### Summary
- Parse all `web_search` tool actions (`search`, `find_in_page`,
`open_page`).
- Previously we only parsed + displayed `search`, which made the TUI
appear to pause when the other actions were being used.
- Show in progress `web_search` calls as `Searching the web`
- Previously we only showed completed tool calls
<img width="308" height="149" alt="image"
src="https://github.com/user-attachments/assets/90a4e8ff-b06a-48ff-a282-b57b31121845"
/>
### Tests
Added + updated tests, tested locally
### Follow ups
Update VSCode extension to display these as well
### Summary
Add `isOther` to question object from request_user_input tool input and
remove `other` option from the tool prompt to better handle tool input.
## Summary
Add dynamic tool injection to thread startup in API v2, wire dynamic
tool calls through the app server to clients, and plumb responses back
into the model tool pipeline.
### Flow (high level)
- Thread start injects `dynamic_tools` into the model tool list for that
thread (validation is done here).
- When the model emits a tool call for one of those names, core raises a
`DynamicToolCallRequest` event.
- The app server forwards it to the client as `item/tool/call`, waits
for the client’s response, then submits a `DynamicToolResponse` back to
core.
- Core turns that into a `function_call_output` in the next model
request so the model can continue.
### What changed
- Added dynamic tool specs to v2 thread start params and protocol types;
introduced `item/tool/call` (request/response) for dynamic tool
execution.
- Core now registers dynamic tool specs at request time and routes those
calls via a new dynamic tool handler.
- App server validates tool names/schemas, forwards dynamic tool call
requests to clients, and publishes tool outputs back into the session.
- Integration tests
## Summary
Adds /personality selector in the TUI, which leverages the new core
interface in #9644
Notes:
- We are doing some of our own state management for model_info loading
here, but not sure if that's ideal. open to opinions on simpler
approach, but would like to avoid blocking on a larger refactor
- Right now, the `/personality` selector just hides when the model
doesn't support it. we can update this behavior down the line
## Testing
- [x] Tested locally
- [x] Added snapshot tests
Keep an unmasked base collaboration mode and apply the active mask on
demand. Simplify the TUI mask helpers and update tests/docs to match the
mask contract.
## What
Fix bash command parsing to accept double-quoted strings that contain
literal newlines so execpolicy can match allow rules.
## Why
Allow rules like [git, commit] should still match when commit messages
include a newline in a quoted argument; the parser currently rejects
these strings and falls back to the outer shell invocation.
## How
- Validate double-quoted strings by ensuring all named children are
string_content and then stripping the outer quotes from the raw node
text so embedded newlines are preserved.
- Reuse the helper for concatenated arguments.
- Ensure large SI suffix formatting uses the caller-provided locale
formatter for grouping.
- Add coverage for newline-containing quoted arguments.
Fixes#9541.
## Tests
- cargo test -p codex-core
- just fix -p codex-core
- cargo test -p codex-protocol
- just fix -p codex-protocol
- cargo test --all-features
## Summary
Support updating Personality mid-Thread via UserTurn/OverwriteTurn. This
is explicitly unused by the clients so far, to simplify PRs - app-server
and tui implementations will be follow-ups.
## Testing
- [x] added integration tests
## Summary
#9555 is the start of a rename, so I'm starting to standardize here.
Sets up `model_instructions` templating with a strongly-typed object for
injecting a personality block into the model instructions.
## Testing
- [x] Added tests
- [x] Ran locally
This PR adds support for chained (layered) config.toml file merging for
clients that use the app server interface. This feature already exists
for the TUI, but it does not work for GUI clients.
It does the following:
* Changes code paths for new thread, resume thread, and fork thread to
use the effective config based on the cwd.
* Updates the `config/read` API to accept an optional `cwd` parameter.
If specified, the API returns the effective config based on that cwd
path. Also optionally includes all layers including project config
files. If cwd is not specified, the API falls back on its older behavior
where it considers only the global (non-project) config files when
computing the effective config.
