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.
This adds a tool the model can call to update a plan. The tool doesn't
actually _do_ anything but it gives clients a chance to read and render
the structured plan. We will likely iterate on the prompt and tools
exposed for planning over time.
see
[discussion](https://github.com/rhysd/tui-textarea/issues/51#issuecomment-3021191712),
it's surprising that ^U behaves this way. IMO the undo/redo
functionality in tui-textarea isn't good enough to be worth preserving,
but if we do bring it back it should probably be on C-z / C-S-z / C-y.
Perhaps there was an intention to make the login screen prettier, but it
feels quite silly right now to just have a screen that says "press q",
so replace it with something that lets the user directly login without
having to quit the app.
<img width="1283" height="635" alt="Screenshot 2025-07-28 at 2 54 05 PM"
src="https://github.com/user-attachments/assets/f19e5595-6ef9-4a2d-b409-aa61b30d3628"
/>
## Summary
Per the [latest MCP
spec](https://modelcontextprotocol.io/specification/2025-06-18/basic#meta),
the `_meta` field is reserved for metadata. In the [Typescript
Schema](0695a497eb/schema/2025-06-18/schema.ts (L37-L40)),
`progressToken` is defined as a value to be attached to subsequent
notifications for that request.
The
[CallToolRequestParams](0695a497eb/schema/2025-06-18/schema.ts (L806-L817))
extends this definition but overwrites the params field. This ambiguity
makes our generated type definitions tricky, so I'm going to skip
`progressToken` field for now and just send back the `requestId`
instead.
In a future PR, we can clarify, update our `generate_mcp_types.py`
script, and update our progressToken logic accordingly.
## Testing
- [x] Added unit tests
- [x] Manually tested with mcp client
(Hopefully) temporary solution to the invisible approvals problem -
prints commands to history when they need approval and then also prints
the result of the approval. In the near future we should be able to do
some fancy stuff with updating commands before writing them to permanent
history.
Also, ctr-c while in the approval modal now acts as esc (aborts command)
and puts the TUI in the state where one additional ctr-c will exit.
This is a straight refactor, moving apply-patch-related code from
`codex.rs` and into the new `apply_patch.rs` file. The only "logical"
change is inlining `#[allow(clippy::unwrap_used)]` instead of declaring
`#![allow(clippy::unwrap_used)]` at the top of the file (which is
currently the case in `codex.rs`).
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/1703).
* #1705
* __->__ #1703
* #1702
* #1698
* #1697
This introduces some special behavior to the CLIs that are using the
`codex-arg0` crate where if `arg1` is `--codex-run-as-apply-patch`, then
it will run as if `apply_patch arg2` were invoked. This is important
because it means we can do things like:
```
SANDBOX_TYPE=landlock # or seatbelt for macOS
codex debug "${SANDBOX_TYPE}" -- codex --codex-run-as-apply-patch PATCH
```
which gives us a way to run `apply_patch` while ensuring it adheres to
the sandbox the user specified.
While it would be nice to use the `arg0` trick like we are currently
doing for `codex-linux-sandbox`, there is no way to specify the `arg0`
for the underlying command when running under `/usr/bin/sandbox-exec`,
so it will not work for us in this case.
Admittedly, we could have also supported this via a custom environment
variable (e.g., `CODEX_ARG0`), but since environment variables are
inherited by child processes, that seemed like a potentially leakier
abstraction.
This change, as well as our existing reliance on checking `arg0`, place
additional requirements on those who include `codex-core`. Its
`README.md` has been updated to reflect this.
While we could have just added an `apply-patch` subcommand to the
`codex` multitool CLI, that would not be sufficient for the standalone
`codex-exec` CLI, which is something that we distribute as part of our
GitHub releases for those who know they will not be using the TUI and
therefore prefer to use a slightly smaller executable:
https://github.com/openai/codex/releases/tag/rust-v0.10.0
To that end, this PR adds an integration test to ensure that the
`--codex-run-as-apply-patch` option works with the standalone
`codex-exec` CLI.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/1702).
* #1705
* #1703
* __->__ #1702
* #1698
* #1697
The overall idea here is: skip ratatui for writing into scrollback,
because its primitives are wrong. We want to render full lines of text,
that will be wrapped natively by the terminal, and which we never plan
to update using ratatui (so the `Buffer` struct is overhead and in fact
an inhibition).
Instead, we use ANSI scrolling regions (link reference doc to come).
Essentially, we:
1. Define a scrolling region that extends from the top of the prompt
area all the way to the top of scrollback
2. Scroll that region up by N < (screen_height - viewport_height) lines,
in this PR N=1
3. Put our cursor at the top of the newly empty region
4. Print out our new text like normal
The terminal interactions here (write_spans and its dependencies) are
mostly extracted from ratatui.
Most of the time, we expect the `String` returned by
`serde_json::to_string()` to have extra capacity, so `push('\n')` is
unlikely to allocate, which seems cheaper than an extra `write(2)` call,
on average?
This update replaces the previous ratatui history widget with an
append-only log so that the terminal can handle text selection and
scrolling. It also disables streaming responses, which we'll do our best
to bring back in a later PR. It also adds a small summary of token use
after the TUI exits.
Currently, codex on start shows the value for the approval policy as
name of
[AskForApproval](2437a8d17a/codex-rs/core/src/protocol.rs (L128))
enum, which differs from
[approval_policy](2437a8d17a/codex-rs/config.md (approval_policy))
config values.
E.g. "untrusted" becomes "UnlessTrusted", "on-failure" -> "OnFailure",
"never" -> "Never".
This PR changes render names of the approval policy to match with
configuration values.
This PR updates `is_known_safe_command()` to account for "safe
operators" to expand the set of commands that can be run without
approval. This concept existed in the TypeScript CLI, and we are
[finally!] porting it to the Rust one:
c9e2def494/codex-cli/src/approvals.ts (L531-L541)
The idea is that if we have `EXPR1 SAFE_OP EXPR2` and `EXPR1` and
`EXPR2` are considered safe independently, then `EXPR1 SAFE_OP EXPR2`
should be considered safe. Currently, `SAFE_OP` includes `&&`, `||`,
`;`, and `|`.
In the TypeScript implementation, we relied on
https://www.npmjs.com/package/shell-quote to parse the string of Bash,
as it could provide a "lightweight" parse tree, parsing `'beep || boop >
/byte'` as:
```
[ 'beep', { op: '||' }, 'boop', { op: '>' }, '/byte' ]
```
Though in this PR, we introduce the use of
https://crates.io/crates/tree-sitter-bash for parsing (which
incidentally we were already using in
[`codex-apply-patch`](c9e2def494/codex-rs/apply-patch/Cargo.toml (L18))),
which gives us a richer parse tree. (Incidentally, if you have never
played with tree-sitter, try the
[playground](https://tree-sitter.github.io/tree-sitter/7-playground.html)
and select **Bash** from the dropdown to see how it parses various
expressions.)
As a concrete example, prior to this change, our implementation of
`is_known_safe_command()` could verify things like:
```
["bash", "-lc", "grep -R \"Cargo.toml\" -n"]
```
but not:
```
["bash", "-lc", "grep -R \"Cargo.toml\" -n || true"]
```
With this change, the version with `|| true` is also accepted.
Admittedly, this PR does not expand the safety check to support
subshells, so it would reject, e.g. `bash -lc 'ls || (pwd && echo hi)'`,
but that can be addressed in a subsequent PR.
`nl` is a line-numbering tool that should be on the _trusted _ list, as
there is nothing concerning on https://gtfobins.github.io/gtfobins/nl/
that would merit exclusion.
`true` and `false` are also safe, though not particularly useful given
how `is_known_safe_command()` works today, but that will change with
https://github.com/openai/codex/pull/1668.
Because of a quirk of how implementation tests work in Rust, we had a
number of `#[allow(dead_code)]` annotations that were misleading because
the functions _were_ being used, just not by all integration tests in a
`tests/` folder, so when compiling the test that did not use the
function, clippy would complain that it was unused.
This fixes things by create a "test_support" crate under the `tests/`
folder that is imported as a dev dependency for the respective crate.
# Summary
- Writing effective evals for codex sessions requires context of the
overall repository state at the moment the session began
- This change adds this metadata (git repository, branch, commit hash)
to the top of the rollout of the session (if available - if not it
doesn't add anything)
- Currently, this is only effective on a clean working tree, as we can't
track uncommitted/untracked changes with the current metadata set.
Ideally in the future we may want to track unclean changes somehow, or
perhaps prompt the user to stash or commit them.
# Testing
- Added unit tests
- `cargo test && cargo clippy --tests && cargo fmt -- --config
imports_granularity=Item`
### Resulting Rollout
<img width="1243" height="127" alt="Screenshot 2025-07-17 at 1 50 00 PM"
src="https://github.com/user-attachments/assets/68108941-f015-45b2-985c-ea315ce05415"
/>
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1. Emit call_id to exec approval elicitations for mcp client convenience
2. Remove the `-retry` from the call id for the same reason as above but
upstream the reset behavior to the mcp client
Always store the entire conversation history.
Request encrypted COT when not storing Responses.
Send entire input context instead of sending previous_response_id
This PR adds a `load_dotenv()` helper function to the `codex-common`
crate that is available when the `cli` feature is enabled. The function
uses [`dotenvy`](https://crates.io/crates/dotenvy) to update the
environment from:
- `$CODEX_HOME/.env`
- `$(pwd)/.env`
To test:
- ran `printenv OPENAI_API_KEY` to verify the env var exists in my
environment
- ran `just codex exec hello` to verify the CLI uses my `OPENAI_API_KEY`
- ran `unset OPENAI_API_KEY`
- ran `just codex exec hello` again and got **ERROR: Missing environment
variable: `OPENAI_API_KEY`**, as expected
- created `~/.codex/.env` and added `OPENAI_API_KEY=sk-proj-...` (also
ran `chmod 400 ~/.codex/.env` for good measure)
- ran `just codex exec hello` again and it worked, verifying it picked
up `OPENAI_API_KEY` from `~/.codex/.env`
Note this functionality was available in the TypeScript CLI:
https://github.com/openai/codex/pull/122 and was recently requested over
on https://github.com/openai/codex/issues/1262#issuecomment-3093203551.
I noticed that releases have taken longer and longer to build.
Originally, I think I did `--all-targets` to be confident that
everything builds cleanly, but that's really the job of CI that runs on
`main`, so we're spending a lot of time in `rust-release.yml` for not
that much additional signal.
Some users have reported issues where child processes are not cleaned up
after Codex exits (e.g., https://github.com/openai/codex/issues/1570).
This is generally a tricky issue on operating systems: if a parent
process receives `SIGKILL`, then it terminates immediately and cannot
communicate with the child.
**It only helps on Linux**, but this PR introduces the use of `prctl(2)`
so that if the parent process dies, `SIGTERM` will be delivered to the
child process. Whereas previously, I believe that if Codex spawned a
long-running process (like `tsc --watch`) and the Codex process received
`SIGKILL`, the `tsc --watch` process would be reparented to the init
process and would never be killed. Now with the use of `prctl(2)`, the
`tsc --watch` process should receive `SIGTERM` in that scenario.
We still need to come up with a solution for macOS. I've started to look
at `launchd`, but I'm researching a number of options.
1. Added an elicitation for `approve-patch` which is very similar to
`approve-exec`.
2. Extracted both elicitations to their own files to prevent
`codex_tool_runner` from blowing up in size.
## Summary
Adds a new mcp tool call, `codex-reply`, so we can continue existing
sessions. This is a first draft and does not yet support sessions from
previous processes.
## Testing
- [x] tested with mcp client
This PR introduces a single integration test for `cargo mcp`, though it
also introduces a number of reusable components so that it should be
easier to introduce more integration tests going forward.
The new test is introduced in `codex-rs/mcp-server/tests/elicitation.rs`
and the reusable pieces are in `codex-rs/mcp-server/tests/common`.
The test itself verifies new functionality around elicitations
introduced in https://github.com/openai/codex/pull/1623 (and the fix
introduced in https://github.com/openai/codex/pull/1629) by doing the
following:
- starts a mock model provider with canned responses for
`/v1/chat/completions`
- starts the MCP server with a `config.toml` to use that model provider
(and `approval_policy = "untrusted"`)
- sends the `codex` tool call which causes the mock model provider to
request a shell call for `git init`
- the MCP server sends an elicitation to the client to approve the
request
- the client replies to the elicitation with `"approved"`
- the MCP server runs the command and re-samples the model, getting a
`"finish_reason": "stop"`
- in turn, the MCP server sends the final response to the original
`codex` tool call
- verifies that `git init` ran as expected
To test:
```
cargo test shell_command_approval_triggers_elicitation
```
In writing this test, I discovered that `ExecApprovalResponse` does not
conform to `ElicitResult`, so I added a TODO to fix that, since I think
that should be updated in a separate PR. As it stands, this PR does not
update any business logic, though it does make a number of members of
the `mcp-server` crate `pub` so they can be used in the test.
One additional learning from this PR is that
`std::process::Command::cargo_bin()` from the `assert_cmd` trait is only
available for `std::process::Command`, but we really want to use
`tokio::process::Command` so that everything is async and we can
leverage utilities like `tokio::time::timeout()`. The trick I came up
with was to use `cargo_bin()` to locate the program, and then to use
`std::process::Command::get_program()` when constructing the
`tokio::process::Command`.
This updates the MCP server so that if it receives an
`ExecApprovalRequest` from the `Codex` session, it in turn sends an [MCP
elicitation](https://modelcontextprotocol.io/specification/draft/client/elicitation)
to the client to ask for the approval decision. Upon getting a response,
it forwards the client's decision via `Op::ExecApproval`.
Admittedly, we should be doing the same thing for
`ApplyPatchApprovalRequest`, but this is our first time experimenting
with elicitations, so I'm inclined to defer wiring that code path up
until we feel good about how this one works.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/1623).
* __->__ #1623
* #1622
* #1621
* #1620
Previous to this change, `MessageProcessor` had a
`tokio::sync::mpsc::Sender<JSONRPCMessage>` as an abstraction for server
code to send a message down to the MCP client. Because `Sender` is cheap
to `clone()`, it was straightforward to make it available to tasks
scheduled with `tokio::task::spawn()`.
This worked well when we were only sending notifications or responses
back down to the client, but we want to add support for sending
elicitations in #1623, which means that we need to be able to send
_requests_ to the client, and now we need a bit of centralization to
ensure all request ids are unique.
To that end, this PR introduces `OutgoingMessageSender`, which houses
the existing `Sender<OutgoingMessage>` as well as an `AtomicI64` to mint
out new, unique request ids. It has methods like `send_request()` and
`send_response()` so that callers do not have to deal with
`JSONRPCMessage` directly, as having to set the `jsonrpc` for each
message was a bit tedious (this cleans up `codex_tool_runner.rs` quite a
bit).
We do not have `OutgoingMessageSender` implement `Clone` because it is
important that the `AtomicI64` is shared across all users of
`OutgoingMessageSender`. As such, `Arc<OutgoingMessageSender>` must be
used instead, as it is frequently shared with new tokio tasks.
As part of this change, we update `message_processor.rs` to embrace
`await`, though we must be careful that no individual handler blocks the
main loop and prevents other messages from being handled.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/1622).
* #1623
* __->__ #1622
* #1621
* #1620
This updates the schema in `generate_mcp_types.py` from `2025-03-26` to
`2025-06-18`, regenerates `mcp-types/src/lib.rs`, and then updates all
the code that uses `mcp-types` to honor the changes.
Ran
```
npx @modelcontextprotocol/inspector just codex mcp
```
and verified that I was able to invoke the `codex` tool, as expected.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/1621).
* #1623
* #1622
* __->__ #1621
## Summary
- extend rollout format to store all session data in JSON
- add resume/write helpers for rollouts
- track session state after each conversation
- support `LoadSession` op to resume a previous rollout
- allow starting Codex with an existing session via
`experimental_resume` config variable
We need a way later for exploring the available sessions in a user
friendly way.
## Testing
- `cargo test --no-run` *(fails: `cargo: command not found`)*
------
https://chatgpt.com/codex/tasks/task_i_68792a29dd5c832190bf6930d3466fba
This video is outdated. you should use `-c experimental_resume:<full
path>` instead of `--resume <full path>`
https://github.com/user-attachments/assets/7a9975c7-aa04-4f4e-899a-9e87defd947a
## Summary
- add OpenAI retry and timeout fields to Config
- inject these settings in tests instead of mutating env vars
- plumb Config values through client and chat completions logic
- document new configuration options
## Testing
- `cargo test -p codex-core --no-run`
------
https://chatgpt.com/codex/tasks/task_i_68792c5b04cc832195c03050c8b6ea94
---------
Co-authored-by: Michael Bolin <mbolin@openai.com>
This is designed to facilitate programmatic use of Codex in a more
lightweight way than using `codex mcp`.
Passing `--json` to `codex exec` will print each event as a line of JSON
to stdout. Note that it does not print the individual tokens as they are
streamed, only full messages, as this is aimed at programmatic use
rather than to power UI.
<img width="1348" height="1307" alt="image"
src="https://github.com/user-attachments/assets/fc7908de-b78d-46e4-a6ff-c85de28415c7"
/>
I changed the existing `EventProcessor` into a trait and moved the
implementation to `EventProcessorWithHumanOutput`. Then I introduced an
alternative implementation, `EventProcessorWithJsonOutput`. The `--json`
flag determines which implementation to use.
Adds a default vscode config with generally applicable settings.
Adds more entrypoints to justfile both for environment setup and to help
agents better verify changes.
When Codex CLI is installed via `npm`, we use a `.js` wrapper script to
launch the Rust binary.
- Previously, we were not listening for signals to ensure that killing
the Node.js process would also kill the underlying Rust process.
- We also did not have a proper `exit` handler in place on the child
process to ensure we exited from the Node.js process.
This PR fixes these things and hopefully addresses
https://github.com/openai/codex/issues/1570.
This also adds logic so that Windows falls back to the TypeScript CLI
again, which should address https://github.com/openai/codex/issues/1573.
This PR implements server name validation for MCP (Model Context
Protocol) servers to ensure they conform to the required pattern
^[a-zA-Z0-9_-]+$. This addresses the TODO comment in
mcp_connection_manager.rs:82.
+ Added validation before spawning MCP client tasks
+ Invalid server names are added to errors map with descriptive messages
I have read the CLA Document and I hereby sign the CLA
---------
Co-authored-by: Michael Bolin <bolinfest@gmail.com>
- Added support for message and reasoning deltas
- Skipped adding the support in the cli and tui for later
- Commented a failing test (wrong merge) that needs fix in a separate
PR.
Side note: I think we need to disable merge when the CI don't pass.
While this does make it so that `ctrl-d` will not exit Codex when the
composer is not empty, `ctrl-d` will still exit Codex if it is in the
"working" state.
Fixes https://github.com/openai/codex/issues/1443.
It appears that `0.5.0` was built with `stage_release.sh` instead of
`stage_rust_release.py`, so add docs to clarify this and recommend
running `--version` on the release candidate to verify the right thing
was built.
## Summary
- add integration test for chat mode streaming via CLI using wiremock
- add integration test for Responses API streaming via fixture
- call `cargo run` to invoke the CLI during tests
## Testing
- `cargo test -p codex-core --test cli_stream -- --nocapture`
- `cargo clippy --all-targets --all-features -- -D warnings`
------
https://chatgpt.com/codex/tasks/task_i_68715980bbec8321999534fdd6a013c1
[](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores)
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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
https://github.com/openai/codex/pull/1524 introduced the new `config`
field on `ModelClient`, so this does the post-PR cleanup to remove the
now-unnecessary `model` field.
As noted in the updated docs, this makes it so that you can set:
```toml
model_supports_reasoning_summaries = true
```
as a way of overriding the existing heuristic for when to set the
`reasoning` field on a sampling request:
341c091c5b/codex-rs/core/src/client_common.rs (L152-L166)
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Bumps node from 22-slim to 24-slim.
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Bumps [toml](https://github.com/toml-rs/toml) from 0.9.0 to 0.9.1.
<details>
<summary>Commits</summary>
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<li><a
href="8c8ef44ea1"><code>8c8ef44</code></a>
chore: Release</li>
<li><a
href="b60ac5bfe9"><code>b60ac5b</code></a>
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<li><a
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## Summary
Add Android platform support to Codex CLI
## What?
- Added `android` to the list of supported platforms in
`codex-cli/bin/codex.js`
- Treats Android as Linux for binary compatibility
## Why?
- Fixes "Unsupported platform: android (arm64)" error on Termux
- Enables Codex CLI usage on Android devices via Termux
- Improves platform compatibility without affecting other platforms
## How?
- Modified the platform detection switch statement to include `case
"android":`
- Android falls through to the same logic as Linux, using appropriate
ARM64 binaries
- Minimal change with no breaking effects on existing functionality
## Testing
- Tested on Android/Termux environment
- Verified the fix resolves the platform detection error
- Confirmed no impact on other platforms
## Related Issues
Fixes the "Unsupported platform: android (arm64)" error reported by
Termux users
Current 0.4.0 release:
```
~/code/codex2/codex-rs$ codex completion | head
_codex-cli() {
local i cur prev opts cmd
COMPREPLY=()
if [[ "${BASH_VERSINFO[0]}" -ge 4 ]]; then
cur="$2"
else
cur="${COMP_WORDS[COMP_CWORD]}"
fi
prev="$3"
cmd=""
```
with this change:
```
~/code/codex2/codex-rs$ just codex completion | head
cargo run --bin codex -- "$@"
Finished `dev` profile [unoptimized + debuginfo] target(s) in 0.82s
Running `target/debug/codex completion`
_codex() {
local i cur prev opts cmd
COMPREPLY=()
if [[ "${BASH_VERSINFO[0]}" -ge 4 ]]; then
cur="$2"
else
cur="${COMP_WORDS[COMP_CWORD]}"
fi
prev="$3"
cmd=""
```
Some users have proxies or other setups where they are ultimately
hitting OpenAI endpoints, but need a custom `base_url` rather than the
default value of `"https://api.openai.com/v1"`. This PR makes it
possible to override the `base_url` for the `openai` provider via the
`OPENAI_BASE_URL` environment variable.
This is a stopgap solution before migrating the build for the npm
release to GitHub Actions (which is ultimately what should be done to
ensure hermetic builds).
The idea is that instead of continuing to create PRs like
https://github.com/openai/codex/pull/1472 where I have to check in a
change to the `WORKFLOW_URL`, this script uses `gh run list` to get the
`WORKFLOW_URL` dynamically and then threads the value through to
`install_native_deps.sh`.
To create the 0.3.0 release on npm, I ran:
```shell
./codex-cli/scripts/stage_rust_release.py --release-version 0.3.0
```
and then did `npm publish --dry-run` followed by `npm publish` in the
temp directory created by `stage_rust_release.py`.
On a high-level, we try to design `config.toml` so that you don't have
to "comment out a lot of stuff" when testing different options.
Previously, defining a sandbox policy was somewhat at odds with this
principle because you would define the policy as attributes of
`[sandbox]` like so:
```toml
[sandbox]
mode = "workspace-write"
writable_roots = [ "/tmp" ]
```
but if you wanted to temporarily change to a read-only sandbox, you
might feel compelled to modify your file to be:
```toml
[sandbox]
mode = "read-only"
# mode = "workspace-write"
# writable_roots = [ "/tmp" ]
```
Technically, commenting out `writable_roots` would not be strictly
necessary, as `mode = "read-only"` would ignore `writable_roots`, but
it's still a reasonable thing to do to keep things tidy.
Currently, the various values for `mode` do not support that many
attributes, so this is not that hard to maintain, but one could imagine
this becoming more complex in the future.
In this PR, we change Codex CLI so that it no longer recognizes
`[sandbox]`. Instead, it introduces a top-level option, `sandbox_mode`,
and `[sandbox_workspace_write]` is used to further configure the sandbox
when when `sandbox_mode = "workspace-write"` is used:
```toml
sandbox_mode = "workspace-write"
[sandbox_workspace_write]
writable_roots = [ "/tmp" ]
```
This feels a bit more future-proof in that it is less tedious to
configure different sandboxes:
```toml
sandbox_mode = "workspace-write"
[sandbox_read_only]
# read-only options here...
[sandbox_workspace_write]
writable_roots = [ "/tmp" ]
[sandbox_danger_full_access]
# danger-full-access options here...
```
In this scheme, you never need to comment out the configuration for an
individual sandbox type: you only need to redefine `sandbox_mode`.
Relatedly, previous to this change, a user had to do `-c
sandbox.mode=read-only` to change the mode on the command line. With
this change, things are arguably a bit cleaner because the equivalent
option is `-c sandbox_mode=read-only` (and now `-c
sandbox_workspace_write=...` can be set separately).
Though more importantly, we introduce the `-s/--sandbox` option to the
CLI, which maps directly to `sandbox_mode` in `config.toml`, making
config override behavior easier to reason about. Moreover, as you can
see in the updates to the various Markdown files, it is much easier to
explain how to configure sandboxing when things like `--sandbox
read-only` can be used as an example.
Relatedly, this cleanup also made it straightforward to add support for
a `sandbox` option for Codex when used as an MCP server (see the changes
to `mcp-server/src/codex_tool_config.rs`).
Fixes https://github.com/openai/codex/issues/1248.
v0.2.0 of https://www.npmjs.com/package/@openai/codex now runs the Rust
CLI, so it makes sense to bring back the instructions to use `npm i -g
@openai/codex`.
In most places, I list `npm install` before `brew install` because I
believe `npm` is more readily available, though I in the more detailed
part of the documentation, I note that `brew install` will download
fewer bytes, and in that sense, is preferred.
This adds support for two new model provider config options:
- `http_headers` for hardcoded (key, value) pairs
- `env_http_headers` for headers whose values should be read from
environment variables
This also updates the built-in `openai` provider to use this feature to
set the following headers:
- `originator` => `codex_cli_rs`
- `version` => [CLI version]
- `OpenAI-Organization` => `OPENAI_ORGANIZATION` env var
- `OpenAI-Project` => `OPENAI_PROJECT` env var
for consistency with the TypeScript implementation:
bd5a9e8ba9/codex-cli/src/utils/agent/agent-loop.ts (L321-L329)
While here, this also consolidates some logic that was duplicated across
`client.rs` and `chat_completions.rs` by introducing
`ModelProviderInfo.create_request_builder()`.
Resolves https://github.com/openai/codex/discussions/1152
This introduces two changes to make a quick fix so we can deploy the
Rust CLI for `0.2.0` of `@openai/codex` on npm:
- Updates `WORKFLOW_URL` to point to
https://github.com/openai/codex/actions/runs/15981617627, which is the
GitHub workflow run used to create the binaries for the `0.2.0` release
we published to Homebrew.
- Adds a `--version` option to `stage_release.sh` to specify what the
`version` field in the `package.json` will be.
Locally, I ran the following:
```
./codex-cli/scripts/stage_release.sh --native --version 0.2.0
```
Previously, we only used the `--native` flag to publish to the `native`
tag of `@openai/codex` (e.g., `npm publish --tag native`), but we should
just publish this as the default tag for `0.2.0` to be consistent with
what is in Homebrew.
We can still publish one "final" version of the TypeScript CLI as 0.1.x
later.
Under the hood, this release will still contain `dist/cli.js`,
`bin/codex-linux-sandbox-x64`, and `bin/codex-x86_64-apple-darwin`,
which are not strictly necessary, but we'll fix that in `0.3.0`.
As promised on https://github.com/openai/codex/discussions/1405, we are
making the first official release of the Rust CLI as v0.2.0. As part of
this move, we are making it available in Homebrew:
https://github.com/Homebrew/homebrew-core/pull/228615
Ultimately, we also plan to continue to make the CLI available in npm,
as well, though brew is a bit nicer in that `brew install` will download
only the binary for your platform whereas an npm module is expected to
contain the binaries for _all_ supported platforms, so it is a bit more
heavyweight.
A big part of this change is updating the root `README.md` to document
the behavior of the Rust CLI, which differs in a number of ways from the
TypeScript CLI. The existing `README.md` is moved to
`codex-cli/README.md` as part of this PR, as it is still applicable to
that folder.
As this is still early days for the Rust CLI, I encourage folks to
provide feedback on the command line flags and configuration options.
As discovered in https://github.com/openai/codex/issues/1365, the Azure
provider needs to be able to specify `api-version` as a query param, so
this PR introduces a generic `query_params` option to the
`model_providers` config so that an Azure provider can be defined as
follows:
```toml
[model_providers.azure]
name = "Azure"
base_url = "https://YOUR_PROJECT_NAME.openai.azure.com/openai"
env_key = "AZURE_OPENAI_API_KEY"
query_params = { api-version = "2025-04-01-preview" }
```
This PR also updates the docs with this example.
While here, we also update `wire_api` to default to `"chat"`, as that is
likely the common case for someone defining an external provider.
Fixes https://github.com/openai/codex/issues/1365.
Looking at existing releases such as
https://github.com/openai/codex/releases/tag/codex-rs-b289c9207090b2e27494545d7b5404e063bd86f3-1-rust-v0.1.0-alpha.4,
the `.tar.gz` for the source code still seems to have `0.0.0` as the
`version` in `codex-rs/Cargo.toml` instead of what the tag seems to say
it should have:
b289c92070/codex-rs/Cargo.toml (L21)
ChatGPT claims:
> When GitHub generates the Source code (tar.gz) archive for a tag:
• It uses the commit the tag points to.
• But in some cases (e.g., shallow clones, GitHub CI, or local tools
that only clone the default branch), that commit may not be included,
and you might get an outdated view or nothing at all depending on how
it’s fetched.
Trying this recommended fix.
This is a small quality-of-life feature, the addition of
`--compute-indices` to the CLI, which, if enabled, will compute and set
the `indices` field for each `FileMatch` returned by `run()`. Note we
only bother to compute `indices` once we have the top N results because
there could be a lot of intermediate "top N" results during the search
that are ultimately discarded.
When set, the indices are included in the JSON output when `--json` is
specified and the matching indices are displayed in bold when `--json`
is not specified.
Introduces support for `@` to trigger a fuzzy-filename search in the
composer. Under the hood, this leverages
https://crates.io/crates/nucleo-matcher to do the fuzzy matching and
https://crates.io/crates/ignore to build up the list of file candidates
(so that it respects `.gitignore`).
For simplicity (at least for now), we do not do any caching between
searches like VS Code does for its file search:
1d89ed699b/src/vs/workbench/services/search/node/rawSearchService.ts (L212-L218)
Because we do not do any caching, I saw queries take up to three seconds
on large repositories with hundreds of thousands of files. To that end,
we do not perform searches synchronously on each keystroke, but instead
dispatch an event to do the search on a background thread that
asynchronously reports back to the UI when the results are available.
This is largely handled by the `FileSearchManager` introduced in this
PR, which also has logic for debouncing requests so there is at most one
search in flight at a time.
While we could potentially polish and tune this feature further, it may
already be overengineered for how it will be used, in practice, so we
can improve things going forward if it turns out that this is not "good
enough" in the wild.
Note this feature does not work like `@` in the TypeScript CLI, which
was more like directory-based tab completion. In the Rust CLI, `@`
triggers a full-repo fuzzy-filename search.
