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feat(automation): add empty Capability / Action / Trigger registries
Three registries under app/automations/registries/, each as its own
folder with the same SRP-per-file split (types.py for the dataclass,
store.py for the in-memory dict + register/get/all functions). All
three start empty; concrete entries land when the user signs off on
which capabilities / actions / triggers to include (step 2).
Capability (locked at v1-minimum five fields — see commit 2):
- id, description, input_schema, output_schema, handler
- CapabilityHandler = Callable[[dict[str, Any]], Awaitable[Any]]
- Frozen, slotted dataclass (immutable post-registration).
ActionDefinition (v1-trim of design plan §4):
- type, name, description, config_schema, handler
- Defers output_contract (handled per-step by agent_task's
config.output_schema), uses_capabilities (no static analysis
needed until >1 action ships), and produces_artifacts (deferred
alongside the artifact pipeline).
TriggerDefinition (declarative, no handler):
- type, description, config_schema, payload_schema
- No handler field — firing is a single dispatcher's
responsibility, not a per-trigger one.
store.py contract for all three:
- register_*: idempotent at process startup, raises on duplicate
- get_*: returns None on miss
- all_*: returns a defensive copy of the registry dict
Verified by an inline smoke test (10 checks): empty initial state,
registration and lookup work, duplicates raise, frozen dataclasses
reject mutation, snapshots are copies, handlers are awaitable.
Isolation invariant audit: grep across the full app/automations/
tree shows only three app.* imports, all of them
``from app.db import BaseModel, TimestampMixin`` in the model files.
No imports from app.agents.*, app.services.*, app.tasks.*,
app.routes.*, or any other business-logic module.
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10 changed files with 291 additions and 4 deletions
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from __future__ import annotations
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__all__: list[str] = []
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from .store import all_triggers, get_trigger, register_trigger
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from .types import TriggerDefinition
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__all__ = [
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"TriggerDefinition",
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"all_triggers",
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"get_trigger",
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"register_trigger",
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]
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"""Trigger registry: in-memory dict + ``register_trigger`` API."""
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from __future__ import annotations
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from .types import TriggerDefinition
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_REGISTRY: dict[str, TriggerDefinition] = {}
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def register_trigger(trigger: TriggerDefinition) -> None:
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"""Add a trigger to the in-memory registry.
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Raises ``ValueError`` on duplicate ``type`` — registration runs
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once per process, so a duplicate is always a bug.
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"""
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if trigger.type in _REGISTRY:
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raise ValueError(
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f"Trigger already registered: {trigger.type!r}"
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)
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_REGISTRY[trigger.type] = trigger
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def get_trigger(trigger_type: str) -> TriggerDefinition | None:
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"""Look up one trigger by type. Returns ``None`` on miss."""
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return _REGISTRY.get(trigger_type)
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def all_triggers() -> dict[str, TriggerDefinition]:
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"""Snapshot of the registry as a defensive copy."""
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return dict(_REGISTRY)
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"""``TriggerDefinition`` dataclass — declarative trigger metadata, no handler."""
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import Any
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@dataclass(frozen=True, slots=True)
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class TriggerDefinition:
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"""A trigger type the dispatcher knows how to fire.
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Triggers are purely declarative: the dispatcher (a single
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process-wide component, not a per-type handler) reads the
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``automation_triggers`` table and decides when each row should
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fire. The trigger's job here is to declare its input/output
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contract:
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- ``config_schema``: JSON Schema for the persisted
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``AutomationTrigger.config`` — used by the form editor and
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validated on save.
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- ``payload_schema``: JSON Schema for the payload the dispatcher
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will deliver to the executor at fire time (e.g., a schedule
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trigger emits ``fired_at`` / ``scheduled_for`` /
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``last_fired_at``).
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No ``handler`` field — firing is a dispatcher responsibility,
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not a per-trigger one. This keeps the dispatcher single and
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leaves trigger types as pure metadata.
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"""
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type: str
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description: str
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config_schema: dict[str, Any]
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payload_schema: dict[str, Any]
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