pipelines_config

Bases: BasePipelinesConfig

Source code in airia/client/pipelines_config/sync_pipelines_config.py

def __init__(self, request_handler: RequestHandler):
    super().__init__(request_handler)

delete_pipeline(pipeline_id, correlation_id=None)

Delete a pipeline by its ID.

This method permanently removes a pipeline and all its configuration from the Airia platform. This action cannot be undone.

Parameters:

Name	Type	Description	Default
pipeline_id	str	The unique identifier of the pipeline to delete.	required
correlation_id	str	A unique identifier for request tracing and logging. If not provided, one will be automatically generated.	None

Returns:

Name	Type	Description
None	None	This method returns nothing upon successful deletion (204 No Content).

Raises:

Type	Description
AiriaAPIError	If the API request fails, including cases where: - The pipeline_id doesn't exist (404) - Authentication fails (401) - Access is forbidden (403) - Server errors (5xx)

Example

from airia import AiriaClient

client = AiriaClient(api_key="your_api_key")

# Delete a pipeline
client.pipelines_config.delete_pipeline(
    pipeline_id="your_pipeline_id"
)
print("Pipeline deleted successfully")

Warning

This operation is permanent and cannot be reversed. Ensure you have the correct pipeline_id before calling this method.

Source code in airia/client/pipelines_config/sync_pipelines_config.py

def delete_pipeline(
    self,
    pipeline_id: str,
    correlation_id: Optional[str] = None,
) -> None:
    """
    Delete a pipeline by its ID.

    This method permanently removes a pipeline and all its configuration
    from the Airia platform. This action cannot be undone.

    Args:
        pipeline_id (str): The unique identifier of the pipeline to delete.
        correlation_id (str, optional): A unique identifier for request tracing
            and logging. If not provided, one will be automatically generated.

    Returns:
        None: This method returns nothing upon successful deletion (204 No Content).

    Raises:
        AiriaAPIError: If the API request fails, including cases where:
            - The pipeline_id doesn't exist (404)
            - Authentication fails (401)
            - Access is forbidden (403)
            - Server errors (5xx)

    Example:
        ```python
        from airia import AiriaClient

        client = AiriaClient(api_key="your_api_key")

        # Delete a pipeline
        client.pipelines_config.delete_pipeline(
            pipeline_id="your_pipeline_id"
        )
        print("Pipeline deleted successfully")
        ```

    Warning:
        This operation is permanent and cannot be reversed. Ensure you have
        the correct pipeline_id before calling this method.
    """
    request_data = self._pre_delete_pipeline(
        pipeline_id=pipeline_id,
        correlation_id=correlation_id,
        api_version=ApiVersion.V1.value,
    )
    self._request_handler.make_request("DELETE", request_data, return_json=False)

export_pipeline_definition(pipeline_id, correlation_id=None)

Export the complete definition of a pipeline including all its components.

This method retrieves a comprehensive export of a pipeline definition including metadata, agent configuration, data sources, prompts, tools, models, memories, Python code blocks, routers, and deployment information.

Parameters:

Name	Type	Description	Default
pipeline_id	str	The unique identifier of the pipeline to export definition for.	required
correlation_id	str	A unique identifier for request tracing and logging. If not provided, one will be automatically generated.	None

Returns:

Name	Type	Description
ExportPipelineDefinitionResponse	ExportPipelineDefinitionResponse	A response object containing the complete pipeline definition export.

Raises:

Type	Description
AiriaAPIError	If the API request fails, including cases where: - The pipeline_id doesn't exist (404) - Authentication fails (401) - Access is forbidden (403) - Server errors (5xx)

Example

from airia import AiriaClient

client = AiriaClient(api_key="your_api_key")

# Export pipeline definition
export = client.pipelines_config.export_pipeline_definition(
    pipeline_id="your_pipeline_id"
)

print(f"Pipeline: {export.agent.name}")
print(f"Export version: {export.metadata.export_version}")
print(f"Data sources: {len(export.data_sources or [])}")
print(f"Tools: {len(export.tools or [])}")

Note

This method exports the complete pipeline definition which can be used for backup, version control, or importing into other environments.

Source code in airia/client/pipelines_config/sync_pipelines_config.py

def export_pipeline_definition(
    self, pipeline_id: str, correlation_id: Optional[str] = None
) -> ExportPipelineDefinitionResponse:
    """
    Export the complete definition of a pipeline including all its components.

    This method retrieves a comprehensive export of a pipeline definition including
    metadata, agent configuration, data sources, prompts, tools, models, memories,
    Python code blocks, routers, and deployment information.

    Args:
        pipeline_id (str): The unique identifier of the pipeline to export
            definition for.
        correlation_id (str, optional): A unique identifier for request tracing
            and logging. If not provided, one will be automatically generated.

    Returns:
        ExportPipelineDefinitionResponse: A response object containing the complete
            pipeline definition export.