Fixes https://github.com/openai/codex/issues/1261.
Update `run()` to take `cancel_flag: Arc<AtomicBool>` that the worker
threads will periodically check to see if it is `true`, exiting early
(and returning empty results) if so.
As we are [close to releasing the Rust CLI
beta](https://github.com/openai/codex/discussions/1405), for the moment,
let's take a more neutral stance on what it takes to be a "built-in"
provider.
* For example, there seems to be a discrepancy around what the "right"
configuration for Gemini is: https://github.com/openai/codex/pull/881
* And while the current list of "built-in" providers are all arguably
"well-known" names, this raises a question of what to do about
potentially less familiar providers, such as
https://github.com/openai/codex/pull/1142. Do we just accept every pull
request like this, or is there some criteria a provider has to meet to
"qualify" to be bundled with Codex CLI?
I think that if we can establish clear ground rules for being a built-in
provider, then we can bring this back. But until then, I would rather
take a minimalist approach because if we decided to reverse our position
later, it would break folks who were depending on the presence of the
built-in providers.
Adds support for a `/diff` command comparable to the one available in
the TypeScript CLI.
<img width="1103" alt="Screenshot 2025-06-26 at 12 31 33 PM"
src="https://github.com/user-attachments/assets/5dc646ca-301f-41ff-92a7-595c68db64b6"
/>
While here, changed the `SlashCommand` enum so the declared variant
order is the order the commands appear in the popup menu. This way,
`/toggle-mouse-mode` is listed last, as it is the least likely to be
used.
Fixes https://github.com/openai/codex/issues/1253.
When using the OpenAI Responses API, we now record the `usage` field for
a `"response.completed"` event, which includes metrics about the number
of tokens consumed. We also introduce `openai_model_info.rs`, which
includes current data about the most common OpenAI models available via
the API (specifically `context_window` and `max_output_tokens`). If
Codex does not recognize the model, you can set `model_context_window`
and `model_max_output_tokens` explicitly in `config.toml`.
When then introduce a new event type to `protocol.rs`, `TokenCount`,
which includes the `TokenUsage` for the most recent turn.
Finally, we update the TUI to record the running sum of tokens used so
the percentage of available context window remaining can be reported via
the placeholder text for the composer:

We could certainly get much fancier with this (such as reporting the
estimated cost of the conversation), but for now, we are just trying to
achieve feature parity with the TypeScript CLI.
Though arguably this improves upon the TypeScript CLI, as the TypeScript
CLI uses heuristics to estimate the number of tokens used rather than
using the `usage` information directly:
296996d74e/codex-cli/src/utils/approximate-tokens-used.ts (L3-L16)
Fixes https://github.com/openai/codex/issues/1242
This PR reworks `assess_command_safety()` so that the combination of
`AskForApproval::Never` and `SandboxPolicy::DangerFullAccess` ensures
that commands are run without _any_ sandbox and the user should never be
prompted. In turn, it adds support for a new
`--dangerously-bypass-approvals-and-sandbox` flag (that cannot be used
with `--approval-policy` or `--full-auto`) that sets both of those
options.
Fixes https://github.com/openai/codex/issues/1254
For the `approval_policy` config option, renames `unless-allow-listed`
to `untrusted`. In general, when it comes to exec'ing commands, I think
"trusted" is a more accurate term than "safe."
Also drops the `AskForApproval::AutoEdit` variant, as we were not really
making use of it, anyway.
Fixes https://github.com/openai/codex/issues/1250.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/1378).
* #1379
* __->__ #1378
Apparently `just` was added to `apt` in Ubuntu 24, so this required
updating the Ubuntu version in the `Dockerfile` to make it so we could
simply `apt install just`.
Though then that caused a conflict with the custom `dev` user we were
using, though the end result seems simpler since now we just use the
default `ubuntu` user provided by Ubuntu 24.
This is a major redesign of how sandbox configuration works and aims to
fix https://github.com/openai/codex/issues/1248. Specifically, it
replaces `sandbox_permissions` in `config.toml` (and the
`-s`/`--sandbox-permission` CLI flags) with a "table" with effectively
three variants:
```toml
# Safest option: full disk is read-only, but writes and network access are disallowed.
[sandbox]
mode = "read-only"
# The cwd of the Codex task is writable, as well as $TMPDIR on macOS.
# writable_roots can be used to specify additional writable folders.
[sandbox]
mode = "workspace-write"
writable_roots = [] # Optional, defaults to the empty list.
network_access = false # Optional, defaults to false.
# Disable sandboxing: use at your own risk!!!
[sandbox]
mode = "danger-full-access"
```
This should make sandboxing easier to reason about. While we have
dropped support for `-s`, the way it works now is:
- no flags => `read-only`
- `--full-auto` => `workspace-write`
- currently, there is no way to specify `danger-full-access` via a CLI
flag, but we will revisit that as part of
https://github.com/openai/codex/issues/1254
Outstanding issue:
- As noted in the `TODO` on `SandboxPolicy::is_unrestricted()`, we are
still conflating sandbox preferences with approval preferences in that
case, which needs to be cleaned up.
- Use Responses API for Azure provider endpoints
- Added a unit test to catch regression on the change from
`/chat/completions` to `/responses`
- Updated the default AOAI api version from `2025-03-01-preview` to
`2025-04-01-preview` to avoid user/400 errors due to missing summary
support in the March API version.
- Changes have been tested locally on AOAI endpoints
## Summary
This PR refactors the Codex CLI authentication flow so that
**non-OpenAI** providers (for example **azure**, or any future addition)
can supply their API key through a dedicated environment variable
without triggering the OpenAI login flow.
Key behaviours introduced:
* When `provider !== "openai"` the CLI consults `src/utils/providers.ts`
to locate the correct environment variable (`AZURE_OPENAI_API_KEY`,
`GEMINI_API_KEY`, and so on) before considering any interactive login.
* Credit redemption (`--free`) and PKCE login now run **only** when the
provider is OpenAI, eliminating unwanted browser prompts for Azure and
others.
* User-facing error messages are revamped to guide Azure users to
**[https://ai.azure.com/](https://ai.azure.com)** and show the exact
variable name they must set.
* All code paths still export `OPENAI_API_KEY` so legacy scripts
continue to operate unchanged.
---
## Example `config.json`
```jsonc
{
"model": "codex-mini",
"provider": "azure",
"providers": {
"azure": {
"name": "AzureOpenAI",
"baseURL": "https://ai-<project-name>.openai.azure.com/openai",
"envKey": "AZURE_OPENAI_API_KEY"
}
},
"history": {
"maxSize": 1000,
"saveHistory": true,
"sensitivePatterns": []
}
}
```
With this file in `~/.codex/config.json`, a single command line is
enough:
```bash
export AZURE_OPENAI_API_KEY="<your-key>"
codex "Hello from Azure"
```
No browser window opens, and the CLI works in entirely non-interactive
mode.
---
## Rationale
The new flow enables Codex to run **asynchronously** in sandboxed
environments such as GitHub Actions pipelines. By passing `--provider
azure` (or setting it in `config.json`) and exporting the correct key,
CI/CD jobs can invoke Codex without any ChatGPT-style login or PKCE
round-trip. This unlocks fully automated testing and deployment
scenarios.
---
## What’s changed
| File | Type | Description |
| ------------------------ | ------------------- |
-----------------------------------------------------------------------------------------------------------------------------
|
| `codex-cli/src/cli.tsx` | **feat / refactor** | +43 / -20 lines.
Imports `providers`, adds early provider-specific key lookup, gates
`--free` redemption, rewrites help text. |
| `src/utils/providers.ts` | **chore** | Now consumed by CLI for env-var
discovery. |
---
## How to test
```bash
# Azure example
export AZURE_OPENAI_API_KEY="<your-key>"
codex --provider azure "Automated run in CI"
# OpenAI example (unchanged behaviour)
codex --provider openai --login "Standard OpenAI flow"
```
Expected outcomes:
* Azure and other provider paths are non-interactive when provider flag
is passed.
* The CLI always sets `OPENAI_API_KEY` for backward compatibility.
---
## Checklist
* [x] Logic behind provider-specific env-var lookup added.
* [x] Redundant OpenAI login steps removed for other providers.
* [x] Unit tests cover new branches.
* [x] README and sample config updated.
* [x] CI passes on all supported Node versions.
---
**Related work**
* #92
* #769
* #1321
I have read the CLA Document and I hereby sign the CLA.
I noticed that `/clear` wasn't fully clearing chat history; it would
clear the chat history widgets _in the UI_, but the LLM still had access
to information from previous messages.
This PR renames `/clear` to `/new` for clarity as per Michael's
suggestion, resetting `app_state` to a fresh `ChatWidget`.
Now that we have published a GitHub Release that contains arm64 musl
artifacts for Linux, update the following scripts to take advantage of
them:
- `dotslash-config.json` now uses musl artifacts for the `linux-aarch64`
target
- `install_native_deps.sh` for the TypeScript CLI now includes
`codex-linux-sandbox-aarch64-unknown-linux-musl` instead of
`codex-linux-sandbox-aarch64-unknown-linux-gnu` for sandboxing
- `codex-cli/bin/codex.js` now checks for `aarch64-unknown-linux-musl`
artifacts instead of `aarch64-unknown-linux-gnu` ones
Users were running into issues with glibc mismatches on arm64 linux. In
the past, we did not provide a musl build for arm64 Linux because we had
trouble getting the openssl dependency to build correctly. Though today
I just tried the same trick in `Cargo.toml` that we were doing for
`x86_64-unknown-linux-musl` (using `openssl-sys` with `features =
["vendored"]`), so I'm not sure what problem we had in the past the
builds "just worked" today!
Though one tweak that did have to be made is that the integration tests
for Seccomp/Landlock empirically require longer timeouts on arm64 linux,
or at least on the `ubuntu-24.04-arm` GitHub Runner. As such, we change
the timeouts for arm64 in `codex-rs/linux-sandbox/tests/landlock.rs`.
Though in solving this problem, I decided I needed a turnkey solution
for testing the Linux build(s) from my Mac laptop, so this PR introduces
`.devcontainer/Dockerfile` and `.devcontainer/devcontainer.json` to
facilitate this. Detailed instructions are in `.devcontainer/README.md`.
We will update `dotslash-config.json` and other release-related scripts
in a follow-up PR.
This does not implement the full Login with ChatGPT experience, but it
should unblock people.
**What works**
* The `codex` multitool now has a `login` subcommand, so you can run
`codex login`, which should write `CODEX_HOME/auth.json` if you complete
the flow successfully. The TUI will now read the `OPENAI_API_KEY` from
`auth.json`.
* The TUI should refresh the token if it has expired and the necessary
information is in `auth.json`.
* There is a `LoginScreen` in the TUI that tells you to run `codex
login` if both (1) your model provider expects to use `OPENAI_API_KEY`
as its env var, and (2) `OPENAI_API_KEY` is not set.
**What does not work**
* The `LoginScreen` does not support the login flow from within the TUI.
Instead, it tells you to quit, run `codex login`, and then run `codex`
again.
* `codex exec` does read from `auth.json` yet, nor does it direct the
user to go through the login flow if `OPENAI_API_KEY` is not be found.
* The `maybeRedeemCredits()` function from `get-api-key.tsx` has not
been ported from TypeScript to `login_with_chatgpt.py` yet:
a67a67f325/codex-cli/src/utils/get-api-key.tsx (L84-L89)
**Implementation**
Currently, the OAuth flow requires running a local webserver on
`127.0.0.1:1455`. It seemed wasteful to incur the additional binary cost
of a webserver dependency in the Rust CLI just to support login, so
instead we implement this logic in Python, as Python has a `http.server`
module as part of its standard library. Specifically, we bundle the
contents of a single Python file as a string in the Rust CLI and then
use it to spawn a subprocess as `python3 -c
{{SOURCE_FOR_PYTHON_SERVER}}`.
As such, the most significant files in this PR are:
```
codex-rs/login/src/login_with_chatgpt.py
codex-rs/login/src/lib.rs
```
Now that the CLI may load `OPENAI_API_KEY` from the environment _or_
`CODEX_HOME/auth.json`, we need a new abstraction for reading/writing
this variable, so we introduce:
```
codex-rs/core/src/openai_api_key.rs
```
Note that `std::env::set_var()` is [rightfully] `unsafe` in Rust 2024,
so we use a LazyLock<RwLock<Option<String>>> to store `OPENAI_API_KEY`
so it is read in a thread-safe manner.
Ultimately, it should be possible to go through the entire login flow
from the TUI. This PR introduces a placeholder `LoginScreen` UI for that
right now, though the new `codex login` subcommand introduced in this PR
should be a viable workaround until the UI is ready.
**Testing**
Because the login flow is currently implemented in a standalone Python
file, you can test it without building any Rust code as follows:
```
rm -rf /tmp/codex_home && mkdir /tmp/codex_home
CODEX_HOME=/tmp/codex_home python3 codex-rs/login/src/login_with_chatgpt.py
```
For reference:
* the original TypeScript implementation was introduced in
https://github.com/openai/codex/pull/963
* support for redeeming credits was later added in
https://github.com/openai/codex/pull/974
This PR overhauls how active tool calls and completed tool calls are
displayed:
1. More use of colour to indicate success/failure and distinguish
between components like tool name+arguments
2. Previously, the entire `CallToolResult` was serialized to JSON and
pretty-printed. Now, we extract each individual `CallToolResultContent`
and print those
1. The previous solution was wasting space by unnecessarily showing
details of the `CallToolResult` struct to users, without formatting the
actual tool call results nicely
2. We're now able to show users more information from tool results in
less space, with nicer formatting when tools return JSON results
### Before:
<img width="1251" alt="Screenshot 2025-06-03 at 11 24 26"
src="https://github.com/user-attachments/assets/5a58f222-219c-4c53-ace7-d887194e30cf"
/>
### After:
<img width="1265" alt="image"
src="https://github.com/user-attachments/assets/99fe54d0-9ebe-406a-855b-7aa529b91274"
/>
## Future Work
1. Integrate image tool result handling better. We should be able to
display images even if they're not the first `CallToolResultContent`
2. Users should have some way to view the full version of truncated tool
results
3. It would be nice to add some left padding for tool results, make it
more clear that they are results. This is doable, just a little fiddly
due to the way `first_visible_line` scrolling works
4. There's almost certainly a better way to format JSON than "all on 1
line with spaces to make Ratatui wrapping work". But I think that works
OK for now.
This fixes a longstanding error in the Rust CLI where `codex.rs`
contained an errant `is_first_turn` check that would exclude the user
instructions for subsequent "turns" of a conversation when using the
responses API (i.e., when `previous_response_id` existed).
While here, renames `Prompt.instructions` to `Prompt.user_instructions`
since we now have quite a few levels of instructions floating around.
Also removed an unnecessary use of `clone()` in
`Prompt.get_full_instructions()`.
As explained in detail in the doc comment for `ParseMode::Lenient`, we
have observed that GPT-4.1 does not always generate a valid invocation
of `apply_patch`. Fortunately, the error is predictable, so we introduce
some new logic to the `codex-apply-patch` crate to recover from this
error.
Because we would like to avoid this becoming a de facto standard (as it
would be incompatible if `apply_patch` were provided as an actual
executable, unless we also introduced the lenient behavior in the
executable, as well), we require passing `ParseMode::Lenient` to
`parse_patch_text()` to make it clear that the caller is opting into
supporting this special case.
Note the analogous change to the TypeScript CLI was
https://github.com/openai/codex/pull/930. In addition to changing the
accepted input to `apply_patch`, it also introduced additional
instructions for the model, which we include in this PR.
Note that `apply-patch` does not depend on either `regex` or
`regex-lite`, so some of the checks are slightly more verbose to avoid
introducing this dependency.
That said, this PR does not leverage the existing
`extract_heredoc_body_from_apply_patch_command()`, which depends on
`tree-sitter` and `tree-sitter-bash`:
5a5aa89914/codex-rs/apply-patch/src/lib.rs (L191-L246)
though perhaps it should.
Previous to this PR, we always set `reasoning` when making a request
using the Responses API:
d7245cbbc9/codex-rs/core/src/client.rs (L108-L111)
Though if you tried to use the Rust CLI with `--model gpt-4.1`, this
would fail with:
```shell
"Unsupported parameter: 'reasoning.effort' is not supported with this model."
```
We take a cue from the TypeScript CLI, which does a check on the model
name:
d7245cbbc9/codex-cli/src/utils/agent/agent-loop.ts (L786-L789)
This PR does a similar check, though also adds support for the following
config options:
```
model_reasoning_effort = "low" | "medium" | "high" | "none"
model_reasoning_summary = "auto" | "concise" | "detailed" | "none"
```
This way, if you have a model whose name happens to start with `"o"` (or
`"codex"`?), you can set these to `"none"` to explicitly disable
reasoning, if necessary. (That said, it seems unlikely anyone would use
the Responses API with non-OpenAI models, but we provide an escape
hatch, anyway.)
This PR also updates both the TUI and `codex exec` to show `reasoning
effort` and `reasoning summaries` in the header.
Prior to this PR, there were two big misses in `chat_completions.rs`:
1. The loop in `stream_chat_completions()` was only including items of
type `ResponseItem::Message` when building up the `"messages"` JSON for
the `POST` request to the `chat/completions` endpoint. This fixes things
by ensuring other variants (`FunctionCall`, `LocalShellCall`, and
`FunctionCallOutput`) are included, as well.
2. In `process_chat_sse()`, we were not recording tool calls and were
only emitting items of type
`ResponseEvent::OutputItemDone(ResponseItem::Message)` to the stream.
Now we introduce `FunctionCallState`, which is used to accumulate the
`delta`s of type `tool_calls`, so we can ultimately emit a
`ResponseItem::FunctionCall`, when appropriate.
While function calling now appears to work for chat completions with my
local testing, I believe that there are still edge cases that are not
covered and that this codepath would benefit from a battery of
integration tests. (As part of that further cleanup, we should also work
to support streaming responses in the UI.)
The other important part of this PR is some cleanup in
`core/src/codex.rs`. In particular, it was hard to reason about how
`run_task()` was building up the list of messages to include in a
request across the various cases:
- Responses API
- Chat Completions API
- Responses API used in concert with ZDR
I like to think things are a bit cleaner now where:
- `zdr_transcript` (if present) contains all messages in the history of
the conversation, which includes function call outputs that have not
been sent back to the model yet
- `pending_input` includes any messages the user has submitted while the
turn is in flight that need to be injected as part of the next `POST` to
the model
- `input_for_next_turn` includes the tool call outputs that have not
been sent back to the model yet
This PR introduces a `hide_agent_reasoning` config option (that defaults
to `false`) that users can enable to make the output less verbose by
suppressing reasoning output.
To test, verified that this includes agent reasoning in the output:
```
echo hello | just exec
```
whereas this does not:
```
echo hello | just exec --config hide_agent_reasoning=false
```
This required changing `ts_println!()` to take `$self:ident`, which is a
bit more verbose, but the usability improvement seems worth it.
Also eliminated an unnecessary `.to_string()` while here.
Fixes:
* Instantiate `EventProcessor` earlier in `lib.rs` so
`print_config_summary()` can be an instance method of it and leverage
its various `Style` fields to ensure it honors `with_ansi` properly.
* After printing the config summary, print out user's prompt with the
heading `User instructions:`. As noted in the comment, now that we can
read the instructions via stdin as of #1178, it is helpful to the user
to ensure they know what instructions were given to Codex.
* Use same colors/bold/italic settings for headers as the TUI, making
the output a bit easier to read.
This attempts to make `codex exec` more flexible in how the prompt can
be passed:
* as before, it can be passed as a single string argument
* if `-` is passed as the value, the prompt is read from stdin
* if no argument is passed _and stdin is a tty_, prints a warning to
stderr that no prompt was specified an exits non-zero.
* if no argument is passed _and stdin is NOT a tty_, prints `Reading
prompt from stdin...` to stderr to let the user know that Codex will
wait until it reads EOF from stdin to proceed. (You can repro this case
by doing `yes | just exec` since stdin is not a TTY in that case but it
also never reaches EOF).
The main motivator behind this PR is that `stream_chat_completions()`
was not adding the `"tools"` entry to the payload posted to the
`/chat/completions` endpoint. This (1) refactors the existing logic to
build up the `"tools"` JSON from `client.rs` into `openai_tools.rs`, and
(2) updates the use of responses API (`client.rs`) and chat completions
API (`chat_completions.rs`) to both use it.
Note this PR alone is not sufficient to get tool calling from chat
completions working: that is done in
https://github.com/openai/codex/pull/1167.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/1177).
* #1167
* __->__ #1177
This is a first cut at a GitHub Action that lets you define prompt
templates in `.md` files under `.github/codex/labels` that will run
Codex with the associated prompt when the label is added to a GitHub
pull request.
For example, this PR includes these files:
```
.github/codex/labels/codex-attempt.md
.github/codex/labels/codex-code-review.md
.github/codex/labels/codex-investigate-issue.md
```
And the new `.github/workflows/codex.yml` workflow declares the
following triggers:
```yaml
on:
issues:
types: [opened, labeled]
pull_request:
branches: [main]
types: [labeled]
```
as well as the following expression to gate the action:
```
jobs:
codex:
if: |
(github.event_name == 'issues' && (
(github.event.action == 'labeled' && (github.event.label.name == 'codex-attempt' || github.event.label.name == 'codex-investigate-issue'))
)) ||
(github.event_name == 'pull_request' && github.event.action == 'labeled' && github.event.label.name == 'codex-code-review')
```
Note the "actor" who added the label must have write access to the repo
for the action to take effect.
After adding a label, the action will "ack" the request by replacing the
original label (e.g., `codex-review`) with an `-in-progress` suffix
(e.g., `codex-review-in-progress`). When it is finished, it will swap
the `-in-progress` label with a `-completed` one (e.g.,
`codex-review-completed`).
Users of the action are responsible for providing an `OPENAI_API_KEY`
and making it available as a secret to the action.
The way these definitions worked before, they did not handle quoted args
with spaces properly.
For example, if you had `/tmp/test-just/printlen.py` as:
```python
#!/usr/bin/env python3
import sys
print(len(sys.argv))
```
and your `justfile` was:
```
printlen *args:
/tmp/test-just/printlen.py {{args}}
```
Then:
```shell
$ just printlen foo bar
3
$ just printlen 'foo bar'
3
```
which is not what we want: `'foo bar'` should be treated as one
argument.
The fix is to use
[positional-arguments](515e806b51/README.md (L1131)):
```
set positional-arguments
printlen *args:
/tmp/test-just/printlen.py "$@"
```
The output of an MCP server tool call can be one of several types, but
to date, we treated all outputs as text by showing the serialized JSON
as the "tool output" in Codex:
25a9949c49/codex-rs/mcp-types/src/lib.rs (L96-L101)
This PR adds support for the `ImageContent` variant so we can now
display an image output from an MCP tool call.
In making this change, we introduce a new
`ResponseInputItem::McpToolCallOutput` variant so that we can work with
the `mcp_types::CallToolResult` directly when the function call is made
to an MCP server.
Though arguably the more significant change is the introduction of
`HistoryCell::CompletedMcpToolCallWithImageOutput`, which is a cell that
uses `ratatui_image` to render an image into the terminal. To support
this, we introduce `ImageRenderCache`, cache a
`ratatui_image::picker::Picker`, and `ensure_image_cache()` to cache the
appropriate scaled image data and dimensions based on the current
terminal size.
To test, I created a minimal `package.json`:
```json
{
"name": "kitty-mcp",
"version": "1.0.0",
"type": "module",
"description": "MCP that returns image of kitty",
"main": "index.js",
"dependencies": {
"@modelcontextprotocol/sdk": "^1.12.0"
}
}
```
with the following `index.js` to define the MCP server:
```js
#!/usr/bin/env node
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { readFile } from "node:fs/promises";
import { join } from "node:path";
const IMAGE_URI = "image://Ada.png";
const server = new McpServer({
name: "Demo",
version: "1.0.0",
});
server.tool(
"get-cat-image",
"If you need a cat image, this tool will provide one.",
async () => ({
content: [
{ type: "image", data: await getAdaPngBase64(), mimeType: "image/png" },
],
})
);
server.resource("Ada the Cat", IMAGE_URI, async (uri) => {
const base64Image = await getAdaPngBase64();
return {
contents: [
{
uri: uri.href,
mimeType: "image/png",
blob: base64Image,
},
],
};
});
async function getAdaPngBase64() {
const __dirname = new URL(".", import.meta.url).pathname;
// From 9705ce2c59/assets/Ada.png
const filePath = join(__dirname, "Ada.png");
const imageData = await readFile(filePath);
const base64Image = imageData.toString("base64");
return base64Image;
}
const transport = new StdioServerTransport();
await server.connect(transport);
```
With the local changes from this PR, I added the following to my
`config.toml`:
```toml
[mcp_servers.kitty]
command = "node"
args = ["/Users/mbolin/code/kitty-mcp/index.js"]
```
Running the TUI from source:
```
cargo run --bin codex -- --model o3 'I need a picture of a cat'
```
I get:
<img width="732" alt="image"
src="https://github.com/user-attachments/assets/bf80b721-9ca0-4d81-aec7-77d6899e2869"
/>
Now, that said, I have only tested in iTerm and there is definitely some
funny business with getting an accurate character-to-pixel ratio
(sometimes the `CompletedMcpToolCallWithImageOutput` thinks it needs 10
rows to render instead of 4), so there is still work to be done here.
The motivation behind this PR is to make it so a `HistoryCell` is more
like a `WidgetRef` that knows how to render itself into a `Rect` so that
it can be backed by something other than a `Vec<Line>`. Because a
`HistoryCell` is intended to appear in a scrollable list, we want to
ensure the stack of cells can be scrolled one `Line` at a time even if
the `HistoryCell` is not backed by a `Vec<Line>` itself.
To this end, we introduce the `CellWidget` trait whose key method is:
```
fn render_window(&self, first_visible_line: usize, area: Rect, buf: &mut Buffer);
```
The `first_visible_line` param is what differs from
`WidgetRef::render_ref()`, as a `CellWidget` needs to know the offset
into its "full view" at which it should start rendering.
The bookkeeping in `ConversationHistoryWidget` has been updated
accordingly to ensure each `CellWidget` in the history is rendered
appropriately.
This PR introduces support for `-c`/`--config` so users can override
individual config values on the command line using `--config
name=value`. Example:
```
codex --config model=o4-mini
```
Making it possible to set arbitrary config values on the command line
results in a more flexible configuration scheme and makes it easier to
provide single-line examples that can be copy-pasted from documentation.
Effectively, it means there are four levels of configuration for some
values:
- Default value (e.g., `model` currently defaults to `o4-mini`)
- Value in `config.toml` (e.g., user could override the default to be
`model = "o3"` in their `config.toml`)
- Specifying `-c` or `--config` to override `model` (e.g., user can
include `-c model=o3` in their list of args to Codex)
- If available, a config-specific flag can be used, which takes
precedence over `-c` (e.g., user can specify `--model o3` in their list
of args to Codex)
Now that it is possible to specify anything that could be configured in
`config.toml` on the command line using `-c`, we do not need to have a
custom flag for every possible config option (which can clutter the
output of `--help`). To that end, as part of this PR, we drop support
for the `--disable-response-storage` flag, as users can now specify `-c
disable_response_storage=true` to get the equivalent functionality.
Under the hood, this works by loading the `config.toml` into a
`toml::Value`. Then for each `key=value`, we create a small synthetic
TOML file with `value` so that we can run the TOML parser to get the
equivalent `toml::Value`. We then parse `key` to determine the point in
the original `toml::Value` to do the insert/replace. Once all of the
overrides from `-c` args have been applied, the `toml::Value` is
deserialized into a `ConfigToml` and then the `ConfigOverrides` are
applied, as before.
I discovered that if I ran `codex <PROMPT>` in a cwd that was not a Git
repo, Codex did not automatically run `<PROMPT>` after I accepted the
Git warning. It appears that we were not managing the `AppState`
transition correctly, so this fixes the bug and ensures the Codex
session does not start until the user accepts the Git warning.
In particular, we now create the `ChatWidget` lazily and store it in the
`AppState::Chat` variant.
Historically, we spawned the Seatbelt and Landlock sandboxes in
substantially different ways:
For **Seatbelt**, we would run `/usr/bin/sandbox-exec` with our policy
specified as an arg followed by the original command:
d1de7bb383/codex-rs/core/src/exec.rs (L147-L219)
For **Landlock/Seccomp**, we would do
`tokio::runtime::Builder::new_current_thread()`, _invoke
Landlock/Seccomp APIs to modify the permissions of that new thread_, and
then spawn the command:
d1de7bb383/codex-rs/core/src/exec_linux.rs (L28-L49)
While it is neat that Landlock/Seccomp supports applying a policy to
only one thread without having to apply it to the entire process, it
requires us to maintain two different codepaths and is a bit harder to
reason about. The tipping point was
https://github.com/openai/codex/pull/1061, in which we had to start
building up the `env` in an unexpected way for the existing
Landlock/Seccomp approach to continue to work.
This PR overhauls things so that we do similar things for Mac and Linux.
It turned out that we were already building our own "helper binary"
comparable to Mac's `sandbox-exec` as part of the `cli` crate:
d1de7bb383/codex-rs/cli/Cargo.toml (L10-L12)
We originally created this to build a small binary to include with the
Node.js version of the Codex CLI to provide support for Linux
sandboxing.
Though the sticky bit is that, at this point, we still want to deploy
the Rust version of Codex as a single, standalone binary rather than a
CLI and a supporting sandboxing binary. To satisfy this goal, we use
"the arg0 trick," in which we:
* use `std::env::current_exe()` to get the path to the CLI that is
currently running
* use the CLI as the `program` for the `Command`
* set `"codex-linux-sandbox"` as arg0 for the `Command`
A CLI that supports sandboxing should check arg0 at the start of the
program. If it is `"codex-linux-sandbox"`, it must invoke
`codex_linux_sandbox::run_main()`, which runs the CLI as if it were
`codex-linux-sandbox`. When acting as `codex-linux-sandbox`, we make the
appropriate Landlock/Seccomp API calls and then use `execvp(3)` to spawn
the original command, so do _replace_ the process rather than spawn a
subprocess. Incidentally, we do this before starting the Tokio runtime,
so the process should only have one thread when `execvp(3)` is called.
Because the `core` crate that needs to spawn the Linux sandboxing is not
a CLI in its own right, this means that every CLI that includes `core`
and relies on this behavior has to (1) implement it and (2) provide the
path to the sandboxing executable. While the path is almost always
`std::env::current_exe()`, we needed to make this configurable for
integration tests, so `Config` now has a `codex_linux_sandbox_exe:
Option<PathBuf>` property to facilitate threading this through,
introduced in https://github.com/openai/codex/pull/1089.
This common pattern is now captured in
`codex_linux_sandbox::run_with_sandbox()` and all of the `main.rs`
functions that should use it have been updated as part of this PR.
