Dashboards

These dataclasses are used in the SDK to represent API requests and responses for services in the databricks.sdk.service.dashboards module.

class databricks.sdk.service.dashboards.AuthorizationDetails(grant_rules: 'Optional[List[AuthorizationDetailsGrantRule]]' = None, resource_legacy_acl_path: 'Optional[str]' = None, resource_name: 'Optional[str]' = None, type: 'Optional[str]' = None)

grant_rules: List[AuthorizationDetailsGrantRule] | None = None

Represents downscoped permission rules with specific access rights. This field is specific to workspace_rule_set constraint.

resource_legacy_acl_path: str | None = None

The acl path of the tree store resource resource.

resource_name: str | None = None

The resource name to which the authorization rule applies. This field is specific to workspace_rule_set constraint. Format: workspaces/{workspace_id}/dashboards/{dashboard_id}

type: str | None = None

The type of authorization downscoping policy. Ex: workspace_rule_set defines access rules for a specific workspace resource

as_dict() → dict

Serializes the AuthorizationDetails into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the AuthorizationDetails into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → AuthorizationDetails

Deserializes the AuthorizationDetails from a dictionary.

class databricks.sdk.service.dashboards.AuthorizationDetailsGrantRule(permission_set: 'Optional[str]' = None)

permission_set: str | None = None

Permission sets for dashboard are defined in iam-common/rbac-common/permission-sets/definitions/TreeStoreBasePermissionSets Ex: permissionSets/dashboard.runner

as_dict() → dict

Serializes the AuthorizationDetailsGrantRule into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the AuthorizationDetailsGrantRule into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → AuthorizationDetailsGrantRule

Deserializes the AuthorizationDetailsGrantRule from a dictionary.

class databricks.sdk.service.dashboards.CronSchedule(quartz_cron_expression: 'str', timezone_id: 'str')

quartz_cron_expression: str

A cron expression using quartz syntax. EX: 0 0 8 * * ? represents everyday at 8am. See [Cron Trigger] for details.

[Cron Trigger]: http://www.quartz-scheduler.org/documentation/quartz-2.3.0/tutorials/crontrigger.html

timezone_id: str

A Java timezone id. The schedule will be resolved with respect to this timezone. See [Java TimeZone] for details.

[Java TimeZone]: https://docs.oracle.com/javase/7/docs/api/java/util/TimeZone.html

as_dict() → dict

Serializes the CronSchedule into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the CronSchedule into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → CronSchedule

Deserializes the CronSchedule from a dictionary.

class databricks.sdk.service.dashboards.Dashboard(create_time: 'Optional[str]' = None, dashboard_id: 'Optional[str]' = None, display_name: 'Optional[str]' = None, etag: 'Optional[str]' = None, lifecycle_state: 'Optional[LifecycleState]' = None, parent_path: 'Optional[str]' = None, path: 'Optional[str]' = None, serialized_dashboard: 'Optional[str]' = None, update_time: 'Optional[str]' = None, warehouse_id: 'Optional[str]' = None)

create_time: str | None = None

The timestamp of when the dashboard was created.

dashboard_id: str | None = None

UUID identifying the dashboard.

display_name: str | None = None

The display name of the dashboard.

etag: str | None = None

The etag for the dashboard. Can be optionally provided on updates to ensure that the dashboard has not been modified since the last read. This field is excluded in List Dashboards responses.

lifecycle_state: LifecycleState | None = None

The state of the dashboard resource. Used for tracking trashed status.

parent_path: str | None = None

The workspace path of the folder containing the dashboard. Includes leading slash and no trailing slash. This field is excluded in List Dashboards responses.

path: str | None = None

The workspace path of the dashboard asset, including the file name. Exported dashboards always have the file extension .lvdash.json. This field is excluded in List Dashboards responses.

serialized_dashboard: str | None = None

The contents of the dashboard in serialized string form. This field is excluded in List Dashboards responses. Use the [get dashboard API] to retrieve an example response, which includes the serialized_dashboard field. This field provides the structure of the JSON string that represents the dashboard’s layout and components.

[get dashboard API]: https://docs.databricks.com/api/workspace/lakeview/get

update_time: str | None = None

The timestamp of when the dashboard was last updated by the user. This field is excluded in List Dashboards responses.

warehouse_id: str | None = None

The warehouse ID used to run the dashboard.

as_dict() → dict

Serializes the Dashboard into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the Dashboard into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → Dashboard

Deserializes the Dashboard from a dictionary.

class databricks.sdk.service.dashboards.DashboardView

DASHBOARD_VIEW_BASIC = "DASHBOARD_VIEW_BASIC"

class databricks.sdk.service.dashboards.EvaluationStatusType

DONE = "DONE"

EVALUATION_CANCELLED = "EVALUATION_CANCELLED"

EVALUATION_FAILED = "EVALUATION_FAILED"

EVALUATION_TIMEOUT = "EVALUATION_TIMEOUT"

NOT_STARTED = "NOT_STARTED"

RUNNING = "RUNNING"

class databricks.sdk.service.dashboards.GenieAttachment(attachment_id: str | None = None, query: GenieQueryAttachment | None = None, suggested_questions: GenieSuggestedQuestionsAttachment | None = None, text: TextAttachment | None = None)

Genie AI Response

attachment_id: str | None = None

Attachment ID

query: GenieQueryAttachment | None = None

Query Attachment if Genie responds with a SQL query

suggested_questions: GenieSuggestedQuestionsAttachment | None = None

Follow-up questions suggested by Genie

text: TextAttachment | None = None

Text Attachment if Genie responds with text This also contains the final summary when available.

as_dict() → dict

Serializes the GenieAttachment into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieAttachment into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieAttachment

Deserializes the GenieAttachment from a dictionary.

class databricks.sdk.service.dashboards.GenieConversation(space_id: 'str', title: 'str', conversation_id: 'str', created_timestamp: 'Optional[int]' = None, id: 'Optional[str]' = None, last_updated_timestamp: 'Optional[int]' = None, user_id: 'Optional[int]' = None)

space_id: str

Genie space ID

title: str

Conversation title

conversation_id: str

Conversation ID

created_timestamp: int | None = None

Timestamp when the message was created

id: str | None = None

Conversation ID. Legacy identifier, use conversation_id instead

last_updated_timestamp: int | None = None

Timestamp when the message was last updated

user_id: int | None = None

ID of the user who created the conversation

as_dict() → dict

Serializes the GenieConversation into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieConversation into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieConversation

Deserializes the GenieConversation from a dictionary.

class databricks.sdk.service.dashboards.GenieConversationSummary(conversation_id: 'str', created_timestamp: 'Optional[int]' = None, title: 'Optional[str]' = None)

conversation_id: str

created_timestamp: int | None = None

title: str | None = None

as_dict() → dict

Serializes the GenieConversationSummary into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieConversationSummary into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieConversationSummary

