FE-1583: Run the connected optimizer's trials through the experiments backend by kube · Pull Request #9516 · hashintel/hash

kube · 2026-09-03T00:21:37Z

Important

Experimental
Behind the In-browser optimization feature flag.

Summary

Before this PR, PetrinautOptimizationContext accepted a self-contained remote capability, and a study's trials were numbers in a table. Study drawer's Surface could sample the objective locally, but it knew nothing of where the optimizer was looking, and the optimizer could not use the browser's compute at all.

This PR lets the context carry a connected optimization source and runs its trials through the experiments layer. A new runDetachedObjective action runs a frozen study's objective at one parameter point on the chosen backend with pinned seeds and streams its frames. Optimizations provider evaluates each trial through it, follows the trial in the navigator, streams its metrics live, and after the study settles refines the best point, or whichever point the user picks. Study drawer shows the optimizer's own steps as dots on the Surface with the field filling in as steps report, a Stop that keeps the study and a Continue that adds steps to it, up to four steps in flight with an activity list, and one metric line always in view. Form gains Runs per step, Parallel steps and the experiments' Backend switch. A remote capability such as the HASH host's NodeAPI bridge is unaffected, and the connected source only takes effect with the experimental setting on.

9516.mp4

Links

Ticket FE-1583

Changes

Feature flag

New experimental setting In-browser optimization under Settings > Simulation

Row shows only when the host supplies a connected optimizer.
useOptimizationSource is the one place that reads the context and the setting

A remote capability passes through as is.
A connected source passes through only with the setting on, else the tab stays hidden and nothing connects; turning it off cancels connected runs and disposes.

Experiments layer

runDetachedObjective runs a study's objective at one point and streams it

Compiles once per study, chooses the backend once per study and backend with the experiments' registrations at a third of the CPU pool, pins per-run seeds on the CPU pool only, streams frames and progress.
Settles with per-run results or a reason: compile diagnostics, backend refusals, failed runs, cancellation.
Runs queue per queueKey while sharing one compiled snapshot per cacheKey

Parallel steps of one study overlap on the backend; refinement rungs of one point stay in order.
A cancelled run settles instead of hanging its queue

Instantiation gets its own abort controller, mirrored from the run signal only until the backend handle exists.
A later cancel goes through the handle, whose cancelled event releases the queue to the next run.
Sweep throttle moves to experiments/shared for reuse

Optimization channel and provider

Channel evaluates a trial as one detached objective run with the trial's seeds and the study's backend

Objective is the mean of the per-run finals when the backend reports them, else the last frames' value; a failure prunes the trial with its reason; the channel never throws.
Records carry computeBackend, the study's axes and, for a connected study only, a connected state with its navigation, selection stream, activity, inFlight trials, resumable, parallelism and fallback reason

Remote records carry connected: null, the one discriminant the drawer branches on.
Navigation follows the most recently started step; a user move stops following. Selection stream carries the followed step's frames, then the refined point's.
Study settles on its best point when it completes or stops

Navigation moves to the best step while it still follows, and refinement starts there.
Point refinement climbs the run ladder to 100 runs for the navigated point

Starts when the study settles or the user moves, cancels and restarts on a navigation change, caches per point, stops with the reason on failure.
Between rungs it compares the point's estimate with the best: a point that cannot beat the best by 2.5 standard errors stops after its first rung with the note "8 runs · cannot beat the best"; the best point refines fully.
extendOptimization(id, steps) continues a finished or stopped connected study

Provider calls extendOptimizationRun, re-attaches from the record's cursor, turns following back on; the steps continue Optuna's numbering.
Stop keeps the attachment so the segment's terminal event lands and marks the record resumable.
Removing a connected record releases its study in the worker
Connected runs are not written to session storage since they cannot outlive the page

Form and drawer

Create form gains Runs per step, Parallel steps, Seed and the Backend switch

Runs per step lands in execution.seedsPerTrial; the total-steps rule multiplies by it.
Parallel steps is 1 to 4 and shows for a connected source only.
Seed starts at a fresh random value each time the form opens and seeds both the proposals and the runs; every study used to share one fixed seed, so two studies drew the same random steps.
Backend cell is the experiments' shared toggle, shown for a connected source with WebGPU on; it stays disabled with the reason because the GPU backend cannot compute an expression objective.
Connected study drawer lays everything out to fit one screen

