Observers, watches, and alerts
When to use
- Observability — log model responses, tool calls, token usage.
- Runtime safety — block dangerous tool arguments, halt the agent.
- Reactive metrics — fire on every Nth response, or every M seconds.
- Loop / repetition detection — catch infinite tool-call loops.
- Stateful monitoring — anything that needs to remember prior events to decide what to do next.
Two observer shapes
| Shape | When | Use |
|---|---|---|
| Stateless function | One-off event hook (logging, metrics) | @observer(EventType) |
| Stateful class | Counters / windows / thresholds / composed triggers | Subclass BaseObserver |
Both are stream subscribers under the hood — registered on the agent rather than directly on the stream.
60-second recipe — @observer
from ag2 import Agent, observer
from ag2.config import OpenAIConfig
from ag2.events import ModelResponse
@observer(ModelResponse)
async def log_response(event: ModelResponse) -> None:
print(f"Model said: {event.content}")
agent = Agent(
"assistant",
config=OpenAIConfig(model="gpt-4o-mini"),
observers=[log_response],
)
Or attach after construction with @agent.observer(...). Per-call observers also supported (agent.ask("...", observers=[...])).
Observer callbacks support full dependency injection (Context, Inject, Variable, Depends). Filter by event type, multiple types (ModelRequest | ModelResponse), or field value (ToolCallEvent.name == "search"). Use interrupt=True to modify or suppress events before regular subscribers see them.
Built-in stateful observers
from ag2 import Agent
from ag2.observers import LoopDetector, TokenMonitor
agent = Agent(
"assistant",
config=config,
observers=[
TokenMonitor(warn_threshold=50_000, alert_threshold=100_000),
LoopDetector(window_size=10, repeat_threshold=3),
],
)
TokenMonitor— tracks cumulative tokens acrossModelResponseandTaskCompleted. EmitsWARNING/CRITICALObserverAlerts as thresholds are crossed. Read state viamonitor.total_tokens.LoopDetector— sliding window of recent tool calls. Emits aWARNINGalert whenrepeat_thresholdconsecutive identical calls are seen.
Custom BaseObserver
A BaseObserver pairs a Watch (when to fire) with a process() method (what to do):
from ag2 import Context
from ag2.observers import BaseObserver
from ag2.watch import CadenceWatch
from ag2.events import BaseEvent, ModelResponse
from ag2.events.alert import ObserverAlert, Severity
class AvgCompletionObserver(BaseObserver):
"""Every N responses, emit an INFO alert with avg completion-token count."""
def __init__(self, window: int = 5) -> None:
super().__init__("avg-completion", watch=CadenceWatch(n=window, condition=ModelResponse))
self._window = window
async def process(self, events: list[BaseEvent], ctx: Context) -> ObserverAlert | None:
tokens = [e.usage.completion_tokens for e in events if isinstance(e, ModelResponse) and e.usage]
if not tokens:
return None
return ObserverAlert(
source=self.name,
severity=Severity.INFO,
message=f"Avg completion tokens over last {self._window}: {sum(tokens) / len(tokens):.0f}",
)
If process() returns an ObserverAlert, the base class emits it onto the stream. You can also send events manually via await ctx.send(...).
Watch primitives — picking when to fire
| You need | Use |
|---|---|
| Every matching event | EventWatch(EventType) or just stream.subscribe(fn, condition=...) |
| Every N matching events | CadenceWatch(n=N, condition=EventType) |
| Every T seconds (buffered events) | CadenceWatch(max_wait=T, condition=EventType) |
| Either threshold | CadenceWatch(n=N, max_wait=T, condition=EventType) |
| Once after delay | DelayWatch(seconds) |
| Periodic timer | IntervalWatch(seconds) |
| Cron schedule | CronWatch("0 9 * * MON") |
| All sub-watches must fire | AllOf(w1, w2) |
| Any sub-watch fires | AnyOf(w1, w2) |
| In order | Sequence(w1, w2) |
All importable from ag2.watch. Callback signature is uniform: async def cb(events: list[BaseEvent], ctx: Context) -> None. Time-driven watches pass events=[].