Deserializes the GenieConversationSummary from a dictionary.

class databricks.sdk.service.dashboards.GenieEvalAssessment

BAD = "BAD"

GOOD = "GOOD"

NEEDS_REVIEW = "NEEDS_REVIEW"

class databricks.sdk.service.dashboards.GenieEvalResponse(response: 'Optional[str]' = None, response_type: 'Optional[GenieEvalResponseType]' = None, sql_execution_result: 'Optional[sql.StatementResponse]' = None)

response: str | None = None

The response content (either text or SQL query).

response_type: GenieEvalResponseType | None = None

Type of response

sql_execution_result: StatementResponse | None = None

SQL Statement Execution response.

as_dict() → dict

Serializes the GenieEvalResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieEvalResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieEvalResponse

Deserializes the GenieEvalResponse from a dictionary.

class databricks.sdk.service.dashboards.GenieEvalResponseType

SQL = "SQL"

TEXT = "TEXT"

class databricks.sdk.service.dashboards.GenieEvalResult(result_id: str, space_id: str, benchmark_question_id: str, benchmark_answer: str | None = None, created_by_user: int | None = None, question: str | None = None, status: EvaluationStatusType | None = None)

Shows summary information for an evaluation result. For detailed information including SQL execution results, actual/expected responses, and assessment scores, use GenieGetEvalResultDetails.

result_id: str

Unique identifier for this evaluation result.

space_id: str

The ID of the space the evaluation result belongs to.

benchmark_question_id: str

The ID of the benchmark question that was evaluated.

benchmark_answer: str | None = None

Stored snapshot of original benchmark answer text.

created_by_user: int | None = None

User ID who created evaluation result.

question: str | None = None

Stored snapshot of original benchmark question text.

status: EvaluationStatusType | None = None

Current status of this evaluation result.

as_dict() → dict

Serializes the GenieEvalResult into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieEvalResult into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieEvalResult

Deserializes the GenieEvalResult from a dictionary.

class databricks.sdk.service.dashboards.GenieEvalResultDetails(result_id: str, space_id: str, benchmark_question_id: str, actual_response: List[GenieEvalResponse] | None = None, assessment: GenieEvalAssessment | None = None, assessment_reasons: List[ScoreReason] | None = None, eval_run_status: EvaluationStatusType | None = None, expected_response: List[GenieEvalResponse] | None = None, manual_assessment: bool | None = None)

Shows detailed information for an evaluation result.

result_id: str

The unique identifier for the evaluation result.

space_id: str

The ID of the space the evaluation result belongs to.

benchmark_question_id: str

The ID of the benchmark question that was evaluated.

actual_response: List[GenieEvalResponse] | None = None

The actual response generated by Genie.

assessment: GenieEvalAssessment | None = None

Assessment of the evaluation result: good, bad, or needs review

assessment_reasons: List[ScoreReason] | None = None

Reasons for the assessment score.

Assessment reasons describe why a Genie response was scored as BAD.

Deterministic values (compared against the ground truth result): - EMPTY_RESULT: Genie’s generated SQL results were empty for this benchmark question. - RESULT_MISSING_ROWS: Genie’s generated SQL response is missing rows from the provided ground truth SQL. - RESULT_EXTRA_ROWS: Genie’s generated SQL response has more rows than the provided ground truth SQL. - RESULT_MISSING_COLUMNS: Genie’s generated SQL response is missing columns from the provided ground truth SQL. - RESULT_EXTRA_COLUMNS: Genie’s generated SQL response has more columns than the provided ground truth SQL. - SINGLE_CELL_DIFFERENCE: Single value result was produced but differs from ground truth result. - EMPTY_GOOD_SQL: The benchmark SQL returned an empty result. - COLUMN_TYPE_DIFFERENCE: The values between the results match but the column type is different.

LLM judge ratings explain the factors driving BAD results: - LLM_JUDGE_MISSING_OR_INCORRECT_FILTER: Genie’s generated SQL is missing a WHERE clause condition or has incorrect filter logic that excludes/includes wrong data. - LLM_JUDGE_INCOMPLETE_OR_PARTIAL_OUTPUT: Genie’s generated SQL returns only some of the requested data or columns, missing parts of what the ground truth SQL returns. - LLM_JUDGE_MISINTERPRETATION_OF_USER_REQUEST: Genie’s generated SQL fundamentally misunderstands what the user is asking for, addressing the wrong question or goal. - LLM_JUDGE_INSTRUCTION_COMPLIANCE_OR_MISSING_BUSINESS_LOGIC: Genie’s generated SQL fails to apply specified instructions or business logic that should be followed. - LLM_JUDGE_INCORRECT_METRIC_CALCULATION: Genie’s generated SQL uses incorrect logic or makes wrong assumptions when calculating metrics. - LLM_JUDGE_INCORRECT_TABLE_OR_FIELD_USAGE: Genie’s generated SQL references wrong tables, columns, or uses fields that don’t match the ground truth SQL’s intent. - LLM_JUDGE_INCORRECT_FUNCTION_USAGE: Genie’s generated SQL uses SQL functions incorrectly or inappropriately (wrong parameters, wrong function for the task, etc.). - LLM_JUDGE_MISSING_OR_INCORRECT_JOIN: Genie’s generated SQL is missing necessary joins between tables or has incorrect join conditions/types that produce wrong results. - LLM_JUDGE_MISSING_OR_INCORRECT_AGGREGATION: Genie’s generated SQL is missing GROUP BY clauses or has incorrect grouping that doesn’t match the requested aggregation level. - LLM_JUDGE_FORMATTING_ERROR: Genie’s generated SQL output has incorrect formatting, ordering (ORDER BY), or presentation issues that don’t match expectations. - LLM_JUDGE_OTHER: LLM judge identified an error that doesn’t fall into other categories.

