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## Summary
Add original-resolution support for `view_image` behind the
under-development `view_image_original_resolution` feature flag.
When the flag is enabled and the target model is `gpt-5.3-codex` or
newer, `view_image` now preserves original PNG/JPEG/WebP bytes and sends
`detail: "original"` to the Responses API instead of using the legacy
resize/compress path.
## What changed
- Added `view_image_original_resolution` as an under-development feature
flag.
- Added `ImageDetail` to the protocol models and support for serializing
`detail: "original"` on tool-returned images.
- Added `PromptImageMode::Original` to `codex-utils-image`.
- Preserves original PNG/JPEG/WebP bytes.
- Keeps legacy behavior for the resize path.
- Updated `view_image` to:
- use the shared `local_image_content_items_with_label_number(...)`
helper in both code paths
- select original-resolution mode only when:
- the feature flag is enabled, and
- the model slug parses as `gpt-5.3-codex` or newer
- Kept local user image attachments on the existing resize path; this
change is specific to `view_image`.
- Updated history/image accounting so only `detail: "original"` images
use the docs-based GPT-5 image cost calculation; legacy images still use
the old fixed estimate.
- Added JS REPL guidance, gated on the same feature flag, to prefer JPEG
at 85% quality unless lossless is required, while still allowing other
formats when explicitly requested.
- Updated tests and helper code that construct
`FunctionCallOutputContentItem::InputImage` to carry the new `detail`
field.
## Behavior
### Feature off
- `view_image` keeps the existing resize/re-encode behavior.
- History estimation keeps the existing fixed-cost heuristic.
### Feature on + `gpt-5.3-codex+`
- `view_image` sends original-resolution images with `detail:
"original"`.
- PNG/JPEG/WebP source bytes are preserved when possible.
- History estimation uses the GPT-5 docs-based image-cost calculation
for those `detail: "original"` images.
#### [git stack](https://github.com/magus/git-stack-cli)
- 👉 `1` https://github.com/openai/codex/pull/13050
- ⏳ `2` https://github.com/openai/codex/pull/13331
- ⏳ `3` https://github.com/openai/codex/pull/13049
codex-api
Typed clients for Codex/OpenAI APIs built on top of the generic transport in codex-client.
- Hosts the request/response models and request builders for Responses and Compact APIs.
- Owns provider configuration (base URLs, headers, query params), auth header injection, retry tuning, and stream idle settings.
- Parses SSE streams into
ResponseEvent/ResponseStream, including rate-limit snapshots and API-specific error mapping. - Serves as the wire-level layer consumed by
codex-core; higher layers handle auth refresh and business logic.
Core interface
The public interface of this crate is intentionally small and uniform:
-
Responses endpoint
- Input:
ResponsesApiRequestfor the request body (model,instructions,input,tools,parallel_tool_calls, reasoning/text controls).ResponsesOptionsfor transport/header concerns (conversation_id,session_source,extra_headers,compression,turn_state).
- Output: a
ResponseStreamofResponseEvent(both re-exported fromcommon).
- Input:
-
Compaction endpoint
- Input:
CompactionInput<'a>(re-exported ascodex_api::CompactionInput):model: &str.input: &[ResponseItem]– history to compact.instructions: &str– fully-resolved compaction instructions.
- Output:
Vec<ResponseItem>. CompactClient::compact_input(&CompactionInput, extra_headers)wraps the JSON encoding and retry/telemetry wiring.
- Input:
-
Memory summarize endpoint
- Input:
MemorySummarizeInput(re-exported ascodex_api::MemorySummarizeInput):model: String.raw_memories: Vec<RawMemory>(serialized astracesfor wire compatibility).RawMemoryincludesid,metadata.source_path, and normalizeditems.
reasoning: Option<Reasoning>.
- Output:
Vec<MemorySummarizeOutput>. MemoriesClient::summarize_input(&MemorySummarizeInput, extra_headers)wraps JSON encoding and retry/telemetry wiring.
- Input:
All HTTP details (URLs, headers, retry/backoff policies, SSE framing) are encapsulated in codex-api and codex-client. Callers construct prompts/inputs using protocol types and work with typed streams of ResponseEvent or compacted ResponseItem values.