
     * sorted by visual similarity (1.0 being very similar or exact match and 0.0 being very
     * dissimlar). For a search by Output concept, this means we're asking the system to rank
     * the Hits by confidence of our model's predicted Outputs. So for example if the model
     * predicts an image is 0.95 likely there is a "dog" present, that should related directly
     * to the score returned if you search for Output concept "dog" in your query. This provides
     * a natural ranking to search results based on confidence of predictions from the models and
     * is used when ANDing multiple of these types of RANK by Output queries together as well.
     * ########## Supported fields ##########
     *  - data.clusters[].id
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - input.data.image - empty image is required when searching by input ID
     *  - input.data.image.base64[]
     *  - input.data.image.url
     *  - input.id
     * 
     *
     * .clarifai.api.Output output = 2;
     */
    public com.clarifai.grpc.api.OutputOrBuilder getOutputOrBuilder() {
      if (outputBuilder_ != null) {
        return outputBuilder_.getMessageOrBuilder();
      } else {
        return output_ == null ?
            com.clarifai.grpc.api.Output.getDefaultInstance() : output_;
      }
    }
    /**
     * 
     * RANK based predicted outputs from models such as custom trained models, pre-trained models,
     * etc. This is also where you enter the image url for a visual search because what we're asking
     * the system to do is find output embedding most visually similar to the provided input (that
     * input being in And.output.input.data.image.url for example). This will return the Hits
     * sorted by visual similarity (1.0 being very similar or exact match and 0.0 being very
     * dissimlar). For a search by Output concept, this means we're asking the system to rank
     * the Hits by confidence of our model's predicted Outputs. So for example if the model
     * predicts an image is 0.95 likely there is a "dog" present, that should related directly
     * to the score returned if you search for Output concept "dog" in your query. This provides
     * a natural ranking to search results based on confidence of predictions from the models and
     * is used when ANDing multiple of these types of RANK by Output queries together as well.
     * ########## Supported fields ##########
     *  - data.clusters[].id
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - input.data.image - empty image is required when searching by input ID
     *  - input.data.image.base64[]
     *  - input.data.image.url
     *  - input.id
     * 
     *
     * .clarifai.api.Output output = 2;
     */
    private com.google.protobuf.SingleFieldBuilderV3<
        com.clarifai.grpc.api.Output, com.clarifai.grpc.api.Output.Builder, com.clarifai.grpc.api.OutputOrBuilder> 
        getOutputFieldBuilder() {
      if (outputBuilder_ == null) {
        outputBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
            com.clarifai.grpc.api.Output, com.clarifai.grpc.api.Output.Builder, com.clarifai.grpc.api.OutputOrBuilder>(
                getOutput(),
                getParentForChildren(),
                isClean());
        output_ = null;
      }
      return outputBuilder_;
    }

    private boolean negate_ ;
    /**
     * 
     * If True then this will flip the meaning of this part of the
     * query. This allow for queries such as dog AND ! metadata=={"blah":"value"}
     * 
     *
     * bool negate = 3;
     * @return The negate.
     */
    @java.lang.Override
    public boolean getNegate() {
      return negate_;
    }
    /**
     * 
     * If True then this will flip the meaning of this part of the
     * query. This allow for queries such as dog AND ! metadata=={"blah":"value"}
     * 
     *
     * bool negate = 3;
     * @param value The negate to set.
     * @return This builder for chaining.
     */
    public Builder setNegate(boolean value) {
      
      negate_ = value;
      onChanged();
      return this;
    }
    /**
     * 
     * If True then this will flip the meaning of this part of the
     * query. This allow for queries such as dog AND ! metadata=={"blah":"value"}
     * 
     *
     * bool negate = 3;
     * @return This builder for chaining.
     */
    public Builder clearNegate() {
      