Deprecated LLM judge values (kept for backward compatibility, do not use): - LLM_JUDGE_MISSING_JOIN (deprecated) - LLM_JUDGE_WRONG_FILTER (deprecated) - LLM_JUDGE_WRONG_AGGREGATION (deprecated) - LLM_JUDGE_WRONG_COLUMNS (deprecated) - LLM_JUDGE_SYNTAX_ERROR (deprecated) - LLM_JUDGE_SEMANTIC_ERROR (deprecated)

eval_run_status: EvaluationStatusType | None = None

Current status of the evaluation run.

expected_response: List[GenieEvalResponse] | None = None

The expected responses from the benchmark.

manual_assessment: bool | None = None

Whether this evaluation was manually assessed.

as_dict() → dict

Serializes the GenieEvalResultDetails into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieEvalResultDetails into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieEvalResultDetails

Deserializes the GenieEvalResultDetails from a dictionary.

class databricks.sdk.service.dashboards.GenieEvalRunResponse(eval_run_id: 'str', created_timestamp: 'Optional[int]' = None, eval_run_status: 'Optional[EvaluationStatusType]' = None, last_updated_timestamp: 'Optional[int]' = None, num_correct: 'Optional[int]' = None, num_done: 'Optional[int]' = None, num_needs_review: 'Optional[int]' = None, num_questions: 'Optional[int]' = None, run_by_user: 'Optional[int]' = None)

eval_run_id: str

The unique identifier for the evaluation run.

created_timestamp: int | None = None

Timestamp when the evaluation run was created (milliseconds since epoch).

eval_run_status: EvaluationStatusType | None = None

Current status of the evaluation run.

last_updated_timestamp: int | None = None

Timestamp when the evaluation run was last updated (milliseconds since epoch).

num_correct: int | None = None

Number of questions answered correctly.

num_done: int | None = None

Number of questions that have been completed.

num_needs_review: int | None = None

Number of questions that need manual review.

num_questions: int | None = None

Total number of questions in the evaluation run.

run_by_user: int | None = None

User ID who initiated the evaluation run.

as_dict() → dict

Serializes the GenieEvalRunResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieEvalRunResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieEvalRunResponse

Deserializes the GenieEvalRunResponse from a dictionary.

class databricks.sdk.service.dashboards.GenieFeedback(comment: str | None = None, rating: GenieFeedbackRating | None = None)

Feedback containing rating and optional comment

comment: str | None = None

Optional feedback comment text

rating: GenieFeedbackRating | None = None

The feedback rating

as_dict() → dict

Serializes the GenieFeedback into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieFeedback into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieFeedback

Deserializes the GenieFeedback from a dictionary.

class databricks.sdk.service.dashboards.GenieFeedbackRating

Feedback rating for Genie messages

NEGATIVE = "NEGATIVE"

NONE = "NONE"

POSITIVE = "POSITIVE"

class databricks.sdk.service.dashboards.GenieGenerateDownloadFullQueryResultResponse(download_id: 'Optional[str]' = None, download_id_signature: 'Optional[str]' = None)

download_id: str | None = None

Download ID. Use this ID to track the download request in subsequent polling calls

download_id_signature: str | None = None

JWT signature for the download_id to ensure secure access to query results

as_dict() → dict

Serializes the GenieGenerateDownloadFullQueryResultResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieGenerateDownloadFullQueryResultResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieGenerateDownloadFullQueryResultResponse

Deserializes the GenieGenerateDownloadFullQueryResultResponse from a dictionary.

class databricks.sdk.service.dashboards.GenieGetDownloadFullQueryResultResponse(statement_response: 'Optional[sql.StatementResponse]' = None)

statement_response: StatementResponse | None = None

SQL Statement Execution response. See [Get status, manifest, and result first chunk](:method:statementexecution/getstatement) for more details.

as_dict() → dict

Serializes the GenieGetDownloadFullQueryResultResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieGetDownloadFullQueryResultResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieGetDownloadFullQueryResultResponse

Deserializes the GenieGetDownloadFullQueryResultResponse from a dictionary.

class databricks.sdk.service.dashboards.GenieGetMessageQueryResultResponse(statement_response: 'Optional[sql.StatementResponse]' = None)

statement_response: StatementResponse | None = None

SQL Statement Execution response. See [Get status, manifest, and result first chunk](:method:statementexecution/getstatement) for more details.

as_dict() → dict

Serializes the GenieGetMessageQueryResultResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieGetMessageQueryResultResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieGetMessageQueryResultResponse

Deserializes the GenieGetMessageQueryResultResponse from a dictionary.

class databricks.sdk.service.dashboards.GenieListConversationCommentsResponse(comments: 'Optional[List[GenieMessageComment]]' = None, next_page_token: 'Optional[str]' = None)

comments: List[GenieMessageComment] | None = None

List of comments in the conversation.

next_page_token: str | None = None

Token to get the next page of results.

as_dict() → dict

Serializes the GenieListConversationCommentsResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieListConversationCommentsResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieListConversationCommentsResponse

Deserializes the GenieListConversationCommentsResponse from a dictionary.

class databricks.sdk.service.dashboards.GenieListConversationMessagesResponse(messages: 'Optional[List[GenieMessage]]' = None, next_page_token: 'Optional[str]' = None)

messages: List[GenieMessage] | None = None

List of messages in the conversation.

next_page_token: str | None = None

The token to use for retrieving the next page of results.

as_dict() → dict

Serializes the GenieListConversationMessagesResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieListConversationMessagesResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieListConversationMessagesResponse

Deserializes the GenieListConversationMessagesResponse from a dictionary.

class databricks.sdk.service.dashboards.GenieListConversationsResponse(conversations: 'Optional[List[GenieConversationSummary]]' = None, next_page_token: 'Optional[str]' = None)

conversations: List[GenieConversationSummary] | None = None

List of conversations in the Genie space

next_page_token: str | None = None

Token to get the next page of results

as_dict() → dict

Serializes the GenieListConversationsResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieListConversationsResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieListConversationsResponse

Deserializes the GenieListConversationsResponse from a dictionary.

class databricks.sdk.service.dashboards.GenieListEvalResultsResponse(eval_results: 'Optional[List[GenieEvalResult]]' = None, next_page_token: 'Optional[str]' = None)

eval_results: List[GenieEvalResult] | None = None

List of evaluation results for the specified run.

next_page_token: str | None = None

The token to use for retrieving the next page of results.

as_dict() → dict

Serializes the GenieListEvalResultsResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieListEvalResultsResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieListEvalResultsResponse

Deserializes the GenieListEvalResultsResponse from a dictionary.

class databricks.sdk.service.dashboards.GenieListEvalRunsResponse(eval_runs: 'Optional[List[GenieEvalRunResponse]]' = None, next_page_token: 'Optional[str]' = None)

eval_runs: List[GenieEvalRunResponse] | None = None

List of evaluation runs for a space on provided page token and page size

next_page_token: str | None = None

The token to use for retrieving the next page of results.

as_dict() → dict

Serializes the GenieListEvalRunsResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieListEvalRunsResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieListEvalRunsResponse

Deserializes the GenieListEvalRunsResponse from a dictionary.

class databricks.sdk.service.dashboards.GenieListMessageCommentsResponse(comments: 'Optional[List[GenieMessageComment]]' = None, next_page_token: 'Optional[str]' = None)

comments: List[GenieMessageComment] | None = None

List of comments on the message.

next_page_token: str | None = None

Token to get the next page of results.