The `codex-linux-sandbox` crate added to the Cargo workspace as part of
this PR now has the bulk of the Landlock/Seccomp logic, which makes
`core` a bit simpler. Indeed, `core/src/exec_linux.rs` and
`core/src/landlock.rs` were removed/ported as part of this PR. I also
moved the unit tests for this code into an integration test,
`linux-sandbox/tests/landlock.rs`, in which I use
`env!("CARGO_BIN_EXE_codex-linux-sandbox")` as the value for
`codex_linux_sandbox_exe` since `std::env::current_exe()` is not
appropriate in that case.
https://github.com/openai/codex/pull/1086 is a work-in-progress to make
Linux sandboxing work more like Seatbelt where, for the command we want
to sandbox, we build up the command and then hand it, and some sandbox
configuration flags, to another command to set up the sandbox and then
run it.
In the case of Seatbelt, macOS provides this helper binary and provides
it at `/usr/bin/sandbox-exec`. For Linux, we have to build our own and
pass it through (which is what #1086 does), so this makes the new
`codex_linux_sandbox_exe` available on `Config` so that it will later be
available in `exec.rs` when we need it in #1086.
Added logic so that when we run `./scripts/stage_release.sh --native`
(for the `@native` version of the Node module), we drop a `use-native`
file next to `codex.js`. If present, `codex.js` will now run the Rust
CLI.
Ran `./scripts/stage_release.sh --native` and verified that when the
running `codex.js` in the staged folder:
```
$ /var/folders/wm/f209bc1n2bd_r0jncn9s6j_00000gp/T/tmp.efvEvBlSN6/bin/codex.js --version
codex-cli 0.0.2505220956
```
it ran the expected Rust version of the CLI, as desired.
While here, I also updated the Rust version to one that I cut today,
which includes the new shell environment policy config option:
https://github.com/openai/codex/pull/1061. Note this may "break" some
users if the processes spawned by Codex need extra environment
variables. (We are still working to determine what the right defaults
should be for this option.)
To date, when handling `shell` and `local_shell` tool calls, we were
spawning new processes using the environment inherited from the Codex
process itself. This means that the sensitive `OPENAI_API_KEY` that
Codex needs to talk to OpenAI models was made available to everything
run by `shell` and `local_shell`. While there are cases where that might
be useful, it does not seem like a good default.
This PR introduces a complex `shell_environment_policy` config option to
control the `env` used with these tool calls. It is inevitably a bit
complex so that it is possible to override individual components of the
policy so without having to restate the entire thing.
Details are in the updated `README.md` in this PR, but here is the
relevant bit that explains the individual fields of
`shell_environment_policy`:
| Field | Type | Default | Description |
| ------------------------- | -------------------------- | ------- |
-----------------------------------------------------------------------------------------------------------------------------------------------
|
| `inherit` | string | `core` | Starting template for the
environment:<br>`core` (`HOME`, `PATH`, `USER`, …), `all` (clone full
parent env), or `none` (start empty). |
| `ignore_default_excludes` | boolean | `false` | When `false`, Codex
removes any var whose **name** contains `KEY`, `SECRET`, or `TOKEN`
(case-insensitive) before other rules run. |
| `exclude` | array<string> | `[]` | Case-insensitive glob
patterns to drop after the default filter.<br>Examples: `"AWS_*"`,
`"AZURE_*"`. |
| `set` | table<string,string> | `{}` | Explicit key/value
overrides or additions – always win over inherited values. |
| `include_only` | array<string> | `[]` | If non-empty, a
whitelist of patterns; only variables that match _one_ pattern survive
the final step. (Generally used with `inherit = "all"`.) |
In particular, note that the default is `inherit = "core"`, so:
* if you have extra env variables that you want to inherit from the
parent process, use `inherit = "all"` and then specify `include_only`
* if you have extra env variables where you want to hardcode the values,
the default `inherit = "core"` will work fine, but then you need to
specify `set`
This configuration is not battle-tested, so we will probably still have
to play with it a bit. `core/src/exec_env.rs` has the critical business
logic as well as unit tests.
Though if nothing else, previous to this change:
```
$ cargo run --bin codex -- debug seatbelt -- printenv OPENAI_API_KEY
# ...prints OPENAI_API_KEY...
```
But after this change it does not print anything (as desired).
One final thing to call out about this PR is that the
`configure_command!` macro we use in `core/src/exec.rs` has to do some
complex logic with respect to how it builds up the `env` for the process
being spawned under Landlock/seccomp. Specifically, doing
`cmd.env_clear()` followed by `cmd.envs(&$env_map)` (which is arguably
the most intuitive way to do it) caused the Landlock unit tests to fail
because the processes spawned by the unit tests started failing in
unexpected ways! If we forgo `env_clear()` in favor of updating env vars
one at a time, the tests still pass. The comment in the code talks about
this a bit, and while I would like to investigate this more, I need to
move on for the moment, but I do plan to come back to it to fully
understand what is going on. For example, this suggests that we might
not be able to spawn a C program that calls `env_clear()`, which would
be...weird. We may still have to fiddle with our Landlock config if that
is the case.
Now the `exec` output starts with something like:
```
--------
workdir: /Users/mbolin/code/codex/codex-rs
model: o3
provider: openai
approval: Never
sandbox: SandboxPolicy { permissions: [DiskFullReadAccess, DiskWritePlatformUserTempFolder, DiskWritePlatformGlobalTempFolder, DiskWriteCwd, DiskWriteFolder { folder: "/Users/mbolin/.pyenv/shims" }] }
--------
```
which makes it easier to reason about when looking at logs.
`config.rs` is already quite long without these definitions. Since they
have no real dependencies of their own, let's move them to their own
file so `config.rs` can focus on the business logic of loading a config.
This introduces an experimental `--output-last-message` flag that can be
used to identify a file where the final message from the agent will be
written. Two use cases:
- Ultimately, we will likely add a `--quiet` option to `exec`, but even
if the user does not want any output written to the terminal, they
probably want to know what the agent did. Writing the output to a file
makes it possible to get that information in a clean way.
- Relatedly, when using `exec` in CI, it is easier to review the
transcript written "normally," (i.e., not as JSON or something with
extra escapes), but getting programmatic access to the last message is
likely helpful, so writing the last message to a file gets the best of
both worlds.
I am calling this "experimental" because it is possible that we are
overfitting and will want a more general solution to this problem that
would justify removing this flag.
## Summary
- add `--login` and `--free` flags to cli help
- handle `--login` and `--free` logic in cli
- factor out redeem flow into `maybeRedeemCredits`
- call new helper from login callback
Prior to this PR, I would frequently see glyphs from previous frames
"bleed" through like this:

I think this was due to two issues (now addressed in this PR):
* We were not making use of `ratatui::widgets::Clear` to clear out the
buffer before drawing into it.
* To calculate the `width` used with `wrapped_line_count_for_cell()`, we
were not accounting for the scrollbar.
* Now we calculate `effective_width` using
`inner.width.saturating_sub(1)` where the `1` is for the scrollbar.
* We compute `text_area` using `effective_with` and pass the `text_area`
to `paragraph.render()`.
* We eliminate the conditional `needs_scrollbar` check and always call
`render(Scrollbar)`
I suspect this bug was introduced in
https://github.com/openai/codex/pull/937, though I did not try to
verify: I'm just happy that it appears to be fixed!
Previously, if the first user message was sent with the command
invocation, e.g.:
```
$ cargo run --bin codex 'hello'
```
Then the user message was added as the first entry in the history and
then `is_first_event` would be `false` here:
031df77dfb/codex-rs/tui/src/conversation_history_widget.rs (L178-L179)
which would prevent the "welcome" message with things like the the model
version from displaying.
The fix in this PR is twofold:
* Reorganize the logic so the `ChatWidget` constructor stores
`initial_user_message` rather than sending it right away. Now inside
`handle_codex_event()`, it waits for the `SessionConfigured` event and
sends the `initial_user_message`, if it exists.
* In `conversation_history_widget.rs`, `add_session_info()` checks to
see whether a `WelcomeMessage` exists in the history when determining
the value of `has_welcome_message`. By construction, we expect that
`WelcomeMessage` is always the first message (in which case the existing
`let is_first_event = self.entries.is_empty();` logic would be sound),
but we decide to be extra defensive in case an `EventMsg::Error` is
processed before `EventMsg::SessionConfigured`.
When running `npm test` on `codex-cli`, the test
`agent-cancel-prev-response.test.ts` logs a significant body of text to
console for no obvious reason.
This is not helpful, as it makes test logs messy and far longer.
This change deletes the `console.log(...)` that produces the behavior.
I did a bit of research to understand why I could not use my mouse to
drag to select text to copy to the clipboard in iTerm.
Apparently https://github.com/openai/codex/pull/641 to enable mousewheel
scrolling broke this functionality. It seems that, unless we put in a
bit of effort, we can have drag-to-select or scrolling, but not both.
Though if you know the trick to hold down `Option` will dragging with
the mouse in iTerm, you can probably get by with this. (I did not know
about this option prior to researching this issue.)
Nevertheless, users may still prefer to disable mouse capture
altogether, so this PR introduces:
* the ability to set `tui.disable_mouse_capture = true` in `config.toml`
to disable mouse capture
* a new command, `/toggle-mouse-mode` to toggle mouse capture
The new `codex-mini-latest` model expects a new tool with `{"type":
"local_shell"}`. Its contract is similar to the existing `function` tool
with `"name": "shell"`, so this takes the `local_shell` tool call into
`ExecParams` and sends it through the existing
`handle_container_exec_with_params()` code path.
This also adds the following logic when adding the default set of tools
to a request:
```rust
let default_tools = if self.model.starts_with("codex") {
&DEFAULT_CODEX_MODEL_TOOLS
} else {
&DEFAULT_TOOLS
};
```
That is, if the model name starts with `"codex"`, we add `{"type":
"local_shell"}` to the list of tools; otherwise, we add the
aforementioned `shell` tool.
To test this, I ran the TUI with `-m codex-mini-latest` and verified
that it used the `local_shell` tool. Though I also had some entries in
`[mcp_servers]` in my personal `config.toml`. The `codex-mini-latest`
model seemed eager to try the tools from the MCP servers first, so I
have personally commented them out for now, so keep an eye out if you're
testing `codex-mini-latest`!
Perhaps we should include more details with `{"type": "local_shell"}` or
update the following:
fd0b1b0208/codex-rs/core/prompt.md
For reference, the corresponding change in the TypeScript CLI is
https://github.com/openai/codex/pull/951.
## `0.1.2505161243`
- Sign in with chatgpt (#963)
- Session history viewer (#912)
- Apply patch issue when using different cwd (#942)
- Diff command for filenames with special characters (#954)
- A new “/sessions” command is available for browsing previous sessions,
as shown in the updated slash command list
- The CLI now documents and parses a new “--history” flag to browse past
sessions from the command line
- A dedicated `SessionsOverlay` component loads session metadata and
allows toggling between viewing and resuming sessions
- When the sessions overlay is opened during a chat, selecting a session
can either show the saved rollout or resume it
If you run a codex instance outside of the current working directory
from where you launched the codex binary it won't be able to apply
patches correctly, even if the sandbox policy allows it. This manifests
weird behaviours, such as
* Reading the same filename in the binary working directory, and
overwriting it in the session working directory. e.g. if you have a
`readme` in both folders it will overwrite the readme in the session
working directory with the readme in the binary working directory
*applied with the suggested patch*.
* The LLM ends up in weird loops trying to verify and debug why the
apply_patch won't work, and it can result in it applying patches by
manually writing python or javascript if it figures out that either is
supported by the system instead.
I added a test-case to ensure that the patch contents are based on the
cwd.
## Issue: mixing relative & absolute paths in apply_patch
1. The apply_patch tool use relative paths based on the session working
directory.
2. `unified_diff_from_chunks` eventually ends up [reading the source
file](https://github.com/reflectionai/codex/blob/main/codex-rs/apply-patch/src/lib.rs#L410)
to figure out what the diff is, by using the relative path.
3. The changes are targeted using an absolute path derived from the
current working directory.
The end-result in case session working directory differs from the binary
working directory: we get the diff for a file relative to the binary
working directory, and apply it on a file in the session working
directory.
## Summary
- fix quoting issues in `/diff` to correctly handle files with special
characters
- add regression test for `getGitDiff` when filenames contain `$`
- relax timeout in raw-exec-process-group test
Fixes https://github.com/openai/codex/issues/943
## Testing
- `pnpm test`
When I originally wrote `elapsed.rs`, I realized we were using both
`std::time` and `chrono` with no real benefit of having both. We should
try to keep the `exec` subcommand trim (as it also buildable as a
standalone executable), so this helps tighten things up.
This is a large change to support a "history" feature like you would
expect in a shell like Bash.
History events are recorded in `$CODEX_HOME/history.jsonl`. Because it
is a JSONL file, it is straightforward to append new entries (as opposed
to the TypeScript file that uses `$CODEX_HOME/history.json`, so to be
valid JSON, each new entry entails rewriting the entire file). Because
it is possible for there to be multiple instances of Codex CLI writing
to `history.jsonl` at once, we use advisory file locking when working
with `history.jsonl` in `codex-rs/core/src/message_history.rs`.
Because we believe history is a sufficiently useful feature, we enable
it by default. Though to provide some safety, we set the file
permissions of `history.jsonl` to be `o600` so that other users on the
system cannot read the user's history. We do not yet support a default
list of `SENSITIVE_PATTERNS` as the TypeScript CLI does:
3fdf9df133/codex-cli/src/utils/storage/command-history.ts (L10-L17)
We are going to take a more conservative approach to this list in the
Rust CLI. For example, while `/\b[A-Za-z0-9-_]{20,}\b/` might exclude
sensitive information like API tokens, it would also exclude valuable
information such as references to Git commits.
As noted in the updated documentation, users can opt-out of history by
adding the following to `config.toml`:
```toml
[history]
persistence = "none"
```
Because `history.jsonl` could, in theory, be quite large, we take a[n
arguably overly pedantic] approach in reading history entries into
memory. Specifically, we start by telling the client the current number
of entries in the history file (`history_entry_count`) as well as the
inode (`history_log_id`) of `history.jsonl` (see the new fields on
`SessionConfiguredEvent`).
The client is responsible for keeping new entries in memory to create a
"local history," but if the user hits up enough times to go "past" the
end of local history, then the client should use the new
`GetHistoryEntryRequest` in the protocol to fetch older entries.
Specifically, it should pass the `history_log_id` it was given
originally and work backwards from `history_entry_count`. (It should
really fetch history in batches rather than one-at-a-time, but that is
something we can improve upon in subsequent PRs.)
The motivation behind this crazy scheme is that it is designed to defend
against:
* The `history.jsonl` being truncated during the session such that the
index into the history is no longer consistent with what had been read
up to that point. We do not yet have logic to enforce a `max_bytes` for
`history.jsonl`, but once we do, we will aspire to implement it in a way
that should result in a new inode for the file on most systems.
* New items from concurrent Codex CLI sessions amending to the history.
Because, in absence of truncation, `history.jsonl` is an append-only
log, so long as the client reads backwards from `history_entry_count`,
it should always get a consistent view of history. (That said, it will
not be able to read _new_ commands from concurrent sessions, but perhaps
we will introduce a `/` command to reload latest history or something
down the road.)
Admittedly, my testing of this feature thus far has been fairly light. I
expect we will find bugs and introduce enhancements/fixes going forward.
Moving to Rust 1.87 introduced a clippy warning that
`SendError<AppEvent>` was too large.
In practice, the only thing we ever did when we got this error was log
it (if the mspc channel is closed, then the app is likely shutting down
or something, so there's not much to do...), so this finally motivated
me to introduce `AppEventSender`, which wraps
`std::sync::mpsc::Sender<AppEvent>` with a `send()` method that invokes
`send()` on the underlying `Sender` and logs an `Err` if it gets one.
This greatly simplifies the code, as many functions that previously
returned `Result<(), SendError<AppEvent>>` now return `()`, so we don't
have to propagate an `Err` all over the place that we don't really
handle, anyway.
This also makes it so we can upgrade to Rust 1.87 in CI.
Previously, our GitHub actions specified the Rust toolchain as
`dtolnay/rust-toolchain@stable`, which meant the version could change
out from under us. In this case, the move from 1.86 to 1.87 introduced
new clippy warnings, causing build failures.
Because it will take a little time to fix all the new clippy warnings,
this PR pins things to 1.86 for now to unbreak the build.
It also replaces `io::Error::new(io::ErrorKind::Other)` with
`io::Error::other()` in preparation for 1.87.
As discussed on
699ec5a87f (commitcomment-156776835),
to properly support scrolling long content in Ratatui for a sequence of
cells, we need to:
* take the `Vec<Line>` for each cell
* using the wrapping logic we want to use at render time, compute the
_effective line count_ using `Paragraph::line_count()` (see
`wrapped_line_count_for_cell()` in this PR)
* sum up the effective line count to compute the height of the area
being scrolled
* given a `scroll_position: usize`, index into the list of "effective
lines" and accumulate the appropriate `Vec<Line>` for the cells that
should be displayed
* take that `Vec<Line>` to create a `Paragraph` and use the same
line-wrapping policy that was used in `wrapped_line_count_for_cell()`
* display the resulting `Paragraph` and use the accounting to display a
scrollbar with the appropriate thumb size and offset without having to
render the `Vec<Line>` for the full history
With this change, lines wrap as I expect and everything appears to
redraw correctly as I resize my terminal!
For now, this removes the `#[non_exhaustive]` directive on `EventMsg` so
that we are forced to handle all `EventMsg` by default. (We may revisit
this if/when we publish `core/` as a `lib` crate.) For now, it is
helpful to have this as a forcing function because we have effectively
two UIs (`tui` and `exec`) and usually when we add a new variant to
`EventMsg`, we want to be sure that we update both.
Previously, running Codex as an MCP server required a standalone binary
in our Cargo workspace, but this PR makes it available as a subcommand
(`mcp`) of the main CLI.
Ran this with:
```
RUST_LOG=debug npx @modelcontextprotocol/inspector cargo run --bin codex -- mcp
```
and verified it worked as expected in the inspector at
`http://127.0.0.1:6274/`.
Introduces support for slash commands like in the TypeScript CLI. We do
not support the full set of commands yet, but the core abstraction is
there now.
In particular, we have a `SlashCommand` enum and due to thoughtful use
of the [strum](https://crates.io/crates/strum) crate, it requires
minimal boilerplate to add a new command to the list.
The key new piece of UI is `CommandPopup`, though the keyboard events
are still handled by `ChatComposer`. The behavior is roughly as follows:
* if the first character in the composer is `/`, the command popup is
displayed (if you really want to send a message to Codex that starts
with a `/`, simply put a space before the `/`)
* while the popup is displayed, up/down can be used to change the
selection of the popup
* if there is a selection, hitting tab completes the command, but does
not send it
* if there is a selection, hitting enter sends the command
* if the prefix of the composer matches a command, the command will be
visible in the popup so the user can see the description (commands could
take arguments, so additional text may appear after the command name
itself)
https://github.com/user-attachments/assets/39c3e6ee-eeb7-4ef7-a911-466d8184975f
Incidentally, Codex wrote almost all the code for this PR!
`BottomPane` was getting a bit unwieldy because it maintained a
`PaneState` enum with three variants and many of its methods had `match`
statements to handle each variant. To replace the enum, this PR:
* Introduces a `trait BottomPaneView` that has two implementations:
`StatusIndicatorView` and `ApprovalModalView`.
* Migrates `PaneState::TextInput` into its own struct, `ChatComposer`,
that does **not** implement `BottomPaneView`.
* Updates `BottomPane` so it has `composer: ChatComposer` and
`active_view: Option<Box<dyn BottomPaneView<'a> + 'a>>`. The idea is
that `active_view` takes priority and is displayed when it is `Some`;
otherwise, `ChatComposer` is displayed.
* While methods of `BottomPane` often have to check whether
`active_view` is present to decide which component to delegate to, the
code is more straightforward than before and introducing new
implementations of `BottomPaneView` should be less painful.
Because we want to retain the `TextArea` owned by `ChatComposer` even
when another view is displayed, to keep the ownership logic simple, it
seemed best to keep `ChatComposer` distinct from `BottomPaneView`.
More about codespell: https://github.com/codespell-project/codespell .
I personally introduced it to dozens if not hundreds of projects already
and so far only positive feedback.
CI workflow has 'permissions' set only to 'read' so also should be safe.
Let me know if just want to take typo fixes in and get rid of the CI
---------
Signed-off-by: Yaroslav O. Halchenko <debian@onerussian.com>
## `0.1.2505140839`
### 🪲 Bug Fixes
- Gpt-4.1 apply_patch handling (#930)
- Add support for fileOpener in config.json (#911)
- Patch in #366 and #367 for marked-terminal (#916)
- Remember to set lastIndex = 0 on shared RegExp (#918)
- Always load version from package.json at runtime (#909)
- Tweak the label for citations for better rendering (#919)
- Tighten up some logic around session timestamps and ids (#922)
- Change EventMsg enum so every variant takes a single struct (#925)
- Reasoning default to medium, show workdir when supplied (#931)
- Test_dev_null_write() was not using echo as intended (#923)
While the `TextArea` used in the Rust TUI is "multiline," it is not like
an HTML `<textarea>` in that it does not wrap, so there was not much
benefit to setting `MIN_TEXTAREA_ROWS` to `3`, so this PR changes it to
`1`. Though there are now three ways to "increase" the height due to
actual linebreaks:
* paste in multiline content (this worked before this PR)
* pressing `Ctrl+J` will insert a newline
* if you have your terminal emulator set such that it is possible to
press something that `crossterm` interprets as "Enter plus some
modifier," then now that will also work
Now things look a bit more compact on startup:
<img width="745" alt="image"
src="https://github.com/user-attachments/assets/86e2857f-f31c-46f5-a80b-1ab2120b266e"
/>
I believe this test meant to verify that echoing content to `/dev/null`
succeeded, but instead, I believe it was testing the equivalent to `echo
'blah > /dev/null'`.
https://github.com/openai/codex/pull/922 did this for the
`SessionConfigured` enum variant, and I think it is generally helpful to
be able to work with the values as each enum variant as their own type,
so this converts the remaining variants and updates all of the
callsites.
Added a simple unit test to verify that the JSON-serialized version of
`Event` does not have any unexpected nesting.
* update `SessionConfigured` event to include the UUID for the session
* show the UUID in the Rust TUI
* use local timestamps in log files instead of UTC
* include timestamps in log file names for easier discovery
This introduces a much-needed "profile" concept where users can specify
a collection of options under one name and then pass that via
`--profile` to the CLI.
This PR introduces the `ConfigProfile` struct and makes it a field of
`CargoToml`. It further updates
`Config::load_from_base_config_with_overrides()` to respect
`ConfigProfile`, overriding default values where appropriate. A detailed
unit test is added at the end of `config.rs` to verify this behavior.
Details on how to use this feature have also been added to
`codex-rs/README.md`.
Right now since the repo is having two different implementations of
codex, flake was updated to work with both typescript implementation and
rust implementation
Adds a space so that sequential citations have some more breathing room.
As I had to update the tests for this change, I also introduced a
`toDiffableString()` helper to make the test easier to update as we make
formatting changes to the output.
This PR uses [`pnpm
patch`](https://www.petermekhaeil.com/til/pnpm-patch/) to pull in the
following proposed fixes for `marked-terminal`:
* https://github.com/mikaelbr/marked-terminal/pull/366
* https://github.com/mikaelbr/marked-terminal/pull/367
This adds a substantial test to `codex-cli/tests/markdown.test.tsx` to
verify the new behavior.
Note that one of the tests shows two citations being split across a line
even though the rendered version would fit comfortably on one line.
Changing this likely requires a subtle fix to `marked-terminal` to
account for "rendered length" when determining line breaks.
This PR introduces the following type:
```typescript
export type FileOpenerScheme = "vscode" | "cursor" | "windsurf";
```
and uses it as the new type for a `fileOpener` option in `config.json`.
If set, this will be used to linkify file annotations in the output
using the URI-based file opener supported in VS Code-based IDEs.
Currently, this does not pass:
Updated `codex-cli/tests/markdown.test.tsx` to verify the new behavior.
Note it required mocking `supports-hyperlinks` and temporarily modifying
`chalk.level` to yield the desired output.
Note the high-level motivation behind this change is to avoid the need
to make temporary changes in the source tree in order to cut a release
build since that runs the risk of leaving things in an inconsistent
state in the event of a failure. The existing code:
```
import pkg from "../../package.json" assert { type: "json" };
```
did not work as intended because, as written, ESBuild would bake the
contents of the local `package.json` into the release build at build
time whereas we want it to read the contents at runtime so we can use
the `package.json` in the tree to build the code and later inject a
modified version into the release package with a timestamped build
version.
Changes:
* move `CLI_VERSION` out of `src/utils/session.ts` and into
`src/version.ts` so `../package.json` is a correct relative path both
from `src/version.ts` in the source tree and also in the final
`dist/cli.js` build output
* change `assert` to `with` in `import pkg` as apparently `with` became
standard in Node 22
* mark `"../package.json"` as external in `build.mjs` so the version is
not baked into the `.js` at build time
After using `pnpm stage-release` to build a release version, if I use
Node 22.0 to run Codex, I see the following printed to stderr at
startup:
```
(node:71308) ExperimentalWarning: Importing JSON modules is an experimental feature and might change at any time
(Use `node --trace-warnings ...` to show where the warning was created)
```
Note it is a warning and does not prevent Codex from running.
In Node 22.12, the warning goes away, but the warning still appears in
Node 22.11. For Node 22, 22.15.0 is the current LTS version, so LTS
users will not see this.
Also, something about moving the definition of `CLI_VERSION` caused a
problem with the mocks in `check-updates.test.ts`. I asked Codex to fix
it, and it came up with the change to the test configs. I don't know
enough about vitest to understand what it did, but the tests seem
healthy again, so I'm going with it.
I had seen issues where `codex-rs` would not always write files without
me pressuring it to do so, and between that and the report of
https://github.com/openai/codex/issues/900, I decided to look into this
further. I found two serious issues with agent instructions:
(1) We were only sending agent instructions on the first turn, but
looking at the TypeScript code, we should be sending them on every turn.
(2) There was a serious issue where the agent instructions were
frequently lost:
* The TypeScript CLI appears to keep writing `~/.codex/instructions.md`:
55142e3e6c/codex-cli/src/utils/config.ts (L586)
* If `instructions.md` is present, the Rust CLI uses the contents of it
INSTEAD OF the default prompt, even if `instructions.md` is empty:
55142e3e6c/codex-rs/core/src/config.rs (L202-L203)
The combination of these two things means that I have been using
`codex-rs` without these key instructions:
https://github.com/openai/codex/blob/main/codex-rs/core/prompt.md
Looking at the TypeScript code, it appears we should be concatenating
these three items every time (if they exist):
* `prompt.md`
* `~/.codex/instructions.md`
* nearest `AGENTS.md`
This PR fixes things so that:
* `Config.instructions` is `None` if `instructions.md` is empty
* `Payload.instructions` is now `&'a str` instead of `Option<&'a
String>` because we should always have _something_ to send
* `Prompt` now has a `get_full_instructions()` helper that returns a
`Cow<str>` that will always include the agent instructions first.
This PR fixes a potential path traversal vulnerability by ensuring all
paths are properly normalized in the `resolvePathAgainstWorkdir`
function.
## Changes
- Added path normalization for both absolute and relative paths
- Ensures normalized paths are used in all subsequent operations
- Prevents potential path traversal attacks through non-normalized paths
This minimal change addresses the security concern without adding
unnecessary complexity, while maintaining compatibility with existing
code.
This PR introduces an optional build flag, `--native`, that will build a
version of the Codex npm module that:
- Includes both the Node.js and native Rust versions (for Mac and Linux)
- Will run the native version if `CODEX_RUST=1` is set
- Runs the TypeScript version otherwise
Note this PR also updates the workflow URL to
https://github.com/openai/codex/actions/runs/14872557396, as that is a
build from today that includes everything up through
https://github.com/openai/codex/pull/843.
Test Plan:
In `~/code/codex/codex-cli`, I ran:
```
pnpm stage-release --native
```
The end of the output was:
```
Staged version 0.1.2505121317 for release in /var/folders/wm/f209bc1n2bd_r0jncn9s6j_00000gp/T/tmp.xd2p5ETYGN
Test Node:
node /var/folders/wm/f209bc1n2bd_r0jncn9s6j_00000gp/T/tmp.xd2p5ETYGN/bin/codex.js --help
Test Rust:
CODEX_RUST=1 node /var/folders/wm/f209bc1n2bd_r0jncn9s6j_00000gp/T/tmp.xd2p5ETYGN/bin/codex.js --help
Next: cd "/var/folders/wm/f209bc1n2bd_r0jncn9s6j_00000gp/T/tmp.xd2p5ETYGN" && npm publish --tag native
```
I verified that running each of these commands ran the expected version
of Codex.
While here, I also added `bin` to the `files` list in `package.json`,
which should have been done as part of
https://github.com/openai/codex/pull/757, as that added new entries to
`bin` that were matched by `.gitignore` but should have been included in
a release.
Adds `expect()` as a denied lint. Same deal applies with `unwrap()`
where we now need to put `#[expect(...` on ones that we legit want. Took
care to enable `expect()` in test contexts.
# Tests
```
cargo fmt
cargo clippy --all-features --all-targets --no-deps -- -D warnings
cargo test
```
This PR fixes things so that:
* when the `BottomPane` is in the `StatusIndicator` state, the border
should be dim
* when the `BottomPane` does not have input focus, the border should be
dim
To make it easier to enforce this invariant, this PR introduces
`BottomPane::set_state()` that will:
* update `self.state`
* call `update_border_for_input_focus()`
* request a repaint
This should make it easier to enforce other updates for state changes
going forward.
As shown in the screenshot, we now include reasoning messages from the
model in the TUI under the heading "codex reasoning":

To ensure these are visible by default when using `o4-mini`, this also
changes the default value for `summary` (formerly `generate_summary`,
which is deprecated in favor of `summary` according to the docs) from
unset to `"auto"`.
The TypeScript CLI already has support for including the contents of
`AGENTS.md` in the instructions sent with the first turn of a
conversation. This PR brings this functionality to the Rust CLI.
To be considered, `AGENTS.md` must be in the `cwd` of the session, or in
one of the parent folders up to a Git/filesystem root (whichever is
encountered first).
By default, a maximum of 32 KiB of `AGENTS.md` will be included, though
this is configurable using the new-in-this-PR `project_doc_max_bytes`
option in `config.toml`.
* Add flexMode to stored config, and use it during config loading unless
the flag is explicitly passed.
* If the config asks for flexMode and the model doesn't support it,
silently disable flexMode.
Resolves#803
- Added ArceeAI as a provider - https://conductor.arcee.ai/v1
- Compatible with ArceeAI SLMs (Virtuoso, Maestro)
- Works with ArceeAI's Conductor auto‑router models (auto, auto‑tool),
once #817 is merged
- Fixes guard by using optional chaining to safely check
chunk.choices?.[0] before accessing.
- Currently, accessing chunk.choices[0] without checking could throw if
choices was missing from the chunk.
Reasoning effort was already available, but not expressed into the help
text, so it was non-discoverable.
