`process_exec_tool_call()` was taking `SandboxType` as a param, but in
practice, the only place it was constructed was in
`codex_message_processor.rs` where it was derived from the other
`sandbox_policy` param, so this PR inlines the logic that decides the
`SandboxType` into `process_exec_tool_call()`.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/7122).
* #7112
* __->__ #7122
Previously, we were running into an issue where we would run the `shell`
tool call with a timeout of 10s, but it fired an elicitation asking for
user approval, the time the user took to respond to the elicitation was
counted agains the 10s timeout, so the `shell` tool call would fail with
a timeout error unless the user is very fast!
This PR addresses this issue by introducing a "stopwatch" abstraction
that is used to manage the timeout. The idea is:
- `Stopwatch::new()` is called with the _real_ timeout of the `shell`
tool call.
- `process_exec_tool_call()` is called with the `Cancellation` variant
of `ExecExpiration` because it should not manage its own timeout in this
case
- the `Stopwatch` expiration is wired up to the `cancel_rx` passed to
`process_exec_tool_call()`
- when an elicitation for the `shell` tool call is received, the
`Stopwatch` pauses
- because it is possible for multiple elicitations to arrive
concurrently, it keeps track of the number of "active pauses" and does
not resume until that counter goes down to zero
I verified that I can test the MCP server using
`@modelcontextprotocol/inspector` and specify `git status` as the
`command` with a timeout of 500ms and that the elicitation pops up and I
have all the time in the world to respond whereas previous to this PR,
that would not have been possible.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/6973).
* #7005
* __->__ #6973
* #6972
This updates `ExecParams` so that instead of taking `timeout_ms:
Option<u64>`, it now takes a more general cancellation mechanism,
`ExecExpiration`, which is an enum that includes a
`Cancellation(tokio_util::sync::CancellationToken)` variant.
If the cancellation token is fired, then `process_exec_tool_call()`
returns in the same way as if a timeout was exceeded.
This is necessary so that in #6973, we can manage the timeout logic
external to the `process_exec_tool_call()` because we want to "suspend"
the timeout when an elicitation from a human user is pending.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/6972).
* #7005
* #6973
* __->__ #6972
- Use /bin/sh instead of /bin/bash on FreeBSD/OpenBSD in the process
group timeout test to avoid command-not-found failures.
- Accept /usr/local/bin/bash as a valid SHELL path to match common
FreeBSD installations.
- Switch the shell serialization duration test to /bin/sh for improved
portability across Unix platforms.
With this change, `cargo test -p codex-core --lib` runs and passes on
FreeBSD.
second attempt to fix this test after
https://github.com/openai/codex/pull/6884. I think this flakiness is
happening because yield_time is too small for a 10,000 step loop in
python.
adding execpolicycheck tool onto codex cli
this is useful for validating policies (can be multiple) against
commands.
it will also surface errors in policy syntax:
<img width="1150" height="281" alt="Screenshot 2025-11-19 at 12 46
21 PM"
src="https://github.com/user-attachments/assets/8f99b403-564c-4172-acc9-6574a8d13dc3"
/>
this PR also changes output format when there's no match in the CLI.
instead of returning the raw string `noMatch`, we return
`{"noMatch":{}}`
this PR is a rewrite of: https://github.com/openai/codex/pull/6932 (due
to the numerous merge conflicts present in the original PR)
---------
Co-authored-by: Michael Bolin <mbolin@openai.com>
setting user shell timeout to an unreasonably high value since there
isn't an easy way to have a command run without timeouts
currently, user shell commands timeout is 10 seconds
## 🐛 Problem
Users running commands with non-ASCII characters (like Russian text
"пример") in Windows/WSL environments experience garbled text in
VSCode's shell preview window, with Unicode replacement characters (�)
appearing instead of the actual text.
**Issue**: https://github.com/openai/codex/issues/6178
## 🔧 Root Cause
The issue was in `StreamOutput<Vec<u8>>::from_utf8_lossy()` method in
`codex-rs/core/src/exec.rs`, which used `String::from_utf8_lossy()` to
convert shell output bytes to strings. This function immediately
replaces any invalid UTF-8 byte sequences with replacement characters,
without attempting to decode using other common encodings.
