A data scientist keeps their code where it is and decorates it: `@node` declares a function's ports beside the function, `Flow(name, nodes=[...])` says which of them make a flow, and `use(fn, wire=..., **settings)` rebinds one for a single flow. `fluksio sync` uploads the document plus a generated import shim per node, so the store still holds a complete, runnable, git-versioned definition while the code it imports stays theirs. `fluksio login|run|runs` and `flow.submit().wait()` are the client half, over the run endpoints that already existed. Runs record the user repository's commit beside the store's, so "what code produced this number" is answerable on the side that now holds the code. - `fluksio/sdk/`: ports, decorators, the flow builder and its checks, the shim generator, an HTTP client and sync. Standard library only at import, so `from fluksio import node` in a training script pulls in no engine. - `FlowDef.origin` marks a flow code-defined; `Run.origin_commit` carries the repository's commit; `POST /modules/refresh` retires the workers without an install, which every sync calls — a worker holds the imported package in memory, so an edit to it is invisible until the process goes. - The canvas shows a generated body read-only and names the repository to edit instead; a body edited there stops the next sync rather than being discarded. - The worker's reporter carries inert `Port`, `node`, `use` and `Flow`, since the shim imports a module whose first line declares them. - `examples/myresearch` is the worked example, `make sync-example` uploads it. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_012ue1tkFWB1bcGy3aWhCKpU
287 lines
9.0 KiB
Python
287 lines
9.0 KiB
Python
"""Runs over the API: submit one, watch it, read what it made.
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Submitting returns immediately with a queued run — a training run is measured
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in hours, so nothing here waits for one. The way to follow a run is to poll it
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or to listen on the flow socket, which carries its start and finish.
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"""
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from typing import Any
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from fastapi import APIRouter, Depends, HTTPException, Request
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from fastapi.concurrency import run_in_threadpool
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from pydantic import BaseModel, Field
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from sqlmodel import col, select
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from fluksio.api.deps import CurrentUser, SessionDep, get_current_user
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from fluksio.flow.runs import RunRejected, RunService, new_run_id
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from fluksio.flow.store import FlowNotFound
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from fluksio.models import Run, RunArtifact, RunMetric, RunNode
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router = APIRouter(
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prefix="/runs", tags=["runs"], dependencies=[Depends(get_current_user)]
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)
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#: A sweep bigger than this is almost always a mistake in a loop.
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MAX_SWEEP = 1000
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class RunCreate(BaseModel):
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params: dict[str, Any] = Field(default_factory=dict)
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seed: int | None = None
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#: Run the unpublished draft instead of what is published.
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draft: bool = False
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class SweepEntry(BaseModel):
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params: dict[str, Any] = Field(default_factory=dict)
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seed: int | None = None
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class SweepCreate(BaseModel):
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runs: list[SweepEntry] = Field(default_factory=list)
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draft: bool = False
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class RunNodeRow(BaseModel):
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node: str
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status: str
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attempt: int
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duration_ms: float
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worker: str
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error: str
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logs: str
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class ArtifactRow(BaseModel):
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name: str
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node: str
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digest: str
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size: int
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media_type: str
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class RunRow(BaseModel):
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"""A run without its result, which is the part that can be large."""
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id: str
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flow: str
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status: str
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status_reason: str
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cause: str
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params: dict[str, Any]
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params_digest: str
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#: The user repository's commit, for a flow declared in code with the
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#: decorators. Empty for one drawn on the canvas, where `commit` is the
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#: whole answer to what produced the number.
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origin_commit: str = ""
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seed: int | None
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group_id: str | None
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labels: list[str]
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created_at: Any
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started_at: Any = None
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finished_at: Any = None
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duration_ms: float
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actor: str
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class RunDetail(RunRow):
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result: dict[str, Any] = Field(default_factory=dict)
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commit: str = ""
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flow_version: int = 1
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nodes: list[RunNodeRow] = Field(default_factory=list)
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artifacts: list[ArtifactRow] = Field(default_factory=list)
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class MetricPoint(BaseModel):
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step: int
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ts: float
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value: float
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class MetricSeries(BaseModel):
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"""The shape a chart widget already draws, so comparing runs is a binding."""
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label: str
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points: list[list[float]] = Field(default_factory=list)
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class SeriesAnswer(BaseModel):
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metric: str
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lines: list[MetricSeries] = Field(default_factory=list)
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def _service(request: Request) -> RunService:
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service: RunService | None = getattr(request.app.state, "run_service", None)
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if service is None:
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raise HTTPException(status_code=503, detail="Runs are not available")
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return service
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@router.post("/flows/{name}", response_model=RunRow, status_code=202)
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async def create_run(
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name: str, body: RunCreate, request: Request, user: CurrentUser
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) -> Any:
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"""Queue one run of a flow."""
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service = _service(request)
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try:
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return await run_in_threadpool(
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service.submit,
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name,
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params=body.params,
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seed=body.seed,
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cause="api",
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actor=user.email,
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draft=body.draft,
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)
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except FlowNotFound as exc:
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raise HTTPException(status_code=404, detail=str(exc)) from exc
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except RunRejected as exc:
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raise HTTPException(status_code=422, detail=str(exc)) from exc
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@router.post("/flows/{name}/sweep", response_model=list[RunRow], status_code=202)
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async def create_sweep(
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name: str, body: SweepCreate, request: Request, user: CurrentUser
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) -> Any:
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"""Queue many runs of one flow under a shared group.
