Method●Since v0.3

create

Create a background run.

create(
  self,
  thread_id: str | None,
  assistant_id: str,
  *,
  input: Input | None = None,
  command: Command | None = None,
  stream_mode: StreamMode | Sequence[StreamMode] = 'values',
  stream_subgraphs: bool = False,
  stream_resumable: bool = False,
  metadata: Mapping[str, Any] | None = None,
  config: Config | None = None,
  context: Context | None = None,
  checkpoint: Checkpoint | None = None,
  checkpoint_id: str | None = None,
  checkpoint_during: bool | None = None,
  interrupt_before: All | Sequence[str] | None = None,
  interrupt_after: All | Sequence[str] | None = None,
  webhook: str | None = None,
  multitask_strategy: MultitaskStrategy | None = None,
  if_not_exists: IfNotExists | None = None,
  on_completion: OnCompletionBehavior | None = None,
  after_seconds: int | None = None,
  headers: Mapping[str, str] | None = None,
  params: QueryParamTypes | None = None,
  on_run_created: Callable[[RunCreateMetadata], None] | None = None,
  durability: Durability | None = None
) -> Run

client = get_sync_client(url="http://localhost:2024")
background_run = client.runs.create(
    thread_id="my_thread_id",
    assistant_id="my_assistant_id",
    input={"messages": [{"role": "user", "content": "hello!"}]},
    metadata={"name":"my_run"},
    context={"model_name": "openai"},
    interrupt_before=["node_to_stop_before_1","node_to_stop_before_2"],
    interrupt_after=["node_to_stop_after_1","node_to_stop_after_2"],
    webhook="https://my.fake.webhook.com",
    multitask_strategy="interrupt"
)
print(background_run)

--------------------------------------------------------------------------------

{
    'run_id': 'my_run_id',
    'thread_id': 'my_thread_id',
    'assistant_id': 'my_assistant_id',
    'created_at': '2024-07-25T15:35:42.598503+00:00',
    'updated_at': '2024-07-25T15:35:42.598503+00:00',
    'metadata': {},
    'status': 'pending',
    'kwargs':
        {
            'input':
                {
                    'messages': [
                        {
                            'role': 'user',
                            'content': 'how are you?'
                        }
                    ]
                },
            'config':
                {
                    'metadata':
                        {
                            'created_by': 'system'
                        },
                    'configurable':
                        {
                            'run_id': 'my_run_id',
                            'user_id': None,
                            'graph_id': 'agent',
                            'thread_id': 'my_thread_id',
                            'checkpoint_id': None,
                            'assistant_id': 'my_assistant_id'
                        }
                },
            'context':
                {
                    'model_name': 'openai'
                },
            'webhook': "https://my.fake.webhook.com",
            'temporary': False,
            'stream_mode': ['values'],
            'feedback_keys': None,
            'interrupt_after': ["node_to_stop_after_1","node_to_stop_after_2"],
            'interrupt_before': ["node_to_stop_before_1","node_to_stop_before_2"]
        },
    'multitask_strategy': 'interrupt'
}

Parameters

Name	Type	Description
`thread_id`*	`str \| None`	the thread ID to assign to the thread. If `None` will create a stateless run.
`assistant_id`*	`str`	The assistant ID or graph name to stream from. If using graph name, will default to first assistant created from that graph.
`input`	`Input \| None`	Default:`None` The input to the graph.
`command`	`Command \| None`	Default:`None` The command to execute.
`stream_mode`	`StreamMode \| Sequence[StreamMode]`	Default:`'values'` The stream mode(s) to use.
`stream_subgraphs`	`bool`	Default:`False` Whether to stream output from subgraphs.
`stream_resumable`	`bool`	Default:`False` Whether the stream is considered resumable. If true, the stream can be resumed and replayed in its entirety even after disconnection.
`metadata`	`Mapping[str, Any] \| None`	Default:`None` Metadata to assign to the run.
`config`	`Config \| None`	Default:`None` The configuration for the assistant.
`context`	`Context \| None`	Default:`None` Static context to add to the assistant.
`checkpoint`	`Checkpoint \| None`	Default:`None` The checkpoint to resume from.
`checkpoint_during`	`bool \| None`	Default:`None` (deprecated) Whether to checkpoint during the run (or only at the end/interruption).
`interrupt_before`	`All \| Sequence[str] \| None`	Default:`None` Nodes to interrupt immediately before they get executed.
`interrupt_after`	`All \| Sequence[str] \| None`	Default:`None` Nodes to Nodes to interrupt immediately after they get executed.
`webhook`	`str \| None`	Default:`None` Webhook to call after LangGraph API call is done.
`multitask_strategy`	`MultitaskStrategy \| None`	Default:`None` Multitask strategy to use. Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
`on_completion`	`OnCompletionBehavior \| None`	Default:`None` Whether to delete or keep the thread created for a stateless run. Must be one of 'delete' or 'keep'.
`if_not_exists`	`IfNotExists \| None`	Default:`None` How to handle missing thread. Defaults to 'reject'. Must be either 'reject' (raise error if missing), or 'create' (create new thread).
`after_seconds`	`int \| None`	Default:`None` The number of seconds to wait before starting the run. Use to schedule future runs.
`headers`	`Mapping[str, str] \| None`	Default:`None` Optional custom headers to include with the request.
`on_run_created`	`Callable[[RunCreateMetadata], None] \| None`	Default:`None` Optional callback to call when a run is created.
`durability`	`Durability \| None`	Default:`None` The durability to use for the run. Values are "sync", "async", or "exit". "async" means checkpoints are persisted async while next graph step executes, replaces checkpoint_during=True "sync" means checkpoints are persisted sync after graph step executes, replaces checkpoint_during=False "exit" means checkpoints are only persisted when the run exits, does not save intermediate steps

