client.agents manages agents (“co-workers”) — configurable AI assistants with tools, personas, and their own versioned lifecycle. Once created, you chat with them through conversations and read their analytics through insights.
Creating an agent
An agent is configured with AgentSettings, which controls its model, behavior, and available tools.
AgentSettings fields: model: list[str], temperature: float, max_tokens
(default 64000), tools: list[...] (required — the discriminated tool union:
web_research, kb_qa, workflow, code_execution, sandbox, …), persona, tone,
extra_instructions, agent_flow_id.
CRUD & lifecycle
update(..., preview=True) returns what the change would look like without
saving. From an Agent object you can call .update(name, settings),
.delete(), and .triggers() / .add_trigger(trigger_data) directly.
Export / import
mode is "clone" | "version" | "replace"; dry_run=True validates only.
Triggers
Agent triggers (as opposed to workflow triggers) are managed directly from an
Agent object:
For workflow triggers and deployment channels, see Deployments & Triggers.
