fix(openai-chat): normalize oversized inline images before they reach the wire - #4119
fix(openai-chat): normalize oversized inline images before they reach the wire#4119DamnUi wants to merge 7 commits into
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Included review availability: Your plan provides up to 10 included reviews per hour; 8 remain after this review. 📝 WalkthroughWalkthroughThe OpenAI Chat adapter now detects oversized inline image data URLs, normalizes them within a 3.5 MiB base64 budget, preserves non-data and invalid images, and passes incoming image tier bias to normalization. Tests cover request behavior, delegation, passthrough, and edge cases. ChangesOpenAI chat image normalization
Estimated code review effort: 3 (Moderate) | ~20 minutes Sequence Diagram(s)sequenceDiagram
participant Caller
participant buildRequest
participant normalizeOpenAIChatImages
participant normalizeImageTargets
participant OpenAIRequest
Caller->>buildRequest: provide parsed messages and IncomingMeta
buildRequest->>buildRequest: detect shrinkable inline images
buildRequest->>normalizeOpenAIChatImages: normalize with image tier bias
normalizeOpenAIChatImages->>normalizeImageTargets: normalize image targets
normalizeImageTargets-->>normalizeOpenAIChatImages: return replacement URLs
normalizeOpenAIChatImages-->>buildRequest: update image URLs in place
buildRequest->>OpenAIRequest: finish request construction
OpenAIRequest-->>Caller: return request or Promise
Merge Risk: ⚪ Minimal · up to The routed OpenAI Chat path now shrinks oversized inline images while preserving images and captions, with safe fallback behavior; delegated requests await normalization and native passthrough remains unchanged. The supplied regression coverage leaves no actionable merge-blocking risk. 🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
✨ Finishing Touches🧪 Generate unit tests (beta)
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In `@src/adapters/openai-chat.ts`:
- Line 1655: Update the imageTierBias documentation comment in the base adapter
to include openai-chat as a consumer, removing the stale claim that only the
anthropic adapter uses it while preserving the existing description of adapters
that ignore the option.
- Around line 1654-1656: Update the image-normalization path around
normalizeOpenAIChatImages so its rejection is caught and routed to finish(),
matching processAt’s failure behavior and allowing buildRequest to proceed.
Preserve the existing tierBias options and successful normalization flow.
- Around line 1653-1658: Await the potentially asynchronous buildRequest result
in the MiMo wrapper before accessing baseReq.body, preserving the
image-normalization flow in openai-chat. Update direct buildRequest callers,
including the parallel-tool-calls and fastwire-policy tests, to await the
returned request instead of casting the promise to AdapterRequest.
In `@tests/adapters/openai/openai-chat-image-normalization.test.ts`:
- Line 161: Remove the unused terminalEdge assertion and its associated
TIER_SPECS usage from the test, including the TIER_SPECS import. Keep the
assertions verifying that all six parts survive and remain data URLs.
- Around line 227-230: Add translatorBudget: createTestTranslatorBudget() to the
IncomingMeta object passed to buildRequest in the image normalization test,
avoiding a type assertion and preserving the existing adapter and request setup.
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…failure Addresses the CodeRabbit findings on lidge-jun#4119. mimo-free wraps this adapter and read baseReq.body from a synchronous cast. Once an image-bearing turn made buildRequest return a promise, that read produced undefined and JSON.parse threw, so image turns on that provider failed outright. Verified against the built adapter before and after: body was undefined, and is now a string. A normalizer rejection no longer fails the turn. The shared pipeline already leaves an image it cannot process untouched, so degrading to the unshrunk request is strictly better than losing the turn: the worst case is the oversized request the caller would have sent anyway. Also corrects the imageTierBias doc in base.ts, which still claimed anthropic was the only consumer, and drops a tautological assertion in the new test that advertised floor-tier coverage it did not provide. Tests: two new regressions cover the delegated-adapter await and the normalizer-failure fallback. tests/adapters/openai/openai-chat-image- normalization.test.ts now 10 pass / 0 fail. Broad run over tests/adapters, tests/providers/kiro, tests/images and the openai-chat callers: 1023 pass / 108 fail, unchanged failure set from dev at 57077ca. bun run typecheck and bun scripts/privacy-scan.ts pass.
