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PaperClipAI/tests/runner-e2e/FIXTURES.md
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DottaandPaperclip b54b2dc35c fix: preserve warm Codex turns with incremental managed file checkpoints (#14735)
## Thinking Path

> - Paperclip manages AI agents and keeps their instructions and files
durable.
> - Native Codex runners can keep a process alive between compatible
turns.
> - Managed file collection stopped that process after each turn, which
defeated warm reuse.
> - Agent folders can contain large images and other files, so full
copies on every turn are expensive.
> - This change keeps one managed directory for the live session and
saves only file changes after each turn.
> - Ownership, authorization, instruction changes, and process
retirement still control when reuse is safe.

## Linked Issues or Issue Description

Related: #13710 introduced native warm session reuse. This fixes managed
file collection that still forced those sessions to stop. No duplicate
open PR or issue was found.

**What happened?**

With managed instructions and warm native Codex enabled, consecutive
turns reused a Daytona sandbox but started a new runner process each
time. The managed directory collector required process termination
before saving files.

**Expected behavior**

Compatible turns keep the same process and managed `AGENT_HOME`. Each
completed turn saves added, changed, and deleted files before the next
turn starts. Unchanged large files do not transfer again.

**Steps to reproduce**

1. Use a native Codex agent with managed instructions and a reusable
Daytona environment.
2. Enable warm session reuse and run three turns on the same task.
3. Write a large binary on the first turn, edit a small note on each
turn, and delete a file on the second turn.
4. Compare process identity across turns and read the canonical files
through the public agent-files API.

**Paperclip version or commit**

Reproduced on `d30b03bd8c17604cdab1533eeeeb087aba30e8b1`.

**Deployment mode**

Local server with remote Daytona execution; cloud native runner uses the
same path.

## What Changed

- Retain the managed directory only for the verified owner of a live
native Codex session.
- Checkpoint each completed turn before releasing the session for reuse.
Retry unstable captures, then stop and collect when a warm checkpoint
cannot be validated.
- Compare metadata and cached hashes, stream only changed file payloads,
record deletions, and validate path, content, quota, and authorization
before saving.
- Rotate sessions when canonical files, loaded instructions,
credentials, or launch policy change. Fence stale collection and cleanup
callbacks from later owners.
- Keep cleanup and recovery aware of the current session owner. Recheck
canonical files under the writer lock at handoff, attach the successor
collector before fallible bookkeeping, and emit one final save receipt
on checkpoint fallback. Preserve storage warnings across unchanged
checkpoints.
- Add regression coverage and a three-turn Daytona test with independent
public API file checks, an unchanged 8 MiB binary, deletion checks, and
strict process identity checks.
- Document checkpoint consistency, lifecycle behavior, and local run-log
counters.
- Replace a timing assumption in the Daytona teardown test with explicit
transfer-arrival gates after CI exposed an unset release callback.

