## What changed
- Drop failed websocket connections immediately after a terminal stream
error instead of awaiting a graceful close handshake before forwarding
the error to the caller.
- Keep the success path and the closed-connection guard behavior
unchanged.
## Why this fixes the flake
- The failing integration test waits for the second websocket stream to
surface the model error before issuing a follow-up request.
- On slower runners, the old error path awaited
`ws_stream.close().await` before sending the error downstream. If that
close handshake stalled, the test kept waiting for an error that had
already happened server-side and nextest timed it out.
- Dropping the failed websocket immediately makes the terminal error
observable right away and marks the session closed so the next request
reconnects cleanly instead of depending on a best-effort close
handshake.
## Code or test?
- This is a production logic fix in `codex-api`. The existing websocket
integration test already exercises the regression path.
Pass more params to /compact. This should give us parity with the
/responses endpoint to improve caching.
I'm torn about the MCP await. Blocking will give us parity but it seems
like we explicitly don't block on MCPs. Happy either way
- collect input/output transcript deltas into active handoff transcript
state
- attach and clear that transcript on each handoff, and regenerate
schema/tests
# External (non-OpenAI) Pull Request Requirements
Before opening this Pull Request, please read the dedicated
"Contributing" markdown file or your PR may be closed:
https://github.com/openai/codex/blob/main/docs/contributing.md
If your PR conforms to our contribution guidelines, replace this text
with a detailed and high quality description of your changes.
Include a link to a bug report or enhancement request.
add `web_search_tool_type` on model_info that can be populated from
backend. will be used to filter which models can use `web_search` with
images and which cant.
added small unit test.
## 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
- add a local Fast mode setting in codex-core (similar to how model id
is currently stored on disk locally)
- send `service_tier=priority` on requests when Fast is enabled
- add `/fast` in the TUI and persist it locally
- feature flag
- migrate the realtime websocket transport to the new session and
handoff flow
- make the realtime model configurable in config.toml and use API-key
auth for the websocket
---------
Co-authored-by: Codex <noreply@openai.com>
- replace show_nux with structured availability_nux model metadata
- expose availability NUX data through the app-server model API
- update shared fixtures and tests for the new field
## Summary
- make `Config.model_reasoning_summary` optional so unset means use
model default
- resolve the optional config value to a concrete summary when building
`TurnContext`
- add protocol support for `default_reasoning_summary` in model metadata
## Validation
- `cargo test -p codex-core --lib client::tests -- --nocapture`
---------
Co-authored-by: Codex <noreply@openai.com>
Send a request with `generate: falls` but a full set of tools and
instructions to pre-warm inference.
---------
Co-authored-by: Codex <noreply@openai.com>
- Introduce `RealtimeConversationManager` for realtime API management
- Add `op::conversation` to start conversation, insert audio, insert
text, and close conversation.
- emit conversation lifecycle and realtime events.
- Move shared realtime payload types into codex-protocol and add core
e2e websocket tests for start/replace/transport-close paths.
Things to consider:
- Should we use the same `op::` and `Events` channel to carry audio? I
think we should try this simple approach and later we can create
separate one if the channels got congested.
- Sending text updates to the client: we can start simple and later
restrict that.
- Provider auth isn't wired for now intentionally
## Summary
- add realtime websocket client transport in codex-api
- send session.create on connect with backend prompt and optional
conversation_id
- keep session.update for prompt changes after connect
- switch inbound event parsing to a tagged enum (typed variants instead
of optional field bag)
- add a websocket e2e integration test in
codex-rs/codex-api/tests/realtime_websocket_e2e.rs
## Why
This moves the realtime transport to an explicit session-create
handshake and improves protocol safety with typed inbound events.
## Testing
- Added e2e integration test coverage for session create + event flow in
the API crate.
### Summary
Ensure that we use the model value from the response header only so that
we are guaranteed with the correct slug name. We are no longer checking
against the model value from response so that we are less likely to have
false positive.
There are two different treatments - for SSE we use the header from the
response and for websocket we check top-level events.
Add per-turn notice when a request is downgraded to a fallback model due
to cyber safety checks.
**Changes**
- codex-api: Emit a ServerModel event based on the openai-model response
header and/or response payload (SSE + WebSocket), including when the
model changes mid-stream.
