## Summary
Code mode has two separate truncation points: the nested tool result
returned to JavaScript and the code-mode output later recorded for the
model. These tests now verify those behaviors independently.
- Report whether `result.output` was truncated before printing it.
- Verify omitted or sufficiently large nested limits produce `Variable
truncated: False`, while allowing the printed value to be truncated
downstream.
- Verify an explicit nested limit produces `Variable truncated: True`
when the command output exceeds it.
- Use a token-policy model fixture so downstream truncation is visible
as `…N tokens truncated…`.
- Align the explicit nested-truncation expectation with the warning
header.
This PR changes test coverage only; runtime truncation behavior is
unchanged.
## Validation
- `env -u CODEX_SANDBOX_NETWORK_DISABLED RUST_MIN_STACK=8388608 cargo
test -p codex-core --test all code_mode_exec -- --nocapture` (8 passed)
## Context
Inline compaction is part of the active logical turn. Compact requests
and the sampling requests around them should use the same turn state,
including when compaction is the first request to establish it.
## Change
Pass the turn-scoped `OnceLock` directly to inline v1 compaction so
`/responses/compact` includes an established value in the existing HTTP
header. Capture `x-codex-turn-state` from the compact response into that
same lock, allowing pre-turn compact to establish the value that
subsequent sampling reuses.
V2 compact already uses the normal Responses HTTP/WebSocket path and
continues to share the same `OnceLock` without separate plumbing. The
first returned value wins for the logical turn.
## Test plan
Integration coverage verifies that:
- pre-turn v1 compact can establish state for the first sampling request
- inline v1 compact receives established state over HTTP
- inline v2 compact reuses established state over HTTP
- inline v2 compact reuses established state over WebSocket
CI validates the full change.
## Context
Turn state is scoped to one logical turn, but the WebSocket path
currently exchanges it through upgrade headers, which are scoped to the
physical connection. A connection may be reused across turns, so its
handshake cannot represent the turn lifecycle reliably.
## Change
Exchange turn state on each WebSocket response request instead:
- send an established value in `response.create.client_metadata`
- read the returned value from the existing `response.metadata` event
- retain the first value in the turn-scoped `ModelClientSession`
`OnceLock`
- start the next logical turn without state, even when it reuses the
same WebSocket connection
This gives WebSocket requests the same first-value-wins contract as the
existing HTTP path.
## Test plan
Integration coverage verifies that:
- WebSocket replays returned state on same-turn follow-ups
- later response metadata does not replace the first value
- state resets at the logical turn boundary without requiring a
reconnect
CI validates the full change.
## Stack
This is 1/2. #28002 builds on this request-scoped transport to carry
established state through compact requests.
## Summary
- snapshot `comp_hash` into `TurnContext` when the turn is created and
use that snapshot as the downstream source of truth
- persist the turn hash in rollout context and recover it into
previous-turn settings during resume and fork replay
- compact existing history with the previous model only when both
adjacent turns provide hashes and the values differ
- record `comp_hash_changed` as the compaction reason
- cover ordinary transitions, resume, and missing-hash compatibility
with end-to-end tests
## Why
History produced under one compaction-compatible model configuration may
not be safe to carry directly into another. Compacting at the turn
boundary converts that history before context updates and the new user
message are added. Persisting the turn snapshot in `TurnContextItem`
makes the same protection work after resuming a rollout.
A missing hash is not treated as evidence of incompatibility. `None →
Some`, `Some → None`, and `None → None` do not trigger compaction; only
`Some(previous) → Some(current)` with unequal values does.
## Stack
- depends on #27532
- #27532 is based directly on `main`
## Testing
- `just test -p codex-core pre_sampling_compact_` — 6 passed
- `just test -p codex-core
turn_context_item_uses_turn_context_comp_hash_snapshot` — passed
- `just fix -p codex-core -p codex-protocol -p codex-analytics -p
codex-models-manager`
## Summary
- add optional `comp_hash` metadata to `ModelInfo`
- update `ModelInfo` fixtures for the shared schema change
- keep older model responses compatible by defaulting the field to
`None`
## Why
The models endpoint needs an opaque identifier for compaction-compatible
model configurations. This PR only exposes that value in model metadata;
it does not add it to turn context or change runtime behavior.
Follow-up #27520 carries the value through turn context and rollouts,
then uses it to trigger compaction.
## Stack
- based directly on `main`
- replaces #27519, which was accidentally merged into the wrong base
branch
- functionality follow-up: #27520
## Testing
- `just test -p codex-protocol
model_info_defaults_availability_nux_to_none_when_omitted`
- `just fix -p codex-core -p codex-protocol -p codex-analytics -p
codex-models-manager`
## Why
Required MCP server startup was enforced in `Session::new` after
`McpConnectionManager` had already created the clients. That split let
other manager construction paths bypass the same requirement and exposed
manager internals solely so the session could validate them. Keeping
required-server readiness in the constructor gives every caller one
consistent startup contract.
## What changed
- make `McpConnectionManager::new` return `anyhow::Result<Self>` and
fail when an enabled, required server cannot initialize
- pass the startup cancellation token into the constructor so
required-server waits remain cancellable
- propagate constructor failures through resource reads, connector
discovery, and MCP status collection
- preserve the active manager and cancellation token when a refreshed
replacement fails
- keep required-startup failure collection private and cover the
constructor error contract directly
## Validation
- updated the focused connection-manager test to assert the complete
required-server startup error
- local tests not run; relying on CI
## Summary
- order `McpConnectionManager` methods by visibility, with the primary
constructor and public API first
- restrict `list_available_server_infos` to `codex-mcp`
- make `new_uninitialized` a private test-only helper
## Why
The manager exposed methods that are only used inside `codex-mcp` or its
unit tests. Tightening those methods keeps the exported API intentional,
while the new ordering makes the supported surface easier to scan.
## Validation
- `just fmt`
- `git diff --check`
- local tests not run; relying on CI
## Why
The Python SDK must treat the runtime's initial goal turn and its
continuations as one logical operation. That requires a private
lifecycle engine before the public API can return the existing turn
handle and result types.
## What
- start goals by composing the existing clear/set goal RPCs
- enforce persisted, idle threads and a bounded startup handshake
- coalesce continuation notifications under a stable logical turn ID
- aggregate items, usage, timing, and terminal status
- support rollover-aware steering, interruption, cancellation, and
cleanup
- provide equivalent sync and async internals
This is the second PR in the stack and intentionally adds no public API.
## Test plan
- online CI, including the Python SDK suite
- behavioral coverage is added in the following two stack PRs
## Why
Goal continuation turns are emitted by the existing runtime as separate
physical turns. The Python SDK needs private thread-scoped routing
before it can present those notifications as one logical operation,
without changing ordinary turn routing or the app-server protocol.
## What
- add private goal operation state and thread-scoped notification
routing
- add internal wrappers for the existing `thread/goal/clear` and
`thread/goal/set` RPCs
- include existing goal notifications in the SDK notification union
- preserve ordinary turn-ID routing unchanged
- add focused routing coverage
This PR does not expose a public goal API. It is the first PR in the
Python goal operations stack.
## Test plan
- online CI, including the Python SDK suite
- focused typed-notification routing coverage
## Summary
Add flat profiling fields to `codex_turn_event` so analytics can explain
where turn wall-clock time is spent without changing tool execution
behavior.
The profile reports:
- time before the first sampling request
- sampling time across all attempts and follow-ups
- overhead between sampling requests
- time blocked in the post-sampling tool drain
- time after the final sampling request
- sampling request and retry counts
## Implementation
- Extend the existing turn timing state with constant-memory phase
accounting and one RAII phase guard.
- Observe sampling and the existing post-sampling drain only at turn
orchestration boundaries.
- Keep tool runtime, tool futures, response item handling, and turn
lifecycle values unchanged.
- Add the profiling fields directly to the existing analytics turn event
without changing app-server protocol or rollout persistence.
- Use the existing turn `status` to distinguish completed, failed, and
interrupted profiles.
Exact sampling/tool overlap is intentionally omitted because measuring
tool completion accurately would require hooks in the tool execution
path.
## Validation
- Add app-server end-to-end coverage for a single-sampling turn with no
blocking tool work.
- Add app-server end-to-end coverage for `request_user_input` blocking
followed by a second sampling request.
- CI is running on the PR; tests were not executed locally per
repository guidance.
## Summary
- preserve the model catalog order for app-server
`supportedReasoningEfforts` and document that client contract
- render TUI reasoning choices in the advertised order
- step reasoning shortcuts by adjacent list position instead of deriving
order from known effort names
- anchor unsupported configured values to the advertised default, or the
first option when needed
- remove canonical effort ordering helpers and the unused upgrade effort
mapping
## Validation
- `just fmt`
- Local tests and compilation were not run per request; relying on CI.
Stacked on #26444.
## Summary
- accept non-empty model-defined reasoning effort values while
preserving built-in effort behavior
- propagate the non-Copy effort type through core, app-server, TUI,
telemetry, and persistence call sites
- preserve string wire encoding and expose an open-string schema for
clients
- update model selection and shortcut behavior for model-advertised
effort values
## Root cause
`ReasoningEffort` gained a string-backed custom variant, so it could no
longer implement `Copy` or rely on derived closed-enum serialization.
Existing consumers still moved effort values from shared references and
assumed a fixed built-in value set.
