agent

Execute Agent

Changed on
post/v1/agent/execute

Request

  • Base URL: https://api.vlm.run (the document declares no server; this is the origin it was published from)
  • URL: https://api.vlm.run/v1/agent/execute
  • Auth: HTTP bearer

Request body

idstring

Unique identifier of the request.

created_atstring date-time

Date and time when the request was created (in UTC timezone)

callback_urlstring uri nullable

The URL to call when the request is completed.

namestring nullable

Name of the agent. If not provided, we use the prompt to identify the unique agent.

batchboolean

Whether to process the document in batch mode (async).

inputsAgentExecutionInputs

Base class for agent execution inputs.

Users can subclass this to create typed input models for their agents. For example:

class MyAgentInputs(AgentExecutionInputs):
    image: MessageContent
    prompt: str

request = AgentExecutionRequest(
    name="my-agent",
    inputs=MyAgentInputs(image=..., prompt=...)
)

Response

Successful Response

idstring

Unique identifier of the agent execution response.

namestring required

Name of the agent

responseunknown
execution_mode'agent' | 'program'

How the execution ran: program when a cached skill pipeline.py ran as fixed code (no LLM agent loop), else agent. Always agent for non-Orion-2 models.

status'pending' | 'enqueued' | 'running' | 'completed' | 'failed' | 'paused'

The status of the job.

fallbackboolean

True when the JSON was produced by a fallback model. False when the primary model succeeded.

created_atstring date-time

Date and time when the execution was created (in UTC timezone)

completed_atstring date-time nullable

Date and time when the execution was completed (in UTC timezone)

Changes