## Verification

- Full local `pnpm -r typecheck` and `pnpm build` passed. Server checks
were repeated after the final storage-warning fix.
- Runner E2E typecheck and 749 runner E2E unit tests passed.
- Focused file checkpoint, directory ownership, instruction collection,
native session, and merge tests passed. After review fixes, the
managed-directory and native-session suites passed 550 tests, including
intervening canonical edits, same-run fresh restore, failed handoff
collection, and one-call fallback collection. Server typecheck passed
again. The Daytona plugin suite passed 218 tests. The quota-warning
regression failed before the fix and passed afterward.
- Three real Daytona campaigns passed before the final handoff review
fixes. The latest kept PID 547 across all three turns. The first
checkpoint copied 8,388,635 bytes; the next two copied 36 and 54 bytes.
Public API reads verified the binary, note contents, and deletion after
every turn. Test cleanup deleted the sandbox.
- The final head was also deployed to an isolated cloud staging instance
and passed three UI-triggered native Codex turns with managed
instructions. All three retained the same process ID/start time, native
session, provider session, runner instance, and Daytona sandbox.
Checkpoints copied 8,388,643 bytes on turn 1, then only 52 and 78 bytes
on turns 2 and 3; those warm captures also hashed only 52 and 78 bytes.
Independent canonical API reads verified every byte of the unchanged 8
MiB binary and the exact note contents after every turn; the deleted
file returned 404 after turns 2 and 3. After restoring the original
lifecycle and agent-auth configuration, removing the temporary secret,
pausing the test agent, and deleting both test sandboxes, independent
canonical API reads still verified the entire binary, the final 78-byte
three-line note, and the deletion. The native runner flag remained
enabled and the final serving revision remained the PR head.
- Two earlier staging attempts are preserved as failures and are
excluded from the acceptance result: a saved ChatGPT login failed with a
provider routing 401, and its subsequent stopped-sandbox retry failed
before provider startup with a closed-lease admission error. The
successful campaign used a fresh sandbox and a temporary encrypted
API-key binding. The stopped-lease retry remains unexplained; this
campaign does not establish recovery of that failed sandbox.
- All [Paperclip CI
gates](https://github.com/paperclipai/paperclip/actions/runs/36750397355)
pass on `26ef2ef56a389259246809805c0b34a4747eb86b`, including full test
partitions, build, typecheck, runner verification, E2E shards, and the
Canary clean public-npm install. Greptile reviewed that exact head at
5/5 with no unresolved review threads or outstanding findings.
- Full local repository coverage used the existing CI partitions, but
the 40,000-file Git streaming stress test timed out and its local retry
was interrupted by macOS thermal emergency sleep; this is not a green
full local suite claim. The exact stress test passed on the final head
in [CI server shard
2/12](https://github.com/paperclipai/paperclip/actions/runs/36750397355/job/110008294290),
in 111.9 seconds.
- Repeat the live test with configured credentials and a Linux runner
artifact: `pnpm test:e2e:runner -- --id
daytona-warm-continuity.runner-codex.daytona.warm-three-turn`.

## Risks

- This is a file-level checkpoint, not an atomic snapshot of the whole
folder. Background writes after a capture are saved by the next
checkpoint or final stopped collection.
- Metadata scans still visit all paths. Modified files transfer in full;
unchanged files do not rehash or transfer.
- Incorrect ownership or reuse could collect the wrong directory. Run
ownership fences, current authorization, stable capture validation, and
stopped collection fallbacks are covered by tests.
- Warm reuse remains opt-in. No database migration or fleet default
changes.

## Model Used

OpenAI GPT-6 through Codex, with reasoning, code editing, tool use, and
test execution. The exact serving model ID and context-window size are
not exposed by this session.

## Checklist

- [x] I have included a thinking path that traces from project context
to this change
- [x] I have specified the model used (with version and capability
details)
- [x] I have checked ROADMAP.md and confirmed this PR does not duplicate
planned core work
- [x] I have searched GitHub for duplicate or related PRs and linked
them above
- [x] I have either (a) linked existing issues with `Fixes: #` / `Closes
#` / `Refs #` OR (b) described the issue in-PR following the relevant
issue template
- [x] I have not referenced internal/instance-local Paperclip issues or
links (only public GitHub `#NNN` / `github.com/paperclipai/paperclip`
URLs)
- [x] My branch name describes the change (e.g. `docs/...`, `fix/...`)
and contains no internal Paperclip ticket id or instance-derived details
- [x] I have run tests locally and they pass
- [x] I have added or updated tests where applicable
- [x] I have updated relevant documentation to reflect my changes
- [x] I have considered and documented any risks above
- [x] All Paperclip CI gates are green
- [x] Greptile is 5/5 with no open P2s, recommendations, or follow-ups
- [x] I will address all Greptile and reviewer comments before
requesting merge

