## Why
Once the repo-local lint exists, `codex-rs` needs to follow the
checked-in convention and CI needs to keep it from drifting. This commit
applies the fallback `/*param*/` style consistently across existing
positional literal call sites without changing those APIs.
The longer-term preference is still to avoid APIs that require comments
by choosing clearer parameter types and call shapes. This PR is
intentionally the mechanical follow-through for the places where the
existing signatures stay in place.
After rebasing onto newer `main`, the rollout also had to cover newly
introduced `tui_app_server` call sites. That made it clear the first cut
of the CI job was too expensive for the common path: it was spending
almost as much time installing `cargo-dylint` and re-testing the lint
crate as a representative test job spends running product tests. The CI
update keeps the full workspace enforcement but trims that extra
overhead from ordinary `codex-rs` PRs.
## What changed
- keep a dedicated `argument_comment_lint` job in `rust-ci`
- mechanically annotate remaining opaque positional literals across
`codex-rs` with exact `/*param*/` comments, including the rebased
`tui_app_server` call sites that now fall under the lint
- keep the checked-in style aligned with the lint policy by using
`/*param*/` and leaving string and char literals uncommented
- cache `cargo-dylint`, `dylint-link`, and the relevant Cargo
registry/git metadata in the lint job
- split changed-path detection so the lint crate's own `cargo test` step
runs only when `tools/argument-comment-lint/*` or `rust-ci.yml` changes
- continue to run the repo wrapper over the `codex-rs` workspace, so
product-code enforcement is unchanged
Most of the code changes in this commit are intentionally mechanical
comment rewrites or insertions driven by the lint itself.
## Verification
- `./tools/argument-comment-lint/run.sh --workspace`
- `cargo test -p codex-tui-app-server -p codex-tui`
- parsed `.github/workflows/rust-ci.yml` locally with PyYAML
---
* -> #14652
* #14651
- [x] Add tool_suggest tool.
- [x] Move chatgpt/src/connectors.rs and core/src/connectors.rs into a
dedicated mod so that we have all the logic and global cache in one
place.
- [x] Update TUI app link view to support rendering the installation
view for mcp elicitation.
---------
Co-authored-by: Shaqayeq <shaqayeq@openai.com>
Co-authored-by: Eric Traut <etraut@openai.com>
Co-authored-by: pakrym-oai <pakrym@openai.com>
Co-authored-by: Ahmed Ibrahim <aibrahim@openai.com>
Co-authored-by: guinness-oai <guinness@openai.com>
Co-authored-by: Eugene Brevdo <ebrevdo@users.noreply.github.com>
Co-authored-by: Charlie Guo <cguo@openai.com>
Co-authored-by: Fouad Matin <fouad@openai.com>
Co-authored-by: Fouad Matin <169186268+fouad-openai@users.noreply.github.com>
Co-authored-by: xl-openai <xl@openai.com>
Co-authored-by: alexsong-oai <alexsong@openai.com>
Co-authored-by: Owen Lin <owenlin0@gmail.com>
Co-authored-by: sdcoffey <stevendcoffey@gmail.com>
Co-authored-by: Codex <noreply@openai.com>
Co-authored-by: Won Park <won@openai.com>
Co-authored-by: Dylan Hurd <dylan.hurd@openai.com>
Co-authored-by: celia-oai <celia@openai.com>
Co-authored-by: gabec-openai <gabec@openai.com>
Co-authored-by: joeytrasatti-openai <joey.trasatti@openai.com>
Co-authored-by: Leo Shimonaka <leoshimo@openai.com>
Co-authored-by: Rasmus Rygaard <rasmus@openai.com>
Co-authored-by: maja-openai <163171781+maja-openai@users.noreply.github.com>
Co-authored-by: pash-openai <pash@openai.com>
Co-authored-by: Josh McKinney <joshka@openai.com>
## Note-- added plugin mentions via @, but that conflicts with file
mentions
depends and builds upon #13433.
- introduces explicit `@plugin` mentions. this injects the plugin's mcp
servers, app names, and skill name format into turn context as a dev
message.