Other issues discovered, but will fix in separate PR since they are
larger:
* #816 reasoningEffort isn't displayed in the terminal-header, making it
rather hard to see the state of configuration
* I don't think the config file setting works, as the CLI option always
"wins" and overwrites it
Fix: retry on server_error responses that lack an HTTP status code
### What happened
1. An OpenAI endpoint returned a **5xx** (transient server-side
failure).
2. The SDK surfaced it as an `APIError` with
{ "type": "server_error", "message": "...", "status": undefined }
(The SDK does not always populate `status` for these cases.)
3. Our retry logic in `src/utils/agent/agent-loop.ts` determined
isServerError = typeof status === "number" && status >= 500;
Because `status` was *undefined*, the error was **not** recognised as
retriable, the exception bubbled out, and the CLI crashed with a stack
trace similar to:
Error: An error occurred while processing the request.
at .../cli.js:474:1514
### Root cause
The transient-error detector ignored the semantic flag type ===
"server_error" that the SDK provides when the numeric status is missing.
#### Fix (1 loc + comment)
Extend the check:
const status = errCtx?.status ?? errCtx?.httpStatus ??
errCtx?.statusCode;
const isServerError = (typeof status === "number" && status >= 500) ||
// classic 5xx
errCtx?.type === "server_error"; // <-- NEW
Now the agent:
* Retries up to **5** times (existing logic) when the backend reports a
transient failure, even if `status` is absent.
* If all retries fail, surfaces the existing friendly system message
instead of an uncaught exception.
### Tests & validation
pnpm test # all suites green (17 agent-level tests now include this
path)
pnpm run lint # 0 errors / warnings
pnpm run typecheck
A new unit-test file isn’t required—the behaviour is already covered by
tests/agent-server-retry.test.ts, which stubs type: "server_error" and
now passes with the updated logic.
### Impact
* No API-surface changes.
* Prevents CLI crashes on intermittent OpenAI outages.
* Adds robust handling for other providers that may follow the same
error-shape.
When using Codex to develop Codex itself, I noticed that sometimes it
would try to add `#[ignore]` to the following tests:
```
keeps_previous_response_id_between_tasks()
retries_on_early_close()
```
Both of these tests start a `MockServer` that launches an HTTP server on
an ephemeral port and requires network access to hit it, which the
Seatbelt policy associated with `--full-auto` correctly denies. If I
wasn't paying attention to the code that Codex was generating, one of
these `#[ignore]` annotations could have slipped into the codebase,
effectively disabling the test for everyone.
To that end, this PR enables an experimental environment variable named
`CODEX_SANDBOX_NETWORK_DISABLED` that is set to `1` if the
`SandboxPolicy` used to spawn the process does not have full network
access. I say it is "experimental" because I'm not convinced this API is
quite right, but we need to start somewhere. (It might be more
appropriate to have an env var like `CODEX_SANDBOX=full-auto`, but the
challenge is that our newer `SandboxPolicy` abstraction does not map to
a simple set of enums like in the TypeScript CLI.)
We leverage this new functionality by adding the following code to the
aforementioned tests as a way to "dynamically disable" them:
```rust
if std::env::var(CODEX_SANDBOX_NETWORK_DISABLED_ENV_VAR).is_ok() {
println!(
"Skipping test because it cannot execute when network is disabled in a Codex sandbox."
);
return;
}
```
We can use the `debug seatbelt --full-auto` command to verify that
`cargo test` fails when run under Seatbelt prior to this change:
```
$ cargo run --bin codex -- debug seatbelt --full-auto -- cargo test
---- keeps_previous_response_id_between_tasks stdout ----
thread 'keeps_previous_response_id_between_tasks' panicked at /Users/mbolin/.cargo/registry/src/index.crates.io-1949cf8c6b5b557f/wiremock-0.6.3/src/mock_server/builder.rs:107:46:
Failed to bind an OS port for a mock server.: Os { code: 1, kind: PermissionDenied, message: "Operation not permitted" }
note: run with `RUST_BACKTRACE=1` environment variable to display a backtrace
failures:
keeps_previous_response_id_between_tasks
test result: FAILED. 0 passed; 1 failed; 0 ignored; 0 measured; 0 filtered out; finished in 0.00s
error: test failed, to rerun pass `-p codex-core --test previous_response_id`
```
Though after this change, the above command succeeds! This means that,
going forward, when Codex operates on Codex itself, when it runs `cargo
test`, only "real failures" should cause the command to fail.
As part of this change, I decided to tighten up the codepaths for
running `exec()` for shell tool calls. In particular, we do it in `core`
for the main Codex business logic itself, but we also expose this logic
via `debug` subcommands in the CLI in the `cli` crate. The logic for the
`debug` subcommands was not quite as faithful to the true business logic
as I liked, so I:
* refactored a bit of the Linux code, splitting `linux.rs` into
`linux_exec.rs` and `landlock.rs` in the `core` crate.
* gating less code behind `#[cfg(target_os = "linux")]` because such
code does not get built by default when I develop on Mac, which means I
either have to build the code in Docker or wait for CI signal
* introduced `macro_rules! configure_command` in `exec.rs` so we can
have both sync and async versions of this code. The synchronous version
seems more appropriate for straight threads or potentially fork/exec.
## Summary
This PR introduces support for Azure OpenAI as a provider within the
Codex CLI. Users can now configure the tool to leverage their Azure
OpenAI deployments by specifying `"azure"` as the provider in
`config.json` and setting the corresponding `AZURE_OPENAI_API_KEY` and
`AZURE_OPENAI_API_VERSION` environment variables. This functionality is
added alongside the existing provider options (OpenAI, OpenRouter,
etc.).
Related to #92
**Note:** This PR is currently in **Draft** status because tests on the
`main` branch are failing. It will be marked as ready for review once
the `main` branch is stable and tests are passing.
---
## What’s Changed
- **Configuration (`config.ts`, `providers.ts`, `README.md`):**
- Added `"azure"` to the supported `providers` list in `providers.ts`,
specifying its name, default base URL structure, and environment
variable key (`AZURE_OPENAI_API_KEY`).
- Defined the `AZURE_OPENAI_API_VERSION` environment variable in
`config.ts` with a default value (`2025-03-01-preview`).
- Updated `README.md` to:
- Include "azure" in the list of providers.
- Add a configuration section for Azure OpenAI, detailing the required
environment variables (`AZURE_OPENAI_API_KEY`,
`AZURE_OPENAI_API_VERSION`) with examples.
- **Client Instantiation (`terminal-chat.tsx`, `singlepass-cli-app.tsx`,
`agent-loop.ts`, `compact-summary.ts`, `model-utils.ts`):**
- Modified various components and utility functions where the OpenAI
client is initialized.
- Added conditional logic to check if the configured `provider` is
`"azure"`.
- If the provider is Azure, the `AzureOpenAI` client from the `openai`
package is instantiated, using the configured `baseURL`, `apiKey` (from
`AZURE_OPENAI_API_KEY`), and `apiVersion` (from
`AZURE_OPENAI_API_VERSION`).
- Otherwise, the standard `OpenAI` client is instantiated as before.
- **Dependencies:**
- Relies on the `openai` package's built-in support for `AzureOpenAI`.
No *new* external dependencies were added specifically for this Azure
implementation beyond the `openai` package itself.
---
## How to Test
*This has been tested locally and confirmed working with Azure OpenAI.*
1. **Configure `config.json`:**
Ensure your `~/.codex/config.json` (or project-specific config) includes
Azure and sets it as the active provider:
```json
{
"providers": {
// ... other providers
"azure": {
"name": "AzureOpenAI",
"baseURL": "https://YOUR_RESOURCE_NAME.openai.azure.com", // Replace
with your Azure endpoint
"envKey": "AZURE_OPENAI_API_KEY"
}
},
"provider": "azure", // Set Azure as the active provider
"model": "o4-mini" // Use your Azure deployment name here
// ... other config settings
}
```
2. **Set up Environment Variables:**
```bash
# Set the API Key for your Azure OpenAI resource
export AZURE_OPENAI_API_KEY="your-azure-api-key-here"
# Set the API Version (Optional - defaults to `2025-03-01-preview` if
not set)
# Ensure this version is supported by your Azure deployment and endpoint
export AZURE_OPENAI_API_VERSION="2025-03-01-preview"
```
3. **Get the Codex CLI by building from this PR branch:**
Clone your fork, checkout this branch (`feat/azure-openai`), navigate to
`codex-cli`, and build:
```bash
# cd /path/to/your/fork/codex
git checkout feat/azure-openai # Or your branch name
cd codex-cli
corepack enable
pnpm install
pnpm build
```
4. **Invoke Codex:**
Run the locally built CLI using `node` from the `codex-cli` directory:
```bash
node ./dist/cli.js "Explain the purpose of this PR"
```
*(Alternatively, if you ran `pnpm link` after building, you can use
`codex "Explain the purpose of this PR"` from anywhere)*.
5. **Verify:** Confirm that the command executes successfully and
interacts with your configured Azure OpenAI deployment.
---
## Tests
- [x] Tested locally against an Azure OpenAI deployment using API Key
authentication. Basic commands and interactions confirmed working.
---
## Checklist
- [x] Added Azure provider details to configuration files
(`providers.ts`, `config.ts`).
- [x] Implemented conditional `AzureOpenAI` client initialization based
on provider setting.
- [x] Ensured `apiVersion` is passed correctly to the Azure client.
- [x] Updated `README.md` with Azure OpenAI setup instructions.
- [x] Manually tested core functionality against a live Azure OpenAI
endpoint.
- [x] Add/update automated tests for the Azure code path (pending `main`
stability).
cc @theabhinavdas @nikodem-wrona @fouad-openai @tibo-openai (adjust as
needed)
---
I have read the CLA Document and I hereby sign the CLA
Noticed that when pasting multi-line blocks, each newline was treated
like a new submission.
Update tui to handle Paste directly and map newlines to shift+enter.
# Test
Copied this into clipboard:
```
Do nothing.
Explain this repo to me.
```
Pasted in and saw multi-line input. Hitting Enter then submitted the
full block.
This PR is a straight refactor so that creating the `Child` process for
an `shell` tool call and consuming its output can be separate concerns.
For the actual tool call, we will always apply
`consume_truncated_output()`, but for the top-level debug commands in
the CLI (e.g., `debug seatbelt` and `debug landlock`), we only want to
use the `spawn_child()` part of `exec()`.
We want the subcommands to match the `shell` tool call usage as
faithfully as possible. This becomes more important when we introduce a
new parameter to `spawn_child()` in
https://github.com/openai/codex/pull/879.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/878).
* #879
* __->__ #878
I inadvertently regressed support for the Responses API when adding
support for the chat completions API in
https://github.com/openai/codex/pull/862. This should get both APIs
working again, but the chat completions codepath seems more complex than
necessary. I'll try to clean that up shortly, but I want to get things
working again ASAP.
This is a substantial PR to add support for the chat completions API,
which in turn makes it possible to use non-OpenAI model providers (just
like in the TypeScript CLI):
* It moves a number of structs from `client.rs` to `client_common.rs` so
they can be shared.
* It introduces support for the chat completions API in
`chat_completions.rs`.
* It updates `ModelProviderInfo` so that `env_key` is `Option<String>`
instead of `String` (for e.g., ollama) and adds a `wire_api` field
* It updates `client.rs` to choose between `stream_responses()` and
`stream_chat_completions()` based on the `wire_api` for the
`ModelProviderInfo`
* It updates the `exec` and TUI CLIs to no longer fail if the
`OPENAI_API_KEY` environment variable is not set
* It updates the TUI so that `EventMsg::Error` is displayed more
prominently when it occurs, particularly now that it is important to
alert users to the `CodexErr::EnvVar` variant.
* `CodexErr::EnvVar` was updated to include an optional `instructions`
field so we can preserve the behavior where we direct users to
https://platform.openai.com if `OPENAI_API_KEY` is not set.
* Cleaned up the "welcome message" in the TUI to ensure the model
provider is displayed.
* Updated the docs in `codex-rs/README.md`.
To exercise the chat completions API from OpenAI models, I added the
following to my `config.toml`:
```toml
model = "gpt-4o"
model_provider = "openai-chat-completions"
[model_providers.openai-chat-completions]
name = "OpenAI using Chat Completions"
base_url = "https://api.openai.com/v1"
env_key = "OPENAI_API_KEY"
wire_api = "chat"
```
Though to test a non-OpenAI provider, I installed ollama with mistral
locally on my Mac because ChatGPT said that would be a good match for my
hardware:
```shell
brew install ollama
ollama serve
ollama pull mistral
```
Then I added the following to my `~/.codex/config.toml`:
```toml
model = "mistral"
model_provider = "ollama"
```
Note this code could certainly use more test coverage, but I want to get
this in so folks can start playing with it.
For reference, I believe https://github.com/openai/codex/pull/247 was
roughly the comparable PR on the TypeScript side.
I installed the GitHub Actions extension for VS Code and it started
giving me lint warnings about this line:
a9adb4175c/.github/workflows/rust-ci.yml (L99)
Using an env var to track the state of individual steps was not great,
so I did some research about GitHub actions, which led to the discovery
of combining `continue-on-error: true` with `if .. steps.STEP.outcome ==
'failure'...`.
Apparently there is also a `failure()` macro that is supposed to make
this simpler, but I saw a number of complains online about it not
working as expected. Checking `outcome` seems maybe more reliable at the
cost of being slightly more verbose.
https://github.com/openai/codex/pull/855 added the clippy warning to
disallow `unwrap()`, but apparently we were not verifying that tests
were "clippy clean" in CI, so I ended up with a lot of local errors in
VS Code.
This turns on the check in CI and fixes the offenders.
I noticed that sometimes I would enter a new message, but it would not
show up in the conversation history. Even if I focused the conversation
history and tried to scroll it to the bottom, I could not bring it into
view. At first, I was concerned that messages were not making it to the
UI layer, but I added debug statements and verified that was not the
issue.
It turned out that, previous to this PR, lines that are wider than the
viewport take up multiple lines of vertical space because `wrap()` was
set on the `Paragraph` inside the scroll pane. Unfortunately, that broke
our "scrollbar math" that assumed each `Line` contributes one line of
height in the UI.
This PR removes the `wrap()`, but introduces a new issue, which is that
now you cannot see long lines without resizing your terminal window. For
now, I filed an issue here:
https://github.com/openai/codex/issues/869
I think the long-term fix is to fix our math so it calculates the height
of a `Line` after it is wrapped given the current width of the viewport.
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.
Some effects of this change:
- New formatting changes across many files. No functionality changes
should occur from that.
- Calls to `set_env` are considered unsafe, since this only happens in
tests we wrap them in `unsafe` blocks
I started this PR because I wanted to share the `format_duration()`
utility function in `codex-rs/exec/src/event_processor.rs` with the TUI.
The question was: where to put it?
`core` should have as few dependencies as possible, so moving it there
would introduce a dependency on `chrono`, which seemed undesirable.
`core` already had this `cli` feature to deal with a similar situation
around sharing common utility functions, so I decided to:
* make `core` feature-free
* introduce `common`
* `common` can have as many "special interest" features as it needs,
each of which can declare their own deps
* the first two features of common are `cli` and `elapsed`
In practice, this meant updating a number of `Cargo.toml` files,
replacing this line:
```toml
codex-core = { path = "../core", features = ["cli"] }
```
with these:
```toml
codex-core = { path = "../core" }
codex-common = { path = "../common", features = ["cli"] }
```
Moving `format_duration()` into its own file gave it some "breathing
room" to add a unit test, so I had Codex generate some tests and new
support for durations over 1 minute.
Out of the box, we will make `/` the only official "escape sequence" for
commands in the Rust TUI. We will look to support `q` (or any string you
want to use as a "macro") via a plugin, but not make it part of the
default experience.
Existing `q` users will have to get by with `ctrl+d` for now.
https://github.com/openai/codex/pull/829 noted it introduced a circular
dep between `codex.rs` and `mcp_tool_call.rs`. This attempts to clean
things up: the circular dep still exists, but at least all the fields of
`Session` are private again.
This adds initial support for MCP servers in the style of Claude Desktop
and Cursor. Note this PR is the bare minimum to get things working end
to end: all configured MCP servers are launched every time Codex is run,
there is no recovery for MCP servers that crash, etc.
(Also, I took some shortcuts to change some fields of `Session` to be
`pub(crate)`, which also means there are circular deps between
`codex.rs` and `mcp_tool_call.rs`, but I will clean that up in a
subsequent PR.)
`codex-rs/README.md` is updated as part of this PR to explain how to use
this feature. There is a bit of plumbing to route the new settings from
`Config` to the business logic in `codex.rs`. The most significant
chunks for new code are in `mcp_connection_manager.rs` (which defines
the `McpConnectionManager` struct) and `mcp_tool_call.rs`, which is
responsible for tool calls.
This PR also introduces new `McpToolCallBegin` and `McpToolCallEnd`
event types to the protocol, but does not add any handlers for them.
(See https://github.com/openai/codex/pull/836 for initial usage.)
To test, I added the following to my `~/.codex/config.toml`:
```toml
# Local build of https://github.com/hideya/mcp-server-weather-js
[mcp_servers.weather]
command = "/Users/mbolin/code/mcp-server-weather-js/dist/index.js"
args = []
```
And then I ran the following:
```
codex-rs$ cargo run --bin codex exec 'what is the weather in san francisco'
[2025-05-06T22:40:05] Task started: 1
[2025-05-06T22:40:18] Agent message: Here’s the latest National Weather Service forecast for San Francisco (downtown, near 37.77° N, 122.42° W):
This Afternoon (Tue):
• Sunny, high near 69 °F
• West-southwest wind around 12 mph
Tonight:
• Partly cloudy, low around 52 °F
• SW wind 7–10 mph
...
```
Note that Codex itself is not able to make network calls, so it would
not normally be able to get live weather information like this. However,
the weather MCP is [currently] not run under the Codex sandbox, so it is
able to hit `api.weather.gov` and fetch current weather information.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/829).
* #836
* __->__ #829
I discovered that `cargo build` worked for the entire workspace, but not
for the `mcp-client` or `core` crates.
* `mcp-client` failed to build because it underspecified the set of
features it needed from `tokio`.
* `core` failed to build because it was using a "feature" of its own
crate in the default, no-feature version.
This PR fixes the builds and adds a check in CI to defend against this
sort of thing going forward.
Cleans up the signature for `new_stdio_client()` to more closely mirror
how MCP servers are declared in config files (`command`, `args`, `env`).
Also takes a cue from Claude Code where the MCP server is launched with
a restricted `env` so that it only includes "safe" things like `USER`
and `PATH` (see the `create_env_for_mcp_server()` function introduced in
this PR for details) by default, as it is common for developers to have
sensitive API keys present in their environment that should only be
forwarded to the MCP server when the user has explicitly configured it
to do so.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/831).
* #829
* __->__ #831
This PR introduces an initial `McpClient` that we will use to give Codex
itself programmatic access to foreign MCPs. This does not wire it up in
Codex itself yet, but the new `mcp-client` crate includes a `main.rs`
for basic testing for now.
Manually tested by sending a `tools/list` request to Codex's own MCP
server:
```
codex-rs$ cargo build
codex-rs$ cargo run --bin codex-mcp-client ./target/debug/codex-mcp-server
{
"tools": [
{
"description": "Run a Codex session. Accepts configuration parameters matching the Codex Config struct.",
"inputSchema": {
"properties": {
"approval-policy": {
"description": "Execution approval policy expressed as the kebab-case variant name (`unless-allow-listed`, `auto-edit`, `on-failure`, `never`).",
"enum": [
"auto-edit",
"unless-allow-listed",
"on-failure",
"never"
],
"type": "string"
},
"cwd": {
"description": "Working directory for the session. If relative, it is resolved against the server process's current working directory.",
"type": "string"
},
"disable-response-storage": {
"description": "Disable server-side response storage.",
"type": "boolean"
},
"model": {
"description": "Optional override for the model name (e.g. \"o3\", \"o4-mini\")",
"type": "string"
},
"prompt": {
"description": "The *initial user prompt* to start the Codex conversation.",
"type": "string"
},
"sandbox-permissions": {
"description": "Sandbox permissions using the same string values accepted by the CLI (e.g. \"disk-write-cwd\", \"network-full-access\").",
"items": {
"enum": [
"disk-full-read-access",
"disk-write-cwd",
"disk-write-platform-user-temp-folder",
"disk-write-platform-global-temp-folder",
"disk-full-write-access",
"network-full-access"
],
"type": "string"
},
"type": "array"
}
},
"required": [
"prompt"
],
"type": "object"
},
"name": "codex"
}
]
}
```
This Pull Request addresses an issue where the output of commands
executed in the raw-exec utility was being truncated due to restrictive
limits on the number of lines and bytes collected. The truncation caused
the message [Output truncated: too many lines or bytes] to appear when
processing large outputs, which could hinder the functionality of the
CLI.
Changes Made
Increased the maximum output limits in the
[createTruncatingCollector](https://github.com/openai/codex/pull/575)
utility:
Bytes: Increased from 10 KB to 100 KB.
Lines: Increased from 256 lines to 1024 lines.
Installed the @types/node package to resolve missing type definitions
for [NodeJS](https://github.com/openai/codex/pull/575) and
[Buffer](https://github.com/openai/codex/pull/575).
Verified and fixed any related errors in the
[createTruncatingCollector](https://github.com/openai/codex/pull/575)
implementation.
Issue Solved:
This PR ensures that larger outputs can be processed without truncation,
improving the usability of the CLI for commands that generate extensive
output. https://github.com/openai/codex/issues/509
---------
Co-authored-by: Michael Bolin <bolinfest@gmail.com>
This PR replaces the placeholder `"echo"` tool call in the MCP server
with a `"codex"` tool that calls Codex. Events such as
`ExecApprovalRequest` and `ApplyPatchApprovalRequest` are not handled
properly yet, but I have `approval_policy = "never"` set in my
`~/.codex/config.toml` such that those codepaths are not exercised.
The schema for this MPC tool is defined by a new `CodexToolCallParam`
struct introduced in this PR. It is fairly similar to `ConfigOverrides`,
as the param is used to help create the `Config` used to start the Codex
session, though it also includes the `prompt` used to kick off the
session.
This PR also introduces the use of the third-party `schemars` crate to
generate the JSON schema, which is verified in the
`verify_codex_tool_json_schema()` unit test.
Events that are dispatched during the Codex session are sent back to the
MCP client as MCP notifications. This gives the client a way to monitor
progress as the tool call itself may take minutes to complete depending
on the complexity of the task requested by the user.
In the video below, I launched the server via:
```shell
mcp-server$ RUST_LOG=debug npx @modelcontextprotocol/inspector cargo run --
```
In the video, you can see the flow of:
* requesting the list of tools
* choosing the **codex** tool
* entering a value for **prompt** and then making the tool call
Note that I left the other fields blank because when unspecified, the
values in my `~/.codex/config.toml` were used:
https://github.com/user-attachments/assets/1975058c-b004-43ef-8c8d-800a953b8192
Note that while using the inspector, I did run into
https://github.com/modelcontextprotocol/inspector/issues/293, though the
tip about ensuring I had only one instance of the **MCP Inspector** tab
open in my browser seemed to fix things.
https://github.com/openai/codex/pull/800 kicked off some work to be more
disciplined about honoring the `cwd` param passed in rather than
assuming `std::env::current_dir()` as the `cwd`. As part of this, we
need to ensure `apply_patch` calls honor the appropriate `cwd` as well,
which is significant if the paths in the `apply_patch` arg are not
absolute paths themselves. Failing that:
- The `apply_patch` function call can contain an optional`workdir`
param, so:
- If specified and is an absolute path, it should be used to resolve
relative paths
- If specified and is a relative path, should be resolved against
`Config.cwd` and then any relative paths will be resolved against the
result
- If `workdir` is not specified on the function call, relative paths
should be resolved against `Config.cwd`
Note that we had a similar issue in the TypeScript CLI that was fixed in
https://github.com/openai/codex/pull/556.
As part of the fix, this PR introduces `ApplyPatchAction` so clients can
deal with that instead of the raw `HashMap<PathBuf,
ApplyPatchFileChange>`. This enables us to enforce, by construction,
that all paths contained in the `ApplyPatchAction` are absolute paths.
https://github.com/openai/codex/pull/800 made `cwd` a property of
`Config` and made it so the `cwd` is not necessarily
`std::env::current_dir()`. As such, `is_inside_git_repo()` should check
`Config.cwd` rather than `std::env::current_dir()`.
This PR updates `is_inside_git_repo()` to take `Config` instead of an
arbitrary `PathBuf` to force the check to operate on a `Config` where
`cwd` has been resolved to what the user specified.
In order to expose Codex via an MCP server, I realized that we should be
taking `cwd` as a parameter rather than assuming
`std::env::current_dir()` as the `cwd`. Specifically, the user may want
to start a session in a directory other than the one where the MCP
server has been started.
This PR makes `cwd: PathBuf` a required field of `Session` and threads
it all the way through, though I think there is still an issue with not
honoring `workdir` for `apply_patch`, which is something we also had to
fix in the TypeScript version: https://github.com/openai/codex/pull/556.
This also adds `-C`/`--cd` to change the cwd via the command line.
To test, I ran:
```
cargo run --bin codex -- exec -C /tmp 'show the output of ls'
```
and verified it showed the contents of my `/tmp` folder instead of
`$PWD`.
https://github.com/openai/codex/pull/793 had important information on
the `notify` config option that seemed worth memorializing, so this PR
updates the documentation about all of the configurable options in
`~/.codex/config.toml`.
With this change, you can specify a program that will be executed to get
notified about events generated by Codex. The notification info will be
packaged as a JSON object. The supported notification types are defined
by the `UserNotification` enum introduced in this PR. Initially, it
contains only one variant, `AgentTurnComplete`:
```rust
pub(crate) enum UserNotification {
#[serde(rename_all = "kebab-case")]
AgentTurnComplete {
turn_id: String,
/// Messages that the user sent to the agent to initiate the turn.
input_messages: Vec<String>,
/// The last message sent by the assistant in the turn.
last_assistant_message: Option<String>,
},
}
```
This is intended to support the common case when a "turn" ends, which
often means it is now your chance to give Codex further instructions.
For example, I have the following in my `~/.codex/config.toml`:
```toml
notify = ["python3", "/Users/mbolin/.codex/notify.py"]
```
I created my own custom notifier script that calls out to
[terminal-notifier](https://github.com/julienXX/terminal-notifier) to
show a desktop push notification on macOS. Contents of `notify.py`:
```python
#!/usr/bin/env python3
import json
import subprocess
import sys
def main() -> int:
if len(sys.argv) != 2:
print("Usage: notify.py <NOTIFICATION_JSON>")
return 1
try:
notification = json.loads(sys.argv[1])
except json.JSONDecodeError:
return 1
match notification_type := notification.get("type"):
case "agent-turn-complete":
assistant_message = notification.get("last-assistant-message")
if assistant_message:
title = f"Codex: {assistant_message}"
else:
title = "Codex: Turn Complete!"
input_messages = notification.get("input_messages", [])
message = " ".join(input_messages)
title += message
case _:
print(f"not sending a push notification for: {notification_type}")
return 0
subprocess.check_output(
[
"terminal-notifier",
"-title",
title,
"-message",
message,
"-group",
"codex",
"-ignoreDnD",
"-activate",
"com.googlecode.iterm2",
]
)
return 0
if __name__ == "__main__":
sys.exit(main())
```
For reference, here are related PRs that tried to add this functionality
to the TypeScript version of the Codex CLI:
* https://github.com/openai/codex/pull/160
* https://github.com/openai/codex/pull/498
While creating a basic MCP server in
https://github.com/openai/codex/pull/792, I discovered a number of bugs
with the initial `mcp-types` crate that I needed to fix in order to
implement the server.
For example, I discovered that when serializing a message, `"jsonrpc":
"2.0"` was not being included.
I changed the codegen so that the field is added as:
```rust
#[serde(rename = "jsonrpc", default = "default_jsonrpc")]
pub jsonrpc: String,
```
This ensures that the field is serialized as `"2.0"`, though the field
still has to be assigned, which is tedious. I may experiment with
`Default` or something else in the future. (I also considered creating a
custom serializer, but I'm not sure it's worth the trouble.)
While here, I also added `MCP_SCHEMA_VERSION` and `JSONRPC_VERSION` as
`pub const`s for the crate.
I also discovered that MCP rejects sending `null` for optional fields,
so I had to add `#[serde(skip_serializing_if = "Option::is_none")]` on
`Option` fields.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/791).
* #792
* __->__ #791
This adds our own `mcp-types` crate to our Cargo workspace. We vendor in
the
[`2025-03-26/schema.json`](05f2045136/schema/2025-03-26/schema.json)
from the MCP repo and introduce a `generate_mcp_types.py` script to
codegen the `lib.rs` from the JSON schema.
Test coverage is currently light, but I plan to refine things as we
start making use of this crate.
And yes, I am aware that
https://github.com/modelcontextprotocol/rust-sdk exists, though the
published https://crates.io/crates/rmcp appears to be a competing
effort. While things are up in the air, it seems better for us to
control our own version of this code.
Incidentally, Codex did a lot of the work for this PR. I told it to
never edit `lib.rs` directly and instead to update
`generate_mcp_types.py` and then re-run it to update `lib.rs`. It
followed these instructions and once things were working end-to-end, I
iteratively asked for changes to the tests until the API looked
reasonable (and the code worked). Codex was responsible for figuring out
what to do to `generate_mcp_types.py` to achieve the requested test/API
changes.
Building on top of https://github.com/openai/codex/pull/757, this PR
updates Codex to use the Landlock executor binary for sandboxing in the
Node.js CLI. Note that Codex has to be invoked with either `--full-auto`
or `--auto-edit` to activate sandboxing. (Using `--suggest` or
`--dangerously-auto-approve-everything` ensures the sandboxing codepath
will not be exercised.)
When I tested this on a Linux host (specifically, `Ubuntu 24.04.1 LTS`),
things worked as expected: I ran Codex CLI with `--full-auto` and then
asked it to do `echo 'hello mbolin' into hello_world.txt` and it
succeeded without prompting me.
However, in my testing, I discovered that the sandboxing did *not* work
when using `--full-auto` in a Linux Docker container from a macOS host.
I updated the code to throw a detailed error message when this happens:

This introduces `./codex-cli/scripts/stage_release.sh`, which is a shell
script that stages a release for the Node.js module in a temp directory.
It updates the release to include these native binaries:
```
bin/codex-linux-sandbox-arm64
bin/codex-linux-sandbox-x64
```
though this PR does not update Codex CLI to use them yet.
When doing local development, run
`./codex-cli/scripts/install_native_deps.sh` to install these in your
own `bin/` folder.
This PR also updates `README.md` to document the new workflow.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/757).
