diff --git a/output/openapi/elasticsearch-openapi.json b/output/openapi/elasticsearch-openapi.json index e531acd1d6..5a07e1e9c6 100644 --- a/output/openapi/elasticsearch-openapi.json +++ b/output/openapi/elasticsearch-openapi.json @@ -17022,6 +17022,9 @@ "description": "The maximum number of threads to be used by the analysis. Using more\nthreads may decrease the time necessary to complete the analysis at the\ncost of using more CPU. Note that the process may use additional threads\nfor operational functionality other than the analysis itself.", "type": "number" }, + "_meta": { + "$ref": "#/components/schemas/_types:Metadata" + }, "model_memory_limit": { "description": "The approximate maximum amount of memory resources that are permitted for\nanalytical processing. If your `elasticsearch.yml` file contains an\n`xpack.ml.max_model_memory_limit` setting, an error occurs when you try\nto create data frame analytics jobs that have `model_memory_limit` values\ngreater than that setting.", "type": "string" @@ -17081,6 +17084,9 @@ "max_num_threads": { "type": "number" }, + "_meta": { + "$ref": "#/components/schemas/_types:Metadata" + }, "model_memory_limit": { "type": "string" }, @@ -17828,6 +17834,46 @@ "$ref": "#/components/schemas/_types:Id" }, "style": "simple" + }, + { + "in": "query", + "name": "allow_no_indices", + "description": "If `true`, wildcard indices expressions that resolve into no concrete indices are ignored. This includes the\n`_all` string or when no indices are specified.", + "deprecated": false, + "schema": { + "type": "boolean" + }, + "style": "form" + }, + { + "in": "query", + "name": "expand_wildcards", + "description": "Type of index that wildcard patterns can match. If the request can target data streams, this argument determines\nwhether wildcard expressions match hidden data streams. Supports comma-separated values. Valid values are:\n\n* `all`: Match any data stream or index, including hidden ones.\n* `closed`: Match closed, non-hidden indices. Also matches any non-hidden data stream. Data streams cannot be closed.\n* `hidden`: Match hidden data streams and hidden indices. Must be combined with `open`, `closed`, or both.\n* `none`: Wildcard patterns are not accepted.\n* `open`: Match open, non-hidden indices. Also matches any non-hidden data stream.", + "deprecated": false, + "schema": { + "$ref": "#/components/schemas/_types:ExpandWildcards" + }, + "style": "form" + }, + { + "in": "query", + "name": "ignore_throttled", + "description": "If `true`, concrete, expanded or aliased indices are ignored when frozen.", + "deprecated": true, + "schema": { + "type": "boolean" + }, + "style": "form" + }, + { + "in": "query", + "name": "ignore_unavailable", + "description": "If `true`, unavailable indices (missing or closed) are ignored.", + "deprecated": false, + "schema": { + "type": "boolean" + }, + "style": "form" } ], "requestBody": { @@ -17866,6 +17912,9 @@ "description": "A description of the job.", "type": "string" }, + "job_id": { + "$ref": "#/components/schemas/_types:Id" + }, "groups": { "description": "A list of job groups. A job can belong to no groups or many.", "type": "array", @@ -18215,6 +18264,9 @@ { "$ref": "#/components/parameters/ml.get_trained_models#include" }, + { + "$ref": "#/components/parameters/ml.get_trained_models#include_model_definition" + }, { "$ref": "#/components/parameters/ml.get_trained_models#size" }, @@ -20120,6 +20172,9 @@ { "$ref": "#/components/parameters/ml.get_trained_models#include" }, + { + "$ref": "#/components/parameters/ml.get_trained_models#include_model_definition" + }, { "$ref": "#/components/parameters/ml.get_trained_models#size" }, @@ -20421,13 +20476,13 @@ "schema": { "type": "object", "properties": { - "bucket_count": { - "type": "number" + "job_id": { + "$ref": "#/components/schemas/_types:Id" }, - "earliest_record_timestamp": { + "processed_record_count": { "type": "number" }, - "empty_bucket_count": { + "processed_field_count": { "type": "number" }, "input_bytes": { @@ -20436,53 +20491,59 @@ "input_field_count": { "type": "number" }, - "input_record_count": { - "type": "number" - }, "invalid_date_count": { "type": "number" }, - "job_id": { - "$ref": "#/components/schemas/_types:Id" - }, - "last_data_time": { + "missing_field_count": { "type": "number" }, - "latest_record_timestamp": { + "out_of_order_timestamp_count": { "type": "number" }, - "missing_field_count": { + "empty_bucket_count": { "type": "number" }, - "out_of_order_timestamp_count": { + "sparse_bucket_count": { "type": "number" }, - "processed_field_count": { + "bucket_count": { "type": "number" }, - "processed_record_count": { - "type": "number" + "earliest_record_timestamp": { + "$ref": "#/components/schemas/_types:EpochTimeUnitMillis" }, - "sparse_bucket_count": { + "latest_record_timestamp": { + "$ref": "#/components/schemas/_types:EpochTimeUnitMillis" + }, + "last_data_time": { + "$ref": "#/components/schemas/_types:EpochTimeUnitMillis" + }, + "latest_empty_bucket_timestamp": { + "$ref": "#/components/schemas/_types:EpochTimeUnitMillis" + }, + "latest_sparse_bucket_timestamp": { + "$ref": "#/components/schemas/_types:EpochTimeUnitMillis" + }, + "input_record_count": { "type": "number" + }, + "log_time": { + "$ref": "#/components/schemas/_types:EpochTimeUnitMillis" } }, "required": [ - "bucket_count", - "earliest_record_timestamp", - "empty_bucket_count", + "job_id", + "processed_record_count", + "processed_field_count", "input_bytes", "input_field_count", - "input_record_count", "invalid_date_count", - "job_id", - "last_data_time", - "latest_record_timestamp", "missing_field_count", "out_of_order_timestamp_count", - "processed_field_count", - "processed_record_count", - "sparse_bucket_count" + "empty_bucket_count", + "sparse_bucket_count", + "bucket_count", + "input_record_count" ] } } @@ -22017,7 +22078,7 @@ "description": "An array of detector update objects.", "type": "array", "items": { - "$ref": "#/components/schemas/ml._types:Detector" + "$ref": "#/components/schemas/ml._types:DetectorUpdate" } }, "per_partition_categorization": { @@ -73778,6 +73839,9 @@ }, "version": { "$ref": "#/components/schemas/_types:VersionString" + }, + "_meta": { + "$ref": "#/components/schemas/_types:Metadata" } }, "required": [ @@ -74165,7 +74229,7 @@ "$ref": "#/components/schemas/_types:Id" }, "node": { - "$ref": "#/components/schemas/ml._types:DiscoveryNode" + "$ref": "#/components/schemas/ml._types:DiscoveryNodeCompact" }, "state": { "$ref": "#/components/schemas/ml._types:DatafeedState" @@ -74179,18 +74243,14 @@ }, "required": [ "datafeed_id", - "state", - "timing_stats" + "state" ] }, - "ml._types:DiscoveryNode": { + "ml._types:DiscoveryNodeCompact": { "type": "object", "properties": { - "attributes": { - "type": "object", - "additionalProperties": { - "type": "string" - } + "name": { + "$ref": "#/components/schemas/_types:Name" }, "ephemeral_id": { "$ref": "#/components/schemas/_types:Id" @@ -74198,19 +74258,22 @@ "id": { "$ref": "#/components/schemas/_types:Id" }, - "name": { - "$ref": "#/components/schemas/_types:Name" - }, "transport_address": { "$ref": "#/components/schemas/_types:TransportAddress" + }, + "attributes": { + "type": "object", + "additionalProperties": { + "type": "string" + } } }, "required": [ - "attributes", + "name", "ephemeral_id", "id", - "name", - "transport_address" + "transport_address", + "attributes" ] }, "ml._types:DatafeedTimingStats": { @@ -74223,6 +74286,9 @@ "exponential_average_search_time_per_hour_ms": { "$ref": "#/components/schemas/_types:DurationValueUnitFloatMillis" }, + "exponential_average_calculation_context": { + "$ref": "#/components/schemas/ml._types:ExponentialAverageCalculationContext" + }, "job_id": { "$ref": "#/components/schemas/_types:Id" }, @@ -74256,6 +74322,23 @@ "description": "Time unit for fractional milliseconds", "type": "number" }, + "ml._types:ExponentialAverageCalculationContext": { + "type": "object", + "properties": { + "incremental_metric_value_ms": { + "$ref": "#/components/schemas/_types:DurationValueUnitFloatMillis" + }, + "latest_timestamp": { + "$ref": "#/components/schemas/_types:EpochTimeUnitMillis" + }, + "previous_exponential_average_ms": { + "$ref": "#/components/schemas/_types:DurationValueUnitFloatMillis" + } + }, + "required": [ + "incremental_metric_value_ms" + ] + }, "ml._types:DatafeedRunningState": { "type": "object", "properties": { @@ -74546,7 +74629,7 @@ "$ref": "#/components/schemas/ml._types:ModelSizeStats" }, "node": { - "$ref": "#/components/schemas/ml._types:DiscoveryNode" + "$ref": "#/components/schemas/ml._types:DiscoveryNodeCompact" }, "open_time": { "$ref": "#/components/schemas/_types:DateTime" @@ -74724,6 +74807,9 @@ "model_bytes_memory_limit": { "$ref": "#/components/schemas/_types:ByteSize" }, + "output_memory_allocator_bytes": { + "$ref": "#/components/schemas/_types:ByteSize" + }, "peak_model_bytes": { "$ref": "#/components/schemas/_types:ByteSize" }, @@ -74923,8 +75009,7 @@ "type": "number" }, "model_memory_limit": { - "description": "The approximate maximum amount of memory resources that are required for analytical processing. Once this limit is approached, data pruning becomes more aggressive. Upon exceeding this limit, new entities are not modeled. If the `xpack.ml.max_model_memory_limit` setting has a value greater than 0 and less than 1024mb, that value is used instead of the default. The default value is relatively small to ensure that high resource usage is a conscious decision. If you have jobs that are expected to analyze high cardinality fields, you will likely need to use a higher value. If you specify a number instead of a string, the units are assumed to be MiB. Specifying a string is recommended for clarity. If you specify a byte size unit of `b` or `kb` and the number does not equate to a discrete number of megabytes, it is rounded down to the closest MiB. The minimum valid value is 1 MiB. If you specify a value less than 1 MiB, an error occurs. If you specify a value for the `xpack.ml.max_model_memory_limit` setting, an error occurs when you try to create jobs that have `model_memory_limit` values greater than that setting value.", - "type": "string" + "$ref": "#/components/schemas/_types:ByteSize" } } }, @@ -75172,6 +75257,62 @@ "failed" ] }, + "ml._types:DiscoveryNode": { + "type": "object", + "additionalProperties": { + "$ref": "#/components/schemas/ml._types:DiscoveryNodeContent" + }, + "minProperties": 1, + "maxProperties": 1 + }, + "ml._types:DiscoveryNodeContent": { + "type": "object", + "properties": { + "name": { + "$ref": "#/components/schemas/_types:Name" + }, + "ephemeral_id": { + "$ref": "#/components/schemas/_types:Id" + }, + "transport_address": { + "$ref": "#/components/schemas/_types:TransportAddress" + }, + "external_id": { + "type": "string" + }, + "attributes": { + "type": "object", + "additionalProperties": { + "type": "string" + } + }, + "roles": { + "type": "array", + "items": { + "type": "string" + } + }, + "version": { + "$ref": "#/components/schemas/_types:VersionString" + }, + "min_index_version": { + "type": "number" + }, + "max_index_version": { + "type": "number" + } + }, + "required": [ + "ephemeral_id", + "transport_address", + "external_id", + "attributes", + "roles", + "version", + "min_index_version", + "max_index_version" + ] + }, "ml._types:ModelSnapshot": { "type": "object", "properties": { @@ -75259,8 +75400,7 @@ "jobs", "overall_score", "result_type", - "timestamp", - "timestamp_string" + "timestamp" ] }, "ml._types:OverallBucketJob": { @@ -75628,6 +75768,9 @@ "model_size_bytes": { "$ref": "#/components/schemas/_types:ByteSize" }, + "model_package": { + "$ref": "#/components/schemas/ml._types:ModelPackageConfig" + }, "location": { "$ref": "#/components/schemas/ml._types:TrainedModelLocation" }, @@ -75717,6 +75860,9 @@ "bert": { "$ref": "#/components/schemas/ml._types:NlpBertTokenizationConfig" }, + "bert_ja": { + "$ref": "#/components/schemas/ml._types:NlpBertTokenizationConfig" + }, "mpnet": { "$ref": "#/components/schemas/ml._types:NlpBertTokenizationConfig" }, @@ -75728,26 +75874,36 @@ "maxProperties": 1 }, "ml._types:NlpBertTokenizationConfig": { + "allOf": [ + { + "$ref": "#/components/schemas/ml._types:CommonTokenizationConfig" + }, + { + "type": "object" + } + ] + }, + "ml._types:CommonTokenizationConfig": { "type": "object", "properties": { "do_lower_case": { "description": "Should the tokenizer lower case the text", "type": "boolean" }, - "with_special_tokens": { - "description": "Is tokenization completed with special tokens", - "type": "boolean" - }, "max_sequence_length": { "description": "Maximum input sequence length for the model", "type": "number" }, - "truncate": { - "$ref": "#/components/schemas/ml._types:TokenizationTruncate" - }, "span": { "description": "Tokenization spanning options. Special value of -1 indicates no spanning takes place", "type": "number" + }, + "truncate": { + "$ref": "#/components/schemas/ml._types:TokenizationTruncate" + }, + "with_special_tokens": { + "description": "Is tokenization completed with special tokens", + "type": "boolean" } } }, @@ -75760,28 +75916,20 @@ ] }, "ml._types:NlpRobertaTokenizationConfig": { - "type": "object", - "properties": { - "add_prefix_space": { - "description": "Should the tokenizer prefix input with a space character", - "type": "boolean" - }, - "with_special_tokens": { - "description": "Is tokenization completed with special tokens", - "type": "boolean" - }, - "max_sequence_length": { - "description": "Maximum input sequence length for the model", - "type": "number" - }, - "truncate": { - "$ref": "#/components/schemas/ml._types:TokenizationTruncate" + "allOf": [ + { + "$ref": "#/components/schemas/ml._types:CommonTokenizationConfig" }, - "span": { - "description": "Tokenization spanning options. Special value of -1 indicates no spanning takes place", - "type": "number" + { + "type": "object", + "properties": { + "add_prefix_space": { + "description": "Should the tokenizer prefix input with a space character", + "type": "boolean" + } + } } - } + ] }, "ml._types:ZeroShotClassificationInferenceOptions": { "type": "object", @@ -75837,8 +75985,25 @@ "results_field": { "description": "The field that is added to incoming documents to contain the inference prediction. Defaults to predicted_value.", "type": "string" + }, + "vocabulary": { + "$ref": "#/components/schemas/ml._types:Vocabulary" } - } + }, + "required": [ + "vocabulary" + ] + }, + "ml._types:Vocabulary": { + "type": "object", + "properties": { + "index": { + "$ref": "#/components/schemas/_types:IndexName" + } + }, + "required": [ + "index" + ] }, "ml._types:NerInferenceOptions": { "type": "object", @@ -75862,17 +76027,6 @@ } } }, - "ml._types:Vocabulary": { - "type": "object", - "properties": { - "index": { - "$ref": "#/components/schemas/_types:IndexName" - } - }, - "required": [ - "index" - ] - }, "ml._types:PassThroughInferenceOptions": { "type": "object", "properties": { @@ -75901,8 +76055,14 @@ "results_field": { "description": "The field that is added to incoming documents to contain the inference prediction. Defaults to predicted_value.", "type": "string" + }, + "vocabulary": { + "$ref": "#/components/schemas/ml._types:Vocabulary" } - } + }, + "required": [ + "vocabulary" + ] }, "ml._types:TextExpansionInferenceOptions": { "type": "object", @@ -75913,8 +76073,14 @@ "results_field": { "description": "The field that is added to incoming documents to contain the inference prediction. Defaults to predicted_value.", "type": "string" + }, + "vocabulary": { + "$ref": "#/components/schemas/ml._types:Vocabulary" } - } + }, + "required": [ + "vocabulary" + ] }, "ml._types:QuestionAnsweringInferenceOptions": { "type": "object", @@ -76080,6 +76246,75 @@ "importance" ] }, + "ml._types:ModelPackageConfig": { + "type": "object", + "properties": { + "create_time": { + "$ref": "#/components/schemas/_types:EpochTimeUnitMillis" + }, + "description": { + "type": "string" + }, + "inference_config": { + "type": "object", + "additionalProperties": { + "type": "object" + } + }, + "metadata": { + "$ref": "#/components/schemas/_types:Metadata" + }, + "minimum_version": { + "type": "string" + }, + "model_repository": { + "type": "string" + }, + "model_type": { + "type": "string" + }, + "packaged_model_id": { + "$ref": "#/components/schemas/_types:Id" + }, + "platform_architecture": { + "type": "string" + }, + "prefix_strings": { + "$ref": "#/components/schemas/ml._types:TrainedModelPrefixStrings" + }, + "size": { + "$ref": "#/components/schemas/_types:ByteSize" + }, + "sha256": { + "type": "string" + }, + "tags": { + "type": "array", + "items": { + "type": "string" + } + }, + "vocabulary_file": { + "type": "string" + } + }, + "required": [ + "packaged_model_id" + ] + }, + "ml._types:TrainedModelPrefixStrings": { + "type": "object", + "properties": { + "ingest": { + "description": "String prepended to input at ingest", + "type": "string" + }, + "search": { + "description": "String prepended to input at search", + "type": "string" + } + } + }, "ml._types:TrainedModelLocation": { "type": "object", "properties": { @@ -76102,19 +76337,6 @@ "name" ] }, - "ml._types:TrainedModelPrefixStrings": { - "type": "object", - "properties": { - "ingest": { - "description": "String prepended to input at ingest", - "type": "string" - }, - "search": { - "description": "String prepended to input at search", - "type": "string" - } - } - }, "ml._types:TrainedModelStats": { "type": "object", "properties": { @@ -76151,6 +76373,9 @@ "ml._types:TrainedModelDeploymentStats": { "type": "object", "properties": { + "adaptive_allocations": { + "$ref": "#/components/schemas/ml._types:AdaptiveAllocationsSettings" + }, "allocation_status": { "$ref": "#/components/schemas/ml._types:TrainedModelDeploymentAllocationStatus" }, @@ -76182,6 +76407,12 @@ "description": "The number of allocations requested.", "type": "number" }, + "peak_throughput_per_minute": { + "type": "number" + }, + "priority": { + "$ref": "#/components/schemas/ml._types:TrainingPriority" + }, "queue_capacity": { "description": "The number of inference requests that can be queued before new requests are rejected.", "type": "number" @@ -76210,20 +76441,29 @@ } }, "required": [ - "allocation_status", "deployment_id", - "error_count", - "inference_count", "model_id", "nodes", - "number_of_allocations", - "queue_capacity", - "rejected_execution_count", - "reason", - "start_time", - "state", - "threads_per_allocation", - "timeout_count" + "peak_throughput_per_minute", + "priority", + "start_time" + ] + }, + "ml._types:AdaptiveAllocationsSettings": { + "type": "object", + "properties": { + "enabled": { + "type": "boolean" + }, + "min_number_of_allocations": { + "type": "number" + }, + "max_number_of_allocations": { + "type": "number" + } + }, + "required": [ + "enabled" ] }, "ml._types:TrainedModelDeploymentAllocationStatus": { @@ -76261,6 +76501,12 @@ "average_inference_time_ms": { "$ref": "#/components/schemas/_types:DurationValueUnitFloatMillis" }, + "average_inference_time_ms_last_minute": { + "$ref": "#/components/schemas/_types:DurationValueUnitFloatMillis" + }, + "average_inference_time_ms_excluding_cache_hits": { + "$ref": "#/components/schemas/_types:DurationValueUnitFloatMillis" + }, "error_count": { "description": "The number of errors when evaluating the trained model.", "type": "number" @@ -76269,10 +76515,15 @@ "description": "The total number of inference calls made against this node for this model.", "type": "number" }, - "last_access": { - "description": "The epoch time stamp of the last inference call for the model on this node.", + "inference_cache_hit_count": { "type": "number" }, + "inference_cache_hit_count_last_minute": { + "type": "number" + }, + "last_access": { + "$ref": "#/components/schemas/_types:EpochTimeUnitMillis" + }, "node": { "$ref": "#/components/schemas/ml._types:DiscoveryNode" }, @@ -76284,6 +76535,9 @@ "description": "The number of inference requests queued to be processed.", "type": "number" }, + "peak_throughput_per_minute": { + "type": "number" + }, "rejection_execution_count": { "description": "The number of inference requests that were not processed because the queue was full.", "type": "number" @@ -76298,24 +76552,18 @@ "description": "The number of threads used by each allocation during inference.", "type": "number" }, + "throughput_last_minute": { + "type": "number" + }, "timeout_count": { "description": "The number of inference requests that timed out before being processed.", "type": "number" } }, "required": [ - "average_inference_time_ms", - "error_count", - "inference_count", - "last_access", - "node", - "number_of_allocations", - "number_of_pending_requests", - "rejection_execution_count", + "peak_throughput_per_minute", "routing_state", - "start_time", - "threads_per_allocation", - "timeout_count" + "throughput_last_minute" ] }, "ml._types:TrainedModelAssignmentRoutingTable": { @@ -76338,7 +76586,6 @@ } }, "required": [ - "reason", "routing_state", "current_allocations", "target_allocations" @@ -76354,6 +76601,13 @@ "stopping" ] }, + "ml._types:TrainingPriority": { + "type": "string", + "enum": [ + "normal", + "low" + ] + }, "ml._types:DeploymentAssignmentState": { "type": "string", "enum": [ @@ -76808,18 +77062,23 @@ "ml.info:Limits": { "type": "object", "properties": { + "max_single_ml_node_processors": { + "type": "number" + }, + "total_ml_processors": { + "type": "number" + }, "max_model_memory_limit": { - "type": "string" + "$ref": "#/components/schemas/_types:ByteSize" }, "effective_max_model_memory_limit": { - "type": "string" + "$ref": "#/components/schemas/_types:ByteSize" }, "total_ml_memory": { - "type": "string" + "$ref": "#/components/schemas/_types:ByteSize" } }, "required": [ - "effective_max_model_memory_limit", "total_ml_memory" ] }, @@ -77358,22 +77617,29 @@ "field_names" ] }, - "ml._types:TrainingPriority": { - "type": "string", - "enum": [ - "normal", - "low" - ] - }, "ml._types:TrainedModelAssignment": { "type": "object", "properties": { + "adaptive_allocations": { + "oneOf": [ + { + "$ref": "#/components/schemas/ml._types:AdaptiveAllocationsSettings" + }, + { + "nullable": true, + "type": "string" + } + ] + }, "assignment_state": { "$ref": "#/components/schemas/ml._types:DeploymentAssignmentState" }, "max_assigned_allocations": { "type": "number" }, + "reason": { + "type": "string" + }, "routing_table": { "description": "The allocation state for each node.", "type": "object", @@ -77399,8 +77665,7 @@ "type": "object", "properties": { "model_bytes": { - "description": "The size of the trained model in bytes.", - "type": "number" + "$ref": "#/components/schemas/_types:ByteSize" }, "model_id": { "$ref": "#/components/schemas/_types:Id" @@ -77418,6 +77683,12 @@ "priority": { "$ref": "#/components/schemas/ml._types:TrainingPriority" }, + "per_deployment_memory_bytes": { + "$ref": "#/components/schemas/_types:ByteSize" + }, + "per_allocation_memory_bytes": { + "$ref": "#/components/schemas/_types:ByteSize" + }, "queue_capacity": { "description": "Number of inference requests are allowed in the queue at a time.", "type": "number" @@ -77431,9 +77702,10 @@ "model_bytes", "model_id", "deployment_id", - "cache_size", "number_of_allocations", "priority", + "per_deployment_memory_bytes", + "per_allocation_memory_bytes", "queue_capacity", "threads_per_allocation" ] @@ -77450,6 +77722,29 @@ "model_memory_limit" ] }, + "ml._types:DetectorUpdate": { + "type": "object", + "properties": { + "detector_index": { + "description": "A unique identifier for the detector.