## 📝 Review Mode -- Core
This PR introduces the Core implementation for Review mode:
- New op `Op::Review { prompt: String }:` spawns a child review task
with isolated context, a review‑specific system prompt, and a
`Config.review_model`.
- `EnteredReviewMode`: emitted when the child review session starts.
Every event from this point onwards reflects the review session.
- `ExitedReviewMode(Option<ReviewOutputEvent>)`: emitted when the review
finishes or is interrupted, with optional structured findings:
```json
{
"findings": [
{
"title": "<≤ 80 chars, imperative>",
"body": "<valid Markdown explaining *why* this is a problem; cite files/lines/functions>",
"confidence_score": <float 0.0-1.0>,
"priority": <int 0-3>,
"code_location": {
"absolute_file_path": "<file path>",
"line_range": {"start": <int>, "end": <int>}
}
}
],
"overall_correctness": "patch is correct" | "patch is incorrect",
"overall_explanation": "<1-3 sentence explanation justifying the overall_correctness verdict>",
"overall_confidence_score": <float 0.0-1.0>
}
```
## Questions
### Why separate out its own message history?
We want the review thread to match the training of our review models as
much as possible -- that means using a custom prompt, removing user
instructions, and starting a clean chat history.
We also want to make sure the review thread doesn't leak into the parent
thread.
### Why do this as a mode, vs. sub-agents?
1. We want review to be a synchronous task, so it's fine for now to do a
bespoke implementation.
2. We're still unclear about the final structure for sub-agents. We'd
prefer to land this quickly and then refactor into sub-agents without
rushing that implementation.
## Compact feature:
1. Stops the model when the context window become too large
2. Add a user turn, asking for the model to summarize
3. Build a bridge that contains all the previous user message + the
summary. Rendered from a template
4. Start sampling again from a clean conversation with only that bridge
This adds `SetDefaultModel`, which takes `model` and `reasoning_effort`
as optional fields. If set, the field will overwrite what is in the
user's `config.toml`.
This reuses logic that was added to support the `/model` command in the
TUI: https://github.com/openai/codex/pull/2799.
This PR does the following:
* Adds the ability to paste or type an API key.
* Removes the `preferred_auth_method` config option. The last login
method is always persisted in auth.json, so this isn't needed.
* If OPENAI_API_KEY env variable is defined, the value is used to
prepopulate the new UI. The env variable is otherwise ignored by the
CLI.
* Adds a new MCP server entry point "login_api_key" so we can implement
this same API key behavior for the VS Code extension.
<img width="473" height="140" alt="Screenshot 2025-09-04 at 3 51 04 PM"
src="https://github.com/user-attachments/assets/c11bbd5b-8a4d-4d71-90fd-34130460f9d9"
/>
<img width="726" height="254" alt="Screenshot 2025-09-04 at 3 51 32 PM"
src="https://github.com/user-attachments/assets/6cc76b34-309a-4387-acbc-15ee5c756db9"
/>
## Unified PTY-Based Exec Tool
Note: this requires to have this flag in the config:
`use_experimental_unified_exec_tool=true`
- Adds a PTY-backed interactive exec feature (“unified_exec”) with
session reuse via
session_id, bounded output (128 KiB), and timeout clamping (≤ 60 s).
- Protocol: introduces ResponseItem::UnifiedExec { session_id,
arguments, timeout_ms }.
- Tools: exposes unified_exec as a function tool (Responses API);
excluded from Chat
Completions payload while still supported in tool lists.
- Path handling: resolves commands via PATH (or explicit paths), with
UTF‑8/newline‑aware
truncation (truncate_middle).
- Tests: cover command parsing, path resolution, session
persistence/cleanup, multi‑session
isolation, timeouts, and truncation behavior.
The previous config approach had a few issues:
1. It is part of the config but not designed to be used externally
2. It had to be wired through many places (look at the +/- on this PR
3. It wasn't guaranteed to be set consistently everywhere because we
don't have a super well defined way that configs stack. For example, the
extension would configure during newConversation but anything that
happened outside of that (like login) wouldn't get it.
This env var approach is cleaner and also creates one less thing we have
to deal with when coming up with a better holistic story around configs.
One downside is that I removed the unit test testing for the override
because I don't want to deal with setting the global env or spawning
child processes and figuring out how to introspect their originator
header. The new code is sufficiently simple and I tested it e2e that I
feel as if this is still worth it.
When item ids are sent to Responses API it will load them from the
database ignoring the provided values. This adds extra latency.
Not having the mode to store requests also allows us to simplify the
code.
## Breaking change
The `disable_response_storage` configuration option is removed.
We had multiple issues with context size calculation:
1. `initial_prompt_tokens` calculation based on cache size is not
reliable, cache misses might set it to much higher value. For now
hardcoded to a safer constant.
2. Input context size for GPT-5 is 272k (that's where 33% came from).
Fixes.