* #763
* __->__ #757
## `0.1.2504301751`
### 🚀 Features
- User config api key (#569)
- `@mention` files in codex (#701)
- Add `--reasoning` CLI flag (#314)
- Lower default retry wait time and increase number of tries (#720)
- Add common package registries domains to allowed-domains list (#414)
### 🪲 Bug Fixes
- Insufficient quota message (#758)
- Input keyboard shortcut opt+delete (#685)
- `/diff` should include untracked files (#686)
- Only allow running without sandbox if explicitly marked in safe
container (#699)
- Tighten up check for /usr/bin/sandbox-exec (#710)
- Check if sandbox-exec is available (#696)
- Duplicate messages in quiet mode (#680)
Solves #700
## State of the World Before
Prior to this PR, when users wanted to share file contents with Codex,
they had two options:
- Manually copy and paste file contents into the chat
- Wait for the assistant to use the shell tool to view the file
The second approach required the assistant to:
1. Recognize the need to view a file
2. Execute a shell tool call
3. Wait for the tool call to complete
4. Process the file contents
This consumed extra tokens and reduced user control over which files
were shared with the model.
## State of the World After
With this PR, users can now:
- Reference files directly in their chat input using the `@path` syntax
- Have file contents automatically expanded into XML blocks before being
sent to the LLM
For example, users can type `@src/utils/config.js` in their message, and
the file contents will be included in context. Within the terminal chat
history, these file blocks will be collapsed back to `@path` format in
the UI for clean presentation.
Tag File suggestions:
<img width="857" alt="file-suggestions"
src="https://github.com/user-attachments/assets/397669dc-ad83-492d-b5f0-164fab2ff4ba"
/>
Tagging files in action:
<img width="858" alt="tagging-files"
src="https://github.com/user-attachments/assets/0de9d559-7b7f-4916-aeff-87ae9b16550a"
/>
Demo video of file tagging:
[](https://www.youtube.com/watch?v=vL4LqtBnqt8)
## Implementation Details
This PR consists of 2 main components:
1. **File Tag Utilities**:
- New `file-tag-utils.ts` utility module that handles both expansion and
collapsing of file tags
- `expandFileTags()` identifies `@path` tokens and replaces them with
XML blocks containing file contents
- `collapseXmlBlocks()` reverses the process, converting XML blocks back
to `@path` format for UI display
- Tokens are only expanded if they point to valid files (directories are
ignored)
- Expansion happens just before sending input to the model
2. **Terminal Chat Integration**:
- Leveraged the existing file system completion system for tabbing to
support the `@path` syntax
- Added `updateFsSuggestions` helper to manage filesystem suggestions
- Added `replaceFileSystemSuggestion` to replace input with filesystem
suggestions
- Applied `collapseXmlBlocks` in the chat response rendering so that
tagged files are shown as simple `@path` tags
The PR also includes test coverage for both the UI and the file tag
utilities.
## Next Steps
Some ideas I'd like to implement if this feature gets merged:
- Line selection: `@path[50:80]` to grab specific sections of files
- Method selection: `@path#methodName` to grab just one function/class
- Visual improvements: highlight file tags in the UI to make them more
noticeable
This pull request includes a change to improve the error message
displayed when there is insufficient quota in the `AgentLoop` class. The
updated message provides more detailed information and a link for
managing or purchasing credits.
Error message improvement:
*
[`codex-cli/src/utils/agent/agent-loop.ts`](diffhunk://#diff-b15957eac2720c3f1f55aa32f172cdd0ac6969caf4e7be87983df747a9f97083L1140-R1140):
Updated the error message in the `AgentLoop` class to include the
specific error message (if available) and a link to manage or purchase
credits.
Fixes#751
I suspect this was done originally so that `execForSandbox()` had a
consistent signature for both the `SandboxType.NONE` and
`SandboxType.MACOS_SEATBELT` cases, but that is not really necessary and
turns out to make the upcoming Landlock support a bit more complicated
to implement, so I had Codex remove it and clean up the call sites.
Apparently the URLs for draft releases cannot be downloaded using
unauthenticated `curl`, which means the DotSlash file only works for
users who are authenticated with `gh`. According to chat, prereleases
_can_ be fetched with unauthenticated `curl`, so let's try that.
For now, keep things simple such that we never update the `version` in
the `Cargo.toml` for the workspace root on the `main` branch. Instead,
create a new branch for a release, push one commit that updates the
`version`, and then tag that branch to kick off a release.
To test, I ran this script and created this release job:
https://github.com/openai/codex/actions/runs/14762580641
The generated DotSlash file has URLs that refer to
`https://github.com/openai/codex/releases/`, so let's set
`prerelease:false` (but keep `draft:true` for now) so those URLs should
work.
Also updated `version` in Cargo workspace so I will kick off a build
once this lands.
I am working to simplify the build process. As a first step, update
`session.ts` so it reads the `version` from `package.json` at runtime so
we no longer have to modify it during the build process. I want to get
to a place where the build looks like:
```
cd codex-cli
pnpm i
pnpm build
RELEASE_DIR=$(mktemp -d)
cp -r bin "$RELEASE_DIR/bin"
cp -r dist "$RELEASE_DIR/dist"
cp -r src "$RELEASE_DIR/src" # important if we want sourcemaps to continue to work
cp ../README.md "$RELEASE_DIR"
VERSION=$(printf '0.1.%d' $(date +%y%m%d%H%M))
jq --arg version "$VERSION" '.version = $version' package.json > "$RELEASE_DIR/package.json"
```
Then the contents of `$RELEASE_DIR` should be good to `npm publish`, no?
@oai-ragona and I discussed it, and we feel the REPL crate has served
its purpose, so we're going to delete the code and future archaeologists
can find it in Git history.
Apparently I made two key mistakes in
https://github.com/openai/codex/pull/740 (fixed in this PR):
* I forgot to redefine `$dest` in the `Stage Linux-only artifacts` step
* I did not define the `if` check correctly in the `Stage Linux-only
artifacts` step
This fixes both of those issues and bumps the workspace version to
`0.0.2504292006` in preparation for another release attempt.
This introduces a standalone executable that run the equivalent of the
`codex debug landlock` subcommand and updates `rust-release.yml` to
include it in the release.
The idea is that we will include this small binary with the TypeScript
CLI to provide support for Linux sandboxing.
Taking a pass at building artifacts per platform so we can consider
different distribution strategies that don't require users to install
the full `cargo` toolchain.
Right now this grabs just the `codex-repl` and `codex-tui` bins for 5
different targets and bundles them into a draft release. I think a
clearly marked pre-release set of artifacts will unblock the next step
of testing.
Previous to this PR, `SandboxPolicy` was a bit difficult to work with:
237f8a11e1/codex-rs/core/src/protocol.rs (L98-L108)
Specifically:
* It was an `enum` and therefore options were mutually exclusive as
opposed to additive.
* It defined things in terms of what the agent _could not_ do as opposed
to what they _could_ do. This made things hard to support because we
would prefer to build up a sandbox config by starting with something
extremely restrictive and only granting permissions for things the user
as explicitly allowed.
This PR changes things substantially by redefining the policy in terms
of two concepts:
* A `SandboxPermission` enum that defines permissions that can be
granted to the agent/sandbox.
* A `SandboxPolicy` that internally stores a `Vec<SandboxPermission>`,
but externally exposes a simpler API that can be used to configure
Seatbelt/Landlock.
Previous to this PR, we supported a `--sandbox` flag that effectively
mapped to an enum value in `SandboxPolicy`. Though now that
`SandboxPolicy` is a wrapper around `Vec<SandboxPermission>`, the single
`--sandbox` flag no longer makes sense. While I could have turned it
into a flag that the user can specify multiple times, I think the
current values to use with such a flag are long and potentially messy,
so for the moment, I have dropped support for `--sandbox` altogether and
we can bring it back once we have figured out the naming thing.
Since `--sandbox` is gone, users now have to specify `--full-auto` to
get a sandbox that allows writes in `cwd`. Admittedly, there is no clean
way to specify the equivalent of `--full-auto` in your `config.toml`
right now, so we will have to revisit that, as well.
Because `Config` presents a `SandboxPolicy` field and `SandboxPolicy`
changed considerably, I had to overhaul how config loading works, as
well. There are now two distinct concepts, `ConfigToml` and `Config`:
* `ConfigToml` is the deserialization of `~/.codex/config.toml`. As one
might expect, every field is `Optional` and it is `#[derive(Deserialize,
Default)]`. Consistent use of `Optional` makes it clear what the user
has specified explicitly.
* `Config` is the "normalized config" and is produced by merging
`ConfigToml` with `ConfigOverrides`. Where `ConfigToml` contains a raw
`Option<Vec<SandboxPermission>>`, `Config` presents only the final
`SandboxPolicy`.
The changes to `core/src/exec.rs` and `core/src/linux.rs` merit extra
special attention to ensure we are faithfully mapping the
`SandboxPolicy` to the Seatbelt and Landlock configs, respectively.
Also, take note that `core/src/seatbelt_readonly_policy.sbpl` has been
renamed to `codex-rs/core/src/seatbelt_base_policy.sbpl` and that
`(allow file-read*)` has been removed from the `.sbpl` file as now this
is added to the policy in `core/src/exec.rs` when
`sandbox_policy.has_full_disk_read_access()` is `true`.
The saveConfig() function only includes a hardcoded subset of properties
when writing the config file. Any property not explicitly listed (like
disableResponseStorage) will be dropped.
I have added `disableResponseStorage` to the `configToSave` object as
the immediate fix.
[Linking Issue this fixes.](https://github.com/openai/codex/issues/726)
This PR adds a new CLI flag: `--reasoning`, which allows users to
customize the reasoning effort level (`low`, `medium`, or `high`) used
by OpenAI's `o` models.
By introducing the `--reasoning` flag, users gain more flexibility when
working with the models. It enables optimization for either speed or
depth of reasoning, depending on specific use cases.
This PR resolves#107
- **Flag**: `--reasoning`
- **Accepted Values**: `low`, `medium`, `high`
- **Default Behavior**: If not specified, the model uses the default
reasoning level.
## Example Usage
```bash
codex --reasoning=low "Write a simple function to calculate factorial"
---------
Co-authored-by: Fouad Matin <169186268+fouad-openai@users.noreply.github.com>
Co-authored-by: yashrwealthy <yash.rastogi@wealthy.in>
Co-authored-by: Thibault Sottiaux <tibo@openai.com>
When processing an `apply_patch` tool call, we were already computing
the new file content in order to compute the unified diff. Before this
PR, we were shelling out to `patch(1)` to apply the unified diff once
the user accepted the change, but this updates the code to just retain
the new file content and use it to write the file when the user accepts.
This simplifies deployment because it no longer assumes `patch(1)` is on
the host.
Note this change is internal to the Codex agent and does not affect
`protocol.rs`.
This PR adds a `debug landlock` subcommand to the Codex CLI for testing
how Codex would execute a command using the specified sandbox policy.
Built and ran this code in the `rust:latest` Docker container. In the
container, hitting the network with vanilla `curl` succeeds:
```
$ curl google.com
<HTML><HEAD><meta http-equiv="content-type" content="text/html;charset=utf-8">
<TITLE>301 Moved</TITLE></HEAD><BODY>
<H1>301 Moved</H1>
The document has moved
<A HREF="http://www.google.com/">here</A>.
</BODY></HTML>
```
whereas this fails, as expected:
```
$ cargo run -- debug landlock -s network-restricted -- curl google.com
curl: (6) getaddrinfo() thread failed to start
```
https://github.com/openai/codex/pull/642 introduced support for the
`--disable-response-storage` flag, but if you are a ZDR customer, it is
tedious to set this every time, so this PR makes it possible to set this
once in `config.toml` and be done with it.
Incidentally, this tidies things up such that now `init_codex()` takes
only one parameter: `Config`.
Originally, the `interactive` crate was going to be a placeholder for
building out a UX that was comparable to that of the existing TypeScript
CLI. Though after researching how Ratatui works, that seems difficult to
do because it is designed around the idea that it will redraw the full
screen buffer each time (and so any scrolling should be "internal" to
your Ratatui app) whereas the TypeScript CLI expects to render the full
history of the conversation every time(*) (which is why you can use your
terminal scrollbar to scroll it).
While it is possible to use Ratatui in a way that acts more like what
the TypeScript CLI is doing, it is awkward and seemingly results in
tedious code, so I think we should abandon that approach. As such, this
PR deletes the `interactive/` folder and the code that depended on it.
Further, since we added support for mousewheel scrolling in the TUI in
https://github.com/openai/codex/pull/641, it certainly feels much better
and the need for scroll support via the terminal scrollbar is greatly
diminished. This is now a more appropriate default UX for the
"multitool" CLI.
(*) Incidentally, I haven't verified this, but I think this results in
O(N^2) work in rendering, which seems potentially problematic for long
conversations.
* In both TypeScript and Rust, we now invoke `/usr/bin/sandbox-exec`
explicitly rather than whatever `sandbox-exec` happens to be on the
`PATH`.
* Changed `isSandboxExecAvailable` to use `access()` rather than
`command -v` so that:
* We only do the check once over the lifetime of the Codex process.
* The check is specific to `/usr/bin/sandbox-exec`.
* We now do a syscall rather than incur the overhead of spawning a
process, dealing with timeouts, etc.
I think there is still room for improvement here where we should move
the `isSandboxExecAvailable` check earlier in the CLI, ideally right
after we do arg parsing to verify that we can provide the Seatbelt
sandbox if that is what the user has requested.
Although we made some promising fixes in
https://github.com/openai/codex/pull/662, we are still seeing some
flakiness in `test_writable_root()`. If this continues to flake with the
more generous timeout, we should try something other than simply
increasing the timeout.
The existing `b` and `space` are sufficient and `d` and `u` default to
half-page scrolling in `less`, so the way we supported `d` and `u`
wasn't faithful to that, anyway:
https://man7.org/linux/man-pages/man1/less.1.html
If we decide to bring `d` and `u` back, they should probably match
`less`?
This changes how instantiating `Config` works and also adds
`approval_policy` and `sandbox_policy` as fields. The idea is:
* All fields of `Config` have appropriate default values.
* `Config` is initially loaded from `~/.codex/config.toml`, so values in
`config.toml` will override those defaults.
* Clients must instantiate `Config` via
`Config::load_with_overrides(ConfigOverrides)` where `ConfigOverrides`
has optional overrides that are expected to be settable based on CLI
flags.
The `Config` should be defined early in the program and then passed
down. Now functions like `init_codex()` take fewer individual parameters
because they can just take a `Config`.
Also, `Config::load()` used to fail silently if `~/.codex/config.toml`
had a parse error and fell back to the default config. This seemed
really bad because it wasn't clear why the values in my `config.toml`
weren't getting picked up. I changed things so that
`load_with_overrides()` returns `Result<Config>` and verified that the
various CLIs print a reasonable error if `config.toml` is malformed.
Finally, I also updated the TUI to show which **sandbox** value is being
used, as we do for other key values like **model** and **approval**.
This was also a reminder that the various values of `--sandbox` are
honored on Linux but not macOS today, so I added some TODOs about fixing
that.
- Introduce `isSandboxExecAvailable()` helper and tidy import ordering
in `handle-exec-command.ts`.
- Add runtime check for the `sandbox-exec` binary on macOS; fall back to
`SandboxType.NONE` with a warning if it’s missing, preventing crashes.
---------
Signed-off-by: Thibault Sottiaux <tibo@openai.com>
Co-authored-by: Fouad Matin <fouad@openai.com>
Adds support for reading OPENAI_API_KEY (and other variables) from a
user‑wide dotenv file (~/.codex.config). Precedence order is now:
1. explicit environment variable
2. project‑local .env (loaded earlier)
3. ~/.codex.config
Also adds a regression test that ensures the multiline editor correctly
handles cases where printable text and the CSI‑u Shift+Enter sequence
arrive in the same input chunk.
House‑kept with Prettier; removed stray temp.json artifact.
Addressing #600 and #664 (partially)
## Bug
Codex was staging duplicate items in output running when the same
response item appeared in both the streaming events. Specifically:
1. Items would be staged once when received as a
`response.output_item.done` event
2. The same items would be staged again when included in the final
`response.completed` payload
This duplication would result in each message being sent several times
in the quiet mode output.
## Changes
- Added a Set (`alreadyStagedItemIds`) to track items that have already
been staged
- Modified the `stageItem` function to check if an item's ID is already
in this set before staging it
- Added a regression test (`agent-dedupe-items.test.ts`) that verifies
items with the same ID are only staged once
## Testing
Like other tests, the included test creates a mock OpenAI stream that
emits the same message twice (once as an incremental event and once in
the final response) and verifies the item is only passed to `onItem`
once.
Previously, the Rust TUI was writing log files to `/tmp`, which is
world-readable and not available on Windows, so that isn't great.
This PR tries to clean things up by adding a function that provides the
path to the "Codex config dir," e.g., `~/.codex` (though I suppose we
could support `$CODEX_HOME` to override this?) and then defines other
paths in terms of the result of `codex_dir()`.
For example, `log_dir()` returns the folder where log files should be
written which is defined in terms of `codex_dir()`. I updated the TUI to
use this function. On UNIX, we even go so far as to `chmod 600` the log
file by default, though as noted in a comment, it's a bit tedious to do
the equivalent on Windows, so we just let that go for now.
This also changes the default logging level to `info` for `codex_core`
and `codex_tui` when `RUST_LOG` is not specified. I'm not really sure if
we should use a more verbose default (it may be helpful when debugging
user issues), though if so, we should probably also set up log rotation?
## `0.1.2504251709`
### 🚀 Features
- Add openai model info configuration (#551)
- Added provider to run quiet mode function (#571)
- Create parent directories when creating new files (#552)
- Print bug report URL in terminal instead of opening browser (#510)
(#528)
- Add support for custom provider configuration in the user config
(#537)
- Add support for OpenAI-Organization and OpenAI-Project headers (#626)
- Add specific instructions for creating API keys in error msg (#581)
- Enhance toCodePoints to prevent potential unicode 14 errors (#615)
- More native keyboard navigation in multiline editor (#655)
- Display error on selection of invalid model (#594)
### 🪲 Bug Fixes
- Model selection (#643)
- Nits in apply patch (#640)
- Input keyboard shortcuts (#676)
- `apply_patch` unicode characters (#625)
- Don't clear turn input before retries (#611)
- More loosely match context for apply_patch (#610)
- Update bug report template - there is no --revision flag (#614)
- Remove outdated copy of text input and external editor feature (#670)
- Remove unreachable "disableResponseStorage" logic flow introduced in
#543 (#573)
- Non-openai mode - fix for gemini content: null, fix 429 to throw
before stream (#563)
- Only allow going up in history when not already in history if input is
empty (#654)
- Do not grant "node" user sudo access when using run_in_container.sh
(#627)
- Update scripts/build_container.sh to use pnpm instead of npm (#631)
- Update lint-staged config to use pnpm --filter (#582)
- Non-openai mode - don't default temp and top_p (#572)
- Fix error catching when checking for updates (#597)
- Close stdin when running an exec tool call (#636)
Small fixes required:
* `ExitStatusExt` differs because UNIX expects exit code to be `i32`
whereas Windows does `u32`
* Marking a file "executable only by owner" is a bit more involved on
Windows. We just do something approximate for now (and add a TODO) to
get things compiling.
I created this PR on my personal Windows machine and `cargo test` and
`cargo clippy` succeed. Once this is in, I'll rebase
https://github.com/openai/codex/pull/665 on top so Windows stays fixed!
In putting up https://github.com/openai/codex/pull/665, I discovered
that the `expanduser` crate does not compile on Windows. Looking into
it, we do not seem to need it because we were only using it with a value
that was passed in via a command-line flag, so the shell expands `~` for
us before we see it, anyway. (I changed the type in `Cli` from `String`
to `PathBuf`, to boot.)
If we do need this sort of functionality in the future,
https://docs.rs/shellexpand/latest/shellexpand/fn.tilde.html seems
promising.
I got the sense of this wrong in
https://github.com/openai/codex/pull/642. In that PR, I made
`--disable-response-storage` work, but broke the default case.
With this fix, both cases work and I think the code is a bit cleaner.
This adds support for the `--disable-response-storage` flag across our
multiple Rust CLIs to support customers who have opted into Zero-Data
Retention (ZDR). The analogous changes to the TypeScript CLI were:
* https://github.com/openai/codex/pull/481
* https://github.com/openai/codex/pull/543
For a client using ZDR, `previous_response_id` will never be available,
so the `input` field of an API request must include the full transcript
of the conversation thus far. As such, this PR changes the type of
`Prompt.input` from `Vec<ResponseInputItem>` to `Vec<ResponseItem>`.
Practically speaking, `ResponseItem` was effectively a "superset" of
`ResponseInputItem` already. The main difference for us is that
`ResponseItem` includes the `FunctionCall` variant that we have to
include as part of the conversation history in the ZDR case.
Another key change in this PR is modifying `try_run_turn()` so that it
returns the `Vec<ResponseItem>` for the turn in addition to the
`Vec<ResponseInputItem>` produced by `try_run_turn()`. This is because
the caller of `run_turn()` needs to record the `Vec<ResponseItem>` when
ZDR is enabled.
To that end, this PR introduces `ZdrTranscript` (and adds
`zdr_transcript: Option<ZdrTranscript>` to `struct State` in `codex.rs`)
to take responsibility for maintaining the conversation transcript in
the ZDR case.
It is intuitive to try to scroll the conversation history using the
mouse in the TUI, but prior to this change, we only supported scrolling
via keyboard events.
This PR enables mouse capture upon initialization (and disables it on
exit) such that we get `ScrollUp` and `ScrollDown` events in
`codex-rs/tui/src/app.rs`. I initially mapped each event to scrolling by
one line, but that felt sluggish. I decided to introduce
`ScrollEventHelper` so we could debounce scroll events and measure the
number of scroll events in a 100ms window to determine the "magnitude"
of the scroll event. I put in a basic heuristic to start, but perhaps
someone more motivated can play with it over time.
`ScrollEventHelper` takes care of handling the atomic fields and thread
management to ensure an `AppEvent::Scroll` event is pumped back through
the event loop at the appropriate time with the accumulated delta.
We currently see a behavior that looks like this:
```
2025-04-25T16:52:24.552789Z WARN codex_core::codex: stream disconnected - retrying turn (1/10 in 232ms)...
codex> event: BackgroundEvent { message: "stream error: stream disconnected before completion: Transport error: error decoding response body; retrying 1/10 in 232ms…" }
2025-04-25T16:52:54.789885Z WARN codex_core::codex: stream disconnected - retrying turn (2/10 in 418ms)...
codex> event: BackgroundEvent { message: "stream error: stream disconnected before completion: Transport error: error decoding response body; retrying 2/10 in 418ms…" }
```
This PR contains a few different fixes that attempt to resolve/improve
this:
1. **Remove overall client timeout.** I think
[this](https://github.com/openai/codex/pull/658/files#diff-c39945d3c42f29b506ff54b7fa2be0795b06d7ad97f1bf33956f60e3c6f19c19L173)
is perhaps the big fix -- it looks to me like this was actually timing
out even if events were still coming through, and that was causing a
disconnect right in the middle of a healthy stream.
2. **Cap response sizes.** We were frequently sending MUCH larger
responses than the upstream typescript `codex`, and that was definitely
not helping. [Fix
here](https://github.com/openai/codex/pull/658/files#diff-d792bef59aa3ee8cb0cbad8b176dbfefe451c227ac89919da7c3e536a9d6cdc0R21-R26)
for that one.
3. **Much higher idle timeout.** Our idle timeout value was much lower
than typescript.
4. **Sub-linear backoff.** We were much too aggressively backing off,
[this](https://github.com/openai/codex/pull/658/files#diff-5d5959b95c6239e6188516da5c6b7eb78154cd9cfedfb9f753d30a7b6d6b8b06R30-R33)
makes it sub-exponential but maintains the jitter and such.
I was seeing that `stream error: stream disconnected` behavior
constantly, and anecdotally I can no longer reproduce. It feels much
snappier.
- Replace setTimeout(10ms) with queueMicrotask for immediate processing
- Add minimal 3ms setTimeout for rendering to maintain readable UX
- Reduces per-token delay while preserving streaming experience
- Add performance test to verify optimization works correctly
---------
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Thibault Sottiaux <tibo@openai.com>
\+ cleanup below input help to be "ctrl+c to exit | "/" to see commands
| enter to send" now that we have command autocompletion
\+ minor other drive-by code cleanups
---------
Signed-off-by: Thibault Sottiaux <tibo@openai.com>
fix: pass correct selected model in ModelOverlay
The ModelOverlay component was incorrectly passing the current model
instead of the newly selected model to its onSelect callback. This
prevented model changes from being applied properly.
The fix ensures that when a user selects a new model, the parent
component receives the correct newly selected model value, allowing
model changes to work as intended.
close: #651
Hi! @tibo-openai 👋 Could you share some great examples of
`instructions.md` files? Thanks!
---------
Co-authored-by: Thibault Sottiaux <tibo@openai.com>
## Description
This PR addresses the following improvements:
**Unify Prettier Version**: Currently, the Prettier version used in
`/package.json` and `/codex-cli/package.json` are different. In this PR,
we're updating both to use Prettier v3.
- Prettier v3 introduces improved support for JavaScript and TypeScript.
(e.g. the formatting scenario shown in the image below. This is more
aligned with the TypeScript indentation standard).
<img width="1126" alt="image"
src="https://github.com/user-attachments/assets/6e237eb8-4553-4574-b336-ed9561c55370"
/>
**Add Prettier Auto-Formatting in lint-staged**: We've added a step to
automatically run prettier --write on JavaScript and TypeScript files as
part of the lint-staged process, before the ESLint checks.
- This will help ensure that all committed code is properly formatted
according to the project's Prettier configuration.
The `rust-ci.yml` build appears to be a bit flaky (we're looking into
it...), so to save TypeScript contributors some noise, restrict the
`rust-ci.yml` job so that it only runs on PRs that touch files in
`codex-rs/`.
## Description
When `saveConfig` is called, the project doc is incorrectly saved into
user instructions. This change ensures that only user instructions are
saved to `instructions.md` during saveConfig, preventing data
corruption.
close: #576
---------
Co-authored-by: Thibault Sottiaux <tibo@openai.com>
As described in detail in `codex-rs/execpolicy/README.md` introduced in
this PR, `execpolicy` is a tool that lets you define a set of _patterns_
used to match [`execv(3)`](https://linux.die.net/man/3/execv)
invocations. When a pattern is matched, `execpolicy` returns the parsed
version in a structured form that is amenable to static analysis.
The primary use case is to define patterns match commands that should be
auto-approved by a tool such as Codex. This supports a richer pattern
matching mechanism that the sort of prefix-matching we have done to
date, e.g.:
5e40d9d221/codex-cli/src/approvals.ts (L333-L354)
Note we are still playing with the API and the `system_path` option in
particular still needs some work.
Solves #510
This PR changes the `/bug` command to print the URL into the terminal
(so it works in headless sessions) instead of trying to open a browser.
---------
Co-authored-by: Thibault Sottiaux <tibo@openai.com>
Up-to-date of #78Fixes#32
addressed requested changes @tibo-openai :) made sense to me
though, previous rationale with passing the state up was assuming there
could be a future need to have a shared state with all available models
being available to the parent
I suspect this is why some contributors kept accidentally including a
new `codex-cli/package-lock.json` in their PRs.
Note the `Dockerfile` still uses `npm` instead of `pnpm`, but that
appears to be fine. (Probably nicer to globally install as few things as
possible in the image.)
##### What/Why
This PR makes it so that in Linux we actually respect the different
types of `--sandbox` flag, such that users can apply network and
filesystem restrictions in combination (currently the only supported
behavior), or just pick one or the other.
We should add similar support for OSX in a future PR.
##### Testing
From Linux devbox, updated tests to use more specific flags:
```
test linux::tests_linux::sandbox_blocks_ping ... ok
test linux::tests_linux::sandbox_blocks_getent ... ok
test linux::tests_linux::test_root_read ... ok
test linux::tests_linux::test_dev_null_write ... ok
test linux::tests_linux::sandbox_blocks_dev_tcp_redirection ... ok
test linux::tests_linux::sandbox_blocks_ssh ... ok
test linux::tests_linux::test_writable_root ... ok
test linux::tests_linux::sandbox_blocks_curl ... ok
test linux::tests_linux::sandbox_blocks_wget ... ok
test linux::tests_linux::sandbox_blocks_nc ... ok
test linux::tests_linux::test_root_write - should panic ... ok
```
##### Todo
- [ ] Add negative tests (e.g. confirm you can hit the network if you
configure filesystem only restrictions)
This exploration came out of my review of
https://github.com/openai/codex/pull/414.
`run_in_container.sh` runs Codex in a Docker container like so:
bd1c3deed9/codex-cli/scripts/run_in_container.sh (L51-L58)
But then runs `init_firewall.sh` to set up the firewall to restrict
network access.
Previously, we did this by adding `/usr/local/bin/init_firewall.sh` to
the container and adding a special rule in `/etc/sudoers.d` so the
unprivileged user (`node`) could run the privileged `init_firewall.sh`
script to open up the firewall for `api.openai.com`:
31d0d7a305/codex-cli/Dockerfile (L51-L56)
Though I believe this is unnecessary, as we can use `docker exec --user
root` from _outside_ the container to run
`/usr/local/bin/init_firewall.sh` as `root` without adding a special
case in `/etc/sudoers.d`.
This appears to work as expected, as I tested it by doing the following:
```
./codex-cli/scripts/build_container.sh
./codex-cli/scripts/run_in_container.sh 'what is the output of `curl https://www.openai.com`'
```
This was a bit funny because in some of my runs, Codex wasn't convinced
it had network access, so I had to convince it to try the `curl`
request:

As you can see, when it ran `curl -s https\://www.openai.com`, it a
connection failure, so the network policy appears to be working as
intended.
Note this PR also removes `sudo` from the `apt-get install` list in the
`Dockerfile`.
As stated in `codex-rs/README.md`:
Today, Codex CLI is written in TypeScript and requires Node.js 22+ to
run it. For a number of users, this runtime requirement inhibits
adoption: they would be better served by a standalone executable. As
maintainers, we want Codex to run efficiently in a wide range of
environments with minimal overhead. We also want to take advantage of
operating system-specific APIs to provide better sandboxing, where
possible.
To that end, we are moving forward with a Rust implementation of Codex
CLI contained in this folder, which has the following benefits:
- The CLI compiles to small, standalone, platform-specific binaries.
- Can make direct, native calls to
[seccomp](https://man7.org/linux/man-pages/man2/seccomp.2.html) and
[landlock](https://man7.org/linux/man-pages/man7/landlock.7.html) in
order to support sandboxing on Linux.
- No runtime garbage collection, resulting in lower memory consumption
and better, more predictable performance.
Currently, the Rust implementation is materially behind the TypeScript
implementation in functionality, so continue to use the TypeScript
implmentation for the time being. We will publish native executables via
GitHub Releases as soon as we feel the Rust version is usable.
## Description
The `as AppConfig` type assertion in the constructor may introduce
potential type safety risks. Removing the assertion and making `notify`
an optional parameter could enhance type robustness and prevent
unexpected runtime errors.
close: #605
When using a non-built-in provider with the `--provider` option, users
are prompted:
```
Set the environment variable <provider>_API_KEY and re-run this command.
You can create a <provider>_API_KEY in the <provider> dashboard.