ObserverAlert — the alert type
from ag2.events.alert import ObserverAlert, Severity
ObserverAlert(
source="my-observer",
severity=Severity.WARNING, # INFO, WARNING, CRITICAL, FATAL
message="What happened",
)
Important: ObserverAlert is on the stream and persisted in history, but the default provider mappers do not render it back to the LLM. To make the agent see alerts, add AlertPolicy() to assembly=[...]:
from ag2.policies import AlertPolicy
agent = Agent("assistant", config=config, assembly=[AlertPolicy()])
FATAL alerts → HaltEvent → short-circuit
AlertPolicy does two things on Severity.FATAL:
- Emits a
HaltEventon the stream. - Appends a halt notice to the system prompt.
When assembly=[...] is non-empty, the harness automatically wires _HaltCheckMiddleware which sees the HaltEvent and short-circuits the next LLM call with a synthetic HALTED: ... response.
from ag2 import Context
from ag2.observers import BaseObserver
from ag2.events import BaseEvent, ToolCallEvent
from ag2.events.alert import HaltEvent, ObserverAlert, Severity
from ag2.policies import AlertPolicy
from ag2.watch import EventWatch
class PathGuardian(BaseObserver):
def __init__(self) -> None:
super().__init__("path-guardian", watch=EventWatch(ToolCallEvent))
async def process(self, events: list[BaseEvent], ctx: Context) -> ObserverAlert | None:
for event in events:
if not isinstance(event, ToolCallEvent) or event.name != "write_file":
continue
if "/etc/" in event.arguments or "/usr/" in event.arguments:
return ObserverAlert(
source=self.name,
severity=Severity.FATAL,
message=f"blocked dangerous write: {event.arguments}",
)
return None
agent = Agent(
"safe-shell",
prompt="...",
config=config,
tools=[write_file],
observers=[PathGuardian()],
assembly=[AlertPolicy()], # routes FATAL → HaltEvent
)
The first dangerous tool call triggers FATAL → halt; the agent's next ask is short-circuited. Full runnable demo: assets/safety_guard.py.
Subscribing to alerts and halts from outside
from ag2 import MemoryStream
from ag2.events.alert import HaltEvent, ObserverAlert
stream = MemoryStream()
stream.where(ObserverAlert).subscribe(lambda e: print(f"[{e.severity}] {e.source}: {e.message}"))
stream.where(HaltEvent).subscribe(lambda e: print(f"HALT: {e.reason}"))
await agent.ask("...", stream=stream)
Observers vs Middleware vs Stream subscribers
| Feature | Observer | Middleware | Stream subscriber |
|---|---|---|---|
| Registered on | Agent | Agent | Stream |
| Lifecycle | Scoped to execution | Scoped to execution | Manual |
| Boilerplate | Function (or BaseObserver) |
BaseMiddleware class |
Function |
| Can modify events | interrupt=True |
Yes (wraps execution) | interrupt=True |
| DI support | Yes | Yes | Yes |
| Use case | Monitoring, metrics, alerts | Cross-cutting (retry, auth, rate limit) | Low-level event wiring |
Going deeper
assets/token_watchdog.py— three observers (TokenMonitor,LoopDetector, customAlertConsole) on one agent. Mirrorscode_examples/04.assets/safety_guard.py—PathGuardian→ FATAL →AlertPolicy→HaltEvent→ short-circuit. Mirrorscode_examples/08.- Source docs:
website/docs/user-guide/advanced/observers.mdx—@observer,BaseObserver, registration, built-ins,ObserverAlert.website/docs/user-guide/advanced/watches.mdx— every Watch primitive, composition rules.website/docs/user-guide/advanced/stream.mdx— Stream API,where,subscribe, interrupters,RedisStream.website/docs/user-guide/advanced/assembly.mdx—AlertPolicyordering and dedup.
Common pitfalls
- Alerts not reaching the model —
ObserverAlertevents are on the stream but invisible to the LLM by default. AddAlertPolicy()toassembly=[...]. - FATAL not halting —
AlertPolicyis what createsHaltEvent. Withoutassembly=[..., AlertPolicy(), ...](or any non-empty assembly chain enabling_HaltCheckMiddleware), nothing halts. - Sharing one
AlertPolicy()across agents — dedup state lives on the instance. Give each agent its own. - Watch callback assumes
eventsis non-empty — for time-driven watches (DelayWatch,IntervalWatch,CronWatch),eventsis always[]. - Forgetting
process()is async —BaseObserver.processmust beasync def. - Subscribing with
subscribe(fn)when you wantedsubscribe()decorator — both work; the bare-call form isstream.subscribe(fn), the decorator form is@stream.subscribe()(with parens). CadenceWatchwith nonand nomax_wait— raisesValueError; at least one is required.