A summary strip carries status, finished over requested steps, best value, the backend badge, the steps bar and the "N computing" chip.
Parameters band holds a slider per axis, Follow steps and the refinement status.
Surface sits beside the objective chart, the Steps table fills the rest, and the footer holds Stop, or Remove and Continue with a step count.
Surface shows the optimizer's steps only

Each step with an objective is one sample of the field at its projected position and a dot, the best emphasized, pruned steps hollow.
A step in flight enters the field with its running value, and so does the refined point after settle, so the plot fills in as the study streams.
While a running study is followed the plot and the sliders are display-only; once the study is terminal, or Follow steps is off, a click or drag commits the navigation.
Remote study drawer keeps its locally sampled Surface and its Cancel
New layers react.optimizations.connected-study and ui.views.editor.optimizations declare the study machinery and the Optimizations tab in the architecture docs
Shared pieces move to SimulateView/shared: useGpuAvailability, ComputeBackendToggle, ComputeBackendBadge, MetricTiles, ComputeActivity, SummaryStrip, format-value

One number formatter for the list, the drawer and the experiments; one batch registry in experiments/shared for sweeps and studies; one errorMessage helper; the connected and remote drawers render the same summary strip.
Slider in @hashintel/ds-components accepts disabled

Stories and example

Storybook Simulate / Browser optimizer (real) runs the real Pyodide optimizer against the real experiments backends

SirCpu, SirGpuRequested, SupplyChain, VaccinationCampaign start a study on load; Manual opens the create form.
Shared harness simulate-view-story-harness.tsx with AutoStudy; the synthetic-optimizer story is renamed RunSupplyChainOptimizationSyntheticOptimizer.
New core example Vaccination Campaign built for optimization demos

SIR with pre-wave vaccination coverage and contact reduction, a Total cost objective whose minimum lies inside the domain, GPU-eligible; listed under Load example.

Review fixes

Study seed masks a 32-bit crypto draw with the seed range instead of reducing it modulo
Stop on a connected study whose run has no id yet aborts the creation

The run is cancelled where it was made once its id arrives, and nothing attaches to it.
A point stopped early as unable to beat the best resumes its ladder once it is the best

A parked point is re-evaluated when a trial changes the best, and when the study settles.
Surface cell cache keys on the axes as well as the positions

Swapped X and Y axes never reuse each other's samples.
One changeset per package

@hashintel/petrinaut, @hashintel/ds-components and one for the Vaccination Campaign example in @hashintel/petrinaut-core.
Continue follows the terminal event's resumable flag

A study stopped while the runtime loads, or while another study holds the worker, has no study to continue and offers no Continue.

Known issues

GPU studies are unreachable from the form until the WebGPU backend computes expression metrics

Record, channel and registrations already carry the choice.

Test coverage

provider/detached-objective.test.ts:

Streaming, pinned seeds on the CPU and none on the GPU, fallback re-pinning, failure reasons for refusal, errored runs and compile errors, one walk per study and backend, per-key queueing, a cancelled batch settling and releasing the queue, distinct queue keys side by side, cancel and dispose.
optimizations/provider.test.tsx, provider/connected-study.test.ts, provider/point-refinement.test.ts, provider/point-refinement/objective-estimate.test.ts, provider/activity-registry.test.ts, channel/create-optimization-channel.test.ts:

Setting gate on, off and toggled, remote unaffected, trials through runDetachedObjective with seeds and backend, following and user moves, settle on the best, the ladder and its early stop, restart on navigation change, stop then continue from the cursor, refused continuation, removal releasing the study, activity throttling.
create-optimization-drawer.test.tsx, view-optimization-drawer.test.tsx, study-summary-strip.test.ts, steps-table.test.ts, optimization-navigator.test.tsx, optimization-surface/surface-plot.test.tsx, simulate-view.test.tsx, viewport-settings-dialog.test.tsx:

Runs per step, parallel steps, the typed seed and its limit, the backend option, Stop, Stopped and Continue, progress bars and the computing chip, the note on a refused point, trials-only field and provisional samples, display-only while following, tab gating, default off.
examples/vaccination-campaign.test.ts, webgpu/compilation-report.test.ts:

GPU eligibility and readiness of the example, its default marking, and a seeded check that the cost at the valley is below the domain's boundary points.
Storybook DOM probes and screenshots:

SirCpu streaming, Stop at step 2 then Continue +4 to Complete 6 / 6, a hopeless pick stopping after 8 runs, the best point climbing to 100 runs.

How to test

yarn workspace @hashintel/petrinaut dev
Simulate > Browser optimizer (real) > SirCpu

Expect the runtime to download once, then steps as dots on the Surface, the field filling in, the metric line streaming
Stop

Expect Stopped, the navigation on the best step, refinement to 100 runs
Continue

Expect steps resuming with continued numbering, then Complete
Click a corner of the Surface

Expect "0 of 8 runs — refining" then "8 runs · cannot beat the best"
Click next to the best dot

Expect refinement climbing to 100 runs and the metric line restreaming
Simulate > Browser optimizer (real) > VaccinationCampaign

Expect a valley on the Surface with the best dot on its floor
Simulate > ViewOptimizationDrawer stories

Expect the running, complete, stopped, fallback and remote variants to render

vercel · 2026-09-03T00:21:41Z

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cursor · 2026-09-08T01:35:11Z

PR Summary

High Risk
Large cross-cutting change to optimization lifecycle, experiment compute queuing, and backend fallback; incorrect trial/refinement or cancellation handling could skew results or leak workers, though coverage is extensive.

Overview
Adds in-browser optimization behind the experimental In-browser optimization setting: the host can supply a connected optimization source whose trials run locally instead of only a remote capability.

The experiments layer gains runDetachedObjective, which streams Monte Carlo batches for a frozen study snapshot on CPU or WebGPU (with backend selection, per-study compile cache, queued runs per queueKey, pinned seeds on CPU, and structured failure/cancel outcomes). Sweeps reuse a shared batch registry and throttle helpers moved under experiments/shared.

The optimizations stack wires a channel that maps each optimizer trial to one detached run (objective from per-run means or last frames; failures become pruned trials). OptimizationsProvider tracks connected study state—navigation, follow-trials, live selection, in-flight trials, activity, stop/continue via extendOptimization, and point refinement up to 100 runs—while remote studies stay unchanged. Public exports expand for connected optimization types.

Slider in @hashintel/ds-components supports disabled. @hashintel/petrinaut-core adds the Vaccination Campaign optimization example (SIR + policy levers, interior cost minimum, GPU-ready) with tests and docs.

^{Reviewed by Cursor Bugbot for commit b058535. Bugbot is set up for automated code reviews on this repo. Configure here.}

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Copilot

🟡 Changes recommended

Surface caching, best-point refinement, user documentation, and package changesets contain unresolved correctness issues.

Once you've addressed the issues Copilot identified, you can request another Copilot review.

Pull request overview

Adds experimental in-browser optimization to Petrinaut, routing optimizer trials through the experiments backend with streaming, refinement, navigation, and continuation support.

Changes:

Adds connected optimizer lifecycle, feature gating, detached objective execution, and refinement.
Introduces connected-study UI, shared experiment components, and surface visualization enhancements.
Adds the Vaccination Campaign example, tests, stories, documentation, and package changeset.