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Inline comments:
In `@tests/adapters/openai/openai-chat-image-normalization.test.ts`:
- Line 244: Update the test setup for ProviderAdapter.buildRequest to include
translatorBudget: createTestTranslatorBudget() in the IncomingMeta object passed
alongside parsed, preserving the existing request-building assertions.
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The image reduction direction is useful, and awaiting the delegated Mimo build fixes a real async-boundary problem. Two changes are still needed on this head:
tests/adapters/openai/openai-chat-image-normalization.test.ts, the terminal-overflow test: its 40x40 PNG already fits the shared codec's dimension and byte caps.processAttherefore validates/pass-throughs it before reaching the injected sizedEncoder; six such images do not enter terminal overflow. Assert that the encoder actually reaches the terminal tier, that the remaining byte total exceeds the budget, and that every image is retained. Also make the rejection test observe the claimed fallback bytes, not merely a string body/image count.- This is a default lossy transformation for every provider that reaches
createOpenAIChatAdapter, not just Copilot, but no public/structure documentation is updated. Document the exact adapter scope, JPEG/alpha/fidelity tradeoff and the fact that 3.5 MiB is a best-effort image budget—not a hard request-size guarantee. The native Chat fast path inchat-completions.ts/chat-native.tsbypasses this builder; add a caller-level regression to make that boundary explicit and avoid advertising universal Chat endpoint recovery. Do not silently widen scope to that fast path without the corresponding contract review.
The reported 1018/108 comparison is useful baseline evidence but is not a green full suite, and the current upstream rollup has no product-test execution. Keep #4112's text/non-stream classification separate. No local product code or live-provider probes were executed for this review.
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Both points were correct. Fixed in 5c4039e. 1. The terminal-overflow test was vacuous. Confirmed by instrumenting the encoder rather than reading the code: the 40x40 PNG is 196 base64 chars and fits tier 0's caps (maxEdge 2000, hardCap 2MiB), so It now uses the same 1000x1000 noise PNG as the other tests, which misses every tier's caps. That run walks all six tiers (44 encode calls, maxEdges 2000/1024/700/500/400/320), so the test asserts the encoder reaches the terminal tier, that the retained total is still over budget, and that all six images are kept. The rejection test now asserts the exact original bytes come back and that I checked the new assertions actually bite: clearing the URL in the 2. Scope and the fast-path boundary are now documented. The same section states that One note on that regression: I first imported On validation: agreed the 1019/108 comparison is a baseline delta, not a green suite. The baseline was measured on a clean |
리뷰 · 우선순위 66 / 80설명 이 PR은 GitHub Copilot 같은 OpenAI-compatible chat 경로에서 인라인 이미지가 직렬화 body 바이트 한도(약 5.2MB)를 넘기면 bare HTTP 413이 나고, compaction이 같은 history를 다시 보내며 연쇄 실패하는 문제를 고친다. 관련 추적의 recovery 절반은 #2511이고, 분류(classification) 쪽은 열린 #4127 / #4112가 맡는다. 지금 고치는 층은 어댑터 부수 수정이 알맞다. 점수 66은 "Copilot 413 사망 나선 막는 CLEAR recovery"라서 중상이다. 다만 공유 ladder의 합산 회계와 no-op drop 조합, 서버 src/adapters/openai-chat-images.ts src/server/image-retry.ts src/adapters/openai-chat-images.ts src/adapters/openai-chat.ts src/adapters/mimo-free.ts src/adapters/openai-chat.ts 메인테이너의 판단이 필요한 지점
너의 추천 이 댓글은 grok-bot이 작성했습니다 |
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Thanks for fixing the vacuous test and documenting the lossy adapter scope. I read the 460f66f -> 5c4039e delta: the new fixture observes actual encoder work, reaches the terminal tier, remains over budget, and retains all six images. The failure-path assertion now checks the original URL bytes. Those parts address my earlier feedback.
