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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.
43 lines
1.3 KiB
Python
43 lines
1.3 KiB
Python
"""``InputsBlock`` — the ``inputs`` section of the automation definition."""
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from __future__ import annotations
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from typing import Any
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from pydantic import BaseModel, ConfigDict, Field
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class InputsBlock(BaseModel):
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"""The ``inputs`` block of an ``AutomationDefinition``.
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Holds a JSON Schema describing what data the automation accepts at
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fire time. The same schema is used by:
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- The form editor (to render the manual-run dialog).
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- The dispatcher (to validate trigger payloads before enqueueing
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executor work).
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- The template engine (to expose ``{{ inputs.* }}`` references in
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plan-step configs).
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The ``schema`` value is the JSON-Schema dict itself, not a
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Pydantic model — automations express their input contract in pure
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JSON Schema so it round-trips losslessly through the database and
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the NL generator.
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"""
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model_config = ConfigDict(
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extra="forbid",
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populate_by_name=True,
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serialize_by_alias=True,
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)
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schema_: dict[str, Any] = Field(
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...,
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alias="schema",
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description=(
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"JSON Schema (draft-07 compatible) describing the inputs "
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"this automation accepts. Properties may use the special "
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"``$last_fired_at`` default literal to bind to the "
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"trigger's last fire time."
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),
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)
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