ORIGIN.md pinned the intended checkout to an absolute path under a
personal home directory, docs/LOCAL-SETUP.md listed folders on one
developer's machine, and two tests used what looks like a real tailnet
address. Use a home-relative path, drop the machine-specific folder list,
and use 100.100.100.100 in the tests; it is still inside 100.64.0.0/10,
so both tests check the same thing as before.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
packages/db carried four hand-run scripts outside the package build that
query or seed a developer database with a hard-coded connection string,
one of them for a specific account. docs/VOICE-FIRST-REVIEW.md was a
one-time verification note for a workflow that no longer exists and
named private machines and local paths. Nothing references them.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
The repository still carried the pre-evOo prototype: a Python orchestrator,
the old HTML "evoo-platform" cockpit (whose test ran in the root unit
suite), an apex-trading package, the hot-reload deploy.sh for it, a
permissions manifest, an architecture note with local file links, agent
handoff notes, a Steve Jobs persona template and about ninety one-off
scripts that probe a developer database with hard-coded local URLs. None
of it is used by the product, CI or the real deploy in ops/evo-deploy.
Delete those files, drop the evoo-platform test glob from the root vitest
config, the Cockpit section from .env.example and the dead biome and
gitignore entries, and update the docs that listed the removed tools.
scripts/start-tmux.sh no longer starts the removed sentinel and resolves
the checkout from its own location instead of a machine-specific path;
scripts/seed-ollama.ts requires DATABASE_URL instead of falling back to a
local URL with a username.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
The live screen opens wide beside the chat while the bot works on it or asks
for a takeover, a file the bot presents as its result opens next to the
conversation, and a question that scrolled away gets a "Needs you" pill back
to it. Shared core rules derive the focus from signals clients already have
(pointer events, takeover requests, a new `present` flag on attach_file,
pending asks), move the pane only on focus edges, never replace a pane the
user opened, and learn per bot whether the screen opens on its own. Pane
widths persist per device; mobile shows a pill that opens the computer.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01C7VSRHHzyt2KwoCkUkZ2Gc
* feat(db): main agent, main conversation, user model and delegated task foundation
The product needs one main agent that leads a main conversation, knows the
user across spaces, and hands work to visible specialists. Today none of
that exists in the data model: "Chief" is a client-side naming convention,
the "Hauptthread" is a group the web client creates by name, and nothing
stores what the agents know about the user.
This adds the shared foundation the Phase 1 features build on:
- Bot.kind ("main" | "specialist", one main bot per user) plus capability
fields (tags, builtin tool allowlist, model tier).
- ChatGroup.kind ("group" | "main", one main conversation per user) and
ChatGroup.leadBotId.
- UserProfile and UserFact with category, confidence, source, consent
status and per-space visibility; embeddings are stored as float arrays
because none of the Postgres images ship pgvector.
- DelegatedTask for work the main bot hands to a specialist.
- SpaceModelTier to map a model tier to a connected model per space.
The migration backfills each user's onboarding bot in the home space as the
main bot and turns an existing "Hauptthread" group containing it into the
main conversation. CHECK and foreign key constraints on existing tables are
added NOT VALID and validated in a separate migration, as elsewhere in this
repo.
New db helpers ensure the main bot and the main conversation (idempotent and
race-safe, repairing a lost lead), add same-space specialists to the main
conversation and announce it with a group.updated event, and load the user
context a run may see. The main conversation is exempt from the two-member
floor and cannot have its members replaced through a group update. The
contracts expose the new fields and the user model and delegated task
schemas.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* feat(adapters): every run knows who it is and who the user is, in the user's time zone
Runs dropped the bot's name, title and description whenever custom
instructions existed, always stated the time in UTC, and knew the user only
through free-form durable memory. Groups with a lead, like the main
conversation, still got the peer-group lines that forbid handing work back.
And every group follow-up run failed during setup: the inbound handoff lookup
selected a `bot` relation that Message does not have, which Prisma rejects.