---------

Co-authored-by: Paperclip <noreply@paperclip.ing>
2026-09-30 13:33:37 -05:00

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16 KiB
Markdown

# Runner E2E fixture authoring
The fixture catalog is executable production-contract data. Keep it small,
typed, deterministic, and free of raw credentials.
## Suites and matrices
A `RunnerSuiteFixture` declares one durable testing purpose: stable ID, label,
description, profiles, environments, cases, expected size, and definition or
ranking metadata. Its execution IDs are globally prefixed as
`<suite>.<profile>.<environment>.<case>`. Add a new suite when the testing
purpose or desired cross-product differs; do not inflate an existing suite with
unrelated dimensions.
The suite definition fingerprint is historical comparison metadata. Any
profile, model qualification, environment, task, or ranking-snapshot change
must change that fingerprint automatically so the dashboard can annotate the
boundary instead of silently joining unlike totals.
## Agent profiles
Add `RunnerProfileFixture` entries in `catalog.ts`. A profile declares:
- a stable ID and searchable groups;
- legacy or native generation;
- adapter/provider and required credential;
- a model imported from its adapter constant or qualified runner profile;
- supported environment IDs;
- expected runtime metadata; and
- an agent payload factory.
Do not duplicate model IDs, qualification decisions, CLI versions, or runner
artifact rules. Codex profiles import `DEFAULT_CODEX_LOCAL_MODEL`, OpenCode
profiles import `QUALIFIED_OPENCODE_MODEL`, and ACPX profiles import
`QUALIFIED_ACPX_PROFILES`. Add or qualify models at their owning production
source first.
OpenRouter breadth profiles are generated from `openrouter-models.json`, not
written by hand. That reviewed snapshot must contain exactly five unique,
available, tool-capable models with rank, canonical ID, display name, supported
parameters, source URL, capture time, and verified content hash. Refresh it
manually with `pnpm test:e2e:runner:models:update`; nightly campaigns never
change fixture definitions.
Agent `adapterConfig.env` values must be `{type:"secret_ref", secretId,
version:"latest"}` objects supplied to the factory. A fixture source containing
a raw secret-looking value is rejected by catalog validation.
The manual Grok subscription profile uses `GROK_AUTH_JSON` as an explicit login
fixture. It does not put this credential in agent configuration or substitute an
API key. Setup seeds a new company-scoped Grok home inside the disposable instance
with mode 0700 and an exclusive mode-0600 auth file. Setup rejects redirected,
occupied, or nonisolated homes. Production runner discovery and refresh operate on
that company login; teardown destroys it after the remote environment is removed.
This fixture tests subscription execution, not the interactive browser login flow.
## Environments
An `EnvironmentFixture` declares driver/provider, credential requirements,
attempt deadline, lifecycle behavior, expected execution target, and a payload
factory validated by the shared environment schema.
The local environment is instance-managed: company creation ensures it exists,
and the public API intentionally rejects a second local environment. The setup
registry therefore discovers that row through the public environments API.
This still provides full isolation because every cell starts a new Paperclip
instance and database.
Daytona creates sandbox environments through the public API. The core fixture
keeps `reuseLease:false` and `runnerLifecycleMode:"per_turn"`. The dedicated
warm-continuity fixture uses `reuseLease:true` and
`runnerLifecycleMode:"warm"`; its distinct `configurationKey` is part of the
suite fingerprint even though both fixtures report `environmentId:"daytona"`.
Keep short provider cleanup backstops, a Daytona secret reference, and an
immutable image digest. Teardown
must delete the environment with reusable-lease destruction and must fail the
cell if cleanup cannot be confirmed. Keep CPU, memory, and disk explicit: lease
metadata and the per-test public-list-price runtime estimate depend on that
pinned billable resource shape. Changing it requires updating billing tests and
reviewing the versioned Daytona rates in `billing.ts`.
## Usage and billing data
Do not add fixture-authored token or dollar expectations. The live harness
reads usage from selected public heartbeat-run records and records coverage per
run. Provider-reported dollars remain distinct from runtime estimates. A zero
or missing native usage payload is `unavailable` unless a real token-bearing
receipt or provider cost proves otherwise. New execution environments must
provide lease/resource metadata for a runtime estimate or explicitly remain
`unavailable`; never infer that missing billing data means free execution.
Future providers (SSH, E2B, Modal, Cloudflare, Kubernetes, Novita, exe.dev)
should implement the same setup/probe/cleanup contract before being added to a
matrix. Unsupported profile/environment combinations belong in
`supportedEnvironments`, not in ad hoc test conditionals.
## Task cases and matchers
A `RunnerTaskFixture` owns a work mode, a typed flow, expected run count,
nonce-based title/prompt/marker factories, per-environment attempt deadlines,
