> ## Documentation Index > Fetch the complete documentation index at: https://docs.domino.ai/llms.txt > Use this file to discover all available pages before exploring further. # Search runs > Search for runs that satisfy expressions. Search expressions can use :ref:`mlflowMetric` and :ref:`mlflowParam` keys. ## OpenAPI ````yaml /api-specs/cloud/public-api.json post /api/2.0/mlflow/runs/search openapi: 3.0.3 info: title: Domino Public API description: Reference for Domino's public REST API endpoints. version: 6.4.0 x-catalog-key: nucleus servers: - url: https://mycluster.domino.tech description: >- Replace 'mycluster.domino.tech' with your Domino cluster hostname. For Domino Cloud customers, that is `your-subdomain`.domino.tech (e.g., acme.domino.tech). For self-hosted deployments, it is the hostname you reach the Domino UI at. security: [] tags: - name: Projects - name: Project templates - name: Workspaces - name: Jobs - name: HPC Jobs - name: Environments - name: Hardware Tiers - name: Datasets - name: Data Sources - name: GenAI - name: AI Systems - name: MLflow experiments and runs - name: MLflow models - name: MLflow artifacts - name: MLflow traces - name: Apps - name: App versions - name: App instances - name: Model APIs - name: Registered models - name: Model deployment - name: Extensions - name: Cost and billing - name: Users and organizations - name: Service accounts - name: Personal Access Tokens - name: Personal Access Tokens (admin) - name: Audit Trail - name: Custom metrics - name: PPM - name: Model Monitoring models - name: Model Monitoring drift and quality - name: Model Monitoring settings - name: Model Monitoring authentication - name: Governance bundles - name: Governance policies - name: Governance evidence and results - name: Governance operations - name: NetApp Volumes - name: NetApp Volumes snapshots - name: NetApp Volumes filesystems - name: NetApp Volumes transfers - name: Tags - name: Properties externalDocs: description: OpenAPI url: https://swagger.io/resources/open-api/ paths: /api/2.0/mlflow/runs/search: post: tags: - MLflow experiments and runs description: >- Search for runs that satisfy expressions. Search expressions can use :ref:`mlflowMetric` and :ref:`mlflowParam` keys. operationId: runs.Search requestBody: content: application/json: schema: $ref: '#/components/schemas/mlflow-proxy_SearchRunsRequest' responses: '200': description: Runs matching search content: application/json: schema: $ref: '#/components/schemas/mlflow-proxy_SearchRunsResponse' default: $ref: '#/components/responses/mlflow-proxy_MLflowNativeError' components: schemas: mlflow-proxy_SearchRunsRequest: properties: experiment_ids: description: List of experiment IDs to search over. items: type: string type: array filter: description: >- A filter expression over params, metrics, and tags, that allows returning a subset of runs. The syntax is a subset of SQL that supports ANDing together binary operations between a param, metric, or tag and a constant. Example: ``metrics.rmse < 1 and params.model_class = 'LogisticRegression'`` You can select columns with special characters (hyphen, space, period, etc.) by using double quotes: ``metrics."model class" = 'LinearRegression' and tags."user-name" = 'Tomas'`` Supported operators are ``=``, ``!=``, ``>``, ``>=``, ``<``, and ``<=``. type: string max_results: default: 1000 description: Maximum number of runs desired. Max threshold is 50000 oneOf: - type: integer format: int32 - type: string order_by: description: >- List of columns to be ordered by, including attributes, params, metrics, and tags with an optional "DESC" or "ASC" annotation, where "ASC" is the default. Example: ["params.input DESC", "metrics.alpha ASC", "metrics.rmse"] Tiebreaks are done by start_time DESC followed by run_id for runs with the same start time (and this is the default ordering criterion if order_by is not provided). items: type: string type: array page_token: description: '' type: string run_view_type: default: ACTIVE_ONLY description: |- Whether to display only active, only deleted, or all runs. Defaults to only active runs. enum: - ACTIVE_ONLY - DELETED_ONLY - ALL type: string type: object mlflow-proxy_SearchRunsResponse: properties: next_page_token: description: '' type: string runs: description: Runs that match the search criteria. items: $ref: '#/components/schemas/mlflow-proxy_Run' type: array type: object mlflow-proxy_Run: description: >- Run metadata (name, start time, etc) and data (metrics, params, and tags). properties: data: $ref: '#/components/schemas/mlflow-proxy_RunData' info: $ref: '#/components/schemas/mlflow-proxy_RunInfo' inputs: $ref: '#/components/schemas/mlflow-proxy_RunInputs' required: - data - info - inputs type: object mlflow-proxy_ErrorResponse: properties: error_code: $ref: '#/components/schemas/mlflow-proxy_ErrorCode' message: description: Error message type: string required: - error_code - message type: object mlflow-proxy_RunData: properties: metrics: description: Run metrics. items: $ref: '#/components/schemas/mlflow-proxy_Metric' type: array params: description: Run parameters. items: $ref: '#/components/schemas/mlflow-proxy_Param' type: array tags: description: Additional metadata key-value pairs. items: $ref: '#/components/schemas/mlflow-proxy_Tag' type: array required: - tags type: object mlflow-proxy_RunInfo: properties: artifact_uri: description: >- URI of the directory where artifacts should be uploaded. This can be a local path (starting with "/"), or a distributed file system (DFS) path, like ``s3://bucket/directory`` or ``dbfs:/my/directory``. If not set, the local ``./mlruns`` directory is chosen. type: string end_time: description: Unix timestamp of when the run ended in milliseconds. type: integer format: int64 experiment_id: description: The experiment ID. type: string lifecycle_stage: description: >- Current life cycle stage of the experiment : OneOf("active", "deleted") type: string run_id: description: Unique identifier for the run. type: string run_name: description: Name for the run. type: string start_time: description: Unix timestamp of when the run started in milliseconds. type: integer format: int64 status: description: Current status of the run. enum: - RUNNING - SCHEDULED - FINISHED - FAILED - KILLED type: string user_id: description: >- User who initiated the run. This field is deprecated as of MLflow 1.0, and will be removed in a future MLflow release. Use 'mlflow.user' tag instead. type: string required: - artifact_uri - experiment_id - run_name - user_id - lifecycle_stage - run_id - start_time - status type: object mlflow-proxy_RunInputs: description: >- Run inputs. Experimental: This API may change or be removed in a future release without warning. properties: dataset_inputs: description: Dataset inputs to the Run. items: $ref: '#/components/schemas/mlflow-proxy_DatasetInput' type: array type: object mlflow-proxy_ErrorCode: description: Error code enum: - INTERNAL_ERROR - INVALID_STATE - DATA_LOSS - NOT_IMPLEMENTED - TEMPORARILY_UNAVAILABLE - DEADLINE_EXCEEDED - CANCELLED - RESOURCE_EXHAUSTED - REQUEST_LIMIT_EXCEEDED - ABORTED - RESOURCE_CONFLICT - ALREADY_EXISTS - NOT_FOUND - ENDPOINT_NOT_FOUND - RESOURCE_DOES_NOT_EXIST - PERMISSION_DENIED - CUSTOMER_UNAUTHORIZED - UNAUTHENTICATED - BAD_REQUEST - RESOURCE_ALREADY_EXISTS - INVALID_PARAMETER_VALUE type: string mlflow-proxy_Metric: properties: key: description: Key identifying this metric. type: string step: default: '0' description: Step at which to log the metric. type: integer format: int64 timestamp: description: The timestamp at which this metric was recorded. oneOf: - format: int64 type: integer - type: string value: description: Value associated with this metric. oneOf: - format: double type: number - type: string required: - key - value - step - timestamp type: object mlflow-proxy_Param: properties: key: description: Key identifying this param. type: string value: description: Value associated with this param. type: string required: - key - value type: object mlflow-proxy_Tag: properties: key: description: >- Name of the tag. Maximum size depends on storage backend. If a tag with this name already exists, its preexisting value will be replaced by the specified value. All storage backends are guaranteed to support key values up to 250 bytes in size. This field is required. type: string value: description: >- String value of the tag being logged. Maximum size depends on storage backend. All storage backends are guaranteed to support key values up to 5000 bytes in size. This field is required. type: string required: - key - value type: object mlflow-proxy_DatasetInput: description: >- Experimental: This API may change or be removed in a future release without warning. properties: tags: description: >- A list of tags for the dataset input, e.g. a "context" tag with value "training" items: $ref: '#/components/schemas/mlflow-proxy_Tag' type: array dataset: $ref: '#/components/schemas/mlflow-proxy_Dataset' required: - dataset - tags type: object mlflow-proxy_Dataset: description: >- Represents a reference to data used for training, testing, or evaluation during the model development process. Experimental: This API may change or be removed in a future release without warning. properties: name: description: >- The name of the dataset. E.g. "my.uc.table@2" "nyc-taxi-dataset", "fantastic-elk-3" This field is required. type: string digest: description: >- Dataset digest, e.g. an md5 hash of the dataset that uniquely identifies it within datasets of the same name. This field is required. type: string source_type: description: >- Source information for the dataset. Note that the source may not exactly reproduce the dataset if it was transformed / modified before use with MLflow. This field is required. type: string source: description: >- The type of the dataset source, e.g. "databricks-uc-table", "DBFS", "S3", … This field is required. type: string schema: description: >- The schema of the dataset. E.g., MLflow ColSpec JSON for a dataframe, MLflow TensorSpec JSON for an ndarray, or another schema format. type: string profile: description: >- The profile of the dataset. Summary statistics for the dataset, such as the number of rows in a table, the mean / std / mode of each column in a table, or the number of elements in an array. type: string required: - name - digest - source_type - source type: object responses: mlflow-proxy_MLflowNativeError: description: The client issued a bad request to the server content: application/json: schema: $ref: '#/components/schemas/mlflow-proxy_ErrorResponse' ```` ## Related topics - [The python-domino library](/cloud/reference/python-sdk/python-domino.md) - [Search experiments](/api-reference/mlflow-experiments-and-runs/post-api20mlflowexperimentssearch.md) - [Use Domino search](/cloud/platform-capabilities/features/collaboration/domino-search.md) - [Search model versions](/api-reference/mlflow-models/get-api20mlflowmodel-versionssearch.md)