InMemoryMessageAccumulator#

Build extensions, choose hooks, and manage request-scoped state. See the guide.

class zett_agent.extensions.memory.InMemoryMessageAccumulator[source]#

Retain replayable conversation messages for reuse by later requests.

Messages with include_in_messages=False belong to the current request only. System instructions are rebuilt for every request and therefore do not accumulate stale prompts when an Agent or its tool guidance changes.

async on_state(context)[source]#

Combine current instructions with an independent copy of remembered dialogue.

Parameters:

context (AgentRunContext)

Return type:

None

async on_event(context, event)[source]#

Accumulate raw messages and replace dialogue after successful compaction.

Parameters:
Return type:

None

messages(session_id)[source]#

Return remembered dialogue without request-specific system instructions.

Parameters:

session_id (str)

Return type:

tuple[AnyMessage, …]

clear(session_id)[source]#

Forget one session without changing other accumulated sessions.

Parameters:

session_id (str)

Return type:

None

accept(config, event)#

Handle one external event and report whether it was accepted.

The Agent broadcasts each event to every registered extension. Override this synchronous hook when an extension waits for input from another thread, HTTP request, TUI, or Web UI. The default ignores the event. Config is passed separately and can be None before initialization. Each extension decides whether the supplied identity and payload match its protocol. Return True to include this extension’s name in the broadcast result; returning False does not stop later receivers.

Parameters:
Return type:

bool

async after_model(context, response)#

Run after the complete assistant message is appended.

Parameters:
Return type:

None

async after_run(context, result)#

Run after a successful final answer is appended.

Parameters:
Return type:

None

async after_tool(context, call, result, error)#

Inspect or modify a tool result before it is appended.

error is the original execution exception for a failed result and None after successful execution. Changes made to result are included in context, persistence, and the next model request. Raising prevents the result from being appended.

Parameters:
Return type:

None

async after_turn(context, result)#

Run once the turn’s assistant message and tool results are settled.

result is the assistant message that opened the turn: either the final answer, or the tool-calling message whose ToolMessages were appended. Every requested call is settled first, including calls that failed, and calls that steering skipped, which arrive as unsuccessful or skipped ToolMessages.

Steering that interrupts a turn is accepted while the runtime settles that batch, so its UserMessage is already appended when this hook runs and the steering turn follows as the next turn.

A turn that never completed, because the request failed or was cancelled, has no after_turn call; use on_error and RunCancelledEvent for those paths.

Parameters:
Return type:

None

async before_model(context, request)#

Inspect the current request before preprocessing a primary model call.

Request fields are frozen. Change messages through AgentRunContext.add_message() or AgentRunContext.replace_messages(), local tools through context.tools, and provider tools through context.server_tools; the runtime rebuilds these fields before the next hook and before calling the provider. This is a shallow request view, not an immutable copy of each message or tool definition.

Examples

Inspect the tools offered in this iteration:

async def before_model(self, context, request):
    offered = {definition.name for definition in request.tools}
    if "write_file" in offered:
        context.add_message(
            SystemMessage(content="Read existing files before editing."),
        )
Parameters:
Return type:

None

async before_run(context)#

Run after the transformed user input is appended and published.

Parameters:

context (AgentRunContext)

Return type:

None

async before_tool(context, call)#

Run before one requested tool is invoked.

Parameters:
Return type:

None

async before_turn(context)#

Run before this turn’s model call.

Runs after before_run() on the first turn and after the previous turn’s after_turn() on later ones. Model request assembly, compaction, and before_model() follow this hook, so context edited here reaches the provider.

Parameters:

context (AgentRunContext)

Return type:

None

property name: str#

Unique registration identity, defaulting to the concrete class name.

Override with a class attribute or assign an instance name to register independently configured instances of the same extension type.

async on_compact(context)#

Summarize restored context when a caller asks for compaction.

Agent.compact restores the session through on_tool and on_state exactly as a request does, appends no input message, and makes no primary model call: the only work a compaction pass does is what this hook performs. The default does nothing, so an extension with nothing to compact pays nothing.

Examples

Usage:

async def on_compact(self, context):
    await self.compact(context)
Parameters:

context (AgentRunContext)

Return type:

None

async on_error(context, error)#

Run before an agent error is propagated to the caller.

Parameters:
Return type:

None

async on_message(context)#

Transform context.input_message after state restoration, before append.

Replace the pending UserMessage to implement externally selected modes. Do not append or persist it here: the runtime appends the final message exactly once after all input hooks finish. before_run sees that message through AgentRunContext.add_message() or AgentRunContext.replace_messages(), and persistence subscribers have already received it.

Parameters:

context (AgentRunContext)

Return type:

None

async on_model_request(context, request, call_next)#

Wrap one provider request and its complete streamed response.

Pass request (or a dataclass replacement) to call_next. The default closes the inner stream so cancellation reaches the provider.

Parameters:
Return type:

AsyncIterator[ModelEvent]

async on_success(context, result)#

Run once after all after_run hooks succeed, before RUN_COMPLETED.

This callback observes a completed request, not an intermediate model step. Failed or cancelled requests do not trigger it. Callback errors propagate through on_error and prevent RUN_COMPLETED from being emitted.

Examples

Usage:

async def on_success(self, context, result):
    await save_answer(context.session_id, result.content)
Parameters:
Return type:

None

async on_tool(context)#

Register local or provider-hosted tools before context restoration.

All extensions finish this hook before the first on_state() call, so prompt extensions can reliably inspect context.tools and context.server_tools as complete request-scoped registries.

Examples

Usage:

async def on_tool(self, context):
    context.register_tool(read_file)
    context.register_server_tool(ServerToolDefinition(type="web_search"))
Parameters:

context (AgentRunContext)

Return type:

None

async on_tool_call(context, call, call_next)#

Wrap one registered local tool handler and return its ToolResult.

An extension may adjust call.arguments, return without calling the next layer, transform its result, or raise into normal tool-failure handling.

Parameters:
Return type:

ToolResult

property pending: bool#

Return whether this extension is participating in an active request.

The Agent updates this state for every registered extension, including extensions whose hooks are currently idle. One extension instance may be shared by multiple Agents and sessions; pending remains true until all requests using that instance have finished, failed, or been cancelled. Persistent data retained between requests does not count.