One verification boundary remains: directly calling buildOpenAIChatPassthroughRequest proves that builder preserves bytes, but does not prove the native /v1/chat/completions dispatcher actually selects it. The test name currently implies that wider caller coverage. Please rebase onto current dev and add a small request/dispatch-level regression, or name the builder-only test precisely and keep the missing integration evidence explicit. The import failure on 57077ca is useful historical baseline evidence, not a permanent substitute for checking the current caller.
The PR currently still has a failed enforce-target check and no successful repository product suite in its check rollup. Please resolve those on the new exact head; the old 108-failure baseline comparison is not a green suite. I am keeping the change request pending that caller/readiness gap, not asking you to repeat the now-correct terminal and fallback assertions. No live-provider or local product execution was performed for this follow-up.
… the wire Several OpenAI-compatible providers enforce a raw byte ceiling on the serialized chat-completions body, separate from any token limit. GitHub Copilot rejects at roughly 5.2MB with a bare HTTP 413 and no diagnostic content, so a turn carrying a few full-resolution screenshots cannot be sent at all and the conversation cannot recover: compaction has to send the same history to summarize it, so it fails the same way. The image ladder that already solves this for the anthropic and kiro wires is wire-neutral. normalizeImageTargets operates on generic NormalizeTarget handles, and kiro-images.ts already reuses it for the CodeWhisperer format. This adds the equivalent wrapper for image_url parts in Chat Completions messages. Images are never dropped on this wire. overflowAction is "none" and the drop callback keeps the original URL, because unlike anthropic there is no downstream guard that would re-attach or textify a removed image, and silently discarding a user's screenshot is worse than a large request. buildRequest stays synchronous unless a turn actually carries inline image bytes over the budget. base.ts already permits a promise return and every routed caller awaits it, but many direct callers rely on the synchronous shape, and making every text-only turn async would change their timing for no benefit. Tests: bun test tests/adapters/openai/openai-chat-image-normalization.test.ts (8 pass). Full tests/adapters, tests/providers/kiro, tests/images and the openai-chat callers show 1004 pass / 108 fail, against 996 pass / 108 fail on unmodified dev at 57077ca: same failures, plus the 8 new tests. bun run typecheck and bun scripts/privacy-scan.ts both pass.
…failure Addresses the CodeRabbit findings on lidge-jun#4119. mimo-free wraps this adapter and read baseReq.body from a synchronous cast. Once an image-bearing turn made buildRequest return a promise, that read produced undefined and JSON.parse threw, so image turns on that provider failed outright. Verified against the built adapter before and after: body was undefined, and is now a string. A normalizer rejection no longer fails the turn. The shared pipeline already leaves an image it cannot process untouched, so degrading to the unshrunk request is strictly better than losing the turn: the worst case is the oversized request the caller would have sent anyway. Also corrects the imageTierBias doc in base.ts, which still claimed anthropic was the only consumer, and drops a tautological assertion in the new test that advertised floor-tier coverage it did not provide. Tests: two new regressions cover the delegated-adapter await and the normalizer-failure fallback. tests/adapters/openai/openai-chat-image- normalization.test.ts now 10 pass / 0 fail. Broad run over tests/adapters, tests/providers/kiro, tests/images and the openai-chat callers: 1023 pass / 108 fail, unchanged failure set from dev at 57077ca. bun run typecheck and bun scripts/privacy-scan.ts pass.
…egression IncomingMeta.translatorBudget is required, and the delegating-adapter regression added in the previous commit omitted it. tsconfig only includes src, so the test tree is not type-checked and this did not surface as an error. The two sibling cases in this file already pass a budget; this makes the third consistent. Tests: tests/adapters/openai/openai-chat-image-normalization.test.ts 10 pass / 0 fail. Broad run unchanged at 1023 pass / 108 fail, same failure set as dev at 57077ca. typecheck and privacy:scan pass.