\nThis identifier is based on the order of the detectors in the `analysis_config`, starting at zero.", + "type": "number" + }, + "description": { + "description": "A description of the detector.", + "type": "string" + }, + "custom_rules": { + "description": "An array of custom rule objects, which enable you to customize the way detectors operate.\nFor example, a rule may dictate to the detector conditions under which results should be skipped.\nKibana refers to custom rules as job rules.", + "type": "array", + "items": { + "$ref": "#/components/schemas/ml._types:DetectionRule" + } + } + }, + "required": [ + "detector_index" + ] + }, "_global.msearch:MultiSearchResult": { "type": "object", "properties": { @@ -98859,6 +99154,16 @@ }, "style": "form" }, + "ml.get_trained_models#include_model_definition": { + "in": "query", + "name": "include_model_definition", + "description": "parameter is deprecated! Use [include=definition] instead", + "deprecated": true, + "schema": { + "type": "boolean" + }, + "style": "form" + }, "ml.get_trained_models#size": { "in": "query", "name": "size", diff --git a/output/openapi/elasticsearch-serverless-openapi.json b/output/openapi/elasticsearch-serverless-openapi.json index 2f6bbb7420..597cbfcab5 100644 --- a/output/openapi/elasticsearch-serverless-openapi.json +++ b/output/openapi/elasticsearch-serverless-openapi.json @@ -10233,6 +10233,9 @@ "description": "The maximum number of threads to be used by the analysis. Using more\nthreads may decrease the time necessary to complete the analysis at the\ncost of using more CPU. Note that the process may use additional threads\nfor operational functionality other than the analysis itself.", "type": "number" }, + "_meta": { + "$ref": "#/components/schemas/_types:Metadata" + }, "model_memory_limit": { "description": "The approximate maximum amount of memory resources that are permitted for\nanalytical processing. If your `elasticsearch.yml` file contains an\n`xpack.ml.max_model_memory_limit` setting, an error occurs when you try\nto create data frame analytics jobs that have `model_memory_limit` values\ngreater than that setting.", "type": "string" @@ -10292,6 +10295,9 @@ "max_num_threads": { "type": "number" }, + "_meta": { + "$ref": "#/components/schemas/_types:Metadata" + }, "model_memory_limit": { "type": "string" }, @@ -10828,6 +10834,46 @@ "$ref": "#/components/schemas/_types:Id" }, "style": "simple" + }, + { + "in": "query", + "name": "allow_no_indices", + "description": "If `true`, wildcard indices expressions that resolve into no concrete indices are ignored. This includes the\n`_all` string or when no indices are specified.", + "deprecated": false, + "schema": { + "type": "boolean" + }, + "style": "form" + }, + { + "in": "query", + "name": "expand_wildcards", + "description": "Type of index that wildcard patterns can match. If the request can target data streams, this argument determines\nwhether wildcard expressions match hidden data streams. Supports comma-separated values. Valid values are:\n\n* `all`: Match any data stream or index, including hidden ones.\n* `closed`: Match closed, non-hidden indices. Also matches any non-hidden data stream. Data streams cannot be closed.\n* `hidden`: Match hidden data streams and hidden indices. Must be combined with `open`, `closed`, or both.\n* `none`: Wildcard patterns are not accepted.\n* `open`: Match open, non-hidden indices. Also matches any non-hidden data stream.", + "deprecated": false, + "schema": { + "$ref": "#/components/schemas/_types:ExpandWildcards" + }, + "style": "form" + }, + { + "in": "query", + "name": "ignore_throttled", + "description": "If `true`, concrete, expanded or aliased indices are ignored when frozen.", + "deprecated": true, + "schema": { + "type": "boolean" + }, + "style": "form" + }, + { + "in": "query", + "name": "ignore_unavailable", + "description": "If `true`, unavailable indices (missing or closed) are ignored.", + "deprecated": false, + "schema": { + "type": "boolean" + }, + "style": "form" } ], "requestBody": { @@ -10866,6 +10912,9 @@ "description": "A description of the job.", "type": "string" }, + "job_id": { + "$ref": "#/components/schemas/_types:Id" + }, "groups": { "description": "A list of job groups. A job can belong to no groups or many.", "type": "array", @@ -11084,6 +11133,9 @@ { "$ref": "#/components/parameters/ml.get_trained_models#include" }, + { + "$ref": "#/components/parameters/ml.get_trained_models#include_model_definition" + }, { "$ref": "#/components/parameters/ml.get_trained_models#size" }, @@ -12175,6 +12227,9 @@ { "$ref": "#/components/parameters/ml.get_trained_models#include" }, + { + "$ref": "#/components/parameters/ml.get_trained_models#include_model_definition" + }, { "$ref": "#/components/parameters/ml.get_trained_models#size" }, @@ -13760,7 +13815,7 @@ "description": "An array of detector update objects.", "type": "array", "items": { - "$ref": "#/components/schemas/ml._types:Detector" + "$ref": "#/components/schemas/ml._types:DetectorUpdate" } }, "per_partition_categorization": { @@ -49061,6 +49116,9 @@ }, "version": { "$ref": "#/components/schemas/_types:VersionString" + }, + "_meta": { + "$ref": "#/components/schemas/_types:Metadata" } }, "required": [ @@ -49796,8 +49854,7 @@ }, "required": [ "datafeed_id", - "state", - "timing_stats" + "state" ] }, "ml._types:DatafeedTimingStats": { @@ -49810,6 +49867,9 @@ "exponential_average_search_time_per_hour_ms": { "$ref": "#/components/schemas/_types:DurationValueUnitFloatMillis" }, + "exponential_average_calculation_context": { + "$ref": "#/components/schemas/ml._types:ExponentialAverageCalculationContext" + }, "job_id": { "$ref": "#/components/schemas/_types:Id" }, @@ -49843,6 +49903,23 @@ "description": "Time unit for fractional milliseconds", "type": "number" }, + "ml._types:ExponentialAverageCalculationContext": { + "type": "object", + "properties": { + "incremental_metric_value_ms": { + "$ref": "#/components/schemas/_types:DurationValueUnitFloatMillis" + }, + "latest_timestamp": { + "$ref": "#/components/schemas/_types:EpochTimeUnitMillis" + }, + "previous_exponential_average_ms": { + "$ref": "#/components/schemas/_types:DurationValueUnitFloatMillis" + } + }, + "required": [ + "incremental_metric_value_ms" + ] + }, "ml._types:DatafeedRunningState": { "type": "object", "properties": { @@ -50251,6 +50328,9 @@ "model_bytes_memory_limit": { "$ref": "#/components/schemas/_types:ByteSize" }, + "output_memory_allocator_bytes": { + "$ref": "#/components/schemas/_types:ByteSize" + }, "peak_model_bytes": { "$ref": "#/components/schemas/_types:ByteSize" }, @@ -50450,8 +50530,7 @@ "type": "number" }, "model_memory_limit": { - "description": "The approximate maximum amount of memory resources that are required for analytical processing. Once this limit is approached, data pruning becomes more aggressive. Upon exceeding this limit, new entities are not modeled. If the `xpack.ml.max_model_memory_limit` setting has a value greater than 0 and less than 1024mb, that value is used instead of the default. The default value is relatively small to ensure that high resource usage is a conscious decision. If you have jobs that are expected to analyze high cardinality fields, you will likely need to use a higher value. If you specify a number instead of a string, the units are assumed to be MiB. Specifying a string is recommended for clarity. If you specify a byte size unit of `b` or `kb` and the number does not equate to a discrete number of megabytes, it is rounded down to the closest MiB. The minimum valid value is 1 MiB. If you specify a value less than 1 MiB, an error occurs. If you specify a value for the `xpack.ml.max_model_memory_limit` setting, an error occurs when you try to create jobs that have `model_memory_limit` values greater than that setting value.", - "type": "string" + "$ref": "#/components/schemas/_types:ByteSize" } } }, @@ -50554,8 +50633,7 @@ "jobs", "overall_score", "result_type", - "timestamp", - "timestamp_string" + "timestamp" ] }, "_types:DurationValueUnitSeconds": { @@ -50658,6 +50736,9 @@ "model_size_bytes": { "$ref": "#/components/schemas/_types:ByteSize" }, + "model_package": { + "$ref": "#/components/schemas/ml._types:ModelPackageConfig" + }, "location": { "$ref": "#/components/schemas/ml._types:TrainedModelLocation" }, @@ -50747,6 +50828,9 @@ "bert": { "$ref": "#/components/schemas/ml._types:NlpBertTokenizationConfig" }, + "bert_ja": { + "$ref": "#/components/schemas/ml._types:NlpBertTokenizationConfig" + }, "mpnet": { "$ref": "#/components/schemas/ml._types:NlpBertTokenizationConfig" }, @@ -50758,26 +50842,36 @@ "maxProperties": 1 }, "ml._types:NlpBertTokenizationConfig": { + "allOf": [ + { + "$ref": "#/components/schemas/ml._types:CommonTokenizationConfig" + }, + { + "type": "object" + } + ] + }, + "ml._types:CommonTokenizationConfig": { "type": "object", "properties": { "do_lower_case": { "description": "Should the tokenizer lower case the text", "type": "boolean" }, - "with_special_tokens": { - "description": "Is tokenization completed with special tokens", - "type": "boolean" - }, "max_sequence_length": { "description": "Maximum input sequence length for the model", "type": "number" }, - "truncate": { - "$ref": "#/components/schemas/ml._types:TokenizationTruncate" - }, "span": { "description": "Tokenization spanning options. Special value of -1 indicates no spanning takes place", "type": "number" + }, + "truncate": { + "$ref": "#/components/schemas/ml._types:TokenizationTruncate" + }, + "with_special_tokens": { + "description": "Is tokenization completed with special tokens", + "type": "boolean" } } }, @@ -50790,28 +50884,20 @@ ] }, "ml._types:NlpRobertaTokenizationConfig": { - "type": "object", - "properties": { - "add_prefix_space": { - "description": "Should the tokenizer prefix input with a space character", - "type": "boolean" - }, - "with_special_tokens": { - "description": "Is tokenization completed with special tokens", - "type": "boolean" - }, - "max_sequence_length": { - "description": "Maximum input sequence length for the model", - "type": "number" - }, - "truncate": { - "$ref": "#/components/schemas/ml._types:TokenizationTruncate" + "allOf": [ + { + "$ref": "#/components/schemas/ml._types:CommonTokenizationConfig" }, - "span": { - "description": "Tokenization spanning options. Special value of -1 indicates no spanning takes place", - "type": "number" + { + "type": "object", + "properties": { + "add_prefix_space": { + "description": "Should the tokenizer prefix input with a space character", + "type": "boolean" + } + } } - } + ] }, "ml._types:ZeroShotClassificationInferenceOptions": { "type": "object", @@ -50867,8 +50953,25 @@ "results_field": { "description": "The field that is added to incoming documents to contain the inference prediction. Defaults to predicted_value.", "type": "string" + }, + "vocabulary": { + "$ref": "#/components/schemas/ml._types:Vocabulary" } - } + }, + "required": [ + "vocabulary" + ] + }, + "ml._types:Vocabulary": { + "type": "object", + "properties": { + "index": { + "$ref": "#/components/schemas/_types:IndexName" + } + }, + "required": [ + "index" + ] }, "ml._types:NerInferenceOptions": { "type": "object", @@ -50892,17 +50995,6 @@ } } }, - "ml._types:Vocabulary": { - "type": "object", - "properties": { - "index": { - "$ref": "#/components/schemas/_types:IndexName" - } - }, - "required": [ - "index" - ] - }, "ml._types:PassThroughInferenceOptions": { "type": "object", "properties": { @@ -50931,8 +51023,14 @@ "results_field": { "description": "The field that is added to incoming documents to contain the inference prediction. Defaults to predicted_value.", "type": "string" + }, + "vocabulary": { + "$ref": "#/components/schemas/ml._types:Vocabulary" } - } + }, + "required": [ + "vocabulary" + ] }, "ml._types:TextExpansionInferenceOptions": { "type": "object", @@ -50943,8 +51041,14 @@ "results_field": { "description": "The field that is added to incoming documents to contain the inference prediction. Defaults to predicted_value.", "type": "string" + }, + "vocabulary": { + "$ref": "#/components/schemas/ml._types:Vocabulary" } - } + }, + "required": [ + "vocabulary" + ] }, "ml._types:QuestionAnsweringInferenceOptions": { "type": "object", @@ -51110,6 +51214,75 @@ "importance" ] }, + "ml._types:ModelPackageConfig": { + "type": "object", + "properties": { + "create_time": { + "$ref": "#/components/schemas/_types:EpochTimeUnitMillis" + }, + "description": { + "type": "string" + }, + "inference_config": { + "type": "object", + "additionalProperties": { + "type": "object" + } + }, + "metadata": { + "$ref": "#/components/schemas/_types:Metadata" + }, + "minimum_version": { + "type": "string" + }, + "model_repository": { + "type": "string" + }, + "model_type": { + "type": "string" + }, + "packaged_model_id": { + "$ref": "#/components/schemas/_types:Id" + }, + "platform_architecture": { + "type": "string" + }, + "prefix_strings": { + "$ref": "#/components/schemas/ml._types:TrainedModelPrefixStrings" + }, + "size": { + "$ref": "#/components/schemas/_types:ByteSize" + }, + "sha256": { + "type": "string" + }, + "tags": { + "type": "array", + "items": { + "type": "string" + } + }, + "vocabulary_file": { + "type": "string" + } + }, + "required": [ + "packaged_model_id" + ] + }, + "ml._types:TrainedModelPrefixStrings": { + "type": "object", + "properties": { + "ingest": { + "description": "String prepended to input at ingest", + "type": "string" + }, + "search": { + "description": "String prepended to input at search", + "type": "string" + } + } + }, "ml._types:TrainedModelLocation": { "type": "object", "properties": { @@ -51132,19 +51305,6 @@ "name" ] }, - "ml._types:TrainedModelPrefixStrings": { - "type": "object", - "properties": { - "ingest": { - "description": "String prepended to input at ingest", - "type": "string" - }, - "search": { - "description": "String prepended to input at search", - "type": "string" - } - } - }, "ml._types:TrainedModelStats": { "type": "object", "properties": { @@ -51181,6 +51341,9 @@ "ml._types:TrainedModelDeploymentStats": { "type": "object", "properties": { + "adaptive_allocations": { + "$ref": "#/components/schemas/ml._types:AdaptiveAllocationsSettings" + }, "allocation_status": { "$ref": "#/components/schemas/ml._types:TrainedModelDeploymentAllocationStatus" }, @@ -51212,6 +51375,12 @@ "description": "The number of allocations requested.", "type": "number" }, + "peak_throughput_per_minute": { + "type": "number" + }, + "priority": { + "$ref": "#/components/schemas/ml._types:TrainingPriority" + }, "queue_capacity": { "description": "The number of inference requests that can be queued before new requests are rejected.", "type": "number" @@ -51240,20 +51409,29 @@ } }, "required": [ - "allocation_status", "deployment_id", - "error_count", - "inference_count", "model_id", "nodes", - "number_of_allocations", - "queue_capacity", - "rejected_execution_count", - "reason", - "start_time", - "state", - "threads_per_allocation", - "timeout_count" + "peak_throughput_per_minute", + "priority", + "start_time" + ] + }, + "ml._types:AdaptiveAllocationsSettings": { + "type": "object", + "properties": { + "enabled": { + "type": "boolean" + }, + "min_number_of_allocations": { + "type": "number" + }, + "max_number_of_allocations": { + "type": "number" + } + }, + "required": [ + "enabled" ] }, "ml._types:TrainedModelDeploymentAllocationStatus": { @@ -51291,6 +51469,12 @@ "average_inference_time_ms": { "$ref": "#/components/schemas/_types:DurationValueUnitFloatMillis" }, + "average_inference_time_ms_last_minute": { + "$ref": "#/components/schemas/_types:DurationValueUnitFloatMillis" + }, + "average_inference_time_ms_excluding_cache_hits": { + "$ref": "#/components/schemas/_types:DurationValueUnitFloatMillis" + }, "error_count": { "description": "The number of errors when evaluating the trained model.", "type": "number" @@ -51299,10 +51483,15 @@ "description": "The total number of inference calls made against this node for this model.", "type": "number" }, - "last_access": { - "description": "The epoch time stamp of the last inference call for the model on this node.", + "inference_cache_hit_count": { + "type": "number" + }, + "inference_cache_hit_count_last_minute": { "type": "number" }, + "last_access": { + "$ref": "#/components/schemas/_types:EpochTimeUnitMillis" + }, "number_of_allocations": { "description": "The number of allocations assigned to this node.", "type": "number" @@ -51311,6 +51500,9 @@ "description": "The number of inference requests queued to be processed.", "type": "number" }, + "peak_throughput_per_minute": { + "type": "number" + }, "rejection_execution_count": { "description": "The number of inference requests that were not processed because the queue was full.", "type": "number" @@ -51325,23 +51517,18 @@ "description": "The number of threads used by each allocation during inference.", "type": "number" }, + "throughput_last_minute": { + "type": "number" + }, "timeout_count": { "description": "The number of inference requests that timed out before being processed.", "type": "number" } }, "required": [ - "average_inference_time_ms", - "error_count", - "inference_count", - "last_access", - "number_of_allocations", - "number_of_pending_requests", - "rejection_execution_count", + "peak_throughput_per_minute", "routing_state", - "start_time", - "threads_per_allocation", - "timeout_count" + "throughput_last_minute" ] }, "ml._types:TrainedModelAssignmentRoutingTable": { @@ -51364,7 +51551,6 @@ } }, "required": [ - "reason", "routing_state", "current_allocations", "target_allocations" @@ -51380,6 +51566,13 @@ "stopping" ] }, + "ml._types:TrainingPriority": { + "type": "string", + "enum": [ + "normal", + "low" + ] + }, "ml._types:DeploymentAssignmentState": { "type": "string", "enum": [ @@ -52311,22 +52504,29 @@ } ] }, - "ml._types:TrainingPriority": { - "type": "string", - "enum": [ - "normal", - "low" - ] - }, "ml._types:TrainedModelAssignment": { "type": "object", "properties": { + "adaptive_allocations": { + "oneOf": [ + { + "$ref": "#/components/schemas/ml._types:AdaptiveAllocationsSettings" + }, + { + "nullable": true, + "type": "string" + } + ] + }, "assignment_state": { "$ref": "#/components/schemas/ml._types:DeploymentAssignmentState" }, "max_assigned_allocations": { "type": "number" }, + "reason": { + "type": "string" + }, "routing_table": { "description": "The allocation state for each node.", "type": "object", @@ -52352,8 +52552,7 @@ "type": "object", "properties": { "model_bytes": { - "description": "The size of the trained model in bytes.", - "type": "number" + "$ref": "#/components/schemas/_types:ByteSize" }, "model_id": { "$ref": "#/components/schemas/_types:Id" @@ -52371,6 +52570,12 @@ "priority": { "$ref": "#/components/schemas/ml._types:TrainingPriority" }, + "per_deployment_memory_bytes": { + "$ref": "#/components/schemas/_types:ByteSize" + }, + "per_allocation_memory_bytes": { + "$ref": "#/components/schemas/_types:ByteSize" + }, "queue_capacity": { "description": "Number of inference requests are allowed in the queue at a time.", "type": "number" @@ -52384,9 +52589,10 @@ "model_bytes", "model_id", "deployment_id", - "cache_size", "number_of_allocations", "priority", + "per_deployment_memory_bytes", + "per_allocation_memory_bytes", "queue_capacity", "threads_per_allocation" ] @@ -52403,6 +52609,29 @@ "model_memory_limit" ] }, + "ml._types:DetectorUpdate": { + "type": "object", + "properties": { + "detector_index": { + "description": "A unique identifier for the detector.\nThis identifier is based on the order of the detectors in the `analysis_config`, starting at zero.", + "type": "number" + }, + "description": { + "description": "A description of the detector.", + "type": "string" + }, + "custom_rules": { + "description": "An array of custom rule objects, which enable you to customize the way detectors operate.\nFor example, a rule may dictate to the detector conditions under which results should be skipped.\nKibana refers to custom rules as job rules.", + "type": "array", + "items": { + "$ref": "#/components/schemas/ml._types:DetectionRule" + } + } + }, + "required": [ + "detector_index" + ] + }, "_global.msearch:RequestItem": { "oneOf": [ { @@ -60473,6 +60702,16 @@ }, "style": "form" }, + "ml.get_trained_models#include_model_definition": { + "in": "query", + "name": "include_model_definition", + "description": "parameter is deprecated! Use [include=definition] instead", + "deprecated": true, + "schema": { + "type": "boolean" + }, + "style": "form" + }, "ml.get_trained_models#size": { "in": "query", "name": "size", diff --git a/output/schema/schema-serverless.json b/output/schema/schema-serverless.json index 02a0ec82d9..dcee298009 100644 --- a/output/schema/schema-serverless.json +++ b/output/schema/schema-serverless.json @@ -28825,6 +28825,22 @@ } } }, + { + "deprecation": { + "description": "", + "version": "7.10.0" + }, + "description": "parameter is deprecated! Use [include=definition] instead", + "name": "include_model_definition", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "boolean", + "namespace": "_builtins" + } + } + }, { "description": "Specifies the maximum number of models to obtain.", "name": "size", @@ -28866,7 +28882,7 @@ } } ], - "specLocation": "ml/get_trained_models/MlGetTrainedModelRequest.ts#L25-L92" + "specLocation": "ml/get_trained_models/MlGetTrainedModelRequest.ts#L25-L99" }, { "body": { @@ -29816,6 +29832,17 @@ } } }, + { + "name": "_meta", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "Metadata", + "namespace": "_types" + } + } + }, { "description": "The approximate maximum amount of memory resources that are permitted for\nanalytical processing. If your `elasticsearch.yml` file contains an\n`xpack.ml.max_model_memory_limit` setting, an error occurs when you try\nto create data frame analytics jobs that have `model_memory_limit` values\ngreater than that setting.", "name": "model_memory_limit", @@ -29904,7 +29931,7 @@ } ], "query": [], - "specLocation": "ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts#L30-L142" + "specLocation": "ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts#L30-L144" }, { "body": { @@ -30018,6 +30045,17 @@ } } }, + { + "name": "_meta", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "Metadata", + "namespace": "_types" + } + } + }, { "name": "model_memory_limit", "required": true, @@ -30058,7 +30096,7 @@ "name": "Response", "namespace": "ml.put_data_frame_analytics" }, - "specLocation": "ml/put_data_frame_analytics/MlPutDataFrameAnalyticsResponse.ts#L31-L46" + "specLocation": "ml/put_data_frame_analytics/MlPutDataFrameAnalyticsResponse.ts#L31-L47" }, { "attachedBehaviors": [ @@ -30068,6 +30106,9 @@ "kind": "properties", "properties": [ { + "aliases": [ + "aggs" + ], "description": "If set, the datafeed performs aggregation searches.