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app/backend/fluksio/api/routes/runs.py
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stroblmeandClaude Opus 5 400d7d9c5c
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Stage caching for batch runs, and an engine that lives in the command
A code node in a batch run is now fingerprinted by its source, its raw
settings and the values it reads — an artifact input counting as its digest,
which is what the content addressing was always for. A run that finds the key
restores what the earlier one returned and skips the node, recorded as
`cached`. The run history is the cache: `run_node.outputs` beside the
`cache_key` the schema already had, no second store. On for code nodes, never
for the built-in and connector types that have side effects; off per node with
`@node(cache=False)` and per run with `--no-cache`.

Emissions are not replayed on a hit, so a cached training node returns its
result without redrawing its curve. Recorded in NOTEPAD.md with the two other
deliberate limits.

`fluksio run --local` boots the real app in the command's own process and
drives it through its ASGI interface behind the ordinary client, so a run no
longer needs a `serve` terminal beside it — same data directory, same history,
and the cache carries between the two. It always waits, because the engine it
starts lives exactly as long as the command.

Also: `fluksio sweep --param lr=0.1,0.01` for the product of the lists,
`run --follow` for a run's numbers as they arrive, Ctrl-C cancelling a waited
run rather than abandoning it, coloured statuses on a terminal, and `name`
made optional on the metrics endpoint so a follower can ask for every series.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-24 20:31:31 +02:00

