This is a stopgap solution, but today, we are seeing the client get
flooded with events. Since we already truncate the output we send to the
model, it feels reasonable to limit how many deltas we send to the
client.
## Summary
Adds a GetConfig request to the MCP Protocol, so MCP clients can
evaluate the resolved config.toml settings which the harness is using.
## Testing
- [x] Added an end to end test of the endpoint
Prevented panics when deleting placeholders near multibyte characters by
clamping the cursor to a valid boundary and using get-based slicing
Added a regression test to ensure backspacing after multibyte text
leaves placeholders intact without crashing
---------
Co-authored-by: Ahmed Ibrahim <aibrahim@openai.com>
This fixes a bug where if you ran /diff while at turn was running,
transcript lines would be added to the end of the diff view. Also,
refactor to make this kind of issue less likely in future.
This pr addresses the fix for
https://github.com/openai/codex/issues/2713
### Changes:
- Added key handler for `Alt+Ctrl+H` → `delete_backward_word()`
- Added test coverage in `delete_backward_word_alt_keys()` that verifies
both:
- Standard `Alt+Backspace` binding continues to work
- New `Alt+Ctrl+H` binding works correctly for backward word deletion
### Testing:
The test ensures both key combinations produce identical behavior:
- Delete the previous word from "hello world" → "hello "
- Cursor positioned correctly after deletion
### Backward Compatibility:
This change is backward compatible - existing `Alt+Backspace`
functionality remains unchanged while adding support for the
terminal-specific `Alt+Ctrl+H` variant
Use emoji variation selector (VS16) for the keyboard icon so it
consistently renders as emoji (⌨️) rather than text (⌨) across
terminals.
Touches TUI command rendering for unknown parsed commands. No behavior
change beyond display.
### What this PR does
This PR introduces a new public method,
remove_conversation(conversation_id: Uuid), to the ConversationManager.
This allows consumers of the codex-core library to manually remove a
conversation from the manager's in-memory storage.
### Why this change is needed
I am currently adapting the Codex client to run as a long-lived server
application. In this server environment, ConversationManager instances
persist for extended periods, and new conversations are created for each
incoming user request.
The current implementation of ConversationManager stores all created
conversations in a HashMap indefinitely, with no mechanism for removal.
This leads to unbounded memory growth in a server context, as every new
conversation permanently occupies memory.
While an automatic TTL-based cleanup mechanism could be one solution, a
simpler, more direct remove_conversation method provides the necessary
control for my use case. It allows my server application to explicitly
manage the lifecycle of conversations, such as cleaning them up after a
request is fully processed or after a period of inactivity is detected
at the application level.
This change provides a minimal, non-intrusive way to address the memory
management issue for server-like applications built on top of
codex-core, giving developers the flexibility to implement their own
cleanup logic.
Signed-off-by: M4n5ter <m4n5terrr@gmail.com>
Co-authored-by: Michael Bolin <mbolin@openai.com>
There are some design issues with this action, so until we work them
out, we'll remove this code from the repository to avoid folks from
taking a dependency on it.
The CLI supports config settings `stream_max_retries` and
`request_max_retries` that allow users to override the default retry
counts (4 and 5, respectively). However, there's currently no cap placed
on these values. In theory, a user could configure an effectively
infinite retry count which could hammer the server. This PR adds a
reasonable cap (currently 100) to both of these values.
This PR improves the error message presented to the user when logged in
with ChatGPT and a rate-limit error occurs. In particular, it provides
the user with information about when the rate limit will be reset. It
removes older code that attempted to do the same but relied on parsing
of error messages that are not generated by the ChatGPT endpoint. The
new code uses newly-added error fields.
Esc and Ctrl+C while a task is running should do the same thing. There
were some cases where pressing Esc would leave a "stuck" widget in the
history; this fixes that and cleans up the logic so there's just one
path for interrupting the task. Also clean up some subtly mishandled key
events (e.g. Ctrl+D would quit the app while an approval modal was
showing if the textarea was empty).
---------
Co-authored-by: Ahmed Ibrahim <aibrahim@openai.com>
This PR fixes a bug in the token refresh logic. Token refresh is
performed in a retry loop so if we receive a 401 error, we refresh the
token, then we go around the loop again and reissue the fetch with a
fresh token. The bug is that we're not using the updated token on the
second and subsequent times through the loop. The result is that we'll
try to refresh the token a few more times until we hit the retry limit
(default of 4). The 401 error is then passed back up to the caller.
Subsequent calls will use the refreshed token, so the problem clears
itself up.
The fix is straightforward — make sure we use the updated auth
information each time through the retry loop.
In this PR:
- [x] Add support for dragging / copying image files into chat.
- [x] Don't remove image placeholders when submitting.
- [x] Add tests.
Works for:
- Image Files
- Dragging MacOS Screenshots (Terminal, iTerm)
Todos:
- [ ] In some terminals (VSCode, WIndows Powershell, and remote
SSH-ing), copy-pasting a file streams the escaped filepath as individual
key events rather than a single Paste event. We'll need to have a
function (in a separate PR) for detecting these paste events.
Esc should have other functionalities when it's not used in a
backtracking situation. i.e. to cancel pop up menu when selecting
model/approvals or to interrupt an active turn.
## Summary
These tests were getting a bit unwieldy, and they're starting to become
load-bearing. Let's clean them up, and get them working solidly so we
can easily expand this harness with new tests.