The changes in codex_message_processor.rs look deceptively large. They
mostly just involve moving existing blocks of code to a later point in
some functions so it can use the cwd to calculate the config.
This PR builds upon #9509 and should be reviewed and merged after that
PR.
Tested:
* Verified change with (dependent, as-yet-uncommitted) changes to IDE
Extension and confirmed correct behavior
The full fix requires additional changes in the IDE Extension code base,
but they depend on this PR.
## Summary
- add optional `collaboration_mode` to `TurnContextItem` in rollouts
- persist the current collaboration mode when recording turn context
(sampling + compaction)
## Rationale
We already persist turn context data for resume logic. Capturing
collaboration mode in the rollout gives us the mode context for each
turn, enabling follow‑up work to diff mode instructions correctly on
resume.
## Changes
- protocol: add optional `collaboration_mode` field to `TurnContextItem`
- core: persist collaboration mode alongside other turn context settings
in rollouts
Summary
- Preserve `text_elements` through custom prompt argument parsing and
expansion (named and numeric placeholders).
- Translate text element ranges through Shlex parsing using sentinel
substitution, and rehydrate text + element ranges per arg.
- Drop image attachments when their placeholder does not survive prompt
expansion, keeping attachments consistent with rendered elements.
- Mirror changes in TUI2 and expand tests for prompt parsing/expansion
edge cases.
Tests
- placeholders with spaces as single tokens (positional + key=value,
quoted + unquoted),
- prompt expansion with image placeholders,
- large paste + image arg combinations,
- unused image arg dropped after expansion.
## Summary
- Make `TextElement` placeholders private and add a text-backed accessor
to avoid assuming `Some`.
- Since they are optional in the protocol, we want to make sure any
accessors properly handle the None case (getting the placeholder using
the byte range in the text)
- Preserve placeholders during protocol/app-server conversions using the
accessor fallback.
- Update TUI composer/remap logic and tests to use the new
constructor/accessor.
## Summary
This PR consolidates base_instructions onto SessionMeta /
SessionConfiguration, so we ensure `base_instructions` is set once per
session and should be (mostly) immutable, unless:
- overridden by config on resume / fork
- sub-agent tasks, like review or collab
In a future PR, we should convert all references to `base_instructions`
to consistently used the typed struct, so it's less likely that we put
other strings there. See #9423. However, this PR is already quite
complex, so I'm deferring that to a follow-up.
## Testing
- [x] Added a resume test to assert that instructions are preserved. In
particular, `resume_switches_models_preserves_base_instructions` fails
against main.
Existing test coverage thats assert base instructions are preserved
across multiple requests in a session:
- Manual compact keeps baseline instructions:
core/tests/suite/compact.rs:199
- Auto-compact keeps baseline instructions:
core/tests/suite/compact.rs:1142
- Prompt caching reuses the same instructions across two requests:
core/tests/suite/prompt_caching.rs:150 and
core/tests/suite/prompt_caching.rs:157
- Prompt caching with explicit expected string across two requests:
core/tests/suite/prompt_caching.rs:213 and
core/tests/suite/prompt_caching.rs:222
- Resume with model switch keeps original instructions:
core/tests/suite/resume.rs:136
- Compact/resume/fork uses request 0 instructions for later expected
payloads: core/tests/suite/compact_resume_fork.rs:215
- `tui/` and `tui2/` submit `Op::UserTurn` and own full turn context
(cwd/approval/sandbox/model/etc.).
- `Op::UserInput` is documented as legacy in `codex-protocol` (doc-only;
no `#[deprecated]` to avoid `-D warnings` fallout).
- Remove obsolete `#[allow(deprecated)]` and the unused `ConversationId`
alias/re-export.
# 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.
### Description
- Remove the now-unused `instructions` field from the session metadata
to simplify SessionMeta and stop propagating transient instruction text
through the rollout recorder API. This was only saving
user_instructions, and was never being read.
- Stop passing user instructions into the rollout writer at session
creation so the rollout header only contains canonical session metadata.
### Testing
- Ran `just fmt` which completed successfully.