      negate_ = false;
      onChanged();
      return this;
    }

    private com.clarifai.grpc.api.Annotation annotation_;
    private com.google.protobuf.SingleFieldBuilderV3<
        com.clarifai.grpc.api.Annotation, com.clarifai.grpc.api.Annotation.Builder, com.clarifai.grpc.api.AnnotationOrBuilder> annotationBuilder_;
    /**
     * 
     * FILTER by annotation information. This is more flexible than just filtering by
     * Input information because in the general case each input can have several annotations.
     * Some example use cases for filtering by annotations:
     * 1) find all the inputs annotated "dog" by worker_id = "XYZ"
     * 2) find all the annotations associated with embed_model_version_id = "123"
     * 3) find all the annotations that are trusted, etc.
     * Since all the annotations under the hood are joined to the embedding model's annotation
     * using worker_id's of other models like cluster models or concept models should be
     * combinable with queries like visual search (a query with Output filled in).
     * ########## Supported fields ##########
     *  - annotation_info - allows searching by empty annotation info
     *    note that searching by empty annotation info will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty annotation info.
     *  - annotation_info.fields - filter by annotation info
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - input_id
     *  - input_level
     *  - model_version_id
     *  - status.code
     *  - task_id
     *  - trusted
     *  - user_id
     * 
     *
     * .clarifai.api.Annotation annotation = 4;
     * @return Whether the annotation field is set.
     */
    public boolean hasAnnotation() {
      return annotationBuilder_ != null || annotation_ != null;
    }
    /**
     * 
     * FILTER by annotation information. This is more flexible than just filtering by
     * Input information because in the general case each input can have several annotations.
     * Some example use cases for filtering by annotations:
     * 1) find all the inputs annotated "dog" by worker_id = "XYZ"
     * 2) find all the annotations associated with embed_model_version_id = "123"
     * 3) find all the annotations that are trusted, etc.
     * Since all the annotations under the hood are joined to the embedding model's annotation
     * using worker_id's of other models like cluster models or concept models should be
     * combinable with queries like visual search (a query with Output filled in).
     * ########## Supported fields ##########
     *  - annotation_info - allows searching by empty annotation info
     *    note that searching by empty annotation info will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty annotation info.
     *  - annotation_info.fields - filter by annotation info
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - input_id
     *  - input_level
     *  - model_version_id
     *  - status.code
     *  - task_id
     *  - trusted
     *  - user_id
     * 
     *
     * .clarifai.api.Annotation annotation = 4;
     * @return The annotation.
     */
    public com.clarifai.grpc.api.Annotation getAnnotation() {
      if (annotationBuilder_ == null) {
        return annotation_ == null ? com.clarifai.grpc.api.Annotation.getDefaultInstance() : annotation_;
      } else {
        return annotationBuilder_.getMessage();
      }
    }
    /**
     * 
     * FILTER by annotation information. This is more flexible than just filtering by
     * Input information because in the general case each input can have several annotations.
     * Some example use cases for filtering by annotations:
     * 1) find all the inputs annotated "dog" by worker_id = "XYZ"
     * 2) find all the annotations associated with embed_model_version_id = "123"
     * 3) find all the annotations that are trusted, etc.
     * Since all the annotations under the hood are joined to the embedding model's annotation
     * using worker_id's of other models like cluster models or concept models should be
     * combinable with queries like visual search (a query with Output filled in).
     * ########## Supported fields ##########
     *  - annotation_info - allows searching by empty annotation info
     *    note that searching by empty annotation info will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty annotation info.
     *  - annotation_info.fields - filter by annotation info
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - input_id
     *  - input_level
     *  - model_version_id
     *  - status.code
     *  - task_id
     *  - trusted
     *  - user_id
     * 
     *
     * .clarifai.api.Annotation annotation = 4;
     */
    public Builder setAnnotation(com.clarifai.grpc.api.Annotation value) {
      if (annotationBuilder_ == null) {
        if (value == null) {
          throw new NullPointerException();
        }
        annotation_ = value;
        onChanged();
      } else {
        annotationBuilder_.setMessage(value);
      }

      return this;
    }
    /**
     * 
     * FILTER by annotation information. This is more flexible than just filtering by
     * Input information because in the general case each input can have several annotations.
     * Some example use cases for filtering by annotations:
     * 1) find all the inputs annotated "dog" by worker_id = "XYZ"
     * 2) find all the annotations associated with embed_model_version_id = "123"
     * 3) find all the annotations that are trusted, etc.
     * Since all the annotations under the hood are joined to the embedding model's annotation
     * using worker_id's of other models like cluster models or concept models should be
     * combinable with queries like visual search (a query with Output filled in).
     * ########## Supported fields ##########
     *  - annotation_info - allows searching by empty annotation info
     *    note that searching by empty annotation info will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty annotation info.
     *  - annotation_info.fields - filter by annotation info
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - input_id
     *  - input_level
     *  - model_version_id
     *  - status.code
     *  - task_id
     *  - trusted
     *  - user_id
     * 
     *
     * .clarifai.api.Annotation annotation = 4;
     */
    public Builder setAnnotation(
        com.clarifai.grpc.api.Annotation.Builder builderForValue) {
      if (annotationBuilder_ == null) {
        annotation_ = builderForValue.build();
        onChanged();
      } else {
        annotationBuilder_.setMessage(builderForValue.build());
      }