as_dict() → dict

Serializes the GenieListMessageCommentsResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieListMessageCommentsResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieListMessageCommentsResponse

Deserializes the GenieListMessageCommentsResponse from a dictionary.

class databricks.sdk.service.dashboards.GenieListSpacesResponse(next_page_token: 'Optional[str]' = None, spaces: 'Optional[List[GenieSpace]]' = None)

next_page_token: str | None = None

Token to get the next page of results

spaces: List[GenieSpace] | None = None

List of Genie spaces

as_dict() → dict

Serializes the GenieListSpacesResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieListSpacesResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieListSpacesResponse

Deserializes the GenieListSpacesResponse from a dictionary.

class databricks.sdk.service.dashboards.GenieMessage(space_id: 'str', conversation_id: 'str', content: 'str', message_id: 'str', attachments: 'Optional[List[GenieAttachment]]' = None, created_timestamp: 'Optional[int]' = None, error: 'Optional[MessageError]' = None, feedback: 'Optional[GenieFeedback]' = None, id: 'Optional[str]' = None, last_updated_timestamp: 'Optional[int]' = None, query_result: 'Optional[Result]' = None, status: 'Optional[MessageStatus]' = None, user_id: 'Optional[int]' = None)

space_id: str

Genie space ID

conversation_id: str

Conversation ID

content: str

User message content

message_id: str

Message ID

attachments: List[GenieAttachment] | None = None

AI-generated response to the message

created_timestamp: int | None = None

Timestamp when the message was created

error: MessageError | None = None

Error message if Genie failed to respond to the message

feedback: GenieFeedback | None = None

User feedback for the message if provided

id: str | None = None

Message ID. Legacy identifier, use message_id instead

last_updated_timestamp: int | None = None

Timestamp when the message was last updated

query_result: Result | None = None

The result of SQL query if the message includes a query attachment. Deprecated. Use query_result_metadata in GenieQueryAttachment instead.

status: MessageStatus | None = None

user_id: int | None = None

ID of the user who created the message

as_dict() → dict

Serializes the GenieMessage into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieMessage into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieMessage

Deserializes the GenieMessage from a dictionary.

class databricks.sdk.service.dashboards.GenieMessageComment(space_id: str, conversation_id: str, message_id: str, message_comment_id: str, content: str, created_timestamp: int | None = None, user_id: int | None = None)

A comment on a Genie conversation message.

space_id: str

Genie space ID

conversation_id: str

Conversation ID

message_id: str

Message ID

message_comment_id: str

Comment ID

content: str

Comment text content

created_timestamp: int | None = None

Timestamp when the comment was created

user_id: int | None = None

ID of the user who created the comment

as_dict() → dict

Serializes the GenieMessageComment into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieMessageComment into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieMessageComment

Deserializes the GenieMessageComment from a dictionary.

class databricks.sdk.service.dashboards.GenieQueryAttachment(description: 'Optional[str]' = None, id: 'Optional[str]' = None, last_updated_timestamp: 'Optional[int]' = None, parameters: 'Optional[List[QueryAttachmentParameter]]' = None, query: 'Optional[str]' = None, query_result_metadata: 'Optional[GenieResultMetadata]' = None, statement_id: 'Optional[str]' = None, thoughts: 'Optional[List[Thought]]' = None, title: 'Optional[str]' = None)

description: str | None = None

Description of the query

id: str | None = None

last_updated_timestamp: int | None = None

Time when the user updated the query last

parameters: List[QueryAttachmentParameter] | None = None

query: str | None = None

AI generated SQL query

query_result_metadata: GenieResultMetadata | None = None

Metadata associated with the query result.

statement_id: str | None = None

Statement Execution API statement id. Use [Get status, manifest, and result first chunk](:method:statementexecution/getstatement) to get the full result data.

thoughts: List[Thought] | None = None

Insights into how Genie came to generate the SQL.

title: str | None = None

Name of the query

as_dict() → dict

Serializes the GenieQueryAttachment into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieQueryAttachment into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieQueryAttachment

Deserializes the GenieQueryAttachment from a dictionary.

class databricks.sdk.service.dashboards.GenieResultMetadata(is_truncated: 'Optional[bool]' = None, row_count: 'Optional[int]' = None)

is_truncated: bool | None = None

Indicates whether the result set is truncated.

row_count: int | None = None

The number of rows in the result set.

as_dict() → dict

Serializes the GenieResultMetadata into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieResultMetadata into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieResultMetadata

Deserializes the GenieResultMetadata from a dictionary.

class databricks.sdk.service.dashboards.GenieSpace(space_id: 'str', title: 'str', description: 'Optional[str]' = None, etag: 'Optional[str]' = None, parent_path: 'Optional[str]' = None, serialized_space: 'Optional[str]' = None, warehouse_id: 'Optional[str]' = None)

space_id: str

Genie space ID

title: str

Title of the Genie Space

description: str | None = None

Description of the Genie Space

etag: str | None = None

ETag for this space. Pass this value back in the update request to prevent overwriting concurrent changes.

parent_path: str | None = None

Parent folder path of the Genie Space

serialized_space: str | None = None

The contents of the Genie Space in serialized string form. This field is excluded in List Genie spaces responses. Use the [Get Genie Space](:method:genie/getspace) API to retrieve an example response, which includes the serialized_space field. This field provides the structure of the JSON string that represents the space’s layout and components.

warehouse_id: str | None = None

Warehouse associated with the Genie Space

as_dict() → dict

Serializes the GenieSpace into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieSpace into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieSpace

Deserializes the GenieSpace from a dictionary.

class databricks.sdk.service.dashboards.GenieStartConversationResponse(message_id: 'str', conversation_id: 'str', conversation: 'Optional[GenieConversation]' = None, message: 'Optional[GenieMessage]' = None)

message_id: str

Message ID

conversation_id: str

Conversation ID

conversation: GenieConversation | None = None

message: GenieMessage | None = None

as_dict() → dict

Serializes the GenieStartConversationResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieStartConversationResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieStartConversationResponse

Deserializes the GenieStartConversationResponse from a dictionary.

class databricks.sdk.service.dashboards.GenieSuggestedQuestionsAttachment(questions: List[str] | None = None)

Follow-up questions suggested by Genie

questions: List[str] | None = None

The suggested follow-up questions

as_dict() → dict

Serializes the GenieSuggestedQuestionsAttachment into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GenieSuggestedQuestionsAttachment into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GenieSuggestedQuestionsAttachment

Deserializes the GenieSuggestedQuestionsAttachment from a dictionary.