    Raises:
        AiriaAPIError: If the API request fails, including cases where:
            - The pipeline_id doesn't exist (404)
            - Authentication fails (401)
            - Access is forbidden (403)
            - Server errors (5xx)

    Example:
        ```python
        from airia import AiriaClient

        client = AiriaClient(api_key="your_api_key")

        # Export pipeline definition
        export = client.pipelines_config.export_pipeline_definition(
            pipeline_id="your_pipeline_id"
        )

        print(f"Pipeline: {export.agent.name}")
        print(f"Export version: {export.metadata.export_version}")
        print(f"Data sources: {len(export.data_sources or [])}")
        print(f"Tools: {len(export.tools or [])}")
        ```

    Note:
        This method exports the complete pipeline definition which can be used
        for backup, version control, or importing into other environments.
    """
    request_data = self._pre_export_pipeline_definition(
        pipeline_id=pipeline_id,
        correlation_id=correlation_id,
        api_version=ApiVersion.V1.value,
    )
    resp = self._request_handler.make_request("GET", request_data)

    return ExportPipelineDefinitionResponse(**resp)

get_pipeline_config(pipeline_id, correlation_id=None)

Retrieve configuration details for a specific pipeline.

This method fetches comprehensive information about a pipeline including its deployment details, execution statistics, version information, and metadata.

Parameters:

Name	Type	Description	Default
pipeline_id	str	The unique identifier of the pipeline to retrieve configuration for.	required
correlation_id	str	A unique identifier for request tracing and logging. If not provided, one will be automatically generated.	None

Returns:

Name	Type	Description
PipelineConfigResponse	PipelineConfigResponse	A response object containing the pipeline configuration.

Raises:

Type	Description
AiriaAPIError	If the API request fails, including cases where: - The pipeline_id doesn't exist (404) - Authentication fails (401) - Access is forbidden (403) - Server errors (5xx)

Example

from airia import AiriaClient

client = AiriaClient(api_key="your_api_key")

# Get pipeline configuration
config = client.pipelines_config.get_pipeline_config(
    pipeline_id="your_pipeline_id"
)

print(f"Pipeline: {config.agent.name}")
print(f"Description: {config.agent.agent_description}")

Note

This method only retrieves configuration information and does not execute the pipeline. Use execute_pipeline() to run the pipeline.

Source code in airia/client/pipelines_config/sync_pipelines_config.py

def get_pipeline_config(
    self, pipeline_id: str, correlation_id: Optional[str] = None
) -> PipelineConfigResponse:
    """
    Retrieve configuration details for a specific pipeline.

    This method fetches comprehensive information about a pipeline including its
    deployment details, execution statistics, version information, and metadata.

    Args:
        pipeline_id (str): The unique identifier of the pipeline to retrieve
            configuration for.
        correlation_id (str, optional): A unique identifier for request tracing
            and logging. If not provided, one will be automatically generated.

    Returns:
        PipelineConfigResponse: A response object containing the pipeline
            configuration.

    Raises:
        AiriaAPIError: If the API request fails, including cases where:
            - The pipeline_id doesn't exist (404)
            - Authentication fails (401)
            - Access is forbidden (403)
            - Server errors (5xx)

    Example:
        ```python
        from airia import AiriaClient

        client = AiriaClient(api_key="your_api_key")

        # Get pipeline configuration
        config = client.pipelines_config.get_pipeline_config(
            pipeline_id="your_pipeline_id"
        )

        print(f"Pipeline: {config.agent.name}")
        print(f"Description: {config.agent.agent_description}")
        ```

    Note:
        This method only retrieves configuration information and does not
        execute the pipeline. Use execute_pipeline() to run the pipeline.
    """
    request_data = self._pre_get_pipeline_config(
        pipeline_id=pipeline_id,
        correlation_id=correlation_id,
        api_version=ApiVersion.V1.value,
    )
    resp = self._request_handler.make_request("GET", request_data)

    return PipelineConfigResponse(**resp)

get_pipelines_config(page_number=None, page_size=None, sort_by=None, sort_direction=None, filter=None, project_id=None, model_credential_source_type=None, correlation_id=None)

Retrieve a list of pipeline configurations with optional filtering, pagination, and sorting.

This method fetches a list of pipeline configurations including their deployment details, execution statistics, version information, and metadata. The results can be filtered, paginated, and sorted using various parameters.

Parameters:

Name	Type	Description	Default
page_number	int	The page number to be fetched.	None
page_size	int	The number of items per page.	None
sort_by	str	Property to sort by.	None
sort_direction	str	The direction of the sort, either "ASC" for ascending or "DESC" for descending.	None
filter	str	The search filter.	None
project_id	str	The unique identifier of the project to filter pipelines by. If not provided, pipelines from all accessible projects will be returned.	None
model_credential_source_type	str	Optional filter to return only pipelines using models with specified source type ("UserProvided" or "Library").	None
correlation_id	str	A unique identifier for request tracing and logging. If not provided, one will be automatically generated.	None

Returns:

Name	Type	Description
GetPipelinesConfigResponse	GetPipelinesConfigResponse	A response object containing the list of pipeline configurations and the total count.