## Summary
Follow-up to #3056
This PR updates the mcp-server interface for reading the config settings
saved by the user. At risk of introducing _another_ Config struct, I
think it makes sense to avoid tying our protocol to ConfigToml, as its
become a bit unwieldy. GetConfigTomlResponse was a de-facto struct for
this already - better to make it explicit, in my opinion.
This is technically a breaking change of the mcp-server protocol, but
given the previous interface was introduced so recently in #2725, and we
have not yet even started to call it, I propose proceeding with the
breaking change - but am open to preserving the old endpoint.
## Testing
- [x] Added additional integration test coverage
## Summary
It appears that #2108 hit a merge conflict with #2355 - I failed to
notice the path difference when re-reviewing the former. This PR
rectifies that, and consolidates it into the protocol package, in line
with our philosophy of specifying types in one place.
## Testing
- [x] Adds config test for model_verbosity
- Introduce websearch end to complement the begin
- Moves the logic of adding the sebsearch tool to
create_tools_json_for_responses_api
- Making it the client responsibility to toggle the tool on or off
- Other misc in #2371 post commit feedback
- Show the query:
<img width="1392" height="151" alt="image"
src="https://github.com/user-attachments/assets/8457f1a6-f851-44cf-bcca-0d4fe460ce89"
/>
This PR fixes two edge cases in managing burst paste (mainly on power
shell).
Bugs:
- Needs an event key after paste to render the pasted items
> ChatComposer::flush_paste_burst_if_due() flushes on timeout. Called:
> - Pre-render in App on TuiEvent::Draw.
> - Via a delayed frame
>
BottomPane::request_redraw_in(ChatComposer::recommended_paste_flush_delay()).
- Parses two key events separately before starting parsing burst paste
> When threshold is crossed, pull preceding burst chars out of the
textarea and prepend to paste_burst_buffer, then keep buffering.
- Integrates with #2567 to bring image pasting to windows.
- added `uninlined_format_args` to `[workspace.lints.clippy]` in the
`Cargo.toml` for the workspace
- ran `cargo clippy --tests --fix`
- ran `just fmt`
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>
## Summary
When resolving our current directory as a project, we want to be a
little bit more clever:
1. If we're in a sub-directory of a git repo, resolve our project
against the root of the git repo
2. If we're in a git worktree, resolve the project against the root of
the git repo
## Testing
- [x] Added unit tests
- [x] Confirmed locally with a git worktree (the one i was using for
this feature)
## Summary
GPT-5 introduced the concept of [custom
tools](https://platform.openai.com/docs/guides/function-calling#custom-tools),
which allow the model to send a raw string result back, simplifying
json-escape issues. We are migrating gpt-5 to use this by default.
However, gpt-oss models do not support custom tools, only normal
functions. So we keep both tool definitions, and provide whichever one
the model family supports.
## Testing
- [x] Tested locally with various models
- [x] Unit tests pass
**Summary**
- Adds `model_verbosity` config (values: low, medium, high).
- Sends `text.verbosity` only for GPT‑5 family models via the Responses
API.
- Updates docs and adds serialization tests.
**Motivation**
- GPT‑5 introduces a verbosity control to steer output length/detail
without pro
mpt surgery.
- Exposing it as a config knob keeps prompts stable and makes behavior
explicit
and repeatable.
**Changes**
- Config:
- Added `Verbosity` enum (low|medium|high).
- Added optional `model_verbosity` to `ConfigToml`, `Config`, and
`ConfigProfi
le`.
- Request wiring:
- Extended `ResponsesApiRequest` with optional `text` object.
- Populates `text.verbosity` only when model family is `gpt-5`; omitted
otherw
ise.
- Tests:
- Verifies `text.verbosity` serializes when set and is omitted when not
set.
- Docs:
- Added “GPT‑5 Verbosity” section in `codex-rs/README.md`.
- Added `model_verbosity` section to `codex-rs/config.md`.
**Usage**
- In `~/.codex/config.toml`:
- `model = "gpt-5"`
- `model_verbosity = "low"` (or `"medium"` default, `"high"`)
- CLI override example:
- `codex -c model="gpt-5" -c model_verbosity="high"`
**API Impact**
- Requests to GPT‑5 via Responses API include: `text: { verbosity:
"low|medium|h
igh" }` when configured.
- For legacy models or Chat Completions providers, `text` is omitted.
**Backward Compatibility**
- Default behavior unchanged when `model_verbosity` is not set (server
default “
medium”).
**Testing**
- Added unit tests for serialization/omission of `text.verbosity`.
- Ran `cargo fmt` and `cargo test --all-features` (all green).
**Docs**
- `README.md`: new “GPT‑5 Verbosity” note under Config with example.
- `config.md`: new `model_verbosity` section.
**Out of Scope**
- No changes to temperature/top_p or other GPT‑5 parameters.
- No changes to Chat Completions wiring.
**Risks / Notes**
- If OpenAI changes the wire shape for verbosity, we may need to update
`Respons
esApiRequest`.
- Behavior gated to `gpt-5` model family to avoid unexpected effects
elsewhere.
