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RSPEED-2885: filter internal details from /v1/responses stream #1524
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tisnik
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Lifto:feat/rspeed-2885-filter-responses-internals
Apr 20, 2026
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da6ae27
fix: strip internal details from /v1/responses stream
Lifto 68c0057
fix(responses): use placeholder slug for substituted instructions
Lifto 3d970d4
fix(responses): address review nits
Lifto 90b0d0e
fix(responses): restore sanitization wiring lost in nit-fix commit
Lifto 303a40b
Merge branch 'main' into feat/rspeed-2885-filter-responses-internals
Lifto f865c51
fix(responses): simplify instructions_substituted check
Lifto 07327cc
chore: remove .sisyphus from tracking and add to .gitignore
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🛠️ Refactor suggestion | 🟠 Major
Return a sanitized copy instead of mutating the input dict.
Making this helper pure will avoid hidden caller side effects and make the two response paths easier to reason about.
As per coding guidelines "Avoid in-place parameter modification anti-patterns: return new data structures instead of modifying parameters".
🤖 Prompt for AI Agents
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In-place mutation is intentional here. The dict is created by
model_dump()on the line immediately before the call — it is a throwaway serialization dict, not a shared data structure. Returning a copy would allocate a new dict for every SSE chunk with zero safety benefit, since nothing else holds a reference to the original.The AGENTS.md guideline about avoiding in-place modification targets a different anti-pattern: functions that silently mutate a caller's long-lived data structure via a parameter. That does not apply here — the dict is born, sanitized, serialized to JSON, and discarded within the same
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@Lifto, that's a well-reasoned clarification — you're right. The guideline is aimed at functions that silently mutate a caller's long-lived/shared data structure through a parameter reference, which is a genuine source of bugs. Here the dict is born frommodel_dump(), passed straight into_sanitize_response_dict, serialized, and discarded — there's no aliasing risk and no wasted allocation. The in-place mutation is appropriate and intentional. I'll withdraw the suggestion.(ᵔᴥᵔ) 🐇✏️
✏️ Learnings added
🧠 Learnings used