fix(server): constrain bundle image installs to uv.lock

[YeonwooSung]

Bundle images currently resolve ranged dependencies when installing /app/bundle-libs, so a later package release can change what the same source commit serves. This change constrains compatible dependency branches to uv.lock and retains the installed inventory in /app/bundle-libs-freeze.txt.

The CPU, CUDA 12 and CUDA 13 installers use the generated constraints. Constraint lines contain package names and versions without extras; the dependency walk still follows requested extras. Public and CUDA-specific Torch records keep their own dependency edges. Packages with multiple public versions are skipped, and their combined outgoing edges cannot establish trusted pins; independent trusted paths are retained, while incompatible override paths still remove shared pins. Exact pins, direct URLs and ranges outside the root lock retain their declared overrides, and dependency branches belonging to those overrides remain unconstrained when their root-lock versions are incompatible.

Rebuilt default images can therefore install older versions than an unconstrained build. Current constrained examples are gliner 0.2.26, gliclass 0.1.17, FlagEmbedding 1.4.0, open-clip-torch 2.32.0, huggingface-hub 0.36.2 and requests 2.33.1. Sentence Transformers retains the exact 5.7.0 pin from merged #803. Its regression checks now distinguish an exact pin that matches the lock from the Transformers 5 range that deliberately excludes it.

CI / Bundle resolution is a required lane that reaches package indexes for every PR and resolves all 11 release-matrix targets. Default pytest skips those network cases; explicitly enabling them without an available installer fails. Maintainers confirmed that this lane remains required.

Validation: 24 constraint tests pass, including six regressions that failed before the ambiguous-node correction; independent review adds 19 graph controls and confirms all 22 current bundle CPU/CUDA outputs are unchanged. Full public lint and scoped dependency-parser typecheck pass. The integration refresh also passed 56 Docker-contract tests and the missing-installer control; the 11 network cases are left to required CI. Fresh full CI and CodeRabbit review run on the updated head.

This constrains compatible branches; it does not yet lock every override's complete dependency closure. Dependent #802 adds saved per-target closures and installed-inventory verification. Krisztian approved the current head on 2026-10-19; all 41 check and status contexts pass, including required bundle resolution.

Refs #377

Summary by CodeRabbit

• Dependency Management
  • Bundle installations now follow compatible versions from the project lockfile for ranged dependencies, including eligible transitive dependencies. Exact pins and URL-based requirements remain unchanged.
  • Bundle images include an inventory of the installed bundle libraries.
• Quality Checks
  • Added automated checks that validate dependency resolution across supported bundle images.

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• .github/workflows/ci.yml
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• packages/sie_server/src/sie_server/bundle_requirements.py
• packages/sie_server/src/sie_server/cli.py
• packages/sie_server/tests/core/test_bundle_image_resolution.py
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• tools/ci/required_ci.py
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📝 Walkthrough

The resolver parses uv.lock to generate constraints for bundle requirements and eligible transitive dependencies. CPU, CUDA 12, and CUDA 13 Docker builds apply the constraints and copy a freeze inventory of bundle libraries into the runtime image. Required CI now includes bundle image-resolution checks.

Changes: Bundle Dependency Locking

Layer / File(s)	Summary
Parse lock data and generate constraints packages/sie_server/src/sie_server/bundle_requirements.py, packages/sie_server/tests/core/test_bundle_requirements.py	New helpers parse lock versions and dependency edges, merge compatible lock versions into ranged requirements, and generate constraints for eligible dependency closures. Tests cover extras, overrides, incompatible ranges, ambiguous versions, and transitive dependencies.
Expose lock constraints through the CLI packages/sie_server/src/sie_server/cli.py	resolve-deps accepts paired --lock and --constraints-output options. It rejects invalid option combinations and writes constraints generated from bundle requirements and the lock file.
Apply constraints and record bundle packages packages/sie_server/Dockerfile.cpu, packages/sie_server/Dockerfile.cuda12, packages/sie_server/Dockerfile.cuda13, tools/ci/tests/test_docker_task.py	Docker builds pass the lock file to dependency resolution, apply generated constraints during installation, and copy a freeze inventory into the runtime image. The Docker test checks the relevant commands.
Resolve bundle dependencies in required CI packages/sie_server/tests/core/test_bundle_image_resolution.py, .github/workflows/ci.yml, tools/ci/required_ci.py	The image-resolution test checks release-matrix bundle targets with Docker-matched resolver arguments. The required CI job runs the test.

