Make ModelClient a session-scoped object.
Move state that is session level onto the client, and make state that is
per-turn explicit on corresponding methods.
Stop taking a huge Config object, instead only pass in values that are
actually needed.
---------
Co-authored-by: Josh McKinney <joshka@openai.com>
adds basic git context to the session prefix so the model can anchor git
actions and be a bit more version-aware. structured it in a
multiroot-friendly shape even though we only have one root today
Summary
- expose websocket telemetry hooks through the responses client so
request durations and event processing can be reported
- record websocket request/event metrics and emit runtime telemetry
events that the history UI now surfaces
- improve tests to cover websocket telemetry reporting and guard runtime
summary updates
<img width="824" height="79" alt="Screenshot 2026-01-31 at 5 28 12 PM"
src="https://github.com/user-attachments/assets/ea9a7965-d8b4-4e3c-a984-ef4fdc44c81d"
/>
This enables a new use case where `codex app-server` is embedded into a
parent application that will directly own the user's ChatGPT auth
lifecycle, which means it owns the user’s auth tokens and refreshes it
when necessary. The parent application would just want a way to pass in
the auth tokens for codex to use directly.
The idea is that we are introducing a new "auth mode" currently only
exposed via app server: **`chatgptAuthTokens`** which consist of the
`id_token` (stores account metadata) and `access_token` (the bearer
token used directly for backend API calls). These auth tokens are only
stored in-memory. This new mode is in addition to the existing `apiKey`
and `chatgpt` auth modes.
This PR reuses the shape of our existing app-server account APIs as much
as possible:
- Update `account/login/start` with a new `chatgptAuthTokens` variant,
which will allow the client to pass in the tokens and have codex
app-server use them directly. Upon success, the server emits
`account/login/completed` and `account/updated` notifications.
- A new server->client request called
`account/chatgptAuthTokens/refresh` which the server can use whenever
the access token previously passed in has expired and it needs a new one
from the parent application.
I leveraged the core 401 retry loop which typically triggers auth token
refreshes automatically, but made it pluggable:
- **chatgpt** mode refreshes internally, as usual.
- **chatgptAuthTokens** mode calls the client via
`account/chatgptAuthTokens/refresh`, the client responds with updated
tokens, codex updates its in-memory auth, then retries. This RPC has a
10s timeout and handles JSON-RPC errors from the client.
Also some additional things:
- chatgpt logins are blocked while external auth is active (have to log
out first. typically clients will pick one OR the other, not support
both)
- `account/logout` clears external auth in memory
- Ensures that if `forced_chatgpt_workspace_id` is set via the user's
config, we respect it in both:
- `account/login/start` with `chatgptAuthTokens` (returns a JSON-RPC
error back to the client)
- `account/chatgptAuthTokens/refresh` (fails the turn, and on next
request app-server will send another `account/chatgptAuthTokens/refresh`
request to the client).
web_search can now be updated per-turn, for things like changes to
sandbox policy.
`SandboxPolicy::DangerFullAccess` now sets web_search to `live`, and the
default is still `cached`.
Added integration tests.
We've recently standardized a [feature maturity
model](https://developers.openai.com/codex/feature-maturity) that we're
using in our docs and support forums to communicate expectations to
users. This PR updates the internal stage names and descriptions to
match.
This change involves a simple internal rename and updates to a few
user-visible strings. No functional change.
## 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
- capture the header from SSE/WS handshakes, store it per
ModelClientSession using `Oncelock`, echo it on turn-scoped requests,
and add SSE+WS integration tests for within-turn persistence +
cross-turn reset.
- keep `x-codex-turn-state` sticky within a user turn to maintain
routing continuity for retries/tool follow-ups.
moving `web_search` rollout serverside, so need a way to explicitly
disable search + signal eligibility from the client.
- Add `x‑oai‑web‑search‑eligible` header that signifies whether the
request can have web search.