\nSupport for aggregations is limited and should be used only with low cardinality data.", "name": "aggregations", "required": false, @@ -30353,7 +30394,7 @@ } } ], - "specLocation": "ml/put_datafeed/MlPutDatafeedRequest.ts#L37-L173" + "specLocation": "ml/put_datafeed/MlPutDatafeedRequest.ts#L37-L175" }, { "body": { @@ -30789,6 +30830,18 @@ } } }, + { + "description": "The identifier for the anomaly detection job. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters.", + "name": "job_id", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "Id", + "namespace": "_types" + } + } + }, { "description": "A list of job groups. A job can belong to no groups or many.", "name": "groups", @@ -30894,8 +30947,65 @@ } } ], - "query": [], - "specLocation": "ml/put_job/MlPutJobRequest.ts#L30-L113" + "query": [ + { + "description": "If `true`, wildcard indices expressions that resolve into no concrete indices are ignored. This includes the\n`_all` string or when no indices are specified.", + "name": "allow_no_indices", + "required": false, + "serverDefault": true, + "type": { + "kind": "instance_of", + "type": { + "name": "boolean", + "namespace": "_builtins" + } + } + }, + { + "description": "Type of index that wildcard patterns can match. If the request can target data streams, this argument determines\nwhether wildcard expressions match hidden data streams. Supports comma-separated values. Valid values are:\n\n* `all`: Match any data stream or index, including hidden ones.\n* `closed`: Match closed, non-hidden indices. Also matches any non-hidden data stream. Data streams cannot be closed.\n* `hidden`: Match hidden data streams and hidden indices. Must be combined with `open`, `closed`, or both.\n* `none`: Wildcard patterns are not accepted.\n* `open`: Match open, non-hidden indices. Also matches any non-hidden data stream.", + "name": "expand_wildcards", + "required": false, + "serverDefault": "open", + "type": { + "kind": "instance_of", + "type": { + "name": "ExpandWildcards", + "namespace": "_types" + } + } + }, + { + "deprecation": { + "description": "", + "version": "7.16.0" + }, + "description": "If `true`, concrete, expanded or aliased indices are ignored when frozen.", + "name": "ignore_throttled", + "required": false, + "serverDefault": true, + "type": { + "kind": "instance_of", + "type": { + "name": "boolean", + "namespace": "_builtins" + } + } + }, + { + "description": "If `true`, unavailable indices (missing or closed) are ignored.", + "name": "ignore_unavailable", + "required": false, + "serverDefault": false, + "type": { + "kind": "instance_of", + "type": { + "name": "boolean", + "namespace": "_builtins" + } + } + } + ], + "specLocation": "ml/put_job/MlPutJobRequest.ts#L30-L148" }, { "body": { @@ -33497,7 +33607,7 @@ "value": { "kind": "instance_of", "type": { - "name": "Detector", + "name": "DetectorUpdate", "namespace": "ml._types" } } @@ -95008,7 +95118,7 @@ "name": "CategorizationStatus", "namespace": "ml._types" }, - "specLocation": "ml/_types/Model.ts#L83-L86" + "specLocation": "ml/_types/Model.ts#L84-L87" }, { "kind": "enum", @@ -95027,7 +95137,7 @@ "name": "ChunkingMode", "namespace": "ml._types" }, - "specLocation": "ml/_types/Datafeed.ts#L235-L239" + "specLocation": "ml/_types/Datafeed.ts#L245-L249" }, { "kind": "enum", @@ -95083,7 +95193,7 @@ "name": "DatafeedState", "namespace": "ml._types" }, - "specLocation": "ml/_types/Datafeed.ts#L135-L140" + "specLocation": "ml/_types/Datafeed.ts#L136-L141" }, { "kind": "enum", @@ -95130,7 +95240,7 @@ "name": "DeploymentAllocationState", "namespace": "ml._types" }, - "specLocation": "ml/_types/TrainedModel.ts#L273-L286" + "specLocation": "ml/_types/TrainedModel.ts#L318-L331" }, { "kind": "enum", @@ -95156,7 +95266,156 @@ "name": "DeploymentAssignmentState", "namespace": "ml._types" }, - "specLocation": "ml/_types/TrainedModel.ts#L288-L305" + "specLocation": "ml/_types/TrainedModel.ts#L333-L350" + }, + { + "kind": "type_alias", + "name": { + "name": "DiscoveryNode", + "namespace": "ml._types" + }, + "specLocation": "ml/_types/DiscoveryNode.ts#L25-L25", + "type": { + "key": { + "kind": "instance_of", + "type": { + "name": "Id", + "namespace": "_types" + } + }, + "kind": "dictionary_of", + "singleKey": true, + "value": { + "kind": "instance_of", + "type": { + "name": "DiscoveryNodeContent", + "namespace": "ml._types" + } + } + } + }, + { + "kind": "interface", + "name": { + "name": "DiscoveryNodeContent", + "namespace": "ml._types" + }, + "properties": [ + { + "name": "name", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "Name", + "namespace": "_types" + } + } + }, + { + "name": "ephemeral_id", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "Id", + "namespace": "_types" + } + } + }, + { + "name": "transport_address", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "TransportAddress", + "namespace": "_types" + } + } + }, + { + "name": "external_id", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, + { + "name": "attributes", + "required": true, + "type": { + "key": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + }, + "kind": "dictionary_of", + "singleKey": false, + "value": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + } + }, + { + "name": "roles", + "required": true, + "type": { + "kind": "array_of", + "value": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + } + }, + { + "name": "version", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "VersionString", + "namespace": "_types" + } + } + }, + { + "name": "min_index_version", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "integer", + "namespace": "_types" + } + } + }, + { + "name": "max_index_version", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "integer", + "namespace": "_types" + } + } + } + ], + "specLocation": "ml/_types/DiscoveryNode.ts#L27-L37" }, { "kind": "enum", @@ -95178,7 +95437,7 @@ "name": "ExcludeFrequent", "namespace": "ml._types" }, - "specLocation": "ml/_types/Detector.ts#L127-L132" + "specLocation": "ml/_types/Detector.ts#L145-L150" }, { "kind": "enum", @@ -95292,7 +95551,7 @@ "name": "MemoryStatus", "namespace": "ml._types" }, - "specLocation": "ml/_types/Model.ts#L88-L92" + "specLocation": "ml/_types/Model.ts#L89-L93" }, { "kind": "type_alias", @@ -95300,7 +95559,7 @@ "name": "PredictedValue", "namespace": "ml._types" }, - "specLocation": "ml/_types/inference.ts#L457-L457", + "specLocation": "ml/_types/inference.ts#L445-L445", "type": { "items": [ { @@ -95352,7 +95611,7 @@ "name": "RoutingState", "namespace": "ml._types" }, - "specLocation": "ml/_types/TrainedModel.ts#L347-L368" + "specLocation": "ml/_types/TrainedModel.ts#L395-L416" }, { "kind": "enum", @@ -95392,7 +95651,7 @@ "name": "SnapshotUpgradeState", "namespace": "ml._types" }, - "specLocation": "ml/_types/Model.ts#L94-L99" + "specLocation": "ml/_types/Model.ts#L95-L100" }, { "kind": "enum", @@ -95411,7 +95670,7 @@ "name": "TokenizationTruncate", "namespace": "ml._types" }, - "specLocation": "ml/_types/inference.ts#L350-L354" + "specLocation": "ml/_types/inference.ts#L338-L342" }, { "kind": "enum", @@ -95433,7 +95692,7 @@ "name": "TrainedModelType", "namespace": "ml._types" }, - "specLocation": "ml/_types/TrainedModel.ts#L257-L271" + "specLocation": "ml/_types/TrainedModel.ts#L302-L316" }, { "kind": "enum", @@ -95449,7 +95708,7 @@ "name": "TrainingPriority", "namespace": "ml._types" }, - "specLocation": "ml/_types/TrainedModel.ts#L307-L310" + "specLocation": "ml/_types/TrainedModel.ts#L352-L355" }, { "codegenNames": [ @@ -128494,9 +128753,20 @@ "namespace": "_types" } } + }, + { + "name": "_meta", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "Metadata", + "namespace": "_types" + } + } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L305-L321" + "specLocation": "ml/_types/DataframeAnalytics.ts#L306-L323" }, { "kind": "interface", @@ -128548,7 +128818,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L83-L100", + "specLocation": "ml/_types/DataframeAnalytics.ts#L84-L101", "variants": { "kind": "container" } @@ -128591,7 +128861,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L226-L235" + "specLocation": "ml/_types/DataframeAnalytics.ts#L227-L236" }, { "kind": "interface", @@ -128826,7 +129096,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L133-L212" + "specLocation": "ml/_types/DataframeAnalytics.ts#L134-L213" }, { "kind": "interface", @@ -128896,7 +129166,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L245-L257", + "specLocation": "ml/_types/DataframeAnalytics.ts#L246-L258", "variants": { "kind": "container" } @@ -128955,7 +129225,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L259-L266" + "specLocation": "ml/_types/DataframeAnalytics.ts#L260-L267" }, { "kind": "interface", @@ -128980,7 +129250,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L268-L271" + "specLocation": "ml/_types/DataframeAnalytics.ts#L269-L272" }, { "kind": "interface", @@ -129064,7 +129334,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L273-L285" + "specLocation": "ml/_types/DataframeAnalytics.ts#L274-L286" }, { "kind": "interface", @@ -129098,7 +129368,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L287-L292" + "specLocation": "ml/_types/DataframeAnalytics.ts#L288-L293" }, { "kind": "interface", @@ -129163,7 +129433,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L294-L303" + "specLocation": "ml/_types/DataframeAnalytics.ts#L295-L304" }, { "kind": "interface", @@ -129249,7 +129519,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L102-L131" + "specLocation": "ml/_types/DataframeAnalytics.ts#L103-L132" }, { "inherits": { @@ -129290,7 +129560,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L214-L224" + "specLocation": "ml/_types/DataframeAnalytics.ts#L215-L225" }, { "kind": "interface", @@ -129331,7 +129601,7 @@ } ], "shortcutProperty": "includes", - "specLocation": "ml/_types/DataframeAnalytics.ts#L237-L243" + "specLocation": "ml/_types/DataframeAnalytics.ts#L238-L244" }, { "kind": "interface", @@ -129448,7 +129718,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L76-L81" + "specLocation": "ml/_types/DataframeAnalytics.ts#L77-L82" }, { "kind": "interface", @@ -129508,7 +129778,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L38-L52" + "specLocation": "ml/_types/DataframeAnalytics.ts#L39-L53" }, { "kind": "interface", @@ -129605,7 +129875,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L323-L343" + "specLocation": "ml/_types/DataframeAnalytics.ts#L325-L345" }, { "kind": "interface", @@ -129651,7 +129921,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L372-L380", + "specLocation": "ml/_types/DataframeAnalytics.ts#L374-L382", "variants": { "kind": "container" } @@ -129733,7 +130003,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L382-L401" + "specLocation": "ml/_types/DataframeAnalytics.ts#L384-L403" }, { "kind": "interface", @@ -129911,7 +130181,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L418-L524" + "specLocation": "ml/_types/DataframeAnalytics.ts#L420-L526" }, { "kind": "interface", @@ -129963,7 +130233,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L562-L567" + "specLocation": "ml/_types/DataframeAnalytics.ts#L564-L569" }, { "kind": "interface", @@ -130000,7 +130270,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L569-L574" + "specLocation": "ml/_types/DataframeAnalytics.ts#L571-L576" }, { "kind": "interface", @@ -130055,7 +130325,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L403-L416" + "specLocation": "ml/_types/DataframeAnalytics.ts#L405-L418" }, { "kind": "interface", @@ -130140,7 +130410,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L526-L560" + "specLocation": "ml/_types/DataframeAnalytics.ts#L528-L562" }, { "kind": "interface", @@ -130186,7 +130456,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L363-L370" + "specLocation": "ml/_types/DataframeAnalytics.ts#L365-L372" }, { "kind": "interface", @@ -130253,7 +130523,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L352-L361" + "specLocation": "ml/_types/DataframeAnalytics.ts#L354-L363" }, { "kind": "interface", @@ -130287,7 +130557,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L345-L350" + "specLocation": "ml/_types/DataframeAnalytics.ts#L347-L352" }, { "kind": "interface", @@ -130335,7 +130605,7 @@ { "description": "An object that provides statistical information about timing aspect of this datafeed.", "name": "timing_stats", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -130357,7 +130627,7 @@ } } ], - "specLocation": "ml/_types/Datafeed.ts#L142-L171" + "specLocation": "ml/_types/Datafeed.ts#L143-L172" }, { "kind": "interface", @@ -130399,6 +130669,17 @@ } } }, + { + "name": "exponential_average_calculation_context", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "ExponentialAverageCalculationContext", + "namespace": "ml._types" + } + } + }, { "description": "Identifier for the anomaly detection job.", "name": "job_id", @@ -130466,7 +130747,77 @@ } } ], - "specLocation": "ml/_types/Datafeed.ts#L173-L198" + "specLocation": "ml/_types/Datafeed.ts#L174-L202" + }, + { + "kind": "interface", + "name": { + "name": "ExponentialAverageCalculationContext", + "namespace": "ml._types" + }, + "properties": [ + { + "name": "incremental_metric_value_ms", + "required": true, + "type": { + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitFloatMillis", + "namespace": "_types" + } + } + ], + "kind": "instance_of", + "type": { + "name": "DurationValue", + "namespace": "_types" + } + } + }, + { + "name": "latest_timestamp", + "required": false, + "type": { + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitMillis", + "namespace": "_types" + } + } + ], + "kind": "instance_of", + "type": { + "name": "EpochTime", + "namespace": "_types" + } + } + }, + { + "name": "previous_exponential_average_ms", + "required": false, + "type": { + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitFloatMillis", + "namespace": "_types" + } + } + ], + "kind": "instance_of", + "type": { + "name": "DurationValue", + "namespace": "_types" + } + } + } + ], + "specLocation": "ml/_types/Datafeed.ts#L204-L208" }, { "kind": "interface", @@ -130512,7 +130863,7 @@ } } ], - "specLocation": "ml/_types/Datafeed.ts#L200-L214" + "specLocation": "ml/_types/Datafeed.ts#L210-L224" }, { "kind": "interface", @@ -130588,7 +130939,7 @@ } } ], - "specLocation": "ml/_types/Datafeed.ts#L216-L233" + "specLocation": "ml/_types/Datafeed.ts#L226-L243" }, { "kind": "interface", @@ -130808,7 +131159,7 @@ } } ], - "specLocation": "ml/_types/Datafeed.ts#L36-L60" + "specLocation": "ml/_types/Datafeed.ts#L37-L61" }, { "kind": "interface", @@ -130892,7 +131243,7 @@ } } ], - "specLocation": "ml/_types/Datafeed.ts#L241-L254" + "specLocation": "ml/_types/Datafeed.ts#L251-L264" }, { "kind": "interface", @@ -130926,7 +131277,7 @@ } } ], - "specLocation": "ml/_types/Datafeed.ts#L121-L132" + "specLocation": "ml/_types/Datafeed.ts#L122-L133" }, { "description": "Controls how to deal with unavailable concrete indices (closed or missing), how wildcard expressions are expanded\nto actual indices (all, closed or open indices) and how to deal with wildcard expressions that resolve to no indices.", @@ -131600,6 +131951,17 @@ } } }, + { + "name": "output_memory_allocator_bytes", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "ByteSize", + "namespace": "_types" + } + } + }, { "name": "peak_model_bytes", "required": false, @@ -131755,7 +132117,7 @@ } } ], - "specLocation": "ml/_types/Model.ts#L59-L81" + "specLocation": "ml/_types/Model.ts#L59-L82" }, { "kind": "interface", @@ -132224,8 +132586,8 @@ "type": { "kind": "instance_of", "type": { - "name": "string", - "namespace": "_builtins" + "name": "ByteSize", + "namespace": "_types" } } } @@ -132486,7 +132848,7 @@ { "description": "The start time of the bucket for which these results were calculated.", "name": "timestamp_string", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -132753,6 +133115,17 @@ } } }, + { + "name": "model_package", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "ModelPackageConfig", + "namespace": "ml._types" + } + } + }, { "name": "location", "required": false, @@ -132776,7 +133149,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L164-L199" + "specLocation": "ml/_types/TrainedModel.ts#L191-L227" }, { "description": "Inference configuration provided when storing the model config", @@ -133020,7 +133393,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L189-L199" + "specLocation": "ml/_types/inference.ts#L173-L183" }, { "description": "Tokenization options stored in inference configuration", @@ -133042,6 +133415,18 @@ } } }, + { + "description": "Indicates BERT Japanese tokenization and its options", + "name": "bert_ja", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "NlpBertTokenizationConfig", + "namespace": "ml._types" + } + } + }, { "availability": { "serverless": {}, @@ -133079,18 +133464,33 @@ } } ], - "specLocation": "ml/_types/inference.ts#L110-L129", + "specLocation": "ml/_types/inference.ts#L110-L131", "variants": { "kind": "container" } }, { "description": "BERT and MPNet tokenization configuration options", + "inherits": { + "type": { + "name": "CommonTokenizationConfig", + "namespace": "ml._types" + } + }, "kind": "interface", "name": { "name": "NlpBertTokenizationConfig", "namespace": "ml._types" }, + "properties": [], + "specLocation": "ml/_types/inference.ts#L161-L162" + }, + { + "kind": "interface", + "name": { + "name": "CommonTokenizationConfig", + "namespace": "ml._types" + }, "properties": [ { "description": "Should the tokenizer lower case the text", @@ -133106,23 +133506,23 @@ } }, { - "description": "Is tokenization completed with special tokens", - "name": "with_special_tokens", + "description": "Maximum input sequence length for the model", + "name": "max_sequence_length", "required": false, - "serverDefault": true, + "serverDefault": 512, "type": { "kind": "instance_of", "type": { - "name": "boolean", - "namespace": "_builtins" + "name": "integer", + "namespace": "_types" } } }, { - "description": "Maximum input sequence length for the model", - "name": "max_sequence_length", + "description": "Tokenization spanning options. Special value of -1 indicates no spanning takes place", + "name": "span", "required": false, - "serverDefault": 512, + "serverDefault": -1, "type": { "kind": "instance_of", "type": { @@ -133145,23 +133545,29 @@ } }, { - "description": "Tokenization spanning options. Special value of -1 indicates no spanning takes place", - "name": "span", + "description": "Is tokenization completed with special tokens", + "name": "with_special_tokens", "required": false, - "serverDefault": -1, + "serverDefault": true, "type": { "kind": "instance_of", "type": { - "name": "integer", - "namespace": "_types" + "name": "boolean", + "namespace": "_builtins" } } } ], - "specLocation": "ml/_types/inference.ts#L131-L158" + "specLocation": "ml/_types/inference.ts#L133-L159" }, { "description": "RoBERTa tokenization configuration options", + "inherits": { + "type": { + "name": "CommonTokenizationConfig", + "namespace": "ml._types" + } + }, "kind": "interface", "name": { "name": "NlpRobertaTokenizationConfig", @@ -133180,61 +133586,9 @@ "namespace": "_builtins" } } - }, - { - "description": "Is tokenization completed with special tokens", - "name": "with_special_tokens", - "required": false, - "serverDefault": true, - "type": { - "kind": "instance_of", - "type": { - "name": "boolean", - "namespace": "_builtins" - } - } - }, - { - "description": "Maximum input sequence length for the model", - "name": "max_sequence_length", - "required": false, - "serverDefault": 512, - "type": { - "kind": "instance_of", - "type": { - "name": "integer", - "namespace": "_types" - } - } - }, - { - "description": "Should tokenization input be automatically truncated before sending to the model for inference", - "name": "truncate", - "required": false, - "serverDefault": "first", - "type": { - "kind": "instance_of", - "type": { - "name": "TokenizationTruncate", - "namespace": "ml._types" - } - } - }, - { - "description": "Tokenization spanning options. Special value of -1 indicates no spanning takes place", - "name": "span", - "required": false, - "serverDefault": -1, - "type": { - "kind": "instance_of", - "type": { - "name": "integer", - "namespace": "_types" - } - } } ], - "specLocation": "ml/_types/inference.ts#L160-L187" + "specLocation": "ml/_types/inference.ts#L164-L171" }, { "description": "Zero shot classification configuration options", @@ -133325,7 +133679,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L201-L222" + "specLocation": "ml/_types/inference.ts#L185-L206" }, { "description": "Fill mask inference options", @@ -133382,9 +133736,41 @@ "namespace": "_builtins" } } + }, + { + "name": "vocabulary", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "Vocabulary", + "namespace": "ml._types" + } + } + } + ], + "specLocation": "ml/_types/inference.ts#L253-L268" + }, + { + "kind": "interface", + "name": { + "name": "Vocabulary", + "namespace": "ml._types" + }, + "properties": [ + { + "name": "index", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "IndexName", + "namespace": "_types" + } + } } ], - "specLocation": "ml/_types/inference.ts#L266-L280" + "specLocation": "ml/_types/inference.ts#L217-L219" }, { "description": "Named entity recognition options", @@ -133445,28 +133831,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L255-L264" - }, - { - "kind": "interface", - "name": { - "name": "Vocabulary", - "namespace": "ml._types" - }, - "properties": [ - { - "name": "index", - "required": true, - "type": { - "kind": "instance_of", - "type": { - "name": "IndexName", - "namespace": "_types" - } - } - } - ], - "specLocation": "ml/_types/inference.ts#L233-L235" + "specLocation": "ml/_types/inference.ts#L242-L251" }, { "description": "Pass through configuration options", @@ -133512,7 +133877,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L224-L231" + "specLocation": "ml/_types/inference.ts#L208-L215" }, { "description": "Text