View source on GitHub

client = get_sync_client(url="http://localhost:2024") background_run = client.runs.create( thread_id="my_thread_id", assistant_id="my_assistant_id", input={"messages": [{"role": "user", "content": "hello!"}]}, metadata={"name":"my_run"}, context={"model_name": "openai"}, interrupt_before=["node_to_stop_before_1","node_to_stop_before_2"], interrupt_after=["node_to_stop_after_1","node_to_stop_after_2"], webhook="https://my.fake.webhook.com", multitask_strategy="interrupt" ) print(background_run)

-------------------------------------------------------------------------------- { 'run_id': 'my_run_id', 'thread_id': 'my_thread_id', 'assistant_id': 'my_assistant_id', 'created_at': '2024-07-25T15:35:42.598503+00:00', 'updated_at': '2024-07-25T15:35:42.598503+00:00', 'metadata': {}, 'status': 'pending', 'kwargs': { 'input': { 'messages': [ { 'role': 'user', 'content': 'how are you?' } ] }, 'config': { 'metadata': { 'created_by': 'system' }, 'configurable': { 'run_id': 'my_run_id', 'user_id': None, 'graph_id': 'agent', 'thread_id': 'my_thread_id', 'checkpoint_id': None, 'assistant_id': 'my_assistant_id' } }, 'context': { 'model_name': 'openai' }, 'webhook': "https://my.fake.webhook.com", 'temporary': False, 'stream_mode': ['values'], 'feedback_keys': None, 'interrupt_after': ["node_to_stop_after_1","node_to_stop_after_2"], 'interrupt_before': ["node_to_stop_before_1","node_to_stop_before_2"] }, 'multitask_strategy': 'interrupt' }

Parameters

Name	Type	Description
`thread_id`*	`str \| None`	the thread ID to assign to the thread. If `None` will create a stateless run.
`assistant_id`*	`str`	The assistant ID or graph name to stream from. If using graph name, will default to first assistant created from that graph.
`input`	`Input \| None`	Default:`None` The input to the graph.
`command`	`Command \| None`	Default:`None` The command to execute.
`stream_mode`	`StreamMode \| Sequence[StreamMode]`	Default:`'values'` The stream mode(s) to use.
`stream_subgraphs`	`bool`	Default:`False` Whether to stream output from subgraphs.
`stream_resumable`	`bool`	Default:`False` Whether the stream is considered resumable. If true, the stream can be resumed and replayed in its entirety even after disconnection.
`metadata`	`Mapping[str, Any] \| None`	Default:`None` Metadata to assign to the run.
`config`	`Config \| None`	Default:`None` The configuration for the assistant.
`context`	`Context \| None`	Default:`None` Static context to add to the assistant.
`checkpoint`	`Checkpoint \| None`	Default:`None` The checkpoint to resume from.
`checkpoint_during`	`bool \| None`	Default:`None` (deprecated) Whether to checkpoint during the run (or only at the end/interruption).
`interrupt_before`	`All \| Sequence[str] \| None`	Default:`None` Nodes to interrupt immediately before they get executed.
`interrupt_after`	`All \| Sequence[str] \| None`	Default:`None` Nodes to Nodes to interrupt immediately after they get executed.
`webhook`	`str \| None`	Default:`None` Webhook to call after LangGraph API call is done.
`multitask_strategy`	`MultitaskStrategy \| None`	Default:`None` Multitask strategy to use. Must be one of 'reject', 'interrupt', 'rollback', or 'enqueue'.
`on_completion`	`OnCompletionBehavior \| None`	Default:`None` Whether to delete or keep the thread created for a stateless run. Must be one of 'delete' or 'keep'.
`if_not_exists`	`IfNotExists \| None`	Default:`None` How to handle missing thread. Defaults to 'reject'. Must be either 'reject' (raise error if missing), or 'create' (create new thread).
`after_seconds`	`int \| None`	Default:`None` The number of seconds to wait before starting the run. Use to schedule future runs.
`headers`	`Mapping[str, str] \| None`	Default:`None` Optional custom headers to include with the request.
`on_run_created`	`Callable[[RunCreateMetadata], None] \| None`	Default:`None` Optional callback to call when a run is created.
`durability`	`Durability \| None`	Default:`None` The durability to use for the run. Values are "sync", "async", or "exit". "async" means checkpoints are persisted async while next graph step executes, replaces checkpoint_during=True "sync" means checkpoints are persisted sync after graph step executes, replaces checkpoint_during=False "exit" means checkpoints are only persisted when the run exits, does not save intermediate steps

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create

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