- Only attach the `web_search` tool when the resolved `WebSearchMode` is
`Live` or `Cached`.
Historically we started with a CodexAuth that knew how to refresh it's
own tokens and then added AuthManager that did a different kind of
refresh (re-reading from disk).
I don't think it makes sense for both `CodexAuth` and `AuthManager` to
be mutable and contain behaviors.
Move all refresh logic into `AuthManager` and keep `CodexAuth` as a data
object.
Add metrics capabilities to Codex. The `README.md` is up to date.
This will not be merged with the metrics before this PR of course:
https://github.com/openai/codex/pull/8350
Adds a new feature
`enable_request_compression` that will compress using zstd requests to
the codex-backend. Currently only enabled for codex-backend so only enabled for openai providers when using chatgpt::auth even when the feature is enabled
Added a new info log line too for evaluating the compression ratio and
overhead off compressing before requesting. You can enable with
`RUST_LOG=$RUST_LOG,codex_client::transport=info`
```
2026-01-06T00:09:48.272113Z INFO codex_client::transport: Compressed request body with zstd pre_compression_bytes=28914 post_compression_bytes=11485 compression_duration_ms=0
```
- Merge ModelFamily into ModelInfo
- Remove logic for adding instructions to apply patch
- Add compaction limit and visible context window to `ModelInfo`
# 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.
- Make Config.model optional and centralize default-selection logic in
ModelsManager, including a default_model helper (with
codex-auto-balanced when available) so sessions now carry an explicit
chosen model separate from the base config.
- Resolve `model` once in `core` and `tui` from config. Then store the
state of it on other structs.
- Move refreshing models to be before resolving the default model
This is a step towards removing the need to know `model` when
constructing config. We firstly don't need to know `model_info` and just
respect if the user has already set it. Next step, we don't need to know
`model` unless the user explicitly set it in `config.toml`
This PR moves `ModelsFamily` to `openai_models`. It also propagates
`ModelsManager` to session services and use it to drive model family. We
also make `derive_default_model_family` private because it's a step
towards what we want: one place that gives model configuration.
This is a second step at having one source of truth for models
information and config: `ModelsManager`.
Next steps would be to remove `ModelsFamily` from config. That's massive
because it's being used in 41 occasions mostly pre launching `codex`.
Also, we need to make `find_family_for_model` private. It's also big
because it's being used in 21 occasions ~ all tests.
- Introduce `openai_models` in `/core`
- Move `PRESETS` under it
- Move `ModelPreset`, `ModelUpgrade`, `ReasoningEffortPreset`,
`ReasoningEffortPreset`, and `ReasoningEffortPreset` to `protocol`
- Introduce `Op::ListModels` and `EventMsg::AvailableModels`
Next steps:
- migrate `app-server` and `tui` to use the introduced Operation
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
- 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)
core event to app server event mapping:
1. `codex/event/reasoning_content_delta` ->
`item/reasoning/summaryTextDelta`.
2. `codex/event/reasoning_raw_content_delta` ->
`item/reasoning/textDelta`
3. `codex/event/agent_message_content_delta` →
`item/agentMessage/delta`.
4. `codex/event/agent_reasoning_section_break` ->
`item/reasoning/summaryPartAdded`.
Also added a change in core to pass down content index, summary index
and item id from events.
Tested with the `git checkout owen/app_server_test_client && cargo run
-p codex-app-server-test-client -- send-message-v2 "hello"` and verified
that new events are emitted correctly.
This PR makes an "insufficient quota" error fatal so we don't attempt to
retry it multiple times in the agent loop.
We have multiple bug reports from users about intermittent retry
behaviors, and this could explain some of them. With this change, we'll
eliminate the retries and surface a clear error message.
The PR is a nearly identical copy of [this
PR](https://github.com/openai/codex/pull/4837) contributed by
@abimaelmartell. The original PR has gone stale. Rather than wait for
the contributor to resolve merge conflicts, I wanted to get this change
in.