…test The terminal-overflow test used a 40x40 PNG, which fits every tier's dimension and byte caps. processAt validated and passed it through before the injected encoder was reached, so the ladder never ran and the assertion that six images survived held vacuously: encodeCalls was 0 and the total was 1176 bytes against a 3.5MiB budget. It now uses a 1000x1000 noise PNG that misses those caps, asserts the encoder reaches the terminal tier, and asserts the total is still over budget when every image is retained. The rejection test now observes the claimed fallback bytes rather than a string body and an image count. Document the scope in structure/. This is a default lossy transformation for every provider reaching createOpenAIChatAdapter, the JPEG/alpha tradeoff is real, and 3.5MiB is a best-effort image budget rather than a request-size guarantee. A caller-level regression pins the native Chat fast path, which builds through buildOpenAIChatPassthroughRequest and bypasses this builder.
The shared core stops counting a target once it calls drop, which is correct for anthropic and kiro because their drop callbacks remove or textify the image. This wire's drop is a deliberate no-op that leaves the original URL in place, so those bytes stayed on the wire while the accounting forgot them and the demotion loop could stop early believing it was under budget. Measured on one truncated-PNG data URL plus three 1000x1000 noise PNGs: the normalized turn came out at 5,680,788 base64 chars against a 3,670,016 budget. With the fix it lands at 3,179,572, still retaining the undecodable image. NormalizeTarget gains an opt-in retainsBytesOnDrop flag set only by openai-chat-images, so anthropic and kiro accounting is untouched. Also make the mimo regression hermetic and prove native dispatch. The mimo test called the real adapter, whose buildRequest bootstraps a JWT over the network; it passed locally and failed CI with ECONNRESET against api.xiaomimimo.com. It now stubs fetch and resets the JWT cache on both sides, following the pattern in tests/providers/mimo-free-provider.test.ts, and the file passes with all network blocked at preload. The native-path assertion moves to openai-chat-native-policy.test.ts and now drives handleChatCompletions against a fake upstream, so it proves the dispatcher selects the passthrough builder rather than only that the builder preserves bytes. That file already imports the handler; importing it into the image suite triggers unrelated mock pollution from tests/images.
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The terminal-overflow branch subtracted a dropped target's bytes from the running total unconditionally. On a wire whose drop leaves the original bytes in place, that made the loop believe a drop had freed space when nothing had left, so it could stop before dropping a target that can actually go. Unreachable from openai-chat today because it passes overflowAction "none", but the flag is part of the shared contract and the two drop paths should agree. Anthropic and kiro do not set the flag and are unaffected.
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Both points are addressed on Rebase. The branch is on the current Dispatch-level regression. You were right that calling It lives in that file rather than the image suite because importing the handler into the image suite still trips CI. The One real bug found while rechecking. The shared core subtracts a dropped target's bytes from the running sum. That is right for anthropic and kiro, whose The last commit extends that to the terminal-overflow branch, which was still subtracting unconditionally. It is unreachable from On validation. Agreed that a baseline delta is not a green suite, so I have written it as a delta and left the failures visible. Same command, clean worktree: 1003 pass / 106 fail / 55 errors on this branch against 991 / 106 / 55 on Keeping #4112/#4127 classification separate, and I have not widened |
The finish closure and the two message-walking helpers had no doc comments, which left the diff's docstring coverage below the repo threshold.
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Rechecked 91835dd. The new test calls handleChatCompletions and observes the actual outgoing native request, including all four unchanged large image URLs. This resolves the builder-versus-dispatch evidence gap in my previous followup.
I also checked the new shared-normalizer accounting: retainsBytesOnDrop is set by the OpenAI Chat no-op drop callback, and the shared core keeps those bytes counted on rejection, failed demotion, and terminal overflow paths rather than subtracting bytes still on the wire. Other callers retain the prior drop-accounting default. This is useful, but it expands the reviewed production delta beyond the dispatcher test.
The author-reported 1003-pass/106-fail/55-error versus 991/106/55 comparison is regression-delta evidence, not a green product suite. Please keep that distinction in readiness reporting and provide the required exact-head checks covering the shared normalizer and native dispatch. The previously failed metadata gate is now green; I am not asking you to redo that resolved gate. No live-provider or local product execution was performed here.
sorry man, messed those points i revieweed but missed that point. will take a bit for this next one |
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Follow-up to #4112, and the payload-reduction half of what #2511 tracks.