## Validation
- `just fmt`
- Local tests and compilation were not run per request; relying on CI.
## Why
Python SDK releases pin an exact `openai-codex-cli-bin` version, so all
eight platform runtime wheels must be available on PyPI before the SDK
package is built and published. PyPI does not support reusable workflows
as Trusted Publishers, which means OIDC-backed publishing must run from
each top-level release workflow.
## What changed
- add reusable `python-runtime-build.yml` to prepare and upload all
eight runtime wheels without publishing
- add top-level `python-runtime-release.yml` for manual runtime
publication before updating an SDK pin
- have `python-sdk-release.yml` publish and verify the prepared runtime
wheels from its own top-level trusted job before building the SDK
- verify PyPI exposes exactly the expected eight runtime wheels before
either release workflow continues
## PyPI configuration
- keep the trusted publisher for
`.github/workflows/python-sdk-release.yml` with environment `pypi`
- add a trusted publisher for
`.github/workflows/python-runtime-release.yml` with environment `pypi`
- no trusted publisher is needed for
`.github/workflows/python-runtime-build.yml`
## Validation
- parsed all three workflow YAML files
- validated all embedded shell blocks with `bash -n`
- no local tests run; relying on online CI
## Summary
- pin the Python SDK runtime to `openai-codex-cli-bin==0.137.0a4`
- refresh generated protocol artifacts from `rust-v0.137.0-alpha.4`
- refresh `sdk/python/uv.lock` with all eight published runtime wheels
## Runtime publication
- published `openai-codex-cli-bin==0.137.0a4` through the
`python-sdk-release` workflow
- includes macOS, manylinux, musllinux, and Windows wheels
- publication run:
https://github.com/openai/codex/actions/runs/26905608531
## Validation
- ran `just fmt`
- generated artifacts from the `rust-v0.137.0-alpha.4` release wheel
- ran `uv lock --check --default-index https://pypi.org/simple`
- did not run tests locally, per request; CI provides the test signal
## Summary
- stop publishing Python runtime wheels as a side effect of Rust
releases
- publish runtime wheels from the Python SDK release workflow, either
explicitly before updating the SDK pin or immediately before a
`python-v*` SDK release
- resolve the runtime release from the requested version or the SDK
package's exact `openai-codex-cli-bin` pin
- build two musllinux-tagged wheels from the Rust-release Linux package
archives alongside the six existing runtime wheels
- validate SDK beta tags before any PyPI write
## Release configuration
- update the `openai-codex-cli-bin` PyPI trusted publisher to trust
`.github/workflows/python-sdk-release.yml` and the
`publish-python-runtime` job
## Pin update flow
- run the `python-sdk-release` workflow manually with the new runtime
version before opening or updating the SDK pin PR
- after the pin lands, a `python-v*` SDK tag republishes with
`skip-existing: true` before publishing the SDK package
## Validation
- ran `just fmt`
- validated the edited workflow YAML
- validated the embedded `publish-python-runtime` Bash with `bash -n`
- validated manual `0.136.0 -> rust-v0.136.0` mapping
- validated tag-driven `python-v0.1.0b3 -> 0.132.0 -> rust-v0.132.0`
mapping
- validated rejection of an invalid SDK tag before publication
- confirmed `rust-v0.136.0` contains the two required Linux package
archives
- CI will provide the full test signal
## Why
`code_mode_only` moved ordinary runtime tools behind `exec`, but it also
hid hosted Responses tools. Hosted `web_search` and `image_generation`
do not have a nested `exec` runtime path, so code-only sessions lost
those capabilities entirely even when their existing provider, auth,
model, and configuration gates passed.
## What changed
- Keep hosted Responses tools top-level in `code_mode_only` sessions
after their existing gates pass.
- Preserve the existing nested-tool behavior for ordinary runtimes and
the direct-only behavior for multi-agent v2 tools.
- Add planner coverage for `code_mode_only` with default multi-agent v2
settings, hosted live web search, and hosted image generation.
## Verification
- Added focused regression coverage in
`codex-rs/core/src/tools/spec_plan_tests.rs`.
- Left execution to CI per repository workflow.
## Summary
- pin the Python SDK runtime package to `openai-codex-cli-bin==0.136.0`
so Ubuntu/glibc installs resolve a compatible wheel
- refresh generated SDK artifacts and lock data for the runtime update
- keep newly generated client-message-id wire models internal to the
generated protocol layer
## Dependency
- merge #25906 first so the Python SDK release publishes both manylinux
and musllinux runtime wheels before publishing the package with this pin
## Validation
- ran `just fmt`
- regenerated the Python public API helpers
- validated the edited workflow YAML
- CI passed 29/29 checks
## Why
Some models need to select their code-execution behavior through model
catalog metadata. Models without that metadata must continue to follow
the existing `CodeMode` and `CodeModeOnly` feature flags, including when
a newer server sends an enum value this client does not recognize.
## What changed
- add optional `ModelInfo.tool_mode` metadata with `direct`,
`code_mode`, and `code_mode_only`
- treat omitted and unknown wire values as `None`
- resolve `None` from the existing feature flags
- carry the resolved `ToolMode` directly on `TurnContext`, outside
`Config`
- use the resolved value for turn creation, model switches, review
turns, tool planning, and code execution
## Coverage
- add protocol coverage for omitted, known, and unknown enum values
- add focused coverage for flag fallback and explicit metadata
overriding feature flags
- add core integration coverage that fetches remote model metadata
through `/v1/models` and verifies the outbound `/responses` tools for
explicit `direct` and `code_mode_only` selectors
## Stack
- followed by #25032
## Summary
- Treat `sdk/python` as a development template with source version
`0.0.0-dev`, matching the existing Python runtime packaging pattern.
- Have `python-v*` tags supply the published SDK beta version through
the existing `stage-sdk --sdk-version` path.
- Remove the workflow check requiring a source version bump for each
beta release and remove its now-unused host Python setup step.
- Keep the reviewed runtime dependency pin at
`openai-codex-cli-bin==0.132.0`.
- Remove beta-number-specific documentation so it does not need editing
for each publish.
## Why
The package staging script already writes the release version into the
artifact. Requiring the checked-in SDK template version to match every
tag adds release-only source churn without changing the package users
receive.
## Validation
- Not run locally; relying on online CI for this workflow and metadata
change.
## Release
After this PR lands, publish the next beta by pushing tag
`python-v0.1.0b2` from merged `main`.
## Summary
- Remove the beta warning callout from the PyPI-facing Python SDK
README.
- Keep the existing Beta title and install/usage guidance unchanged.
## Validation
- Not run locally; relying on online CI for this documentation-only
change.
## Release
- Land this change before publishing the next Python SDK beta.
## Summary
- Remove the Python language classifiers from the Python SDK package
metadata.
- Keep `requires-python = ">=3.10"` as the package's interpreter
compatibility constraint.
- Avoid presenting a curated version-support list in PyPI metadata.
## Validation
- Not run locally; relying on online CI for this metadata-only change.
## Release
- Land this change before publishing the next Python SDK beta.
## Summary
- Remove the exact-version install snippet from the PyPI-facing Python
SDK README.
- Remove the release-selection explanation so the install section
presents the standard `pip install openai-codex` path directly.
## Validation
- Not run locally; relying on online CI for this documentation-only
change.
## Why
The initial public `openai-codex` beta should read and install like a
normal published Python package before a release tag is created. This
follows merged PR #24828, which establishes the independent SDK beta
release plumbing and exact runtime dependency.
## What changed
- Rewrote `sdk/python/README.md` as a compact PyPI-facing beta package
page: published installation, one quickstart, short login examples,
built-in help, and links to deeper guides.
- Updated the getting-started guide, API reference, FAQ, and examples
index to present the published beta consistently without repeating
onboarding in the package landing page or reference page.
- Made `pip install openai-codex` the primary install path while beta
releases are the only published SDK releases, with `--pre` documented
for opting into prereleases after a stable release exists.
- Added curated `help()` / `pydoc` docstrings across the public API and
generated public convenience methods through
`scripts/update_sdk_artifacts.py`.
- Declared the repository `Apache-2.0` license expression and
Documentation URL in package metadata, without introducing a duplicated
SDK-local license file.
- Kept the source distribution focused on installable package material
(`src/openai_codex`, `README.md`, and `pyproject.toml`); the repository
docs and runnable examples remain linked from the PyPI README.
- Built release artifacts in an Alpine container on the Ubuntu runner,
matching Python SDK CI and allowing type generation to install the
published `musllinux` runtime wheel.
- Added `twine check --strict` to the release workflow so malformed PyPI
metadata or rendered README content fails before publishing.
- Added focused SDK assertions for beta metadata, the exact runtime pin,
source distribution contents, and the built-in Python documentation
surface.
## Validation
- Ran `uv run --frozen --extra dev ruff check
scripts/update_sdk_artifacts.py src/openai_codex
tests/test_public_api_signatures.py
tests/test_artifact_workflow_and_binaries.py` before the final
README-only reductions and review-fix follow-ups.
- Built `openai_codex-0.1.0b1-py3-none-any.whl` and
`openai_codex-0.1.0b1.tar.gz` before the final README-only reductions
and review-fix follow-ups.
- Ran `python -m twine check --strict` on both built artifacts before
the final README-only reductions and review-fix follow-ups.