class databricks.sdk.service.dashboards.GetPublishedDashboardTokenInfoResponse(authorization_details: 'Optional[List[AuthorizationDetails]]' = None, custom_claim: 'Optional[str]' = None, scope: 'Optional[str]' = None)

authorization_details: List[AuthorizationDetails] | None = None

Authorization constraints for accessing the published dashboard. Currently includes workspace_rule_set and could be enriched with unity_catalog_privileges before oAuth token generation.

custom_claim: str | None = None

Custom claim generated from external_value and external_viewer_id. Format: urn:aibi:external_data:<external_value>:<external_viewer_id>:<dashboard_id>

scope: str | None = None

Scope defining access permissions.

as_dict() → dict

Serializes the GetPublishedDashboardTokenInfoResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the GetPublishedDashboardTokenInfoResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → GetPublishedDashboardTokenInfoResponse

Deserializes the GetPublishedDashboardTokenInfoResponse from a dictionary.

class databricks.sdk.service.dashboards.LifecycleState

ACTIVE = "ACTIVE"

TRASHED = "TRASHED"

class databricks.sdk.service.dashboards.ListDashboardsResponse(dashboards: 'Optional[List[Dashboard]]' = None, next_page_token: 'Optional[str]' = None)

dashboards: List[Dashboard] | None = None

next_page_token: str | None = None

A token, which can be sent as page_token to retrieve the next page. If this field is omitted, there are no subsequent dashboards.

as_dict() → dict

Serializes the ListDashboardsResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the ListDashboardsResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → ListDashboardsResponse

Deserializes the ListDashboardsResponse from a dictionary.

class databricks.sdk.service.dashboards.ListSchedulesResponse(next_page_token: 'Optional[str]' = None, schedules: 'Optional[List[Schedule]]' = None)

next_page_token: str | None = None

A token that can be used as a page_token in subsequent requests to retrieve the next page of results. If this field is omitted, there are no subsequent schedules.

schedules: List[Schedule] | None = None

as_dict() → dict

Serializes the ListSchedulesResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the ListSchedulesResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → ListSchedulesResponse

Deserializes the ListSchedulesResponse from a dictionary.

class databricks.sdk.service.dashboards.ListSubscriptionsResponse(next_page_token: 'Optional[str]' = None, subscriptions: 'Optional[List[Subscription]]' = None)

next_page_token: str | None = None

A token that can be used as a page_token in subsequent requests to retrieve the next page of results. If this field is omitted, there are no subsequent subscriptions.

subscriptions: List[Subscription] | None = None

as_dict() → dict

Serializes the ListSubscriptionsResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the ListSubscriptionsResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → ListSubscriptionsResponse

Deserializes the ListSubscriptionsResponse from a dictionary.

class databricks.sdk.service.dashboards.MessageError(error: 'Optional[str]' = None, type: 'Optional[MessageErrorType]' = None)

error: str | None = None

type: MessageErrorType | None = None

as_dict() → dict

Serializes the MessageError into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the MessageError into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → MessageError

Deserializes the MessageError from a dictionary.

class databricks.sdk.service.dashboards.MessageErrorType

BLOCK_MULTIPLE_EXECUTIONS_EXCEPTION = "BLOCK_MULTIPLE_EXECUTIONS_EXCEPTION"

CHAT_COMPLETION_CLIENT_EXCEPTION = "CHAT_COMPLETION_CLIENT_EXCEPTION"

CHAT_COMPLETION_CLIENT_TIMEOUT_EXCEPTION = "CHAT_COMPLETION_CLIENT_TIMEOUT_EXCEPTION"

CHAT_COMPLETION_NETWORK_EXCEPTION = "CHAT_COMPLETION_NETWORK_EXCEPTION"

CONTENT_FILTER_EXCEPTION = "CONTENT_FILTER_EXCEPTION"

CONTEXT_EXCEEDED_EXCEPTION = "CONTEXT_EXCEEDED_EXCEPTION"

COULD_NOT_GET_DASHBOARD_SCHEMA_EXCEPTION = "COULD_NOT_GET_DASHBOARD_SCHEMA_EXCEPTION"

COULD_NOT_GET_MODEL_DEPLOYMENTS_EXCEPTION = "COULD_NOT_GET_MODEL_DEPLOYMENTS_EXCEPTION"

COULD_NOT_GET_UC_SCHEMA_EXCEPTION = "COULD_NOT_GET_UC_SCHEMA_EXCEPTION"

DEPLOYMENT_NOT_FOUND_EXCEPTION = "DEPLOYMENT_NOT_FOUND_EXCEPTION"

DESCRIBE_QUERY_INVALID_SQL_ERROR = "DESCRIBE_QUERY_INVALID_SQL_ERROR"

DESCRIBE_QUERY_TIMEOUT = "DESCRIBE_QUERY_TIMEOUT"

DESCRIBE_QUERY_UNEXPECTED_FAILURE = "DESCRIBE_QUERY_UNEXPECTED_FAILURE"

EXCEEDED_MAX_TOKEN_LENGTH_EXCEPTION = "EXCEEDED_MAX_TOKEN_LENGTH_EXCEPTION"

FUNCTIONS_NOT_AVAILABLE_EXCEPTION = "FUNCTIONS_NOT_AVAILABLE_EXCEPTION"

FUNCTION_ARGUMENTS_INVALID_EXCEPTION = "FUNCTION_ARGUMENTS_INVALID_EXCEPTION"

FUNCTION_ARGUMENTS_INVALID_JSON_EXCEPTION = "FUNCTION_ARGUMENTS_INVALID_JSON_EXCEPTION"

FUNCTION_ARGUMENTS_INVALID_TYPE_EXCEPTION = "FUNCTION_ARGUMENTS_INVALID_TYPE_EXCEPTION"

FUNCTION_CALL_MISSING_PARAMETER_EXCEPTION = "FUNCTION_CALL_MISSING_PARAMETER_EXCEPTION"

GENERATED_SQL_QUERY_TOO_LONG_EXCEPTION = "GENERATED_SQL_QUERY_TOO_LONG_EXCEPTION"

GENERIC_CHAT_COMPLETION_EXCEPTION = "GENERIC_CHAT_COMPLETION_EXCEPTION"

GENERIC_CHAT_COMPLETION_SERVICE_EXCEPTION = "GENERIC_CHAT_COMPLETION_SERVICE_EXCEPTION"

GENERIC_SQL_EXEC_API_CALL_EXCEPTION = "GENERIC_SQL_EXEC_API_CALL_EXCEPTION"

ILLEGAL_PARAMETER_DEFINITION_EXCEPTION = "ILLEGAL_PARAMETER_DEFINITION_EXCEPTION"

INTERNAL_CATALOG_ASSET_CREATION_FAILED_EXCEPTION = "INTERNAL_CATALOG_ASSET_CREATION_FAILED_EXCEPTION"

