Remove the redundant inline compaction request trace and clarify that streamed server-side compaction rebuilds replacement history on response.completed from the checkpoint snapshot.
Co-authored-by: Codex <noreply@openai.com>
Move normal auto-compaction onto inline Responses API compaction behind a feature flag, keep the legacy path for manual and compatibility cases, and add observability plus integration coverage.
Co-authored-by: Codex <noreply@openai.com>
Pass more params to /compact. This should give us parity with the
/responses endpoint to improve caching.
I'm torn about the MCP await. Blocking will give us parity but it seems
like we explicitly don't block on MCPs. Happy either way
## Summary
This is a purely mechanical refactor of `OtelManager` ->
`SessionTelemetry` to better convey what the struct is doing. No
behavior change.
## Why
`OtelManager` ended up sounding much broader than what this type
actually does. It doesn't manage OTEL globally; it's the session-scoped
telemetry surface for emitting log/trace events and recording metrics
with consistent session metadata (`app_version`, `model`, `slug`,
`originator`, etc.).
`SessionTelemetry` is a more accurate name, and updating the call sites
makes that boundary a lot easier to follow.
## Validation
- `just fmt`
- `cargo test -p codex-otel`
- `cargo test -p codex-core`
## Summary
Add original-resolution support for `view_image` behind the
under-development `view_image_original_resolution` feature flag.
When the flag is enabled and the target model is `gpt-5.3-codex` or
newer, `view_image` now preserves original PNG/JPEG/WebP bytes and sends
`detail: "original"` to the Responses API instead of using the legacy
resize/compress path.
## What changed
- Added `view_image_original_resolution` as an under-development feature
flag.
- Added `ImageDetail` to the protocol models and support for serializing
`detail: "original"` on tool-returned images.
- Added `PromptImageMode::Original` to `codex-utils-image`.
- Preserves original PNG/JPEG/WebP bytes.
- Keeps legacy behavior for the resize path.
- Updated `view_image` to:
- use the shared `local_image_content_items_with_label_number(...)`
helper in both code paths
- select original-resolution mode only when:
- the feature flag is enabled, and
- the model slug parses as `gpt-5.3-codex` or newer
- Kept local user image attachments on the existing resize path; this
change is specific to `view_image`.
- Updated history/image accounting so only `detail: "original"` images
use the docs-based GPT-5 image cost calculation; legacy images still use
the old fixed estimate.
- Added JS REPL guidance, gated on the same feature flag, to prefer JPEG
at 85% quality unless lossless is required, while still allowing other
formats when explicitly requested.
- Updated tests and helper code that construct
`FunctionCallOutputContentItem::InputImage` to carry the new `detail`
field.
## Behavior
### Feature off
- `view_image` keeps the existing resize/re-encode behavior.
- History estimation keeps the existing fixed-cost heuristic.
### Feature on + `gpt-5.3-codex+`
- `view_image` sends original-resolution images with `detail:
"original"`.
- PNG/JPEG/WebP source bytes are preserved when possible.
- History estimation uses the GPT-5 docs-based image-cost calculation
for those `detail: "original"` images.
#### [git stack](https://github.com/magus/git-stack-cli)
- 👉 `1` https://github.com/openai/codex/pull/13050
- ⏳ `2` https://github.com/openai/codex/pull/13331
- ⏳ `3` https://github.com/openai/codex/pull/13049
- add a local Fast mode setting in codex-core (similar to how model id
is currently stored on disk locally)
- send `service_tier=priority` on requests when Fast is enabled
- add `/fast` in the TUI and persist it locally
- feature flag
We propagate the session ID when sending requests for inference but we
don't do the same for compaction requests. This makes it hard to link
compaction requests to their session for debugging purposes
Send a request with `generate: falls` but a full set of tools and
instructions to pre-warm inference.
---------
Co-authored-by: Codex <noreply@openai.com>
Summary
- add a `prefer_websockets` field to `ModelInfo`, defaulting to `false`
in all fixtures and constructors
- wire the new flag into websocket selection so models that opt in
always use websocket transport even when the feature gate is off
Testing
- Not run (not requested)
Instead of storing a special connection on the client level make the
regular task responsible for establishing a normal client session and
open a connection on it.
Then when the turn is started we pass in a pre-established session.
## Problem
The first user turn can pay websocket handshake latency even when a
session has already started. We want to reduce that initial delay while
preserving turn semantics and avoiding any prompt send during startup.
Reviewer feedback also called out duplicated connect/setup paths and
unnecessary preconnect state complexity.
## Mental model
`ModelClient` owns session-scoped transport state. During session
startup, it can opportunistically warm one websocket handshake slot. A
turn-scoped `ModelClientSession` adopts that slot once if available,
restores captured sticky turn-state, and otherwise opens a websocket
through the same shared connect path.
