Codex created this PR from the following prompt:
> upgrade this entire repo to Rust 1.89. Note that this requires
updating codex-rs/rust-toolchain.toml as well as the workflows in
.github/. Make sure that things are "clippy clean" as this change will
likely uncover new Clippy errors. `just fmt` and `cargo clippy --tests`
are sufficient to check for correctness
Note this modifies a lot of lines because it folds nested `if`
statements using `&&`.
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with [ReviewStack](https://reviewstack.dev/openai/codex/pull/2465).
* #2467
* __->__ #2465
Updates the tokio task that monitors `shutdown_notify` and server
requests to ensure that `server.unblock()` is always called, which means
that `ShutdownHandle` only has to invoke `notify_waiters()`.
Now `LoginServer` no longer has to maintain a reference to `Server`. The
`Arc<Server>` only has two active references: the `thread::spawn()` for
reading server messages and the `tokio::task()` that consumes them (and
the shutdown message). Now when shutdown is called (or if login
completes successfully), the `server.unblock()` call ensures the thread
terminates cleanly, which in turn ensures `rx.recv()` in the
`tokio::spawn()` returns `Err`, causing the `tokio::task()` to exit
cleanly, as well.
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with [ReviewStack](https://reviewstack.dev/openai/codex/pull/2398).
* #2399
* __->__ #2398
* #2396
* #2395
* #2394
* #2393
* #2389
Folds the top-level `shutdown()` function into a method of
`ShutdownHandle` and then simply stores `ShutdownHandle` on
`LoginServer` since the two fields it contains were always being used
together, anyway.
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Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/2396).
* #2399
* #2398
* __->__ #2396
* #2395
* #2394
* #2393
* #2389
https://github.com/openai/codex/pull/2373 introduced
`ServerOptions.login_timeout` and `spawn_timeout_watcher()` to use an
extra thread to manage the timeout for the login server. Now that we
have asyncified the login stack, we can use `tokio::time::timeout()`
from "outside" the login library to manage the timeout rather than
having to a commit to a specific "timeout" concept from within.
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Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/2395).
* #2399
* #2398
* #2396
* __->__ #2395
* #2394
* #2393
* #2389
Prior to this PR, we had:
71cae06e66/codex-rs/login/src/server.rs (L141-L142)
which means that we could be blocked waiting for a new request in
`server_for_thread.recv()` and not notice that the state of
`shutdown_flag` had changed.
With this PR, we use `shutdown_flag: Notify` so that we can
`tokio::select!` on `shutdown_notify.notified()` and `rx.recv()` (which
is the "async stream" of requests read from `server_for_thread.recv()`)
and handle whichever one happens first.
---
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Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/2394).
* #2399
* #2398
* #2396
* #2395
* __->__ #2394
* #2393
* #2389
This PR adds two new APIs for the MCP server: 1) loginChatGpt, and 2)
cancelLoginChatGpt. The first starts a login server and returns a local
URL that allows for browser-based authentication, and the second
provides a way to cancel the login attempt. If the login attempt
succeeds, a notification (in the form of an event) is sent to a
subscriber.
I also added a timeout mechanism for the existing login server. The
loginChatGpt code path uses a 10-minute timeout by default, so if the
user fails to complete the login flow in that timeframe, the login
server automatically shuts down. I tested the timeout code by manually
setting the timeout to a much lower number and confirming that it works
as expected when used e2e.