      return this;
    }
    /**
     * 
     * FILTER by annotation information. This is more flexible than just filtering by
     * Input information because in the general case each input can have several annotations.
     * Some example use cases for filtering by annotations:
     * 1) find all the inputs annotated "dog" by worker_id = "XYZ"
     * 2) find all the annotations associated with embed_model_version_id = "123"
     * 3) find all the annotations that are trusted, etc.
     * Since all the annotations under the hood are joined to the embedding model's annotation
     * using worker_id's of other models like cluster models or concept models should be
     * combinable with queries like visual search (a query with Output filled in).
     * ########## Supported fields ##########
     *  - annotation_info - allows searching by empty annotation info
     *    note that searching by empty annotation info will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty annotation info.
     *  - annotation_info.fields - filter by annotation info
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - input_id
     *  - input_level
     *  - model_version_id
     *  - status.code
     *  - task_id
     *  - trusted
     *  - user_id
     * 
     *
     * .clarifai.api.Annotation annotation = 4;
     */
    public Builder mergeAnnotation(com.clarifai.grpc.api.Annotation value) {
      if (annotationBuilder_ == null) {
        if (annotation_ != null) {
          annotation_ =
            com.clarifai.grpc.api.Annotation.newBuilder(annotation_).mergeFrom(value).buildPartial();
        } else {
          annotation_ = value;
        }
        onChanged();
      } else {
        annotationBuilder_.mergeFrom(value);
      }

      return this;
    }
    /**
     * 
     * FILTER by annotation information. This is more flexible than just filtering by
     * Input information because in the general case each input can have several annotations.
     * Some example use cases for filtering by annotations:
     * 1) find all the inputs annotated "dog" by worker_id = "XYZ"
     * 2) find all the annotations associated with embed_model_version_id = "123"
     * 3) find all the annotations that are trusted, etc.
     * Since all the annotations under the hood are joined to the embedding model's annotation
     * using worker_id's of other models like cluster models or concept models should be
     * combinable with queries like visual search (a query with Output filled in).
     * ########## Supported fields ##########
     *  - annotation_info - allows searching by empty annotation info
     *    note that searching by empty annotation info will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty annotation info.
     *  - annotation_info.fields - filter by annotation info
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - input_id
     *  - input_level
     *  - model_version_id
     *  - status.code
     *  - task_id
     *  - trusted
     *  - user_id
     * 
     *
     * .clarifai.api.Annotation annotation = 4;
     */
    public Builder clearAnnotation() {
      if (annotationBuilder_ == null) {
        annotation_ = null;
        onChanged();
      } else {
        annotation_ = null;
        annotationBuilder_ = null;
      }

      return this;
    }
    /**
     * 
     * FILTER by annotation information. This is more flexible than just filtering by
     * Input information because in the general case each input can have several annotations.
     * Some example use cases for filtering by annotations:
     * 1) find all the inputs annotated "dog" by worker_id = "XYZ"
     * 2) find all the annotations associated with embed_model_version_id = "123"
     * 3) find all the annotations that are trusted, etc.
     * Since all the annotations under the hood are joined to the embedding model's annotation
     * using worker_id's of other models like cluster models or concept models should be
     * combinable with queries like visual search (a query with Output filled in).
     * ########## Supported fields ##########
     *  - annotation_info - allows searching by empty annotation info
     *    note that searching by empty annotation info will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty annotation info.
     *  - annotation_info.fields - filter by annotation info
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - input_id
     *  - input_level
     *  - model_version_id
     *  - status.code
     *  - task_id
     *  - trusted
     *  - user_id
     * 
     *
     * .clarifai.api.Annotation annotation = 4;
     */
    public com.clarifai.grpc.api.Annotation.Builder getAnnotationBuilder() {
      