- we do not yet have UI for these mentions, so we currently parse raw
text (as opposed to skills and apps which have UI chips, autocomplete,
etc.) this depends on a `plugins/list` app-server endpoint we can feed
the UI with, which is upcoming
- also annotate mcp and app tool descriptions with the plugin(s) they
come from. this gives the model a first class way of understanding what
tools come from which plugins, which will help implicit invocation.
### Tests
Added and updated tests, unit and integration. Also confirmed locally a
raw `@plugin` injects the dev message, and the model knows about its
apps, mcps, and skills.
load plugin-apps from `.app.json`.
make apps runtime-mentionable iff `codex_apps` MCP actually exposes
tools for that `connector_id`.
if the app isn't available, it's filtered out of runtime connector set,
so no tools are added and no app-mentions resolve.
right now we don't have a clean cli-side error for an app not being
installed. can look at this after.
### Tests
Added tests, tested locally that using a plugin that bundles an app
picks up the app.
We now write MCP tools from installed apps to disk cache so that they
can be picked up instantly at startup. We still do a fresh fetch from
remote MCP server but it's non blocking unless there's a cache miss.
- [x] Store apps tool cache in disk to reduce startup time.
When `app/list` is called with `force_refetch=True`, we should seed the
results with what is already cached instead of starting from an empty
list. Otherwise when we send app/list/updated events, the client will
first see an empty list of accessible apps and then get the updated one.
We are removing feature-gated shared crates from the `codex-rs`
workspace. `codex-common` grouped several unrelated utilities behind
`[features]`, which made dependency boundaries harder to reason about
and worked against the ongoing effort to eliminate feature flags from
workspace crates.
Splitting these utilities into dedicated crates under `utils/` aligns
this area with existing workspace structure and keeps each dependency
explicit at the crate boundary.
## What changed
- Removed `codex-rs/common` (`codex-common`) from workspace members and
workspace dependencies.
- Added six new utility crates under `codex-rs/utils/`:
- `codex-utils-cli`
- `codex-utils-elapsed`
- `codex-utils-sandbox-summary`
- `codex-utils-approval-presets`
- `codex-utils-oss`
- `codex-utils-fuzzy-match`
- Migrated the corresponding modules out of `codex-common` into these
crates (with tests), and added matching `BUILD.bazel` targets.
- Updated direct consumers to use the new crates instead of
`codex-common`:
- `codex-rs/cli`
- `codex-rs/tui`
- `codex-rs/exec`
- `codex-rs/app-server`
- `codex-rs/mcp-server`
- `codex-rs/chatgpt`
- `codex-rs/cloud-tasks`
- Updated workspace lockfile entries to reflect the new dependency graph
and removal of `codex-common`.
There are two concepts of apps that we load in the harness:
- Directory apps, which is all the apps that the user can install.
- Accessible apps, which is what the user actually installed and can be
$ inserted and be used by the model. These are extracted from the tools
that are loaded through the gateway MCP.
Previously we wait for both sets of apps before returning the full apps
list. Which causes many issues because accessible apps won't be
available to the UI or the model if directory apps aren't loaded or
failed to load.
In this PR we are separating them so that accessible apps can be loaded
separately and are instantly available to be shown in the UI and to be
provided in model context. We also added an app-server event so that
clients can subscribe to also get accessible apps without being blocked
on the full app list.
- [x] Separate accessible apps and directory apps loading.
- [x] `app/list` request will also emit `app/list/updated` notifications
that app-server clients can subscribe. Which allows clients to get
accessible apps list to render in the $ menu without being blocked by
directory apps.
- [x] Cache both accessible and directory apps with 1 hour TTL to avoid
reloading them when creating new threads.
- [x] TUI improvements to redraw $ menu and /apps menu when app list is
updated.
- [x] Support `/apps` slash command to browse the apps in tui.
- [x] Support inserting apps to prompt using `$`.
- [x] Lots of simplification/renaming from connectors to apps.
In order to make Codex work with connectors, we add a built-in gateway
MCP that acts as a transparent proxy between the client and the
connectors. The gateway MCP collects actions that are accessible to the
user and sends them down to the user, when a connector action is chosen
to be called, the client invokes the action through the gateway MCP as
well.
- [x] Add the system built-in gateway MCP to list and run connectors.