- Instructions now open with the bot's identity, then its own instructions,
a main-agent role paragraph for the main bot, the current time in the
user's time zone with its offset (UTC when unknown), and a `<user>` block
built from loadUserContext: profile fields and the active facts visible in
the run's space, escaped, clipped and framed as data rather than
instructions. Runs that reply in a shared messaging channel get only the
name, zone, locale, language and style, matching how those runs already
leave out durable memory.
- run_subagent helpers receive the identity, time and user block through a
new optional AgentRunRequest.subagentContext instead of nothing.
- Groups with an active lead get lead and specialist lines and matching
inbound handoff instructions. Members may hand a stage back to the lead and
the lead may delegate the next stage; the bounce rules still apply between
members. Ordinary groups keep today's lines.
- The teammate directory is rendered only when the run has message_bot, which
group runs never have, and tool guidance names a tool only when the run has
it.
- The auto-review judge, history compaction and the team chat judge read the
time in the user's zone, and schedule_create defaults to it.
- The inbound handoff sender is read from the handoff block and looked up
among the user's bots; a Postgres test covers the follow-up run, the prompt
it receives, and handing the result back to the lead.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* feat(memory): learn the user profile from conversations; add built-in semantic memory
Why: the user profile only knew what onboarding wrote, so people had to repeat themselves,
and semantic recall needed a hosted or separately run memory service. The profile now grows
from everyday conversations, and recall can run on the user's own server with a local
embeddings endpoint (for example llama.cpp). Both stay optional and are tested offline.
What:
- adapter-kit: EmbeddingProvider contract (describe, embed) and the profile.consolidate job
(payload schema and a replace-keyed job factory, one pending job per user).
- adapters: OpenAI-compatible embeddings (POST {baseUrl}/embeddings through the guarded
OpenAI-compatible fetch, batching, bounded responses, clear errors), a deterministic
emulator, an in-process /v1/embeddings server emulator, and a shared conformance suite.
- adapters: "builtin" semantic memory stored in Postgres (semantic_memory_items with Float[]
embeddings, cosine ranking in process, bot/shared/history scopes matching the existing
providers), registered in the memory provider factory and configured through
memory.connectProvider with an embeddings URL, model and optional API key. Private
endpoints require the deployment owner, like the other local memory providers.
- adapters: profile consolidation reads the user's settled app conversations since
UserProfile.consolidatedAt (never messaging channels), asks the main bot's model for strict
JSON facts and an updated summary, drops restatements (embedding cosine when built-in
memory is configured, normalized text otherwise), stores sensitive categories as pending,
and advances the cursor with a compare-and-set. A reconciler hook enqueues it at most daily
per active user; it skips under the scripted runtime and without a usable model.
- db: additive migration 20261002210400_ws4_semantic_memory.
- web: a "Built-in" option in Memory settings; AI data sharing names the embeddings server.
Tests: new embedding conformance, OpenAI-compatible wire, built-in provider and consolidation
unit tests; new Postgres suites for built-in memory (including a real loopback embeddings
server through the memory provider resolver) and for consolidation and its scheduling query,
both added to the integration harness. The settings E2E spec now opens the new form.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* feat(models): map model tiers per space and let bots and helpers ask for one
A space can now map the tiers fast, standard and code to connected models,
including several models served by one OpenAI-compatible router endpoint
(one credential, many model ids). A bot can ask for a tier, and a single
run_subagent call can ask for one. A tier with no model mapped falls back
to the usual model choice, so nothing breaks before tiers are set up.
- db: SpaceModelTier repo (list, find, set or clear); tier mappings are
copied into a new space like model and voice preferences; createBot
carries a tier, so duplicates keep it and spawned bots inherit it.
- contracts/api: models.tiers.list and models.tiers.set;
models.probeOpenAiCompatible can list a connected server's models by
credential id with its stored address and key; bots.update accepts
modelTier and keeps a pinned model and a tier mutually exclusive, so a
model picked on a surface that knows no tiers (mobile) is never silently
overridden. Thinking-level validation follows the tier's model. AI
consent status discloses tier models; desktop local settings allow the
tier procedures.
