fix(translation): emit Responses tool arguments once when decoding - #469
fix(translation): emit Responses tool arguments once when decoding#469arozumenko wants to merge 2 commits into
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`response.output_item.done` repeats the complete function-call arguments the
delta events already carried, so the decoder suppresses it when it matches
what has been seen. That comparison read `StreamToolState::arguments` — a
field no decoder writes. It is populated by the Anthropic encoder, so the
check only held when a single StreamTranslationState performed both halves
of the translation.
libsy buffers a streamed turn with its own state and encodes later, so every
llm_classifier route emitted the arguments twice. Passthrough, where one
state does decode and encode, was unaffected — which is why this survived.
Observed through switchyard-server 0.2.0 against a live Azure gpt-5.6
target: an Anthropic client accumulating input_json_delta received
`{"skill":"x"}{"skill":"x"}`. Claude Code rejects that with
"InputValidationError: The parameter '' type is expected as 'object' but
provided as 'string'", making every tool-using agent session fail on any
llm_classifier route.
The decoder now accumulates into its own `decoded_arguments`, so the
deduplication holds regardless of which state encodes, or whether anything
encodes at all.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Signed-off-by: Artem Rozumenko <artyom.rozumenko@gmail.com>
WalkthroughThe change adds separate source-decoded argument state and updates Responses stream decoding to prevent duplicate function-call arguments. A regression test verifies that repeated completion events emit the arguments once. ChangesResponses stream argument handling
Estimated code review effort: 3 (Moderate) | ~20 minutes Merge Risk: ⚪ Minimal · up to The decoder change and regression coverage address the duplicated-arguments behavior; only a non-functional test-comment cleanup remains. No actionable merge-blocking risk remains after normal checks. Poem
🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
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Inline comments:
In `@crates/switchyard-translation/tests/stream_translation.rs`:
- Around line 1202-1215: Replace the multi-paragraph comment above the test with
a concise comment describing the preserved behavior: decoding streamed tool-call
arguments must emit them exactly once, including when the completion event
repeats arguments already delivered by delta events. Remove the outdated claim
that the decoder does not write decoded_arguments.
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Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com> Signed-off-by: Artem Rozumenko <artyom.rozumenko@gmail.com>
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What
Fixes duplicated function-call arguments when decoding an OpenAI Responses stream.
response.output_item.donerepeats the complete arguments that the delta events already carried, sodecode_responses_output_item_donesuppresses it when it matches what has been seen. That comparison readStreamToolState::arguments— a field no decoder writes. It is populated by the Anthropic encoder (codecs/anthropic/stream.rs), so the check only held when a singleStreamTranslationStateperformed both halves of the translation.The decoder now accumulates into its own
decoded_arguments, so deduplication holds regardless of which state encodes, or whether anything encodes at all.Why
libsybuffers a streamed turn with its own state and encodes later (algorithms/advisor_gate/turn.rs), so the guard always saw an empty string. Everyllm_classifierroute emitted the tool arguments twice.passthroughwas unaffected, because one state does both decode and encode there.Observed against switchyard-server 0.2.0 with a live Azure
gpt-5.6target. An Anthropic client accumulatinginput_json_deltareceived:Claude Code rejects that with
InputValidationError: The parameter '' type is expected as 'object' but provided as 'string', so every tool-using agent session fails on anyllm_classifierroute.Measured across route types, same tool and prompt:
passthroughllm_classifier(capability)llm_classifier(escalation)The extra encoding in escalation mode disappears once the duplication is fixed; it was a consequence, not a separate defect.
Why this survived to 0.2.0
It requires four things at once: Anthropic Messages inbound, Responses upstream, streaming, and a route that decodes with its own state.
benchmark/server-configs/tb-lite-llm-classifier-*.tomlusesformat = "openai_chat", so classifier benchmarks never exercise the Responses upstream; and the Codex path is Responses-in/Responses-out, whereencode_stream_eventreplays preserved JSON verbatim and never touches the normalized chunks.Anthropic-in with Responses-upstream is forced by pairing Claude Code with a GPT-5.6 target, which requires
/v1/responsesfor function tools with a reasoning effort.How tested
cargo fmt --all --checkcleancargo clippy --workspace --all-targets -- -D warningsclean (excludingswitchyard-py, which does not link outside a Python build env locally)cargo test --workspace --exclude switchyard-pygreenresponses_decode_emits_tool_arguments_oncefails before the change and passes afterswitchyard-server, ran anllm_classifierescalation route against Azuregpt-5.6through a real Anthropic Messages client. Accumulatedpartial_jsonbefore:{"skill":…}{"skill":…}string-wrapped; after:{"args":{},"skill":"demo:thing"}, parsing as an object.Python gates were not run — this change is Rust-only.
Checklist
--helpunchanged — no customer-facing surface change.Notes for reviewers
openai_chatforwards its argument deltas without deduplicating, and Chat Completions has no terminal repeat, so it does not share the flaw. Only the Anthropic encoder touchestool_states.output_indexaccumulation matters more than in the single-call reproduction.Summary by CodeRabbit
Bug Fixes
Tests