Channels: Reactive Agent Input

Channel + QueueManager (nooa.runtime.channels) are the producer side of agent input: outside events flow in through named channels; the agent's dispatch loop races them and reacts. Peer of EventManager/ContextManager, but NOT auto-created — you construct it.

from nooa.runtime.channels import QueueManager
from nooa.runtime.producers import monitor, cron

class Watcher(Agent, llm=llm):
    def __init__(self, **kw):
        super().__init__(**kw)
        qm = QueueManager(agent=self, event_manager=self.event_manager)
        self.qm = qm
        self.user_messages_in = qm.queue("user_messages")   # producer side (put)
        self.user_messages = self.user_messages_in.reader   # LLM-facing side (get/snapshot only)
        self.notifications = qm.event("notifications")      # fire-and-forget → prompt

    async def run(self) -> None:                            # pure-Python dispatcher
        self.qm.spawn(monitor("make test"), channel="user_messages", buffer=100)
        while True:
            items = await self.qm.race()                    # block until any channel produces
            if items:                                       # [(channel_name, item)] — queue winner
                await self.handle(items[0])
            # [] means an event-mode put woke us — it's already rendered
            # into the next turn's prompt; just proceed to a turn.

    async def handle(self, item: tuple[str, object]) -> str:
        """React to the new input."""
        ...

Two channel modes

• Use queue for inputs the agent must consume one at a time (user messages, job results); event for notifications the agent should merely notice ("build finished", status pings).
• QueueOutput renders source/valuetype/valuepreview to the model; the full value is hidden (repr=False) but reachable from code via event_manager.get(tag).value.
• Expose the read side to the LLM as channel.reader — a get(timeout=5.0)/status() wrapper without put (readers time out with QueueReadTimeoutError instead of blocking a cell forever).
• channel.snapshot() peeks without consuming; qm.status() renders a composite status block for all channels (pin it as a dynamic context block so the model sees pending input).

race() — the dispatch primitive

• Returns a length-1 list [(name, item)] for a queue-mode winner, or [] when an event-mode put woke it (events are already in the prompt; the empty list tells you no queue item was consumed). The list shape is the contract.
• If multiple puts land on adjacent ticks, the first channel in registration order wins; the other drained items are restored to the head of their channels — nothing is dropped. on_get hooks fire only for the winner.
• Raises ValueError when no channels are registered (dispatchers treat this as "exit cleanly"); propagates CancelledError after cleaning up its drain tasks.
• Thread-safe wakeups: producers may put() from another thread (e.g. a UI thread); the manager wakes race() via the owning event loop.

spawn() — background jobs feeding channels

from nooa.runtime.producers import monitor, after, cron, tail, run_job

handle = qm.spawn(monitor("pytest -q"), channel="ci", buffer=100)  # stream stdout lines
qm.spawn(after(300), channel="wakeup")                              # one-shot timer → None
qm.spawn(cron(60), channel="ticks")                                 # yields 1, 2, 3, ... per minute
qm.spawn(tail("app.log"), channel="logs")                           # new lines as they appear
qm.spawn(run_job(some_coro(), job_id="batch-7"), channel="jobs")    # {"job_id": ..., "result": ...}

• A coroutine job puts its single result on completion; an async generator puts each yielded value.
• Lifecycle events go to the agent's event log: StreamEnd(channelname=...) when a job finishes, JobError(channelname, errortype, errormessage) on failure — JobError is also put on the data channel so race() wakes the agent to react.
• JobHandle: .state (running/done/cancelled/failed), await handle.cancel() (awaits generator finally cleanup), .values (buffered outputs — buffer=True unbounded, buffer=N ring of last N, default off).
• monitor() runs the command in its own process group and kills the whole group on cancel — no orphaned children; stderr is merged into stdout.

Pitfalls

• QueueManager is hidden from the LLM by default; expose deliberately (spec(self, "queue_manager", hidden=False)) or, better, expose only the reader attributes and keep put/spawn on the Python side.
• Registration order is priority order for race() — register the highest-priority channel (usually user messages) first.
• Don't await channel.get() (producer object) from LLM code — give the LLM the .reader, whose get(timeout=...) can't deadlock a cell.
• The dispatcher belongs in a pure-Python orchestrator method (run() above) — see "Orchestrators are pure Python" in nooa-agent-authoring.
• spawn() requires the channel to already exist (ValueError otherwise).

Related skills

• nooa-agent-authoring — the orchestrator pattern the dispatch loop lives in.
• nooa-context-and-state — QueueOutput/StreamEnd/JobError are events; query them like any others.
• nooa-middleware-hooks — on() observers if you only need to react to recorded events, not consume input.