- core: When the server-reported model differs from the requested model,
emit a single per-turn warning explaining the reroute to gpt-5.2 and
directing users to Trusted
Access verification and the cyber safety explainer.
- app-server (v2): Surface these cyber model-routing warnings as
synthetic userMessage items with text prefixed by Warning: (and document
this behavior).
### What
It's currently unclear when the harness falls back to the default,
generic `ModelInfo`. This happens when the `remote_models` feature is
disabled or the model is truly unknown, and can lead to bad performance
and issues in the harness.
Add a user-facing warning when this happens so they are aware when their
setup is broken.
### Tests
Added tests, tested locally.
# External (non-OpenAI) Pull Request Requirements
Before opening this Pull Request, please read the dedicated
"Contributing" markdown file or your PR may be closed:
https://github.com/openai/codex/blob/main/docs/contributing.md
If your PR conforms to our contribution guidelines, replace this text
with a detailed and high quality description of your changes.
Include a link to a bug report or enhancement request.
Added multi-limit support end-to-end by carrying limit_name in
rate-limit snapshots and handling multiple buckets instead of only
codex.
Extended /usage client parsing to consume additional_rate_limits
Updated TUI /status and in-memory state to store/render per-limit
snapshots
Extended app-server rate-limit read response: kept rate_limits and added
rate_limits_by_name.
Adjusted usage-limit error messaging for non-default codex limit buckets
Summary
- add a `prefer_websockets` field to `ModelInfo`, defaulting to `false`
in all fixtures and constructors
- wire the new flag into websocket selection so models that opt in
always use websocket transport even when the feature gate is off
Testing
- Not run (not requested)
When communicating over websockets, we can't rely on headers to deliver
rate limit information. This PR adds a `codex.rate_limits` event that
the server can pass to the client to inform them about rate limit usage.
The client parses this data the same way we parse rate limit headers in
HTTP mode.
This PR also wires up the etag and reasoning headers for websockets
###### Summary
- Add input_modalities to model metadata so clients can determine
supported input types.
- Gate image paste/attach in TUI when the selected model does not
support images.
- Block submits that include images for unsupported models and show a
clear warning.
- Propagate modality metadata through app-server protocol/model-list
responses.
- Update related tests/fixtures.
###### Rationale
- Models support different input modalities.
- Clients need an explicit capability signal to prevent unsupported
requests.
- Backward-compatible defaults preserve existing behavior when modality
metadata is absent.
###### Scope
- codex-rs/protocol, codex-rs/core, codex-rs/tui
- codex-rs/app-server-protocol, codex-rs/app-server
- Generated app-server types / schema fixtures
###### Trade-offs
- Default behavior assumes text + image when field is absent for
compatibility.
- Server-side validation remains the source of truth.
###### Follow-up
- Non-TUI clients should consume input_modalities to disable unsupported
attachments.
- Model catalogs should explicitly set input_modalities for text-only
models.
###### Testing
- cargo fmt --all
- cargo test -p codex-tui
- env -u GITHUB_APP_KEY cargo test -p codex-core --lib
- just write-app-server-schema
- cargo run -p codex-cli --bin codex -- app-server generate-ts --out
app-server-types
- test against local backend
<img width="695" height="199" alt="image"
src="https://github.com/user-attachments/assets/d22dd04f-5eba-4db9-a7c5-a2506f60ec44"
/>
---------
Co-authored-by: Josh McKinney <joshka@openai.com>
### What
add wiring for `phase` field on `ResponseItem::Message` to lay
groundwork for differentiating model preambles and final messages.
currently optional.
follows pattern in #9698.
updated schemas with `just write-app-server-schema` so we can see type
changes.
### Tests
Updated existing tests for SSE parsing and hydrating from history
Summary
- expose websocket telemetry hooks through the responses client so
request durations and event processing can be reported
- record websocket request/event metrics and emit runtime telemetry
events that the history UI now surfaces
- improve tests to cover websocket telemetry reporting and guard runtime
summary updates
<img width="824" height="79" alt="Screenshot 2026-01-31 at 5 28 12 PM"
src="https://github.com/user-attachments/assets/ea9a7965-d8b4-4e3c-a984-ef4fdc44c81d"
/>
seeing issues with azure after default-enabling web search: #10071,
#10257.
need to work with azure to fix api-side, for now turning off
default-enable of web_search for azure.
diff is big because i moved logic to reuse