embedding inference options", @@ -133557,9 +133922,20 @@ "namespace": "_builtins" } } + }, + { + "name": "vocabulary", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "Vocabulary", + "namespace": "ml._types" + } + } } ], - "specLocation": "ml/_types/inference.ts#L237-L245" + "specLocation": "ml/_types/inference.ts#L221-L231" }, { "description": "Text expansion inference options", @@ -133592,9 +133968,20 @@ "namespace": "_builtins" } } + }, + { + "name": "vocabulary", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "Vocabulary", + "namespace": "ml._types" + } + } } ], - "specLocation": "ml/_types/inference.ts#L247-L253" + "specLocation": "ml/_types/inference.ts#L233-L240" }, { "description": "Question answering inference options", @@ -133653,7 +134040,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L282-L292" + "specLocation": "ml/_types/inference.ts#L270-L280" }, { "kind": "interface", @@ -133678,7 +134065,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L201-L204" + "specLocation": "ml/_types/TrainedModel.ts#L229-L232" }, { "kind": "interface", @@ -133755,7 +134142,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L206-L214" + "specLocation": "ml/_types/TrainedModel.ts#L234-L242" }, { "kind": "interface", @@ -133827,7 +134214,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L216-L230" + "specLocation": "ml/_types/TrainedModel.ts#L261-L275" }, { "kind": "interface", @@ -133879,7 +134266,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L232-L239" + "specLocation": "ml/_types/TrainedModel.ts#L277-L284" }, { "kind": "interface", @@ -133925,7 +134312,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L248-L255" + "specLocation": "ml/_types/TrainedModel.ts#L293-L300" }, { "kind": "interface", @@ -133962,49 +134349,190 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L241-L246" + "specLocation": "ml/_types/TrainedModel.ts#L286-L291" }, { "kind": "interface", "name": { - "name": "TrainedModelLocation", + "name": "ModelPackageConfig", "namespace": "ml._types" }, "properties": [ { - "name": "index", + "name": "create_time", + "required": false, + "type": { + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitMillis", + "namespace": "_types" + } + } + ], + "kind": "instance_of", + "type": { + "name": "EpochTime", + "namespace": "_types" + } + } + }, + { + "name": "description", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, + { + "name": "inference_config", + "required": false, + "type": { + "key": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + }, + "kind": "dictionary_of", + "singleKey": false, + "value": { + "kind": "user_defined_value" + } + } + }, + { + "name": "metadata", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "Metadata", + "namespace": "_types" + } + } + }, + { + "name": "minimum_version", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, + { + "name": "model_repository", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, + { + "name": "model_type", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, + { + "name": "packaged_model_id", "required": true, "type": { "kind": "instance_of", "type": { - "name": "TrainedModelLocationIndex", + "name": "Id", + "namespace": "_types" + } + } + }, + { + "name": "platform_architecture", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, + { + "name": "prefix_strings", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "TrainedModelPrefixStrings", "namespace": "ml._types" } } - } - ], - "specLocation": "ml/_types/TrainedModel.ts#L416-L418" - }, - { - "kind": "interface", - "name": { - "name": "TrainedModelLocationIndex", - "namespace": "ml._types" - }, - "properties": [ + }, { - "name": "name", - "required": true, + "name": "size", + "required": false, "type": { "kind": "instance_of", "type": { - "name": "IndexName", + "name": "ByteSize", "namespace": "_types" } } + }, + { + "name": "sha256", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, + { + "name": "tags", + "required": false, + "type": { + "kind": "array_of", + "value": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + } + }, + { + "name": "vocabulary_file", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } } ], - "specLocation": "ml/_types/TrainedModel.ts#L420-L422" + "specLocation": "ml/_types/TrainedModel.ts#L244-L259" }, { "kind": "interface", @@ -134038,7 +134566,49 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L424-L433" + "specLocation": "ml/_types/TrainedModel.ts#L474-L483" + }, + { + "kind": "interface", + "name": { + "name": "TrainedModelLocation", + "namespace": "ml._types" + }, + "properties": [ + { + "name": "index", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "TrainedModelLocationIndex", + "namespace": "ml._types" + } + } + } + ], + "specLocation": "ml/_types/TrainedModel.ts#L466-L468" + }, + { + "kind": "interface", + "name": { + "name": "TrainedModelLocationIndex", + "namespace": "ml._types" + }, + "properties": [ + { + "name": "name", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "IndexName", + "namespace": "_types" + } + } + } + ], + "specLocation": "ml/_types/TrainedModel.ts#L470-L472" }, { "kind": "interface", @@ -134129,7 +134699,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L41-L59" + "specLocation": "ml/_types/TrainedModel.ts#L42-L60" }, { "kind": "interface", @@ -134138,10 +134708,21 @@ "namespace": "ml._types" }, "properties": [ + { + "name": "adaptive_allocations", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "AdaptiveAllocationsSettings", + "namespace": "ml._types" + } + } + }, { "description": "The detailed allocation status for the deployment.", "name": "allocation_status", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -134176,7 +134757,7 @@ { "description": "The sum of `error_count` for all nodes in the deployment.", "name": "error_count", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -134188,7 +134769,7 @@ { "description": "The sum of `inference_count` for all nodes in the deployment.", "name": "inference_count", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -134227,7 +134808,7 @@ { "description": "The number of allocations requested.", "name": "number_of_allocations", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -134236,10 +134817,32 @@ } } }, + { + "name": "peak_throughput_per_minute", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "long", + "namespace": "_types" + } + } + }, + { + "name": "priority", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "TrainingPriority", + "namespace": "ml._types" + } + } + }, { "description": "The number of inference requests that can be queued before new requests are rejected.", "name": "queue_capacity", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -134251,7 +134854,7 @@ { "description": "The sum of `rejected_execution_count` for all nodes in the deployment.\nIndividual nodes reject an inference request if the inference queue is full.\nThe queue size is controlled by the `queue_capacity` setting in the start\ntrained model deployment API.", "name": "rejected_execution_count", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -134263,7 +134866,7 @@ { "description": "The reason for the current deployment state. Usually only populated when\nthe model is not deployed to a node.", "name": "reason", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -134296,7 +134899,7 @@ { "description": "The overall state of the deployment.", "name": "state", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -134308,7 +134911,7 @@ { "description": "The number of threads used be each allocation during inference.", "name": "threads_per_allocation", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -134320,7 +134923,50 @@ { "description": "The sum of `timeout_count` for all nodes in the deployment.", "name": "timeout_count", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "integer", + "namespace": "_types" + } + } + } + ], + "specLocation": "ml/_types/TrainedModel.ts#L62-L107" + }, + { + "kind": "interface", + "name": { + "name": "AdaptiveAllocationsSettings", + "namespace": "ml._types" + }, + "properties": [ + { + "name": "enabled", "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "boolean", + "namespace": "_builtins" + } + } + }, + { + "name": "min_number_of_allocations", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "integer", + "namespace": "_types" + } + } + }, + { + "name": "max_number_of_allocations", + "required": false, "type": { "kind": "instance_of", "type": { @@ -134330,7 +134976,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L61-L101" + "specLocation": "ml/_types/TrainedModel.ts#L109-L113" }, { "kind": "interface", @@ -134376,7 +135022,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L390-L397" + "specLocation": "ml/_types/TrainedModel.ts#L438-L445" }, { "kind": "interface", @@ -134388,7 +135034,48 @@ { "description": "The average time for each inference call to complete on this node.", "name": "average_inference_time_ms", - "required": true, + "required": false, + "type": { + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitFloatMillis", + "namespace": "_types" + } + } + ], + "kind": "instance_of", + "type": { + "name": "DurationValue", + "namespace": "_types" + } + } + }, + { + "name": "average_inference_time_ms_last_minute", + "required": false, + "type": { + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitFloatMillis", + "namespace": "_types" + } + } + ], + "kind": "instance_of", + "type": { + "name": "DurationValue", + "namespace": "_types" + } + } + }, + { + "description": "The average time for each inference call to complete on this node, excluding cache", + "name": "average_inference_time_ms_excluding_cache_hits", + "required": false, "type": { "generics": [ { @@ -134409,7 +135096,7 @@ { "description": "The number of errors when evaluating the trained model.", "name": "error_count", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -134421,11 +135108,33 @@ { "description": "The total number of inference calls made against this node for this model.", "name": "inference_count", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { - "name": "integer", + "name": "long", + "namespace": "_types" + } + } + }, + { + "name": "inference_cache_hit_count", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "long", + "namespace": "_types" + } + } + }, + { + "name": "inference_cache_hit_count_last_minute", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "long", "namespace": "_types" } } @@ -134433,11 +135142,20 @@ { "description": "The epoch time stamp of the last inference call for the model on this node.", "name": "last_access", - "required": true, + "required": false, "type": { + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitMillis", + "namespace": "_types" + } + } + ], "kind": "instance_of", "type": { - "name": "long", + "name": "EpochTime", "namespace": "_types" } } @@ -134445,7 +135163,7 @@ { "description": "The number of allocations assigned to this node.", "name": "number_of_allocations", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -134457,7 +135175,7 @@ { "description": "The number of inference requests queued to be processed.", "name": "number_of_pending_requests", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -134466,10 +135184,21 @@ } } }, + { + "name": "peak_throughput_per_minute", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "long", + "namespace": "_types" + } + } + }, { "description": "The number of inference requests that were not processed because the queue was full.", "name": "rejection_execution_count", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -134493,7 +135222,7 @@ { "description": "The epoch timestamp when the allocation started.", "name": "start_time", - "required": true, + "required": false, "type": { "generics": [ { @@ -134514,6 +135243,17 @@ { "description": "The number of threads used by each allocation during inference.", "name": "threads_per_allocation", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "integer", + "namespace": "_types" + } + } + }, + { + "name": "throughput_last_minute", "required": true, "type": { "kind": "instance_of", @@ -134526,7 +135266,7 @@ { "description": "The number of inference requests that timed out before being processed.", "name": "timeout_count", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -134536,7 +135276,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L132-L162" + "specLocation": "ml/_types/TrainedModel.ts#L144-L189" }, { "kind": "interface", @@ -134548,7 +135288,7 @@ { "description": "The reason for the current state. It is usually populated only when the\n`routing_state` is `failed`.", "name": "reason", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -134594,7 +135334,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L370-L388" + "specLocation": "ml/_types/TrainedModel.ts#L418-L436" }, { "kind": "interface", @@ -134675,7 +135415,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L103-L123" + "specLocation": "ml/_types/TrainedModel.ts#L115-L135" }, { "kind": "interface", @@ -134709,7 +135449,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L125-L130" + "specLocation": "ml/_types/TrainedModel.ts#L137-L142" }, { "kind": "interface", @@ -134839,7 +135579,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L296-L318", + "specLocation": "ml/_types/inference.ts#L284-L306", "variants": { "kind": "container" } @@ -134903,7 +135643,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L363-L372" + "specLocation": "ml/_types/inference.ts#L351-L360" }, { "kind": "interface", @@ -134937,7 +135677,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L356-L361" + "specLocation": "ml/_types/inference.ts#L344-L349" }, { "kind": "interface", @@ -134998,7 +135738,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L374-L383" + "specLocation": "ml/_types/inference.ts#L362-L371" }, { "kind": "interface", @@ -135044,7 +135784,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L411-L418" + "specLocation": "ml/_types/inference.ts#L399-L406" }, { "kind": "interface", @@ -135078,7 +135818,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L404-L409" + "specLocation": "ml/_types/inference.ts#L392-L397" }, { "kind": "interface", @@ -135112,7 +135852,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L385-L390" + "specLocation": "ml/_types/inference.ts#L373-L378" }, { "kind": "interface", @@ -135145,7 +135885,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L392-L396" + "specLocation": "ml/_types/inference.ts#L380-L384" }, { "kind": "interface", @@ -135178,7 +135918,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L398-L402" + "specLocation": "ml/_types/inference.ts#L386-L390" }, { "kind": "interface", @@ -135248,7 +135988,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L420-L431" + "specLocation": "ml/_types/inference.ts#L408-L419" }, { "kind": "interface", @@ -135390,7 +136130,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L459-L507" + "specLocation": "ml/_types/inference.ts#L447-L495" }, { "kind": "interface", @@ -135455,7 +136195,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L433-L439" + "specLocation": "ml/_types/inference.ts#L421-L427" }, { "kind": "interface", @@ -135498,7 +136238,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L440-L444" + "specLocation": "ml/_types/inference.ts#L428-L432" }, { "kind": "interface", @@ -135544,7 +136284,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L451-L455" + "specLocation": "ml/_types/inference.ts#L439-L443" }, { "kind": "interface", @@ -135576,7 +136316,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L446-L449" + "specLocation": "ml/_types/inference.ts#L434-L437" }, { "kind": "interface", @@ -135847,7 +136587,7 @@ } } ], - "specLocation": "ml/_types/Datafeed.ts#L62-L119" + "specLocation": "ml/_types/Datafeed.ts#L63-L120" }, { "kind": "interface", @@ -137057,6 +137797,29 @@ "namespace": "ml._types" }, "properties": [ + { + "name": "adaptive_allocations", + "required": false, + "type": { + "items": [ + { + "kind": "instance_of", + "type": { + "name": "AdaptiveAllocationsSettings", + "namespace": "ml._types" + } + }, + { + "kind": "instance_of", + "type": { + "name": "null", + "namespace": "_builtins" + } + } + ], + "kind": "union_of" + } + }, { "description": "The overall assignment state.", "name": "assignment_state", @@ -137080,6 +137843,17 @@ } } }, + { + "name": "reason", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, { "description": "The allocation state for each node.", "name": "routing_table", @@ -137127,7 +137901,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L399-L414" + "specLocation": "ml/_types/TrainedModel.ts#L447-L464" }, { "kind": "interface", @@ -137143,7 +137917,7 @@ "type": { "kind": "instance_of", "type": { - "name": "integer", + "name": "ByteSize", "namespace": "_types" } } @@ -137181,7 +137955,7 @@ }, "description": "The size of the trained model cache.", "name": "cache_size", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -137213,6 +137987,28 @@ } } }, + { + "name": "per_deployment_memory_bytes", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "ByteSize", + "namespace": "_types" + } + } + }, + { + "name": "per_allocation_memory_bytes", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "ByteSize", + "namespace": "_types" + } + } + }, { "description": "Number of inference requests are allowed in the queue at a time.", "name": "queue_capacity", @@ -137238,7 +138034,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L312-L345" + "specLocation": "ml/_types/TrainedModel.ts#L357-L393" }, { "kind": "interface", @@ -137262,6 +138058,55 @@ ], "specLocation": "ml/_types/Analysis.ts#L174-L179" }, + { + "kind": "interface", + "name": { + "name": "DetectorUpdate", + "namespace": "ml._types" + }, + "properties": [ + { + "description": "A unique identifier for the detector.\nThis identifier is based on the order of the detectors in the `analysis_config`, starting at zero.", + "name": "detector_index", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "integer", + "namespace": "_types" + } + } + }, + { + "description": "A description of the detector.", + "name": "description", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, + { + "description": "An array of custom rule objects, which enable you to customize the way detectors operate.\nFor example, a rule may dictate to the detector conditions under which results should be skipped.\nKibana refers to custom rules as job rules.", + "name": "custom_rules", + "required": false, + "type": { + "kind": "array_of", + "value": { + "kind": "instance_of", + "type": { + "name": "DetectionRule", + "namespace": "ml._types" + } + } + } + } + ], + "specLocation": "ml/_types/Detector.ts#L127-L143" + }, { "generics": [ { diff --git a/output/schema/schema.json b/output/schema/schema.json index cd14c91a74..2a2f991e10 100644 --- a/output/schema/schema.json +++ b/output/schema/schema.json @@ -149555,6 +149555,49 @@ }, "specLocation": "migration/post_feature_upgrade/PostFeatureUpgradeResponse.ts#L20-L25" }, + { + "kind": "interface", + "name": { + "name": "AdaptiveAllocationsSettings", + "namespace": "ml._types" + }, + "properties": [ + { + "name": "enabled", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "boolean", + "namespace": "_builtins" + } + } + }, + { + "name": "min_number_of_allocations", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "integer", + "namespace": "_types" + } + } + }, + { + "name": "max_number_of_allocations", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "integer", + "namespace": "_types" + } + } + } + ], + "specLocation": "ml/_types/TrainedModel.ts#L109-L113" + }, { "kind": "interface", "name": { @@ -149909,8 +149952,8 @@ "type": { "kind": "instance_of", "type": { - "name": "string", - "namespace": "_builtins" + "name": "ByteSize", + "namespace": "_types" } } } @@ -151125,7 +151168,7 @@ "name": "CategorizationStatus", "namespace": "ml._types" }, - "specLocation": "ml/_types/Model.ts#L83-L86" + "specLocation": "ml/_types/Model.ts#L84-L87" }, { "kind": "interface", @@ -151341,7 +151384,7 @@ } } ], - "specLocation": "ml/_types/Datafeed.ts#L241-L254" + "specLocation": "ml/_types/Datafeed.ts#L251-L264" }, { "kind": "enum", @@ -151360,7 +151403,7 @@ "name": "ChunkingMode", "namespace": "ml._types" }, - "specLocation": "ml/_types/Datafeed.ts#L235-L239" + "specLocation": "ml/_types/Datafeed.ts#L245-L249" }, { "kind": "interface", @@ -151435,6 +151478,81 @@ ], "specLocation": "ml/_types/inference.ts#L93-L108" }, + { + "kind": "interface", + "name": { + "name": "CommonTokenizationConfig", + "namespace": "ml._types" + }, + "properties": [ + { + "description": "Should the tokenizer lower case the text", + "name": "do_lower_case", + "required": false, + "serverDefault": false, + "type": { + "kind": "instance_of", + "type": { + "name": "boolean", + "namespace": "_builtins" + } + } + }, + { + "description": "Maximum input sequence length for the model", + "name": "max_sequence_length", + "required": false, + "serverDefault": 512, + "type": { + "kind": "instance_of", + "type": { + "name": "integer", + "namespace": "_types" + } + } + }, + { + "description": "Tokenization spanning options. Special value of -1 indicates no spanning takes place", + "name": "span", + "required": false, + "serverDefault": -1, + "type": { + "kind": "instance_of", + "type": { + "name": "integer", + "namespace": "_types" + } + } + }, + { + "description": "Should tokenization input be automatically truncated before sending to the model for inference", + "name": "truncate", + "required": false, + "serverDefault": "first", + "type": { + "kind": "instance_of", + "type": { + "name": "TokenizationTruncate", + "namespace": "ml._types" + } + } + }, + { + "description": "Is tokenization completed with special tokens", + "name": "with_special_tokens", + "required": false, + "serverDefault": true, + "type": { + "kind": "instance_of", + "type": { + "name": "boolean", + "namespace": "_builtins" + } + } + } + ], + "specLocation": "ml/_types/inference.ts#L133-L159" + }, { "kind": "enum", "members": [ @@ -151965,7 +152083,7 @@ } } ], - "specLocation": "ml/_types/Datafeed.ts#L36-L60" + "specLocation": "ml/_types/Datafeed.ts#L37-L61" }, { "kind": "interface", @@ -152220,7 +152338,7 @@ } } ], - "specLocation": "ml/_types/Datafeed.ts#L62-L119" + "specLocation": "ml/_types/Datafeed.ts#L63-L120" }, { "kind": "interface", @@ -152266,7 +152384,7 @@ } } ], - "specLocation": "ml/_types/Datafeed.ts#L200-L214" + "specLocation": "ml/_types/Datafeed.ts#L210-L224" }, { "kind": "enum", @@ -152288,7 +152406,7 @@ "name": "DatafeedState", "namespace": "ml._types" }, - "specLocation": "ml/_types/Datafeed.ts#L135-L140" + "specLocation": "ml/_types/Datafeed.ts#L136-L141" }, { "kind": "interface", @@ -152331,7 +152449,7 @@ "type": { "kind": "instance_of", "type": { - "name": "DiscoveryNode", + "name": "DiscoveryNodeCompact", "namespace": "ml._types" } } @@ -152351,7 +152469,7 @@ { "description": "An object that provides statistical information about timing aspect of this datafeed.", "name": "timing_stats", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -152373,7 +152491,7 @@ } } ], - "specLocation": "ml/_types/Datafeed.ts#L142-L171" + "specLocation": "ml/_types/Datafeed.ts#L143-L172" }, { "kind": "interface", @@ -152415,6 +152533,17 @@ } } }, + { + "name": "exponential_average_calculation_context", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "ExponentialAverageCalculationContext", + "namespace": "ml._types" + } + } + }, { "description": "Identifier for the anomaly detection job.", "name": "job_id", @@ -152482,7 +152611,7 @@ } } ], - "specLocation": "ml/_types/Datafeed.ts#L173-L198" + "specLocation": "ml/_types/Datafeed.ts#L174-L202" }, { "kind": "interface", @@ -152717,7 +152846,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L133-L212" + "specLocation": "ml/_types/DataframeAnalytics.ts#L134-L213" }, { "kind": "interface", @@ -152758,7 +152887,7 @@ } ], "shortcutProperty": "includes", - "specLocation": "ml/_types/DataframeAnalytics.ts#L237-L243" + "specLocation": "ml/_types/DataframeAnalytics.ts#L238-L244" }, { "kind": "interface", @@ -152798,7 +152927,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L226-L235" + "specLocation": "ml/_types/DataframeAnalytics.ts#L227-L236" }, { "kind": "interface", @@ -152850,7 +152979,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L83-L100", + "specLocation": "ml/_types/DataframeAnalytics.ts#L84-L101", "variants": { "kind": "container" } @@ -152923,7 +153052,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L245-L257", + "specLocation": "ml/_types/DataframeAnalytics.ts#L246-L258", "variants": { "kind": "container" } @@ -152982,7 +153111,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L259-L266" + "specLocation": "ml/_types/DataframeAnalytics.ts#L260-L267" }, { "kind": "interface", @@ -153007,7 +153136,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L268-L271" + "specLocation": "ml/_types/DataframeAnalytics.ts#L269-L272" }, { "kind": "interface", @@ -153091,7 +153220,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L273-L285" + "specLocation": "ml/_types/DataframeAnalytics.ts#L274-L286" }, { "kind": "interface", @@ -153125,7 +153254,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L287-L292" + "specLocation": "ml/_types/DataframeAnalytics.ts#L288-L293" }, { "kind": "interface", @@ -153190,7 +153319,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L294-L303" + "specLocation": "ml/_types/DataframeAnalytics.ts#L295-L304" }, { "kind": "interface", @@ -153276,7 +153405,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L102-L131" + "specLocation": "ml/_types/DataframeAnalytics.ts#L103-L132" }, { "kind": "interface", @@ -153317,7 +153446,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L214-L224" + "specLocation": "ml/_types/DataframeAnalytics.ts#L215-L225" }, { "kind": "interface", @@ -153429,7 +153558,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L323-L343" + "specLocation": "ml/_types/DataframeAnalytics.ts#L325-L345" }, { "kind": "interface", @@ -153512,7 +153641,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L76-L81" + "specLocation": "ml/_types/DataframeAnalytics.ts#L77-L82" }, { "kind": "interface", @@ -153597,7 +153726,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L54-L67" + "specLocation": "ml/_types/DataframeAnalytics.ts#L55-L68" }, { "kind": "interface", @@ -153631,7 +153760,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L69-L74" + "specLocation": "ml/_types/DataframeAnalytics.ts#L70-L75" }, { "kind": "interface", @@ -153691,7 +153820,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L38-L52" + "specLocation": "ml/_types/DataframeAnalytics.ts#L39-L53" }, { "kind": "interface", @@ -153737,7 +153866,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L372-L380", + "specLocation": "ml/_types/DataframeAnalytics.ts#L374-L382", "variants": { "kind": "container" } @@ -153786,7 +153915,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L363-L370" + "specLocation": "ml/_types/DataframeAnalytics.ts#L365-L372" }, { "kind": "interface", @@ -153865,7 +153994,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L382-L401" + "specLocation": "ml/_types/DataframeAnalytics.ts#L384-L403" }, { "kind": "interface", @@ -153932,7 +154061,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L352-L361" + "specLocation": "ml/_types/DataframeAnalytics.ts#L354-L363" }, { "kind": "interface", @@ -153987,7 +154116,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L403-L416" + "specLocation": "ml/_types/DataframeAnalytics.ts#L405-L418" }, { "kind": "interface", @@ -154021,7 +154150,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L345-L350" + "specLocation": "ml/_types/DataframeAnalytics.ts#L347-L352" }, { "kind": "interface", @@ -154171,9 +154300,20 @@ "namespace": "_types" } } + }, + { + "name": "_meta", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "Metadata", + "namespace": "_types" + } + } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L305-L321" + "specLocation": "ml/_types/DataframeAnalytics.ts#L306-L323" }, { "kind": "interface", @@ -154733,7 +154873,7 @@ } } ], - "specLocation": "ml/_types/Datafeed.ts#L121-L132" + "specLocation": "ml/_types/Datafeed.ts#L122-L133" }, { "kind": "enum", @@ -154755,7 +154895,7 @@ "name": "DeploymentAllocationState", "namespace": "ml._types" }, - "specLocation": "ml/_types/TrainedModel.ts#L273-L286" + "specLocation": "ml/_types/TrainedModel.ts#L318-L331" }, { "kind": "enum", @@ -154781,7 +154921,7 @@ "name": "DeploymentAssignmentState", "namespace": "ml._types" }, - "specLocation": "ml/_types/TrainedModel.ts#L288-L305" + "specLocation": "ml/_types/TrainedModel.ts#L333-L350" }, { "kind": "interface", @@ -155142,45 +155282,99 @@ { "kind": "interface", "name": { - "name": "DiscoveryNode", + "name": "DetectorUpdate", "namespace": "ml._types" }, "properties": [ { - "name": "attributes", + "description": "A unique identifier for the detector.\nThis identifier is based on the order of the detectors in the `analysis_config`, starting at zero.", + "name": "detector_index", "required": true, "type": { - "kind": "dictionary_of", - "key": { - "kind": "instance_of", - "type": { - "name": "string", - "namespace": "_builtins" - } - }, - "singleKey": false, + "kind": "instance_of", + "type": { + "name": "integer", + "namespace": "_types" + } + } + }, + { + "description": "A description of the detector.", + "name": "description", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, + { + "description": "An array of custom rule objects, which enable you to customize the way detectors operate.\nFor example, a rule may dictate to the detector conditions under which results should be skipped.\nKibana refers to custom rules as job rules.", + "name": "custom_rules", + "required": false, + "type": { + "kind": "array_of", "value": { "kind": "instance_of", "type": { - "name": "string", - "namespace": "_builtins" + "name": "DetectionRule", + "namespace": "ml._types" } } } + } + ], + "specLocation": "ml/_types/Detector.ts#L127-L143" + }, + { + "kind": "type_alias", + "name": { + "name": "DiscoveryNode", + "namespace": "ml._types" + }, + "specLocation": "ml/_types/DiscoveryNode.ts#L25-L25", + "type": { + "kind": "dictionary_of", + "key": { + "kind": "instance_of", + "type": { + "name": "Id", + "namespace": "_types" + } }, + "singleKey": true, + "value": { + "kind": "instance_of", + "type": { + "name": "DiscoveryNodeContent", + "namespace": "ml._types" + } + } + } + }, + { + "kind": "interface", + "description": "Alternative representation of DiscoveryNode used in ml.get_job_stats and ml.get_datafeed_stats", + "name": { + "name": "DiscoveryNodeCompact", + "namespace": "ml._types" + }, + "properties": [ { - "name": "ephemeral_id", + "name": "name", "required": true, "type": { "kind": "instance_of", "type": { - "name": "Id", + "name": "Name", "namespace": "_types" } } }, { - "name": "id", + "name": "ephemeral_id", "required": true, "type": { "kind": "instance_of", @@ -155191,12 +155385,12 @@ } }, { - "name": "name", + "name": "id", "required": true, "type": { "kind": "instance_of", "type": { - "name": "Name", + "name": "Id", "namespace": "_types" } } @@ -155211,19 +155405,164 @@ "namespace": "_types" } } + }, + { + "name": "attributes", + "required": true, + "type": { + "kind": "dictionary_of", + "key": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + }, + "singleKey": false, + "value": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + } } ], - "specLocation": "ml/_types/DiscoveryNode.ts#L24-L30" + "specLocation": "ml/_types/DiscoveryNode.ts#L39-L48" }, { - "kind": "enum", - "members": [ - { - "name": "all" - }, + "kind": "interface", + "name": { + "name": "DiscoveryNodeContent", + "namespace": "ml._types" + }, + "properties": [ { - "name": "none" - }, + "name": "name", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "Name", + "namespace": "_types" + } + } + }, + { + "name": "ephemeral_id", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "Id", + "namespace": "_types" + } + } + }, + { + "name": "transport_address", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "TransportAddress", + "namespace": "_types" + } + } + }, + { + "name": "external_id", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, + { + "name": "attributes", + "required": true, + "type": { + "kind": "dictionary_of", + "key": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + }, + "singleKey": false, + "value": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + } + }, + { + "name": "roles", + "required": true, + "type": { + "kind": "array_of", + "value": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + } + }, + { + "name": "version", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "VersionString", + "namespace": "_types" + } + } + }, + { + "name": "min_index_version", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "integer", + "namespace": "_types" + } + } + }, + { + "name": "max_index_version", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "integer", + "namespace": "_types" + } + } + } + ], + "specLocation": "ml/_types/DiscoveryNode.ts#L27-L37" + }, + { + "kind": "enum", + "members": [ + { + "name": "all" + }, + { + "name": "none" + }, { "name": "by" }, @@ -155235,7 +155574,77 @@ "name": "ExcludeFrequent", "namespace": "ml._types" }, - "specLocation": "ml/_types/Detector.ts#L127-L132" + "specLocation": "ml/_types/Detector.ts#L145-L150" + }, + { + "kind": "interface", + "name": { + "name": "ExponentialAverageCalculationContext", + "namespace": "ml._types" + }, + "properties": [ + { + "name": "incremental_metric_value_ms", + "required": true, + "type": { + "kind": "instance_of", + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitFloatMillis", + "namespace": "_types" + } + } + ], + "type": { + "name": "DurationValue", + "namespace": "_types" + } + } + }, + { + "name": "latest_timestamp", + "required": false, + "type": { + "kind": "instance_of", + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitMillis", + "namespace": "_types" + } + } + ], + "type": { + "name": "EpochTime", + "namespace": "_types" + } + } + }, + { + "name": "previous_exponential_average_ms", + "required": false, + "type": { + "kind": "instance_of", + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitFloatMillis", + "namespace": "_types" + } + } + ], + "type": { + "name": "DurationValue", + "namespace": "_types" + } + } + } + ], + "specLocation": "ml/_types/Datafeed.ts#L204-L208" }, { "kind": "interface", @@ -155292,9 +155701,20 @@ "namespace": "_builtins" } } + }, + { + "name": "vocabulary", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "Vocabulary", + "namespace": "ml._types" + } + } } ], - "specLocation": "ml/_types/inference.ts#L266-L280" + "specLocation": "ml/_types/inference.ts#L253-L268" }, { "kind": "interface", @@ -155340,7 +155760,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L411-L418" + "specLocation": "ml/_types/inference.ts#L399-L406" }, { "kind": "interface", @@ -155546,7 +155966,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L216-L230" + "specLocation": "ml/_types/TrainedModel.ts#L261-L275" }, { "kind": "interface", @@ -155724,7 +156144,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L418-L524" + "specLocation": "ml/_types/DataframeAnalytics.ts#L420-L526" }, { "kind": "enum", @@ -156066,7 +156486,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L296-L318", + "specLocation": "ml/_types/inference.ts#L284-L306", "variants": { "kind": "container" } @@ -156211,7 +156631,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L459-L507" + "specLocation": "ml/_types/inference.ts#L447-L495" }, { "kind": "interface", @@ -157217,7 +157637,7 @@ "type": { "kind": "instance_of", "type": { - "name": "DiscoveryNode", + "name": "DiscoveryNodeCompact", "namespace": "ml._types" } } @@ -157442,61 +157862,244 @@ "name": "MemoryStatus", "namespace": "ml._types" }, - "specLocation": "ml/_types/Model.ts#L88-L92" + "specLocation": "ml/_types/Model.ts#L89-L93" }, { "kind": "interface", "name": { - "name": "ModelPlotConfig", + "name": "ModelPackageConfig", "namespace": "ml._types" }, "properties": [ { - "availability": { - "serverless": {}, - "stack": { - "since": "7.9.0" - } - }, - "description": "If true, enables calculation and storage of the model change annotations for each entity that is being analyzed.", - "name": "annotations_enabled", + "name": "create_time", "required": false, - "serverDefault": true, "type": { "kind": "instance_of", + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitMillis", + "namespace": "_types" + } + } + ], "type": { - "name": "boolean", - "namespace": "_builtins" + "name": "EpochTime", + "namespace": "_types" } } }, { - "description": "If true, enables calculation and storage of the model bounds for each entity that is being analyzed.", - "name": "enabled", + "name": "description", "required": false, - "serverDefault": false, "type": { "kind": "instance_of", "type": { - "name": "boolean", + "name": "string", "namespace": "_builtins" } } }, { - "availability": { - "serverless": {}, - "stack": { - "since": "7.9.0" + "name": "inference_config", + "required": false, + "type": { + "kind": "dictionary_of", + "key": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + }, + "singleKey": false, + "value": { + "kind": "user_defined_value" } - }, - "description": "Limits data collection to this comma separated list of partition or by field values. If terms are not specified or it is an empty string, no filtering is applied. Wildcards are not supported. Only the specified terms can be viewed when using the Single Metric Viewer.", - "name": "terms", + } + }, + { + "name": "metadata", "required": false, "type": { "kind": "instance_of", "type": { - "name": "Field", + "name": "Metadata", + "namespace": "_types" + } + } + }, + { + "name": "minimum_version", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, + { + "name": "model_repository", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, + { + "name": "model_type", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, + { + "name": "packaged_model_id", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "Id", + "namespace": "_types" + } + } + }, + { + "name": "platform_architecture", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, + { + "name": "prefix_strings", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "TrainedModelPrefixStrings", + "namespace": "ml._types" + } + } + }, + { + "name": "size", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "ByteSize", + "namespace": "_types" + } + } + }, + { + "name": "sha256", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, + { + "name": "tags", + "required": false, + "type": { + "kind": "array_of", + "value": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + } + }, + { + "name": "vocabulary_file", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + } + ], + "specLocation": "ml/_types/TrainedModel.ts#L244-L259" + }, + { + "kind": "interface", + "name": { + "name": "ModelPlotConfig", + "namespace": "ml._types" + }, + "properties": [ + { + "availability": { + "serverless": {}, + "stack": { + "since": "7.9.0" + } + }, + "description": "If true, enables calculation and storage of the model change annotations for each entity that is being analyzed.", + "name": "annotations_enabled", + "required": false, + "serverDefault": true, + "type": { + "kind": "instance_of", + "type": { + "name": "boolean", + "namespace": "_builtins" + } + } + }, + { + "description": "If true, enables calculation and storage of the model bounds for each entity that is being analyzed.", + "name": "enabled", + "required": false, + "serverDefault": false, + "type": { + "kind": "instance_of", + "type": { + "name": "boolean", + "namespace": "_builtins" + } + } + }, + { + "availability": { + "serverless": {}, + "stack": { + "since": "7.9.0" + } + }, + "description": "Limits data collection to this comma separated list of partition or by field values. If terms are not specified or it is an empty string, no filtering is applied. Wildcards are not supported. Only the specified terms can be viewed when using the Single Metric Viewer.", + "name": "terms", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "Field", "namespace": "_types" } } @@ -157588,6 +158191,17 @@ } } }, + { + "name": "output_memory_allocator_bytes", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "ByteSize", + "namespace": "_types" + } + } + }, { "name": "peak_model_bytes", "required": false, @@ -157743,7 +158357,7 @@ } } ], - "specLocation": "ml/_types/Model.ts#L59-L81" + "specLocation": "ml/_types/Model.ts#L59-L82" }, { "kind": "interface", @@ -158002,7 +158616,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L255-L264" + "specLocation": "ml/_types/inference.ts#L242-L251" }, { "kind": "interface", @@ -158036,87 +158650,33 @@ } } ], - "specLocation": "ml/_types/inference.ts#L404-L409" + "specLocation": "ml/_types/inference.ts#L392-L397" }, { "kind": "interface", "description": "BERT and MPNet tokenization configuration options", + "inherits": { + "type": { + "name": "CommonTokenizationConfig", + "namespace": "ml._types" + } + }, "name": { "name": "NlpBertTokenizationConfig", "namespace": "ml._types" }, - "properties": [ - { - "description": "Should the tokenizer lower case the text", - "name": "do_lower_case", - "required": false, - "serverDefault": false, - "type": { - "kind": "instance_of", - "type": { - "name": "boolean", - "namespace": "_builtins" - } - } - }, - { - "description": "Is tokenization completed with special tokens", - "name": "with_special_tokens", - "required": false, - "serverDefault": true, - "type": { - "kind": "instance_of", - "type": { - "name": "boolean", - "namespace": "_builtins" - } - } - }, - { - "description": "Maximum input sequence length for the model", - "name": "max_sequence_length", - "required": false, - "serverDefault": 512, - "type": { - "kind": "instance_of", - "type": { - "name": "integer", - "namespace": "_types" - } - } - }, - { - "description": "Should tokenization input be automatically truncated before sending to the model for inference", - "name": "truncate", - "required": false, - "serverDefault": "first", - "type": { - "kind": "instance_of", - "type": { - "name": "TokenizationTruncate", - "namespace": "ml._types" - } - } - }, - { - "description": "Tokenization spanning options. Special value of -1 indicates no spanning takes place", - "name": "span", - "required": false, - "serverDefault": -1, - "type": { - "kind": "instance_of", - "type": { - "name": "integer", - "namespace": "_types" - } - } - } - ], - "specLocation": "ml/_types/inference.ts#L131-L158" + "properties": [], + "specLocation": "ml/_types/inference.ts#L161-L162" }, { "kind": "interface", "description": "RoBERTa tokenization configuration options", + "inherits": { + "type": { + "name": "CommonTokenizationConfig", + "namespace": "ml._types" + } + }, "name": { "name": "NlpRobertaTokenizationConfig", "namespace": "ml._types" @@ -158134,61 +158694,9 @@ "namespace": "_builtins" } } - }, - { - "description": "Is tokenization completed with special tokens", - "name": "with_special_tokens", - "required": false, - "serverDefault": true, - "type": { - "kind": "instance_of", - "type": { - "name": "boolean", - "namespace": "_builtins" - } - } - }, - { - "description": "Maximum input sequence length for the model", - "name": "max_sequence_length", - "required": false, - "serverDefault": 512, - "type": { - "kind": "instance_of", - "type": { - "name": "integer", - "namespace": "_types" - } - } - }, - { - "description": "Should tokenization input be automatically truncated before sending to the model for inference", - "name": "truncate", - "required": false, - "serverDefault": "first", - "type": { - "kind": "instance_of", - "type": { - "name": "TokenizationTruncate", - "namespace": "ml._types" - } - } - }, - { - "description": "Tokenization spanning options. Special value of -1 indicates no spanning takes place", - "name": "span", - "required": false, - "serverDefault": -1, - "type": { - "kind": "instance_of", - "type": { - "name": "integer", - "namespace": "_types" - } - } } ], - "specLocation": "ml/_types/inference.ts#L160-L187" + "specLocation": "ml/_types/inference.ts#L164-L171" }, { "kind": "interface", @@ -158222,7 +158730,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L356-L361" + "specLocation": "ml/_types/inference.ts#L344-L349" }, { "kind": "interface", @@ -158307,7 +158815,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L526-L560" + "specLocation": "ml/_types/DataframeAnalytics.ts#L528-L562" }, { "kind": "interface", @@ -158412,7 +158920,7 @@ { "description": "The start time of the bucket for which these results were calculated.", "name": "timestamp_string", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -158536,7 +159044,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L224-L231" + "specLocation": "ml/_types/inference.ts#L208-L215" }, { "kind": "interface", @@ -158570,7 +159078,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L385-L390" + "specLocation": "ml/_types/inference.ts#L373-L378" }, { "kind": "interface", @@ -158612,7 +159120,7 @@ "name": "PredictedValue", "namespace": "ml._types" }, - "specLocation": "ml/_types/inference.ts#L457-L457", + "specLocation": "ml/_types/inference.ts#L445-L445", "type": { "kind": "union_of", "items": [ @@ -158693,7 +159201,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L282-L292" + "specLocation": "ml/_types/inference.ts#L270-L280" }, { "kind": "interface", @@ -158763,7 +159271,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L420-L431" + "specLocation": "ml/_types/inference.ts#L408-L419" }, { "kind": "interface", @@ -158830,7 +159338,7 @@ "name": "RoutingState", "namespace": "ml._types" }, - "specLocation": "ml/_types/TrainedModel.ts#L347-L368" + "specLocation": "ml/_types/TrainedModel.ts#L395-L416" }, { "kind": "enum", @@ -158970,7 +159478,7 @@ } } ], - "specLocation": "ml/_types/Datafeed.ts#L216-L233" + "specLocation": "ml/_types/Datafeed.ts#L226-L243" }, { "kind": "enum", @@ -158992,7 +159500,7 @@ "name": "SnapshotUpgradeState", "namespace": "ml._types" }, - "specLocation": "ml/_types/Model.ts#L94-L99" + "specLocation": "ml/_types/Model.ts#L95-L100" }, { "kind": "interface", @@ -159054,7 +159562,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L189-L199" + "specLocation": "ml/_types/inference.ts#L173-L183" }, { "kind": "interface", @@ -159115,7 +159623,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L363-L372" + "specLocation": "ml/_types/inference.ts#L351-L360" }, { "kind": "interface", @@ -159160,9 +159668,20 @@ "namespace": "_builtins" } } + }, + { + "name": "vocabulary", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "Vocabulary", + "namespace": "ml._types" + } + } } ], - "specLocation": "ml/_types/inference.ts#L237-L245" + "specLocation": "ml/_types/inference.ts#L221-L231" }, { "kind": "interface", @@ -159195,7 +159714,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L392-L396" + "specLocation": "ml/_types/inference.ts#L380-L384" }, { "kind": "interface", @@ -159228,9 +159747,20 @@ "namespace": "_builtins" } } + }, + { + "name": "vocabulary", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "Vocabulary", + "namespace": "ml._types" + } + } } ], - "specLocation": "ml/_types/inference.ts#L247-L253" + "specLocation": "ml/_types/inference.ts#L233-L240" }, { "kind": "interface", @@ -159263,7 +159793,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L398-L402" + "specLocation": "ml/_types/inference.ts#L386-L390" }, { "kind": "interface", @@ -159315,7 +159845,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L562-L567" + "specLocation": "ml/_types/DataframeAnalytics.ts#L564-L569" }, { "kind": "interface", @@ -159337,6 +159867,18 @@ } } }, + { + "description": "Indicates BERT Japanese tokenization and its options", + "name": "bert_ja", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "NlpBertTokenizationConfig", + "namespace": "ml._types" + } + } + }, { "availability": { "serverless": {}, @@ -159374,7 +159916,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L110-L129", + "specLocation": "ml/_types/inference.ts#L110-L131", "variants": { "kind": "container" } @@ -159396,7 +159938,7 @@ "name": "TokenizationTruncate", "namespace": "ml._types" }, - "specLocation": "ml/_types/inference.ts#L350-L354" + "specLocation": "ml/_types/inference.ts#L338-L342" }, { "kind": "interface", @@ -159439,7 +159981,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L440-L444" + "specLocation": "ml/_types/inference.ts#L428-L432" }, { "kind": "interface", @@ -159491,7 +160033,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L232-L239" + "specLocation": "ml/_types/TrainedModel.ts#L277-L284" }, { "kind": "interface", @@ -159528,7 +160070,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L241-L246" + "specLocation": "ml/_types/TrainedModel.ts#L286-L291" }, { "kind": "interface", @@ -159574,7 +160116,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L248-L255" + "specLocation": "ml/_types/TrainedModel.ts#L293-L300" }, { "kind": "interface", @@ -159583,6 +160125,29 @@ "namespace": "ml._types" }, "properties": [ + { + "name": "adaptive_allocations", + "required": false, + "type": { + "kind": "union_of", + "items": [ + { + "kind": "instance_of", + "type": { + "name": "AdaptiveAllocationsSettings", + "namespace": "ml._types" + } + }, + { + "kind": "instance_of", + "type": { + "name": "null", + "namespace": "_builtins" + } + } + ] + } + }, { "description": "The overall assignment state.", "name": "assignment_state", @@ -159606,6 +160171,17 @@ } } }, + { + "name": "reason", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "string", + "namespace": "_builtins" + } + } + }, { "description": "The allocation state for each node.", "name": "routing_table", @@ -159653,7 +160229,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L399-L414" + "specLocation": "ml/_types/TrainedModel.ts#L447-L464" }, { "kind": "interface", @@ -159665,7 +160241,7 @@ { "description": "The reason for the current state. It is usually populated only when the\n`routing_state` is `failed`.", "name": "reason", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -159711,7 +160287,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L370-L388" + "specLocation": "ml/_types/TrainedModel.ts#L418-L436" }, { "kind": "interface", @@ -159727,7 +160303,7 @@ "type": { "kind": "instance_of", "type": { - "name": "integer", + "name": "ByteSize", "namespace": "_types" } } @@ -159765,7 +160341,7 @@ }, "description": "The size of the trained model cache.", "name": "cache_size", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -159797,6 +160373,28 @@ } } }, + { + "name": "per_deployment_memory_bytes", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "ByteSize", + "namespace": "_types" + } + } + }, + { + "name": "per_allocation_memory_bytes", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "ByteSize", + "namespace": "_types" + } + } + }, { "description": "Number of inference requests are allowed in the queue at a time.", "name": "queue_capacity", @@ -159822,7 +160420,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L312-L345" + "specLocation": "ml/_types/TrainedModel.ts#L357-L393" }, { "kind": "interface", @@ -160047,6 +160645,17 @@ } } }, + { + "name": "model_package", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "ModelPackageConfig", + "namespace": "ml._types" + } + } + }, { "name": "location", "required": false, @@ -160070,7 +160679,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L164-L199" + "specLocation": "ml/_types/TrainedModel.ts#L191-L227" }, { "kind": "interface", @@ -160095,7 +160704,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L201-L204" + "specLocation": "ml/_types/TrainedModel.ts#L229-L232" }, { "kind": "interface", @@ -160172,7 +160781,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L206-L214" + "specLocation": "ml/_types/TrainedModel.ts#L234-L242" }, { "kind": "interface", @@ -160218,7 +160827,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L390-L397" + "specLocation": "ml/_types/TrainedModel.ts#L438-L445" }, { "kind": "interface", @@ -160230,7 +160839,48 @@ { "description": "The average time for each inference call to complete on this node.", "name": "average_inference_time_ms", - "required": true, + "required": false, + "type": { + "kind": "instance_of", + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitFloatMillis", + "namespace": "_types" + } + } + ], + "type": { + "name": "DurationValue", + "namespace": "_types" + } + } + }, + { + "name": "average_inference_time_ms_last_minute", + "required": false, + "type": { + "kind": "instance_of", + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitFloatMillis", + "namespace": "_types" + } + } + ], + "type": { + "name": "DurationValue", + "namespace": "_types" + } + } + }, + { + "description": "The average time for each inference call to complete on this node, excluding cache", + "name": "average_inference_time_ms_excluding_cache_hits", + "required": false, "type": { "kind": "instance_of", "generics": [ @@ -160251,7 +160901,7 @@ { "description": "The number of errors when evaluating the trained model.", "name": "error_count", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -160263,11 +160913,33 @@ { "description": "The total number of inference calls made against this node for this model.", "name": "inference_count", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { - "name": "integer", + "name": "long", + "namespace": "_types" + } + } + }, + { + "name": "inference_cache_hit_count", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "long", + "namespace": "_types" + } + } + }, + { + "name": "inference_cache_hit_count_last_minute", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "long", "namespace": "_types" } } @@ -160275,11 +160947,20 @@ { "description": "The epoch time stamp of the last inference call for the model on this node.", "name": "last_access", - "required": true, + "required": false, "type": { "kind": "instance_of", + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitMillis", + "namespace": "_types" + } + } + ], "type": { - "name": "long", + "name": "EpochTime", "namespace": "_types" } } @@ -160290,7 +160971,7 @@ }, "description": "Information pertaining to the node.", "name": "node", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -160302,7 +160983,7 @@ { "description": "The number of allocations assigned to this node.", "name": "number_of_allocations", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -160314,7 +160995,7 @@ { "description": "The number of inference requests queued to be processed.", "name": "number_of_pending_requests", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -160323,10 +161004,21 @@ } } }, + { + "name": "peak_throughput_per_minute", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "long", + "namespace": "_types" + } + } + }, { "description": "The number of inference requests that were not processed because the queue was full.", "name": "rejection_execution_count", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -160350,7 +161042,7 @@ { "description": "The epoch timestamp when the allocation started.", "name": "start_time", - "required": true, + "required": false, "type": { "kind": "instance_of", "generics": [ @@ -160371,6 +161063,17 @@ { "description": "The number of threads used by each allocation during inference.", "name": "threads_per_allocation", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "integer", + "namespace": "_types" + } + } + }, + { + "name": "throughput_last_minute", "required": true, "type": { "kind": "instance_of", @@ -160383,7 +161086,7 @@ { "description": "The number of inference requests that timed out before being processed.", "name": "timeout_count", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -160393,7 +161096,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L132-L162" + "specLocation": "ml/_types/TrainedModel.ts#L144-L189" }, { "kind": "interface", @@ -160402,10 +161105,21 @@ "namespace": "ml._types" }, "properties": [ + { + "name": "adaptive_allocations", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "AdaptiveAllocationsSettings", + "namespace": "ml._types" + } + } + }, { "description": "The detailed allocation status for the deployment.", "name": "allocation_status", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -160440,7 +161154,7 @@ { "description": "The sum of `error_count` for all nodes in the deployment.", "name": "error_count", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -160452,7 +161166,7 @@ { "description": "The sum of `inference_count` for all nodes in the deployment.", "name": "inference_count", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -160491,7 +161205,7 @@ { "description": "The number of allocations requested.", "name": "number_of_allocations", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -160500,10 +161214,32 @@ } } }, + { + "name": "peak_throughput_per_minute", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "long", + "namespace": "_types" + } + } + }, + { + "name": "priority", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "TrainingPriority", + "namespace": "ml._types" + } + } + }, { "description": "The number of inference requests that can be queued before new requests are rejected.", "name": "queue_capacity", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -160515,7 +161251,7 @@ { "description": "The sum of `rejected_execution_count` for all nodes in the deployment.\nIndividual nodes reject an inference request if the inference queue is full.\nThe queue size is controlled by the `queue_capacity` setting in the start\ntrained model deployment API.", "name": "rejected_execution_count", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -160527,7 +161263,7 @@ { "description": "The reason for the current deployment state. Usually only populated when\nthe model is not deployed to a node.", "name": "reason", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -160560,7 +161296,7 @@ { "description": "The overall state of the deployment.", "name": "state", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -160572,7 +161308,7 @@ { "description": "The number of threads used be each allocation during inference.", "name": "threads_per_allocation", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -160584,7 +161320,7 @@ { "description": "The sum of `timeout_count` for all nodes in the deployment.", "name": "timeout_count", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { @@ -160594,7 +161330,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L61-L101" + "specLocation": "ml/_types/TrainedModel.ts#L62-L107" }, { "kind": "interface", @@ -160659,7 +161395,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L433-L439" + "specLocation": "ml/_types/inference.ts#L421-L427" }, { "kind": "interface", @@ -160691,7 +161427,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L446-L449" + "specLocation": "ml/_types/inference.ts#L434-L437" }, { "kind": "interface", @@ -160737,7 +161473,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L451-L455" + "specLocation": "ml/_types/inference.ts#L439-L443" }, { "kind": "interface", @@ -160818,7 +161554,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L103-L123" + "specLocation": "ml/_types/TrainedModel.ts#L115-L135" }, { "kind": "interface", @@ -160839,7 +161575,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L416-L418" + "specLocation": "ml/_types/TrainedModel.ts#L466-L468" }, { "kind": "interface", @@ -160860,7 +161596,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L420-L422" + "specLocation": "ml/_types/TrainedModel.ts#L470-L472" }, { "kind": "interface", @@ -160894,7 +161630,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L424-L433" + "specLocation": "ml/_types/TrainedModel.ts#L474-L483" }, { "kind": "interface", @@ -160928,7 +161664,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L125-L130" + "specLocation": "ml/_types/TrainedModel.ts#L137-L142" }, { "kind": "interface", @@ -161019,7 +161755,7 @@ } } ], - "specLocation": "ml/_types/TrainedModel.ts#L41-L59" + "specLocation": "ml/_types/TrainedModel.ts#L42-L60" }, { "kind": "enum", @@ -161041,7 +161777,7 @@ "name": "TrainedModelType", "namespace": "ml._types" }, - "specLocation": "ml/_types/TrainedModel.ts#L257-L271" + "specLocation": "ml/_types/TrainedModel.ts#L302-L316" }, { "kind": "enum", @@ -161057,7 +161793,7 @@ "name": "TrainingPriority", "namespace": "ml._types" }, - "specLocation": "ml/_types/TrainedModel.ts#L307-L310" + "specLocation": "ml/_types/TrainedModel.ts#L352-L355" }, { "kind": "interface", @@ -161143,7 +161879,7 @@ } } ], - "specLocation": "ml/_types/DataframeAnalytics.ts#L569-L574" + "specLocation": "ml/_types/DataframeAnalytics.ts#L571-L576" }, { "kind": "interface", @@ -161164,7 +161900,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L233-L235" + "specLocation": "ml/_types/inference.ts#L217-L219" }, { "kind": "interface", @@ -161255,7 +161991,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L201-L222" + "specLocation": "ml/_types/inference.ts#L185-L206" }, { "kind": "interface", @@ -161316,7 +162052,7 @@ } } ], - "specLocation": "ml/_types/inference.ts#L374-L383" + "specLocation": "ml/_types/inference.ts#L362-L371" }, { "kind": "request", @@ -166973,6 +167709,22 @@ } } }, + { + "deprecation": { + "description": "", + "version": "7.10.0" + }, + "description": "parameter is deprecated! Use [include=definition] instead", + "name": "include_model_definition", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "boolean", + "namespace": "_builtins" + } + } + }, { "description": "Specifies the maximum number of models to obtain.", "name": "size", @@ -167014,7 +167766,7 @@ } } ], - "specLocation": "ml/get_trained_models/MlGetTrainedModelRequest.ts#L25-L92" + "specLocation": "ml/get_trained_models/MlGetTrainedModelRequest.ts#L25-L99" }, { "kind": "response", @@ -167347,7 +168099,7 @@ } } ], - "specLocation": "ml/info/types.ts#L44-L50" + "specLocation": "ml/info/types.ts#L46-L52" }, { "kind": "interface", @@ -167368,7 +168120,7 @@ } } ], - "specLocation": "ml/info/types.ts#L40-L42" + "specLocation": "ml/info/types.ts#L42-L44" }, { "kind": "interface", @@ -167389,45 +168141,67 @@ } }, { - "name": "datafeeds", - "required": true, + "name": "datafeeds", + "required": true, + "type": { + "kind": "instance_of", + "type": { + "name": "Datafeeds", + "namespace": "ml.info" + } + } + } + ], + "specLocation": "ml/info/types.ts#L24-L27" + }, + { + "kind": "interface", + "name": { + "name": "Limits", + "namespace": "ml.info" + }, + "properties": [ + { + "name": "max_single_ml_node_processors", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "integer", + "namespace": "_types" + } + } + }, + { + "name": "total_ml_processors", + "required": false, "type": { "kind": "instance_of", "type": { - "name": "Datafeeds", - "namespace": "ml.info" + "name": "integer", + "namespace": "_types" } } - } - ], - "specLocation": "ml/info/types.ts#L24-L27" - }, - { - "kind": "interface", - "name": { - "name": "Limits", - "namespace": "ml.info" - }, - "properties": [ + }, { "name": "max_model_memory_limit", "required": false, "type": { "kind": "instance_of", "type": { - "name": "string", - "namespace": "_builtins" + "name": "ByteSize", + "namespace": "_types" } } }, { "name": "effective_max_model_memory_limit", - "required": true, + "required": false, "type": { "kind": "instance_of", "type": { - "name": "string", - "namespace": "_builtins" + "name": "ByteSize", + "namespace": "_types" } } }, @@ -167437,13 +168211,13 @@ "type": { "kind": "instance_of", "type": { - "name": "string", - "namespace": "_builtins" + "name": "ByteSize", + "namespace": "_types" } } } ], - "specLocation": "ml/info/types.ts#L34-L38" + "specLocation": "ml/info/types.ts#L34-L40" }, { "kind": "interface", @@ -167826,18 +168600,18 @@ "kind": "properties", "properties": [ { - "name": "bucket_count", + "name": "job_id", "required": true, "type": { "kind": "instance_of", "type": { - "name": "long", + "name": "Id", "namespace": "_types" } } }, { - "name": "earliest_record_timestamp", + "name": "processed_record_count", "required": true, "type": { "kind": "instance_of", @@ -167848,7 +168622,7 @@ } }, { - "name": "empty_bucket_count", + "name": "processed_field_count", "required": true, "type": { "kind": "instance_of", @@ -167881,7 +168655,7 @@ } }, { - "name": "input_record_count", + "name": "invalid_date_count", "required": true, "type": { "kind": "instance_of", @@ -167892,7 +168666,7 @@ } }, { - "name": "invalid_date_count", + "name": "missing_field_count", "required": true, "type": { "kind": "instance_of", @@ -167903,29 +168677,29 @@ } }, { - "name": "job_id", + "name": "out_of_order_timestamp_count", "required": true, "type": { "kind": "instance_of", "type": { - "name": "Id", + "name": "long", "namespace": "_types" } } }, { - "name": "last_data_time", + "name": "empty_bucket_count", "required": true, "type": { "kind": "instance_of", "type": { - "name": "integer", + "name": "long", "namespace": "_types" } } }, { - "name": "latest_record_timestamp", + "name": "sparse_bucket_count", "required": true, "type": { "kind": "instance_of", @@ -167936,7 +168710,7 @@ } }, { - "name": "missing_field_count", + "name": "bucket_count", "required": true, "type": { "kind": "instance_of", @@ -167947,40 +168721,107 @@ } }, { - "name": "out_of_order_timestamp_count", - "required": true, + "name": "earliest_record_timestamp", + "required": false, + "type": { + "kind": "instance_of", + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitMillis", + "namespace": "_types" + } + } + ], + "type": { + "name": "EpochTime", + "namespace": "_types" + } + } + }, + { + "name": "latest_record_timestamp", + "required": false, "type": { "kind": "instance_of", + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitMillis", + "namespace": "_types" + } + } + ], "type": { - "name": "long", + "name": "EpochTime", "namespace": "_types" } } }, { - "name": "processed_field_count", - "required": true, + "name": "last_data_time", + "required": false, "type": { "kind": "instance_of", + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitMillis", + "namespace": "_types" + } + } + ], "type": { - "name": "long", + "name": "EpochTime", "namespace": "_types" } } }, { - "name": "processed_record_count", - "required": true, + "name": "latest_empty_bucket_timestamp", + "required": false, "type": { "kind": "instance_of", + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitMillis", + "namespace": "_types" + } + } + ], "type": { - "name": "long", + "name": "EpochTime", "namespace": "_types" } } }, { - "name": "sparse_bucket_count", + "name": "latest_sparse_bucket_timestamp", + "required": false, + "type": { + "kind": "instance_of", + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitMillis", + "namespace": "_types" + } + } + ], + "type": { + "name": "EpochTime", + "namespace": "_types" + } + } + }, + { + "name": "input_record_count", "required": true, "type": { "kind": "instance_of", @@ -167989,6 +168830,26 @@ "namespace": "_types" } } + }, + { + "name": "log_time", + "required": false, + "type": { + "kind": "instance_of", + "generics": [ + { + "kind": "instance_of", + "type": { + "name": "UnitMillis", + "namespace": "_types" + } + } + ], + "type": { + "name": "EpochTime", + "namespace": "_types" + } + } } ] }, @@ -167996,7 +168857,7 @@ "name": "Response", "namespace": "ml.post_data" }, - "specLocation": "ml/post_data/MlPostJobDataResponse.ts#L23-L41" + "specLocation": "ml/post_data/MlPostJobDataResponse.ts#L24-L45" }, { "kind": "interface", @@ -168563,6 +169424,17 @@ } } }, + { + "name": "_meta", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "Metadata", + "namespace": "_types" + } + } + }, { "description": "The approximate maximum amount of memory resources that are permitted for\nanalytical processing. If your `elasticsearch.yml` file contains an\n`xpack.ml.max_model_memory_limit` setting, an error occurs when you try\nto create data frame analytics jobs that have `model_memory_limit` values\ngreater than that setting.", "name": "model_memory_limit", @@ -168650,7 +169522,7 @@ } ], "query": [], - "specLocation": "ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts#L30-L142" + "specLocation": "ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts#L30-L144" }, { "kind": "response", @@ -168765,6 +169637,17 @@ } } }, + { + "name": "_meta", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "Metadata", + "namespace": "_types" + } + } + }, { "name": "model_memory_limit", "required": true, @@ -168804,7 +169687,7 @@ "name": "Response", "namespace": "ml.put_data_frame_analytics" }, - "specLocation": "ml/put_data_frame_analytics/MlPutDataFrameAnalyticsResponse.ts#L31-L46" + "specLocation": "ml/put_data_frame_analytics/MlPutDataFrameAnalyticsResponse.ts#L31-L47" }, { "kind": "request", @@ -168815,6 +169698,9 @@ "kind": "properties", "properties": [ { + "aliases": [ + "aggs" + ], "description": "If set, the datafeed performs aggregation searches.