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An ensemble is this with the same parameters and different seeds; a grid
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search is this with the parameters spread out. Either way the caller
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builds the list — the engine does not own a sweep grammar.
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"""
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if not body.runs:
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raise HTTPException(status_code=422, detail="A sweep needs at least one run")
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if len(body.runs) > MAX_SWEEP:
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raise HTTPException(
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status_code=422, detail=f"A sweep is capped at {MAX_SWEEP} runs"
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)
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service = _service(request)
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group = new_run_id()
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def submit_all() -> list[Run]:
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return [
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service.submit(
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name,
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params=entry.params,
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seed=entry.seed,
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group_id=group,
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cause="sweep",
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actor=user.email,
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draft=body.draft,
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)
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for entry in body.runs
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]
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try:
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return await run_in_threadpool(submit_all)
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except FlowNotFound as exc:
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raise HTTPException(status_code=404, detail=str(exc)) from exc
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except RunRejected as exc:
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raise HTTPException(status_code=422, detail=str(exc)) from exc
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@router.get("", response_model=list[RunRow])
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def read_runs(
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session: SessionDep,
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flow: str | None = None,
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status: str | None = None,
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group: str | None = None,
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digest: str | None = None,
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limit: int = 50,
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) -> Any:
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"""Runs, newest first. The queryable table an experiment log needs."""
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statement = select(Run).order_by(col(Run.created_at).desc())
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if flow:
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statement = statement.where(col(Run.flow) == flow)
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if status:
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statement = statement.where(col(Run.status) == status)
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if group:
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statement = statement.where(col(Run.group_id) == group)
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if digest:
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statement = statement.where(col(Run.params_digest) == digest)
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return list(session.exec(statement.limit(min(limit, 500))))
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@router.get("/{run_id}", response_model=RunDetail)
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def read_run(run_id: str, session: SessionDep) -> Any:
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"""One run in full: what it was asked, what each node did, what it made."""
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run = session.get(Run, run_id)
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if run is None:
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raise HTTPException(status_code=404, detail="No such run")
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nodes = session.exec(select(RunNode).where(col(RunNode.run_id) == run_id)).all()
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artifacts = session.exec(
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select(RunArtifact).where(col(RunArtifact.run_id) == run_id)
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).all()
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detail = RunDetail.model_validate(run, from_attributes=True)
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detail.nodes = [RunNodeRow.model_validate(n, from_attributes=True) for n in nodes]
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detail.artifacts = [
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ArtifactRow.model_validate(a, from_attributes=True) for a in artifacts
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]
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return detail
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@router.post("/{run_id}/cancel", response_model=RunRow)
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async def cancel_run(run_id: str, request: Request, session: SessionDep) -> Any:
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"""Stop a run. One already past its last node is left as it finished."""
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run = session.get(Run, run_id)
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if run is None:
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raise HTTPException(status_code=404, detail="No such run")
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service = _service(request)
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await run_in_threadpool(service.cancel, run_id)
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session.refresh(run)
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return run
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@router.get("/{run_id}/metrics", response_model=list[MetricPoint])
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def read_metrics(run_id: str, session: SessionDep, name: str, stride: int = 1) -> Any:
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"""One metric's series, in step order.
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``stride`` thins a long curve down: 3000 steps drawn on a 400-pixel chart
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is 3000 points nobody can see.
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"""
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statement = (
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select(RunMetric)
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.where(col(RunMetric.run_id) == run_id, col(RunMetric.name) == name)
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.order_by(col(RunMetric.step))
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)
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rows = list(session.exec(statement))
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if stride > 1:
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rows = rows[:: max(1, stride)]
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return rows
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@router.get("/series/compare", response_model=SeriesAnswer)
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def compare_metric(session: SessionDep, ids: str, metric: str) -> Any:
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"""One metric across several runs, as the chart widget's series shape.
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This is the comparison view: it answers in the same shape a flow answers a
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chart's query with, so putting three training curves beside each other is
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a widget binding rather than a screen of its own.
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"""
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run_ids = [part for part in ids.split(",") if part]
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if not run_ids:
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raise HTTPException(status_code=422, detail="Name at least one run")
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runs = {
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run.id: run
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for run in session.exec(select(Run).where(col(Run.id).in_(run_ids))).all()
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}
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lines: list[MetricSeries] = []
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for run_id in run_ids:
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run = runs.get(run_id)
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if run is None:
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continue
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rows = session.exec(
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select(RunMetric)
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.where(col(RunMetric.run_id) == run_id, col(RunMetric.name) == metric)
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.order_by(col(RunMetric.step))
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).all()
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label = run_id
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if run.seed is not None:
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label = f"{run_id} (seed {run.seed})"
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lines.append(
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MetricSeries(
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label=label, points=[[float(row.step), row.value] for row in rows]
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)
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)
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return SeriesAnswer(metric=metric, lines=lines)
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