- Ran `just fix -p codex-protocol`, `just fix -p codex-core`, `just fix
-p codex-app-server`, `just fix -p codex-tui`, and `just fix -p
codex-tui2` which completed (Clippy fixes applied) as part of
verification.
- Ran `cargo test -p codex-protocol` which passed (28 tests).
- Ran `cargo test -p codex-core` which showed failures in a small set of
tests (not caused by the protocol type change directly):
`default_client::tests::test_create_client_sets_default_headers`,
several `models_manager::manager::tests::refresh_available_models_*`,
and `shell_snapshot::tests::linux_sh_snapshot_includes_sections` (these
tests failed in this CI run).
- Ran `cargo test -p codex-app-server` which reported several failing
integration tests (including
`suite::codex_message_processor_flow::test_codex_jsonrpc_conversation_flow`,
`suite::output_schema::send_user_turn_*`, and
`suite::user_agent::get_user_agent_returns_current_codex_user_agent`).
- `cargo test -p codex-tui` and `cargo test -p codex-tui2` were
attempted but aborted due to disk space exhaustion (`No space left on
device`).
------
[Codex
Task](https://chatgpt.com/codex/tasks/task_i_696bd8ce632483228d298cf07c7eb41c)
- Merge `model` and `reasoning_effort` under collaboration modes.
- Add additional instructions for custom collaboration mode
- Default to Custom to not change behavior
Summary:
- Add forked_from to SessionMeta/SessionConfiguredEvent and persist it
for forked sessions.
- Surface forked_from in /status for tui + tui2 and add snapshots.
The second part of breaking up PR
https://github.com/openai/codex/pull/9116
Summary:
- Add `TextElement` / `ByteRange` to protocol user inputs and user
message events with defaults.
- Thread `text_elements` through app-server v1/v2 request handling and
history rebuild.
- Preserve UI metadata only in user input/events (not `ContentItem`)
while keeping local image attachments in user events for rehydration.
Details:
- Protocol: `UserInput::Text` carries `text_elements`;
`UserMessageEvent` carries `text_elements` + `local_images`.
Serialization includes empty vectors for backward compatibility.
- app-server-protocol: v1 defines `V1TextElement` / `V1ByteRange` in
camelCase with conversions; v2 uses its own camelCase wrapper.
- app-server: v1/v2 input mapping includes `text_elements`; thread
history rebuilds include them.
- Core: user event emission preserves UI metadata while model history
stays clean; history replay round-trips the metadata.
We’re introducing a new SKILL.toml to hold skill metadata so Codex can
deliver a richer Skills experience.
Initial focus is the interface block:
```
[interface]
display_name = "Optional user-facing name"
short_description = "Optional user-facing description"
icon_small = "./assets/small-400px.png"
icon_large = "./assets/large-logo.svg"
brand_color = "#3B82F6"
default_prompt = "Optional surrounding prompt to use the skill with"
```
All fields are exposed via the app server API.
display_name and short_description are consumed by the TUI.
Next step would be to clean Model Upgrade in model presets
---------
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: aibrahim-oai <219906144+aibrahim-oai@users.noreply.github.com>
### What
Add `WebSearchMode` enum (disabled, cached live, defaults to cached) to
config + V2 protocol. This enum takes precedence over legacy flags:
`web_search_cached`, `web_search_request`, and `tools.web_search`.
Keep `--search` as live.
### Tests
Added tests
Emit the following events around the collab tools. On the `app-server`
this will be under `item/started` and `item/completed`
```
#[derive(Debug, Clone, Deserialize, Serialize, PartialEq, JsonSchema, TS)]
pub struct CollabAgentSpawnBeginEvent {
/// Identifier for the collab tool call.
pub call_id: String,
/// Thread ID of the sender.
pub sender_thread_id: ThreadId,
/// Initial prompt sent to the agent. Can be empty to prevent CoT leaking at the
/// beginning.
pub prompt: String,
}
#[derive(Debug, Clone, Deserialize, Serialize, PartialEq, JsonSchema, TS)]
pub struct CollabAgentSpawnEndEvent {
/// Identifier for the collab tool call.