- Verified artifact metadata reports `Apache-2.0` without a duplicated
SDK-local license file.
- Verified `inspect.getdoc(...)` resolves documentation for the package,
`Codex`, `CodexConfig`, and key generated thread methods.
- Rebased the documentation/readiness change onto merged PR #24828
without changing the intended SDK or workflow file contents.
- Final verification is delegated to online CI for this PR.
## Why
`openai-codex` needs a beta release lifecycle without requiring beta
releases of its pinned runtime package. Previously, SDK staging rewrote
its runtime dependency to the SDK version, which made an SDK-only beta
impossible.
## What changed
- Set the initial SDK beta version to `0.1.0b1` and pin it to published
stable `openai-codex-cli-bin==0.132.0`.
- Decoupled SDK release staging from runtime versioning so it preserves
the reviewed exact runtime pin.
- Added a `python-v*` tag workflow that builds and publishes only
`openai-codex` through PyPI trusted publishing.
- Removed the Beta classifier from runtime package metadata for future
runtime publications.
- Regenerated protocol-derived SDK models from the selected stable
runtime package.
`0.132.0` is the newest stable runtime admitted by the checked-in
dependency date fence and retains the Linux wheel family currently used
by SDK CI.
## Release setup
Before pushing `python-v0.1.0b1`, configure PyPI trusted publishing for
the `openai-codex` project with workflow `python-sdk-release.yml`,
environment `pypi`, and job `publish-python-sdk`.
## Validation
- `uv run --frozen --extra dev ruff check src/openai_codex scripts
examples tests`
- Parsed `.github/workflows/python-sdk-release.yml` with PyYAML.
- Built staged release artifacts locally:
`openai_codex-0.1.0b1-py3-none-any.whl` and
`openai_codex-0.1.0b1.tar.gz`.
- Verified wheel metadata pins `openai-codex-cli-bin==0.132.0`.
- Tests are deferred to online CI for this PR.
## Why
`AppServerConfig` is exported as part of the ergonomic Python SDK
surface and passed to `Codex(...)` and `AsyncCodex(...)`. That name
exposes the underlying app-server transport at the same layer where
users are configuring the Codex client. `CodexConfig` makes the common
callsite read naturally and names the object it configures.
## What changed
- Renamed the public configuration dataclass from `AppServerConfig` to
`CodexConfig`.
- Updated `Codex`, `AsyncCodex`, and the transport clients to accept
`CodexConfig`.
- Updated binary-resolution messages, package exports, docs, examples,
and related coverage to use the new public name.
## API impact
```python
from openai_codex import Codex, CodexConfig
with Codex(config=CodexConfig(codex_bin="/path/to/codex")) as codex:
...
```
Callers should now import and construct `CodexConfig`; `AppServerConfig`
is no longer part of the Python SDK surface.
## Validation
- `uv run --frozen --extra dev ruff check src/openai_codex scripts
examples tests`
- Tests are deferred to online CI for this PR.
## Why
The Python SDK currently exposes sandbox selection differently depending
on where it is used: thread lifecycle methods accept `SandboxMode`,
while turns accept the lower-level `SandboxPolicy` shape. For the common
case of choosing an access level, that leaks app-server wire details
into otherwise straightforward SDK usage.
This makes the common path explicit and discoverable: callers choose a
named sandbox preset once, using the same keyword on threads and turns.
The preset name `workspace_write` also makes the granted capability
clear at the callsite.
## What changed
- Added a root-level `Sandbox` enum with documented presets:
- `Sandbox.read_only`: read files without allowing writes.
- `Sandbox.workspace_write`: the normal default for projects with a
recorded trust decision; read files and write inside the workspace and
configured writable roots.
- `Sandbox.full_access`: run without filesystem access restrictions.
- Documented that omitting `sandbox=` delegates to app-server's
configured default, while explicit turn overrides remain sticky for
subsequent turns.
- Updated sync and async thread lifecycle and turn APIs to consistently
accept `sandbox=Sandbox...`, translating to the existing app-server
thread and turn representations internally.
- Updated the public API artifact generator so regenerated SDK wrappers
retain the friendly enum shape.
- Replaced low-level policy construction in Python docs, examples, and
the walkthrough notebook with the preset API.
- Added focused coverage for root exports, method signatures,
preset-to-wire mapping, and rejection of raw string sandbox inputs.
## API impact
High-level turn calls now use `sandbox=` instead of `sandbox_policy=`:
```python
from openai_codex import Codex, Sandbox
with Codex() as codex:
thread = codex.thread_start(sandbox=Sandbox.workspace_write)
result = thread.run("Review the diff only.", sandbox=Sandbox.read_only)
```
`thread_start(...)` already defaults to `ApprovalMode.auto_review`, so
normal writable usage is concise:
```python
with Codex() as codex:
thread = codex.thread_start(sandbox=Sandbox.workspace_write)
thread.run("Update the files in this workspace.")
```
With that combination, edits inside `cwd` and configured writable roots
run within the workspace-write sandbox. Operations that require
approval, such as edits outside those roots, are routed through auto
review. When `sandbox=` is omitted, app-server resolves its configured
default. A sandbox supplied to `run(...)` or `turn(...)` applies to that
turn and subsequent turns.
## Test coverage
- `sdk/python/tests/test_public_api_signatures.py` covers the public
export and parameter names, including the default approval mode.
- `sdk/python/tests/test_public_api_runtime_behavior.py` covers preset
mappings to the existing wire types and raw string rejection.
## Why
Code mode can use nested unified exec calls as data sources. When those
calls omit `max_output_tokens`, code mode should receive raw command
output so the script can parse or summarize it itself. When code mode
does provide `max_output_tokens`, that explicit nested budget should be
respected, including values above the default unified exec limit, rather
than being capped before code mode sees the result.
## What
- Preserve direct unified exec truncation behavior, while letting
code-mode exec/write_stdin keep `max_output_tokens` as `None` unless
explicitly supplied.
- Make code-mode tool results use raw output when no explicit limit is
present, and use the explicit nested limit directly when one is
specified.
- Refactor unified exec output formatting so `truncated_output` takes
the caller-selected token budget.
- Add e2e integration coverage for explicit nested exec limits, omitted
nested exec limits, outer exec limit propagation, omitted-limit outputs
that exceed both the default and a small truncation policy, explicit
nested limits above those caps, and high explicit limits that still
compact larger command output.
- Reuse the code-mode turn setup helper while directly asserting the
exact exec output item in each test.
## Testing
- `just fmt`
- `git diff --check`
- Not run locally per repo guidance; CI should validate the e2e
integration tests.
## Why
Plugin and skill loading is useful as warmup and early validation, but
session startup does not need to wait for that work before it can
continue building the session. Keeping it on the serial startup path
adds avoidable latency to every fresh thread start.
We still want invalid skill configurations to show up quickly, and we
want the warmup to exercise the same plugin and skill manager caches
that the normal turn path uses.
## What changed
- moved plugin and skill warmup into the session startup async path
instead of eagerly awaiting it on the serial setup path
- kept the warmup using the session's resolved filesystem/environment
context so skill loading still sees the right roots
- preserved early skill-load error logging so broken skill
configurations still surface during startup
- left the per-turn plugin and skill loading path unchanged, so turns
still use the normal cached managers
## Testing
- Not run locally; relying on CI for validation.
## Why
Custom agent roles are ordinary config layers, so a role file can
already express `service_tier` just like other config values. The
spawned-agent tier path needs to preserve that effective role config and
follow the same precedence pattern as model/reasoning.
## What changed
- Apply an explicit spawn-time `service_tier` onto the child config
before role application, so a role config layer can override it just
like role-defined model/reasoning settings do.
- Validate the final effective child tier after the final child model is
known, while still falling back to the parent tier when no child tier
survives.
- Add focused integration coverage for both v1 and v2 proving role TOML
loads a service tier, spawned children keep that role-configured tier,
and a role tier wins over a conflicting spawn-time tier.
## Validation
- `just fmt`
- `git diff --check`
- Local Rust tests not run, per repo guidance; CI should exercise the
new coverage.
## Why
The Python SDK depends on `openai-codex-cli-bin` runtime wheels being
installable on the Linux hosts our users actually run. The release
workflow currently tags the Linux runtime artifacts as `musllinux_*`,
which makes pip ignore them on normal glibc distributions even though
the bundled Rust executables are intended to run there.
## What changed
- Tag the Linux runtime wheels as `manylinux_2_17_aarch64` and
`manylinux_2_17_x86_64` instead of `musllinux_1_1_*`.
- Keep the existing runtime wheel build and publish flow unchanged
otherwise.
## Verification
- Confirmed the wheel-tag issue against the PyPA platform-tag rules for
`manylinux` vs `musllinux`.
- This PR is now intentionally scoped to the tag correction only; the
broader Python runtime release workflow has already landed on `main`
through the merged stack.
## Follow-up
After publishing the next alpha from this branch, install the
SDK/runtime in a fresh glibc Linux environment and confirm pip resolves
the tagged Linux wheel as expected.
Co-authored-by: Codex <noreply@openai.com>
## Why
`TurnHandle.run()` returned the raw app-server `Turn`, whose live
start/completed payloads do not include loaded `items`, so users saw
empty `items` after starting a turn. That made the handle-based path
behave differently from `Thread.run(...)`, and pushed examples toward
persisted-thread reads plus helper extraction.