- [x] Add the app server methods and protocol
This PR configures Codex CLI so it can be built with
[Bazel](https://bazel.build) in addition to Cargo. The `.bazelrc`
includes configuration so that remote builds can be done using
[BuildBuddy](https://www.buildbuddy.io).
If you are familiar with Bazel, things should work as you expect, e.g.,
run `bazel test //... --keep-going` to run all the tests in the repo,
but we have also added some new aliases in the `justfile` for
convenience:
- `just bazel-test` to run tests locally
- `just bazel-remote-test` to run tests remotely (currently, the remote
build is for x86_64 Linux regardless of your host platform). Note we are
currently seeing the following test failures in the remote build, so we
still need to figure out what is happening here:
```
failures:
suite::compact::manual_compact_twice_preserves_latest_user_messages
suite::compact_resume_fork::compact_resume_after_second_compaction_preserves_history
suite::compact_resume_fork::compact_resume_and_fork_preserve_model_history_view
```
- `just build-for-release` to build release binaries for all
platforms/architectures remotely
To setup remote execution:
- [Create a buildbuddy account](https://app.buildbuddy.io/) (OpenAI
employees should also request org access at
https://openai.buildbuddy.io/join/ with their `@openai.com` email
address.)
- [Copy your API key](https://app.buildbuddy.io/docs/setup/) to
`~/.bazelrc` (add the line `build
--remote_header=x-buildbuddy-api-key=YOUR_KEY`)
- Use `--config=remote` in your `bazel` invocations (or add `common
--config=remote` to your `~/.bazelrc`, or use the `just` commands)
## CI
In terms of CI, this PR introduces `.github/workflows/bazel.yml`, which
uses Bazel to run the tests _locally_ on Mac and Linux GitHub runners
(we are working on supporting Windows, but that is not ready yet). Note
that the failures we are seeing in `just bazel-remote-test` do not occur
on these GitHub CI jobs, so everything in `.github/workflows/bazel.yml`
is green right now.
The `bazel.yml` uses extra config in `.github/workflows/ci.bazelrc` so
that macOS CI jobs build _remotely_ on Linux hosts (using the
`docker://docker.io/mbolin491/codex-bazel` Docker image declared in the
root `BUILD.bazel`) using cross-compilation to build the macOS
artifacts. Then these artifacts are downloaded locally to GitHub's macOS
runner so the tests can be executed natively. This is the relevant
config that enables this:
```
common:macos --config=remote
common:macos --strategy=remote
common:macos --strategy=TestRunner=darwin-sandbox,local
```
Because of the remote caching benefits we get from BuildBuddy, these new
CI jobs can be extremely fast! For example, consider these two jobs that
ran all the tests on Linux x86_64:
- Bazel 1m37s
https://github.com/openai/codex/actions/runs/20861063212/job/59940545209?pr=8875
- Cargo 9m20s
https://github.com/openai/codex/actions/runs/20861063192/job/59940559592?pr=8875
For now, we will continue to run both the Bazel and Cargo jobs for PRs,
but once we add support for Windows and running Clippy, we should be
able to cutover to using Bazel exclusively for PRs, which should still
speed things up considerably. We will probably continue to run the Cargo
jobs post-merge for commits that land on `main` as a sanity check.
Release builds will also continue to be done by Cargo for now.
Earlier attempt at this PR: https://github.com/openai/codex/pull/8832
Earlier attempt to add support for Buck2, now abandoned:
https://github.com/openai/codex/pull/8504
---------
Co-authored-by: David Zbarsky <dzbarsky@gmail.com>
Co-authored-by: Michael Bolin <mbolin@openai.com>
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.
To support Bazelification in https://github.com/openai/codex/pull/8875,
this PR introduces a new `find_resource!` macro that we use in place of
our existing logic in tests that looks for resources relative to the
compile-time `CARGO_MANIFEST_DIR` env var.
To make this work, we plan to add the following to all `rust_library()`
and `rust_test()` Bazel rules in the project:
```
rustc_env = {
"BAZEL_PACKAGE": native.package_name(),
},
```
Our new `find_resource!` macro reads this value via
`option_env!("BAZEL_PACKAGE")` so that the Bazel package _of the code
using `find_resource!`_ is injected into the code expanded from the
macro. (If `find_resource()` were a function, then
`option_env!("BAZEL_PACKAGE")` would always be
`codex-rs/utils/cargo-bin`, which is not what we want.)