pub call_id: String,
/// Thread ID of the sender.
pub sender_thread_id: ThreadId,
/// Thread ID of the newly spawned agent, if it was created.
pub new_thread_id: Option<ThreadId>,
/// Initial prompt sent to the agent. Can be empty to prevent CoT leaking at the
/// beginning.
pub prompt: String,
/// Last known status of the new agent reported to the sender agent.
pub status: AgentStatus,
}
#[derive(Debug, Clone, Deserialize, Serialize, PartialEq, JsonSchema, TS)]
pub struct CollabAgentInteractionBeginEvent {
/// Identifier for the collab tool call.
pub call_id: String,
/// Thread ID of the sender.
pub sender_thread_id: ThreadId,
/// Thread ID of the receiver.
pub receiver_thread_id: ThreadId,
/// Prompt sent from the sender to the receiver. Can be empty to prevent CoT
/// leaking at the beginning.
pub prompt: String,
}
#[derive(Debug, Clone, Deserialize, Serialize, PartialEq, JsonSchema, TS)]
pub struct CollabAgentInteractionEndEvent {
/// Identifier for the collab tool call.
pub call_id: String,
/// Thread ID of the sender.
pub sender_thread_id: ThreadId,
/// Thread ID of the receiver.
pub receiver_thread_id: ThreadId,
/// Prompt sent from the sender to the receiver. Can be empty to prevent CoT
/// leaking at the beginning.
pub prompt: String,
/// Last known status of the receiver agent reported to the sender agent.
pub status: AgentStatus,
}
#[derive(Debug, Clone, Deserialize, Serialize, PartialEq, JsonSchema, TS)]
pub struct CollabWaitingBeginEvent {
/// Thread ID of the sender.
pub sender_thread_id: ThreadId,
/// Thread ID of the receiver.
pub receiver_thread_id: ThreadId,
/// ID of the waiting call.
pub call_id: String,
}
#[derive(Debug, Clone, Deserialize, Serialize, PartialEq, JsonSchema, TS)]
pub struct CollabWaitingEndEvent {
/// Thread ID of the sender.
pub sender_thread_id: ThreadId,
/// Thread ID of the receiver.
pub receiver_thread_id: ThreadId,
/// ID of the waiting call.
pub call_id: String,
/// Last known status of the receiver agent reported to the sender agent.
pub status: AgentStatus,
}
#[derive(Debug, Clone, Deserialize, Serialize, PartialEq, JsonSchema, TS)]
pub struct CollabCloseBeginEvent {
/// Identifier for the collab tool call.
pub call_id: String,
/// Thread ID of the sender.
pub sender_thread_id: ThreadId,
/// Thread ID of the receiver.
pub receiver_thread_id: ThreadId,
}
#[derive(Debug, Clone, Deserialize, Serialize, PartialEq, JsonSchema, TS)]
pub struct CollabCloseEndEvent {
/// Identifier for the collab tool call.
pub call_id: String,
/// Thread ID of the sender.
pub sender_thread_id: ThreadId,
/// Thread ID of the receiver.
pub receiver_thread_id: ThreadId,
/// Last known status of the receiver agent reported to the sender agent before
/// the close.
pub status: AgentStatus,
}
```
### Motivation
- Landlock alone cannot prevent writes to sensitive in-repo files like
`.git/` when the repo root is writable, so explicit mount restrictions
are required for those paths.
- The sandbox must set up any mounts before calling Landlock so Landlock
can still be applied afterwards and the two mechanisms compose
correctly.
### Description
- Add a new `linux-sandbox` helper `apply_read_only_mounts` in
`linux-sandbox/src/mounts.rs` that: unshares namespaces, maps uids/gids
when required, makes mounts private, bind-mounts targets, and remounts
them read-only.
- Wire the mount step into the sandbox flow by calling
`apply_read_only_mounts(...)` before network/seccomp and before applying
Landlock rules in `linux-sandbox/src/landlock.rs`.