This PR makes the run APIs standalone: starting a turn and running it
returns collected turn data directly, or fails visibly when required
stream events are missing.
## What Changed
- Replaces the public `RunResult` export with `TurnResult`.
- Adds turn metadata to `TurnResult`: `id`, `status`, `error`,
`started_at`, `completed_at`, and `duration_ms`, alongside
`final_response`, `items`, and `usage`.
- Changes `TurnHandle.run()` and `AsyncTurnHandle.run()` to consume
stream events with the same collector used by `Thread.run(...)`.
- Exports `TurnError` from `openai_codex.types` for the new result
shape.
- Updates tests, examples, docs, and the walkthrough notebook to use
`result.final_response` and `result.items` directly.
- Removes persisted-thread helper paths and placeholder/skipped control
flows from the public examples and notebook.
## Verification
- `python3 -m py_compile ...` over changed SDK, example, and test Python
files.
- `python3 -c "import json;
json.load(open('sdk/python/notebooks/sdk_walkthrough.ipynb'))"`
- `git diff --check`
- `PYTHONPATH=sdk/python/src python3 -c ...` import/signature smoke for
`TurnResult`, `TurnHandle.run`, and `AsyncTurnHandle.run`.
## Why
The Python SDK can already create threads and run turns, but
authentication still has to be arranged outside the SDK. App-server
already exposes account login, account inspection, logout, and
`account/login/completed` notifications, so SDK users currently have to
work around a missing public client layer for a core setup step.
This change makes authentication a normal SDK workflow while preserving
the backend flow shape: API-key login completes immediately, and
interactive ChatGPT flows return live handles that complete later
through app-server notifications.
## What changed
- Added public sync and async auth methods on `Codex` / `AsyncCodex`:
- `login_api_key(...)`
- `login_chatgpt()`
- `login_chatgpt_device_code()`
- `account(...)`
- `logout()`
- Added public browser-login and device-code handle types with
attempt-local `wait()` and `cancel()` helpers. Cancellation stays on the
handle instead of a root-level SDK method.
- Extended the Python app-server client and notification router so login
completion events are routed by `login_id` without consuming unrelated
global notifications.
- Kept login request/handle logic in a focused internal `_login.py`
module so `api.py` remains the public facade instead of absorbing more
auth plumbing.
- Exported the new handle types plus curated account/login response
types from the SDK surfaces.
- Updated SDK docs, added sync/async login walkthrough examples, and
added a notebook login walkthrough cell.
## Verification
Added SDK coverage for:
- API-key login, account readback, and logout through the app-server
harness in both sync and async clients.
- Browser login cancellation plus `handle.wait()` completion through the
real app-server boundary used by the Python SDK harness.
- Waiter routing that stays scoped across replaced interactive login
attempts, plus async handle cancellation coverage.
- Login notification demuxing, replay of early completion events, and
async client delegation.
- Public export/signature assertions.
- Real integration-suite smoke coverage for the new examples and
notebook login cell.
## Summary
- Move approval-mode mapping into
`sdk/python/src/openai_codex/_approval_mode.py`.
- Move initialize metadata parsing and normalization into
`sdk/python/src/openai_codex/_initialize_metadata.py`.
- Keep the public `ApprovalMode` export stable and retarget direct
metadata helper coverage.
## Integration coverage
- Add an app-server harness smoke that exercises sync and async SDK
initialization plus thread creation.
## Validation
- Local tests were not run per repo guidance. CI should validate this
branch once the PR is online.
## Summary
- Remove maintainer and release-process wording from the Python SDK
README and docs.
- Rewrite SDK-facing comments/docstrings so they read as standalone
product documentation.
- Add a real app-server integration smoke that follows the public
quickstart-style `Codex() -> thread_start() -> run()` path.
## Integration coverage
- Add `test_real_quickstart_style_flow_smoke` in the real app-server
integration suite.
## Validation
- Local tests were not run per repo guidance. CI should validate this
branch once the PR is online.
## Why
Spawned agents can already override `model` and `reasoning_effort`, but
they have no equivalent way to opt into a model-supported service tier.
That makes it impossible to preserve or intentionally select tiered
execution behavior when delegating work to a sub-agent, even though the
model catalog already advertises supported `service_tiers`.
## What changed
- Add optional `service_tier` to both legacy and `MultiAgentV2`
`spawn_agent` tool inputs.
- Show each picker-visible model's supported service tier ids and
descriptions in the `spawn_agent` tool guidance.
- Resolve service tier selection after the child agent's effective model
is known.
- Inherit the parent tier when omitted and still supported by the final
child model; otherwise clear it.
- Reject explicit unsupported tier requests with a model-facing error.
- Keep explicit `service_tier` usable on full-history forks, while still
honoring the existing model/reasoning fork restrictions.
- Hide `service_tier` alongside other spawn metadata when
`hide_spawn_agent_metadata` is enabled.
## Verification
Added focused coverage for:
- v1/v2 `spawn_agent` schema exposure for `service_tier`
- tier descriptions in spawn guidance
- hidden-metadata suppression
- explicit supported tier selection
- explicit unknown and unsupported tier rejection
- inherited tier preservation or clearing based on child-model support
- full-history fork acceptance for explicit service tiers in both v1 and
v2
Local Rust tests were not run in this workspace per repo guidance; the
new coverage is included for CI.
## Why
The Python SDK needs the same tight formatter/lint loop as the rest of
the repo: a safe Ruff autofix pass, Ruff formatting, editor save
behavior, and CI checks that catch drift. Without that loop, SDK changes
can land with formatting or import ordering that differs from what
reviewers and CI expect.
## What
- Add Ruff configuration to `sdk/python/pyproject.toml`, excluding
generated protocol code and notebooks from the normal lint/format pass.
- Update `just fmt` so it still formats Rust and also runs Python SDK
Ruff autofix and formatting.
- Add Python SDK CI steps for `ruff check` and `ruff format --check`
before pytest.
- Recommend the Ruff VS Code extension and enable Python
format/fix/organize-on-save so Cmd+S uses the same tooling.
- Apply the resulting Ruff formatting to SDK Python files, examples, and
the checked-in generated `v2_all.py` output emitted by the pinned
generator.
- Add a guard test for the `just fmt` recipe so it keeps working from
both Rust and Python SDK working directories.
## Stack
1. #21891 `[1/8]` Pin Python SDK runtime dependency
2. #21893 `[2/8]` Generate Python SDK types from pinned runtime
3. #21895 `[3/8]` Run Python SDK tests in CI
4. #21896 `[4/8]` Define Python SDK public API surface
5. #21905 `[5/8]` Rename Python SDK package to `openai-codex`
6. #21910 `[6/8]` Add high-level Python SDK approval mode
7. #22014 `[7/8]` Add Python SDK app-server integration harness
8. This PR `[8/8]` Add Python SDK Ruff formatting
## Verification
- Added `test_root_fmt_recipe_formats_rust_and_python_sdk` for the
shared format recipe.
- Ran `just fmt` after the recipe update.
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
The SDK had behavioral tests that replaced SDK client internals. Those
tests could catch wrapper mistakes, but they did not prove the pinned
app-server runtime, generated notification models, request routing, and
sync/async public clients worked together.
This PR adds deterministic integration coverage that starts the pinned
`codex app-server` process and mocks only the upstream Responses HTTP
boundary.
## What
- Add `AppServerHarness` and `MockResponsesServer` helpers for isolated
`CODEX_HOME`, mock-provider config, queued SSE responses, and captured
`/v1/responses` requests.
- Add shared helpers for SSE construction, stream assertions,
approval-policy inspection, and image fixtures.
- Split integration coverage into focused modules for run behavior,
inputs, streaming, turn controls, approvals, and thread lifecycle.
- Cover sync and async `Thread.run`, `TurnHandle.stream`, interleaved
streams, approval-mode persistence, lifecycle helpers, final-answer
phase handling, image inputs, loaded skill input injection, steering,
interruption, listing, history reads, run overrides, and token usage
mapping.
- Replace public-wrapper tests that duplicated integration-test behavior
with lower-level client tests only where direct client behavior is the
thing under test.
## Stack
1. #21891 `[1/8]` Pin Python SDK runtime dependency
2. #21893 `[2/8]` Generate Python SDK types from pinned runtime
3. #21895 `[3/8]` Run Python SDK tests in CI
4. #21896 `[4/8]` Define Python SDK public API surface
5. #21905 `[5/8]` Rename Python SDK package to `openai-codex`
6. #21910 `[6/8]` Add high-level Python SDK approval mode
7. This PR `[7/8]` Add Python SDK app-server integration harness
8. #22021 `[8/8]` Add Python SDK Ruff formatting
## Verification
- Added pinned app-server integration tests under
`sdk/python/tests/test_app_server_*.py` and
`test_real_app_server_integration.py`.
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
The high-level SDK should expose the approval behavior it actually
supports instead of leaking generated app-server routing fields. New
work should have two clear choices: default auto review, or explicitly
deny escalated permission requests. Existing threads and subsequent
turns should preserve their current approval behavior unless the caller
passes an override.
## What
- Add the public `ApprovalMode` enum with `auto_review` and `deny_all`.
- Default new thread creation to `ApprovalMode.auto_review`.
- Preserve existing approval settings by default for resume, fork, run,
and turn helpers.
