## Why
PR #13783 moved the `codex.rs` unit tests into `codex_tests.rs`. This
applies the same extraction pattern across the rest of `codex-rs/core`
so the production modules stay focused on runtime code instead of large
inline test blocks.
Keeping the tests in sibling files also makes follow-up edits easier to
review because product changes no longer have to share a file with
hundreds or thousands of lines of test scaffolding.
## What changed
- replaced each inline `mod tests { ... }` in `codex-rs/core/src/**`
with a path-based module declaration
- moved each extracted unit test module into a sibling `*_tests.rs`
file, using `mod_tests.rs` for `mod.rs` modules
- preserved the existing `cfg(...)` guards and module-local structure so
the refactor remains structural rather than behavioral
## Testing
- `cargo test -p codex-core --lib` (`1653 passed; 0 failed; 5 ignored`)
- `just fix -p codex-core`
- `cargo fmt --check`
- `cargo shear`
## 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
## Summary
- allow `request_user_input` in Default collaboration mode as well as
Plan
- update the Default-mode instructions to prefer assumptions first and
use `request_user_input` only when a question is unavoidable
- update request_user_input and app-server tests to match the new
Default-mode behavior
- refactor collaboration-mode availability plumbing into
`CollaborationModesConfig` for future mode-related flags
## Codex author
`codex resume 019c9124-ed28-7c13-96c6-b916b1c97d49`
#### What
Try matching `\w+`-namespaced model after `longest prefix` as heuristic
to match `ModelInfo` from list of candidates.
This shouldn't regress existing behavior:
- `gpt-5.2-codex` -> `gpt-5.2` if `gpt-5.2-codex` not present
- `gpt-5.3` -> `gpt-5` if `gpt-5.3` not present
- `gpt-9` still doesn't match anything
while being more forgiving for custom prefixes:
- `oai/gpt-5.3-codex` -> `gpt-5.3-codex`
#### Tests
Added unit test.
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.
TL;DR
Add top-level `model_catalog_json` config support so users can supply a
local model catalog override from a JSON file path (including adding new
models) without backend changes.
### Problem
Codex previously had no clean client-side way to replace/overlay model
catalog data for local testing of model metadata and new model entries.
### Fix
- Add top-level `model_catalog_json` config field (JSON file path).
- Apply catalog entries when resolving `ModelInfo`:
1. Base resolved model metadata (remote/fallback)
2. Catalog overlay from `model_catalog_json`
3. Existing global top-level overrides (`model_context_window`,
`model_supports_reasoning_summaries`, etc.)
### Note
Will revisit per-field overrides in a follow-up
### Tests
Added tests
rm `remote_models` feature flag.
We see issues like #11527 when a user has `remote_models` disabled, as
we always use the default fallback `ModelInfo`. This causes issues with
model performance.
Builds on #11690, which helps by warning the user when they are using
the default fallback. This PR will make that happen much less frequently
as an accidental consequence of disabling `remote_models`.
### 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.
## Summary
Preserve the specified model slug when we get a prefix-based match
## Testing
- [x] added unit test
---------
Co-authored-by: Ahmed Ibrahim <aibrahim@openai.com>
## Why
`codex-core` was being built in multiple feature-resolved permutations
because test-only behavior was modeled as crate features. For a large
crate, those permutations increase compile cost and reduce cache reuse.
## Net Change
- Removed the `test-support` crate feature and related feature wiring so
`codex-core` no longer needs separate feature shapes for test consumers.
- Standardized cross-crate test-only access behind
`codex_core::test_support`.
- External test code now imports helpers from
`codex_core::test_support`.
- Underlying implementation hooks are kept internal (`pub(crate)`)
instead of broadly public.
## Outcome
- Fewer `codex-core` build permutations.
- Better incremental cache reuse across test targets.
- No intended production behavior change.
The dynamic model refresh feature (`https://api.openai.com/v1/models`
endpoint) is currently gated on a runtime check for an auth method other
than API Key. It should be gated on a check specifically for ChatGPT
Auth because some custom model providers (e.g. for local models) use no
auth mechanism. A call to `self.auth_manager.auth_mode()` will return
`None` in this case.
Addresses #11213
# 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.
Match model metadata by longest matching remote slug prefix before local
fallback.
- Update `get_model_info` to prefer the most specific remote slug prefix
for the requested model.
- Add an integration test to assert `gpt-5.3-codex-test` resolves to
`gpt-5.3-codex` over `gpt-5.3`.
So that the rest of the codebase (like TUI) don't need to be concerned
whether ChatGPT auth was handled by Codex itself or passed in via
app-server's external auth mode.