deterministic matchers, and expected terminal state. Single-turn prompts should
make one bounded request with observable output and no nondeterministic judging.
The `plan_revision_acceptance` flow must also provide revision-request and Plan
marker factories. `question_resume_completion` must define the deterministic
browser answer and prove exactly two successful runs with no pending
interaction. `plan_approval_completion` must target the exact two-step
canonical Plan revision, capture its pending UI, approve in the browser, and
prove exactly two successful runs. `warm_three_turn` provides exactly two
browser follow-up messages, preserves one project/execution-workspace scope,
verifies host file contents after every turn, and finishes within three
ten-minute turn deadlines. The ordinary warm fixture uses managed instructions,
updates AGENT_HOME each turn, and verifies memory, an unchanged 8 MiB binary and
a deletion through public file APIs. Native turns 2 and 3 must copy/hash only the
changed memory file, with a saved receipt and the same provider PID. Journal and
Git stress fixtures retain fixed external bundles as controls. Keep the stable-PID
oracle strict; `instruction-persistence` also covers cold restarts and quota handling.
Native turns 1 and 2 include an actionable human review in the completion report's `attentionRequests`. Paperclip creates the review gate from that report. An explicit question-tool wait yields the turn and suppresses its final prose, so it is not interchangeable with this completion-review fixture. Turn 3 reports Done without another review.
Every selected case runs in its own isolated Paperclip process, and independent
cases may run concurrently. Follow-up turns inside one case retain their shared
task state. Each case creates and tears down its own company, secrets,
environment selection, agent, and browser-created task. The current plan case
proves three runs on the same issue: publish a two-step Plan,
request a three-step revision through the UI, and accept the exact new revision
through the UI before verifying implementation and Done.
The matcher union supports message exact/contains/regex/ordered checks, issue
and run state, runtime/environment metadata, files, artifacts, JSON paths, and
JSON Schema. The initial cases use normalized `message_contains` plus state,
runtime, and environment assertions; the plan flow additionally verifies
canonical document revision IDs, bodies, step counts, interaction targets, and
visible previews. Add matcher behavior and credential-free tests together.
Adding a task expands its suite's matrix. Update the suite's intentional size,
the complete-catalog size, and credential-free unit tests in the same change.
Paid tests never silently skip a missing credential or unsupported artifact.
## New Paperclip object fixtures
The explicit-only `lifecycle-baseline` suite reuses this registry and existing
continuation, chat and governed-action flows. Its narrative pairs require actual
agent/run-attributed comments or exact visible responses. See
[the live baseline contract](LIFECYCLE-BASELINE.md) for selectors and proof boundaries.
Register new objects in `live-fixtures.ts` with explicit dependencies in
`FixtureRegistry`. Setup must use a public API. Teardown runs in reverse order
and is invoked after partial setup failures. Direct database writes and private
test-only runner endpoints are prohibited.
The expected dependency shape is:
```text
company
└── encrypted secrets
└── environment
└── agent
└── browser-created task
```
Projects, goals, apps, and configuration fixtures can be inserted into that
graph without changing the launcher. Keep returned fixture state to IDs and
sanitized metadata; never retain raw secret values.
## Required checks
Run before a fixture change is reviewed:
```bash
pnpm test:e2e:runner:unit
pnpm test:e2e:runner:typecheck
pnpm test:e2e:runner -- --list
```
Then run the narrowest paid cell that exercises the fixture. A full matrix is a
manual or scheduled campaign, not a PR requirement.
## Persistent chat fixtures
`chat-cases.ts` defines the eight-case `agent-chat` suite; `chat-flow.ts` drives the
production composer, plan revision/approval controls, questions, reset command,
and project cards. Keep its 28 local cells intentional. `expectedRunCount`
counts provider turns, including cancelled and handed-off task runs, but excludes
synthetic `/new` runs. Assertions must inspect all company runs because ordinary
issue lists exclude the source conversation. `assertChatHandoff` rejects missing
projects/plans, chat children, wrong assignees, and execution before plan commit.
Retained `api-state.json`, `chat-handoff.json`, and plan-revision evidence
include persisted comments, session generations, run context and logs, project
workspaces, task documents, and ordering. They pass through the normal sanitizer.
Screenshots are allowlisted to the exact disposable agent chat. Cleanup cancels
all active runs in the isolated company, including handed-off work; usage from
failed and cancelled runs must not disappear from campaign totals.
Warm three-turn continuity grades the exact workspace file after each turn,
task completion, and sandbox/session identity. It also requires a visible
persisted final reply with each turn marker once and in order. It does not