File summaries

File	Description
`viewport-settings-dialog.tsx`	Adds the experimental setting.
`viewport-settings-dialog.test.tsx`	Tests its default value.
`simulate-view.tsx`	Gates connected optimization UI.
`simulate-view.test.tsx`	Tests optimization tab gating.
`use-gpu-availability.ts`	Extracts GPU eligibility analysis.
`surface-frame.tsx`	Generalizes surface captions.
`summary-strip.tsx`	Adds shared summary presentation.
`metric-tiles.tsx`	Extracts reusable metric tiles.
`format-value.ts`	Centralizes value formatting.
`compute-backend-toggle.tsx`	Adds shared backend selection UI.
`compute-backend-badge.tsx`	Adds shared backend status UI.
`compute-activity.tsx`	Generalizes compute progress display.
`study-summary-strip.tsx`	Summarizes connected study progress.
`study-summary-strip.test.ts`	Tests step-progress descriptions.
`steps-table.tsx`	Displays recent optimization steps.
`study-progress.ts`	Derives study progress and activity.
`optimization-navigator.tsx`	Adds connected parameter navigation.
`optimization-metrics.tsx`	Displays streamed objective metrics.
`navigator-band.tsx`	Composes connected navigation controls.
`continue-control.tsx`	Adds study continuation controls.
`view-optimization-drawer.stories.tsx`	Adds drawer variants.
`optimizations-view.tsx`	Reuses shared formatting and statuses.
`use-study-surface-walk.ts`	Samples remote study surfaces.
`sample-study-cell.ts`	Caches and samples surface cells.
`navigation-slice.ts`	Resolves surface slices and keys.
`optimization-surface.stories.tsx`	Adds connected surface stories.
`optimization-status.ts`	Distinguishes stopped connected studies.
`optimization-seed.ts`	Generates and validates study seeds.
`browser-optimizer.stories.tsx`	Adds real browser optimizer stories.
`experiment-metrics.tsx`	Adopts shared metric tiles.
`view-experiment-drawer.tsx`	Adopts the shared backend badge.
`sweep-surface.tsx`	Uses generalized surface APIs.
`experiments/shared/format-number.ts`	Removes superseded formatter.
`experiments-story-fixtures.tsx`	Adds streaming objective fixtures.
`bin-histogram-canvas.tsx`	Uses shared fixed formatting.
`frame-popover.tsx`	Uses shared fixed formatting.
`experiment-metric-timeline.tsx`	Supports fixed-size metric charts.
`create-experiment-drawer.tsx`	Reuses shared GPU controls.
`create-experiment-drawer.test.tsx`	Updates provider fixtures.
`editor-view.tsx`	Lists the new example.
`paint-field.ts`	Adds marker variants and sparse-field behavior.
`contour-field.test.ts`	Tests irregular sparse interpolation.
`contour-surface.tsx`	Supports display-only plots and marker options.
`user-settings-provider.tsx`	Persists the new feature flag.
`user-settings-context.ts`	Defines the feature setting.
`use-optimization-source.ts`	Centralizes source gating.
`surface-grid.ts`	Adds navigation key/value helpers.
`sir-optimization-input.fixtures.ts`	Adds shared SIR test input.
`objective-estimate.ts`	Estimates objective uncertainty.
`objective-estimate.test.ts`	Tests refinement stopping logic.
`point-refinement.ts`	Implements the refinement ladder.
`fake-detached-objective-runs.fixtures.ts`	Adds controllable run fixtures.
`optimizations/context.ts`	Expands connected study state and actions.
`trial-outcome.ts`	Converts experiment outcomes to trial outcomes.
`create-optimization-channel.ts`	Connects trials to experiment runs.
`create-optimization-channel.test.ts`	Tests channel execution behavior.
`optimization-context.ts`	Accepts connected optimization sources.
`react/index.ts`	Exports connected optimization APIs.
`sweep-session/README.md`	Updates shared-module architecture.
`sweep-session/batch-registry.ts`	Removes the old private registry.
`sweep-session/batch-registry.test.ts`	Removes superseded tests.
`sweep-session.ts`	Adopts the shared registry and throttle.
`shared/throttle.ts`	Adds reusable throttling.
`shared/error-message.ts`	Adds shared error normalization.
`shared/batch-registry.ts`	Adds the generic batch registry.
`shared/batch-registry.test.ts`	Tests generic registry behavior.
`experiments/provider.tsx`	Exposes streaming detached runs.
`experiments/context.ts`	Defines detached run contracts.
`main.ts`	Exports connected optimization types.
`docs/examples.md`	Documents Vaccination Campaign.
`compilation-report.test.ts`	Includes the new GPU-ready example.
`vaccination-campaign.test.ts`	Tests example behavior and eligibility.
`examples/index.ts`	Exports Vaccination Campaign.
`examples.test.ts`	Adds the example to validation tests.
`ai.ts`	Adds the example to documentation summaries.
`Slider/slider.tsx`	Adds disabled slider support.
`.changeset/connected-optimizer-source.md`	Records consumer-facing changes.