297 lines
9.5 KiB
Python

"""Runs over the API: submit one, watch it, read what it made.
Submitting returns immediately with a queued run — a training run is measured
in hours, so nothing here waits for one. The way to follow a run is to poll it
or to listen on the flow socket, which carries its start and finish.
"""
from typing import Any
from fastapi import APIRouter, Depends, HTTPException, Request
from fastapi.concurrency import run_in_threadpool
from pydantic import BaseModel, Field
from sqlmodel import col, select
from fluksio.api.deps import CurrentUser, SessionDep, get_current_user
from fluksio.flow.runs import RunRejected, RunService, new_run_id
from fluksio.flow.store import FlowNotFound
from fluksio.models import Run, RunArtifact, RunMetric, RunNode
router = APIRouter(
prefix="/runs", tags=["runs"], dependencies=[Depends(get_current_user)]
)
#: A sweep bigger than this is almost always a mistake in a loop.
MAX_SWEEP = 1000
class RunCreate(BaseModel):
params: dict[str, Any] = Field(default_factory=dict)
seed: int | None = None
#: Run the unpublished draft instead of what is published.
draft: bool = False
#: Execute every node, whatever an earlier run already worked out.
no_cache: bool = False
class SweepEntry(BaseModel):
params: dict[str, Any] = Field(default_factory=dict)
seed: int | None = None
class SweepCreate(BaseModel):
runs: list[SweepEntry] = Field(default_factory=list)
draft: bool = False
no_cache: bool = False
class RunNodeRow(BaseModel):
node: str
status: str
attempt: int
duration_ms: float
worker: str
error: str
logs: str
#: What this node's result was looked up by. Empty when it may not be
#: reused; `status` is "cached" when it was.
cache_key: str = ""
class ArtifactRow(BaseModel):
name: str
node: str
digest: str
size: int
media_type: str
class RunRow(BaseModel):
"""A run without its result, which is the part that can be large."""
id: str
flow: str
status: str
status_reason: str
cause: str
params: dict[str, Any]
params_digest: str
#: The user repository's commit, for a flow declared in code with the
#: decorators. Empty for one drawn on the canvas, where `commit` is the
#: whole answer to what produced the number.
origin_commit: str = ""
seed: int | None
group_id: str | None
labels: list[str]
created_at: Any
started_at: Any = None
finished_at: Any = None
duration_ms: float
actor: str
class RunDetail(RunRow):
result: dict[str, Any] = Field(default_factory=dict)
commit: str = ""
flow_version: int = 1
nodes: list[RunNodeRow] = Field(default_factory=list)
artifacts: list[ArtifactRow] = Field(default_factory=list)
class MetricPoint(BaseModel):
step: int
ts: float
value: float
name: str = ""
class MetricSeries(BaseModel):
"""The shape a chart widget already draws, so comparing runs is a binding."""
label: str
points: list[list[float]] = Field(default_factory=list)
class SeriesAnswer(BaseModel):
metric: str
lines: list[MetricSeries] = Field(default_factory=list)
def _service(request: Request) -> RunService:
service: RunService | None = getattr(request.app.state, "run_service", None)
if service is None:
raise HTTPException(status_code=503, detail="Runs are not available")
return service
@router.post("/flows/{name}", response_model=RunRow, status_code=202)
async def create_run(
name: str, body: RunCreate, request: Request, user: CurrentUser
) -> Any:
"""Queue one run of a flow."""
service = _service(request)
try:
return await run_in_threadpool(
service.submit,
name,
params=body.params,
seed=body.seed,
cause="api",
actor=user.email,
draft=body.draft,
no_cache=body.no_cache,
)
except FlowNotFound as exc:
raise HTTPException(status_code=404, detail=str(exc)) from exc
except RunRejected as exc:
raise HTTPException(status_code=422, detail=str(exc)) from exc
@router.post("/flows/{name}/sweep", response_model=list[RunRow], status_code=202)
async def create_sweep(
name: str, body: SweepCreate, request: Request, user: CurrentUser
) -> Any:
"""Queue many runs of one flow under a shared group.
An ensemble is this with the same parameters and different seeds; a grid
search is this with the parameters spread out. Either way the caller
builds the list — the engine does not own a sweep grammar.
"""
if not body.runs:
raise HTTPException(status_code=422, detail="A sweep needs at least one run")
if len(body.runs) > MAX_SWEEP:
raise HTTPException(
status_code=422, detail=f"A sweep is capped at {MAX_SWEEP} runs"
)
service = _service(request)
group = new_run_id()
def submit_all() -> list[Run]:
return [
service.submit(
name,
params=entry.params,
seed=entry.seed,
group_id=group,
cause="sweep",
actor=user.email,
draft=body.draft,
no_cache=body.no_cache,
)
for entry in body.runs
]
try:
return await run_in_threadpool(submit_all)
except FlowNotFound as exc:
raise HTTPException(status_code=404, detail=str(exc)) from exc
except RunRejected as exc:
raise HTTPException(status_code=422, detail=str(exc)) from exc
@router.get("", response_model=list[RunRow])
def read_runs(
session: SessionDep,
flow: str | None = None,
status: str | None = None,
group: str | None = None,
digest: str | None = None,
limit: int = 50,
) -> Any:
"""Runs, newest first. The queryable table an experiment log needs."""
statement = select(Run).order_by(col(Run.created_at).desc())
if flow:
statement = statement.where(col(Run.flow) == flow)
if status:
statement = statement.where(col(Run.status) == status)
if group:
statement = statement.where(col(Run.group_id) == group)
if digest:
statement = statement.where(col(Run.params_digest) == digest)
return list(session.exec(statement.limit(min(limit, 500))))
@router.get("/{run_id}", response_model=RunDetail)
def read_run(run_id: str, session: SessionDep) -> Any:
"""One run in full: what it was asked, what each node did, what it made."""
run = session.get(Run, run_id)
if run is None:
raise HTTPException(status_code=404, detail="No such run")
nodes = session.exec(select(RunNode).where(col(RunNode.run_id) == run_id)).all()
artifacts = session.exec(
select(RunArtifact).where(col(RunArtifact.run_id) == run_id)
).all()
detail = RunDetail.model_validate(run, from_attributes=True)
detail.nodes = [RunNodeRow.model_validate(n, from_attributes=True) for n in nodes]
detail.artifacts = [
ArtifactRow.model_validate(a, from_attributes=True) for a in artifacts
]
return detail
@router.post("/{run_id}/cancel", response_model=RunRow)
async def cancel_run(run_id: str, request: Request, session: SessionDep) -> Any:
"""Stop a run. One already past its last node is left as it finished."""
run = session.get(Run, run_id)
if run is None:
raise HTTPException(status_code=404, detail="No such run")
service = _service(request)
await run_in_threadpool(service.cancel, run_id)
session.refresh(run)
return run
@router.get("/{run_id}/metrics", response_model=list[MetricPoint])
def read_metrics(
run_id: str, session: SessionDep, name: str = "", stride: int = 1
) -> Any:
"""One metric's series, in step order — or every one of them, unnamed.
``stride`` thins a long curve down: 3000 steps drawn on a 400-pixel chart
is 3000 points nobody can see.
"""
statement = select(RunMetric).where(col(RunMetric.run_id) == run_id)
if name:
statement = statement.where(col(RunMetric.name) == name)
statement = statement.order_by(col(RunMetric.name), col(RunMetric.step))
rows = list(session.exec(statement))
if stride > 1:
rows = rows[:: max(1, stride)]
return rows
@router.get("/series/compare", response_model=SeriesAnswer)
def compare_metric(session: SessionDep, ids: str, metric: str) -> Any:
"""One metric across several runs, as the chart widget's series shape.
This is the comparison view: it answers in the same shape a flow answers a
chart's query with, so putting three training curves beside each other is
a widget binding rather than a screen of its own.
"""
run_ids = [part for part in ids.split(",") if part]
if not run_ids:
raise HTTPException(status_code=422, detail="Name at least one run")
runs = {
run.id: run
for run in session.exec(select(Run).where(col(Run.id).in_(run_ids))).all()
}
lines: list[MetricSeries] = []
for run_id in run_ids:
run = runs.get(run_id)
if run is None:
continue
rows = session.exec(
select(RunMetric)
.where(col(RunMetric.run_id) == run_id, col(RunMetric.name) == metric)
.order_by(col(RunMetric.step))
).all()
label = run_id
if run.seed is not None:
label = f"{run_id} (seed {run.seed})"
lines.append(
MetricSeries(
label=label, points=[[float(row.step), row.value] for row in rows]
)
)
return SeriesAnswer(metric=metric, lines=lines)