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strands.types.agent

Agent-related type definitions for the SDK.

This module defines the types used for an Agent.

class LocalAgent(Protocol)

Defined in: src/strands/types/agent.py:35

Interface for SDK-provided agents with locally accessible capabilities.

This protocol is exported for type annotations and is not intended for external implementation.

Attributes:

  • agent_id - Unique identifier for the agent.
  • name - Display name for the agent.
  • description - Optional description of the agent.
  • messages - Conversation history maintained by the agent.
  • state - Application state associated with the agent.
  • hooks - Registry containing the agent’s hook callbacks.
  • model - Model used by the agent.
  • system_prompt - String representation of the agent’s system prompt.
  • tool_registry - Registry containing tools available to the agent.
  • event_loop_metrics - Aggregated metrics for the agent’s loop execution.
@property
def tool() -> _ToolCaller

Defined in: src/strands/types/agent.py:68

Caller for invoking registered tools directly.

@property
def tool_names() -> list[str]

Defined in: src/strands/types/agent.py:73

Names of tools registered with the agent.

@property
def system_prompt_content() -> list[SystemContentBlock] | None

Defined in: src/strands/types/agent.py:78

Structured system prompt content used by the agent.

@property
def session_id() -> str

Defined in: src/strands/types/agent.py:83

Identifier for the current conversation session.

@property
def storage() -> Storage | None

Defined in: src/strands/types/agent.py:88

Default storage backend for agent subsystems.

@property
def sandbox() -> Sandbox

Defined in: src/strands/types/agent.py:93

Execution environment for running commands, code, and file operations.

@property
def context_manager() -> ContextManager | None

Defined in: src/strands/types/agent.py:98

The ContextManager plugin, if one is registered on this agent.

@property
def cancel_signal() -> threading.Event

Defined in: src/strands/types/agent.py:103

The cancellation signal for the current invocation.

def cancel(*,
message: str | None = None,
after_current_tools: bool = False) -> None

Defined in: src/strands/types/agent.py:107

Request cancellation at the agent’s next supported checkpoint.

Arguments:

  • message - Optional terminal assistant message appended to history on exit.
  • after_current_tools - If True, defer cancellation until the current tool batch finishes; the loop exits before the next model call.
def add_hook(callback: HookCallback[_TEvent],
event_type: type[_TEvent] | list[type[_TEvent]] | None = None,
*,
order: float = ...) -> None

Defined in: src/strands/types/agent.py:117

Register a hook callback.

def take_snapshot(*,
preset: SnapshotPreset | None = None,
include: list[SnapshotField] | None = None,
exclude: list[SnapshotField] | None = None,
app_data: dict[str, Any] | None = None) -> Snapshot

Defined in: src/strands/types/agent.py:127

Capture current agent state as an in-memory snapshot.

The fields a preset captures, and the fields accepted by include and exclude, are implementation-defined.

def load_snapshot(snapshot: Snapshot) -> None

Defined in: src/strands/types/agent.py:142

Restore agent state from a previously captured snapshot.

Only fields present in snapshot.data are restored; absent fields are left unchanged.

class Limits(TypedDict)

Defined in: src/strands/types/agent.py:150

Limits for the request a top-level invoke_async / stream_async call starts.

They apply to this agent’s loop and to every nested call: agents passed as tools, and any Graph or Swarm you pass the request’s invocation_context to (Graph and Swarm have no limits option of their own). An agent run by a hand-written tool joins only when the tool forwards tool_context.invocation_context as invocation_context; otherwise it runs standalone under its own limits. A nested call can also set its own limits: it stops at whichever limit is reached first, its own or the request’s.

Auxiliary calls (summarization, routing, memory extraction, steering, HITL, goal judging, web-fetch) add their tokens to the request’s usage, but no limits apply to them. The same holds for an agent that an extension point (a conversation manager, context or routing strategy, or memory extractor) runs with the invocation_context it receives, unless the extension point also passes limits. Usage starts from zero on each top-level call; pass result.invocation_context to a later call to continue on the same limits and usage.

Limits are checked before each turn, so tools requested by the previous turn finish first and agent.messages stays reinvokable. Each limit, when set, must be a positive int; omit a field (or pass limits=None) for no limit on that dimension.

Priority when several are reached at once (highest first): turns, total_tokens, output_tokens, with stop_reason "limit_turns", "limit_total_tokens", or "limit_output_tokens".

Attributes:

  • turns - Maximum number of turns. One turn is one model call plus any tool execution that follows.
  • output_tokens - Maximum cumulative model-generated tokens across every model call in the request, unlike a provider’s per-call cap. Soft limit: a single oversized response can overshoot it, more so when nested calls run in parallel.
  • total_tokens - Maximum cumulative input + output tokens across every model call in the request. Each model call’s input includes prior turns, so this compounds across the run and approximates total token spend. Soft limit, same caveat as output_tokens.
class ConcurrentInvocationMode(str, Enum)

Defined in: src/strands/types/agent.py:198

Mode controlling concurrent invocation behavior.

Values: THROW: Raises ConcurrencyException if concurrent invocation is attempted (default). UNSAFE_REENTRANT: Allows concurrent invocations without locking.

Warnings:

The UNSAFE_REENTRANT mode makes no guarantees about resulting behavior and is provided only for advanced use cases where the caller understands the risks.