## Test Plan
- [x] Tests continue to pass
I noticed that when running `/status` on Windows, I saw something like:
```
Path: ~/src\codex
```
so now it should be:
```
Path: ~\src\codex
```
Admittedly, `~` is understood by PowerShell but not on Windows, in
general, but it's much less verbose than `%USERPROFILE%`.
**Context**
When running `/compact`, `drain_to_completed` would throw an error if
`token_usage` was `None` in `ResponseEvent::Completed`. This made the
command fail even though everything else had succeeded.
**What changed**
- Instead of erroring, we now just check `if let Some(token_usage)`
before sending the event.
- If it’s missing, we skip it and move on.
**Why**
This makes `AgentTask::compact()` behave in the same way as
`AgentTask::spawn()`, which also doesn’t error out when `token_usage`
isn’t available. Keeps things consistent and avoids unnecessary
failures.
**Fixes**
Closes#2417
---------
Co-authored-by: Ahmed Ibrahim <aibrahim@openai.com>
The `SessionManager` in `exec_command` owns a number of
`ExecCommandSession` objects where `ExecCommandSession` has a
non-trivial implementation of `Drop`, so we want to be able to drop an
individual `SessionManager` to help ensure things get cleaned up in a
timely fashion. To that end, we should have one `SessionManager` per
session rather than one global one for the lifetime of the CLI process.
`ToolsConfig::new()` taking a large number of boolean params was hard to
manage and it finally bit us (see
https://github.com/openai/codex/pull/2660). This changes
`ToolsConfig::new()` so that it takes a struct (and also reduces the
visibility of some members, where possible).
Fixes https://github.com/openai/codex/issues/2610
This PR sorts the tools in `get_openai_tools` by name to ensure a
consistent MCP tool order.
Currently, MCP servers are stored in a HashMap, which does not guarantee
ordering. As a result, the tool order changes across turns, effectively
breaking prompt caching in multi-turn sessions.
An alternative solution would be to replace the HashMap with an ordered
structure, but that would require a much larger code change. Given that
it is unrealistic to have so many MCP tools that sorting would cause
performance issues, this lightweight fix is chosen instead.
By ensuring deterministic tool order, this change should significantly
improve cache hit rates and prevent users from hitting usage limits too
quickly. (For reference, my own sessions last week reached the limit
unusually fast, with cache hit rates falling below 1%.)
## Result
After this fix, sessions with MCP servers now show caching behavior
almost identical to sessions without MCP servers.
Without MCP | With MCP
:-------------------------:|:-------------------------:
<img width="1368" height="1634" alt="image"
src="https://github.com/user-attachments/assets/26edab45-7be8-4d6a-b471-558016615fc8"
/> | <img width="1356" height="1632" alt="image"
src="https://github.com/user-attachments/assets/5f3634e0-3888-420b-9aaf-deefd9397b40"
/>
Bumps [whoami](https://github.com/ardaku/whoami) from 1.6.0 to 1.6.1.
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Historically, Codex CLI has treated `apply_patch` (and its sometimes
misspelling, `applypatch`) as a "virtual CLI," intercepting it when it
appears as the first arg to `command` for the `"container.exec",
`"shell"`, or `"local_shell"` tools.
This approach has a known limitation where if, say, the model created a
Python script that runs `apply_patch` and then tried to run the Python
script, we have no insight as to what the model is trying to do and the
Python Script would fail because `apply_patch` was never really on the
`PATH`.
One way to solve this problem is to require users to install an
`apply_patch` executable alongside the `codex` executable (or at least
put it someplace where Codex can discover it). Though to keep Codex CLI
as a standalone executable, we exploit "the arg0 trick" where we create
a temporary directory with an entry named `apply_patch` and prepend that
directory to the `PATH` for the duration of the invocation of Codex.
- On UNIX, `apply_patch` is a symlink to `codex`, which now changes its
behavior to behave like `apply_patch` if arg0 is `apply_patch` (or
`applypatch`)
- On Windows, `apply_patch.bat` is a batch script that runs `codex
--codex-run-as-apply-patch %*`, as Codex also changes its behavior if
the first argument is `--codex-run-as-apply-patch`.
## Summary
We're seeing some issues in the freeform tool - let's disable by default
until it stabilizes.
## Testing
- [x] Ran locally, confirmed codex-cli could make edits
this dramatically improves time to run `cargo test -p codex-core` (~25x
speedup).
before:
```
cargo test -p codex-core 35.96s user 68.63s system 19% cpu 8:49.80 total
```
after:
```
cargo test -p codex-core 5.51s user 8.16s system 63% cpu 21.407 total
```
both tests measured "hot", i.e. on a 2nd run with no filesystem changes,
to exclude compile times.
approach inspired by [Delete Cargo Integration
Tests](https://matklad.github.io/2021/02/27/delete-cargo-integration-tests.html),
we move all test cases in tests/ into a single suite in order to have a
single binary, as there is significant overhead for each test binary
executed, and because test execution is only parallelized with a single
binary.
Adds web_search tool, enabling the model to use Responses API web_search
tool.
- Disabled by default, enabled by --search flag
- When --search is passed, exposes web_search_request function tool to
the model, which triggers user approval. When approved, the model can
use the web_search tool for the remainder of the turn
<img width="1033" height="294" alt="image"
src="https://github.com/user-attachments/assets/62ac6563-b946-465c-ba5d-9325af28b28f"
/>
---------
Co-authored-by: easong-openai <easong@openai.com>
We want to send an aggregated output of stderr and stdout so we don't
have to aggregate it stderr+stdout as we lose order sometimes.
---------
Co-authored-by: Gabriel Peal <gpeal@users.noreply.github.com>
