SurfSense/surfsense_backend/app/automations/schemas/triggers/manual.py

22 lines
757 B
Python
Raw Normal View History

feat(automation): add Pydantic schemas for the automation definition Three layers of Pydantic models under app/automations/schemas/, one file per concern (SRP), matching the envelope in automation-design-plan.md §5. definition/ — the editable envelope persisted in automations.definition: - envelope.py AutomationDefinition (top-level shape) - plan_step.py PlanStep (one step in the sequential plan) - inputs.py InputsBlock (the inputs JSON Schema wrapper) - execution.py ExecutionBlock (timeouts, retries, concurrency, budget cap, on_failure plan) - metadata.py MetadataBlock (tags + created_from_nl + extras) - trigger_spec.py TriggerSpec (one entry in triggers[]) triggers/ — per-trigger config schemas, dispatched by registry on the TriggerSpec.type discriminator: - schedule.py ScheduleTriggerConfig(cron, timezone) - manual.py ManualTriggerConfig() — empty in v1 actions/ — per-action config schemas, dispatched by registry on the PlanStep.action discriminator: - agent_task.py AgentTaskActionConfig(prompt, tools, model, output_schema) Design properties verified by an inline smoke test: - The §5 worked example round-trips through model_validate_json / model_dump_json byte-for-byte (InputsBlock uses serialize_by_alias so the JSON key stays "schema" not "schema_"). - Envelope rejects unknown top-level keys (extra="forbid"). - MetadataBlock tolerates unknown keys (extra="allow"). - ExecutionBlock defaults apply when the block is omitted. - retry_backoff and concurrency are typed as Literal — bogus values rejected at validation time. - Per-type configs enforce their required fields (cron + timezone on schedule; non-empty prompt on agent_task). The envelope keeps trigger and action configs as untyped dicts on purpose — per-type validation is a registry-driven dispatch (commit 10), keeping the envelope free of every-type-knows-every-type coupling.
2026-05-26 22:50:52 +02:00
"""``ManualTriggerConfig`` — config for the ``manual`` trigger type (empty in v1)."""
from __future__ import annotations
from pydantic import BaseModel, ConfigDict
class ManualTriggerConfig(BaseModel):
"""Config for the UI-driven ``manual`` trigger.
Validated against ``AutomationTrigger.config`` whenever the
persisted ``type`` is ``manual``. v1 carries no configurable
fields the "Run now" affordance simply fires this trigger with
an empty config object. The model exists so the registry dispatch
is uniform across all trigger types.
Future versions may add fields here (e.g., a fixed prompt to
pre-fill the run dialog with) without breaking v1 payloads.
"""
model_config = ConfigDict(extra="forbid")