- Remove raw `approval_policy` / `approvals_reviewer` kwargs from
high-level SDK wrappers.
- Update generated wrapper output, docs, examples, notebooks, and tests
for the high-level approval mode API.
## Stack
1. #21891 `[1/8]` Pin Python SDK runtime dependency
2. #21893 `[2/8]` Generate Python SDK types from pinned runtime
3. #21895 `[3/8]` Run Python SDK tests in CI
4. #21896 `[4/8]` Define Python SDK public API surface
5. #21905 `[5/8]` Rename Python SDK package to `openai-codex`
6. This PR `[6/8]` Add high-level Python SDK approval mode
7. #22014 `[7/8]` Add Python SDK app-server integration harness
8. #22021 `[8/8]` Add Python SDK Ruff formatting
## Verification
- Added approval-mode mapping/default tests for new threads, existing
threads, forks, resumes, and subsequent turns.
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
The SDK should publish under the reserved public distribution name
`openai-codex`, and its import module should match that name in the
Python style. Since package names can contain hyphens but import modules
cannot, the public import path becomes `openai_codex`.
Keeping the rename separate from the public API surface change makes the
naming change easy to review and avoids mixing it with API curation.
## What
- Rename the SDK distribution from `openai-codex-app-server-sdk` to
`openai-codex`.
- Rename the import package from `codex_app_server` to `openai_codex`.
- Keep the runtime wheel as the separate `openai-codex-cli-bin`
dependency.
- Update docs, examples, notebooks, artifact scripts, lockfile metadata,
and tests for the new distribution/module names.
## Stack
1. #21891 `[1/8]` Pin Python SDK runtime dependency
2. #21893 `[2/8]` Generate Python SDK types from pinned runtime
3. #21895 `[3/8]` Run Python SDK tests in CI
4. #21896 `[4/8]` Define Python SDK public API surface
5. This PR `[5/8]` Rename Python SDK package to `openai-codex`
6. #21910 `[6/8]` Add high-level Python SDK approval mode
7. #22014 `[7/8]` Add Python SDK app-server integration harness
8. #22021 `[8/8]` Add Python SDK Ruff formatting
## Verification
- Updated package metadata and public API tests to assert the
distribution and import names.
Co-authored-by: Codex <noreply@openai.com>
## Why
The SDK package root should be the ergonomic public client API, not a
dump of every generated app-server schema type. Generated models still
need a supported import path, but callers should be able to tell which
names are high-level SDK entrypoints and which names are protocol value
models.
## What
- Define a curated root `__all__` for clients, handles, input helpers,
retry helpers, config, and public errors.
- Add a `types` module as the supported home for generated app-server
response, event, enum, and helper models.
- Update docs and examples to import protocol/value models from the type
module.
- Add tests that lock root exports, type-module exports, star-import
behavior, and example import hygiene.
## Stack
1. #21891 `[1/8]` Pin Python SDK runtime dependency
2. #21893 `[2/8]` Generate Python SDK types from pinned runtime
3. #21895 `[3/8]` Run Python SDK tests in CI
4. This PR `[4/8]` Define Python SDK public API surface
5. #21905 `[5/8]` Rename Python SDK package to `openai-codex`
6. #21910 `[6/8]` Add high-level Python SDK approval mode
7. #22014 `[7/8]` Add Python SDK app-server integration harness
8. #22021 `[8/8]` Add Python SDK Ruff formatting
## Verification
- Added public API signature tests for root exports, `types` exports,
and example imports.
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
The Python SDK stack now depends on packaging metadata, pinned runtime
wheels, generated artifacts, async behavior, and stream interleaving.
Those checks need to run in CI so future changes cannot bypass the SDK
test suite.
## What
- Add a dedicated `python-sdk` job to `.github/workflows/sdk.yml`.
- Run the job in `python:3.12-alpine` so dependency resolution exercises
the pinned musl runtime wheel.
- Keep the Python SDK test job parallel to the existing SDK job instead
of serializing the full workflow.
## Stack
1. #21891 `[1/8]` Pin Python SDK runtime dependency
2. #21893 `[2/8]` Generate Python SDK types from pinned runtime
3. This PR `[3/8]` Run Python SDK tests in CI
4. #21896 `[4/8]` Define Python SDK public API surface
5. #21905 `[5/8]` Rename Python SDK package to `openai-codex`
6. #21910 `[6/8]` Add high-level Python SDK approval mode
7. #22014 `[7/8]` Add Python SDK app-server integration harness
8. #22021 `[8/8]` Add Python SDK Ruff formatting
## Verification
- The added workflow job installs the SDK with `uv sync --extra dev
--frozen` and runs the Python SDK pytest suite.
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
Once the SDK declares its runtime package, generated Python artifacts
should come from that pinned runtime rather than whatever app-server
schema happens to be in the current checkout. That keeps the generated
API and model surface aligned with the runtime users install.
## What
- Teach `scripts/update_sdk_artifacts.py generate-types` to invoke the
pinned runtime package for schema generation.
- Regenerate `v2_all.py`, `notification_registry.py`, and generated
public wrapper methods from that schema.
- Add freshness coverage so regenerating from the pinned runtime must
leave checked-in artifacts unchanged.
## Stack
1. #21891 `[1/8]` Pin Python SDK runtime dependency
2. This PR `[2/8]` Generate Python SDK types from pinned runtime
3. #21895 `[3/8]` Run Python SDK tests in CI
4. #21896 `[4/8]` Define Python SDK public API surface
5. #21905 `[5/8]` Rename Python SDK package to `openai-codex`
6. #21910 `[6/8]` Add high-level Python SDK approval mode
7. #22014 `[7/8]` Add Python SDK app-server integration harness
8. #22021 `[8/8]` Add Python SDK Ruff formatting
## Verification
- Added `test_generated_files_are_up_to_date` for pinned-runtime
generation drift.
- Added generator-structure tests for schema annotation and notification
metadata generation.
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
The Python SDK depends on the app-server runtime package for the bundled
`codex` binary and schema source of truth. That relationship should be
explicit in package metadata instead of inferred from matching version
numbers, so installers, lockfiles, and reviewers can see exactly which
runtime the SDK expects.
## What
- Declare `openai-codex-cli-bin==0.131.0a4` as a Python SDK dependency.
- Update runtime setup helpers to resolve the runtime version from the
declared dependency pin.
- Refresh the SDK lockfile for the pinned runtime wheel.
- Update package/runtime tests and docs that describe where the runtime
version comes from.
## Stack
1. This PR `[1/8]` Pin Python SDK runtime dependency
2. #21893 `[2/8]` Generate Python SDK types from pinned runtime
3. #21895 `[3/8]` Run Python SDK tests in CI
4. #21896 `[4/8]` Define Python SDK public API surface
5. #21905 `[5/8]` Rename Python SDK package to `openai-codex`
6. #21910 `[6/8]` Add high-level Python SDK approval mode
7. #22014 `[7/8]` Add Python SDK app-server integration harness
8. #22021 `[8/8]` Add Python SDK Ruff formatting
## Verification
- Added coverage for the SDK runtime dependency pin and runtime
distribution naming.
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
Dogfooder feedback exposed two correctness gaps in normal-loop overflow
recovery:
1. a sampling request that hit `ContextWindowExceeded` could keep
re-entering auto-compaction indefinitely if the compacted retry still
did not fit, and
2. local compact-history rebuilds flattened user messages down to text,
so an overflowing `[image, "what is this?"]` turn could be retried
without the image after compaction.
That means recovery could either fail to terminate cleanly or proceed
with a materially weakened version of the user request.
## What changed
- Move normal-loop `ContextWindowExceeded` handling into the sampling
retry loop, so successful rescue compaction consumes the provider retry
budget instead of creating an unbounded outer-turn loop.
- Keep compacted user-history rebuilds structured:
`collect_user_messages` now carries user `UserInput` content rather than
flattened strings, and `build_compacted_history` reconstructs full user
messages from that structured representation.
- Preserve image inputs while retaining the existing text-budget
truncation behavior for compacted user history.
- Preserve existing compaction-task failure handling and client-session
reset behavior while bounding repeated overflow retries.
- Add focused regression coverage for:
- recovery after a normal-loop overflow,
- retry-budget exhaustion after repeated overflow,
- local recovery preserving image + text input,
- remote recovery preserving image + text input,
- remote compaction v2 preserving image + text input, and
- compaction failure still terminating cleanly.
The main behavior changes are in `codex-rs/core/src/session/turn.rs` and
`codex-rs/core/src/compact.rs`.
## Verification
- Not run locally; relying on PR CI for this update.
---------
Co-authored-by: Codex <noreply@openai.com>
### Motivation
- Normalize persisted service tier so selecting the request value
`priority` (or legacy `fast`) is stored as `fast` while preserving
unknown tier IDs and keeping request-time behavior unchanged.
### Description
- Update persistence logic in `codex-rs/core/src/config/edit.rs` so
`ConfigEdit::SetServiceTier` maps request values: `priority`/`fast` ->
`"fast"`, `flex` -> `"flex"`, and leaves unknown strings unchanged.
- Add unit tests in `codex-rs/core/src/config/edit_tests.rs` that verify
a `priority` selection is written to `config.toml` as `"fast"` and that
unknown tiers are preserved.
- Add a config load test in `codex-rs/core/src/config/config_tests.rs`
to ensure `service_tier = "priority"` still resolves to the `priority`
request value at load time.