In Windows/WSL environments, shell output often uses encodings like:
- Windows-1252 (common Windows encoding)
- Latin-1/ISO-8859-1 (extended ASCII)
## 🛠️ Solution
Replaced the simple `String::from_utf8_lossy()` call with intelligent
encoding detection via a new `bytes_to_string_smart()` function that
tries multiple encoding strategies:
1. **UTF-8** (fast path for valid UTF-8)
2. **Windows-1252** (handles Windows-specific characters in 0x80-0x9F
range)
3. **Latin-1** (fallback for extended ASCII)
4. **Lossy UTF-8** (final fallback, same as before)
## 📁 Changes
### New Files
- `codex-rs/core/src/text_encoding.rs` - Smart encoding detection module
- `codex-rs/core/tests/suite/text_encoding_fix.rs` - Integration tests
### Modified Files
- `codex-rs/core/src/lib.rs` - Added text_encoding module
- `codex-rs/core/src/exec.rs` - Updated StreamOutput::from_utf8_lossy()
- `codex-rs/core/tests/suite/mod.rs` - Registered new test module
## ✅ Testing
- **5 unit tests** covering UTF-8, Windows-1252, Latin-1, and fallback
scenarios
- **2 integration tests** simulating the exact Issue #6178 scenario
- **Demonstrates improvement** over the previous
`String::from_utf8_lossy()` approach
All tests pass:
```bash
cargo test -p codex-core text_encoding
cargo test -p codex-core test_shell_output_encoding_issue_6178
```
## 🎯 Impact
- ✅ **Eliminates garbled text** in VSCode shell preview for non-ASCII
content
- ✅ **Supports Windows/WSL environments** with proper encoding detection
- ✅ **Zero performance impact** for UTF-8 text (fast path)
- ✅ **Backward compatible** - UTF-8 content works exactly as before
- ✅ **Handles edge cases** with robust fallback mechanism
## 🧪 Test Scenarios
The fix has been tested with:
- Russian text ("пример")
- Windows-1252 quotation marks (""test")
- Latin-1 accented characters ("café")
- Mixed encoding content
- Invalid byte sequences (graceful fallback)
## 📋 Checklist
- [X] Addresses the reported issue
- [X] Includes comprehensive tests
- [X] Maintains backward compatibility
- [X] Follows project coding conventions
- [X] No breaking changes
---------
Co-authored-by: Josh McKinney <joshka@openai.com>
This PR adds support for a new feature flag `tui.animations`. By
default, the TUI uses animations in its welcome screen, "working"
spinners, and "shimmer" effects. This animations can interfere with
screen readers, so it's good to provide a way to disable them.
This change is inspired by [a
PR](https://github.com/openai/codex/pull/4014) contributed by @Orinks.
That PR has faltered a bit, but I think the core idea is sound. This
version incorporates feedback from @aibrahim-oai. In particular:
1. It uses a feature flag (`tui.animations`) rather than the unqualified
CLI key `no-animations`. Feature flags are the preferred way to expose
boolean switches. They are also exposed via CLI command switches.
2. It includes more complete documentation.
3. It disables a few animations that the other PR omitted.
Thread through an `exit_notify` tokio `Notify` through to the
`UnifiedExecSession` so that we can return early if the command
terminates before `yield_time_ms`.
As Codex review correctly pointed out below 🙌 we also need a
`exit_signaled` flag so that commands which finish before we start
waiting can also exit early.
Since the default `yield_time_ms` is now 10s, this means that we don't
have to wait 10s for trivial commands like ls, sed, etc (which are the
majority of agent commands 😅)
---------
Co-authored-by: jif-oai <jif@openai.com>
This PR adds the API V2 version of the apply_patch approval flow, which
centers around `ThreadItem::FileChange`.
This PR wires the new RPC (`item/fileChange/requestApproval`, V2 only)
and related events (`item/started`, `item/completed` for
`ThreadItem::FileChange`, which are emitted in both V1 and V2) through
the app-server
protocol. The new approval RPC is only sent when the user initiates a
turn with the new `turn/start` API so we don't break backwards
compatibility with VSCE.