\nSupport for aggregations is limited and should be used only with low cardinality data.", "name": "aggregations", "required": false, @@ -169099,7 +169985,7 @@ } } ], - "specLocation": "ml/put_datafeed/MlPutDatafeedRequest.ts#L37-L173" + "specLocation": "ml/put_datafeed/MlPutDatafeedRequest.ts#L37-L175" }, { "kind": "response", @@ -169536,6 +170422,18 @@ } } }, + { + "description": "The identifier for the anomaly detection job. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters.", + "name": "job_id", + "required": false, + "type": { + "kind": "instance_of", + "type": { + "name": "Id", + "namespace": "_types" + } + } + }, { "description": "A list of job groups. A job can belong to no groups or many.", "name": "groups", @@ -169640,8 +170538,65 @@ } } ], - "query": [], - "specLocation": "ml/put_job/MlPutJobRequest.ts#L30-L113" + "query": [ + { + "description": "If `true`, wildcard indices expressions that resolve into no concrete indices are ignored. This includes the\n`_all` string or when no indices are specified.", + "name": "allow_no_indices", + "required": false, + "serverDefault": true, + "type": { + "kind": "instance_of", + "type": { + "name": "boolean", + "namespace": "_builtins" + } + } + }, + { + "description": "Type of index that wildcard patterns can match. If the request can target data streams, this argument determines\nwhether wildcard expressions match hidden data streams. Supports comma-separated values. Valid values are:\n\n* `all`: Match any data stream or index, including hidden ones.\n* `closed`: Match closed, non-hidden indices. Also matches any non-hidden data stream. Data streams cannot be closed.\n* `hidden`: Match hidden data streams and hidden indices. Must be combined with `open`, `closed`, or both.\n* `none`: Wildcard patterns are not accepted.\n* `open`: Match open, non-hidden indices. Also matches any non-hidden data stream.", + "name": "expand_wildcards", + "required": false, + "serverDefault": "open", + "type": { + "kind": "instance_of", + "type": { + "name": "ExpandWildcards", + "namespace": "_types" + } + } + }, + { + "deprecation": { + "description": "", + "version": "7.16.0" + }, + "description": "If `true`, concrete, expanded or aliased indices are ignored when frozen.", + "name": "ignore_throttled", + "required": false, + "serverDefault": true, + "type": { + "kind": "instance_of", + "type": { + "name": "boolean", + "namespace": "_builtins" + } + } + }, + { + "description": "If `true`, unavailable indices (missing or closed) are ignored.", + "name": "ignore_unavailable", + "required": false, + "serverDefault": false, + "type": { + "kind": "instance_of", + "type": { + "name": "boolean", + "namespace": "_builtins" + } + } + } + ], + "specLocation": "ml/put_job/MlPutJobRequest.ts#L30-L148" }, { "kind": "response", @@ -173063,7 +174018,7 @@ "value": { "kind": "instance_of", "type": { - "name": "Detector", + "name": "DetectorUpdate", "namespace": "ml._types" } } diff --git a/output/schema/validation-errors.json b/output/schema/validation-errors.json index 9f83afab68..3d84fdc205 100644 --- a/output/schema/validation-errors.json +++ b/output/schema/validation-errors.json @@ -747,21 +747,6 @@ ], "response": [] }, - "ml.get_trained_models": { - "request": [ - "Request: missing json spec query parameter 'include_model_definition'" - ], - "response": [] - }, - "ml.put_job": { - "request": [ - "Request: missing json spec query parameter 'ignore_unavailable'", - "Request: missing json spec query parameter 'allow_no_indices'", - "Request: missing json spec query parameter 'ignore_throttled'", - "Request: missing json spec query parameter 'expand_wildcards'" - ], - "response": [] - }, "ml.stop_datafeed": { "request": [ "Request: missing json spec query parameter 'allow_no_datafeeds'" diff --git a/output/typescript/types.ts b/output/typescript/types.ts index 8917299a78..38605150e7 100644 --- a/output/typescript/types.ts +++ b/output/typescript/types.ts @@ -13608,6 +13608,12 @@ export interface MigrationPostFeatureUpgradeResponse { features: MigrationPostFeatureUpgradeMigrationFeature[] } +export interface MlAdaptiveAllocationsSettings { + enabled: boolean + min_number_of_allocations?: integer + max_number_of_allocations?: integer +} + export interface MlAnalysisConfig { bucket_span?: Duration categorization_analyzer?: MlCategorizationAnalyzer @@ -13638,7 +13644,7 @@ export interface MlAnalysisConfigRead { export interface MlAnalysisLimits { categorization_examples_limit?: long - model_memory_limit?: string + model_memory_limit?: ByteSize } export interface MlAnalysisMemoryLimit { @@ -13787,6 +13793,14 @@ export interface MlClassificationInferenceOptions { top_classes_results_field?: string } +export interface MlCommonTokenizationConfig { + do_lower_case?: boolean + max_sequence_length?: integer + span?: integer + truncate?: MlTokenizationTruncate + with_special_tokens?: boolean +} + export type MlConditionOperator = 'gt' | 'gte' | 'lt' | 'lte' export type MlCustomSettings = any @@ -13876,15 +13890,16 @@ export type MlDatafeedState = 'started' | 'stopped' | 'starting' | 'stopping' export interface MlDatafeedStats { assignment_explanation?: string datafeed_id: Id - node?: MlDiscoveryNode + node?: MlDiscoveryNodeCompact state: MlDatafeedState - timing_stats: MlDatafeedTimingStats + timing_stats?: MlDatafeedTimingStats running_state?: MlDatafeedRunningState } export interface MlDatafeedTimingStats { bucket_count: long exponential_average_search_time_per_hour_ms: DurationValue + exponential_average_calculation_context?: MlExponentialAverageCalculationContext job_id: Id search_count: long total_search_time_ms: DurationValue @@ -14076,6 +14091,7 @@ export interface MlDataframeAnalyticsSummary { model_memory_limit?: string source: MlDataframeAnalyticsSource version?: VersionString + _meta?: Metadata } export interface MlDataframeEvaluationClassification { @@ -14181,21 +14197,48 @@ export interface MlDetectorRead { use_null?: boolean } -export interface MlDiscoveryNode { - attributes: Record +export interface MlDetectorUpdate { + detector_index: integer + description?: string + custom_rules?: MlDetectionRule[] +} + +export type MlDiscoveryNode = Partial> + +export interface MlDiscoveryNodeCompact { + name: Name ephemeral_id: Id id: Id - name: Name transport_address: TransportAddress + attributes: Record +} + +export interface MlDiscoveryNodeContent { + name?: Name + ephemeral_id: Id + transport_address: TransportAddress + external_id: string + attributes: Record + roles: string[] + version: VersionString + min_index_version: integer + max_index_version: integer } export type MlExcludeFrequent = 'all' | 'none' | 'by' | 'over' +export interface MlExponentialAverageCalculationContext { + incremental_metric_value_ms: DurationValue + latest_timestamp?: EpochTime + previous_exponential_average_ms?: DurationValue +} + export interface MlFillMaskInferenceOptions { mask_token?: string num_top_classes?: integer tokenization?: MlTokenizationConfigContainer results_field?: string + vocabulary: MlVocabulary } export interface MlFillMaskInferenceUpdateOptions { @@ -14383,7 +14426,7 @@ export interface MlJobStats { forecasts_stats: MlJobForecastStatistics job_id: string model_size_stats: MlModelSizeStats - node?: MlDiscoveryNode + node?: MlDiscoveryNodeCompact open_time?: DateTime state: MlJobState timing_stats: MlJobTimingStats @@ -14403,6 +14446,23 @@ export interface MlJobTimingStats { export type MlMemoryStatus = 'ok' | 'soft_limit' | 'hard_limit' +export interface MlModelPackageConfig { + create_time?: EpochTime + description?: string + inference_config?: Record + metadata?: Metadata + minimum_version?: string + model_repository?: string + model_type?: string + packaged_model_id: Id + platform_architecture?: string + prefix_strings?: MlTrainedModelPrefixStrings + size?: ByteSize + sha256?: string + tags?: string[] + vocabulary_file?: string +} + export interface MlModelPlotConfig { annotations_enabled?: boolean enabled?: boolean @@ -14417,6 +14477,7 @@ export interface MlModelSizeStats { model_bytes: ByteSize model_bytes_exceeded?: ByteSize model_bytes_memory_limit?: ByteSize + output_memory_allocator_bytes?: ByteSize peak_model_bytes?: ByteSize assignment_memory_basis?: string result_type: string @@ -14466,20 +14527,11 @@ export interface MlNerInferenceUpdateOptions { results_field?: string } -export interface MlNlpBertTokenizationConfig { - do_lower_case?: boolean - with_special_tokens?: boolean - max_sequence_length?: integer - truncate?: MlTokenizationTruncate - span?: integer +export interface MlNlpBertTokenizationConfig extends MlCommonTokenizationConfig { } -export interface MlNlpRobertaTokenizationConfig { +export interface MlNlpRobertaTokenizationConfig extends MlCommonTokenizationConfig { add_prefix_space?: boolean - with_special_tokens?: boolean - max_sequence_length?: integer - truncate?: MlTokenizationTruncate - span?: integer } export interface MlNlpTokenizationUpdateOptions { @@ -14503,7 +14555,7 @@ export interface MlOverallBucket { overall_score: double result_type: string timestamp: EpochTime - timestamp_string: DateTime + timestamp_string?: DateTime } export interface MlOverallBucketJob { @@ -14591,6 +14643,7 @@ export interface MlTextEmbeddingInferenceOptions { embedding_size?: integer tokenization?: MlTokenizationConfigContainer results_field?: string + vocabulary: MlVocabulary } export interface MlTextEmbeddingInferenceUpdateOptions { @@ -14601,6 +14654,7 @@ export interface MlTextEmbeddingInferenceUpdateOptions { export interface MlTextExpansionInferenceOptions { tokenization?: MlTokenizationConfigContainer results_field?: string + vocabulary: MlVocabulary } export interface MlTextExpansionInferenceUpdateOptions { @@ -14615,6 +14669,7 @@ export interface MlTimingStats { export interface MlTokenizationConfigContainer { bert?: MlNlpBertTokenizationConfig + bert_ja?: MlNlpBertTokenizationConfig mpnet?: MlNlpBertTokenizationConfig roberta?: MlNlpRobertaTokenizationConfig } @@ -14645,27 +14700,31 @@ export interface MlTotalFeatureImportanceStatistics { } export interface MlTrainedModelAssignment { + adaptive_allocations?: MlAdaptiveAllocationsSettings | null assignment_state: MlDeploymentAssignmentState max_assigned_allocations?: integer + reason?: string routing_table: Record start_time: DateTime task_parameters: MlTrainedModelAssignmentTaskParameters } export interface MlTrainedModelAssignmentRoutingTable { - reason: string + reason?: string routing_state: MlRoutingState current_allocations: integer target_allocations: integer } export interface MlTrainedModelAssignmentTaskParameters { - model_bytes: integer + model_bytes: ByteSize model_id: Id deployment_id: Id - cache_size: ByteSize + cache_size?: ByteSize number_of_allocations: integer priority: MlTrainingPriority + per_deployment_memory_bytes: ByteSize + per_allocation_memory_bytes: ByteSize queue_capacity: integer threads_per_allocation: integer } @@ -14688,6 +14747,7 @@ export interface MlTrainedModelConfig { license_level?: string metadata?: MlTrainedModelConfigMetadata model_size_bytes?: ByteSize + model_package?: MlModelPackageConfig location?: MlTrainedModelLocation prefix_strings?: MlTrainedModelPrefixStrings } @@ -14710,36 +14770,45 @@ export interface MlTrainedModelDeploymentAllocationStatus { } export interface MlTrainedModelDeploymentNodesStats { - average_inference_time_ms: DurationValue - error_count: integer - inference_count: integer - last_access: long - node: MlDiscoveryNode - number_of_allocations: integer - number_of_pending_requests: integer - rejection_execution_count: integer + average_inference_time_ms?: DurationValue + average_inference_time_ms_last_minute?: DurationValue + average_inference_time_ms_excluding_cache_hits?: DurationValue + error_count?: integer + inference_count?: long + inference_cache_hit_count?: long + inference_cache_hit_count_last_minute?: long + last_access?: EpochTime + node?: MlDiscoveryNode + number_of_allocations?: integer + number_of_pending_requests?: integer + peak_throughput_per_minute: long + rejection_execution_count?: integer routing_state: MlTrainedModelAssignmentRoutingTable - start_time: EpochTime - threads_per_allocation: integer - timeout_count: integer + start_time?: EpochTime + threads_per_allocation?: integer + throughput_last_minute: integer + timeout_count?: integer } export interface MlTrainedModelDeploymentStats { - allocation_status: MlTrainedModelDeploymentAllocationStatus + adaptive_allocations?: MlAdaptiveAllocationsSettings + allocation_status?: MlTrainedModelDeploymentAllocationStatus cache_size?: ByteSize deployment_id: Id - error_count: integer - inference_count: integer + error_count?: integer + inference_count?: integer model_id: Id nodes: MlTrainedModelDeploymentNodesStats[] - number_of_allocations: integer - queue_capacity: integer - rejected_execution_count: integer - reason: string + number_of_allocations?: integer + peak_throughput_per_minute: long + priority: MlTrainingPriority + queue_capacity?: integer + rejected_execution_count?: integer + reason?: string start_time: EpochTime - state: MlDeploymentAssignmentState - threads_per_allocation: integer - timeout_count: integer + state?: MlDeploymentAssignmentState + threads_per_allocation?: integer + timeout_count?: integer } export interface MlTrainedModelEntities { @@ -15438,6 +15507,7 @@ export interface MlGetTrainedModelsRequest extends RequestBase { exclude_generated?: boolean from?: integer include?: MlInclude + include_model_definition?: boolean size?: integer tags?: string | string[] } @@ -15490,9 +15560,11 @@ export interface MlInfoDefaults { } export interface MlInfoLimits { - max_model_memory_limit?: string - effective_max_model_memory_limit: string - total_ml_memory: string + max_single_ml_node_processors?: integer + total_ml_processors?: integer + max_model_memory_limit?: ByteSize + effective_max_model_memory_limit?: ByteSize + total_ml_memory: ByteSize } export interface MlInfoNativeCode { @@ -15542,21 +15614,24 @@ export interface MlPostDataRequest extends RequestBase { } export interface MlPostDataResponse { - bucket_count: long - earliest_record_timestamp: long - empty_bucket_count: long + job_id: Id + processed_record_count: long + processed_field_count: long input_bytes: long input_field_count: long - input_record_count: long invalid_date_count: long - job_id: Id - last_data_time: integer - latest_record_timestamp: long missing_field_count: long out_of_order_timestamp_count: long - processed_field_count: long - processed_record_count: long + empty_bucket_count: long sparse_bucket_count: long + bucket_count: long + earliest_record_timestamp?: EpochTime + latest_record_timestamp?: EpochTime + last_data_time?: EpochTime + latest_empty_bucket_timestamp?: EpochTime + latest_sparse_bucket_timestamp?: EpochTime + input_record_count: long + log_time?: EpochTime } export interface MlPreviewDataFrameAnalyticsDataframePreviewConfig { @@ -15624,6 +15699,7 @@ export interface MlPutDataFrameAnalyticsRequest extends RequestBase { description?: string dest: MlDataframeAnalyticsDestination max_num_threads?: integer + _meta?: Metadata model_memory_limit?: string source: MlDataframeAnalyticsSource headers?: HttpHeaders @@ -15641,6 +15717,7 @@ export interface MlPutDataFrameAnalyticsResponse { dest: MlDataframeAnalyticsDestination id: Id max_num_threads: integer + _meta?: Metadata model_memory_limit: string source: MlDataframeAnalyticsSource version: VersionString @@ -15654,6 +15731,7 @@ export interface MlPutDatafeedRequest extends RequestBase { ignore_unavailable?: boolean body?: { aggregations?: Record + aggs?: Record chunking_config?: MlChunkingConfig delayed_data_check_config?: MlDelayedDataCheckConfig frequency?: Duration @@ -15705,6 +15783,10 @@ export interface MlPutFilterResponse { export interface MlPutJobRequest extends RequestBase { job_id: Id + allow_no_indices?: boolean + expand_wildcards?: ExpandWildcards + ignore_throttled?: boolean + ignore_unavailable?: boolean body?: { allow_lazy_open?: boolean analysis_config: MlAnalysisConfig @@ -15715,6 +15797,7 @@ export interface MlPutJobRequest extends RequestBase { data_description: MlDataDescription datafeed_config?: MlDatafeedConfig description?: string + job_id?: Id groups?: string[] model_plot_config?: MlModelPlotConfig model_snapshot_retention_days?: long @@ -16082,7 +16165,7 @@ export interface MlUpdateJobRequest extends RequestBase { renormalization_window_days?: long results_retention_days?: long groups?: string[] - detectors?: MlDetector[] + detectors?: MlDetectorUpdate[] per_partition_categorization?: MlPerPartitionCategorization } } diff --git a/specification/ml/_types/Analysis.ts b/specification/ml/_types/Analysis.ts index 3a903917bb..9239b5cd47 100644 --- a/specification/ml/_types/Analysis.ts +++ b/specification/ml/_types/Analysis.ts @@ -21,7 +21,7 @@ import { OverloadOf } from '@spec_utils/behaviors' import { CharFilter } from '@_types/analysis/char_filters' import { Tokenizer } from '@_types/analysis/tokenizers' import { TokenFilter } from '@_types/analysis/token_filters' -import { Field } from '@_types/common' +import { ByteSize, Field } from '@_types/common' import { long } from '@_types/Numeric' import { Duration } from '@_types/Time' import { Detector, DetectorRead } from './Detector' @@ -168,7 +168,7 @@ export class AnalysisLimits { * The approximate maximum amount of memory resources that are required for analytical processing. Once this limit is approached, data pruning becomes more aggressive. Upon exceeding this limit, new entities are not modeled. If the `xpack.ml.max_model_memory_limit` setting has a value greater than 0 and less than 1024mb, that value is used instead of the default. The default value is relatively small to ensure that high resource usage is a conscious decision. If you have jobs that are expected to analyze high cardinality fields, you will likely need to use a higher value. If you specify a number instead of a string, the units are assumed to be MiB. Specifying a string is recommended for clarity. If you specify a byte size unit of `b` or `kb` and the number does not equate to a discrete number of megabytes, it is rounded down to the closest MiB. The minimum valid value is 1 MiB. If you specify a value less than 1 MiB, an error occurs. If you specify a value for the `xpack.ml.max_model_memory_limit` setting, an error occurs when you try to create jobs that have `model_memory_limit` values greater than that setting value. * @server_default 1024mb */ - model_memory_limit?: string + model_memory_limit?: ByteSize } export class AnalysisMemoryLimit { diff --git a/specification/ml/_types/Bucket.ts b/specification/ml/_types/Bucket.ts index cde8cd2836..0f7eb5013d 100644 --- a/specification/ml/_types/Bucket.ts +++ b/specification/ml/_types/Bucket.ts @@ -140,7 +140,7 @@ export class OverallBucket { /** The start time of the bucket for which these results were calculated. */ timestamp: EpochTime /** The start time of the bucket for which these results were calculated. */ - timestamp_string: DateTime + timestamp_string?: DateTime } export class OverallBucketJob { job_id: Id diff --git a/specification/ml/_types/Datafeed.ts b/specification/ml/_types/Datafeed.ts index c9df56e314..e9e63ee692 100644 --- a/specification/ml/_types/Datafeed.ts +++ b/specification/ml/_types/Datafeed.ts @@ -28,10 +28,11 @@ import { ScriptField } from '@_types/Scripting' import { Duration, DurationValue, + EpochTime, UnitFloatMillis, UnitMillis } from '@_types/Time' -import { DiscoveryNode } from './DiscoveryNode' +import { DiscoveryNodeCompact } from './DiscoveryNode' export class Datafeed { /** @aliases aggs */ @@ -154,7 +155,7 @@ export class DatafeedStats { * For started datafeeds only, this information pertains to the node upon which the datafeed is started. * @availability stack */ - node?: DiscoveryNode + node?: DiscoveryNodeCompact /** * The status of the datafeed, which can be one of the following values: `starting`, `started`, `stopping`, `stopped`. */ @@ -162,7 +163,7 @@ export class DatafeedStats { /** * An object that provides statistical information about timing aspect of this datafeed. */ - timing_stats: DatafeedTimingStats + timing_stats?: DatafeedTimingStats /** * An object containing the running state for this datafeed. * It is only provided if the datafeed is started. @@ -179,6 +180,9 @@ export class DatafeedTimingStats { * The exponential average search time per hour, in milliseconds. */ exponential_average_search_time_per_hour_ms: DurationValue + + exponential_average_calculation_context?: ExponentialAverageCalculationContext + /** * Identifier for the anomaly detection job. */ @@ -197,6 +201,12 @@ export class DatafeedTimingStats { average_search_time_per_bucket_ms?: DurationValue } +export class ExponentialAverageCalculationContext { + incremental_metric_value_ms: DurationValue + latest_timestamp?: EpochTime + previous_exponential_average_ms?: DurationValue +} + export class DatafeedRunningState { /** * Indicates if the datafeed is "real-time"; meaning that the datafeed has no configured `end` time. diff --git a/specification/ml/_types/DataframeAnalytics.ts b/specification/ml/_types/DataframeAnalytics.ts index fbafef44ae..95d4b3e9db 100644 --- a/specification/ml/_types/DataframeAnalytics.ts +++ b/specification/ml/_types/DataframeAnalytics.ts @@ -25,6 +25,7 @@ import { Id, IndexName, Indices, + Metadata, Name, VersionString } from '@_types/common' @@ -318,6 +319,7 @@ export class DataframeAnalyticsSummary { model_memory_limit?: string source: DataframeAnalyticsSource version?: VersionString + _meta?: Metadata } export class DataframeAnalytics { diff --git a/specification/ml/_types/Detector.ts b/specification/ml/_types/Detector.ts index 205031d14d..849ac84410 100644 --- a/specification/ml/_types/Detector.ts +++ b/specification/ml/_types/Detector.ts @@ -124,6 +124,24 @@ export class DetectorRead implements OverloadOf { use_null?: boolean } +export class DetectorUpdate { + /** + * A unique identifier for the detector. + * This identifier is based on the order of the detectors in