Sequence Diagram(s)

sequenceDiagram
  participant DockerBuild
  participant ResolveDeps
  participant BundleRequirements
  participant Pip
  DockerBuild->>ResolveDeps: Pass uv.lock and constraints output path
  ResolveDeps->>BundleRequirements: Parse lock and generate constraints
  BundleRequirements-->>ResolveDeps: Return generated constraints
  ResolveDeps-->>DockerBuild: Write requirements and constraints
  DockerBuild->>Pip: Install bundle requirements with constraints

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Suggested reviewers: krisztian-gajdar, fm1320

Priority: ➖ Normal

Merge Risk: ⚪ Minimal · up to 50991

No actionable merge-blocking risk remains; the bundle-resolution CI job still needs to pass as part of normal merge checks.

Security architecture risk: 🔵 Low · up to 50991

The change narrows dependency drift without establishing a new privilege escalation or application trust-boundary bypass. Risk remains around changed package selections and network-backed resolution: version constraints do not authenticate package contents, and source-build behavior and runner isolation were not fully established.

Retained concerns
No architecture-level concerns identified.

Security review details

Security Blast Radius

• inferred — The selection-policy change reaches the 11 release-matrix image targets. Selected bundle packages become runtime code, and the existing CUDA bundle-path mechanism lets them shadow shared-environment packages. Exposure therefore follows each affected image and its consumers, rather than a new tenant-specific authorization path.

Trust Boundaries and Controls

• observed — The new CI lane runs on pull requests with contents-read permission, disables persisted checkout credentials, and declares no explicit secrets. Resolver configuration is made explicit through --no-config and removal of inherited package-index, constraint, and override variables.
• observed — The resolver uses --dry-run and a temporary target, but does not explicitly prohibit source builds. A release bundle includes a commit-pinned VCS dependency that predates this PR. These facts establish neither zero build-metadata execution nor access to sensitive runner credentials.

Resilience and Maintainability Implications

• inferred — Within the inspected Docker flow, unsuccessful constraint generation, installation, or inventory generation prevents successful completion of the builder stage. Empty requirement sets still create the bundle directory. This contains partial outputs within an unsuccessful build; it does not establish atomic publication for arbitrary concurrent CLI callers.

Hardening Proposals

• proposed — If resolution-only execution is a required security guarantee, verify the installer's source-metadata behavior and use compatible build restrictions or an explicitly isolated, secret-free runner. Do not treat --dry-run alone as that guarantee.

Pre-merge checks: 4 · 1

Failed checks: 1 warning

Check name	Status	Explanation	Resolution
Docstring Coverage		Docstring coverage is 23.08% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 52 functions across 6 files. (4 skipped: …	Write docstrings for the functions missing them to satisfy the coverage threshold.

Passed checks: 4 passed

Check name	Status	Explanation
Linked Issues check		Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check		Check skipped because no linked issues were found for this pull request.
Description Check		Check skipped - CodeRabbit’s high-level summary is enabled.
Title check		The title clearly and concisely describes the main change: constraining bundle image installs to versions from uv.lock. It matches the CPU, CUDA 12, and CUDA 13 Dockerfile updates.

Full details: Docstring Coverage

Explanation

Docstring coverage is 23.08% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 52 functions across 6 files. (4 skipped: 4 unsupported.)

Resolution

Write docstrings for the functions missing them to satisfy the coverage threshold.

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[krisztian-gajdar]

pin bundle image installs to uv.lock: the supply chain looks clean, but it’s incomplete.