Have only the following Methods:
- `list_models`: getting current available models
- `try_list_models`: sync version no refresh for tui use
- `get_default_model`: get the default model (should be tightened to
core and received on session configuration)
- `get_model_info`: get `ModelInfo` for a specific model (should be
tightened to core but used in tests)
- `refresh_if_new_etag`: trigger refresh on different etags
Also move the cache to its own struct
- Add a single builder for developer permissions messaging that accepts
SandboxPolicy and approval policy. This builder now drives the developer
“permissions” message that’s injected at session start and any time
sandbox/approval settings change.
- Trim EnvironmentContext to only include cwd, writable roots, and
shell; removed sandbox/approval/network duplication and adjusted XML
serialization and tests accordingly.
Follow-up: adding a config value to replace the developer permissions
message for custom sandboxes.
### Summary
* Added `mcpServer/refresh` command to inform app servers and active
threads to refresh mcpServer on next turn event.
* Added `pending_mcp_server_refresh_config` to codex core so that if the
value is populated, we reinitialize the mcp server manager on the thread
level.
* The config is updated on `mcpServer/refresh` command which we iterate
through threads and provide with the latest config value after last
write.
Add implementation for the `wait` tool.
For this we consider all status different from `PendingInit` and
`Running` as terminal. The `wait` tool call will return either after a
given timeout or when the tool reaches a non-terminal status.
A few points to note:
* The usage of a channel is preferred to prevent some races (just
looping on `get_status()` could "miss" a terminal status)
* The order of operations is very important, we need to first subscribe
and then check the last known status to prevent race conditions
* If the channel gets dropped, we return an error on purpose
Agent wouldn't "see" attached images and would instead try to use the
view_file tool:
<img width="1516" height="504" alt="image"
src="https://github.com/user-attachments/assets/68a705bb-f962-4fc1-9087-e932a6859b12"
/>
In this PR, we wrap image content items in XML tags with the name of
each image (now just a numbered name like `[Image #1]`), so that the
model can understand inline image references (based on name). We also
put the image content items above the user message which the model seems
to prefer (maybe it's more used to definitions being before references).
We also tweak the view_file tool description which seemed to help a bit
Results on a simple eval set of images:
Before
<img width="980" height="310" alt="image"
src="https://github.com/user-attachments/assets/ba838651-2565-4684-a12e-81a36641bf86"
/>
After
<img width="918" height="322" alt="image"
src="https://github.com/user-attachments/assets/10a81951-7ee6-415e-a27e-e7a3fd0aee6f"
/>
```json
[
{
"id": "single_describe",
"prompt": "Describe the attached image in one sentence.",
"images": ["image_a.png"]
},
{
"id": "single_color",
"prompt": "What is the dominant color in the image? Answer with a single color word.",
"images": ["image_b.png"]
},
{
"id": "orientation_check",
"prompt": "Is the image portrait or landscape? Answer in one sentence.",
"images": ["image_c.png"]
},
{
"id": "detail_request",
"prompt": "Look closely at the image and call out any small details you notice.",
"images": ["image_d.png"]
},
{
"id": "two_images_compare",
"prompt": "I attached two images. Are they the same or different? Briefly explain.",
"images": ["image_a.png", "image_b.png"]
},
{
"id": "two_images_captions",
"prompt": "Provide a short caption for each image (Image 1, Image 2).",
"images": ["image_c.png", "image_d.png"]
},
{
"id": "multi_image_rank",
"prompt": "Rank the attached images from most colorful to least colorful.",
"images": ["image_a.png", "image_b.png", "image_c.png"]
},
{
"id": "multi_image_choice",
"prompt": "Which image looks more vibrant? Answer with 'Image 1' or 'Image 2'.",
"images": ["image_b.png", "image_d.png"]
}
]
```
This PR configures Codex CLI so it can be built with
[Bazel](https://bazel.build) in addition to Cargo. The `.bazelrc`
includes configuration so that remote builds can be done using
[BuildBuddy](https://www.buildbuddy.io).