- adapters: selectConfiguredModel runs a mapped tier ahead of the pinned
model and the space default; the executor resolves bot tiers for runs
and model lookups, and helper tiers through resolveModelTier.
run_subagent takes model_tier; an explicit model wins over it.
- web: a collapsed Tiers section in model settings (shown once a model is
connected) and mapped tiers as choices in the bot Model select.
- docs: tiers in self-host model setup.
- tests: resolution order and fallbacks (selection, executor, Pi helper),
repo, API and contract units, authorization and offline Pi Postgres
suites, and a model-tiers web E2E spec.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* fix(adapters): state the consolidation time in the user's zone; name the memory migration after its content
Profile consolidation now passes the profile's time zone to the shared time
instruction, which takes the zone since every run states the time in the
user's zone. The semantic memory migration is renamed after what it creates.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* fix(adapters): keep the user's summary and facts out of replies to other owners' agents
An agent connection wakes a bot with another owner's message, and the reply
goes back to that owner. Such runs now get only the basics of the user block
(name, time zone, locale, language, style), like runs in shared messaging
channels, so confirmed facts such as health never reach another person's
agent.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* feat(profile): readable, writable and forgettable user model
The main agent is meant to know the user, but nothing could read or change
the user model the foundation added. Onboarding pasted the user's answers
into the first bot's instructions as a "User Context" block, and the user
had no way to see or remove what their bots knew about them.
This makes the user model a user-controlled resource:
- db: a profile repository scoped by user. One atomic update writes the
account name, profile fields, new facts (deduplicated by normalized
text, capped per user), fact edits including per-space visibility, and
confirmations. Health and values facts wait for confirmation unless the
user wrote them. Forgetting hard-deletes facts by id, category or all,
clears the summary that may restate them and marks earlier chats as
consolidated so they cannot teach them again; forgetting everything also
clears the profile fields. Writes take a per-user advisory lock.
- api/contracts: profile.get, profile.update and profile.forget. Unknown
fact ids are a 404 on update and ignored on forget; spaces outside the
user's memberships are rejected.
- adapters: an update_user_profile tool for the main bot only, hidden from
specialists and shared messaging channels and refused if called anyway.
Facts carry source "conversation" and the bot, thread and message they
came from. The scripted runtime records "learn about me: [category:]
statement" for tests.
- web: onboarding writes the name, time zone (browser default, now
prefilled and editable), locale, chosen language, communication style
and the hobby and work-style answers to the profile instead of
overwriting the bot's instructions, and the harvested memory section no
longer repeats them. A new "About you" settings section lists profile
fields and facts by category with their origin, confirms pending facts,
and forgets one fact or everything.
Tests cover the contracts, the repository (unit and PostgreSQL), tool
selection and refusal, the scripted trigger, the onboarding mapping and
view helpers, an API suite that runs the tool through the executor with a
real main bot, authorization for the new procedures, and an E2E spec.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* feat(delegation): main bot hands work to specialists as tracked tasks
The main agent had no way to give a specialist a piece of work and keep
track of it. message_bot is a fire-and-forget peer message whose work stays
hidden from the user, and handoff_to_bot ends the main bot's turn and only
works between members of one group. Delegation now runs the specialist's
work where the user follows the main agent and brings the result back so
the main agent can close the task.
- delegate_task({bot, title, brief, deadline?}) is offered to the main bot
only and refused unless the caller leads the main conversation. It
resolves the specialist by id or name across the user's spaces, creates a
DelegatedTask and posts a task card in the main conversation.
- A specialist from the main conversation's space joins it and works there
in a run with the new trigger "delegation", which the peer filters do not
hide, so its progress, asks and approvals appear in the main conversation
with the specialist as sender. A specialist from another space works in
its own chat; its written result is posted into the main conversation as
its message.