**Checklist**
- [x] Code gated to GPT‑5 family only
- [x] Docs updated (`README.md`, `config.md`)
- [x] Tests added and passing
- [x] Formatting applied
Release note: Add `model_verbosity` config to control GPT‑5 output verbosity via the Responses API (low|medium|high).
Codex created this PR from the following prompt:
> upgrade this entire repo to Rust 1.89. Note that this requires
updating codex-rs/rust-toolchain.toml as well as the workflows in
.github/. Make sure that things are "clippy clean" as this change will
likely uncover new Clippy errors. `just fmt` and `cargo clippy --tests`
are sufficient to check for correctness
Note this modifies a lot of lines because it folds nested `if`
statements using `&&`.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/2465).
* #2467
* __->__ #2465
Motivation: we have users who uses their API key although they want to
use ChatGPT account. We want to give them the chance to always login
with their account.
This PR displays login options when the user is not signed in with
ChatGPT. Even if you have set an OpenAI API key as an environment
variable, you will still be prompted to log in with ChatGPT.
We’ve also added a new flag, `always_use_api_key_signing` false by
default, which ensures you are never asked to log in with ChatGPT and
always defaults to using your API key.
https://github.com/user-attachments/assets/b61ebfa9-3c5e-4ab7-bf94-395c23a0e0af
After ChatGPT sign in:
https://github.com/user-attachments/assets/d58b366b-c46a-428f-a22f-2ac230f991c0
The existing `wire_format.rs` should share more types with the
`codex-protocol` crate (like `AskForApproval` instead of maintaining a
parallel `CodexToolCallApprovalPolicy` enum), so this PR moves
`wire_format.rs` into `codex-protocol`, renaming it as
`mcp-protocol.rs`. We also de-dupe types, where appropriate.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/2423).
* #2424
* __->__ #2423
## Summary
We've been seeing a number of issues and reports with our synthetic
`apply_patch` tool, e.g. #802. Let's make this a real tool - in my
anecdotal testing, it's critical for GPT-OSS models, but I'd like to
make it the standard across GPT-5 and codex models as well.
## Testing
- [x] Tested locally
- [x] Integration test
This PR:
* Added the clippy.toml to configure allowable expect / unwrap usage in
tests
* Removed as many expect/allow lines as possible from tests
* moved a bunch of allows to expects where possible
Note: in integration tests, non `#[test]` helper functions are not
covered by this so we had to leave a few lingering `expect(expect_used`
checks around
## Summary
In collaboration with @gpeal: upgrade the onboarding flow, and persist
user settings.
---------
Co-authored-by: Gabriel Peal <gabriel@openai.com>
Replaces the `include_default_writable_roots` option on
`sandbox_workspace_write` (that defaulted to `true`, which was slightly
weird/annoying) with `exclude_tmpdir_env_var`, which defaults to
`false`.
Though perhaps more importantly `/tmp` is now enabled by default as part
of `sandbox_mode = "workspace-write"`, though `exclude_slash_tmp =
false` can be used to disable this.
## Summary
- Prioritize provider-specific API keys over default Codex auth when
building requests
- Add test to ensure provider env var auth overrides default auth
## Testing
- `just fmt`
- `just fix` *(fails: `let` expressions in this position are unstable)*
- `cargo test --all-features` *(fails: `let` expressions in this
position are unstable)*
------
https://chatgpt.com/codex/tasks/task_i_68926a104f7483208f2c8fd36763e0e3
The docs and code do not match. It turns out the docs are "right" in
they are what we have been meaning to support, so this PR updates the
code:
ae88b69b09/README.md (L298-L302)
Support for `instructions.md` is a holdover from the TypeScript CLI, so
we are just going to drop support for it altogether rather than maintain
it in perpetuity.
This adds support for easily running Codex backed by a local Ollama
instance running our new open source models. See
https://github.com/openai/gpt-oss for details.
If you pass in `--oss` you'll be prompted to install/launch ollama, and
it will automatically download the 20b model and attempt to use it.
We'll likely want to expand this with some options later to make the
experience smoother for users who can't run the 20b or want to run the
120b.
Co-authored-by: Michael Bolin <mbolin@openai.com>
https://github.com/openai/codex/pull/1835 has some messed up history.
This adds support for streaming chat completions, which is useful for ollama. We should probably take a very skeptical eye to the code introduced in this PR.
---------
Co-authored-by: Ahmed Ibrahim <aibrahim@openai.com>
To date, we have a number of hardcoded OpenAI model slug checks spread
throughout the codebase, which makes it hard to audit the various
special cases for each model. To mitigate this issue, this PR introduces
the idea of a `ModelFamily` that has fields to represent the existing
special cases, such as `supports_reasoning_summaries` and
`uses_local_shell_tool`.
There is a `find_family_for_model()` function that maps the raw model
slug to a `ModelFamily`. This function hardcodes all the knowledge about
the special attributes for each model. This PR then replaces the
hardcoded model name checks with checks against a `ModelFamily`.
Note `ModelFamily` is now available as `Config::model_family`. We should
ultimately remove `Config::model` in favor of
`Config::model_family::slug`.