Note we only consider the `BAZEL_PACKAGE` value when the `RUNFILES_DIR`
environment variable is set at runtime, indicating that the test is
being run by Bazel. In this case, we have to concatenate the runtime
`RUNFILES_DIR` with the compile-time `BAZEL_PACKAGE` value to build the
path to the resource.
In testing this change, I discovered one funky edge case in
`codex-rs/exec-server/tests/common/lib.rs` where we have to _normalize_
(but not canonicalize!) the result from `find_resource!` because the
path contains a `common/..` component that does not exist on disk when
the test is run under Bazel, so it must be semantically normalized using
the [`path-absolutize`](https://crates.io/crates/path-absolutize) crate
before it is passed to `dotslash fetch`.
Because this new behavior may be non-obvious, this PR also updates
`AGENTS.md` to make humans/Codex aware that this API is preferred.
This PR does various types of cleanup before I can proceed with more
ambitious changes to config loading.
First, I noticed duplicated code across these two methods:
774bd9e432/codex-rs/core/src/config/mod.rs (L314-L324)774bd9e432/codex-rs/core/src/config/mod.rs (L334-L344)
This has now been consolidated in
`load_config_as_toml_with_cli_overrides()`.
Further, I noticed that `Config::load_with_cli_overrides()` took two
similar arguments:
774bd9e432/codex-rs/core/src/config/mod.rs (L308-L311)
The difference between `cli_overrides` and `overrides` was not
immediately obvious to me. At first glance, it appears that one should
be able to be expressed in terms of the other, but it turns out that
some fields of `ConfigOverrides` (such as `cwd` and
`codex_linux_sandbox_exe`) are, by design, not configurable via a
`.toml` file or a command-line `--config` flag.
That said, I discovered that many callers of
`Config::load_with_cli_overrides()` were passing
`ConfigOverrides::default()` for `overrides`, so I created two separate
methods:
- `Config::load_with_cli_overrides(cli_overrides: Vec<(String,
TomlValue)>)`
- `Config::load_with_cli_overrides_and_harness_overrides(cli_overrides:
Vec<(String, TomlValue)>, harness_overrides: ConfigOverrides)`
The latter has a long name, as it is _not_ what should be used in the
common case, so the extra typing is designed to draw attention to this
fact. I tried to update the existing callsites to use the shorter name,
where possible.
Further, in the cases where `ConfigOverrides` is used, usually only a
limited subset of fields are actually set, so I updated the declarations
to leverage `..Default::default()` where possible.
This PR is a follow-up to #5591. It allows users to choose which auth
storage mode they want by using the new
`cli_auth_credentials_store_mode` config.
This PR introduces a new `Auth Storage` abstraction layer that takes
care of read, write, and load of auth tokens based on the
AuthCredentialsStoreMode. It is similar to how we handle MCP client
oauth
[here](https://github.com/openai/codex/blob/main/codex-rs/rmcp-client/src/oauth.rs).
Instead of reading and writing directly from disk for auth tokens, Codex
CLI workflows now should instead use this auth storage using the public
helper functions.
This PR is just a refactor of the current code so the behavior stays the
same. We will add support for keyring and hybrid mode in follow-up PRs.
I have read the CLA Document and I hereby sign the CLA
## Summary
- Factor `load_config_as_toml` into `core::config_loader` so config
loading is reusable across callers.
- Layer `~/.codex/config.toml`, optional `~/.codex/managed_config.toml`,
and macOS managed preferences (base64) with recursive table merging and
scoped threads per source.
## Config Flow
```
Managed prefs (macOS profile: com.openai.codex/config_toml_base64)
▲
│
~/.codex/managed_config.toml │ (optional file-based override)
▲
│
~/.codex/config.toml (user-defined settings)
```
- The loader searches under the resolved `CODEX_HOME` directory
(defaults to `~/.codex`).
- Managed configs let administrators ship fleet-wide overrides via
device profiles which is useful for enforcing certain settings like
sandbox or approval defaults.
- For nested hash tables: overlays merge recursively. Child tables are
merged key-by-key, while scalar or array values replace the prior layer
entirely. This lets admins add or tweak individual fields without
clobbering unrelated user settings.