grade exact final-reply wording; the hello
and continuation fixtures retain those exact-response checks. This separates
workspace persistence failures from model response-format variance.
`chat-hardening.ts` adds the explicit-only `agent-chat-hardening` journeys. Use
the ordinary public APIs to seed source documents and blockers. Keep the answer
out of the user's status/review request. Grade the exact source values, latest
blocker, preserved task identities, worker-authored output, and real executions.
The status request asks for JSON so the grader can distinguish the current
blocker from a historical mention and compare active-run count separately from
task status. The request must not reveal those expected values.
Capture the source after seeding and compare every field in the public issue
update contract, plus labels, dependencies, and dedicated-endpoint settings.
Derived inbound references may change when the chat legitimately cites a task.
The lost-acknowledgement probe may interrupt only the fixture browser's own
comment request after the real server has committed it. Retain its request ID
and replay that same request through the public API after restarting the server.
Never fabricate tool results or repair task state after a failed assertion.
`chat-stories.ts` seeds an ordinary file wait in the isolated agent's actual
home workspace; native Codex intentionally cannot see arbitrary host temp files.
The observed run workspace must match the fixture location. This is a deterministic interruption
boundary. The real provider command writes the readiness file and waits at most
two minutes. The harness must persist the next browser message while the same
run is active before supplying the brief. Always release the wait in `finally`.
Save boundary observations independently of the final outcome. The final answer
must recover a brief reference absent from both prompts; the revision oracle
also reads the actual conversation plan. Fixture setup never enables native API
tools for this suite. Do not describe its prepared-agent settings case as a
production onboarding qualification.
The `agent-chat-qualification` local fixtures use public APIs to seed two workers
and a task with a saved plan, or read-only tasks with contradictory historical
comments. Ordinary Node file waits in the isolated agent workspace establish
observable active execution; no provider output or database outcome is fabricated.
A worker-crash case sends SIGKILL only to a positively identified running native
worker PID, then uses the production Retry button. Each gate is released in a
finally block. Source facts and boundary state are retained with the attempt.
The lifecycle suite also includes two legacy disposition-repair probes. Their
first provider turn intentionally omits task disposition, and their second turn
must be an automatic, causally bound repair that records completion. They use
public task comments/status APIs and run-detail evidence; no private runtime
hooks or database mutations are used by the fixture.
The explicit-only `extended-harnesses` suite uses five bounded journeys for each
pending ACP candidate on local and Daytona. Candidate profile metadata includes
the exact authenticated discovery choice without promoting it to a product
default. Its file case anchors the task to a public project workspace, validates
the model's claimed result by reading the actual final bytes, and also exercises
remote copy-back. Keep candidate admission scoped to the selected model and the
isolated operator environment; ordinary agent configuration must not enable it.
## Persistent agent files
The `instruction_persistence` flow uses production managed storage and public file
APIs. The browser creates a supporting file, then a real agent edits its registered
AGENT_HOME with ordinary filesystem tools. Independent oracles verify instructions,
nested text, binary download bytes, and a stopped-run save receipt without new
revision history. The harness restarts the server and creates a fresh browser task
without disclosing the saved nonces. Its readback oracle downloads and verifies an
attachment's bytes and SHA-256, rather than accepting a filename or model claim.
A third task uploads a ready attachment and waits in an ordinary bounded shell
command while the board changes the current file through the public API. Stopped
cleanup must preserve the original candidate as a conflict. The browser reviews
current and incoming files and applies the run edits against the reviewed current
directory hash. All three tasks' runs count toward billing and teardown. The suite
is explicit-only. No private control-plane hooks or direct database writes are used.
## Direct blocker fixtures
`blocker-cases.ts`, `blocker-fixtures.ts`, `blocker-flow.ts`, and
`blocker-scoring.ts` define the explicit local legacy `blocker-guidance` suite.
Its fixture registry creates a manager through the public API and assigns the
production operational skill to worker and manager. Company-wide evidence and
cleanup include unexpected manager runs. The grader checks saved human input,
requester identity for scope questions, ownership history, no additional work or
hires, and the browser-answer continuation. See [Direct blocker guidance](README.md#direct-blocker-guidance)
for coverage boundaries and run commands.