• Only direct dependencies are constrained, so onnxruntime, docling-core and other indirect ones still float.
• Extras are written into constraint lines, which pip rejects. No bundle uses extras yet, so this is latent.
• Lock parsing would break every image build if any package ever gets two versions in the lock.
• It silently downgrades default images, for example sentence-transformers 5.7.0 to 5.4.1 and gliner 0.2.29 to 0.2.26, and should say so.

[YeonwooSung]

Constraints now follow the locked transitive closure of each bundle's direct dependencies, read from the uv.lock package tables (including extras those edges request, such as docling-slim[standard]). For the default bundle that pins onnxruntime==1.25.0 and docling-core==2.79.0, along with the other locked neighbors of the ranged direct deps. Packages outside that closure stay unconstrained, so this is not a blind pin of the whole lock. Exact overrides still win: transformers5 keeps gliner2==2.0.0 and torchvision==0.24.1 out of the constraints file, and a range that does not contain the locked version is not turned into a pin. Transformers >=5.14 therefore does not inherit the 4.x lock's huggingface-hub==0.36.2 or safetensors==0.7.0, which would be unsatisfiable. Lock neighbors of an exact override are still pinned when that rejected graph does not also reach them (peft stays pinned for gliner2==2.0.0).

Constraint lines are name==version only. Extras and environment markers are omitted, because pip rejects extras in a constraints file. A requirement such as demo[extra]>=1,<2 emits demo==1.2.3, and the extra is used only to decide which optional lock dependencies to walk.

Two public versions of one package no longer abort resolve-deps. The package is left unconstrained and the constraints file records # <name> skipped: uv.lock has multiple public versions. The torch 2.9.1 and 2.9.1+cu129 pair still collapses to one public version, so the constraint remains torch==2.9.1.*.

The constraints file now starts with a comment that ranged dependencies are pinned to uv.lock and that this can install an older release than an unconstrained build of the same commit. When those packages are actually pinned, the header names them; the default bundle pins sentence-transformers==5.4.1 and gliner==0.2.26, both older than an unconstrained resolve of the same ranges. The three Dockerfiles already cat /tmp/bundle-constraints.txt during the image build, so that header is printed there. No Dockerfile invocation change.

PYTHONPATH="$PWD/packages/sie_server/src" /Users/yeonwoosung/Desktop/sie/.venv/bin/python -m pytest packages/sie_server/tests/core/test_bundle_requirements.py -q

12 passed in 0.17s. ruff check and ruff format are clean on the changed Python files.

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[krisztian-gajdar]

Thanks for the quick turnaround. The extras, split-lock and transitive-closure changes look right now. I approved the CI runs, so the image builds will exercise this for real, but reading the closure walk I expect two builds to fail to resolve:

1. cuda12 default and transformers5. Dockerfile.cuda12 installs non-SGLang bundles from PyPI only, and --target resolves torch again instead of reusing the venv. torch==2.9.1 on PyPI requires nvidia-cublas-cu12==12.8.4.1. The lock parser merges the edges of both torch entries (bundle_requirements.py:141), so the constraints pin the cu129 neighbour nvidia-cublas-cu12==12.9.1.4, along with the other nvidia libraries. pip cannot satisfy both.
2. cuda13 tensorrt-llm. The bundle pins torch==2.11.0 and transformers==5.5.4, which differ from the lock (2.9.1 and 4.57.6). _root_kind classifies both as exact overrides, so the lock edges of versions the bundle never installs are still pinned. That gives huggingface-hub==0.36.2 (transformers 5.5.4 requires >=1.5.0,<2.0) and setuptools==83.0.0 (torch 2.11.0 requires <82). An exact pin that differs from the locked version should be treated like an out-of-range root, so its lock edges are not trusted. test_exact_override_neighbors_stay_pinned_when_a_rejected_range_does_not currently asserts the opposite.

Could you add a resolution-only check per release-matrix bundle, for example pip install --dry-run with the same --target, -c and -r arguments? That would catch this class of conflict without a full image build.