Problem
Several OpenAI-compatible providers enforce a raw byte ceiling on the serialized chat-completions body that is separate from any token limit. GitHub Copilot rejects at roughly 5.2MB with a bare
HTTP 413and an empty diagnostic body. Measured ongithub-copilot/claude-opus-5: four screenshots at 4.44MB went through, five at 5.47MB did not, and plain text crosses at about the same point, so it is a byte limit rather than a token or image-count one. The token limit produces a clean 400 with a useful message and is unaffected by this change.On that route a turn over the ceiling cannot recover on its own, because compaction has to send the same history in order to summarize it and gets the same rejection. In one local session, 105 successful turns climbed to roughly 74k tokens and were then followed by eighteen consecutive 413s over eight minutes as compaction repeatedly tried and failed.
Nothing downstream of the adapter can shrink a request once it has been built. The one-tier image retry in
src/server/image-retry.tsis gated toadapterName === "anthropic", and these providers route throughopenai-chat.Change
The image ladder that already solves this for the anthropic and kiro wires operates on generic
NormalizeTargethandles, andkiro-images.tsalready reuses it for the CodeWhisperer format. This adds the equivalent wrapper forimage_urlparts in Chat Completions messages, with a 3.5MiB base64 budget that leaves headroom for text and tools under the observed ceiling.Measured with six 4000x4000 PNGs of real screenshot content in one turn: 6.14MB before, 0.90MB after, all six images still attached and the accompanying text unchanged.
Two deliberate choices are worth review attention:
Images are never dropped on this wire.
overflowActionis"none"and thedropcallback keeps the original URL. Unlike anthropic, this wire has no downstream guard that would re-attach or textify a removed image, so a drop here is silent data loss from the user's point of view. An image floored at the terminal 320px tier stays attached, and a corrupt or decode-bomb input rides through unchanged rather than disappearing.buildRequeststays synchronous unless a turn actually carries inline image bytes over the budget.base.tsalready permits a promise return and every routed caller awaits it, but a large number of direct callers depend on the synchronous shape. Making every text-only turn async changed 85 existing tests and would alter their timing for no benefit, so the async path is entered only viahasShrinkableOpenAIChatImages.Behaviour notes
Re-encoding only happens when an image exceeds its tier's dimension and size caps; anything already within them passes through byte-identical, which covers ordinary screenshots. Re-encoded images are emitted as JPEG, so a large PNG with an alpha channel is flattened, the same trade the anthropic and kiro paths already make. Normalization is wire-only, so stored response state keeps the originals and each turn re-shrinks from source, absorbed by the existing encode cache.
This does not address text-driven overflow. A conversation that crosses the ceiling on text alone still fails, and classifying that failure is what #4112 and #4127 cover.
Budget accounting for images this wire cannot drop
The shared core stops counting a target once it calls
drop. That is correct for anthropic and kiro, whosedropremoves or textifies the image, but this wire'sdropis a deliberate no-op leaving the original URL in place. Those bytes stayed on the wire while the accounting forgot them, so the demotion loop could stop early believing it was under budget and still ship an oversized body.Measured with one truncated-PNG data URL alongside three 1000x1000 noise PNGs: the normalized turn came out at 5,680,788 base64 characters against the 3,670,016 budget. With the fix it lands at 3,179,572 and still retains the undecodable image.