      onChanged();
      return getAnnotationFieldBuilder().getBuilder();
    }
    /**
     * 
     * FILTER by annotation information. This is more flexible than just filtering by
     * Input information because in the general case each input can have several annotations.
     * Some example use cases for filtering by annotations:
     * 1) find all the inputs annotated "dog" by worker_id = "XYZ"
     * 2) find all the annotations associated with embed_model_version_id = "123"
     * 3) find all the annotations that are trusted, etc.
     * Since all the annotations under the hood are joined to the embedding model's annotation
     * using worker_id's of other models like cluster models or concept models should be
     * combinable with queries like visual search (a query with Output filled in).
     * ########## Supported fields ##########
     *  - annotation_info - allows searching by empty annotation info
     *    note that searching by empty annotation info will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty annotation info.
     *  - annotation_info.fields - filter by annotation info
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - input_id
     *  - input_level
     *  - model_version_id
     *  - status.code
     *  - task_id
     *  - trusted
     *  - user_id
     * 
     *
     * .clarifai.api.Annotation annotation = 4;
     */
    public com.clarifai.grpc.api.AnnotationOrBuilder getAnnotationOrBuilder() {
      if (annotationBuilder_ != null) {
        return annotationBuilder_.getMessageOrBuilder();
      } else {
        return annotation_ == null ?
            com.clarifai.grpc.api.Annotation.getDefaultInstance() : annotation_;
      }
    }
    /**
     * 
     * FILTER by annotation information. This is more flexible than just filtering by
     * Input information because in the general case each input can have several annotations.
     * Some example use cases for filtering by annotations:
     * 1) find all the inputs annotated "dog" by worker_id = "XYZ"
     * 2) find all the annotations associated with embed_model_version_id = "123"
     * 3) find all the annotations that are trusted, etc.
     * Since all the annotations under the hood are joined to the embedding model's annotation
     * using worker_id's of other models like cluster models or concept models should be
     * combinable with queries like visual search (a query with Output filled in).
     * ########## Supported fields ##########
     *  - annotation_info - allows searching by empty annotation info
     *    note that searching by empty annotation info will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty annotation info.
     *  - annotation_info.fields - filter by annotation info
     *  - data.concepts[].id
     *  - data.concepts[].name
     *  - data.concepts[].value
     *  - data.geo.geo_box[].geo_point.latitude
     *  - data.geo.geo_box[].geo_point.longitude
     *  - data.geo.geo_limit.type
     *  - data.geo.geo_limit.value
     *  - data.geo.geo_point.latitude
     *  - data.geo.geo_point.longitude
     *  - data.image.url
     *  - data.metadata - allow search with empty metadata
     *    note that searching by empty metadata will actually not influence the search results.
     *    however, in order to be user-friendly, we are still supporting searching by empty metadata.
     *  - data.metadata.fields - filter by metadata. metadata key&value fields are OR-ed.
     *  - input_id
     *  - input_level
     *  - model_version_id
     *  - status.code
     *  - task_id
     *  - trusted
     *  - user_id
     * 
     *
     * .clarifai.api.Annotation annotation = 4;
     */
    private com.google.protobuf.SingleFieldBuilderV3<
        com.clarifai.grpc.api.Annotation, com.clarifai.grpc.api.Annotation.Builder, com.clarifai.grpc.api.AnnotationOrBuilder> 
        getAnnotationFieldBuilder() {
      if (annotationBuilder_ == null) {
        annotationBuilder_ = new com.google.protobuf.SingleFieldBuilderV3<
            com.clarifai.grpc.api.Annotation, com.clarifai.grpc.api.Annotation.Builder, com.clarifai.grpc.api.AnnotationOrBuilder>(
                getAnnotation(),
                getParentForChildren(),
                isClean());
        annotation_ = null;
      }
      return annotationBuilder_;
    }
    @java.lang.Override
    public final Builder setUnknownFields(
        final com.google.protobuf.UnknownFieldSet unknownFields) {
      return super.setUnknownFields(unknownFields);
    }

    @java.lang.Override
    public final Builder mergeUnknownFields(
        final com.google.protobuf.UnknownFieldSet unknownFields) {
      return super.mergeUnknownFields(unknownFields);
    }


    // @@protoc_insertion_point(builder_scope:clarifai.api.And)
  }

  // @@protoc_insertion_point(class_scope:clarifai.api.And)
  private static final com.clarifai.grpc.api.And DEFAULT_INSTANCE;
  static {
    DEFAULT_INSTANCE = new com.clarifai.grpc.api.And();
  }

  public static com.clarifai.grpc.api.And getDefaultInstance() {
    return DEFAULT_INSTANCE;
  }

  private static final com.google.protobuf.Parser
      PARSER = new com.google.protobuf.AbstractParser() {
    @java.lang.Override
    public And parsePartialFrom(
        com.google.protobuf.CodedInputStream input,
        com.google.protobuf.ExtensionRegistryLite extensionRegistry)
        throws com.google.protobuf.InvalidProtocolBufferException {
      return new And(input, extensionRegistry);
    }
  };

  public static com.google.protobuf.Parser parser() {
    return PARSER;
  }

  @java.lang.Override
  public com.google.protobuf.Parser getParserForType() {
    return PARSER;
  }

  @java.lang.Override
  public com.clarifai.grpc.api.And getDefaultInstanceForType() {
    return DEFAULT_INSTANCE;
  }

}