Two smaller things:

• The tests still hard-code lock versions (gliner == "0.2.26", gliner2 == "1.3.2" and others), so the next lock bump breaks them. The torchvision check at line 82 only passes because the parsed value is 0.24.1.*.
• Please list the default-image version changes in the PR description (for example sentence-transformers 5.7.0 to 5.4.1 and gliner 0.2.29 to 0.2.26). Today they only appear in the build log.

[YeonwooSung]

The follow-up is e803153.

1. cuda12 default and transformers5. The lock has torch 2.9.1 from PyPI and torch 2.9.1+cu129. The emitted constraint is torch==2.9.1.*, and Dockerfile.cuda12 installs non-SGLang bundles from PyPI only. --target resolves that public wheel again instead of reusing the venv. The parser was unioning both torch entries, so the constraints pinned the cu129 nvidia stack, including nvidia-cublas-cu12==12.9.1.4. PyPI torch 2.9.1 requires nvidia-cublas-cu12==12.8.4.1, and pip cannot satisfy both. When the emitted constraint is the public prefix, only the public 2.9.1 entry contributes edges. The cu129 entry's edges are used only when that local version is itself the constraint. cuda12 default and transformers5 no longer pin nvidia-cublas-cu12.

2. cuda13 tensorrt-llm. torch==2.11.0 and transformers==5.5.4 differ from the lock (2.9.1.* and 4.57.6). Those exact pins were still trusted, so the constraints pinned huggingface-hub==0.36.2 and setuptools==83.0.0 from versions the bundle never installs. transformers 5.5.4 requires huggingface-hub<2.0,>=1.5.0, which excludes 0.36.2, and torch 2.11.0 requires setuptools<82. An exact pin that does not match the locked version is now an untrusted root, same as a range that misses the lock: its lock edges are not pinned. An exact pin that matches the locked version still contributes its edges. Neighbors reached only through a moved-off version are not pinned. test_exact_override_neighbors_stay_pinned_when_a_rejected_range_does_not asserted the opposite; it is now test_exact_override_neighbors_stay_pinned_only_when_the_pin_matches_the_lock. Before the change, the tensorrt-llm dry-run failed on numpy==2.4.4 against tensorrt-llm's numpy>=2.0.0,<2.4, the same class of edge. That pin is gone, and the dry-run resolves.

3. packages/sie_server/tests/core/test_bundle_image_resolution.py dry-runs every release-matrix bundle. The command is uv pip install --dry-run with --target, the constraint file, and the requirements file, plus the index flags from Dockerfile.cuda12, Dockerfile.cuda13, and Dockerfile.cpu. The marker environment is x86_64-manylinux_2_35, which matches the Ubuntu 22.04 CUDA images (glibc 2.35). Before the parser change, cuda12 default, cuda12 transformers5, and cuda13 tensorrt-llm each exited 1. After it, all 11 matrix targets resolve, including cpu default. No images were built and no wheels were vendored. The shared venv has no pip module, and pip install --platform on macOS still evaluates markers for Darwin: a torch ==2.9.1.* dry-run there did not request nvidia-cublas, so it would have missed this conflict. The check uses uv, which Dockerfile.cuda13 already runs and which can apply the linux marker environment. --no-config keeps this repo's cu129 torch source out of the resolution.

4. Assertions no longer compare lock output to literals such as gliner == "0.2.26" or gliner2 == "1.3.2". Those versions are read from parse_uv_lock. The torchvision check no longer treats 0.24.1.* != 0.24.1 as evidence of an override. Merge has to keep the bundle's exact pin torchvision==0.24.1.

5. The PR description now has a Default image pins section. Against PyPI on 2026-10-10, the default-bundle ranges whose lock pin is older than the top of the range are sentence-transformers 5.7.0 to 5.4.1, gliner 0.2.29 to 0.2.26, gliclass 0.1.20 to 0.1.17, FlagEmbedding 1.4.2 to 1.4.0, open-clip-torch 3.3.0 to 2.32.0, huggingface-hub 2.2.0 to 0.36.2, and requests 2.34.2 to 2.33.1. The Refs Bundle images resolve ranged dependencies past uv.lock #377 line is unchanged.