- The executor mirrors the run on its task (running, waiting, done, failed,
cancelled) after the run starts and when each attempt ends, and updates
the card in place through thread.message.updated. Done and failed tasks
wake the main bot in the main conversation with the result. The job
reconciler settles tasks whose run ended without the executor (stop,
clear, archive, deletion, crash).
- tasks.list({threadId?, status?}) returns the caller's tasks for the
current space.
- The task card shows who, what and status with Lingui labels; the brief
opens on demand. The message_bot card no longer shows the recipient's
unrelated overall status or hard-coded German copy.
- The scripted runtime understands "delegate to the bot named X: ..." and
the task wake prompt; activity rows name delegation runs by task title.
Tests: unit tests for the prompts, status mapping, card, reducer, tool
selection and scripted runtime; a Postgres suite for same-space, group,
other-space, ask and answer, failure, stop and replay; tasks.list in the
authorization suite; and an end-to-end spec for the whole flow.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* fix(adapters): show the main agent the specialists it can delegate to
The main conversation is a group run, and group runs no longer list the
teammate directory, so the main agent could not see the names of the
specialists delegate_task expects. Runs that have delegate_task now list
the user's specialists across the spaces they belong to, those next to the
conversation first and others marked with their space, and that list
replaces the teammate directory so no bot appears twice. It also says when
to prefer delegate_task over handoff_to_bot.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* feat(inbox): show what specialists need from the user in the main conversation
Specialists ask questions, request approvals and the computer screen in
their own threads, and the user only finds out by opening each thread. With
the main conversation as the single entry point, those requests have to
reach the user there, with the specialist as the visible sender.
- inbox.list returns, for the current space and the user's own bots, pending
asks and approvals (bot messages with a pending ask block whose run waits
for input), takeover requests, and unread specialist threads. Asks already
in the main conversation are left out; takeovers stay because their
controls live in the bot's own thread. Each item carries the bot, the
thread target, run and message ids, and the ask block for asks and
approvals.
- The main conversation shows the items above the composer. Asks and
approvals are answered in place through threads.answer with the source
thread target; takeovers and unread threads open the bot's thread. The
list refreshes when the bots' status, unread state or newest message
changes, every 15 seconds, and after an answer.
- The inbox shrinks and scrolls so it never pushes the composer out of view.
The transcript now clips its scroller: with no room left in the column,
the scroller's padding used to spill over whatever sat below it.
- The ask block schema is extracted from MessageBlock so the inbox contract
reuses it, and AskCard accepts a className.
Tests: unit tests for the item builder and the component, a Postgres suite
for the query (added to the harness list), inbox cases in the authorization
suite, and an E2E spec in which a specialist asks in its own thread and the
user answers from the main conversation.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* fix(adapters): write learned facts under the profile's lock and limit
Profile consolidation wrote facts beside the user profile repository: without
its per-user lock, its duplicate check at write time, or its limit of 500
facts. A long-running profile could grow past the limit and then refuse the
user's own additions. Consolidation now takes the same lock, drops facts the
profile gained since the run read it, and keeps only what still fits.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* fix(adapters): keep profile writes out of replies to other owners' agents
A run woken over an agent connection hears another owner's bot, not the
user, so update_user_profile is withheld there: nothing such a conversation
says can become a fact about the user. Detection moves ahead of tool
selection; the reduced user block uses the same flag.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* feat(capabilities): least-privilege builtin tools per bot and schedules on behalf
Every bot saw every builtin tool, and nothing outside the runtime's own
declaration kept a run to the tools it was given: the executor ran any tool a
runtime asked for, and the Pi runtime exposed all builtins whenever a caller
passed an empty tool list, which the safety checker, the history summarizer
and the team chat judge do on purpose. A specialist could not be kept to the
tools of its lane, bots had no capability tags, and the main bot could only
schedule routines for itself.