the `analysis_config`, starting at zero. + */ + detector_index: integer + /** + * A description of the detector. + */ + description?: string + /** + * An array of custom rule objects, which enable you to customize the way detectors operate. + * For example, a rule may dictate to the detector conditions under which results should be skipped. + * Kibana refers to custom rules as job rules. + */ + custom_rules?: DetectionRule[] +} + export enum ExcludeFrequent { all, none, diff --git a/specification/ml/_types/DiscoveryNode.ts b/specification/ml/_types/DiscoveryNode.ts index 5c213f3b0a..578179f9cb 100644 --- a/specification/ml/_types/DiscoveryNode.ts +++ b/specification/ml/_types/DiscoveryNode.ts @@ -17,14 +17,32 @@ * under the License. */ -import { Dictionary } from '@spec_utils/Dictionary' -import { Id, Name } from '@_types/common' +import { Dictionary, SingleKeyDictionary } from '@spec_utils/Dictionary' +import { Id, Name, VersionString } from '@_types/common' import { TransportAddress } from '@_types/Networking' +import { integer } from '@_types/Numeric' -export class DiscoveryNode { +export type DiscoveryNode = SingleKeyDictionary + +export class DiscoveryNodeContent { + name?: Name + ephemeral_id: Id + transport_address: TransportAddress + external_id: string attributes: Dictionary + roles: string[] + version: VersionString + min_index_version: integer + max_index_version: integer +} + +/** + * Alternative representation of DiscoveryNode used in ml.get_job_stats and ml.get_datafeed_stats + */ +export class DiscoveryNodeCompact { + name: Name ephemeral_id: Id id: Id - name: Name transport_address: TransportAddress + attributes: Dictionary } diff --git a/specification/ml/_types/Job.ts b/specification/ml/_types/Job.ts index b15656ac05..2eed0dcf4d 100644 --- a/specification/ml/_types/Job.ts +++ b/specification/ml/_types/Job.ts @@ -30,7 +30,7 @@ import { DurationValue, UnitFloatMillis } from '@_types/Time' -import { DiscoveryNode } from './DiscoveryNode' +import { DiscoveryNodeCompact } from './DiscoveryNode' import { ModelSizeStats } from './Model' export enum JobState { @@ -310,7 +310,7 @@ export class JobStats { * This information is available only for open jobs. * @availability stack */ - node?: DiscoveryNode + node?: DiscoveryNodeCompact /** * For open jobs only, the elapsed time for which the job has been open. */ diff --git a/specification/ml/_types/Model.ts b/specification/ml/_types/Model.ts index 806d14faf2..5ad5eb0e38 100644 --- a/specification/ml/_types/Model.ts +++ b/specification/ml/_types/Model.ts @@ -64,6 +64,7 @@ export class ModelSizeStats { model_bytes: ByteSize model_bytes_exceeded?: ByteSize model_bytes_memory_limit?: ByteSize + output_memory_allocator_bytes?: ByteSize peak_model_bytes?: ByteSize assignment_memory_basis?: string result_type: string diff --git a/specification/ml/_types/TrainedModel.ts b/specification/ml/_types/TrainedModel.ts index 439444e403..d21c37e678 100644 --- a/specification/ml/_types/TrainedModel.ts +++ b/specification/ml/_types/TrainedModel.ts @@ -24,6 +24,7 @@ import { Field, Id, IndexName, + Metadata, Name, VersionString } from '@_types/common' @@ -59,15 +60,16 @@ export class TrainedModelStats { } export class TrainedModelDeploymentStats { + adaptive_allocations?: AdaptiveAllocationsSettings /** The detailed allocation status for the deployment. */ - allocation_status: TrainedModelDeploymentAllocationStatus + allocation_status?: TrainedModelDeploymentAllocationStatus cache_size?: ByteSize /** The unique identifier for the trained model deployment. */ deployment_id: Id /** The sum of `error_count` for all nodes in the deployment. */ - error_count: integer + error_count?: integer /** The sum of `inference_count` for all nodes in the deployment. */ - inference_count: integer + inference_count?: integer /** The unique identifier for the trained model. */ model_id: Id /** @@ -76,28 +78,38 @@ export class TrainedModelDeploymentStats { */ nodes: TrainedModelDeploymentNodesStats[] /** The number of allocations requested. */ - number_of_allocations: integer + number_of_allocations?: integer + + peak_throughput_per_minute: long + + priority: TrainingPriority /** The number of inference requests that can be queued before new requests are rejected. */ - queue_capacity: integer + queue_capacity?: integer /** * The sum of `rejected_execution_count` for all nodes in the deployment. * Individual nodes reject an inference request if the inference queue is full. * The queue size is controlled by the `queue_capacity` setting in the start * trained model deployment API. */ - rejected_execution_count: integer + rejected_execution_count?: integer /** The reason for the current deployment state. Usually only populated when * the model is not deployed to a node. */ - reason: string + reason?: string /** The epoch timestamp when the deployment started. */ start_time: EpochTime /** The overall state of the deployment. */ - state: DeploymentAssignmentState + state?: DeploymentAssignmentState /** The number of threads used be each allocation during inference. */ - threads_per_allocation: integer + threads_per_allocation?: integer /** The sum of `timeout_count` for all nodes in the deployment. */ - timeout_count: integer + timeout_count?: integer +} + +export class AdaptiveAllocationsSettings { + enabled: boolean + min_number_of_allocations?: integer + max_number_of_allocations?: integer } export class TrainedModelInferenceStats { @@ -131,34 +143,49 @@ export class TrainedModelSizeStats { export class TrainedModelDeploymentNodesStats { /** The average time for each inference call to complete on this node. */ - average_inference_time_ms: DurationValue + average_inference_time_ms?: DurationValue + + average_inference_time_ms_last_minute?: DurationValue + + /** The average time for each inference call to complete on this node, excluding cache */ + average_inference_time_ms_excluding_cache_hits?: DurationValue + /** The number of errors when evaluating the trained model. */ - error_count: integer + error_count?: integer /** The total number of inference calls made against this node for this model. */ - inference_count: integer + inference_count?: long + + inference_cache_hit_count?: long + + inference_cache_hit_count_last_minute?: long + /** The epoch time stamp of the last inference call for the model on this node. */ - last_access: long + last_access?: EpochTime /** * Information pertaining to the node. * @availability stack */ - node: DiscoveryNode + node?: DiscoveryNode /** * The number of allocations assigned to this node. */ - number_of_allocations: integer + number_of_allocations?: integer /** The number of inference requests queued to be processed. */ - number_of_pending_requests: integer + number_of_pending_requests?: integer + + peak_throughput_per_minute: long /** The number of inference requests that were not processed because the queue was full. */ - rejection_execution_count: integer + rejection_execution_count?: integer /** The current routing state and reason for the current routing state for this allocation. */ routing_state: TrainedModelAssignmentRoutingTable /** The epoch timestamp when the allocation started. */ - start_time: EpochTime + start_time?: EpochTime /** The number of threads used by each allocation during inference. */ - threads_per_allocation: integer + threads_per_allocation?: integer + + throughput_last_minute: integer /** The number of inference requests that timed out before being processed. */ - timeout_count: integer + timeout_count?: integer } export class TrainedModelConfig { @@ -194,6 +221,7 @@ export class TrainedModelConfig { /** An object containing metadata about the trained model. For example, models created by data frame analytics contain analysis_config and input objects. */ metadata?: TrainedModelConfigMetadata model_size_bytes?: ByteSize + model_package?: ModelPackageConfig location?: TrainedModelLocation prefix_strings?: TrainedModelPrefixStrings } @@ -213,6 +241,23 @@ export class TrainedModelConfigMetadata { total_feature_importance?: TotalFeatureImportance[] } +export class ModelPackageConfig { + create_time?: EpochTime + description?: string + inference_config?: Dictionary + metadata?: Metadata + minimum_version?: string + model_repository?: string + model_type?: string + packaged_model_id: Id + platform_architecture?: string + prefix_strings?: TrainedModelPrefixStrings + size?: ByteSize + sha256?: string + tags?: string[] + vocabulary_file?: string +} + export class Hyperparameter { /** * A positive number showing how much the parameter influences the variation of the loss function. For hyperparameters with values that are not specified by the user but tuned during hyperparameter optimization. @@ -313,7 +358,7 @@ export class TrainedModelAssignmentTaskParameters { /** * The size of the trained model in bytes. */ - model_bytes: integer + model_bytes: ByteSize /** * The unique identifier for the trained model. */ @@ -327,13 +372,16 @@ export class TrainedModelAssignmentTaskParameters { * @availability stack since=8.4.0 * @availability serverless */ - cache_size: ByteSize + cache_size?: ByteSize /** * The total number of allocations this model is assigned across ML nodes. */ number_of_allocations: integer priority: TrainingPriority + per_deployment_memory_bytes: ByteSize + per_allocation_memory_bytes: ByteSize + /** * Number of inference requests are allowed in the queue at a time. */ @@ -372,7 +420,7 @@ export class TrainedModelAssignmentRoutingTable { * The reason for the current state. It is usually populated only when the * `routing_state` is `failed`. */ - reason: string + reason?: string /** * The current routing state. */ @@ -397,11 +445,13 @@ export class TrainedModelDeploymentAllocationStatus { } export class TrainedModelAssignment { + adaptive_allocations?: AdaptiveAllocationsSettings | null /** * The overall assignment state. */ assignment_state: DeploymentAssignmentState max_assigned_allocations?: integer + reason?: string /** * The allocation state for each node. */ diff --git a/specification/ml/_types/inference.ts b/specification/ml/_types/inference.ts index 5da1fe821c..856120e27c 100644 --- a/specification/ml/_types/inference.ts +++ b/specification/ml/_types/inference.ts @@ -114,6 +114,8 @@ export class ClassificationInferenceOptions { export class TokenizationConfigContainer { /** Indicates BERT tokenization and its options */ bert?: NlpBertTokenizationConfig + /** Indicates BERT Japanese tokenization and its options */ + bert_ja?: NlpBertTokenizationConfig /** * Indicates MPNET tokenization and its options * @availability stack since=8.1.0 @@ -128,62 +130,44 @@ export class TokenizationConfigContainer { roberta?: NlpRobertaTokenizationConfig } -/** BERT and MPNet tokenization configuration options */ -export class NlpBertTokenizationConfig { +export class CommonTokenizationConfig { /** * Should the tokenizer lower case the text * @server_default false */ do_lower_case?: boolean - /** - * Is tokenization completed with special tokens - * @server_default true - */ - with_special_tokens?: boolean /** * Maximum input sequence length for the model * @server_default 512 */ max_sequence_length?: integer + /** + * Tokenization spanning options. Special value of -1 indicates no spanning takes place + * @server_default -1 + */ + span?: integer /** * Should tokenization input be automatically truncated before sending to the model for inference * @server_default first */ truncate?: TokenizationTruncate /** - * Tokenization spanning options. Special value of -1 indicates no spanning takes place - * @server_default -1 + * Is tokenization completed with special tokens + * @server_default true */ - span?: integer + with_special_tokens?: boolean } +/** BERT and MPNet tokenization configuration options */ +export class NlpBertTokenizationConfig extends CommonTokenizationConfig {} + /** RoBERTa tokenization configuration options */ -export class NlpRobertaTokenizationConfig { +export class NlpRobertaTokenizationConfig extends CommonTokenizationConfig { /** * Should the tokenizer prefix input with a space character * @server_default false */ add_prefix_space?: boolean - /** - * Is tokenization completed with special tokens - * @server_default true - */ - with_special_tokens?: boolean - /** - * Maximum input sequence length for the model - * @server_default 512 - */ - max_sequence_length?: integer - /** - * Should tokenization input be automatically truncated before sending to the model for inference - * @server_default first - */ - truncate?: TokenizationTruncate - /** - * Tokenization spanning options. Special value of -1 indicates no spanning takes place - * @server_default -1 - */ - span?: integer } /** Text classification configuration options */ @@ -242,6 +226,8 @@ export class TextEmbeddingInferenceOptions { tokenization?: TokenizationConfigContainer /** The field that is added to incoming documents to contain the inference prediction. Defaults to predicted_value. */ results_field?: string + + vocabulary: Vocabulary } /** Text expansion inference options */ @@ -250,6 +236,7 @@ export class TextExpansionInferenceOptions { tokenization?: TokenizationConfigContainer /** The field that is added to incoming documents to contain the inference prediction. Defaults to predicted_value. */ results_field?: string + vocabulary: Vocabulary } /** Named entity recognition options */ @@ -277,6 +264,7 @@ export class FillMaskInferenceOptions { tokenization?: TokenizationConfigContainer /** The field that is added to incoming documents to contain the inference prediction. Defaults to predicted_value. */ results_field?: string + vocabulary: Vocabulary } /** Question answering inference options */ diff --git a/specification/ml/get_trained_models/MlGetTrainedModelRequest.ts b/specification/ml/get_trained_models/MlGetTrainedModelRequest.ts index 738eaa7fb5..d4bce525e7 100644 --- a/specification/ml/get_trained_models/MlGetTrainedModelRequest.ts +++ b/specification/ml/get_trained_models/MlGetTrainedModelRequest.ts @@ -77,6 +77,13 @@ export interface Request extends RequestBase { * body. */ include?: Include + + /** + * parameter is deprecated! Use [include=definition] instead + * @deprecated 7.10.0 + */ + include_model_definition?: boolean + /** * Specifies the maximum number of models to obtain. * @server_default 100 diff --git a/specification/ml/info/types.ts b/specification/ml/info/types.ts index 0fd3132f31..e1f7567656 100644 --- a/specification/ml/info/types.ts +++ b/specification/ml/info/types.ts @@ -18,7 +18,7 @@ */ import { CategorizationAnalyzer } from '@ml/_types/Analysis' -import { VersionString } from '@_types/common' +import { ByteSize, VersionString } from '@_types/common' import { integer } from '@_types/Numeric' export class Defaults { @@ -32,9 +32,11 @@ export class NativeCode { } export class Limits { - max_model_memory_limit?: string - effective_max_model_memory_limit: string - total_ml_memory: string + max_single_ml_node_processors?: integer + total_ml_processors?: integer + max_model_memory_limit?: ByteSize + effective_max_model_memory_limit?: ByteSize + total_ml_memory: ByteSize } export class Datafeeds { diff --git a/specification/ml/post_data/MlPostJobDataResponse.ts b/specification/ml/post_data/MlPostJobDataResponse.ts index 55a530ff43..d6fb5a9de7 100644 --- a/specification/ml/post_data/MlPostJobDataResponse.ts +++ b/specification/ml/post_data/MlPostJobDataResponse.ts @@ -18,24 +18,28 @@ */ import { Id } from '@_types/common' -import { integer, long } from '@_types/Numeric' +import { long } from '@_types/Numeric' +import { EpochTime, UnitMillis } from '@_types/Time' export class Response { body: { - bucket_count: long - earliest_record_timestamp: long - empty_bucket_count: long + job_id: Id + processed_record_count: long + processed_field_count: long input_bytes: long input_field_count: long - input_record_count: long invalid_date_count: long - job_id: Id - last_data_time: integer - latest_record_timestamp: long missing_field_count: long out_of_order_timestamp_count: long - processed_field_count: long - processed_record_count: long + empty_bucket_count: long sparse_bucket_count: long + bucket_count: long + earliest_record_timestamp?: EpochTime + latest_record_timestamp?: EpochTime + last_data_time?: EpochTime + latest_empty_bucket_timestamp?: EpochTime + latest_sparse_bucket_timestamp?: EpochTime + input_record_count: long + log_time?: EpochTime } } diff --git a/specification/ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts b/specification/ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts index 932cfe3f88..cd36199e18 100644 --- a/specification/ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts +++ b/specification/ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts @@ -24,7 +24,7 @@ import { DataframeAnalyticsSource } from '@ml/_types/DataframeAnalytics' import { RequestBase } from '@_types/Base' -import { HttpHeaders, Id, VersionString } from '@_types/common' +import { HttpHeaders, Id, Metadata, VersionString } from '@_types/common' import { integer } from '@_types/Numeric' /** @@ -115,6 +115,8 @@ export interface Request extends RequestBase { * @server_default 1 */ max_num_threads?: integer + + _meta?: Metadata /** * The approximate maximum amount of memory resources that are permitted for * analytical processing. If your `elasticsearch.yml` file contains an diff --git a/specification/ml/put_data_frame_analytics/MlPutDataFrameAnalyticsResponse.ts b/specification/ml/put_data_frame_analytics/MlPutDataFrameAnalyticsResponse.ts index 2a308e8eee..be7ec033d3 100644 --- a/specification/ml/put_data_frame_analytics/MlPutDataFrameAnalyticsResponse.ts +++ b/specification/ml/put_data_frame_analytics/MlPutDataFrameAnalyticsResponse.ts @@ -24,7 +24,7 @@ import { DataframeAnalyticsDestination, DataframeAnalyticsSource } from '@ml/_types/DataframeAnalytics' -import { Id, VersionString } from '@_types/common' +import { Id, Metadata, VersionString } from '@_types/common' import { integer } from '@_types/Numeric' import { EpochTime, UnitMillis } from '@_types/Time' @@ -39,6 +39,7 @@ export class Response { dest: DataframeAnalyticsDestination id: Id max_num_threads: integer + _meta?: Metadata model_memory_limit: string source: DataframeAnalyticsSource version: VersionString diff --git a/specification/ml/put_datafeed/MlPutDatafeedRequest.ts b/specification/ml/put_datafeed/MlPutDatafeedRequest.ts index 34b496dc29..6a317c9640 100644 --- a/specification/ml/put_datafeed/MlPutDatafeedRequest.ts +++ b/specification/ml/put_datafeed/MlPutDatafeedRequest.ts @@ -87,8 +87,10 @@ export interface Request extends RequestBase { ignore_unavailable?: boolean } body: { - /** If set, the datafeed performs aggregation searches. + /** + * If set, the datafeed performs aggregation searches. * Support for aggregations is limited and should be used only with low cardinality data. + * @aliases aggs */ aggregations?: Dictionary /** diff --git a/specification/ml/put_job/MlPutJobRequest.ts b/specification/ml/put_job/MlPutJobRequest.ts index e2a79ae999..c15eb15c9c 100644 --- a/specification/ml/put_job/MlPutJobRequest.ts +++ b/specification/ml/put_job/MlPutJobRequest.ts @@ -23,7 +23,7 @@ import { DataDescription } from '@ml/_types/Job' import { ModelPlotConfig } from '@ml/_types/ModelPlot' import { CustomSettings } from '@ml/_types/Settings' import { RequestBase } from '@_types/Base' -import { Id, IndexName } from '@_types/common' +import { ExpandWildcards, Id, IndexName } from '@_types/common' import { long } from '@_types/Numeric' import { Duration } from '@_types/Time' @@ -44,6 +44,37 @@ export interface Request extends RequestBase { */ job_id: Id } + query_parameters: { + /** + * If `true`, wildcard indices expressions that resolve into no concrete indices are ignored. This includes the + * `_all` string or when no indices are specified. + * @server_default true + */ + allow_no_indices?: boolean + /** + * Type of index that wildcard patterns can match. If the request can target data streams, this argument determines + * whether wildcard expressions match hidden data streams. Supports comma-separated values. Valid values are: + * + * * `all`: Match any data stream or index, including hidden ones. + * * `closed`: Match closed, non-hidden indices. Also matches any non-hidden data stream. Data streams cannot be closed. + * * `hidden`: Match hidden data streams and hidden indices. Must be combined with `open`, `closed`, or both. + * * `none`: Wildcard patterns are not accepted. + * * `open`: Match open, non-hidden indices. Also matches any non-hidden data stream. + * @server_default open + */ + expand_wildcards?: ExpandWildcards + /** + * If `true`, concrete, expanded or aliased indices are ignored when frozen. + * @server_default true + * @deprecated 7.16.0 + */ + ignore_throttled?: boolean + /** + * If `true`, unavailable indices (missing or closed) are ignored. + * @server_default false + */ + ignore_unavailable?: boolean + } body: { /** * Advanced configuration option. Specifies whether this job can open when there is insufficient machine learning node capacity for it to be immediately assigned to a node. By default, if a machine learning node with capacity to run the job cannot immediately be found, the open anomaly detection jobs API returns an error. However, this is also subject to the cluster-wide `xpack.ml.max_lazy_ml_nodes` setting. If this option is set to true, the open anomaly detection jobs API does not return an error and the job waits in the opening state until sufficient machine learning node capacity is available. @@ -83,6 +114,10 @@ export interface Request extends RequestBase { * A description of the job. */ description?: string + /** + * The identifier for the anomaly detection job. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters. + */ + job_id?: Id /** * A list of job groups. A job can belong to no groups or many. */ diff --git a/specification/ml/update_job/MlUpdateJobRequest.ts b/specification/ml/update_job/MlUpdateJobRequest.ts index 6647a8f8a2..da51d765a0 100644 --- a/specification/ml/update_job/MlUpdateJobRequest.ts +++ b/specification/ml/update_job/MlUpdateJobRequest.ts @@ -21,7 +21,7 @@ import { AnalysisMemoryLimit, PerPartitionCategorization } from '@ml/_types/Analysis' -import { Detector } from '@ml/_types/Detector' +import { DetectorUpdate } from '@ml/_types/Detector' import { ModelPlotConfig } from '@ml/_types/ModelPlot' import { Dictionary } from '@spec_utils/Dictionary' import { UserDefinedValue } from '@spec_utils/UserDefinedValue' @@ -131,7 +131,7 @@ export interface Request extends RequestBase { /** * An array of detector update objects. */ - detectors?: Detector[] + detectors?: DetectorUpdate[] /** * Settings related to how categorization interacts with partition fields. */