Similar to https://github.com/openai/codex/pull/6758, the approach I
took was to make as few changes to the Codex core as possible,
leveraging existing `EventMsg` core events, and translating those in
app-server. I did have to add a few additional fields to
`EventMsg::PatchApplyBegin` and `EventMsg::PatchApplyEnd`, but those
were fairly lightweight.
However, the `EventMsg`s emitted by core are the following:
```
1) Auto-approved (no request for approval)
- EventMsg::PatchApplyBegin
- EventMsg::PatchApplyEnd
2) Approved by user
- EventMsg::ApplyPatchApprovalRequest
- EventMsg::PatchApplyBegin
- EventMsg::PatchApplyEnd
3) Declined by user
- EventMsg::ApplyPatchApprovalRequest
- EventMsg::PatchApplyBegin
- EventMsg::PatchApplyEnd
```
For a request triggering an approval, this would result in:
```
item/fileChange/requestApproval
item/started
item/completed
```
which is different from the `ThreadItem::CommandExecution` flow
introduced in https://github.com/openai/codex/pull/6758, which does the
below and is preferable:
```
item/started
item/commandExecution/requestApproval
item/completed
```
To fix this, we leverage `TurnSummaryStore` on codex_message_processor
to store a little bit of state, allowing us to fire `item/started` and
`item/fileChange/requestApproval` whenever we receive the underlying
`EventMsg::ApplyPatchApprovalRequest`, and no-oping when we receive the
`EventMsg::PatchApplyBegin` later.
This is much less invasive than modifying the order of EventMsg within
core (I tried).
The resulting payloads:
```
{
"method": "item/started",
"params": {
"item": {
"changes": [
{
"diff": "Hello from Codex!\n",
"kind": "add",
"path": "/Users/owen/repos/codex/codex-rs/APPROVAL_DEMO.txt"
}
],
"id": "call_Nxnwj7B3YXigfV6Mwh03d686",
"status": "inProgress",
"type": "fileChange"
}
}
}
```
```
{
"id": 0,
"method": "item/fileChange/requestApproval",
"params": {
"grantRoot": null,
"itemId": "call_Nxnwj7B3YXigfV6Mwh03d686",
"reason": null,
"threadId": "019a9e11-8295-7883-a283-779e06502c6f",
"turnId": "1"
}
}
```
```
{
"id": 0,
"result": {
"decision": "accept"
}
}
```
```
{
"method": "item/completed",
"params": {
"item": {
"changes": [
{
"diff": "Hello from Codex!\n",
"kind": "add",
"path": "/Users/owen/repos/codex/codex-rs/APPROVAL_DEMO.txt"
}
],
"id": "call_Nxnwj7B3YXigfV6Mwh03d686",
"status": "completed",
"type": "fileChange"
}
}
}
```
This reverts commit c2ec477d93.
# External (non-OpenAI) Pull Request Requirements
Before opening this Pull Request, please read the dedicated
"Contributing" markdown file or your PR may be closed:
https://github.com/openai/codex/blob/main/docs/contributing.md
If your PR conforms to our contribution guidelines, replace this text
with a detailed and high quality description of your changes.
Include a link to a bug report or enhancement request.
This PR threads execpolicy2 into codex-core.
activated via feature flag: exec_policy (on by default)
reads and parses all .codexpolicy files in `codex_home/codex`
refactored tool runtime API to integrate execpolicy logic
---------
Co-authored-by: Michael Bolin <mbolin@openai.com>
Expand the rate-limit cache/TUI: store credit snapshots alongside
primary and secondary windows, render “Credits” when the backend reports
they exist (unlimited vs rounded integer balances)
## Summary
Setting `/approvals` before the start of a conversation was not updating
the environment_context for a conversation. Not sure exactly when this
problem was introduced, but this should reduce model confusion
dramatically.
## Testing
- [x] Added unit test to reproduce bug, confirmed fix with update
- [x] Tested locally
zhao-oaiandGitHub
Michael BolinandGitHub
Jeremy RoseandGitHub
pakrym-oaiandGitHub
iceweasel-oaiandGitHub
Ahmed IbrahimandGitHub
jif-oaiandGitHub
YorlingandGitHub
Eric TrautandGitHub
Celia ChenandGitHub
Xiao-Yong JinandGitHub
Owen LinandGitHub
Dylan HurdandGitHub