INTERNAL_CATALOG_ASSET_CREATION_ONGOING_EXCEPTION = "INTERNAL_CATALOG_ASSET_CREATION_ONGOING_EXCEPTION"

INTERNAL_CATALOG_ASSET_CREATION_UNSUPPORTED_EXCEPTION = "INTERNAL_CATALOG_ASSET_CREATION_UNSUPPORTED_EXCEPTION"

INTERNAL_CATALOG_MISSING_UC_PATH_EXCEPTION = "INTERNAL_CATALOG_MISSING_UC_PATH_EXCEPTION"

INTERNAL_CATALOG_PATH_OVERLAP_EXCEPTION = "INTERNAL_CATALOG_PATH_OVERLAP_EXCEPTION"

INVALID_CERTIFIED_ANSWER_FUNCTION_EXCEPTION = "INVALID_CERTIFIED_ANSWER_FUNCTION_EXCEPTION"

INVALID_CERTIFIED_ANSWER_IDENTIFIER_EXCEPTION = "INVALID_CERTIFIED_ANSWER_IDENTIFIER_EXCEPTION"

INVALID_CHAT_COMPLETION_JSON_EXCEPTION = "INVALID_CHAT_COMPLETION_JSON_EXCEPTION"

INVALID_COMPLETION_REQUEST_EXCEPTION = "INVALID_COMPLETION_REQUEST_EXCEPTION"

INVALID_FUNCTION_CALL_EXCEPTION = "INVALID_FUNCTION_CALL_EXCEPTION"

INVALID_SQL_MULTIPLE_DATASET_REFERENCES_EXCEPTION = "INVALID_SQL_MULTIPLE_DATASET_REFERENCES_EXCEPTION"

INVALID_SQL_MULTIPLE_STATEMENTS_EXCEPTION = "INVALID_SQL_MULTIPLE_STATEMENTS_EXCEPTION"

INVALID_SQL_UNKNOWN_TABLE_EXCEPTION = "INVALID_SQL_UNKNOWN_TABLE_EXCEPTION"

INVALID_TABLE_IDENTIFIER_EXCEPTION = "INVALID_TABLE_IDENTIFIER_EXCEPTION"

LOCAL_CONTEXT_EXCEEDED_EXCEPTION = "LOCAL_CONTEXT_EXCEEDED_EXCEPTION"

MESSAGE_ATTACHMENT_TOO_LONG_ERROR = "MESSAGE_ATTACHMENT_TOO_LONG_ERROR"

MESSAGE_CANCELLED_WHILE_EXECUTING_EXCEPTION = "MESSAGE_CANCELLED_WHILE_EXECUTING_EXCEPTION"

MESSAGE_DELETED_WHILE_EXECUTING_EXCEPTION = "MESSAGE_DELETED_WHILE_EXECUTING_EXCEPTION"

MESSAGE_UPDATED_WHILE_EXECUTING_EXCEPTION = "MESSAGE_UPDATED_WHILE_EXECUTING_EXCEPTION"

MISSING_SQL_QUERY_EXCEPTION = "MISSING_SQL_QUERY_EXCEPTION"

NO_DEPLOYMENTS_AVAILABLE_TO_WORKSPACE = "NO_DEPLOYMENTS_AVAILABLE_TO_WORKSPACE"

NO_QUERY_TO_VISUALIZE_EXCEPTION = "NO_QUERY_TO_VISUALIZE_EXCEPTION"

NO_TABLES_TO_QUERY_EXCEPTION = "NO_TABLES_TO_QUERY_EXCEPTION"

RATE_LIMIT_EXCEEDED_GENERIC_EXCEPTION = "RATE_LIMIT_EXCEEDED_GENERIC_EXCEPTION"

RATE_LIMIT_EXCEEDED_SPECIFIED_WAIT_EXCEPTION = "RATE_LIMIT_EXCEEDED_SPECIFIED_WAIT_EXCEPTION"

REPLY_PROCESS_TIMEOUT_EXCEPTION = "REPLY_PROCESS_TIMEOUT_EXCEPTION"

RETRYABLE_PROCESSING_EXCEPTION = "RETRYABLE_PROCESSING_EXCEPTION"

SQL_EXECUTION_EXCEPTION = "SQL_EXECUTION_EXCEPTION"

STOP_PROCESS_DUE_TO_AUTO_REGENERATE = "STOP_PROCESS_DUE_TO_AUTO_REGENERATE"

TABLES_MISSING_EXCEPTION = "TABLES_MISSING_EXCEPTION"

TOO_MANY_CERTIFIED_ANSWERS_EXCEPTION = "TOO_MANY_CERTIFIED_ANSWERS_EXCEPTION"

TOO_MANY_TABLES_EXCEPTION = "TOO_MANY_TABLES_EXCEPTION"

UNEXPECTED_REPLY_PROCESS_EXCEPTION = "UNEXPECTED_REPLY_PROCESS_EXCEPTION"

UNKNOWN_AI_MODEL = "UNKNOWN_AI_MODEL"

UNSUPPORTED_CONVERSATION_TYPE_EXCEPTION = "UNSUPPORTED_CONVERSATION_TYPE_EXCEPTION"

WAREHOUSE_ACCESS_MISSING_EXCEPTION = "WAREHOUSE_ACCESS_MISSING_EXCEPTION"

WAREHOUSE_NOT_FOUND_EXCEPTION = "WAREHOUSE_NOT_FOUND_EXCEPTION"

class databricks.sdk.service.dashboards.MessageStatus

MessageStatus. The possible values are: * FETCHING_METADATA: Fetching metadata from the data sources. * FILTERING_CONTEXT: Running smart context step to determine relevant context. * ASKING_AI: Waiting for the LLM to respond to the user’s question. * PENDING_WAREHOUSE: Waiting for warehouse before the SQL query can start executing. * EXECUTING_QUERY: Executing a generated SQL query. Get the SQL query result by calling [getMessageAttachmentQueryResult](:method:genie/getMessageAttachmentQueryResult) API. * FAILED: The response generation or query execution failed. See error field. * COMPLETED: Message processing is completed. Results are in the attachments field. Get the SQL query result by calling [getMessageAttachmentQueryResult](:method:genie/getMessageAttachmentQueryResult) API. * SUBMITTED: Message has been submitted. * QUERY_RESULT_EXPIRED: SQL result is not available anymore. The user needs to rerun the query. Rerun the SQL query result by calling [executeMessageAttachmentQuery](:method:genie/executeMessageAttachmentQuery) API. * CANCELLED: Message has been cancelled.