If startup preconnect is still in flight, first turn setup awaits that
task and treats it as the first connection attempt for the turn.
Preconnect is handshake-only. The first `response.create` is still sent
only when a turn starts.
## Non-goals
This change does not make preconnect required for correctness and does
not change prompt/turn payload semantics. It also does not expand
fallback behavior beyond clearing preconnect state when fallback
activates.
## Tradeoffs
The implementation prioritizes simpler ownership and shared connection
code over header-match gating for reuse. The single-slot cache keeps
lifecycle straightforward but only benefits the immediate next turn.
Awaiting in-flight preconnect has the same app-level connect-timeout
semantics as existing websocket connect behavior (no new timeout class
introduced by this PR).
## Architecture
`core/src/client.rs`:
- Added session-level preconnect lifecycle state (`Idle` / `InFlight` /
`Ready`) carrying one warmed websocket plus optional captured
turn-state.
- Added `pre_establish_connection()` startup warmup and `preconnect()`
handshake-only setup.
- Deduped auth/provider resolution into `current_client_setup()` and
websocket handshake wiring into `connect_websocket()` /
`build_websocket_headers()`.
- Updated turn websocket path to adopt preconnect first, await in-flight
preconnect when present, then create a new websocket only when needed.
- Ensured fallback activation clears warmed preconnect state.
- Added documentation for lifecycle, ownership, sticky-routing
invariants, and timeout semantics.
`core/src/codex.rs`:
- Session startup invokes `model_client.pre_establish_connection(...)`.
- Turn metadata resolution uses the shared timeout helper.
`core/src/turn_metadata.rs`:
- Centralized shared timeout helper used by both turn-time metadata
resolution and startup preconnect metadata building.
`core/tests/common/responses.rs` + websocket test suites:
- Added deterministic handshake waiting helper (`wait_for_handshakes`)
with bounded polling.
- Added startup preconnect and in-flight preconnect reuse coverage.
- Fallback expectations now assert exactly two websocket attempts in
covered scenarios (startup preconnect + turn attempt before fallback
sticks).
## Observability
Preconnect remains best-effort and non-fatal. Existing
websocket/fallback telemetry remains in place, and debug logs now make
preconnect-await behavior and preconnect failures easier to reason
about.
## Tests
Validated with:
1. `just fmt`
2. `cargo test -p codex-core websocket_preconnect -- --nocapture`
3. `cargo test -p codex-core websocket_fallback -- --nocapture`
4. `cargo test -p codex-core
websocket_first_turn_waits_for_inflight_preconnect -- --nocapture`
default-enablement of web_search is now client-side, no need to send
eligibility headers to backend.
Tested locally, headers no longer sent.
will wait for corresponding backend change to deploy before merging
So that the rest of the codebase (like TUI) don't need to be concerned
whether ChatGPT auth was handled by Codex itself or passed in via
app-server's external auth mode.
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"
/>
Previously, `CodexAuth` was defined as follows:
d550fbf41a/codex-rs/core/src/auth.rs (L39-L46)
But if you looked at its constructors, we had creation for
`AuthMode::ApiKey` where `storage` was built using a nonsensical path
(`PathBuf::new()`) and `auth_dot_json` was `None`:
d550fbf41a/codex-rs/core/src/auth.rs (L212-L220)
By comparison, when `AuthMode::ChatGPT` was used, `api_key` was always
`None`:
d550fbf41a/codex-rs/core/src/auth.rs (L665-L671)https://github.com/openai/codex/pull/10012 took things further because
it introduced a new `ChatgptAuthTokens` variant to `AuthMode`, which is
important in when invoking `account/login/start` via the app server, but
most logic _internal_ to the app server should just reason about two
`AuthMode` variants: `ApiKey` and `ChatGPT`.
This PR tries to clean things up as follows:
- `LoginAccountParams` and `AuthMode` in `codex-rs/app-server-protocol/`
both continue to have the `ChatgptAuthTokens` variant, though it is used
exclusively for the on-the-wire messaging.
- `codex-rs/core/src/auth.rs` now has its own `AuthMode` enum, which
only has two variants: `ApiKey` and `ChatGPT`.
- `CodexAuth` has been changed from a struct to an enum. It is a
disjoint union where each variant (`ApiKey`, `ChatGpt`, and
`ChatGptAuthTokens`) have only the associated fields that make sense for
that variant.
---
[//]: # (BEGIN SAPLING FOOTER)
Stack created with [Sapling](https://sapling-scm.com). Best reviewed
with [ReviewStack](https://reviewstack.dev/openai/codex/pull/10208).
* #10224
* __->__ #10208
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).