NormalizeTargetgains an opt-inretainsBytesOnDropflag set only byopenai-chat-images.ts, so anthropic and kiro accounting is unchanged.The terminal-overflow branch needed the same treatment for the flag to be coherent. It subtracted a dropped target's bytes unconditionally, which on a retaining wire would credit space that never came free and could stop the loop before reaching a target that can actually leave. That branch is unreachable from
openai-chatbecause it passesoverflowAction: "none", but the two drop paths should agree; a regression in the shared suite covers it.Scope and tradeoffs
structure/04_transports-and-sidecars.mddocuments this as a default lossy transformation for every provider that reachescreateOpenAIChatAdapter, not only Copilot, plusmimo-freethrough itscontractParent. It records the JPEG/alpha flattening tradeoff, the pass-through behaviour for images already within their tier caps, and that 3.5MiB bounds inline image base64 only. It is not a serialized request-size guarantee: a turn can still exceed a provider's ceiling on text and tool schemas alone.structure/01_runtime.mdcarries the adapter-table entry.The native Chat fast path in
src/server/chat-native.tsbuilds throughbuildOpenAIChatPassthroughRequestand bypasses this normalization. That boundary is pinned at dispatch level inopenai-chat-native-policy.test.ts, which driveshandleChatCompletionsagainst a fake upstream and asserts a 4MB inline image arrives byte-identical, so it exercises the route selection rather than only the builder.Validation
Broader run over
tests/adapters,tests/providers/kiro,tests/imagesandtests/providers/mimo-free-provider.test.ts: 1003 pass / 106 fail / 55 errors on this branch against 991 pass / 106 fail / 55 errors on unmodifieddevat6d3ad12e3, run with the same command in a clean worktree. That is a baseline delta, not a green suite. The two sorted failure lists diff to zero lines and the error count is identical; the difference is the 12 new passing tests. The pre-existing failures are network-pinned transport, GCP ADC, and provider-option spine tests.One caveat on that broad run:
openai-chat-native-policy.test.tsaborts inside the whole-directory batch withSyntaxError: Export named 'pinnedHttpPost' not found. That is order-dependentmock.modulepollution fromtests/images/download-cap-default.test.ts, it occurs identically on unmodifieddevin the same batch, and the file passes 22/22 on its own. It is not caused by this branch, and I have not tried to fix it here.Both focused suites were re-run with a preload that throws on any un-stubbed
fetch, and both still pass, so neither reaches the network.CodeRabbit's Docstring Coverage pre-merge check was failing at 35.71% on this diff. The last commit documents the three functions it flagged: the
finishclosure inopenai-chat.tsand the two message-walking helpers inopenai-chat-images.ts.New coverage: terminal overflow keeps counting a target whose drop leaves the bytes on the wire; an image this wire cannot drop keeps counting toward the budget; a delegating adapter awaits the built request instead of reading an undefined body; a normalizer rejection degrades to the unshrunk request; text-only turns stay synchronous and unchanged; under-budget image turns stay synchronous and byte-identical; an oversized turn is re-encoded through the real adapter wiring and keeps every image; terminal overflow keeps images attached instead of dropping the oldest; remote
https://URLs are untouched; undecodable images keep their original URL; malformed message shapes neither throw nor lose parts; andimageTierBiasfromIncomingMetareaches the normalizer.Review follow-up
mimo-freewraps this adapter and readbaseReq.bodyfrom a synchronous cast. Once an image-bearing turn madebuildRequestreturn a promise, that read producedundefinedandJSON.parsethrew, so image turns on that provider failed outright. Confirmed against the built adapter:bodywasundefinedbefore the fix and is a string after. It now awaits the delegated call, with a regression test.A normalizer rejection no longer fails the turn. The shared pipeline already leaves an image it cannot process untouched, so falling back to the unshrunk request means the worst case is the oversized request the caller would have sent anyway.
The terminal-overflow test was vacuous: its 40x40 PNG fits every tier's caps, so
processAtpassed it through before the injected encoder was reached and the ladder never ran. It now uses a 1000x1000 noise PNG, asserts the encoder reaches the terminal 320px tier, and asserts the total is still over budget while every image is retained.The mimo regression called the real adapter, whose
buildRequestbootstraps a JWT over the network. It passed locally and failed CI withECONNRESETagainstapi.xiaomimimo.com. It now stubsfetchand resets the JWT cache on both sides, followingtests/providers/mimo-free-provider.test.ts.The stale
imageTierBiasdoc inbase.tsnow namesopenai-chatas a second consumer.Review readiness checklist
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