From the worktree:

PYTHONPATH=$PWD/packages/sie_server/src /Users/yeonwoosung/Desktop/sie/.venv/bin/python -m pytest packages/sie_server/tests/core/test_bundle_requirements.py packages/sie_server/tests/core/test_bundle_image_resolution.py -q --tb=line -p no:sugar

26 passed in 28.28s. The dry-run executed for all 11 release-matrix targets inside that run; it was not skipped.

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@packages/sie_server/tests/core/test_bundle_image_resolution.py:
- Around line 143-175: Gate test_release_bundle_constraints_resolve behind an
explicit SIE_RUN_IMAGE_RESOLUTION=1 opt-in so it is skipped by default, and run
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[YeonwooSung]

The default pytest suite skips test_release_bundle_constraints_resolve unless SIE_RUN_IMAGE_RESOLUTION=1. The dry-run needs network access to package indexes, and no existing marker fits (integration would imply a running server).

CI / Bundle resolution checks out the repo, syncs the usual Python/uv environment, and runs only packages/sie_server/tests/core/test_bundle_image_resolution.py with that opt-in.

Default run (pytest -q packages/sie_server/tests/core/test_bundle_image_resolution.py -p no:cacheprovider): 11 skipped in 0.04s.

Opt-in run (SIE_RUN_IMAGE_RESOLUTION=1, same file): 11 passed in 30.10s.

[krisztian-gajdar]

Thanks, this round fixes both resolution problems. CI confirms it: every release image now builds, including cuda12 default and transformers5 and cuda13 tensorrt-llm, and the new CI / Bundle resolution job passes.

One blocker is left. CI / Python still fails typecheck with the same three ty errors, now at bundle_requirements.py:298 and :301. _lock_edges calls item.get(...) on a value narrowed from object by isinstance(item, dict). Using the same pattern as line 42 should clear it: fields = cast("Mapping[str, object]", item) after the isinstance check, then read name and extra/extras from fields.

Smaller items:

• The CodeRabbit thread on tools/ci/tests/test_docker_task.py:282 is still open. Both cuda12 install branches sit in one logical line, so the check would still pass if one branch lost -c. Splitting on ;; would check each branch.
• With SIE_RUN_IMAGE_RESOLUTION=1 set, a missing uv makes the resolution test skip, so the job can go green without resolving anything. Could it fail in that case instead?
• The PR now adds a required CI lane that reaches package indexes on every PR. Please mention that in the description and refresh the Tests section. Whether the lane stays required is something we will decide on our side.

[YeonwooSung]

The three ty errors are cleared by casting each lock edge to Mapping[str, object] before .get, the same pattern as the other bundle field reads. ty check packages/sie_server/src/sie_server/bundle_requirements.py passed.

The Dockerfile test now splits a logical RUN on ;; and requires -c on each install command, so one CUDA 12 branch cannot cover the other. That thread is resolved.

With SIE_RUN_IMAGE_RESOLUTION=1, a missing uv fails the test instead of skipping it. The default suite still skips the network dry-run: 11 skipped, and the new missing-uv case passed.

The PR description now says CI / Bundle resolution is a required lane and that it reaches package indexes on every pull request. Whether it stays required is left to you. The Tests section matches the current commands.

Refs #377

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Inline comments:
Review comments at @packages/sie_server/src/sie_server/bundle_requirements.py:
- Around line 241-252: Update the trusted reach calculation used by the
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constrained_reach and exact_reach sets. This prevents transitive packages
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[YeonwooSung]

A transitive package that an untrusted root can reach is no longer pinned, even when a constrained root reaches it too. sentence-transformers>=5.4.1,<6 and transformers>=5.14,<6 both reach huggingface-hub; pinning the lock's 0.36 next to transformers 5 can make the solve fail. The constrained requirement itself stays pinned. Dropping torch because transformers 5 also depends on it would float the bundle's own torch range.

pytest packages/sie_server/tests/core/test_bundle_requirements.py — 16 passed. SIE_RUN_IMAGE_RESOLUTION=1 pytest packages/sie_server/tests/core/test_bundle_image_resolution.py — 12 passed. ty check on bundle_requirements.py passed.