- Add the required import `use
codex_protocol::config_types::ServiceTier;` to the edited modules.
### Testing
- Ran `just fmt` and `just fix -p codex-core` to apply formatting and
lints and they completed successfully.
- Ran `cargo test -p codex-core --lib service_tier` (focused unit tests
for the change) and the tests passed.
- Ran `cargo test -p codex-protocol` and the protocol test suite passed.
- Note: an initial broader `cargo test -p codex-core service_tier`
invocation matched integration tests and produced unrelated
failures/hangs, so that run was interrupted and the focused `--lib`
unit-test invocation was used instead.
------
[Codex
Task](https://chatgpt.com/codex/cloud/tasks/task_i_69ffc5a1262c8321af91b69c9845147f)
## Why
Service-tier slash commands are built from model-catalog metadata. If
the catalog returns a name like `Fast`, the TUI currently exposes
`/Fast` and exact dispatch expects that casing, which is inconsistent
with the lowercase command style used elsewhere.
## What
- Lowercase service-tier command names when converting catalog tiers
into `ServiceTierCommand` values.
- Add regression coverage that seeds a catalog tier named `Fast` and
expects the generated command to be `fast`.
## Testing
Not run locally per repo instruction; PR CI should run the new
`service_tier_commands_lowercase_catalog_names` coverage.
## Why
The Python SDK previously protected the stdio transport with a single
active turn-consumer guard. That avoided competing reads from stdout,
but it also meant one `Codex`/`AsyncCodex` client could not stream
multiple active turns at the same time. Notifications could also arrive
before the caller received a `TurnHandle` and registered for streaming,
so the SDK needed an explicit routing layer instead of letting
individual API calls read directly from the shared transport.
## What Changed
- Added a private `MessageRouter` that owns per-request response queues,
per-turn notification queues, pending turn-notification replay, and
global notification delivery behind a single stdout reader thread.
- Generated typed notification routing metadata so turn IDs come from
known payload shapes instead of router-side attribute guessing, with
explicit fallback handling for unknown notification payloads.
- Updated sync and async turn streaming so `TurnHandle.stream()`/`run()`
and `stream_text()` consume only notifications for their own turn ID,
while `AsyncAppServerClient` no longer serializes all transport calls
behind one async lock.
- Cleared pending turn-notification buffers when unregistered turns
complete so never-consumed turn handles do not leave stale queues
behind.
- Removed the internal stream-until helper now that turn completion
waiting can register directly with routed turn notifications.
- Updated Python SDK docs and focused tests for concurrent transport
calls, interleaved turn routing, buffered early notifications, unknown
notification routing, async delegation, and routed turn completion
behavior.
## Validation
- `uv run --extra dev ruff format scripts/update_sdk_artifacts.py
src/codex_app_server/_message_router.py src/codex_app_server/client.py
src/codex_app_server/generated/notification_registry.py
tests/test_client_rpc_methods.py
tests/test_public_api_runtime_behavior.py
tests/test_async_client_behavior.py`
- `uv run --extra dev ruff check scripts/update_sdk_artifacts.py
src/codex_app_server/_message_router.py src/codex_app_server/client.py
src/codex_app_server/generated/notification_registry.py
tests/test_client_rpc_methods.py
tests/test_public_api_runtime_behavior.py
tests/test_async_client_behavior.py`
- `uv run --extra dev pytest tests/test_client_rpc_methods.py
tests/test_public_api_runtime_behavior.py
tests/test_async_client_behavior.py`
- `git diff --check`
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
Published Python SDK builds depend on an exact `openai-codex-cli-bin`
runtime package, but the release workflow did not publish that runtime
package to PyPI. That left the SDK packaging story incomplete: release
artifacts could produce Codex binaries, but Python users still needed a
matching wheel carrying the platform-specific runtime and helper
executables.
This PR is stacked on #21787 so release jobs can include helper binaries
in runtime wheels: Linux wheels include `bwrap` for sandbox fallback,
and Windows wheels include the signed sandbox/elevation helpers beside
`codex.exe`.
## What changed
- Builds platform-specific `openai-codex-cli-bin` wheels from signed
release binaries on macOS, Linux, and Windows release runners.
- Packages Linux `bwrap` into musllinux runtime wheels.
- Packages Windows sandbox helper executables into Windows runtime
wheels.
- Uploads runtime wheels as GitHub release assets and publishes them to
PyPI using trusted publishing from the `pypi` GitHub environment.
- Keeps the new Python runtime publish job non-blocking so failures need
follow-up but do not fail the Rust release workflow.
- Pins the PyPA publish action to the `v1.13.0` commit SHA for
reproducible release publishing.
- Documents that runtime wheels are platform wheels published through
PyPI trusted publishing.
## Testing
- `ruby -e 'require "yaml"; ARGV.each { |f| YAML.load_file(f); puts "ok
#{f}" }' .github/workflows/rust-release.yml
.github/workflows/rust-release-windows.yml`
- `git diff --check`
CI is the real end-to-end verification for the release workflow path.
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
Some Codex runtime distributions need helper executables beside the main
bundled binary. Linux sandbox fallback needs a packaged `bwrap` when no
suitable system `bwrap` is available, and Windows sandbox/elevation
needs helper executables discoverable beside `codex.exe`. The checked-in
`openai-codex-cli-bin` template already packages everything under
`codex_cli_bin/bin/**`, but the staging script only copied the main
Codex binary into that directory.
This PR adds the generic staging primitive needed by release workflows
to build complete platform runtime wheels without baking
platform-specific helper names into the package template.
## What changed
- Added repeatable `stage-runtime --resource-binary` support so release
workflows can copy extra executables beside the bundled Codex binary.
- Kept resource selection in workflow code, where the platform target is
known.
- Added tests that verify resource binaries are copied into the staged
runtime package, that the wheel include config covers them, and that the
CLI forwards repeated `--resource-binary` values.
## Testing
- `uv run ruff check scripts/update_sdk_artifacts.py
tests/test_artifact_workflow_and_binaries.py`
- `uv run --extra dev pytest
tests/test_artifact_workflow_and_binaries.py::test_stage_runtime_release_copies_resource_binaries
tests/test_artifact_workflow_and_binaries.py::test_runtime_resource_binaries_are_included_by_wheel_config
tests/test_artifact_workflow_and_binaries.py::test_stage_runtime_stages_binary_without_type_generation`
Full `tests/test_artifact_workflow_and_binaries.py` still has unrelated
schema-normalization drift in the local checkout.
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
`/fast` was wired as a one-off slash command even though model metadata
now exposes service tiers as catalog data. That meant adding another
tier, such as a slower/cheaper tier, would require more hardcoded TUI
plumbing instead of letting the model catalog drive the available
commands.
This change makes service-tier commands data-driven: each advertised
`service_tiers` entry becomes a `/name` command using the catalog
description, while the request path sends the tier `id` only when the
selected model supports it.
## What Changed
- Removed the hardcoded `/fast` slash-command variant and introduced
dynamic service-tier command items in the composer and command popup.
- Added toggle behavior for service-tier commands: invoking `/name`
selects that tier, and invoking it again clears the selection.
- Preserved the existing Fast-mode keybinding/status affordances by
resolving the current model tier whose name is `fast`, while still
sending the tier request value such as `priority`.
- Persisted service-tier selections as raw request strings so non-fast
tiers can round-trip through config.
- Updated the Bedrock catalog entry to advertise fast support through
`service_tiers` with `id: "priority"` and `name: "fast"`.
- Added defensive filtering in core so unsupported selected service
tiers are omitted from `/responses` requests.
## Validation
- Added/updated coverage for dynamic service-tier slash command lookup,
popup descriptions, composer dispatch, TUI fast toggling, and
unsupported-tier omission in core request construction.
- Local tests were not run per request.
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
- enable `apply_patch_freeform` by default in the feature registry
## Why
- make the freeform `apply_patch` tool available by default when model
metadata does not explicitly opt into another mode
## Validation
- `just fmt`
- did not run tests
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
`service_tier` in `config.toml` and profile config was still modeled as
an enum, which blocked newer or experimental service tier IDs even
though the runtime paths already carry string IDs.
This change makes the TOML-facing config accept string service tier IDs
directly while keeping the legacy `fast` alias behavior by normalizing
it to the request value `priority`.
## What Changed
- change the TOML-facing `service_tier` fields in global and profile
config to `Option<String>`
- keep config-load normalization so legacy `fast` still resolves to
`priority`
- persist resolved service tier strings directly in config locks so
arbitrary IDs round-trip cleanly
- regenerate the config schema and add config coverage for arbitrary
string IDs plus legacy `fast` normalization
## Verification
- added config tests for arbitrary string service tiers and legacy
`fast` normalization
- ran `just write-config-schema`
- CI
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
API-key-auth remote compaction requests should not inherit
`service_tier` from normal `/responses` turns. This path needs to match
API auth expectations, while ChatGPT-auth remote compaction should keep
reusing the shared request fields that still apply there.
This change keeps the decision inline in
`codex-rs/core/src/compact_remote.rs` only. Under API key auth, the
classic remote `/responses/compact` path now omits `service_tier`; under
ChatGPT auth, it keeps reusing the configured tier.
`codex-rs/core/src/compact_remote_v2.rs` is unchanged. The remote
compaction parity coverage and snapshots were updated to assert the
API-key omission and preserve the ChatGPT-auth behavior.