- A bot can carry a builtin tool allowlist. Its runs see only the allowlisted
builtins, and an empty allowlist means none. MAIN_ONLY_BUILTIN_TOOLS (empty
until the user profile and delegation tools land) never reach other bots.
applyTool refuses any tool the run did not expose, and an empty tool list
now means no tools for the Pi runtime and its subagents.
- A bot spawned by a restricted bot inherits the restriction and a duplicate
keeps it, so neither path widens a bot's tools.
- bots.create and bots.update accept tags, restrictBuiltinTools and
allowedBuiltinTools; the router rejects names that are not builtin tools.
bots.builtinTools lists the names a bot's allowlist can use.
- Bot settings get a Tags field and a switch with a tool checklist under
Advanced.
- The main bot's schedule_create takes an optional bot: one of the user's
bots in any space the user still belongs to. The routine belongs to that
bot in its space and wakes in the main conversation when the bot is a
member there, otherwise in its 1:1 thread. Routines record the bot that
scheduled them (additive migration), so schedule_list and schedule_cancel
also cover exactly the routines a bot scheduled for others. Cancelling by
a name that matches several routines is refused.
Tested with unit tests for the per-bot filter, the applyTool guard, the empty
tool list, and on-behalf resolution, creation, listing and cancelling; with
Postgres journeys for on-behalf routines waking across spaces and in the main
conversation and for allowlist enforcement through the scripted runtime; and
with a web E2E for the settings section.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* test(adapters): give the consolidation unit tests the profile lock
The write transaction now takes the per-user profile lock, so the mocked
client answers the lock query, and the first case checks the lock is taken.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* feat(adapters): run profile consolidation on the fast tier when one is mapped
Fact extraction is short structured work, so consolidation asks the model
resolver for the fast tier. The resolver takes a per-call tier and, when the
space has not mapped it, keeps the bot's own tier or model as before.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* feat: land in the main conversation, led by the main bot
After onboarding the user ended up in a 1:1 chat with "Chief", and the
"Hauptthread" was a group the web client created and found by name. The
main bot had no conversation it actually led, and addressing another bot
there did nothing unless the user had added it as a member first.
Now the main conversation is a real place:
- bots.ensureMain creates or returns the main bot. Bootstrap and space
navigation return `main` ({ botId, groupId, spaceId }) once the main
bot exists; reading navigation never creates a bot.
- The main bot leads the main conversation and answers when nobody is
addressed: message routing, follow-ups, reactions and clearing the
thread fall back to the group's lead instead of its first member.
- Addressing a same-space bot that is not a member yet, by @Name or a
mention chip, makes it join before the message is routed, so it
answers in the conversation. Specialists from other spaces do not join.
- The main bot cannot be archived or deleted, the main conversation
cannot be archived or deleted or have its members edited, and child
bots never dissolve it. Renaming the main bot renames the conversation.
- Web: onboarding uses bots.ensureMain and finishes in the main
conversation. The main conversation is the first sidebar entry in every
space, shown with the main bot's avatar and name; from another space it
switches back to the home space. The main bot is not listed again among
the bots, its 1:1 thread stays reachable by URL. The client no longer
creates or detects the "Hauptthread" by name, refetches a group when it
changes, and shows the speaker of any of the user's bots in a group.
- Onboarding no longer resets the step when its bootstrap resolves after
the user has already moved on, and new spaces open in the app instead
of walking onboarding again.
Tests: group mention routing with a default responder, lead follow-ups,
child-bot guards, a journey for the main conversation (lead answers,
addressed bot joins, guards, rename), authorization for bots.ensureMain,
and an E2E spec that lands in the main conversation, gets an answer from
the lead, sees an addressed bot join, and reaches the conversation from
another space. Existing E2E specs start in the main bot's thread through
a helper or use the main conversation where that is what they test.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
---------
Co-authored-by: cynarAI <cynarAI@users.noreply.github.com>
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com>
* ci: publish amd64 images under a lowercase name and deploy only after green CI
Image publishing never succeeded: GHCR rejects the capitalized repository
slug, and the arm64 jobs failed on the macOS runners, which have no Docker
buildx. Resolve the namespace in lowercase and build amd64 only until an
arm64 runner with buildx exists; the manifest check expects one digest.