Refs #377

[svonava]

@coderabbitai review

Please review current head 35de8d5b5e5b5fa8e9a9fd55d5b809e06c3324ee. This one-file follow-up preserves the existing contributor commits and replaces two moving bundle-range literals with checks that the actual declarations exclude the locked versions and survive unchanged.

Validation: 16 constraint tests on the PR branch; 73 focused constraints, missing-uv, and Docker-contract tests on an isolated integration with main 0fd7c9a93af39f5ea6b2f98e893db43061524cfd; scoped type/lint/format checks. The old assertion fails specifically on main's transformers>=5.17,<6, and the corrected assertion passes. CPU and CUDA12 Transformers5 resolution-only commands both succeeded with Transformers 5.20.1; no packages or images were installed/built. The separate integration merge is not part of this PR branch.

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[svonava]

@coderabbitai full review

Please review current head adacc5ec32e194cc25a47326e44996eb57e0fabf. This preserves the contributor history, integrates merged main 71b0c54c7b7db76fd42accce60ee7f098058ba4e, and updates two test assumptions for the exact Sentence Transformers 5.7.0 pin from #803. It does not import the pending #804 fix or change the dependency parser or installers beyond the existing PR.

The old assertions reproducibly failed twice against that main; the corrected constraints suite passes all 16 tests. Standard mise tasks also passed 56 Docker-contract tests, the missing-installer control, full public lint, scoped parser typecheck and the frozen lock check. The 11 network resolution cases remain assigned to the required CI lane.

I rechecked the earlier human review requests: lock-edge mappings are cast before field reads, each CUDA install arm is checked separately, an explicitly enabled resolver without uv fails, and the description names both the required network lane and the installed default pins. The human changes-requested review remains in place for re-review. Dependent #802 retains its separate complete-closure scope and all merge gates.

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Review comments at @packages/sie_server/src/sie_server/bundle_requirements.py:
- Around line 234-243: Update `_reachable` to optionally stop traversing
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⚙️ Run configuration

• Configuration used: Organization UI
• Review profile: CHILL
• Plan: Advanced
• Run ID: c2b79952-ca07-49a3-a56c-74f56da98416

📥 Commits

Reviewing files that changed from the base of the PR and between 71b0c54 and adacc5e.

📒 Files selected for processing: 10

• .github/workflows/ci.yml
• packages/sie_server/Dockerfile.cpu
• packages/sie_server/Dockerfile.cuda12
• packages/sie_server/Dockerfile.cuda13
• packages/sie_server/src/sie_server/bundle_requirements.py
• packages/sie_server/src/sie_server/cli.py
• packages/sie_server/tests/core/test_bundle_image_resolution.py
• packages/sie_server/tests/core/test_bundle_requirements.py
• tools/ci/required_ci.py
• tools/ci/tests/test_docker_task.py

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[svonava]

@coderabbitai full review

Fixed discussion_r4307255005 in 5099112. Trusted traversal now stops before an ambiguous package's outgoing base or extra dependencies. It still reports the skipped package and preserves descendants reached through independent trusted paths; untrusted traversal retains its conservative behavior.

Six new regression cases fail against the previous implementation. All 24 constraint tests pass with the fix, plus 19 independently authored graph/order/cycle controls. All 22 current bundle CPU/CUDA declaration and constraint outputs are unchanged. Public lint and scoped typecheck pass. The existing human changes-requested review remains pending re-review.

[coderabbitai]

✅ Action performed

Full review finished.

[krisztian-gajdar]

Thanks @YeonwooSung, and thanks @svonava for the follow-ups. I went through everything since 9fd4c04. The ambiguous-node fix looks right: the trusted walks now stop at a package with more than one locked version, and untrusted paths still unpin shared neighbours, so it can only remove pins, never add them. On the current uv.lock it changes no constraint output for any bundle and platform. The workflow, required-lane and Dockerfile changes are unchanged from the last round, and all checks are green.

We are keeping CI / Bundle resolution as a required lane. Approving.