## Testing
- Updated remote compaction parity coverage in
`codex-rs/core/tests/suite/compact_remote.rs` and the corresponding
snapshots.
## Why
`/responses/compact` should preserve the request-affinity fields that
apply to the active auth mode. ChatGPT-auth compact requests need the
effective `service_tier`, and compact requests for every auth mode need
the stable `prompt_cache_key`, so compaction does not quietly lose
routing or cache behavior that normal sampling already has.
This follows the request-parity direction from #20719, but keeps the net
change focused on the compact payload fields needed here.
## What changed
- Add `service_tier` and `prompt_cache_key` to the compact endpoint
input payload.
- Build the remote compact payload from the existing responses request
builder output so `Fast` still maps to `priority` when compact sends a
service tier.
- Pass the turn service tier into remote compaction, but only include it
in compact payloads for ChatGPT-backed auth.
- Keep `prompt_cache_key` on compact payloads for all auth modes.
- Add request-body diff snapshot coverage in
`core/tests/suite/compact_remote.rs` for:
- API-key auth reusing `prompt_cache_key` while omitting `service_tier`
even when `Fast` is configured.
- ChatGPT auth reusing both `service_tier` and `prompt_cache_key`.
- Drive the snapshot coverage through five varied turns: plain text,
multi-part text, tool-call continuation, image+text input, local-shell
continuation, and final-turn reasoning output.
## Verification
- Added insta snapshots for compact request-body parity against the last
normal `/responses` request after five varied turns.
- Not run locally per repo guidance; relying on GitHub CI for test
execution.
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
The model list needs to carry display-ready service tier metadata so
clients can render tier choices with stable IDs, names, and
descriptions. A raw speed-tier string list is not enough for richer UI
copy or future tier labels.
## What changed
- Added `ModelServiceTier` to shared model metadata with string `id`,
`name`, and `description` fields.
- Added `service_tiers` to `ModelInfo` and `ModelPreset`, preserving
empty defaults for older cached model payloads.
- Exposed `serviceTiers` on app-server v2 `Model` responses and threaded
it through TUI app-server model conversion.
- Marked legacy `additional_speed_tiers` / `additionalSpeedTiers`
metadata as deprecated in source and generated schema output.
- Regenerated app-server protocol JSON schema and TypeScript fixtures,
including `ModelServiceTier.ts`.
## Verification
- Ran `just write-app-server-schema`.
- Did not run local tests per repo instruction; relying on PR CI.
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
Codex is repurposing `session` to mean a thread group, so the realtime
provider session id should no longer use `session_id` / `sessionId` in
Codex-facing protocol payloads. This PR renames that provider-specific
field to `realtime_session_id` / `realtimeSessionId` and intentionally
breaks clients that still send the old field names.
## What Changed
- Renamed realtime provider session fields in `ConversationStartParams`,
`RealtimeConversationStartedEvent`, and `RealtimeEvent::SessionUpdated`.
- Renamed app-server v2 realtime request and notification fields to
`realtimeSessionId`.
- Removed legacy serde aliases for `session_id` / `sessionId`; clients
must send the new names.
- Propagated the rename through core realtime startup, app-server
adapters, codex-api websocket handling, and TUI realtime state.
- Regenerated app-server protocol schema/TypeScript outputs and updated
app-server README examples.
- Kept upstream Realtime API concepts unchanged: provider `session.id`
parsing and `x-session-id` headers still use the upstream wire names.
## Testing
- CI is running on the latest pushed commit.
- Earlier local verification on this PR:
- `cargo test -p codex-protocol`
- `CODEX_SKIP_VENDORED_BWRAP=1 cargo test -p codex-core
realtime_conversation`
- `cargo test -p codex-app-server-protocol`
- `CODEX_SKIP_VENDORED_BWRAP=1 cargo test -p codex-app-server
realtime_conversation`
- attempted `CODEX_SKIP_VENDORED_BWRAP=1 cargo test -p codex-tui` (local
linker bus error while linking the test binary)
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
The visibility cleanup in the base PR reduced what `codex-mcp` exposes,
but several files still made reviewers read private support machinery
before the public or crate-facing entry points. This ordering pass makes
each file easier to scan: exported API first, crate-visible MCP
internals next, then private helpers in breadth-first order from the
higher-level MCP flows to leaf utilities.
## What Changed
- Reordered `codex-mcp` exports so the runtime, configuration, snapshot,
auth, and helper surfaces are grouped by visibility and reader
importance.
- Moved public and crate-visible MCP items ahead of private helpers in
the auth, MCP planning/snapshot, connection manager, and tool-name
modules.
- Kept the change mechanical, with no behavior changes intended.
## Verification
- `cargo check -p codex-mcp`
## Why
`codex-mcp` currently exposes more API than the rest of the workspace
uses. Some of that surface is simply visibility that can be tightened,
and some of it is public helper code that remains compiler-valid because
it is exported even though no workspace caller uses it.
That distinction matters: Rust does not warn on exported API just
because the current workspace does not call it. This PR intentionally
treats those exported-but-workspace-unreferenced paths as stale
`codex-mcp` surface. The main example is MCP skill dependency
collection, where the active implementation now lives in
`codex-rs/core/src/mcp_skill_dependencies.rs`; keeping the older
`codex-mcp` copy makes it unclear which implementation owns skill MCP
installation.
## What Changed
- Pruned unused `codex-mcp` re-exports from `codex-mcp/src/lib.rs`.
- Removed non-runtime helper methods from `McpConnectionManager` so it
stays focused on live MCP clients.
- Made `ToolPluginProvenance` lookup methods crate-private.
- Removed workspace-unreferenced snapshot wrapper APIs and
qualified-tool grouping helpers.
- Deleted the duplicate `codex-mcp` skill dependency module and tests
now that skill MCP dependency handling is owned by `core`.
## Verification
- `cargo check -p codex-mcp`
### Why
The RMCP layer needs a Streamable HTTP client that can talk either
directly over `reqwest` or through the executor HTTP runner without
duplicating MCP session logic higher in the stack. This PR adds that
client-side transport boundary so remote Streamable HTTP MCP can reuse
the same RMCP flow as the local path.
### What
- Add a shared `rmcp-client/src/streamable_http/` module with:
- `transport_client.rs` for the local-or-remote transport enum
- `local_client.rs` for the direct `reqwest` implementation
- `remote_client.rs` for the executor-backed implementation
- `common.rs` for the small shared Streamable HTTP helpers
- Teach `RmcpClient` to build Streamable HTTP transports in either local
or remote mode while keeping the existing OAuth ownership in RMCP.
- Translate remote POST, GET, and DELETE session operations into
executor `http/request` calls.
- Preserve RMCP session expiry handling and reconnect behavior for the
remote transport.
- Add remote transport coverage in
`rmcp-client/tests/streamable_http_remote.rs` and keep the shared test
support in `rmcp-client/tests/streamable_http_test_support.rs`.
### Verification
- `cargo check -p codex-rmcp-client`
- online CI
### Stack
1. #18581 protocol
2. #18582 runner
3. #18583 RMCP client
4. #18584 manager wiring and local/remote coverage
---------
Co-authored-by: Codex <noreply@openai.com>
### Why
Remote streamable HTTP MCP needs the executor to perform ordinary HTTP
requests on the executor side. This keeps network placement aligned with
`experimental_environment = "remote"` without adding MCP-specific
executor APIs.
### What
- Add an executor-side `http/request` runner backed by `reqwest`.
- Validate request method and URL scheme, preserving the transport
boundary at plain HTTP.
- Return buffered responses for ordinary calls and emit ordered
`http/request/bodyDelta` notifications for streaming responses.
- Register the request handler in the exec-server router.
- Document the runner entrypoint, conversion helpers, body-stream
bridge, notification sender, timeout behavior, and new integration-test
helpers.
- Add exec-server integration tests with the existing websocket harness
and a local TCP HTTP peer for buffered and streamed responses, with
comments spelling out what each test proves and its
setup/exercise/assert phases.
### Stack
1. #18581 protocol
2. #18582 runner
3. #18583 RMCP client
4. #18584 manager wiring and local/remote coverage
### Verification
- `just fmt`
- `cargo check -p codex-exec-server -p codex-rmcp-client --tests`
- `cargo check -p codex-core --test all` compile-only
- `git diff --check`
- Online full CI is running from the `full-ci` branch, including the
remote Rust test job.
Co-authored-by: Codex <noreply@openai.com>
---------
Co-authored-by: Codex <noreply@openai.com>
### Why
Remote streamable HTTP MCP needs a transport-shaped executor primitive
before the MCP client can move network I/O to the executor. This layer
keeps the executor unaware of MCP and gives later PRs an ordered
streaming surface for response bodies.
### What
- Add typed `http/request` and `http/request/bodyDelta` protocol
payloads.
- Add executor client helpers for buffered and streamed HTTP responses.
- Route body-delta notifications to request-scoped streams with sequence
validation and cleanup when a stream finishes or is dropped.
- Document the new protocol constants, transport structs, public client
methods, body-stream lifecycle, and request-scoped routing helpers.
- Add in-memory JSON-RPC client coverage for streamed HTTP response-body
notifications, with comments spelling out what the test proves and each
setup/exercise/assert phase.