```
However, many users are confused because, even after correctly setting
`<provider>_API_KEY`, authentication may still fail unless
`OPENAI_API_KEY` is _also_ present in the environment. This is not
intuitive and leads to ambiguity about which API key is actually
required and used as a fallback, especially when using custom or
third-party (non-listed) providers.
Furthermore, the original README/documentation did not mention the
requirement to set `<provider>_BASE_URL` for non-built-in providers,
which is necessary for proper client behavior. This omission made the
configuration process more difficult for users trying to integrate with
custom endpoints.
## Description
In a recent commit, the command `"cd codex-cli && pnpm run typecheck"`
was updated to `"pnpm --filter @openai/codex run typecheck"`.
However, this change introduces an issue:
when running `pnpm --filter @openai/codex run typecheck`, it executes
`tsc --noEmit somefile.ts` directly, bypassing the `tsconfig.json`
configuration. As a result, numerous type errors are triggered,
preventing successful commits.
Close: #619
More of a proposal than anything but models seem to struggle with
composing valid patches for `apply_patch` for context matching when
there are unicode look-a-likes involved. This would normalize them.
```
top-level # ASCII
top-level # U+2011 NON-BREAKING HYPHEN
top–level # U+2013 EN DASH
top—level # U+2014 EM DASH
top‒level # U+2012 FIGURE DASH
```
thanks unicode.
Updates the error message for missing Gemini API keys to reference
"Google AI Studio" instead of the generic "GEMINI dashboard". This
provides users with more accurate information about where to obtain
their Gemini API keys.
This could be extended to other providers as well.
The current turn input in the agent loop is being discarded before
consuming the stream events which causes the stream reconnect (after
rate limit failure) to not include the inputs. Since the new stream
includes the previous response ID, it triggers a bad request exception
considering the input doesn't match what OpenAI has stored on the server
side and subsequently a very confusing error message of: `No tool output
found for function call call_xyz`.
This should fix https://github.com/openai/codex/issues/586.
## Testing
I have a personal project that I'm working on that runs multiple Codex
CLIs in parallel and often runs into rate limit errors (as seen in the
OpenAI logs). After making this change, I am no longer experiencing
Codex crashing and it was able to retry and handle everything gracefully
until completion (even though I still see rate limiting in the OpenAI
logs).
This fixes https://github.com/openai/codex/issues/480 where the latest
code was crashing when attempting to be run inside docker since the
update checker attempts to reach out to `npm.antfu.dev` but that DNS is
not allowed in the firewall rules.
I believe the original code was attempting to catch and ignore any
errors when checking for updates but was doing so incorrectly. If you
use await on a promise, you have to use a standard try/catch instead of
`Promise.catch` so this fixes that.
## Testing
### Before
```
$ scripts/run_in_container.sh "explain this project to me"
7d1aa845edf9a36fe4d5b331474b5cb8ba79537b682922b554ea677f14996c6b
Resolving api.openai.com...
Adding 162.159.140.245 for api.openai.com
Adding 172.66.0.243 for api.openai.com
Host network detected as: 172.17.0.0/24
Firewall configuration complete
Verifying firewall rules...
Firewall verification passed - unable to reach https://example.com as expected
Firewall verification passed - able to reach https://api.openai.com as expected
TypeError: fetch failed
at node:internal/deps/undici/undici:13510:13
at process.processTicksAndRejections (node:internal/process/task_queues:95:5)
at async getLatestVersionBatch (file:///usr/local/share/npm-global/lib/node_modules/@openai/codex/dist/cli.js:132669:17)
at async getLatestVersion (file:///usr/local/share/npm-global/lib/node_modules/@openai/codex/dist/cli.js:132674:19)
at async getUpdateCheckInfo (file:///usr/local/share/npm-global/lib/node_modules/@openai/codex/dist/cli.js:132748:20)
at async checkForUpdates (file:///usr/local/share/npm-global/lib/node_modules/@openai/codex/dist/cli.js:132772:23)
at async file:///usr/local/share/npm-global/lib/node_modules/@openai/codex/dist/cli.js:142027:1 {
[cause]: AggregateError [ECONNREFUSED]:
at internalConnectMultiple (node:net:1122:18)
at afterConnectMultiple (node:net:1689:7) {
code: 'ECONNREFUSED',
[errors]: [ [Error], [Error] ]
}
}
```
### After
```
$ scripts/run_in_container.sh "explain this project to me"
91aa716e3d3f86c9cf6013dd567be31b2c44eb5d7ab184d55ef498731020bb8d
Resolving api.openai.com...
Adding 162.159.140.245 for api.openai.com
Adding 172.66.0.243 for api.openai.com
Host network detected as: 172.17.0.0/24
Firewall configuration complete
Verifying firewall rules...
Firewall verification passed - unable to reach https://example.com as expected
Firewall verification passed - able to reach https://api.openai.com as expected
╭──────────────────────────────────────────────────────────────╮
│ ● OpenAI Codex (research preview) v0.1.2504221401 │
╰──────────────────────────────────────────────────────────────╯
╭──────────────────────────────────────────────────────────────╮
│ localhost session: 7c782f196ae04503866e39f071e26a69 │
│ ↳ model: o4-mini │
│ ↳ provider: openai │
│ ↳ approval: full-auto │
╰──────────────────────────────────────────────────────────────╯
user
explain this project to me
╭───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│( ● ) 2s Thinking │
╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
send q or ctrl+c to exit | send "/clear" to reset | send "/help" for commands | press enter to send | shift+enter for new line — 100% context left
```
### What
- Add support for loading and merging custom provider configurations
from a local `providers.json` file.
- Allow users to override or extend default providers with their own
settings.
### Why
This change enables users to flexibly customize and extend provider
endpoints and API keys without modifying the codebase, making the CLI
more adaptable for various LLM backends and enterprise use cases.
### How
- Introduced `loadProvidersFromFile` and `getMergedProviders` in config
logic.
- Added/updated related tests in [tests/config.test.tsx]
### Checklist
- [x] Lint passes for changed files
- [x] Tests pass for all files
- [x] Documentation/comments updated as needed
---------
Co-authored-by: Thibault Sottiaux <tibo@openai.com>
Adding support to be able to run other models in quiet mode
ie: `codex --approval-mode full-auto -q "explain the current directory"
--provider xai --model grok-3-beta`
I haven't seen any actual errors due to this, but it's been bothering me
that I had it defaulted to 1. I think best to leave it undefined and
have each provider do their thing
Gemini's API is finicky, it 400's without an error when you pass
content: null
Also fixed the rate limiting issues by throwing outside of the iterator.
I think there's a separate issue with the second isRateLimit check in
agent-loop - turnInput is cleared by that time, so it retries without
the last message.
apply_patch doesn't create parent directories when creating a new file
leading to confusion and flailing by the agent. This will create parent
directories automatically when absent.
---------
Co-authored-by: Thibault Sottiaux <tibo@openai.com>
## `0.1.2504221401`
### 🚀 Features
- Show actionable errors when api keys are missing (#523)
- Add CLI `--version` flag (#492)
### 🐛 Bug Fixes
- Agent loop for ZDR (`disableResponseStorage`) (#543)
- Fix relative `workdir` check for `apply_patch` (#556)
- Minimal mid-stream #429 retry loop using existing back-off (#506)
- Inconsistent usage of base URL and API key (#507)
- Remove requirement for api key for ollama (#546)
- Support `[provider]_BASE_URL` (#542)
Previously, we were ignoring the `workdir` field in an `ExecInput` when
running it through `canAutoApprove()`. For ordinary `exec()` calls, that
was sufficient, but for `apply_patch`, we need the `workdir` to resolve
relative paths in the `apply_patch` argument so that we can check them
in `isPathConstrainedTowritablePaths()`.
Likewise, we also need the workdir when running `execApplyPatch()`
because the paths need to be resolved again.
Ideally, the `ApplyPatchCommand` returned by `canAutoApprove()` would
not be a simple `patch: string`, but the parsed patch with all of the
paths resolved, in which case `execApplyPatch()` could expect absolute
paths and would not need `workdir`.
Fixes#540
# Skip API key validation for Ollama provider
## Description
This PR modifies the CLI to not require an API key when using Ollama as
the provider
## Changes
- Modified the validation logic to skip API key checks for these
providers
- Updated the README to clarify that Ollama doesn't require an API key
This introduces a Python script (written by Codex!) to verify that the
table of contents in the root `README.md` matches the headings. Like
`scripts/asciicheck.py` in https://github.com/openai/codex/pull/513, it
reports differences by default (and exits non-zero if there are any) and
also has a `--fix` option to synchronize the ToC with the headings.
This will be enforced by CI and the changes to `README.md` in this PR
were generated by the script, so you can see that our ToC was missing
some entries prior to this PR.
As requested by @tibo-openai at
https://github.com/openai/codex/pull/357#issuecomment-2816554203, this
attempts a more minimal implementation of #357 that preserves as much as
possible of the existing code's exponential backoff logic.
Adds a small retry wrapper around the streaming for‑await loop so that
HTTP 429s which occur *after* the stream has started no longer crash the
CLI.
Highlights
• Re‑uses existing RATE_LIMIT_RETRY_WAIT_MS constant and 5‑attempt
limit.
• Exponential back‑off identical to initial request handling.
This comment is probably more useful here in the PR:
// The OpenAI SDK may raise a 429 (rate‑limit) *after* the stream has
// started. Prior logic already retries the initial `responses.create`
// call, but we need to add equivalent resilience for mid‑stream
// failures. We keep the implementation minimal by wrapping the
// existing `for‑await` loop in a small retry‑for‑loop that re‑creates
// the stream with exponential back‑off.
A recent commit introduced the ability to use third-party model
providers. (Really appreciate it!)
However, the usage is inconsistent: some pieces of code use the custom
providers, whereas others still have the old behavior. Additionally,
`OPENAI_BASE_URL` is now being disregarded when it shouldn't be.
This PR normalizes the usage to `getApiKey` and `getBaseUrl`, and
enables the use of `OPENAI_BASE_URL` if present.
---------
Co-authored-by: Gabriel Bianconi <GabrielBianconi@users.noreply.github.com>
Without this I get an issue running codex it in a docker container. I
receive:
```
{
"answer": "{\"role\":\"user\",\"content\":[{\"type\":\"input_text\",\"text\":\"\\\"Say hello world\\\"\"}],\"type\":\"message\"}\n{\"id\":\"error-1745325184914\",\"type\":\"message\",\"role\":\"system\",\"content\":[{\"type\":\"input_text\",\"text\":\"⚠️ OpenAI rejected the request (request ID: req_f9027b59ebbce00061e9cd2dbb2d529a). Error details: Status: 400, Code: invalid_function_parameters, Type: invalid_request_error, Message: 400 Invalid schema for function 'shell': In context=(), 'required' is required to be supplied and to be an array including every key in properties. Missing 'workdir'.. Please verify your settings and try again.\"}]}\n"
}
```
This fix makes it work.
This all started because I was going to write a script to autogenerate
the Table of Contents in the root `README.md`, but I noticed that the
`href` for the "Why Codex?" heading was `#whycodex` instead of
`#why-codex`. This piqued my curiosity and it turned out that the space
in "Why Codex?" was not an ASCII space but **U+00A0**, a non-breaking
space, and so GitHub ignored it when generating the `href` for the
heading.
This also meant that when I did a text search for `why codex` in the
`README.md` in VS Code, the "Why Codex" heading did not match because of
the presence of **U+00A0**.
In short, these types of Unicode characters seem like a hazard, so I
decided to introduce this script to flag them, and if desired, to
replace them with "good enough" ASCII equivalents. For now, this only
applies to the root `README.md` file, but I think we should ultimately
apply this across our source code, as well, as we seem to have quite a
lot of non-ASCII Unicode and it's probably going to cause `rg` to miss
things.
Contributions of this PR:
* `./scripts/asciicheck.py`, which takes a list of filepaths and returns
non-zero if any of them contain non-ASCII characters. (Currently, there
is one exception for ✨ aka **U+2728**, though I would like to default to
an empty allowlist and then require all exceptions to be specified as
flags.)
* A `--fix` option that will attempt to rewrite files with violations
using a equivalents from a hardcoded substitution list.
* An update to `ci.yml` to verify `./scripts/asciicheck.py README.md`
succeeds.
* A cleanup of `README.md` using the `--fix` option as well as some
editorial decisions on my part.
* I tried to update the `href`s in the Table of Contents to reflect the
changes in the heading titles. (TIL that if a heading has a character
like `&` surrounded by spaces, it becomes `--` in the generated `href`.)
I saw cases where the first chunk of output from `ls -R` could be large
enough to exceed `MAX_OUTPUT_BYTES` or `MAX_OUTPUT_LINES`, in which case
the loop would exit early in `createTruncatingCollector()` such that
nothing was appended to the `chunks` array. As a result, the reported
`stdout` of `ls -R` would be empty.
I asked Codex to add logic to handle this edge case and write a unit
test. I used this as my test:
```
./codex-cli/dist/cli.js -q 'what is the output of `ls -R`'
```
now it appears to include a ton of stuff whereas before this change, I
saw:
```
{"type":"function_call_output","call_id":"call_a2QhVt7HRJYKjb3dIc8w1aBB","output":"{\"output\":\"\\n\\n[Output truncated: too many lines or bytes]\",\"metadata\":{\"exit_code\":0,\"duration_seconds\":0.5}}"}
```
## `0.1.2504211509`
### 🚀 Features
- Support multiple providers via Responses-Completion transformation
(#247)
- Add user-defined safe commands configuration and approval logic #380
(#386)
- Allow switching approval modes when prompted to approve an
edit/command (#400)
- Add support for `/diff` command autocomplete in TerminalChatInput
(#431)
- Auto-open model selector if user selects deprecated model (#427)
- Read approvalMode from config file (#298)
- `/diff` command to view git diff (#426)
- Tab completions for file paths (#279)
- Add /command autocomplete (#317)
- Allow multi-line input (#438)
### 🐛 Bug Fixes
- `full-auto` support in quiet mode (#374)
- Enable shell option for child process execution (#391)
- Configure husky and lint-staged for pnpm monorepo (#384)
- Command pipe execution by improving shell detection (#437)
- Name of the file not matching the name of the component (#354)
- Allow proper exit from new Switch approval mode dialog (#453)
- Ensure /clear resets context and exclude system messages from
approximateTokenUsed count (#443)
- `/clear` now clears terminal screen and resets context left indicator
(#425)
- Correct fish completion function name in CLI script (#485)
- Auto-open model-selector when model is not found (#448)
- Remove unnecessary isLoggingEnabled() checks (#420)
- Improve test reliability for `raw-exec` (#434)
- Unintended tear down of agent loop (#483)
- Remove extraneous type casts (#462)
Updates `isSafeCommand()` so that an invocation of `find` is not
auto-approved if it contains any of: `-exec`, `-execdir`, `-ok`,
`-okdir`, `-delete`, `-fls`, `-fprint`, `-fprint0`, `-fprintf`.
Publish shouldn't need the source files published along with the
distributable bin.
`src` is being shipped to the registry rn:
https://www.npmjs.com/package/@openai/codex?activeTab=code
You can verify that the src is not needed by packing the project
manually after removing src from the files:
```sh
# from the codex-cli dir
rm -rf dist # just for hygiene
pnpm run build
pnpm pack
mkdir /tmp/codex-tar-test
mv openai-codex-0.1.2504181820.tgz /tmp/codex-tar-test
cd /tmp/codex-tar-test
pnpm init
pnpm add ./openai-codex-0.1.2504181820.tgz /tmp/codex-tar-test
pnpm exec codex --full-auto "run a bash -c command to echo hello world"
```
The cli is operational
> noticed this when checking the screenshot included in
https://github.com/openai/codex/pull/461
Reverts https://github.com/openai/codex/pull/386 because:
* The parsing logic for shell commands was unsafe (`split(/\s+/)`
instead of something like `shell-quote`)
* We have a different plan for supporting auto-approved commands.
## What does this PR do?
* Implements the full `/clear` command in **codex‑cli**:
* Resets chat history **and** wipes the terminal screen.
* Shows a single system message: `Context cleared`.
* Adds comprehensive unit tests for the new behaviour.
## Why is it needed?
* Fixes user‑reported bugs:
* **#395**
* **#405**
## How is it implemented?
* **Code** – Adds `process.stdout.write('\x1b[3J\x1b[H\x1b[2J')` in
`terminal.tsx`. Removed reference to `prev` in `
setItems((prev) => [
...prev,
` in `terminal-chat-new-input.tsx` & `terminal-chat-input.tsx`.
## CI / QA
All commands pass locally:
```bash
pnpm test # green
pnpm run lint # green
pnpm run typecheck # zero TS errors
```
## Results
https://github.com/user-attachments/assets/11dcf05c-e054-495a-8ecb-ac6ef21a9da4
---------
Co-authored-by: Thibault Sottiaux <tibo@openai.com>
Another one that I noticed.
The dist structure is very simple rn, so unlikely to run into orphaned
files as you're emitting a single built artifact which wil be
overwritten on build, but I always prefer to do clean builds as
"hygiene".
I had a dirty dist personally after local development and testing some
things, as an example.
Alternatives could be to create a `clean` script with cross platform
`rimraf dist`
This PR tidies up primitives under storage/.
**Noop changes:**
* Promote logger implementation to top-level utility outside of agent/
* Use logger within storage primitives
* Cleanup doc strings and comments
**Functional changes:**
* Increase command history size to 10_000
* Remove unnecessary debounce implementation and ensure a session ID is
created only once per agent loop
---------
Signed-off-by: Thibault Sottiaux <tibo@openai.com>
## Background
Addressing feedback from
https://github.com/openai/codex/pull/333#discussion_r2050893224, this PR
adds support for Bun alongside npm, pnpm while keeping the code simple.
## Summary
The update‑check flow is refactored to use a direct registry lookup
(`fast-npm-meta` + `semver`) instead of shelling out to `npm outdated`,
and adds a lightweight installer‑detection mechanism that:
1. Checks if the invoked script lives under a known global‑bin directory
(npm, pnpm, or bun)
2. If not, falls back to local detection via `getUserAgent()` (the
`package‑manager‑detector` library)
## What’s Changed
- **Registry‑based version check**
- Replace `execFile("npm", ["outdated"])` with `getLatestVersion()` and
`semver.gt()`
- **Multi‑manager support**
- New `renderUpdateCommand` handles update commands for `npm`, `pnpm`,
and `bun`.
- Detect global installer first via `detectInstallerByPath()`
- Fallback to local detection via `getUserAgent()`
- **Module cleanup**
- Extract `detectInstallerByPath` into
`utils/package-manager-detector.ts`
- Remove legacy `checkOutdated`, `getNPMCommandPath`, and child‑process
JSON parsing
- **Flow improvements in `checkForUpdates`**
1. Short‑circuit by `UPDATE_CHECK_FREQUENCY`
3. Fetch & compare versions
4. Persist new timestamp immediately
5. Render & display styled box only when an update exists
- **Maintain simplicity**
- All multi‑manager logic lives in one small helper and a concise lookup
rather than a complex adapter hierarchy
- Core `checkForUpdates` remains a single, easy‑to‑follow async function
- **Dependencies added**
- `fast-npm-meta`, `semver`, `package-manager-detector`, `@types/semver`
## Considerations
If we decide to drop the interactive update‑message (`npm install -g
@openai/codex`) rendering altogether, we could remove most of the
installer‑detection code and dependencies, which would simplify the
codebase further but result in a less friendly UX.
## Preview
* npm

* bun

## Simple Flow Chart
```mermaid
flowchart TD
A(Start) --> B[Read state]
B --> C{Recent check?}
C -- Yes --> Z[End]
C -- No --> D[Fetch latest version]
D --> E[Save check time]
E --> F{Version data OK?}
F -- No --> Z
F -- Yes --> G{Update available?}
G -- No --> Z
G -- Yes --> H{Global install?}
H -- Yes --> I[Select global manager]
H -- No --> K{Local install?}
K -- No --> Z
K -- Yes --> L[Select local manager]
I & L --> M[Render update message]
M --> N[Format with boxen]
N --> O[Print update]
O --> Z
```
This PR removes always included files and folders from the
[`package.json#files`
field](https://docs.npmjs.com/cli/v11/configuring-npm/package-json#files):
> Certain files are always included, regardless of settings:
> - package.json
> - README
> - LICENSE / LICENCE
> - The file in the "main" field
> - The file(s) in the "bin" field
Validated by running `pnpm i && cd codex-cli && pnpm build && pnpm
release:readme && pnpm pack` and confirming both the `README.md` file
and `bin` directory are still included in the tarball:
<img width="227" alt="image"
src="https://github.com/user-attachments/assets/ecd90a07-73c7-4940-8c83-cb1d51dfcf96"
/>
## What
This PR targets #402 and refactors the `history-overlay.tsx`component to
reduce cognitive complexity by splitting the `buildLists` function into
smaller, focused helper functions. It also adds comprehensive test
coverage to ensure the functionality remains intact.
## Why
The original `buildLists` function had high cognitive complexity due to
multiple nested conditionals, complex string manipulation, and mixed
responsibilities. This refactor makes the code more maintainable and
easier to understand while preserving all existing functionality.
## How
- Split `buildLists` into focused helper functions
- Added comprehensive test coverage for all functionality
- Maintained existing behavior and keyboard interactions
- Improved code organization and readability
## Testing
All tests pass, including:
- Command mode functionality
- File mode functionality
- Keyboard interactions
- Error handling
As described in
https://github.com/openai/codex/issues/392#issuecomment-2817090022
introduced by #400
The testing I'd done worked correctly because I was using the (s)
shortcut, but selecting the same option using arrow‑key → Enter on
“Switch approval mode” was preventing the user from subsequently exiting
the Switch approval mode dialog, requiring a ^C to quit codex entirely.
With this fix, both entry methods work correctly in my testing.
Per codex:
Issue
- When you navigated down (↓) to “Switch approval mode (s)” in the Shell
Command review dialog and pressed Enter, the ApprovalModeOverlay would
open—but because the underlying `TerminalChatCommandReview` component
stayed mounted (albeit disabled), its own Ink input handlers immediately
re‑captured the same key events and re‑opened the overlay as soon as you
hit Esc or Enter again. In practice this made it impossible to exit the
submenu.
Root cause
- We only disabled the SelectInput via `isDisabled`, but never fully
unmounted the review UI when an overlay was shown, so its `useInput` and
`<Select>` hooks were still active and “stealing” keys.
Fix
- In `terminal-chat.tsx` we now only render `<TerminalChatInput>` (and
by extension `TerminalChatCommandReview`) when `overlayMode === "none"`.
That unmounts all of its key handlers whenever any overlay (history,
model, approval, help, diff) is open, so no input leaks through.
Files changed
- **src/components/chat/terminal-chat.tsx**: Wrapped the entire
`<TerminalChatInput>` block in `overlayMode === "none" && agent`
With that in place, arrow‑key → Enter on “Switch approval mode”
correctly opens the overlay, and then you can use Enter/Esc inside the
overlay without getting stuck or immediately re‑opening it.
## Description
This PR fixes Issue #421 where commands with pipes (e.g., `grep -R ...
-n | head -n 20`) were failing to execute properly after PR #391 was
merged.
## Changes
- Modified the `requiresShell` function to only enable shell mode when
the command is a single string containing shell operators
- Added logic to handle the case where shell operators are passed as
separate arguments
- Added comprehensive tests to verify the fix
## Root Cause
The issue was that the `requiresShell` function was detecting shell
operators like `|` even when they were passed as separate arguments,
which caused the command to be executed with `shell: true`
unnecessarily. This was causing syntax errors when running commands with
pipes.
## Testing
- Added unit tests to verify the fix
- Manually tested with real commands using pipes
- Ensured all existing tests pass
Fixes#421
This PR improves the reliability of `raw-exec-process-group.test`,
addressing [#415](https://github.com/openai/codex/issues/415)
Before: The test would fail sporadically in CI because it checked for
process termination immediately after abort, without accounting for the
time it takes for processes to fully terminate.
Now: We've added a robust `ensureProcessGone` helper that:
- Polls the process status with a 500ms timeout
- Retries every 50ms if the process is still alive
- Provides clear error messages if termination takes too long
We now wait for the child process to fully exit after sending abort
signals, instead of assuming instant death, fixing flakiness caused by
asynchronous process termination.
Changes:
- Added `ensureProcessGone` helper function with retry logic
- Improved error handling and timeout management
See [this bash
demo](https://gist.github.com/jdocherty/a84dbca2fbf7b47e5f95c87a07034ae8)
for a minimal reproduction of why process death is asynchronous and why
the test needs to retry after aborting.
It appears that use of `isLoggingEnabled()` was erroneously copypasta'd
in many places. This PR updates its docstring to clarify that should
only be used to avoid constructing a potentially expensive docstring.
With this change, the only function that merits/uses this check is
`execCommand()`.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/420).
* #423
* __->__ #420
* #419
To play it safe, let's keep `CONFIG_DIR` out of the default list of
writable roots.
This also fixes an issue where `execWithSeatbelt()` was modifying
`writableRoots` instead of creating a new array.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/419).
* #423
* #420
* __->__ #419
## Description
This PR implements multi-line input support for Codex when it asks for
user feedback (Issue #344). Users can now use Shift+Enter to add new
lines in their responses, making it easier to provide formatted code
snippets, lists, or other structured content.
## Changes
- Replace the single-line TextInput component with the
MultilineTextEditor component in terminal-chat-input.tsx
- Add support for Shift+Enter to create new lines
- Update key handling logic to properly handle history navigation in a
multi-line context
- Add reference to the editor to access cursor position information
- Update help text to inform users about the Shift+Enter functionality
- Add tests for the new functionality
## Testing
- Added new test file (terminal-chat-input-multiline.test.tsx) to test
the multi-line input functionality
- All existing tests continue to pass
- Manually tested the feature to ensure it works as expected
## Fixes
Closes#344
## Screenshots
N/A
## Additional Notes
This implementation maintains backward compatibility while adding the
requested multi-line input functionality. The UI remains clean and
intuitive, with a simple hint about using Shift+Enter for new lines.
---------
Co-authored-by: Thibault Sottiaux <tibo@openai.com>
https://github.com/openai/codex/pull/160 introduced a call to `exec()`
that takes a format string as an argument, but it is not clear that the
expansions within the format string are escaped safely. As written, it
is possible a carefully crafted command (e.g., if `cwd` were `"; && rm
-rf` or something...) could run arbitrary code.
Moving to `spawn()` makes this a bit better, as now at least `spawn()`
itself won't run an arbitrary process, though I suppose `osascript`
itself still could if the value passed to `-e` were abused. I'm not
clear on the escaping rules for AppleScript to ensure that `safePreview`
and `cwd` are injected safely.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/416).
* #423
* #420
* #419
* __->__ #416
This check was lost in https://github.com/openai/codex/pull/287. Both
the root folder and `codex-cli/` have their own `pnpm format` commands
that check the formatting of different things.
Also ran `pnpm format:fix` to fix the formatting violations that got in
while this was disabled in CI.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/417).
* #420
* #419
* #416
* __->__ #417
Add interactive slash‑command autocomplete & navigation in chat input
Description
This PR enhances the chat input component by adding first‑class support
for slash commands (/help, /clear, /compact, etc.)
with:
* **Live filtering:** As soon as the user types leading `/`, a list of
matching commands is shown below the prompt.
* **Arrow‑key navigation:** Up/Down arrows cycle through suggestions.
* **Enter to autocomplete:** Pressing Enter on a partial command will
fill it (without submitting) so you can add
arguments or simply press Enter again to execute.
* **Type‑safe registry:** A new `slash‑commands.ts` file declares all
supported commands in one place, along with
TypeScript types to prevent drift.
* **Validation:** Only registered commands will ever autocomplete or be
suggested; unknown single‑word slash inputs still
show an “Invalid command” system message.
* **Automated tests:**
* Unit tests for the command registry and prefix filtering
* Existing tests continue passing with no regressions
Motivation
Slash commands provide a quick, discoverable way to control the agent
(clearing history, compacting context, opening overlays,
etc.). Before, users had to memorize the exact command or rely on the
generic /help list—autocomplete makes them far more
accessible and reduces typos.
Changes
* `src/utils/slash‑commands.ts` – defines `SlashCommand` and exports a
flat list of supported commands + descriptions
* `terminal‑chat‑input.tsx`
* Import and type the command registry
* Render filtered suggestions under the prompt when input starts with
`/`
* Hook into `useInput` to handle Up/Down and Enter for selection & fill
* Flag to swallow the first Enter (autocomplete) and only submit on the
next
* Updated tests in `tests/slash‑commands.test.ts` to cover registry
contents and filtering logic
* Removed old JS version and fixed stray `@ts‑expect‑error`
How to test locally
1. Type `/` in the prompt—you should see matching commands.
2. Use arrows to move the highlight, press Enter to fill, then Enter
again to execute.
3. Run the full test suite (`npm test`) to verify no regressions.
Notes
* Future work could include fuzzy matching, paging long lists, or more
visual styling.
* This change is purely additive and does not affect non‑slash inputs or
existing slash handlers.
---------
Co-authored-by: Fouad Matin <169186268+fouad-openai@users.noreply.github.com>
Co-authored-by: Thibault Sottiaux <tibo@openai.com>
This PR implements support for reading the approvalMode setting from the
user's config file (`~/.codex/config.json` or `~/.codex/config.yaml`),
allowing users to set a persistent default approval mode without needing
to specify command-line flags for each session.
Changes:
- Added approvalMode to the AppConfig type in config.ts
- Updated loadConfig() to read the approval mode from the config file
- Modified saveConfig() to persist the approval mode setting
- Updated CLI logic to respect the config-defined approval mode (while
maintaining CLI flag priority)
- Added comprehensive tests for approval mode config functionality
- Updated README to document the new config option in both YAML and JSON
formats
- additions to `.gitignore` for other CLI tools
Motivation:
As a user who regularly works with CLI-tools, I found it odd to have to
alias this with the command flags I wanted when `approvalMode` simply
wasn't being parsed even though it was an optional prop in `config.ts`.
This change allows me (and other users) to set the preference once in
the config file, streamlining daily usage while maintaining the ability
to override via command-line flags when needed.
Testing:
I've added a new test case loads and saves approvalMode correctly that
verifies:
- Reading the approvalMode from the config file works correctly
- Saving the approvalMode to the config file works as expected
- The value persists through load/save operations
All tests related to the implementation are passing.
Implements https://github.com/openai/codex/issues/392
When the user is in suggest or auto-edit mode and gets an approval
request, they now have an option in the `Shell Command` dialog to:
`Switch approval mode (v)`
That option brings up the standard `Switch approval mode` dialog,
allowing the user to switch into the desired mode, then drops them back
to the `Shell Command` dialog's `Allow command?` prompt, allowing them
to approve the current command and let the agent continue doing the rest
of what it was doing without interruption.
```
╭────────────────────────────────────────────────────────
│Shell Command
│
│$ apply_patch << 'PATCH'
│*** Begin Patch
│*** Update File: foo.txt
│@@ -1 +1 @@
│-foo
│+bar
│*** End Patch
│PATCH
│
│
│Allow command?