ASKING_AI = "ASKING_AI"

CANCELLED = "CANCELLED"

COMPLETED = "COMPLETED"

EXECUTING_QUERY = "EXECUTING_QUERY"

FAILED = "FAILED"

FETCHING_METADATA = "FETCHING_METADATA"

FILTERING_CONTEXT = "FILTERING_CONTEXT"

PENDING_WAREHOUSE = "PENDING_WAREHOUSE"

QUERY_RESULT_EXPIRED = "QUERY_RESULT_EXPIRED"

SUBMITTED = "SUBMITTED"

class databricks.sdk.service.dashboards.PublishedDashboard(display_name: 'Optional[str]' = None, embed_credentials: 'Optional[bool]' = None, revision_create_time: 'Optional[str]' = None, warehouse_id: 'Optional[str]' = None)

display_name: str | None = None

The display name of the published dashboard.

embed_credentials: bool | None = None

Indicates whether credentials are embedded in the published dashboard.

revision_create_time: str | None = None

The timestamp of when the published dashboard was last revised.

warehouse_id: str | None = None

The warehouse ID used to run the published dashboard.

as_dict() → dict

Serializes the PublishedDashboard into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the PublishedDashboard into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → PublishedDashboard

Deserializes the PublishedDashboard from a dictionary.

class databricks.sdk.service.dashboards.QueryAttachmentParameter(keyword: 'Optional[str]' = None, sql_type: 'Optional[str]' = None, value: 'Optional[str]' = None)

keyword: str | None = None

sql_type: str | None = None

value: str | None = None

as_dict() → dict

Serializes the QueryAttachmentParameter into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the QueryAttachmentParameter into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → QueryAttachmentParameter

Deserializes the QueryAttachmentParameter from a dictionary.

class databricks.sdk.service.dashboards.Result(is_truncated: 'Optional[bool]' = None, row_count: 'Optional[int]' = None, statement_id: 'Optional[str]' = None, statement_id_signature: 'Optional[str]' = None)

is_truncated: bool | None = None

If result is truncated

row_count: int | None = None

Row count of the result

statement_id: str | None = None

Statement Execution API statement id. Use [Get status, manifest, and result first chunk](:method:statementexecution/getstatement) to get the full result data.

statement_id_signature: str | None = None

JWT corresponding to the statement contained in this result

as_dict() → dict

Serializes the Result into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the Result into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → Result

Deserializes the Result from a dictionary.

class databricks.sdk.service.dashboards.RevertDashboardResponse(dashboard: Dashboard | None = None)

Response to revert a dashboard draft to its last published state.

dashboard: Dashboard | None = None

The reverted dashboard.

as_dict() → dict

Serializes the RevertDashboardResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the RevertDashboardResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → RevertDashboardResponse

Deserializes the RevertDashboardResponse from a dictionary.

class databricks.sdk.service.dashboards.Schedule(cron_schedule: 'CronSchedule', create_time: 'Optional[str]' = None, dashboard_id: 'Optional[str]' = None, display_name: 'Optional[str]' = None, etag: 'Optional[str]' = None, pause_status: 'Optional[SchedulePauseStatus]' = None, schedule_id: 'Optional[str]' = None, update_time: 'Optional[str]' = None, warehouse_id: 'Optional[str]' = None)

cron_schedule: CronSchedule

The cron expression describing the frequency of the periodic refresh for this schedule.

create_time: str | None = None

A timestamp indicating when the schedule was created.

dashboard_id: str | None = None

UUID identifying the dashboard to which the schedule belongs.

display_name: str | None = None

The display name for schedule.

etag: str | None = None

The etag for the schedule. Must be left empty on create, must be provided on updates to ensure that the schedule has not been modified since the last read, and can be optionally provided on delete.

pause_status: SchedulePauseStatus | None = None

The status indicates whether this schedule is paused or not.

schedule_id: str | None = None

UUID identifying the schedule.

update_time: str | None = None

A timestamp indicating when the schedule was last updated.

warehouse_id: str | None = None

The warehouse id to run the dashboard with for the schedule.

as_dict() → dict

Serializes the Schedule into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the Schedule into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → Schedule

Deserializes the Schedule from a dictionary.

class databricks.sdk.service.dashboards.SchedulePauseStatus

PAUSED = "PAUSED"

UNPAUSED = "UNPAUSED"

class databricks.sdk.service.dashboards.ScoreReason

COLUMN_TYPE_DIFFERENCE = "COLUMN_TYPE_DIFFERENCE"

EMPTY_GOOD_SQL = "EMPTY_GOOD_SQL"

EMPTY_RESULT = "EMPTY_RESULT"

LLM_JUDGE_FORMATTING_ERROR = "LLM_JUDGE_FORMATTING_ERROR"

LLM_JUDGE_INCOMPLETE_OR_PARTIAL_OUTPUT = "LLM_JUDGE_INCOMPLETE_OR_PARTIAL_OUTPUT"

LLM_JUDGE_INCORRECT_FUNCTION_USAGE = "LLM_JUDGE_INCORRECT_FUNCTION_USAGE"

LLM_JUDGE_INCORRECT_METRIC_CALCULATION = "LLM_JUDGE_INCORRECT_METRIC_CALCULATION"

LLM_JUDGE_INCORRECT_TABLE_OR_FIELD_USAGE = "LLM_JUDGE_INCORRECT_TABLE_OR_FIELD_USAGE"

LLM_JUDGE_INSTRUCTION_COMPLIANCE_OR_MISSING_BUSINESS_LOGIC = "LLM_JUDGE_INSTRUCTION_COMPLIANCE_OR_MISSING_BUSINESS_LOGIC"

LLM_JUDGE_MISINTERPRETATION_OF_USER_REQUEST = "LLM_JUDGE_MISINTERPRETATION_OF_USER_REQUEST"

LLM_JUDGE_MISSING_JOIN = "LLM_JUDGE_MISSING_JOIN"

LLM_JUDGE_MISSING_OR_INCORRECT_AGGREGATION = "LLM_JUDGE_MISSING_OR_INCORRECT_AGGREGATION"

LLM_JUDGE_MISSING_OR_INCORRECT_FILTER = "LLM_JUDGE_MISSING_OR_INCORRECT_FILTER"

LLM_JUDGE_MISSING_OR_INCORRECT_JOIN = "LLM_JUDGE_MISSING_OR_INCORRECT_JOIN"

LLM_JUDGE_OTHER = "LLM_JUDGE_OTHER"

LLM_JUDGE_SEMANTIC_ERROR = "LLM_JUDGE_SEMANTIC_ERROR"

LLM_JUDGE_SYNTAX_ERROR = "LLM_JUDGE_SYNTAX_ERROR"

LLM_JUDGE_WRONG_AGGREGATION = "LLM_JUDGE_WRONG_AGGREGATION"

LLM_JUDGE_WRONG_COLUMNS = "LLM_JUDGE_WRONG_COLUMNS"

LLM_JUDGE_WRONG_FILTER = "LLM_JUDGE_WRONG_FILTER"

RESULT_EXTRA_COLUMNS = "RESULT_EXTRA_COLUMNS"