If you are familiar with Bazel, things should work as you expect, e.g.,
run `bazel test //... --keep-going` to run all the tests in the repo,
but we have also added some new aliases in the `justfile` for
convenience:
- `just bazel-test` to run tests locally
- `just bazel-remote-test` to run tests remotely (currently, the remote
build is for x86_64 Linux regardless of your host platform). Note we are
currently seeing the following test failures in the remote build, so we
still need to figure out what is happening here:
```
failures:
suite::compact::manual_compact_twice_preserves_latest_user_messages
suite::compact_resume_fork::compact_resume_after_second_compaction_preserves_history
suite::compact_resume_fork::compact_resume_and_fork_preserve_model_history_view
```
- `just build-for-release` to build release binaries for all
platforms/architectures remotely
To setup remote execution:
- [Create a buildbuddy account](https://app.buildbuddy.io/) (OpenAI
employees should also request org access at
https://openai.buildbuddy.io/join/ with their `@openai.com` email
address.)
- [Copy your API key](https://app.buildbuddy.io/docs/setup/) to
`~/.bazelrc` (add the line `build
--remote_header=x-buildbuddy-api-key=YOUR_KEY`)
- Use `--config=remote` in your `bazel` invocations (or add `common
--config=remote` to your `~/.bazelrc`, or use the `just` commands)
## CI
In terms of CI, this PR introduces `.github/workflows/bazel.yml`, which
uses Bazel to run the tests _locally_ on Mac and Linux GitHub runners
(we are working on supporting Windows, but that is not ready yet). Note
that the failures we are seeing in `just bazel-remote-test` do not occur
on these GitHub CI jobs, so everything in `.github/workflows/bazel.yml`
is green right now.
The `bazel.yml` uses extra config in `.github/workflows/ci.bazelrc` so
that macOS CI jobs build _remotely_ on Linux hosts (using the
`docker://docker.io/mbolin491/codex-bazel` Docker image declared in the
root `BUILD.bazel`) using cross-compilation to build the macOS
artifacts. Then these artifacts are downloaded locally to GitHub's macOS
runner so the tests can be executed natively. This is the relevant
config that enables this:
```
common:macos --config=remote
common:macos --strategy=remote
common:macos --strategy=TestRunner=darwin-sandbox,local
```
Because of the remote caching benefits we get from BuildBuddy, these new
CI jobs can be extremely fast! For example, consider these two jobs that
ran all the tests on Linux x86_64:
- Bazel 1m37s
https://github.com/openai/codex/actions/runs/20861063212/job/59940545209?pr=8875
- Cargo 9m20s
https://github.com/openai/codex/actions/runs/20861063192/job/59940559592?pr=8875
For now, we will continue to run both the Bazel and Cargo jobs for PRs,
but once we add support for Windows and running Clippy, we should be
able to cutover to using Bazel exclusively for PRs, which should still
speed things up considerably. We will probably continue to run the Cargo
jobs post-merge for commits that land on `main` as a sanity check.
Release builds will also continue to be done by Cargo for now.
Earlier attempt at this PR: https://github.com/openai/codex/pull/8832
Earlier attempt to add support for Buck2, now abandoned:
https://github.com/openai/codex/pull/8504
---------
Co-authored-by: David Zbarsky <dzbarsky@gmail.com>
Co-authored-by: Michael Bolin <mbolin@openai.com>
Fixes#2558
Codex uses alternate screen mode (CSI 1049) which, per xterm spec,
doesn't support scrollback. Zellij follows this strictly, so users can't
scroll back through output.
**Changes:**
- Add `tui.alternate_screen` config: `auto` (default), `always`, `never`
- Add `--no-alt-screen` CLI flag
- Auto-detect Zellij and skip alt screen (uses existing `ZELLIJ` env var
detection)
**Usage:**
```bash
# CLI flag
codex --no-alt-screen
# Or in config.toml
[tui]
alternate_screen = "never"
```
With default `auto` mode, Zellij users get working scrollback without
any config changes.
---------
Co-authored-by: Josh McKinney <joshka@openai.com>