The Evo deploy ran on every push to main regardless of the result of
Product CI, so red commits went live. Trigger it from the completed ci
workflow instead and deploy the head it verified; manual dispatch stays.
The Playwright report publish failed every nightly run because the S3
settings are not configured. The script now skips the gallery with a
notice when they are missing instead of failing the job.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* ci: give each runner on a shared host its own E2E ports
Two Linux runners live on the same host. Every Web E2E job first frees
"stale" listeners on the fixed ports 3110, 3111, 5180 and 4321 with
fuser -k, so a job starting on the second runner killed the Vite server
of the job already running on the first one. The victim died with
SIGKILL (exit 137), and its remaining tests failed on reloads that could
no longer reach a server. This is what made the Web E2E run on this PR
red, and it explains the recurring reload failures on main whenever two
runs overlapped.
The workflow now derives API_PORT, WEB_PORT and WWW_PORT from the runner
name (suffix -N means an offset of N times 100), and the port-freeing
script follows those settings instead of a hard-coded list. The harness,
Vite, the API and the marketing site already read these variables.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* test(testkit): cover the env-driven E2E ports instead of a fixed list
The ports test parsed a hard-coded array that no longer exists. It now
runs the script on a fake host whose fuser finds nothing, and checks the
default ports, the per-runner override, the rejection of a non-numeric
setting, and that the workflow picks the ports before freeing them.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* test(updater): expect the amd64-only publish and the lowercase namespace
The workflow test still described the multi-arch publish. It now checks
that only amd64 builds natively, that arm64 is documented as paused, that
one digest feeds the manifest, and that every image name comes from the
lowercase namespace step.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* ci: keep every runner off the default E2E ports
Branches that still free the fixed ports 3110, 3111, 5180 and 4321 keep
running on the shared host (main, the nightly run, other open PRs) until
they carry the per-runner ports. A job of ours on the runner without a
numeric suffix used exactly those defaults, so such a neighbour could
still kill it, and its own port freeing could kill the neighbour. The
unsuffixed runner now starts at offset 100, so no job from this workflow
touches the defaults in either direction.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
* fix(web): recover lazy routes and overlays from a failed module fetch
When the browser aborts a module request while a page loads, the lazy
import rejects and the route throws, leaving a blank page. Chromium does
this whenever a network interface appears or disappears mid-request
(net::ERR_NETWORK_CHANGED), which happens on a laptop that changes
networks and on the CI host every time a container starts or stops. A
Web E2E run hit exactly this: two modules of the onboarding page failed
to load and the suite waited on an empty document.
Lazy routes and overlays now load through a helper that retries the
import once and, when the browser keeps rejecting it from its module
map, reloads the page a single time before surfacing the error.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
(cherry picked from commit d5dacb12f14380071ef14ba8845d18c9d39e3fac)
* fix(web): reload once when the module graph is aborted while booting
The lazy-route recovery cannot help when the browser aborts a module of
the static import graph: nothing of the app runs, the root stays empty,
and the only trace is a console error. A Web E2E run hit this right
after a page reload, when four modules of the shell failed with
net::ERR_NETWORK_CHANGED and the shell never rendered.
An inline script in the HTML entry now listens for the error event of
the module script and reloads the page once, guarded by a session flag
that the entry module clears after a successful boot. The existing
preload recovery stays in place; it only covers Vite's chunk preloads of
production builds.
A new E2E spec aborts one module request during boot and one lazy route
request, and expects the sign-in page to render in both cases.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MRtGG9ARfqqhma3t85Ro2u
(cherry picked from commit e5b7e036e1a60e7e270592c4b9382ee23ed45ccb)
---------
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: cynarAI <cynarAI@users.noreply.github.com>
Claude