│
│ Yes (y)
│ Explain this command (x)
│ Edit or give feedback (e)
│ Switch approval mode (v)
│ No, and keep going (n)
│ No, and stop for now (esc)
╰────────────────────────────────────────────────────────╭────────────────────────────────────────────────────────
│ Switch approval mode
│ Current mode: suggest
│
│
│
│ ❯ suggest
│ auto-edit
│ full-auto
│ type to search · enter to confirm · esc to cancel
╰────────────────────────────────────────────────────────
```
# Improve Developer Experience with Husky and lint-staged for pnpm
Monorepo
## Summary
This PR enhances the developer experience by configuring Husky and
lint-staged to work properly with our pnpm monorepo structure. It
centralizes Git hooks at the root level and ensures consistent code
quality across the project.
## Changes
- Centralized Husky and lint-staged configuration at the monorepo root
- Added pre-commit hook that runs lint-staged to enforce code quality
- Configured lint-staged to:
- Format JSON, MD, and YAML files with Prettier
- Lint and typecheck TypeScript files before commits
- Fixed release script in codex-cli package.json (changed "pmpm" to "npm
publish")
- Removed duplicate Husky and lint-staged configurations from codex-cli
package.json
## Benefits
- **Consistent Code Quality**: Ensures all committed code meets project
standards
- **Automated Formatting**: Automatically formats code during commits
- **Early Error Detection**: Catches type errors and lint issues before
they're committed
- **Centralized Configuration**: Easier to maintain and update in one
place
- **Improved Collaboration**: Ensures consistent code style across the
team
## Future Improvements
We could further enhance this setup by
**Commit Message Validation**: Add commitlint to enforce conventional
commit messages
---------
Co-authored-by: Thibault Sottiaux <tibo@openai.com>
# What?
* When a prompt references an image path that doesn’t exist, replace it
with
```[missing image: <path>]``` instead of throwing an ENOENT.
* Adds a few unit tests for input-utils as there weren't any beforehand.
# Why?
Right now if you enter an invalid image path (e.g. it doesn't exist),
codex immediately crashes with a ENOENT error like so:
```
Error: ENOENT: no such file or directory, open 'test.png'
...
{
errno: -2,
code: 'ENOENT',
syscall: 'open',
path: 'test.png'
}
```
This aborts the entire session. A soft fallback lets the rest of the
input continue.
# How?
Wraps the image encoding + inputItem content pushing in a try-catch.
This is a minimal patch to avoid completely crashing — future work could
surface a warning to the user when this happens, or something to that
effect.
---------
Co-authored-by: Thibault Sottiaux <tibo@openai.com>
## Changes
- Added a `requiresShell` function to detect when a command contains
shell operators
- In the `exec` function, enabled the `shell: true` option if shell
operators are present
## Why This Is Necessary
See the discussion in this issue comment:
https://github.com/openai/codex/issues/320#issuecomment-2816528014
## Code Explanation
The `requiresShell` function parses the command arguments and checks for
any shell‑specific operators. If it finds shell operators, it adds the
`shell: true` option when running the command so that it’s executed
through a shell interpreter.
This pull request adds a feature that allows users to configure
auto-approved commands via a `safeCommands` array in the configuration
file.
## Related Issue
#380
## Changes
- Added loading and validation of the `safeCommands` array in
`src/utils/config.ts`
- Implemented auto-approval logic for commands matching `safeCommands`
prefixes in `src/approvals.ts`
- Added test cases in `src/tests/approvals.test.ts` to verify
`safeCommands` behavior
- Updated documentation with examples and explanations of the
configuration
Since we migrated to `pnpm` in #287, this updates the README to reflect
that change.
Just a small cleanup to align the commands with the current setup.
Adding in an option to turn on flex processing mode to reduce costs when
running the agent.
Bumped the openai typescript version to add the new feature.
---------
Co-authored-by: Thibault Sottiaux <tibo@openai.com>
**Summary**
This change introduces a new startup check that notifies users if a
newer `@openai/codex` version is available. To avoid spamming, it writes
a small state file recording the last check time and will only re‑check
once every 24 hours.
**What’s Changed**
- **New file** `src/utils/check-updates.ts`
- Runs `npm outdated --global @openai/codex`
- Reads/writes `codex-state.json` under `CONFIG_DIR`
- Limits checks to once per day (`UPDATE_CHECK_FREQUENCY = 24h`)
- Uses `boxen` for a styled alert and `which` to locate the npm binary
- **Hooked into** `src/cli.tsx` entrypoint:
```ts
import { checkForUpdates } from "./utils/check-updates";
// …
// after loading config
await checkForUpdates().catch();
```
- **Dependencies**
- Added `boxen@^8.0.1`, `which@^5.0.0`, `@types/which@^3.0.4`
- **Tests**
- Vitest suite under `tests/check-updates.test.ts`
- Snapshot in `__snapshots__/check-updates.test.ts.snap`
**Motivation**
Addresses issue #244. Users running a stale global install will now see
a friendly reminder—at most once per day—to upgrade and enjoy the latest
features.
**Test Plan**
- `getNPMCommandPath()` resolves npm correctly
- `checkOutdated()` parses `npm outdated` JSON
- State file prevents repeat alerts within 24h
- Boxen snapshot matches expected output
- No console output when state indicates a recent check
**Related Issue**
try resolves#244
**Preview**
Prompt a pnpm‑style alert when outdated

Let me know if you’d tweak any of the messaging, throttle frequency,
placement in the startup flow, or anything else.
---------
Co-authored-by: Thibault Sottiaux <tibo@openai.com>
- Docker container name based on work directory
- Centralize container removal logic
- Improve quoting for command arguments
- Ensure workdir is always set and normalized
Resolves: #371
Signed-off-by: BadPirate <badpirate@gmail.com>
Signed-off-by: BadPirate <badpirate@gmail.com>
# Migrate to pnpm for improved monorepo management
## Summary
This PR migrates the Codex repository from npm to pnpm, providing faster
dependency installation, better disk space usage, and improved monorepo
management.
## Changes
- Added `pnpm-workspace.yaml` to define workspace packages
- Added `.npmrc` with optimal pnpm configuration
- Updated root package.json with workspace scripts
- Moved resolutions and overrides to the root package.json
- Updated scripts to use pnpm instead of npm
- Added documentation for the migration
- Updated GitHub Actions workflow for pnpm
## Benefits
- **Faster installations**: pnpm is significantly faster than npm
- **Disk space savings**: pnpm's content-addressable store avoids
duplication
- **Strict dependency management**: prevents phantom dependencies
- **Simplified monorepo management**: better workspace coordination
- **Preparation for Turborepo**: as discussed, this is the first step
before adding Turborepo
## Testing
- Verified that `pnpm install` works correctly
- Verified that `pnpm run build` completes successfully
- Ensured all existing functionality is preserved
## Documentation
Added a detailed migration guide in `PNPM_MIGRATION.md` explaining:
- Why we're migrating to pnpm
- How to use pnpm with this repository
- Common commands and workspace-specific commands
- Monorepo structure and configuration
## Next Steps
As discussed, once this change is stable, we can consider adding
Turborepo as a follow-up enhancement.
# Fix CLI launcher on Windows by replacing `sh`-based entrypoint with
cross-platform Node script
## What's changed
* This PR attempts to replace the sh-based entry point with a node
script that works on all platforms including Windows Powershell and CMD
## Why
* Previously, when installing Codex globally via `npm i -g
@openai/codex`, Windows resulted in a broken CLI issue due to the `ps1`
launcher trying to execute `sh.exe`.
* If users don't have Unix-style shell, running the command will fail as
seen below since `sh.exe` can't be found
* Output:
```
& : The term 'sh.exe' is not recognized as the name of a cmdlet,
function, script file, or operable program. Check the
spelling of the name, or if a path was included, verify that the path is
correct and try again.
At C:\Users\{user}\AppData\Roaming\npm\codex.ps1:24 char:7
+ & "sh$exe" "$basedir/node_modules/@openai/codex/bin/codex" $args
+ ~~~~~~~~
+ CategoryInfo : ObjectNotFound: (sh.exe:String) [],
CommandNotFoundException
+ FullyQualifiedErrorId : CommandNotFoundException
```
## How
* By using a Node based entry point that resolves the path to the compiled ESM bundle and dynamically loads it using native ESM
* Removed dependency on platform-specific launchers allowing a single entrypoint to work everywhere Node.js runs.
## Result
Codex CLI now supports cross-platform and launches correctly via:
* macOS / Linux
* Windows PowerShell
* GitBash
* CMD
* WSL
Directly addresses #316


Fix: Shift + Enter no longer prints “[27;2;13~” in the single‑line
input. Validated as working and necessary in Ghostty on Linux.
## Key points
- src/components/vendor/ink-text-input.tsx
- Added early handler that recognises the two modifyOtherKeys
escape‑sequences
- [13;<mod>u (mode 2 / CSI‑u)
- [27;<mod>;13~ (mode 1 / legacy CSI‑~)
- If Ctrl is held (hasCtrl flag) → call onSubmit() (same as plain
Enter).
- Otherwise → insert a real newline at the caret (same as Option+Enter).
- Prevents the raw sequence from being inserted into the buffer.
- src/components/chat/multiline-editor.tsx
- Replaced non‑breaking spaces with normal spaces to satisfy eslint
no‑irregular‑whitespace rule (no behaviour change).
All unit tests (114) and ESLint now pass:
npm test ✔️
npm run lint ✔️
We provide the following options to facilitate Codex development in a container. This is particularly useful for verifying the Linux build when working on a macOS host.
## Docker
To build the Docker image locally for x64 and then run it with the repo mounted under `/workspace`:
Note that `/workspace/target` will contain the binaries built for your host platform, so we include `-e CARGO_TARGET_DIR=/workspace/codex-rs/target-amd64` in the `docker run` command so that the binaries built inside your container are written to a separate directory.
For arm64, specify `--platform=linux/amd64` instead for both `docker build` and `docker run`.
Currently, the `Dockerfile` works for both x64 and arm64 Linux, though you need to run `rustup target add x86_64-unknown-linux-musl` yourself to install the musl toolchain for x64.
## VS Code
VS Code recognizes the `devcontainer.json` file and gives you the option to develop Codex in a container. Currently, `devcontainer.json` builds and runs the `arm64` flavor of the container.
From the integrated terminal in VS Code, you can build either flavor of the `arm64` build (GNU or musl):
`openai/codex-action` is a GitHub Action that facilitates the use of [Codex](https://github.com/openai/codex) on GitHub issues and pull requests. Using the action, associate **labels** to run Codex with the appropriate prompt for the given context. Codex will respond by posting comments or creating PRs, whichever you specify!
Here is a sample workflow that uses `openai/codex-action`:
```yaml
name:Codex
on:
issues:
types:[opened, labeled]
pull_request:
branches:[main]
types:[labeled]
jobs:
codex:
if:...# optional, but can be effective in conserving CI resources
runs-on:ubuntu-latest
# TODO(mbolin): Need to verify if/when `write` is necessary.
permissions:
contents:write
issues:write
pull-requests:write
steps:
# By default, Codex runs network disabled using --full-auto, so perform
# any setup that requires network (such as installing dependencies)
See sample usage in [`codex.yml`](../../workflows/codex.yml).
## Triggering the Action
Using the sample workflow above, we have:
```yaml
on:
issues:
types:[opened, labeled]
pull_request:
branches:[main]
types:[labeled]
```
which means our workflow will be triggered when any of the following events occur:
- a label is added to an issue
- a label is added to a pull request against the `main` branch
### Label-Based Triggers
To define a GitHub label that should trigger Codex, create a file named `.github/codex/labels/LABEL-NAME.md` in your repository where `LABEL-NAME` is the name of the label. The content of the file is the prompt template to use when the label is added (see more on [Prompt Template Variables](#prompt-template-variables) below).
For example, if the file `.github/codex/labels/codex-review.md` exists, then:
- Adding the `codex-review` label will trigger the workflow containing the `openai/codex-action` GitHub Action.
- When `openai/codex-action` starts, it will replace the `codex-review` label with `codex-review-in-progress`.
- When `openai/codex-action` is finished, it will replace the `codex-review-in-progress` label with `codex-review-completed`.
If Codex sees that either `codex-review-in-progress` or `codex-review-completed` is already present, it will not perform the action.
As determined by the [default config](./src/default-label-config.ts), Codex will act on the following labels by default:
- Adding the `codex-review` label to a pull request will have Codex review the PR and add it to the PR as a comment.
- Adding the `codex-triage` label to an issue will have Codex investigate the issue and report its findings as a comment.
- Adding the `codex-issue-fix` label to an issue will have Codex attempt to fix the issue and create a PR wit the fix, if any.
## Action Inputs
The `openai/codex-action` GitHub Action takes the following inputs
### `openai_api_key` (required)
Set your `OPENAI_API_KEY` as a [repository secret](https://docs.github.com/en/actions/security-for-github-actions/security-guides/using-secrets-in-github-actions). See **Secrets and varaibles** then **Actions** in the settings for your GitHub repo.
Note that the secret name does not have to be `OPENAI_API_KEY`. For example, you might want to name it `CODEX_OPENAI_API_KEY` and then configure it on `openai/codex-action` as follows:
This is required so that Codex can post a comment or create a PR. Set this value on the action as follows:
```yaml
github_token:${{ secrets.GITHUB_TOKEN }}
```
### `codex_args`
A whitespace-delimited list of arguments to pass to Codex. Defaults to `--full-auto`, but if you want to override the default model to use `o3`:
```yaml
codex_args:"--full-auto --model o3"
```
For more complex configurations, use the `codex_home` input.
### `codex_home`
If set, the value to use for the `$CODEX_HOME` environment variable when running Codex. As explained [in the docs](https://github.com/openai/codex/tree/main/codex-rs#readme), this folder can contain the `config.toml` to configure Codex, custom instructions, and log files.
This should be a relative path within your repo.
## Prompt Template Variables
As shown above, `"prompt"` and `"promptPath"` are used to define prompt templates that will be populated and passed to Codex in response to certain events. All template variables are of the form `{CODEX_ACTION_...}` and the supported values are defined below.
### `CODEX_ACTION_ISSUE_TITLE`
If the action was triggered on a GitHub issue, this is the issue title.
Specifically it is read as the `.issue.title` from the `$GITHUB_EVENT_PATH`.
### `CODEX_ACTION_ISSUE_BODY`
If the action was triggered on a GitHub issue, this is the issue body.
Specifically it is read as the `.issue.body` from the `$GITHUB_EVENT_PATH`.
### `CODEX_ACTION_GITHUB_EVENT_PATH`
The value of the `$GITHUB_EVENT_PATH` environment variable, which is the path to the file that contains the JSON payload for the event that triggered the workflow. Codex can use `jq` to read only the fields of interest from this file.
### `CODEX_ACTION_PR_DIFF`
If the action was triggered on a pull request, this is the diff between the base and head commits of the PR. It is the output from `git diff`.
Note that the content of the diff could be quite large, so is generally safer to point Codex at `CODEX_ACTION_GITHUB_EVENT_PATH` and let it decide how it wants to explore the change.
description:"A reusable action that runs a Codex model."
inputs:
openai_api_key:
description:"The value to use as the OPENAI_API_KEY environment variable when running Codex."
required:true
trigger_phrase:
description:"Text to trigger Codex from a PR/issue body or comment."
required:false
default:""
github_token:
description:"Token so Codex can comment on the PR or issue."
required:true
codex_args:
description:"A whitespace-delimited list of arguments to pass to Codex. Due to limitations in YAML, arguments with spaces are not supported. For more complex configurations, use the `codex_home` input."
Provide a concise and respectful comment summarizing the findings.
### {CODEX_ACTION_ISSUE_TITLE}
{CODEX_ACTION_ISSUE_BODY}
`.trim(),
},
"codex-code-review":{
getPromptTemplate:()=>
`
Review this PR and respond with a very concise final message, formatted in Markdown.
There should be a summary of the changes (1-2 sentences) and a few bullet points if necessary.
Then provide the **review** (1-2 sentences plus bullet points, friendly tone).
{CODEX_ACTION_GITHUB_EVENT_PATH} contains the JSON that triggered this GitHub workflow. It contains the \`base\` and \`head\` refs that define this PR. Both refs are available locally.
`.trim(),
},
"codex-attempt-fix":{
getPromptTemplate:()=>
`
Attempt to solve the reported issue.
If a code change is required, create a new branch, commit the fix, and open a pull-request that resolves the problem.
Review this PR and respond with a very concise final message, formatted in Markdown.
There should be a summary of the changes (1-2 sentences) and a few bullet points if necessary.
Then provide the **review** (1-2 sentences plus bullet points, friendly tone).
{CODEX_ACTION_GITHUB_EVENT_PATH} contains the JSON that triggered this GitHub workflow. It contains the `base` and `head` refs that define this PR. Both refs are available locally.
- Never add or modify any code related to `CODEX_SANDBOX_NETWORK_DISABLED_ENV_VAR`. You operate in a sandbox where `CODEX_SANDBOX_NETWORK_DISABLED=1` will be set whenever you use the `shell` tool. Any existing code that uses `CODEX_SANDBOX_NETWORK_DISABLED_ENV_VAR` was authored with this fact in mind. It is often used to early exit out of tests that the author knew you would not be able to run given your sandbox limitations.
Before creating a pull request with changes to `codex-rs`, run `just fmt` (in `codex-rs` directory) to format the code and `just fix` (in `codex-rs` directory) to fix any linter issues in the code, ensure the test suite passes by running `cargo test --all-features` in the `codex-rs` directory.
When making individual changes prefer running tests on individual files or projects first.
<p align="center">Lightweight coding agent that runs in your terminal</p>
<p align="center"><code>npm i -g @openai/codex</code></p>
<p align="center"><code>npm i -g @openai/codex</code><br />or <code>brew install codex</code></p>

This is the home of the **Codex CLI**, which is a coding agent from OpenAI that runs locally on your computer. If you are looking for the _cloud-based agent_ from OpenAI, **Codex [Web]**, see <https://chatgpt.com/codex>.
<!--  -->
- [Zero Data Retention (ZDR) Organization Limitation](#zero-data-retention-zdr-organization-limitation)
<!-- End ToC -->
</details>
---
## Experimental Technology Disclaimer
## Experimental technology disclaimer
Codex CLI is an experimental project under active development. It is not yet stable, may contain bugs, incomplete features, or undergo breaking changes. We’re building it in the open with the community and welcome:
Codex CLI is an experimental project under active development. It is not yet stable, may contain bugs, incomplete features, or undergo breaking changes. We're building it in the open with the community and welcome:
- Bug reports
- Feature requests
@@ -56,27 +66,103 @@ Help us improve by filing issues or submitting PRs (see the section below for ho
## Quickstart
Install globally:
Install globally with your preferred package manager:
Or go to the [latest GitHub Release](https://github.com/openai/codex/releases/latest) and download the appropriate binary for your platform.
### OpenAI API Users
Next, set your OpenAI API key as an environment variable:
```shell
exportOPENAI_API_KEY="your-api-key-here"
```
> **Note:** This command sets the key only for your current terminal session. To make it permanent, add the `export` line to your shell's configuration file (e.g., `~/.zshrc`).
>
> **Tip:** You can also place your API key into a `.env` file at the root of your project:
>
> ```env
> OPENAI_API_KEY=your-api-key-here
> ```
>
> The CLI will automatically load variables from `.env` (via `dotenv/config`).
> [!NOTE]
>This command sets the key only for your current terminal session. You can add the `export` line to your shell's configuration file (e.g., `~/.zshrc`), but we recommend setting it for the session.
### OpenAI Plus/Pro Users
If you have a paid OpenAI account, run the following to start the login process:
```
codex login
```
If you complete the process successfully, you should have a `~/.codex/auth.json` file that contains the credentials that Codex will use.
To verify whether you are currently logged in, run:
```
codex login status
```
If you encounter problems with the login flow, please comment on <https://github.com/openai/codex/issues/1243>.
<details>
<summary><strong>Use <code>--profile</code> to use other models</strong></summary>
Codex also allows you to use other providers that support the OpenAI Chat Completions (or Responses) API.
To do so, you must first define custom [providers](./config.md#model_providers) in `~/.codex/config.toml`. For example, the provider for a standard Ollama setup would be defined as follows:
```toml
[model_providers.ollama]
name="Ollama"
base_url="http://localhost:11434/v1"
```
The `base_url` will have `/chat/completions` appended to it to build the full URL for the request.
For providers that also require an `Authorization` header of the form `Bearer: SECRET`, an `env_key` can be specified, which indicates the environment variable to read to use as the value of `SECRET` when making a request:
```toml
[model_providers.openrouter]
name="OpenRouter"
base_url="https://openrouter.ai/api/v1"
env_key="OPENROUTER_API_KEY"
```
Providers that speak the Responses API are also supported by adding `wire_api = "responses"` as part of the definition. Accessing OpenAI models via Azure is an example of such a provider, though it also requires specifying additional `query_params` that need to be appended to the request URL:
```toml
[model_providers.azure]
name="Azure"
# Make sure you set the appropriate subdomain for this URL.
env_key="AZURE_OPENAI_API_KEY"# Or "OPENAI_API_KEY", whichever you use.
# Newer versions appear to support the responses API, see https://github.com/openai/codex/pull/1321
query_params={api-version="2025-04-01-preview"}
wire_api="responses"
```
Once you have defined a provider you wish to use, you can configure it as your default provider as follows:
```toml
model_provider="azure"
```
> [!TIP]
> If you find yourself experimenting with a variety of models and providers, then you likely want to invest in defining a _profile_ for each configuration like so:
```toml
[profiles.o3]
model_provider="azure"
model="o3"
[profiles.mistral]
model_provider="ollama"
model="mistral"
```
This way, you can specify one command-line argument (.e.g., `--profile o3`, `--profile mistral`) to override multiple settings together.
</details>
<br />
Run interactively:
@@ -91,143 +177,150 @@ codex "explain this codebase to me"
```
```shell
codex --approval-mode full-auto "create the fanciest todo-list app"
codex --full-auto "create the fanciest todo-list app"
```
That’s it – Codex will scaffold a file, run it inside a sandbox, install any
That's it - Codex will scaffold a file, run it inside a sandbox, install any
missing dependencies, and show you the live result. Approve the changes and
they’ll be committed to your working directory.
they'll be committed to your working directory.
---
## WhyCodex?
## WhyCodex?
Codex CLI is built for developers who already **live in the terminal** and want
ChatGPT‑level reasoning **plus** the power to actually run code, manipulate
files, and iterate – all under version control. In short, it’s _chat‑driven
ChatGPT-level reasoning **plus** the power to actually run code, manipulate
files, and iterate - all under version control. In short, it's _chat-driven
development_ that understands and executes your repo.
- **Zero setup** — bring your OpenAI API key and it just works!
- **Zero setup** - bring your OpenAI API key and it just works!
- **Full auto-approval, while safe + secure** by running network-disabled and directory-sandboxed
- **Multimodal** — pass in screenshots or diagrams to implement features ✨
- **Multimodal** - pass in screenshots or diagrams to implement features ✨
And it's **fully open-source** so you can see and contribute to how it develops!
---
## SecurityModel&Permissions
## Security model & permissions
Codex lets you decide _how much autonomy_the agent receives and auto-approval policy via the
`--approval-mode` flag (or the interactive onboarding prompt):
Codex lets you decide _how much autonomy_you want to grant the agent. The following options can be configured independently:
| Mode | What the agent may do without asking | Still requires approval |
| **FullAuto** | • Read/write files <br>• Execute shell commands (network disabled, writes limited to your workdir) | – |
- [`approval_policy`](./codex-rs/config.md#approval_policy) determines when you should be prompted to approve whether Codex can execute a command
- [`sandbox`](./codex-rs/config.md#sandbox) determines the _sandbox policy_ that Codex uses to execute untrusted commands
In **FullAuto** every command is run **network‑disabled** and confined to the
current working directory (plus temporary files) for defense‑in‑depth. Codex
will also show a warning/confirmation if you start in **auto‑edit** or
**full‑auto** while the directory is _not_ tracked by Git, so you always have a
safety net.
By default, Codex runs with `--ask-for-approval untrusted` and `--sandbox read-only`, which means that:
Coming soon: you’ll be able to whitelist specific commands to auto‑execute with
the network enabled, once we’re confident in additional safeguards.
- The user is prompted to approve every command not on the set of "trusted" commands built into Codex (`cat`, `ls`, etc.)
- Approved commands are run outside of a sandbox because user approval implies "trust," in this case.
Running Codex with the `--full-auto` convenience flag changes the configuration to `--ask-for-approval on-failure` and `--sandbox workspace-write`, which means that:
- Codex does not initially ask for user approval before running an individual command.
- Though when it runs a command, it is run under a sandbox in which:
- It can read any file on the system.
- It can only write files under the current directory (or the directory specified via `--cd`).
- Network requests are completely disabled.
- Only if the command exits with a non-zero exit code will it ask the user for approval. If granted, it will re-attempt the command outside of the sandbox. (A common case is when Codex cannot `npm install` a dependency because that requires network access.)
Again, these two options can be configured independently. For example, if you want Codex to perform an "exploration" where you are happy for it to read anything it wants but you never want to be prompted, you could run Codex with `--ask-for-approval never` and `--sandbox read-only`.
### Platform sandboxing details
The hardening mechanism Codex uses depends on your OS:
The mechanism Codex uses to implement the sandbox policy depends on your OS:
- **macOS12+** – commands are wrapped with**AppleSeatbelt**(`sandbox-exec`).
- **macOS12+** uses**AppleSeatbelt**and runs commands using `sandbox-exec` with a profile (`-p`) that corresponds to the `--sandbox` that was specified.
- **Linux** uses a combination of Landlock/seccomp APIs to enforce the `sandbox` configuration.
- Everything is placed in a read‑only jail except for a small set of
- Outbound network is _fully blocked_ by default – even if a child process
tries to `curl` somewhere it will fail.
- **Linux** – there is no sandboxing by default.
We recommend using Docker for sandboxing, where Codex launches itself inside a **minimal
container image** and mounts your repo _read/write_ at the same path. A
custom `iptables`/`ipset` firewall script denies all egress except the
OpenAI API. This gives you deterministic, reproducible runs without needing
root on the host. You can use the [`run_in_container.sh`](./codex-cli/scripts/run_in_container.sh) script to set up the sandbox.
Note that when running Linux in a containerized environment such as Docker, sandboxing may not work if the host/container configuration does not support the necessary Landlock/seccomp APIs. In such cases, we recommend configuring your Docker container so that it provides the sandbox guarantees you are looking for and then running `codex` with `--sandbox danger-full-access` (or, more simply, the `--dangerously-bypass-approvals-and-sandbox` flag) within your container.
Key flags: `--model/-m`, `--approval-mode/-a`, `--quiet/-q`, and `--notify`.
Key flags: `--model/-m`, `--ask-for-approval/-a`.
---
## Memory&ProjectDocs
## Memory & project docs
Codex merges Markdown instructions in this order:
You can give Codex extra instructions and guidance using `AGENTS.md` files. Codex looks for `AGENTS.md` files in the following places, and merges them top-down:
1.`~/.codex/instructions.md`– personal global guidance
2.`codex.md` at repo root – shared project notes
3.`codex.md` in cwd – sub‑package specifics
Disable with `--no-project-doc` or `CODEX_DISABLE_PROJECT_DOC=1`.
1.`~/.codex/AGENTS.md`- personal global guidance
2.`AGENTS.md` at repo root - shared project notes
3.`AGENTS.md` in the current working directory - sub-folder/feature specifics
---
## Non‑interactive/CImode
## Non-interactive / CImode
Run Codex head‑less in pipelines. Example GitHub Action step:
Run Codex head-less in pipelines. Example GitHub Action step:
```yaml
- name:Update changelog via Codex
run:|
npm install -g @openai/codex
export OPENAI_API_KEY="${{ secrets.OPENAI_KEY }}"
codex -a auto-edit --quiet "update CHANGELOG for next release"
codex exec --full-auto "update CHANGELOG for next release"
```
Set `CODEX_QUIET_MODE=1` to silence interactive UI noise.
## Model Context Protocol (MCP)
## Tracing / Verbose Logging
The Codex CLI can be configured to leverage MCP servers by defining an [`mcp_servers`](./codex-rs/config.md#mcp_servers) section in `~/.codex/config.toml`. It is intended to mirror how tools such as Claude and Cursor define `mcpServers` in their respective JSON config files, though the Codex format is slightly different since it uses TOML rather than JSON, e.g.:
Setting the environment variable `DEBUG=true` prints full API request and response details:
```shell
DEBUG=true codex
```toml
# IMPORTANT: the top-level key is `mcp_servers` rather than `mcpServers`.
[mcp_servers.server-name]
command="npx"
args=["-y","mcp-server"]
env={"API_KEY"="value"}
```
> [!TIP]
> It is somewhat experimental, but the Codex CLI can also be run as an MCP _server_ via `codex mcp`. If you launch it with an MCP client such as `npx @modelcontextprotocol/inspector codex mcp` and send it a `tools/list` request, you will see that there is only one tool, `codex`, that accepts a grab-bag of inputs, including a catch-all `config` map for anything you might want to override. Feel free to play around with it and provide feedback via GitHub issues.
## Tracing / verbose logging
Because Codex is written in Rust, it honors the `RUST_LOG` environment variable to configure its logging behavior.
The TUI defaults to `RUST_LOG=codex_core=info,codex_tui=info` and log messages are written to `~/.codex/log/codex-tui.log`, so you can leave the following running in a separate terminal to monitor log messages as they are written:
```
tail -F ~/.codex/log/codex-tui.log
```
By comparison, the non-interactive mode (`codex exec`) defaults to `RUST_LOG=error`, but messages are printed inline, so there is no need to monitor a separate file.
See the Rust documentation on [`RUST_LOG`](https://docs.rs/env_logger/latest/env_logger/#enabling-logging) for more information on the configuration options.
---
## Recipes
Below are a few bite‑size examples you can copy‑paste. Replace the text in quotes with your own task. See the [prompting guide](https://github.com/openai/codex/blob/main/codex-cli/examples/prompting_guide.md) for more tips and usage patterns.
Below are a few bite-size examples you can copy-paste. Replace the text in quotes with your own task. See the [prompting guide](https://github.com/openai/codex/blob/main/codex-cli/examples/prompting_guide.md) for more tips and usage patterns.
Each archive contains a single entry with the platform baked into the name (e.g., `codex-x86_64-unknown-linux-musl`), so you likely want to rename it to `codex` after extracting it.
### DotSlash
The GitHub Release also contains a [DotSlash](https://dotslash-cli.com/) file for the Codex CLI named `codex`. Using a DotSlash file makes it possible to make a lightweight commit to source control to ensure all contributors use the same version of an executable, regardless of what platform they use for development.
cargo run --bin codex -- "explain this codebase to me"
# Or link the command globally for convenience
npm link
# After making changes, ensure the code is clean.
cargo fmt -- --config imports_granularity=Item
cargo clippy --tests
# Run the tests.
cargo test
```
</details>
@@ -276,22 +396,11 @@ npm link
## Configuration
Codex looks for config files in **`~/.codex/`**.