Review details

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Comments generated: 4
Review effort level: Balanced

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…orker kept A worker crash or a study error settles the run, but the host's trial evaluations kept a live signal and simulated on for outcomes no one would read. Every terminal event now aborts the segment's controller. A crash also took the studies kept for finished runs with it, so a later continuation started a fresh worker only to fail with study_failed; those runs now lose their resumable status and the continuation is refused with the reason.

cursor

Stale Bugbot comment from a previous run.

A host had no way to tell a stopped study the worker kept from a first segment cancelled before it reached the worker, so it offered Continue for studies that were never created and the extension was refused. Terminal events now carry `resumable`: true when the study stays in the worker, false when the run failed or its segment never started. A remote service omits it.

…behind an experimental setting

…rogress activity

…hart stay in view

The study seed masks a 32-bit crypto draw instead of reducing it modulo the range. Stop on a connected study whose run has no id yet aborts the creation so its run is cancelled where it was made. A point stopped early as unable to beat the best resumes its ladder once it is the best. The surface cell cache keys on the axes as well as the positions, so swapped axes never reuse each other's samples. Changesets are one per package, with one for the Vaccination Campaign example in petrinaut-core.

A cancelled terminal marked every connected study resumable while its local study object existed, so a first segment stopped before it reached the worker, as while the runtime loads or another study holds the worker, showed Continue and then had its extension refused. The record's resumable flag now follows the terminal event's, which the runtime sets from whether the study exists.

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The refinement restarts when a point's isBest changes, but nothing asked it to once the study had parked: a trial landing on the parked point and becoming the best left the point stopped at its early-stop note. The connected study now compares the best point's key before and after each trial event and, while the navigation is parked, refines the point again; settling does the same for a parked point instead of only settling a following study.

github-actions Bot added area/infra Relates to version control, CI, CD or IaC (area) area/libs Relates to first-party libraries/crates/packages (area) type/eng > frontend Owned by the @frontend team area/apps > hash.design Affects the `hash.design` design site (app) labels Sep 3, 2026

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Comment thread ...shintel/petrinaut/src/ui/views/Editor/panels/SimulateView/optimizations/optimization-seed.ts Fixed

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kube added 6 commits September 8, 2026 03:54

Add an in-browser optimization runtime to petrinaut-core

f28a5fc

Extend, release and parallelise browser optimization runs

b9b0e65

Record petrinaut-core's task dependency on the optimizer core library

f3c3652

State the continuation test as a sampler-history claim

eb3019d

Restructure the browser optimization runtime after review

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kube added 11 commits September 8, 2026 04:14

Run the connected optimizer's trials through the experiments backend …

718f262

…behind an experimental setting

Add Storybook stories that run the real in-browser optimizer

001bdab

Show only the optimizer's steps on the connected study's Surface

05abef3

Add the Vaccination campaign example for optimization demos

893c33c

Stop, continue and settle connected studies with parallel steps and p…

56ad3c4

…rogress activity

Lay out the connected study drawer so the Surface and the objective c…

f31c359

…hart stay in view

Seed each optimization study afresh from an editable Seed field

c9dbfcc

Consolidate the optimizations provider and drawer after review

6c9690b

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Comment thread libs/@hashintel/petrinaut/src/react/optimizations/provider/connected-study.ts

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FE-1583: Run the connected optimizer's trials through the experiments backend - #9516

FE-1583: Run the connected optimizer's trials through the experiments backend#9516
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Summary

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Changes

Feature flag

Experiments layer

Optimization channel and provider

Form and drawer

Stories and example

Review fixes

Known issues

Test coverage

How to test

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