This PR does the following:
* Adds the ability to paste or type an API key.
* Removes the `preferred_auth_method` config option. The last login
method is always persisted in auth.json, so this isn't needed.
* If OPENAI_API_KEY env variable is defined, the value is used to
prepopulate the new UI. The env variable is otherwise ignored by the
CLI.
* Adds a new MCP server entry point "login_api_key" so we can implement
this same API key behavior for the VS Code extension.
<img width="473" height="140" alt="Screenshot 2025-09-04 at 3 51 04 PM"
src="https://github.com/user-attachments/assets/c11bbd5b-8a4d-4d71-90fd-34130460f9d9"
/>
<img width="726" height="254" alt="Screenshot 2025-09-04 at 3 51 32 PM"
src="https://github.com/user-attachments/assets/6cc76b34-309a-4387-acbc-15ee5c756db9"
/>
The previous config approach had a few issues:
1. It is part of the config but not designed to be used externally
2. It had to be wired through many places (look at the +/- on this PR
3. It wasn't guaranteed to be set consistently everywhere because we
don't have a super well defined way that configs stack. For example, the
extension would configure during newConversation but anything that
happened outside of that (like login) wouldn't get it.
This env var approach is cleaner and also creates one less thing we have
to deal with when coming up with a better holistic story around configs.
One downside is that I removed the unit test testing for the override
because I don't want to deal with setting the global env or spawning
child processes and figuring out how to introspect their originator
header. The new code is sufficiently simple and I tested it e2e that I
feel as if this is still worth it.
this dramatically improves time to run `cargo test -p codex-core` (~25x
speedup).
before:
```
cargo test -p codex-core 35.96s user 68.63s system 19% cpu 8:49.80 total
```
after:
```
cargo test -p codex-core 5.51s user 8.16s system 63% cpu 21.407 total
```
both tests measured "hot", i.e. on a 2nd run with no filesystem changes,
to exclude compile times.
approach inspired by [Delete Cargo Integration
Tests](https://matklad.github.io/2021/02/27/delete-cargo-integration-tests.html),
we move all test cases in tests/ into a single suite in order to have a
single binary, as there is significant overhead for each test binary
executed, and because test execution is only parallelized with a single
binary.
Motivation: we have users who uses their API key although they want to
use ChatGPT account. We want to give them the chance to always login
with their account.
This PR displays login options when the user is not signed in with
ChatGPT. Even if you have set an OpenAI API key as an environment
variable, you will still be prompted to log in with ChatGPT.
We’ve also added a new flag, `always_use_api_key_signing` false by
default, which ensures you are never asked to log in with ChatGPT and
always defaults to using your API key.
https://github.com/user-attachments/assets/b61ebfa9-3c5e-4ab7-bf94-395c23a0e0af
After ChatGPT sign in:
https://github.com/user-attachments/assets/d58b366b-c46a-428f-a22f-2ac230f991c0
This PR:
* Added the clippy.toml to configure allowable expect / unwrap usage in
tests
* Removed as many expect/allow lines as possible from tests
* moved a bunch of allows to expects where possible
Note: in integration tests, non `#[test]` helper functions are not
covered by this so we had to leave a few lingering `expect(expect_used`
checks around
There are two valid ways to create an instance of `CodexAuth`:
`from_api_key()` and `from_codex_home()`. Now both are static methods of
`CodexAuth` and are listed first in the implementation.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/1966).
* #1971
* #1970
* __->__ #1966
* #1965
* #1962
the git tests were failing on my local machine due to gpg signing config
in my ~/.gitconfig. tests should not be affected by ~/.gitconfig, so
configure them to ignore it.
Adds a `CodexAuth` type that encapsulates information about available
auth modes and logic for refreshing the token.
Changes `Responses` API to send requests to different endpoints based on
the auth type.
Updates login_with_chatgpt to support API-less mode and skip the key
exchange.
In order to to this, I created a new `chatgpt` crate where we can put
any code that interacts directly with ChatGPT as opposed to the OpenAI
API. I added a disclaimer to the README for it that it should primarily
be modified by OpenAI employees.
https://github.com/user-attachments/assets/bb978e33-d2c9-4d8e-af28-c8c25b1988e8