Codex supports a rich set of configuration options documented in [`codex-rs/config.md`](./codex-rs/config.md).
```yaml
# ~/.codex/config.yaml
model:o4-mini# Default model
fullAutoErrorMode:ask-user# or ignore-and-continue
notify:true# Enable desktop notifications for responses
```
By default, Codex loads its configuration from `~/.codex/config.toml`.
You can also define custom instructions:
```yaml
# ~/.codex/instructions.md
- Always respond with emojis
- Only use git commands if I explicitly mention you should
```
Though `--config` can be used to set/override ad-hoc config values for individual invocations of `codex`.
---
@@ -326,43 +435,38 @@ Codex runs model-generated commands in a sandbox. If a proposed command or file
<details>
<summary>Does it work on Windows?</summary>
Not directly. It requires [Windows Subsystem for Linux (WSL2)](https://learn.microsoft.com/en-us/windows/wsl/install) – Codex has been tested on macOS and Linux with Node ≥ 22.
Not directly. It requires [Windows Subsystem for Linux (WSL2)](https://learn.microsoft.com/en-us/windows/wsl/install) - Codex has been tested on macOS and Linux with Node22.
</details>
---
## Zero Data Retention (ZDR) Organization Limitation
## Zero data retention (ZDR) usage
> **Note:** Codex CLI does **not** currently support OpenAI organizations with [Zero Data Retention (ZDR)](https://platform.openai.com/docs/guides/your-data#zero-data-retention) enabled.
If your OpenAI organization has Zero Data Retention enabled, you may encounter errors such as:
Codex CLI **does** support OpenAI organizations with [Zero Data Retention (ZDR)](https://platform.openai.com/docs/guides/your-data#zero-data-retention) enabled. If your OpenAI organization has Zero Data Retention enabled and you still encounter errors such as:
```
OpenAI rejected the request. Error details: Status: 400, Code: unsupported_parameter, Type: invalid_request_error, Message: 400 Previous response cannot be used for this organization due to Zero Data Retention.
```
**Why?**
Ensure you are running `codex` with `--config disable_response_storage=true` or add this line to `~/.codex/config.toml` to avoid specifying the command line option each time:
- Codex CLI relies on the Responses API with `store:true`to enable internal reasoning steps.
- As noted in the [docs](https://platform.openai.com/docs/guides/your-data#responses-api), the Responses API requires a 30-day retention period by default, or when the store parameter is set to true.
- ZDR organizations cannot use `store:true`, so requests will fail.
```toml
disable_response_storage= true
```
**What can I do?**
- If you are part of a ZDR organization, Codex CLI will not work until support is added.
- We are tracking this limitation and will update the documentation if support becomes available.
See [the configuration documentation on `disable_response_storage`](./codex-rs/config.md#disable_response_storage) for details.
---
## Funding Opportunity
## Codex open source fund
We’re excited to launch a **$1million initiative** supporting open source projects that use CodexCLI and other OpenAI models.
We're excited to launch a **$1million initiative** supporting open source projects that use CodexCLI and other OpenAI models.
- Grants are awarded in**$25,000** API credit increments.
- Grants are awarded up to**$25,000** API credits.
- Applications are reviewed **on a rolling basis**.
@@ -370,153 +474,96 @@ We’re excited to launch a **$1million initiative** supporting open source pr
This project is under active development and the code will likely change pretty significantly. We'll update this message once that's complete!
More broadly we welcome contributions – whether you are opening your very first pull request or you’re a seasoned maintainer. At the same time we care about reliability and long‑term maintainability, so the bar for merging code is intentionally **high**. The guidelines below spell out what “high‑quality” means in practice and should make the whole process transparent and friendly.
More broadly we welcome contributions - whether you are opening your very first pull request or you're a seasoned maintainer. At the same time we care about reliability and long-term maintainability, so the bar for merging code is intentionally **high**. The guidelines below spell out what "high-quality" means in practice and should make the whole process transparent and friendly.
### Development workflow
- Create a _topic branch_ from `main`– e.g. `feat/interactive-prompt`.
- Create a _topic branch_ from `main`- e.g. `feat/interactive-prompt`.
- Keep your changes focused. Multiple unrelated fixes should be opened as separate PRs.
-Use `npm run test:watch` during development for super‑fast feedback.
- We use **Vitest** for unit tests, **ESLint** + **Prettier** for style, and **TypeScript** for type‑checking.
- Before pushing, run the full test/type/lint suite:
-Following the [development setup](#development-workflow) instructions above, ensure your change is free of lint warnings and test failures.
### Git Hooks with Husky
This project uses [Husky](https://typicode.github.io/husky/) to enforce code quality checks:
- **Pre-commit hook**: Automatically runs lint-staged to format and lint files before committing
- **Pre-push hook**: Runs tests and type checking before pushing to the remote
These hooks help maintain code quality and prevent pushing code with failing tests. For more details, see [HUSKY.md](./codex-cli/HUSKY.md).
```bash
npm test&& npm run lint && npm run typecheck
```
- If you have **not** yet signed the Contributor License Agreement (CLA), add a PR comment containing the exact text
```text
I have read the CLA Document and I hereby sign the CLA
```
The CLA‑Assistant bot will turn the PR status green once all authors have signed.
```bash
#Watch mode (tests rerun on change)
npm run test:watch
#Type‑check without emitting files
npm run typecheck
#Automatically fix lint + prettier issues
npm run lint:fix
npm run format:fix
```
#### Nix Flake Development
Prerequisite: Nix >= 2.4 with flakes enabled (`experimental-features = nix-command flakes` in `~/.config/nix/nix.conf`).
Enter a Nix development shell:
```bash
nix develop
```
This shell includes Node.js, installs dependencies, builds the CLI, and provides a `codex` command alias.
Build and run the CLI directly:
```bash
nix build
./result/bin/codex --help
```
Run the CLI via the flake app:
```bash
nix run .#codex
```
### Writing high‑impact code changes
### Writing high-impact code changes
1.**Start with an issue.** Open a new one or comment on an existing discussion so we can agree on the solution before code is written.
2.**Add or update tests.** Every new feature or bug‑fix should come with test coverage that fails before your change and passes afterwards. 100% coverage is not required, but aim for meaningful assertions.
3.**Document behaviour.** If your change affects user‑facing behaviour, update the README, inline help (`codex --help`), or relevant example projects.
2. **Add or update tests.** Every new feature or bug-fix should come with test coverage that fails before your change and passes afterwards. 100% coverage is not required, but aim for meaningful assertions.
3. **Document behaviour.** If your change affects user-facing behaviour, update the README, inline help (`codex --help`), or relevant example projects.
4.**Keep commits atomic.** Each commit should compile and the tests should pass. This makes reviews and potential rollbacks easier.
### Opening a pull request
- Fill in the PR template (or include similar information) –**What? Why? How?**
- Run **all** checks locally (`npm test && npm run lint && npm run typecheck`). CI failures that could have been caught locally slow down the process.
- Make sure your branch is up‑to‑date with `main` and that you have resolved merge conflicts.
- Mark the PR as **Ready for review** only when you believe it is in a merge‑able state.
- Fill in the PR template (or include similar information) - **What? Why? How?**
- Run **all** checks locally (`cargo test && cargo clippy --tests && cargo fmt -- --config imports_granularity=Item`). CI failures that could have been caught locally slow down the process.
- Make sure your branch is up-to-date with `main` and that you have resolved merge conflicts.
- Mark the PR as **Ready for review** only when you believe it is in a merge-able state.
### Review process
1. One maintainer will be assigned as a primary reviewer.
2. We may ask for changes – please do not take this personally. We value the work, we just also value consistency and long‑term maintainability.
3. When there is consensus that the PR meets the bar, a maintainer will squash‑and‑merge.
2. We may ask for changes - please do not take this personally. We value the work, we just also value consistency and long-term maintainability.
3. When there is consensus that the PR meets the bar, a maintainer will squash-and-merge.
### Community values
- **Be kind and inclusive.** Treat others with respect; we follow the [Contributor Covenant](https://www.contributor-covenant.org/).
- **Assume good intent.** Written communication is hard – err on the side of generosity.
- **Assume good intent.** Written communication is hard - err on the side of generosity.
- **Teach & learn.** If you spot something confusing, open an issue or PR with improvements.
### Getting help
If you run into problems setting up the project, would like feedback on an idea, or just want to say _hi_ – please open a Discussion or jump into the relevant issue. We are happy to help.
If you run into problems setting up the project, would like feedback on an idea, or just want to say _hi_ - please open a Discussion or jump into the relevant issue. We are happy to help.
Together we can make Codex CLI an incredible tool. **Happy hacking!** :rocket:
### Contributor License Agreement (CLA)
### Contributor license agreement (CLA)
All contributors **must** accept the CLA. The process is lightweight:
1. Open your pull request.
2. Paste the following comment (or reply `recheck` if you’ve signed before):
2. Paste the following comment (or reply `recheck` if you've signed before):
```text
I have read the CLA Document and I hereby sign the CLA
```
3. The CLA‑Assistant bot records your signature in the repo and marks the status check as passed.
3. The CLA-Assistant bot records your signature in the repo and marks the status check as passed.
No special Git commands, email attachments, or commit footers required.
This will make a local commit on top of `main` with `version` set to `$VERSION` in `codex-rs/Cargo.toml` (note that on `main`, we leave the version as `version = "0.0.0"`).
This will push the commit using the tag `rust-v${VERSION}`, which in turn kicks off [the release workflow](.github/workflows/rust-release.yml). This will create a new GitHub Release named `$VERSION`.
If everything looks good in the generated GitHub Release, uncheck the **pre-release** box so it is the latest release.
Create a PR to update [`Formula/c/codex.rb`](https://github.com/Homebrew/homebrew-core/blob/main/Formula/c/codex.rb) on Homebrew.
---
## Security&ResponsibleAI
## Security & responsibleAI
Have you discovered a vulnerability or have concerns about model output? Please e‑mail **security@openai.com** and we will respond promptly.
Have you discovered a vulnerability or have concerns about model output? Please e-mail **security@openai.com** and we will respond promptly.
---
## License
This repository is licensed under the [Apache-2.0License](LICENSE).
This repository is licensed under the [Apache-2.0License](LICENSE).
<p align="center">Lightweight coding agent that runs in your terminal</p>
<p align="center"><code>npm i -g @openai/codex</code></p>
> [!IMPORTANT]
> This is the documentation for the _legacy_ TypeScript implementation of the Codex CLI. It has been superseded by the _Rust_ implementation. See the [README in the root of the Codex repository](https://github.com/openai/codex/blob/main/README.md) for details.

---
<details>
<summary><strong>Table of contents</strong></summary>
Codex CLI is an experimental project under active development. It is not yet stable, may contain bugs, incomplete features, or undergo breaking changes. We're building it in the open with the community and welcome:
- Bug reports
- Feature requests
- Pull requests
- Good vibes
Help us improve by filing issues or submitting PRs (see the section below for how to contribute)!
## Quickstart
Install globally:
```shell
npm install -g @openai/codex
```
Next, set your OpenAI API key as an environment variable:
```shell
exportOPENAI_API_KEY="your-api-key-here"
```
> **Note:** This command sets the key only for your current terminal session. You can add the `export` line to your shell's configuration file (e.g., `~/.zshrc`) but we recommend setting for the session. **Tip:** You can also place your API key into a `.env` file at the root of your project:
>
> ```env
> OPENAI_API_KEY=your-api-key-here
> ```
>
> The CLI will automatically load variables from `.env` (via `dotenv/config`).
<details>
<summary><strong>Use <code>--provider</code> to use other models</strong></summary>
> Codex also allows you to use other providers that support the OpenAI Chat Completions API. You can set the provider in the config file or use the `--provider` flag. The possible options for `--provider` are:
>
> - openai (default)
> - openrouter
> - azure
> - gemini
> - ollama
> - mistral
> - deepseek
> - xai
> - groq
> - arceeai
> - any other provider that is compatible with the OpenAI API
>
> If you use a provider other than OpenAI, you will need to set the API key for the provider in the config file or in the environment variable as:
>
> ```shell
> export <provider>_API_KEY="your-api-key-here"
> ```
>
> If you use a provider not listed above, you must also set the base URL for the provider:
Key flags: `--model/-m`, `--approval-mode/-a`, `--quiet/-q`, and `--notify`.
---
## Memory & project docs
You can give Codex extra instructions and guidance using `AGENTS.md` files. Codex looks for `AGENTS.md` files in the following places, and merges them top-down:
1.`~/.codex/AGENTS.md` - personal global guidance
2.`AGENTS.md` at repo root - shared project notes
3.`AGENTS.md` in the current working directory - sub-folder/feature specifics
Disable loading of these files with `--no-project-doc` or the environment variable `CODEX_DISABLE_PROJECT_DOC=1`.
---
## Non-interactive / CI mode
Run Codex head-less in pipelines. Example GitHub Action step:
```yaml
- name:Update changelog via Codex
run:|
npm install -g @openai/codex
export OPENAI_API_KEY="${{ secrets.OPENAI_KEY }}"
codex -a auto-edit --quiet "update CHANGELOG for next release"
```
Set `CODEX_QUIET_MODE=1` to silence interactive UI noise.
## Tracing / verbose logging
Setting the environment variable `DEBUG=true` prints full API request and response details:
```shell
DEBUG=true codex
```
---
## Recipes
Below are a few bite-size examples you can copy-paste. Replace the text in quotes with your own task. See the [prompting guide](https://github.com/openai/codex/blob/main/codex-cli/examples/prompting_guide.md) for more tips and usage patterns.
<summary>OpenAI released a model called Codex in 2021 - is this related?</summary>
In 2021, OpenAI released Codex, an AI system designed to generate code from natural language prompts. That original Codex model was deprecated as of March 2023 and is separate from the CLI tool.
</details>
<details>
<summary>Which models are supported?</summary>
Any model available with [Responses API](https://platform.openai.com/docs/api-reference/responses). The default is `o4-mini`, but pass `--model gpt-4.1` or set `model: gpt-4.1` in your config file to override.
</details>
<details>
<summary>Why does <code>o3</code> or <code>o4-mini</code> not work for me?</summary>
It's possible that your [API account needs to be verified](https://help.openai.com/en/articles/10910291-api-organization-verification) in order to start streaming responses and seeing chain of thought summaries from the API. If you're still running into issues, please let us know!
</details>
<details>
<summary>How do I stop Codex from editing my files?</summary>
Codex runs model-generated commands in a sandbox. If a proposed command or file change doesn't look right, you can simply type **n** to deny the command or give the model feedback.
</details>
<details>
<summary>Does it work on Windows?</summary>
Not directly. It requires [Windows Subsystem for Linux (WSL2)](https://learn.microsoft.com/en-us/windows/wsl/install) - Codex has been tested on macOS and Linux with Node 22.
</details>
---
## Zero data retention (ZDR) usage
Codex CLI **does** support OpenAI organizations with [Zero Data Retention (ZDR)](https://platform.openai.com/docs/guides/your-data#zero-data-retention) enabled. If your OpenAI organization has Zero Data Retention enabled and you still encounter errors such as:
```
OpenAI rejected the request. Error details: Status: 400, Code: unsupported_parameter, Type: invalid_request_error, Message: 400 Previous response cannot be used for this organization due to Zero Data Retention.
```
You may need to upgrade to a more recent version with: `npm i -g @openai/codex@latest`
---
## Codex open source fund
We're excited to launch a **$1 million initiative** supporting open source projects that use Codex CLI and other OpenAI models.
- Grants are awarded up to **$25,000** API credits.
- Applications are reviewed **on a rolling basis**.
This project is under active development and the code will likely change pretty significantly. We'll update this message once that's complete!
More broadly we welcome contributions - whether you are opening your very first pull request or you're a seasoned maintainer. At the same time we care about reliability and long-term maintainability, so the bar for merging code is intentionally **high**. The guidelines below spell out what "high-quality" means in practice and should make the whole process transparent and friendly.
### Development workflow
- Create a _topic branch_ from `main` - e.g. `feat/interactive-prompt`.
- Keep your changes focused. Multiple unrelated fixes should be opened as separate PRs.
- Use `pnpm test:watch` during development for super-fast feedback.
- We use **Vitest** for unit tests, **ESLint** + **Prettier** for style, and **TypeScript** for type-checking.
- Before pushing, run the full test/type/lint suite:
### Git hooks with Husky
This project uses [Husky](https://typicode.github.io/husky/) to enforce code quality checks:
- **Pre-commit hook**: Automatically runs lint-staged to format and lint files before committing
- **Pre-push hook**: Runs tests and type checking before pushing to the remote
These hooks help maintain code quality and prevent pushing code with failing tests. For more details, see [HUSKY.md](./HUSKY.md).
```bash
pnpm test&& pnpm run lint && pnpm run typecheck
```
- If you have **not** yet signed the Contributor License Agreement (CLA), add a PR comment containing the exact text
```text
I have read the CLA Document and I hereby sign the CLA
```
The CLA-Assistant bot will turn the PR status green once all authors have signed.
```bash
# Watch mode (tests rerun on change)
pnpm test:watch
# Type-check without emitting files
pnpm typecheck
# Automatically fix lint + prettier issues
pnpm lint:fix
pnpm format:fix
```
### Debugging
To debug the CLI with a visual debugger, do the following in the `codex-cli` folder:
- Run `pnpm run build` to build the CLI, which will generate `cli.js.map` alongside `cli.js` in the `dist` folder.
- Run the CLI with `node --inspect-brk ./dist/cli.js` The program then waits until a debugger is attached before proceeding. Options:
- In VS Code, choose **Debug: Attach to Node Process** from the command palette and choose the option in the dropdown with debug port `9229` (likely the first option)
- Go to <chrome://inspect> in Chrome and find **localhost:9229** and click **trace**
### Writing high-impact code changes
1. **Start with an issue.** Open a new one or comment on an existing discussion so we can agree on the solution before code is written.
2. **Add or update tests.** Every new feature or bug-fix should come with test coverage that fails before your change and passes afterwards. 100% coverage is not required, but aim for meaningful assertions.
3. **Document behaviour.** If your change affects user-facing behaviour, update the README, inline help (`codex --help`), or relevant example projects.
4. **Keep commits atomic.** Each commit should compile and the tests should pass. This makes reviews and potential rollbacks easier.
### Opening a pull request
- Fill in the PR template (or include similar information) - **What? Why? How?**
- Run **all** checks locally (`npm test && npm run lint && npm run typecheck`). CI failures that could have been caught locally slow down the process.
- Make sure your branch is up-to-date with `main` and that you have resolved merge conflicts.
- Mark the PR as **Ready for review** only when you believe it is in a merge-able state.
### Review process
1. One maintainer will be assigned as a primary reviewer.
2. We may ask for changes - please do not take this personally. We value the work, we just also value consistency and long-term maintainability.
3. When there is consensus that the PR meets the bar, a maintainer will squash-and-merge.
### Community values
- **Be kind and inclusive.** Treat others with respect; we follow the [Contributor Covenant](https://www.contributor-covenant.org/).
- **Assume good intent.** Written communication is hard - err on the side of generosity.
- **Teach & learn.** If you spot something confusing, open an issue or PR with improvements.
### Getting help
If you run into problems setting up the project, would like feedback on an idea, or just want to say _hi_ - please open a Discussion or jump into the relevant issue. We are happy to help.
Together we can make Codex CLI an incredible tool. **Happy hacking!** :rocket:
### Contributor license agreement (CLA)
All contributors **must** accept the CLA. The process is lightweight:
1. Open your pull request.
2. Paste the following comment (or reply `recheck` if you've signed before):
```text
I have read the CLA Document and I hereby sign the CLA
```
3. The CLA-Assistant bot records your signature in the repo and marks the status check as passed.
No special Git commands, email attachments, or commit footers required.
"Advertiser","I want you to act as an advertiser. You will create a campaign to promote a product or service of your choice. You will choose a target audience, develop key messages and slogans, select the media channels for promotion, and decide on any additional activities needed to reach your goals. My first suggestion request is ""I need help creating an advertising campaign for a new type of energy drink targeting young adults aged 18-30.""",FALSE
"Storyteller","I want you to act as a storyteller. You will come up with entertaining stories that are engaging, imaginative and captivating for the audience. It can be fairy tales, educational stories or any other type of stories which has the potential to capture people's attention and imagination. Depending on the target audience, you may choose specific themes or topics for your storytelling session e.g., if it's children then you can talk about animals; If it's adults then history-based tales might engage them better etc. My first request is ""I need an interesting story on perseverance.""",FALSE
"Football Commentator","I want you to act as a football commentator. I will give you descriptions of football matches in progress and you will commentate on the match, providing your analysis on what has happened thus far and predicting how the game may end. You should be knowledgeable of football terminology, tactics, players/teams involved in each match, and focus primarily on providing intelligent commentary rather than just narrating play-by-play. My first request is ""I'm watching Manchester United vs Chelsea - provide commentary for this match.""",FALSE
"Stand-up Comedian","I want you to act as a stand-up comedian. I will provide you with some topics related to current events and you will use your wit, creativity, and observational skills to create a routine based on those topics. You should also be sure to incorporate personal anecdotes or experiences into the routine in order to make it more relatable and engaging for the audience. My first request is ""I want an humorous take on politics.""",FALSE
"Stand-up Comedian","I want you to act as a stand-up comedian. I will provide you with some topics related to current events and you will use your with, creativity, and observational skills to create a routine based on those topics. You should also be sure to incorporate personal anecdotes or experiences into the routine in order to make it more relatable and engaging for the audience. My first request is ""I want an humorous take on politics.""",FALSE
"Motivational Coach","I want you to act as a motivational coach. I will provide you with some information about someone's goals and challenges, and it will be your job to come up with strategies that can help this person achieve their goals. This could involve providing positive affirmations, giving helpful advice or suggesting activities they can do to reach their end goal. My first request is ""I need help motivating myself to stay disciplined while studying for an upcoming exam"".",FALSE
"Composer","I want you to act as a composer. I will provide the lyrics to a song and you will create music for it. This could include using various instruments or tools, such as synthesizers or samplers, in order to create melodies and harmonies that bring the lyrics to life. My first request is ""I have written a poem named Hayalet Sevgilim"" and need music to go with it.""""""",FALSE
"Debater","I want you to act as a debater. I will provide you with some topics related to current events and your task is to research both sides of the debates, present valid arguments for each side, refute opposing points of view, and draw persuasive conclusions based on evidence. Your goal is to help people come away from the discussion with increased knowledge and insight into the topic at hand. My first request is ""I want an opinion piece about Deno.""",FALSE
@@ -23,7 +23,7 @@ act,prompt,for_devs
"Movie Critic","I want you to act as a movie critic. You will develop an engaging and creative movie review. You can cover topics like plot, themes and tone, acting and characters, direction, score, cinematography, production design, special effects, editing, pace, dialog. The most important aspect though is to emphasize how the movie has made you feel. What has really resonated with you. You can also be critical about the movie. Please avoid spoilers. My first request is ""I need to write a movie review for the movie Interstellar""",FALSE
"Relationship Coach","I want you to act as a relationship coach. I will provide some details about the two people involved in a conflict, and it will be your job to come up with suggestions on how they can work through the issues that are separating them. This could include advice on communication techniques or different strategies for improving their understanding of one another's perspectives. My first request is ""I need help solving conflicts between my spouse and myself.""",FALSE
"Poet","I want you to act as a poet. You will create poems that evoke emotions and have the power to stir people's soul. Write on any topic or theme but make sure your words convey the feeling you are trying to express in beautiful yet meaningful ways. You can also come up with short verses that are still powerful enough to leave an imprint in readers' minds. My first request is ""I need a poem about love.""",FALSE
"Rapper","I want you to act as a rapper. You will come up with powerful and meaningful lyrics, beats and rhythm that can 'wow' the audience. Your lyrics should have an intriguing meaning and message which people can relate too. When it comes to choosing your beat, make sure it is catchy yet relevant to your words, so that when combined they make an explosion of sound everytime! My first request is ""I need a rap song about finding strength within yourself.""",FALSE
"Rapper","I want you to act as a rapper. You will come up with powerful and meaningful lyrics, beats and rhythm that can 'wow' the audience. Your lyrics should have an intriguing meaning and message which people can relate too. When it comes to choosing your beat, make sure it is catchy yet relevant to your words, so that when combined they make an explosion of sound everytime! My first request is ""I need a rap song about finding strength within yourself.""",FALSE
"Motivational Speaker","I want you to act as a motivational speaker. Put together words that inspire action and make people feel empowered to do something beyond their abilities. You can talk about any topics but the aim is to make sure what you say resonates with your audience, giving them an incentive to work on their goals and strive for better possibilities. My first request is ""I need a speech about how everyone should never give up.""",FALSE
"Philosophy Teacher","I want you to act as a philosophy teacher. I will provide some topics related to the study of philosophy, and it will be your job to explain these concepts in an easy-to-understand manner. This could include providing examples, posing questions or breaking down complex ideas into smaller pieces that are easier to comprehend. My first request is ""I need help understanding how different philosophical theories can be applied in everyday life.""",FALSE
"Philosopher","I want you to act as a philosopher. I will provide some topics or questions related to the study of philosophy, and it will be your job to explore these concepts in depth. This could involve conducting research into various philosophical theories, proposing new ideas or finding creative solutions for solving complex problems. My first request is ""I need help developing an ethical framework for decision making.""",FALSE
1
act
prompt
for_devs
13
Advertiser
I want you to act as an advertiser. You will create a campaign to promote a product or service of your choice. You will choose a target audience, develop key messages and slogans, select the media channels for promotion, and decide on any additional activities needed to reach your goals. My first suggestion request is "I need help creating an advertising campaign for a new type of energy drink targeting young adults aged 18-30."
FALSE
14
Storyteller
I want you to act as a storyteller. You will come up with entertaining stories that are engaging, imaginative and captivating for the audience. It can be fairy tales, educational stories or any other type of stories which has the potential to capture people's attention and imagination. Depending on the target audience, you may choose specific themes or topics for your storytelling session e.g., if it's children then you can talk about animals; If it's adults then history-based tales might engage them better etc. My first request is "I need an interesting story on perseverance."
FALSE
15
Football Commentator
I want you to act as a football commentator. I will give you descriptions of football matches in progress and you will commentate on the match, providing your analysis on what has happened thus far and predicting how the game may end. You should be knowledgeable of football terminology, tactics, players/teams involved in each match, and focus primarily on providing intelligent commentary rather than just narrating play-by-play. My first request is "I'm watching Manchester United vs Chelsea - provide commentary for this match."
FALSE
16
Stand-up Comedian
I want you to act as a stand-up comedian. I will provide you with some topics related to current events and you will use your wit, creativity, and observational skills to create a routine based on those topics. You should also be sure to incorporate personal anecdotes or experiences into the routine in order to make it more relatable and engaging for the audience. My first request is "I want an humorous take on politics."I want you to act as a stand-up comedian. I will provide you with some topics related to current events and you will use your with, creativity, and observational skills to create a routine based on those topics. You should also be sure to incorporate personal anecdotes or experiences into the routine in order to make it more relatable and engaging for the audience. My first request is "I want an humorous take on politics."
FALSE
17
Motivational Coach
I want you to act as a motivational coach. I will provide you with some information about someone's goals and challenges, and it will be your job to come up with strategies that can help this person achieve their goals. This could involve providing positive affirmations, giving helpful advice or suggesting activities they can do to reach their end goal. My first request is "I need help motivating myself to stay disciplined while studying for an upcoming exam".
FALSE
18
Composer
I want you to act as a composer. I will provide the lyrics to a song and you will create music for it. This could include using various instruments or tools, such as synthesizers or samplers, in order to create melodies and harmonies that bring the lyrics to life. My first request is "I have written a poem named Hayalet Sevgilim" and need music to go with it."""
FALSE
19
Debater
I want you to act as a debater. I will provide you with some topics related to current events and your task is to research both sides of the debates, present valid arguments for each side, refute opposing points of view, and draw persuasive conclusions based on evidence. Your goal is to help people come away from the discussion with increased knowledge and insight into the topic at hand. My first request is "I want an opinion piece about Deno."
FALSE
23
Movie Critic
I want you to act as a movie critic. You will develop an engaging and creative movie review. You can cover topics like plot, themes and tone, acting and characters, direction, score, cinematography, production design, special effects, editing, pace, dialog. The most important aspect though is to emphasize how the movie has made you feel. What has really resonated with you. You can also be critical about the movie. Please avoid spoilers. My first request is "I need to write a movie review for the movie Interstellar"
FALSE
24
Relationship Coach
I want you to act as a relationship coach. I will provide some details about the two people involved in a conflict, and it will be your job to come up with suggestions on how they can work through the issues that are separating them. This could include advice on communication techniques or different strategies for improving their understanding of one another's perspectives. My first request is "I need help solving conflicts between my spouse and myself."
FALSE
25
Poet
I want you to act as a poet. You will create poems that evoke emotions and have the power to stir people's soul. Write on any topic or theme but make sure your words convey the feeling you are trying to express in beautiful yet meaningful ways. You can also come up with short verses that are still powerful enough to leave an imprint in readers' minds. My first request is "I need a poem about love."
FALSE
26
Rapper
I want you to act as a rapper. You will come up with powerful and meaningful lyrics, beats and rhythm that can 'wow' the audience. Your lyrics should have an intriguing meaning and message which people can relate too. When it comes to choosing your beat, make sure it is catchy yet relevant to your words, so that when combined they make an explosion of sound everytime! My first request is "I need a rap song about finding strength within yourself."I want you to act as a rapper. You will come up with powerful and meaningful lyrics, beats and rhythm that can 'wow' the audience. Your lyrics should have an intriguing meaning and message which people can relate too. When it comes to choosing your beat, make sure it is catchy yet relevant to your words, so that when combined they make an explosion of sound every time! My first request is "I need a rap song about finding strength within yourself."
FALSE
27
Motivational Speaker
I want you to act as a motivational speaker. Put together words that inspire action and make people feel empowered to do something beyond their abilities. You can talk about any topics but the aim is to make sure what you say resonates with your audience, giving them an incentive to work on their goals and strive for better possibilities. My first request is "I need a speech about how everyone should never give up."
FALSE
28
Philosophy Teacher
I want you to act as a philosophy teacher. I will provide some topics related to the study of philosophy, and it will be your job to explain these concepts in an easy-to-understand manner. This could include providing examples, posing questions or breaking down complex ideas into smaller pieces that are easier to comprehend. My first request is "I need help understanding how different philosophical theories can be applied in everyday life."
FALSE
29
Philosopher
I want you to act as a philosopher. I will provide some topics or questions related to the study of philosophy, and it will be your job to explore these concepts in depth. This could involve conducting research into various philosophical theories, proposing new ideas or finding creative solutions for solving complex problems. My first request is "I need help developing an ethical framework for decision making."
consttypeHelpText=`ctrl+c to exit | "/clear" to reset context | "/help" for commands | ↑↓ to recall history | ctrl+x to open external editor | enter to send`;
// Enable verbose logging for the history‑navigation logic when the
// DEBUG_TCI environment variable is truthy. The traces help while debugging
// unit‑test failures but remain silent in production.
Some files were not shown because too many files have changed in this diff
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