### Stack
1. #18581 protocol
2. #18582 runner
3. #18583 RMCP client
4. #18584 manager wiring and local/remote coverage
### Verification
- `just fmt`
- `cargo check -p codex-exec-server -p codex-rmcp-client --tests`
- `cargo check -p codex-core --test all` compile-only
- `git diff --check`
- Online full CI is running from the `full-ci` branch, including the
remote Rust test job.
Co-authored-by: Codex <noreply@openai.com>
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
- Reject new exec-server client operations once the transport has
disconnected.
- Convert pending RPC calls into closed errors instead of synthetic
server errors.
- Cover pending read and later write behavior after remote executor
disconnect.
## Verification
- `just fmt`
- `cargo check -p codex-exec-server`
## Stack
```text
@ #18027 [6/6] Fail exec client operations after disconnect
│
o #18212 [5/6] Wire executor-backed MCP stdio
│
o #18087 [4/6] Abstract MCP stdio server launching
│
o #18020 [3/6] Add pushed exec process events
│
o #18086 [2/6] Support piped stdin in exec process API
│
o #18085 [1/6] Add MCP server environment config
│
o main
```
---------
Co-authored-by: Codex <noreply@openai.com>
Fixes stale test fixtures left after the active bundled model catalog
updates in #18586 and #18388. Those changes made `gpt-5.4` the current
default and removed several older hardcoded slugs, which left Windows
Bazel shards failing TUI and config tests.
What changed:
- Refresh TUI model migration, availability NUX, plan-mode, status, and
snapshot fixtures to use active bundled model slugs.
- Update the config edit test expectation for the TOML-quoted
`"gpt-5.2"` migration key.
- Move the model catalog tests into
`codex-rs/tui/src/app/tests/model_catalog.rs` so touching them does not
trip the blob-size policy for `app.rs`.
Verification:
- CI Bazel/lint checks are expected to cover the affected test shards.
- Replace the active models-manager catalog with the deleted core
catalog contents.
- Replace stale hardcoded test model slugs with current bundled model
slugs.
- Keep this as a stacked change on top of the cleanup PR.
## Summary
- Add the executor-backed RMCP stdio transport.
- Wire MCP stdio placement through the executor environment config.
- Cover local and executor-backed stdio paths with the existing MCP test
helpers.
## Stack
```text
o #18027 [6/6] Fail exec client operations after disconnect
│
@ #18212 [5/6] Wire executor-backed MCP stdio
│
o #18087 [4/6] Abstract MCP stdio server launching
│
o #18020 [3/6] Add pushed exec process events
│
o #18086 [2/6] Support piped stdin in exec process API
│
o #18085 [1/6] Add MCP server environment config
│
o main
```
---------
Co-authored-by: Codex <noreply@openai.com>
Adds max_context_window to model metadata and routes core context-window
reads through resolved model info. Config model_context_window overrides
are clamped to max_context_window when present; without an override, the
model context_window is used.
## Summary
- Move local MCP stdio process startup behind a launcher trait.
- Preserve existing local stdio behavior while making transport creation
explicit.
## Stack
```text
o #18027 [6/6] Fail exec client operations after disconnect
│
o #18212 [5/6] Wire executor-backed MCP stdio
│
@ #18087 [4/6] Abstract MCP stdio server launching
│
o #18020 [3/6] Add pushed exec process events
│
o #18086 [2/6] Support piped stdin in exec process API
│
o #18085 [1/6] Add MCP server environment config
│
o main
```
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
- Add a pushed `ExecProcessEvent` stream alongside retained
`process/read` output.
- Publish local and remote output, exit, close, and failure events.
- Cover the event stream with shared local/remote exec process tests.
## Testing
- `cargo check -p codex-exec-server`
- `cargo check -p codex-rmcp-client`
- Not run: `cargo test` per repo instruction; CI will cover.
## Stack
```text
o #18027 [6/6] Fail exec client operations after disconnect
│
o #18212 [5/6] Wire executor-backed MCP stdio
│
o #18087 [4/6] Abstract MCP stdio server launching
│
@ #18020 [3/6] Add pushed exec process events
│
o #18086 [2/6] Support piped stdin in exec process API
│
o #18085 [1/6] Add MCP server environment config
│
o main
```
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
- Add an explicit stdin mode to process/start.
- Keep normal non-interactive exec stdin closed while allowing
pipe-backed processes.
## Stack
```text
o #18027 [8/8] Fail exec client operations after disconnect
│
o #18025 [7/8] Cover MCP stdio tests with executor placement
│
o #18089 [6/8] Wire remote MCP stdio through executor
│
o #18088 [5/8] Add executor process transport for MCP stdio
│
o #18087 [4/8] Abstract MCP stdio server launching
│
o #18020 [3/8] Add pushed exec process events
│
@ #18086 [2/8] Support piped stdin in exec process API
│
o #18085 [1/8] Add MCP server environment config
│
o main
```
Co-authored-by: Codex <noreply@openai.com>
## Summary
- Add an MCP server environment setting with local as the default.
- Thread the default through config serialization, schema generation,
and existing config fixtures.
## Stack
```text
o #18027 [8/8] Fail exec client operations after disconnect
│
o #18025 [7/8] Cover MCP stdio tests with executor placement
│
o #18089 [6/8] Wire remote MCP stdio through executor
│
o #18088 [5/8] Add executor process transport for MCP stdio
│
o #18087 [4/8] Abstract MCP stdio server launching
│
o #18020 [3/8] Add pushed exec process events
│
o #18086 [2/8] Support piped stdin in exec process API
│
@ #18085 [1/8] Add MCP server environment config
│
o main
```
Co-authored-by: Codex <noreply@openai.com>
- Add trace-only wire logging for realtime websocket request/event text
payloads and the WebRTC call SDP request.
- Gate raw realtime logs behind
`RUST_LOG=codex_api::realtime_websocket::wire=trace` so normal logs stay
quiet.
---------
Co-authored-by: Codex <noreply@openai.com>
- Add outputModality to thread/realtime/start and wire text/audio output
selection through app-server, core, API, and TUI.\n- Rename the realtime
transcript delta notification and add a separate transcript done
notification that forwards final text from item done without correlating
it with deltas.
# 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.
Cap mirrored user text sent to realtime with the existing 300-token turn
budget while preserving the full model turn.
Adds integration coverage for capped realtime mirror payloads.
---------
Co-authored-by: Codex <noreply@openai.com>
- Let typed user messages submit while realtime is active and mirror
accepted text into the realtime text stream.
- Add integration coverage and snapshot for outbound realtime text.
Select Current Thread startup context by budget from newest turns, cap
each rendered turn at 300 approximate tokens, and add formatter plus
integration snapshot coverage.
# 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.
Encourages realtime prompt handling to delegate user requests to the
backend agent by default when repo inspection, commands, implementation,
or validation may help.
Co-authored-by: Codex <noreply@openai.com>
Builds on #17264.
- queues Realtime V2 `response.create` while an active response is open,
then flushes it after `response.done` or `response.cancelled`
- requests `response.create` after background agent final output and
steering acknowledgements
- adds app-server integration coverage for all `response.create` paths
Validation:
- `just fmt`
- `cargo check -p codex-app-server --tests`
- `git diff --check`
- CI green
---------
Co-authored-by: Codex <noreply@openai.com>
Stream Realtime V2 background agent updates while the background agent
task is still running, then send the final tool output when it
completes. User input during an active V2 handoff is acknowledged back
to realtime as a steering update.
Stack:
- Depends on #17278 for the background_agent rename.
- Depends on #17280 for the input task handler refactor.
Coverage:
- Adds an app-server integration regression test that verifies V2
progress is sent before the final function-call output.
Validation:
- just fmt
- cargo check -p codex-core
- cargo check -p codex-app-server --tests
- git diff --check
---------
Co-authored-by: Codex <noreply@openai.com>
Refactor the realtime input task select loop into named handlers for
user text, background agent output, realtime server events, and user
audio without changing the V2 behavior.
Stack:
- Depends on #17278 for the background_agent rename.
Validation:
- just fmt
- cargo check -p codex-core
- git diff --check
---------
Co-authored-by: Codex <noreply@openai.com>
Rename the Realtime V2 delegation tool and parser constant to
background_agent, and update the tool description and fixtures to match.
Validation: just fmt; cargo check -p codex-api; git diff --check
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
- omit serialized Responses instructions when an app-server base
instruction override is empty
- skip empty developer instruction messages and add v2 coverage for the
empty-override request shape
## Validation
- just fmt
- git diff --check
## Summary
- make realtime default to the v2 WebRTC path
- keep partial realtime config tables inheriting
`RealtimeConfig::default()`
## Validation
- CI found a stale config-test expectation; fixed in 974ba51bb3
- just fmt
- git diff --check
---------
Co-authored-by: Codex <noreply@openai.com>
- Default realtime sessions to v2 and gpt-realtime-1.5 when no override
is configured.
- Add Op::RealtimeConversationStart integration coverage and keep
v1-specific tests explicit.
---------
Co-authored-by: Codex <noreply@openai.com>
- Adds a core-owned realtime backend prompt template and preparation
path.
- Makes omitted realtime start prompts use the core default, while null
or empty prompts intentionally send empty instructions.
- Covers the core realtime path and app-server v2 path with integration
coverage.
---------
Co-authored-by: Codex <noreply@openai.com>
Ahmed Ibrahim