Fast Mode status was still tied to one model name in the TUI and
model-list plumbing. This changes the model metadata shape so a model
can advertise additional speed tiers, carries that field through the
app-server model list, and uses it to decide when to show Fast Mode
status.
For people using Codex, the behavior is intended to stay the same for
existing models. Fast Mode still requires the existing signed-in /
feature-gated path; the difference is that the UI can now recognize any
model the model list marks as Fast-capable, instead of requiring a new
client-side slug check.
## Why
`argument-comment-lint` was green in CI even though the repo still had
many uncommented literal arguments. The main gap was target coverage:
the repo wrapper did not force Cargo to inspect test-only call sites, so
examples like the `latest_session_lookup_params(true, ...)` tests in
`codex-rs/tui_app_server/src/lib.rs` never entered the blocking CI path.
This change cleans up the existing backlog, makes the default repo lint
path cover all Cargo targets, and starts rolling that stricter CI
enforcement out on the platform where it is currently validated.
## What changed
- mechanically fixed existing `argument-comment-lint` violations across
the `codex-rs` workspace, including tests, examples, and benches
- updated `tools/argument-comment-lint/run-prebuilt-linter.sh` and
`tools/argument-comment-lint/run.sh` so non-`--fix` runs default to
`--all-targets` unless the caller explicitly narrows the target set
- fixed both wrappers so forwarded cargo arguments after `--` are
preserved with a single separator
- documented the new default behavior in
`tools/argument-comment-lint/README.md`
- updated `rust-ci` so the macOS lint lane keeps the plain wrapper
invocation and therefore enforces `--all-targets`, while Linux and
Windows temporarily pass `-- --lib --bins`
That temporary CI split keeps the stricter all-targets check where it is
already cleaned up, while leaving room to finish the remaining Linux-
and Windows-specific target-gated cleanup before enabling
`--all-targets` on those runners. The Linux and Windows failures on the
intermediate revision were caused by the wrapper forwarding bug, not by
additional lint findings in those lanes.
## Validation
- `bash -n tools/argument-comment-lint/run.sh`
- `bash -n tools/argument-comment-lint/run-prebuilt-linter.sh`
- shell-level wrapper forwarding check for `-- --lib --bins`
- shell-level wrapper forwarding check for `-- --tests`
- `just argument-comment-lint`
- `cargo test` in `tools/argument-comment-lint`
- `cargo test -p codex-terminal-detection`
## Follow-up
- Clean up remaining Linux-only target-gated callsites, then switch the
Linux lint lane back to the plain wrapper invocation.
- Clean up remaining Windows-only target-gated callsites, then switch
the Windows lint lane back to the plain wrapper invocation.
### Summary
The goal is for us to get the latest turn model and reasoning effort on
thread/resume is no override is provided on the thread/resume func call.
This is the part 1 which we write the model and reasoning effort for a
thread to the sqlite db and there will be a followup PR to consume the
two new fields on thread/resume.
[part 2 PR is currently WIP](https://github.com/openai/codex/pull/14888)
and this one can be merged independently.
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
- 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>
rm `PRESETS` list harcoded in `model_presets` as we now have bundled
`models.json` with equivalent info.
update logic to rely on bundled models instead, update tests.
### 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.
- Clamp auto-compaction to the minimum of configured limit and 90% of
context window
- Add an e2e compact test for clamped behavior
- Update remote compact tests to account for earlier auto-compaction in
setup turns
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)
###### 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>
## Summary
Let's dial in this api contract in a bit more with more robust fallback
behavior when model_instructions_template is false.
Switches to a more explicit template / variables structure, with more
fallbacks.
## Testing
- [x] Adding unit tests
- [x] Tested locally
## Summary
Adds /personality selector in the TUI, which leverages the new core
interface in #9644
Notes:
- We are doing some of our own state management for model_info loading
here, but not sure if that's ideal. open to opinions on simpler
approach, but would like to avoid blocking on a larger refactor
- Right now, the `/personality` selector just hides when the model
doesn't support it. we can update this behavior down the line
## Testing
- [x] Tested locally
- [x] Added snapshot tests
## Summary
#9555 is the start of a rename, so I'm starting to standardize here.
Sets up `model_instructions` templating with a strongly-typed object for
injecting a personality block into the model instructions.
## Testing
- [x] Added tests
- [x] Ran locally
Next step would be to clean Model Upgrade in model presets
---------
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: aibrahim-oai <219906144+aibrahim-oai@users.noreply.github.com>
Have only the following Methods:
- `list_models`: getting current available models
- `try_list_models`: sync version no refresh for tui use
- `get_default_model`: get the default model (should be tightened to
core and received on session configuration)
- `get_model_info`: get `ModelInfo` for a specific model (should be
tightened to core but used in tests)
- `refresh_if_new_etag`: trigger refresh on different etags
Also move the cache to its own struct
- Merge ModelFamily into ModelInfo
- Remove logic for adding instructions to apply patch
- Add compaction limit and visible context window to `ModelInfo`
This isn't very useful parameter.
logic:
```
if model puts `**` in their reasoning, trim it and visualize the header.
if couldn't trim: don't render
if model doesn't support: don't render
```
We can simplify to:
```
if could trim, visualize header.
if not, don't render
```
# 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.
# 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.
# 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.
# 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.
# 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.
- Introduce `with_remote_overrides` and update
`refresh_available_models`
- Put `auth_manager` instead of `auth_mode` on `models_manager`
- Remove `ShellType` and `ReasoningLevel` to use already existing
structs
- Introduce `openai_models` in `/core`
- Move `PRESETS` under it
- Move `ModelPreset`, `ModelUpgrade`, `ReasoningEffortPreset`,
`ReasoningEffortPreset`, and `ReasoningEffortPreset` to `protocol`
- Introduce `Op::ListModels` and `EventMsg::AvailableModels`
Next steps:
- migrate `app-server` and `tui` to use the introduced Operation
