- create `codex-git-utils` and move the shared git helpers into it with
file moves preserved for diff readability
- move the `GitInfo` helpers out of `core` so stacked rollout work can
depend on the shared crate without carrying its own git info module
---------
Co-authored-by: Ahmed Ibrahim <219906144+aibrahim-oai@users.noreply.github.com>
Co-authored-by: Codex <noreply@openai.com>
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`.
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:
https://github.com/openai/codex/blob/774bd9e432fa2e0f4e059e97648cf92216912e19/codex-rs/core/src/config/mod.rs#L314-L324https://github.com/openai/codex/blob/774bd9e432fa2e0f4e059e97648cf92216912e19/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:
https://github.com/openai/codex/blob/774bd9e432fa2e0f4e059e97648cf92216912e19/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.
## 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.
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.
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
efrazer-oai ·
Ahmed Ibrahim ·
Michael Bolin ·
jif-oai ·
Celia Chen ·
Fouad Matin ·
easong-openai ·
Gabriel Peal ·
pakrym-oai ·