- This PR is to make it on path for truncating by tokens. This path will
be initially used by unified exec and context manager (responsible for
MCP calls mainly).
- We are exposing new config `calls_output_max_tokens`
- Use `tokens` as the main budget unit but truncate based on the model
family by Introducing `TruncationPolicy`.
- Introduce `truncate_text` as a router for truncation based on the
mode.
In next PRs:
- remove truncate_with_line_bytes_budget
- Add the ability to the model to override the token budget.
- Local-shell tool responses were always tagged as
`ExecCommandSource::UserShell` because handler would call
`run_exec_like` with `is_user_shell_cmd` set to true.
- Treat `ToolPayload::LocalShell` the same as other model generated
shell tool calls by deleting `is_user_shell_cmd` from `run_exec_like`
(since actual user shell commands follow a separate code path)
## Summary
Enables shell_command for windows users, and starts adding some basic
command parsing here, to at least remove powershell prefixes. We'll
follow this up with command parsing but I wanted to land this change
separately with some basic UX.
**NOTE**: This implementation parses bash and powershell on both
platforms. In theory this is possible, since you can use git bash on
windows or powershell on linux. In practice, this may not be worth the
complexity of supporting, so I don't feel strongly about the current
approach vs. platform-specific branching.
## Testing
- [x] Added a bunch of tests
- [x] Ran on both windows and os x
## Summary
Similar to #6545, this PR updates the shell_serialization test suite to
cover the various `shell` tool invocations we have. Note that this does
not cover unified_exec, which has its own suite of tests. This should
provide some test coverage for when we eventually consolidate
serialization logic.
## Testing
- [x] These are tests
## Summary
- update documentation, example configs, and automation defaults to
reference gpt-5.1 / gpt-5.1-codex
- bump the CLI and core configuration defaults, model presets, and error
messaging to the new models while keeping the model-family/tool coverage
for legacy slugs
- refresh tests, fixtures, and TUI snapshots so they expect the upgraded
defaults
## Testing
- `cargo test -p codex-core
config::tests::test_precedence_fixture_with_gpt5_profile`
------
[Codex
Task](https://chatgpt.com/codex/tasks/task_i_6916c5b3c2b08321ace04ee38604fc6b)
- enabling execpolicy2 parser to parse multiple policy files to build a
combined `Policy` (useful if codex detects many `.codexpolicy` files)
- adding functionality to `Policy` to allow evaluation of multiple cmds
at once (useful when we have chained commands)
This PR adds the API V2 version of the command‑execution approval flow
for the shell tool.
This PR wires the new RPC (`item/commandExecution/requestApproval`, V2
only) and related events (`item/started`, `item/completed`, and
`item/commandExecution/delta`, 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.
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 additional fields to
`EventMsg::ExecCommandEndEvent` to capture the command's input so that
app-server can statelessly transform these events to a
`ThreadItem::CommandExecution` item for the `item/completed` event.
Once we stabilize the API and it's complete enough for our partners, we
can work on migrating the core to be aware of command execution items as
a first-class concept.
**Note**: We'll need followup work to make sure these APIs work for the
unified exec tool, but will wait til that's stable and landed before
doing a pass on app-server.
Example payloads below:
```
{
"method": "item/started",
"params": {
"item": {
"aggregatedOutput": null,
"command": "/bin/zsh -lc 'touch /tmp/should-trigger-approval'",
"cwd": "/Users/owen/repos/codex/codex-rs",
"durationMs": null,
"exitCode": null,
"id": "call_lNWWsbXl1e47qNaYjFRs0dyU",
"parsedCmd": [
{
"cmd": "touch /tmp/should-trigger-approval",
"type": "unknown"
}
],
"status": "inProgress",
"type": "commandExecution"
}
}
}
```
```
{
"id": 0,
"method": "item/commandExecution/requestApproval",
"params": {
"itemId": "call_lNWWsbXl1e47qNaYjFRs0dyU",
"parsedCmd": [
{
"cmd": "touch /tmp/should-trigger-approval",
"type": "unknown"
}
],
"reason": "Need to create file in /tmp which is outside workspace sandbox",
"risk": null,
"threadId": "019a93e8-0a52-7fe3-9808-b6bc40c0989a",
"turnId": "1"
}
}
```
```
{
"id": 0,
"result": {
"acceptSettings": {
"forSession": false
},
"decision": "accept"
}
}
```
```
{
"params": {
"item": {
"aggregatedOutput": null,
"command": "/bin/zsh -lc 'touch /tmp/should-trigger-approval'",
"cwd": "/Users/owen/repos/codex/codex-rs",
"durationMs": 224,
"exitCode": 0,
"id": "call_lNWWsbXl1e47qNaYjFRs0dyU",
"parsedCmd": [
{
"cmd": "touch /tmp/should-trigger-approval",
"type": "unknown"
}
],
"status": "completed",
"type": "commandExecution"
}
}
}
```
The `cap_sid` file contains the IDs of the two custom SIDs that the
Windows sandbox creates/manages to implement read-only and
workspace-write sandbox policies.
