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* fix(openai): carry cache_control to prompt_cache_breakpoint on chat completions to gpt-5.6 A cache_control mark on a system, developer, user or tool message sent to /v1/chat/completions now reaches an OpenAI deployment that reads prompt_cache_breakpoint (gpt-5.6+ on api.openai.com, or one opted in through prompt_cache_options) as a prompt_cache_breakpoint on the same content part, instead of being stripped. Marks on assistant turns and tool definitions are still dropped, and deployments that do not read breakpoints keep today's behavior. * test(openai): rewrite chat prompt_cache_breakpoint wire test as sent-vs-received literals Each test now shows the request the caller sends and the exact body OpenAI receives as plain JSON, with one helper that returns the upstream body. Drops the per-test marker plumbing and the spend-log check, which did not test the cache mark translation. * test(openai): cover a marked chat message with null content on the breakpoint path A system, developer, user or tool message that carries cache_control but whose content is neither a string nor a list of parts is handed to the existing strip untouched instead of raising inside the transform. The new case pins that the request still goes out with the mark stripped and no breakpoint added. * refactor(openai): reuse the cache control hook's breakpoint placement on chat completions The chat transform had its own copy of how a message-level cache_control lands on a part for OpenAI's prompt_cache_breakpoint. It now calls one hook helper that the injection path also uses, so which roles and part types can carry a breakpoint is decided in one place. A message-level mark on list content now lands on the last part OpenAI accepts a breakpoint on, matching injection. * test(e2e): cover cache_control reaching gpt-5.6 explicit prompt caching on chat completions Four live cases through the proxy: a marked system part, a marked string system message, a marked user part and a marked tool result. Each must write the cache on the first call and read it on the second. * fix(openai): parse content parts instead of a banned TypeGuard when renaming cache marks The strict ruff gate bans typing.TypeGuard as unverified narrowing. The part rename now validates an accepted part with pydantic before handing it to the shared rename helper. |
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| guardrail_translation | ||
| __init__.py | ||
| test_openai_gpt_transformation.py | ||