When using ChatGPT in names of types, we should be consistent, so this
renames some types with `ChatGpt` in the name to `Chatgpt`. From
https://rust-lang.github.io/api-guidelines/naming.html:
> In `UpperCamelCase`, acronyms and contractions of compound words count
as one word: use `Uuid` rather than `UUID`, `Usize` rather than `USize`
or `Stdin` rather than `StdIn`. In `snake_case`, acronyms and
contractions are lower-cased: `is_xid_start`.
This PR updates existing uses of `ChatGpt` and changes them to
`Chatgpt`. Though in all cases where it could affect the wire format, I
visually inspected that we don't change anything there. That said, this
_will_ change the codegen because it will affect the spelling of type
names.
For example, this renames `AuthMode::ChatGPT` to `AuthMode::Chatgpt` in
`app-server-protocol`, but the wire format is still `"chatgpt"`.
This PR also updates a number of types in `codex-rs/core/src/auth.rs`.
This enables a new use case where `codex app-server` is embedded into a
parent application that will directly own the user's ChatGPT auth
lifecycle, which means it owns the user’s auth tokens and refreshes it
when necessary. The parent application would just want a way to pass in
the auth tokens for codex to use directly.
The idea is that we are introducing a new "auth mode" currently only
exposed via app server: **`chatgptAuthTokens`** which consist of the
`id_token` (stores account metadata) and `access_token` (the bearer
token used directly for backend API calls). These auth tokens are only
stored in-memory. This new mode is in addition to the existing `apiKey`
and `chatgpt` auth modes.
This PR reuses the shape of our existing app-server account APIs as much
as possible:
- Update `account/login/start` with a new `chatgptAuthTokens` variant,
which will allow the client to pass in the tokens and have codex
app-server use them directly. Upon success, the server emits
`account/login/completed` and `account/updated` notifications.
- A new server->client request called
`account/chatgptAuthTokens/refresh` which the server can use whenever
the access token previously passed in has expired and it needs a new one
from the parent application.
I leveraged the core 401 retry loop which typically triggers auth token
refreshes automatically, but made it pluggable:
- **chatgpt** mode refreshes internally, as usual.
- **chatgptAuthTokens** mode calls the client via
`account/chatgptAuthTokens/refresh`, the client responds with updated
tokens, codex updates its in-memory auth, then retries. This RPC has a
10s timeout and handles JSON-RPC errors from the client.
Also some additional things:
- chatgpt logins are blocked while external auth is active (have to log
out first. typically clients will pick one OR the other, not support
both)
- `account/logout` clears external auth in memory
- Ensures that if `forced_chatgpt_workspace_id` is set via the user's
config, we respect it in both:
- `account/login/start` with `chatgptAuthTokens` (returns a JSON-RPC
error back to the client)
- `account/chatgptAuthTokens/refresh` (fails the turn, and on next
request app-server will send another `account/chatgptAuthTokens/refresh`
request to the client).
Keep an unmasked base collaboration mode and apply the active mask on
demand. Simplify the TUI mask helpers and update tests/docs to match the
mask contract.
We have `models.json` and `/models` response
Behavior:
1. New models from models endpoint gets added
2. Shared models get replaced by remote ones
3. Existing models in `models.json` but not `/models` are kept
4. Mark highest priority as default
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
Historically we started with a CodexAuth that knew how to refresh it's
own tokens and then added AuthManager that did a different kind of
refresh (re-reading from disk).
I don't think it makes sense for both `CodexAuth` and `AuthManager` to
be mutable and contain behaviors.
Move all refresh logic into `AuthManager` and keep `CodexAuth` as a data
object.
- Merge ModelFamily into ModelInfo
- Remove logic for adding instructions to apply patch
- Add compaction limit and visible context window to `ModelInfo`
With `config.toml`:
```
model = "gpt-5.1-codex"
```
(where `gpt-5.1-codex` has `show_in_picker: false` in
[`model_presets.rs`](https://github.com/openai/codex/blob/main/codex-rs/core/src/models_manager/model_presets.rs);
this happens if the user hasn't used codex in a while so they didn't see
the popup before their model was changed to `show_in_picker: false`)
The upgrade picker used to not show (because `gpt-5.1-codex` was
filtered out of the model list in code). Now, the filtering is done
downstream in tui and app-server, so the model upgrade popup shows:
<img width="1503" height="227" alt="Screenshot 2026-01-06 at 5 04 37 PM"
src="https://github.com/user-attachments/assets/26144cc2-0b3f-4674-ac17-e476781ec548"
/>
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.
Michael Bolin