Sets submodules to use workspace lints. Added denying unwrap as a
workspace level lint, which found a couple of cases where we could have
propagated errors. Also manually labeled ones that were fine by my eye.
This is the first step in supporting other model providers in the Rust
CLI. Specifically, this PR adds support for the new entries in `Config`
and `ConfigOverrides` to specify a `ModelProviderInfo`, which is the
basic config needed for an LLM provider. This PR does not get us all the
way there yet because `client.rs` still categorically appends
`/responses` to the URL and expects the endpoint to support the OpenAI
Responses API. Will fix that next!
I discovered that I accidentally introduced a change in
https://github.com/openai/codex/pull/829 where we load a fresh `Config`
in the middle of `codex.rs`:
c3e10e180a/codex-rs/core/src/codex.rs (L515-L522)
This is not good because the `Config` could differ from the one that has
the user's overrides specified from the CLI. Also, in unit tests, it
means the `Config` was picking up my personal settings as opposed to
using a vanilla config, which was problematic.
This PR cleans things up by moving the common case where
`Op::ConfigureSession` is derived from `Config` (originally done in
`codex_wrapper.rs`) and making it the standard way to initialize `Codex`
by putting it in `Codex::spawn()`. Note this also eliminates quite a bit
of boilerplate from the tests and relieves the caller of the
responsibility of minting out unique IDs when invoking `submit()`.
These abstractions were originally created exclusively for the REPL,
which was removed in https://github.com/openai/codex/pull/754.
Currently, the create some unnecessary Tokio tasks, so we are better off
without them. (We can always bring this back if we have a new use case.)
This adds support for saving transcripts when using the Rust CLI. Like
the TypeScript CLI, it saves the transcript to `~/.codex/sessions`,
though it uses JSONL for the file format (and `.jsonl` for the file
extension) so that even if Codex crashes, what was written to the
`.jsonl` file should generally still be valid JSONL content.
We now impose a 10s timeout on the initial `tools/list` request to an
MCP server. We do not apply a timeout for other types of requests yet,
but we should start enforcing those, as well.
This introduces the use of the `tui-markdown` crate to parse an
assistant message as Markdown and style it using ANSI for a better user
experience. As shown in the screenshot below, it has support for syntax
highlighting for _tagged_ fenced code blocks:
<img width="907" alt="image"
src="https://github.com/user-attachments/assets/900dc229-80bb-46e8-b1bb-efee4c70ba3c"
/>
That said, `tui-markdown` is not as configurable (or stylish!) as
https://www.npmjs.com/package/marked-terminal, which is what we use in
the TypeScript CLI. In particular:
* The styles are hardcoded and `tui_markdown::from_str()` does not take
any options whatsoever. It uses "bold white" for inline code style which
does not stand out as much as the yellow used by `marked-terminal`:
65402cbda7/tui-markdown/src/lib.rs (L464)
I asked Codex to take a first pass at this and it came up with:
https://github.com/joshka/tui-markdown/pull/80
* If a fenced code block is not tagged, then it does not get
highlighted. I would rather add some logic here:
65402cbda7/tui-markdown/src/lib.rs (L262)
that uses something like https://pypi.org/project/guesslang/ to examine
the value of `text` and try to use the appropriate syntax highlighter.
* When we have a fenced code block, we do not want to show the opening
and closing triple backticks in the output.
To unblock ourselves, we might want to bundle our own fork of
`tui-markdown` temporarily until we figure out what the shape of the API
should be and then try to upstream it.