It previously lived in `<cwd>/.codex` which means that the sandbox could
write to it, which could degrade the efficacy of the sandbox. This
change moves it to `~/.codex/` (or wherever `CODEX_HOME` points to) so
that it is outside the workspace.
This PR fixes keyboard handling for the Right Alt (aka "Alt-Gr") key on
Windows. This key appears on keyboards in Central and Eastern Europe.
Codex has effectively never worked for Windows users in these regions
because the code didn't properly handle this key, which is used for
typing common symbols like `\` and `@`.
A few days ago, I merged a [community-authored
PR](https://github.com/openai/codex/pull/6720) that supplied a partial
fix for this issue. Upon closer inspect, that PR was 1) too broad (not
scoped to Windows only) and 2) incomplete (didn't fix all relevant code
paths, so paste was still broken).
This improvement is based on another [community-provided
PR](https://github.com/openai/codex/pull/3241) by @marektomas-cz. He
submitted it back in September and later closed it because it didn't
receive any attention.
This fix addresses the following bugs: #5922, #3046, #3092, #3519,
#5684, #5843.
`--disable shell_tool` disables the built-in shell tool. This is useful
for MCP-only operation.
---------
Co-authored-by: Michael Bolin <mbolin@openai.com>
## Overview
Adds LM Studio OSS support. Closes#1883
### Changes
This PR enhances the behavior of `--oss` flag to support LM Studio as a
provider. Additionally, it introduces a new flag`--local-provider` which
can take in `lmstudio` or `ollama` as values if the user wants to
explicitly choose which one to use.
If no provider is specified `codex --oss` will auto-select the provider
based on whichever is running.
#### Additional enhancements
The default can be set using `oss-provider` in config like:
```
oss_provider = "lmstudio"
```
For non-interactive users, they will need to either provide the provider
as an arg or have it in their `config.toml`
### Notes
For best performance, [set the default context
length](https://lmstudio.ai/docs/app/advanced/per-model) for gpt-oss to
the maximum your machine can support
---------
Co-authored-by: Matt Clayton <matt@lmstudio.ai>
Co-authored-by: Eric Traut <etraut@openai.com>
We're running into quite a bit of drag maintaining this test, since
every time we add fields to an EventMsg that happened to be dumped into
the `binary-size-log.jsonl` fixture, this test starts to fail. The fix
is usually to either manually update the `binary-size-log.jsonl` fixture
file, or update the `upgrade_event_payload_for_tests` function to map
the data in that file into something workable.
Eason says it's fine to delete this test, so let's just delete it
## Summary
- Introduces the `codex-execpolicy2` crate.
- This PR covers only the prefix-rule subset of the planned execpolicy
v2 language; a richer language will follow.
## Policy
- Policy language centers on `prefix_rule(pattern=[...], decision?,
match?, not_match?)`, where `pattern` is an ordered list of tokens; any
element may be a list to denote alternatives. `decision` defaults to
`allow`; valid values are `allow`, `prompt`, and `forbidden`. `match` /
`not_match` hold example commands that are tokenized and validated at
load time (think of these as unit tests).
## Policy shapes
- Prefix rules use Starlark syntax:
```starlark
prefix_rule(
pattern = ["cmd", ["alt1", "alt2"]], # ordered tokens; list entries denote alternatives
decision = "prompt", # allow | prompt | forbidden; defaults to allow
match = [["cmd", "alt1"]], # examples that must match this rule (enforced at compile time)
not_match = [["cmd", "oops"]], # examples that must not match this rule (enforced at compile time)
)
```
## Response shapes
- Match:
```json
{
"match": {
"decision": "allow|prompt|forbidden",
"matchedRules": [
{
"prefixRuleMatch": {
"matchedPrefix": ["<token>", "..."],
"decision": "allow|prompt|forbidden"
}
}
]
}
}
```
- No match:
```json
"noMatch"
```
- `matchedRules` lists every rule whose prefix matched the command;
`matchedPrefix` is the exact prefix that matched.
- The effective `decision` is the strictest severity across all matches
(`forbidden` > `prompt` > `allow`).
---------
Co-authored-by: Michael Bolin <mbolin@openai.com>
kevin zhao