RESULT_EXTRA_ROWS = "RESULT_EXTRA_ROWS"

RESULT_MISSING_COLUMNS = "RESULT_MISSING_COLUMNS"

RESULT_MISSING_ROWS = "RESULT_MISSING_ROWS"

SINGLE_CELL_DIFFERENCE = "SINGLE_CELL_DIFFERENCE"

class databricks.sdk.service.dashboards.Subscriber(destination_subscriber: 'Optional[SubscriptionSubscriberDestination]' = None, user_subscriber: 'Optional[SubscriptionSubscriberUser]' = None)

destination_subscriber: SubscriptionSubscriberDestination | None = None

The destination to receive the subscription email. This parameter is mutually exclusive with user_subscriber.

user_subscriber: SubscriptionSubscriberUser | None = None

The user to receive the subscription email. This parameter is mutually exclusive with destination_subscriber.

as_dict() → dict

Serializes the Subscriber into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the Subscriber into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → Subscriber

Deserializes the Subscriber from a dictionary.

class databricks.sdk.service.dashboards.Subscription(subscriber: 'Subscriber', create_time: 'Optional[str]' = None, created_by_user_id: 'Optional[int]' = None, dashboard_id: 'Optional[str]' = None, etag: 'Optional[str]' = None, schedule_id: 'Optional[str]' = None, skip_notify: 'Optional[bool]' = None, subscription_id: 'Optional[str]' = None, update_time: 'Optional[str]' = None)

subscriber: Subscriber

Subscriber details for users and destinations to be added as subscribers to the schedule.

create_time: str | None = None

A timestamp indicating when the subscription was created.

created_by_user_id: int | None = None

UserId of the user who adds subscribers (users or notification destinations) to the dashboard’s schedule.

dashboard_id: str | None = None

UUID identifying the dashboard to which the subscription belongs.

etag: str | None = None

The etag for the subscription. Must be left empty on create, can be optionally provided on delete to ensure that the subscription has not been deleted since the last read.

schedule_id: str | None = None

UUID identifying the schedule to which the subscription belongs.

skip_notify: bool | None = None

Controls whether notifications are sent to the subscriber for scheduled dashboard refreshes. If not defined, defaults to false in the backend to match the current behavior (refresh and notify)

subscription_id: str | None = None

UUID identifying the subscription.

update_time: str | None = None

A timestamp indicating when the subscription was last updated.

as_dict() → dict

Serializes the Subscription into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the Subscription into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → Subscription

Deserializes the Subscription from a dictionary.

class databricks.sdk.service.dashboards.SubscriptionSubscriberDestination(destination_id: 'str')

destination_id: str

The canonical identifier of the destination to receive email notification.

as_dict() → dict

Serializes the SubscriptionSubscriberDestination into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the SubscriptionSubscriberDestination into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → SubscriptionSubscriberDestination

Deserializes the SubscriptionSubscriberDestination from a dictionary.

class databricks.sdk.service.dashboards.SubscriptionSubscriberUser(user_id: 'int')

user_id: int

UserId of the subscriber.

as_dict() → dict

Serializes the SubscriptionSubscriberUser into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the SubscriptionSubscriberUser into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → SubscriptionSubscriberUser

Deserializes the SubscriptionSubscriberUser from a dictionary.

class databricks.sdk.service.dashboards.TextAttachment(content: 'Optional[str]' = None, id: 'Optional[str]' = None, purpose: 'Optional[TextAttachmentPurpose]' = None)

content: str | None = None

AI generated message

id: str | None = None

purpose: TextAttachmentPurpose | None = None

Purpose/intent of this text attachment

as_dict() → dict

Serializes the TextAttachment into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the TextAttachment into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → TextAttachment

Deserializes the TextAttachment from a dictionary.

class databricks.sdk.service.dashboards.TextAttachmentPurpose

Purpose/intent of a text attachment

FOLLOW_UP_QUESTION = "FOLLOW_UP_QUESTION"

class databricks.sdk.service.dashboards.Thought(content: str | None = None, thought_type: ThoughtType | None = None)

A single thought in the AI’s reasoning process for a query.

content: str | None = None

The md formatted content for this thought.

thought_type: ThoughtType | None = None

The category of this thought. The possible values are: * THOUGHT_TYPE_DESCRIPTION: A high-level description of how the question was interpreted. * THOUGHT_TYPE_UNDERSTANDING: How ambiguous parts of the question were resolved. * THOUGHT_TYPE_DATA_SOURCING: Which tables or datasets were identified as relevant. * THOUGHT_TYPE_INSTRUCTIONS: Which author-defined instructions were referenced. * THOUGHT_TYPE_STEPS: The logical steps taken to compute the answer.

as_dict() → dict

Serializes the Thought into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the Thought into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → Thought

Deserializes the Thought from a dictionary.

class databricks.sdk.service.dashboards.ThoughtType

ThoughtType. The possible values are: * THOUGHT_TYPE_UNSPECIFIED: Default value that should not be used. * THOUGHT_TYPE_DESCRIPTION: A high-level description of how the question was interpreted. * THOUGHT_TYPE_UNDERSTANDING: How ambiguous parts of the question were resolved. * THOUGHT_TYPE_DATA_SOURCING: Which tables or datasets were identified as relevant. * THOUGHT_TYPE_INSTRUCTIONS: Which author-defined instructions were referenced. * THOUGHT_TYPE_STEPS: The logical steps taken to compute the answer. The category of a Thought. Additional values may be added in the future.

THOUGHT_TYPE_DATA_SOURCING = "THOUGHT_TYPE_DATA_SOURCING"

THOUGHT_TYPE_DESCRIPTION = "THOUGHT_TYPE_DESCRIPTION"

THOUGHT_TYPE_INSTRUCTIONS = "THOUGHT_TYPE_INSTRUCTIONS"

THOUGHT_TYPE_STEPS = "THOUGHT_TYPE_STEPS"

THOUGHT_TYPE_UNDERSTANDING = "THOUGHT_TYPE_UNDERSTANDING"

class databricks.sdk.service.dashboards.TrashDashboardResponse

as_dict() → dict

Serializes the TrashDashboardResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the TrashDashboardResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → TrashDashboardResponse

Deserializes the TrashDashboardResponse from a dictionary.

class databricks.sdk.service.dashboards.UnpublishDashboardResponse

as_dict() → dict

Serializes the UnpublishDashboardResponse into a dictionary suitable for use as a JSON request body.

as_shallow_dict() → dict

Serializes the UnpublishDashboardResponse into a shallow dictionary of its immediate attributes.

classmethod from_dict(d: Dict[str, Any]) → UnpublishDashboardResponse

Deserializes the UnpublishDashboardResponse from a dictionary.