Apply review feedback on codexExtractImageResults: preallocate the results
slice to its known maximum capacity to avoid growth reallocations, and guard
the itemsByIndex index-build/sort with a length check so no empty slice is
allocated or sorted when only the fallback items are present.
The OpenAI images path (/v1/images/*) previously called patchCodexCompletedOutput
to concatenate collected output_item.done items back into the completed event and
then re-parsed that rebuilt JSON to pull out the image results. For multi-megabyte
base64 image payloads this produced two extra full-size copies per request (the
concatenated output array plus the rebuilt completed event), inflating peak memory
under concurrent image generation.
Add codexExtractImageResults, which extracts image_generation_call results directly
from either the completed event's response.output or the collected items, without
the concatenate-and-reparse step. Semantics are preserved: completed output is
preferred and collected items are used only when it is empty, matching the original
patchCodexCompletedOutput behaviour. patchCodexCompletedOutput remains in use by the
text/responses path, which still forwards the patched event downstream.
Adds unit tests covering the completed-output path, the ordered fallback to
collected items, output preference, fallback list, and the wrong-event-type guard.
- Replaced `NewUsageReporter` with `NewExecutorUsageReporter` to include executor type in usage records.
- Updated all executors to use the new reporter implementation.
- Extended `UsageReporter` to track and publish executor type.
- Added tests to validate proper executor type recording and handling.
- Enhanced RedisQueue plugin and payload schema with executor type support.
- Modified `applyCodexIdentityConfuse*` functions to include `turn_id` and `window_id` in metadata transformations.
- Updated test cases to validate the inclusion and restoration of these fields.
- Removed deprecated `Conversation_id` header support and related logic for cleaner implementation.
- Added `applyCodexIdentityConfuse*` functions for remapping request and response payloads and headers to enhance security.
- Updated WebSocket and HTTP logic to handle identity state transformations seamlessly.
- Introduced unit tests to verify remapping and restoration of identity-related fields.
- Introduced Time-To-First-Token (TTFT) measurement and reporting across major executors.
- Added TTFT calculation to `UsageReporter`, including support for HTTP clients and WebSocket communication.
- Updated tests to validate TTFT tracking in streamed and non-streamed scenarios.
- Ensured integration with `usage` plugin and augmented usage records with TTFT data.
- Introduced `SetTranslatedReasoningEffort` method in `UsageReporter` to capture and log reasoning efforts from translated payloads.
- Updated executors to incorporate the new reporting functionality for handling reasoning efforts across various providers.
- Enhanced logging for thinking level extraction with new helper function `ExtractTranslatedReasoningEffort`.
- Introduced `GPTImage2BaseModel` configuration for hosted image generation tools with validation for "gpt-" prefix.
- Added logic to dynamically resolve and apply the base model in Codex executor workflows.
- Enhanced server-sent events (SSE) implementation with keep-alive tickers and error events for stream reliability.
- Updated configuration file examples and internal documentation.
- Introduced OpenAI-compatible image model support in the API, enabling integration through image generation and editing endpoints.
- Added registry type for OpenAIImageModelType to classify and validate compatibility.
- Implemented request handling for OpenAI-compatible image models, including JSON and multipart formats.
- Enhanced executor methods to support OpenAI-compatible image streaming and non-streaming requests.
- Included tests to validate model registration, streaming behavior, and multipart payload formatting.