Raises:

Type	Description
AiriaAPIError	If the API request fails, including cases where: - Authentication fails (401) - Access is forbidden (403) - Server errors (5xx)

Example

from airia import AiriaClient

client = AiriaClient(api_key="your_api_key")

# Get all pipeline configurations
pipelines = client.pipelines_config.get_pipelines_config()
print(f"Total pipelines: {pipelines.total_count}")
for pipeline in pipelines.items:
    print(f"Pipeline: {pipeline.name}")
    print(f"Execution name: {pipeline.execution_name}")
    if pipeline.execution_stats:
        print(f"Success count: {pipeline.execution_stats.success_count}")

# Get pipelines with pagination and sorting
pipelines = client.pipelines_config.get_pipelines_config(
    page_number=1,
    page_size=20,
    sort_by="name",
    sort_direction="ASC",
    filter="classification"
)

# Get pipelines for a specific project with model source type filter
project_pipelines = client.pipelines_config.get_pipelines_config(
    project_id="your_project_id",
    model_credential_source_type="UserProvided"
)
print(f"Project pipelines: {project_pipelines.total_count}")

Note

This method retrieves pipeline configuration information only. To execute a pipeline, use the execute_pipeline() method with the appropriate pipeline identifier.

Source code in airia/client/pipelines_config/sync_pipelines_config.py

def get_pipelines_config(
    self,
    page_number: Optional[int] = None,
    page_size: Optional[int] = None,
    sort_by: Optional[str] = None,
    sort_direction: Optional[Literal["ASC", "DESC"]] = None,
    filter: Optional[str] = None,
    project_id: Optional[str] = None,
    model_credential_source_type: Optional[
        Literal["UserProvided", "Library"]
    ] = None,
    correlation_id: Optional[str] = None,
) -> GetPipelinesConfigResponse:
    """
    Retrieve a list of pipeline configurations with optional filtering, pagination, and sorting.

    This method fetches a list of pipeline configurations including their
    deployment details, execution statistics, version information, and metadata.
    The results can be filtered, paginated, and sorted using various parameters.

    Args:
        page_number (int, optional): The page number to be fetched.
        page_size (int, optional): The number of items per page.
        sort_by (str, optional): Property to sort by.
        sort_direction (str, optional): The direction of the sort, either "ASC" for ascending or "DESC" for descending.
        filter (str, optional): The search filter.
        project_id (str, optional): The unique identifier of the project to filter
            pipelines by. If not provided, pipelines from all accessible projects
            will be returned.
        model_credential_source_type (str, optional): Optional filter to return only pipelines
            using models with specified source type ("UserProvided" or "Library").
        correlation_id (str, optional): A unique identifier for request tracing
            and logging. If not provided, one will be automatically generated.

    Returns:
        GetPipelinesConfigResponse: A response object containing the list of
            pipeline configurations and the total count.

    Raises:
        AiriaAPIError: If the API request fails, including cases where:
            - Authentication fails (401)
            - Access is forbidden (403)
            - Server errors (5xx)

    Example:
        ```python
        from airia import AiriaClient

        client = AiriaClient(api_key="your_api_key")

        # Get all pipeline configurations
        pipelines = client.pipelines_config.get_pipelines_config()
        print(f"Total pipelines: {pipelines.total_count}")
        for pipeline in pipelines.items:
            print(f"Pipeline: {pipeline.name}")
            print(f"Execution name: {pipeline.execution_name}")
            if pipeline.execution_stats:
                print(f"Success count: {pipeline.execution_stats.success_count}")

        # Get pipelines with pagination and sorting
        pipelines = client.pipelines_config.get_pipelines_config(
            page_number=1,
            page_size=20,
            sort_by="name",
            sort_direction="ASC",
            filter="classification"
        )

        # Get pipelines for a specific project with model source type filter
        project_pipelines = client.pipelines_config.get_pipelines_config(
            project_id="your_project_id",
            model_credential_source_type="UserProvided"
        )
        print(f"Project pipelines: {project_pipelines.total_count}")
        ```

    Note:
        This method retrieves pipeline configuration information only. To execute
        a pipeline, use the execute_pipeline() method with the appropriate
        pipeline identifier.
    """
    request_data = self._pre_get_pipelines_config(
        page_number=page_number,
        page_size=page_size,
        sort_by=sort_by,
        sort_direction=sort_direction,
        filter=filter,
        project_id=project_id,
        model_credential_source_type=model_credential_source_type,
        correlation_id=correlation_id,
        api_version=ApiVersion.V1.value,
    )
    resp = self._request_handler.make_request("GET", request_data)

    return GetPipelinesConfigResponse(**resp)