## Why
When using the Amazon Bedrock provider with `openai.gpt-5.4-cmb`, the
model picker allowed `xhigh` because the CMB catalog entry was derived
from the bundled `gpt-5.4` reasoning metadata. Bedrock rejects that
effort level, causing the request to fail before the turn can run:
```text
{"error":{"code":"validation_error","message":"Failed to deserialize the JSON body into the target type: Invalid 'reasoning': Invalid 'effort': unknown variant `xhigh`, expected one of `high`, `low`, `medium`, `minimal` at line 1 column 77239","param":null,"type":"invalid_request_error"}}
```
## What Changed
- Replace the runtime lookup of bundled `gpt-5.4` metadata for
`openai.gpt-5.4-cmb` with an explicit Bedrock CMB `ModelInfo` entry.
- Advertise only the Bedrock-supported CMB reasoning levels: `minimal`,
`low`, `medium`, and `high`.
- Keep the existing GPT OSS Bedrock model metadata and reasoning levels
unchanged.
- Add catalog coverage for the hardcoded CMB metadata and
Bedrock-compatible reasoning level list.
## Why
`openai.gpt-5.4-cmb` is served through the Amazon Bedrock provider,
whose request validator currently accepts `function` and `mcp` tool
specs but rejects Responses `custom` tools. The CMB catalog entry reuses
the bundled `gpt-5.4` metadata, which marks `apply_patch_tool_type` as
`freeform`. That causes Codex to include an `apply_patch` tool with
`type: "custom"`, so even heavily disabled sessions can fail before the
model runs with:
```text
Invalid tools: unknown variant `custom`, expected `function` or `mcp`
```
This is provider-specific: the model should still expose `apply_patch`,
but for Bedrock it needs to use the JSON/function tool shape instead of
the freeform/custom shape.
## What Changed
- Override the `openai.gpt-5.4-cmb` static catalog entry to set
`apply_patch_tool_type` to `function` after inheriting the rest of the
`gpt-5.4` model metadata.
- Update the catalog test expectation so the CMB entry continues to
track `gpt-5.4` metadata except for this Bedrock-specific tool shape
override.
## Verification
- `cargo test -p codex-model-provider`
- `just fix -p codex-model-provider`
## Why
`codex-models-manager` had grown to own provider-specific concerns:
constructing OpenAI-compatible `/models` requests, resolving provider
auth, emitting request telemetry, and deciding how provider catalogs
should be sourced. That made the manager harder to reuse for providers
whose model catalog is not fetched from the OpenAI `/models` endpoint,
such as Amazon Bedrock.
This change moves provider-specific model discovery behind
provider-owned implementations, so the models manager can focus on
refresh policy, cache behavior, picker ordering, and model metadata
merging.
## What Changed
- Introduced a `ModelsManager` trait with separate `OpenAiModelsManager`
and `StaticModelsManager` implementations.
- Added `ModelsEndpointClient` so OpenAI-compatible HTTP fetching lives
outside `codex-models-manager`.
- Moved `/models` request construction, provider auth resolution,
timeout handling, and request telemetry into `codex-model-provider` via
`OpenAiModelsEndpoint`.
- Added provider-owned `models_manager(...)` construction so configured
OpenAI-compatible providers use `OpenAiModelsManager`, while
static/catalog-backed providers can return `StaticModelsManager`.
- Added an Amazon Bedrock static model catalog for the GPT OSS Bedrock
model IDs.
- Updated core/session/thread manager code and tests to depend on
`Arc<dyn ModelsManager>`.
- Moved offline model test helpers into
`codex_models_manager::test_support`.
## Metadata References
The Bedrock catalog metadata is based on the official Amazon Bedrock
OpenAI model documentation:
- [Amazon Bedrock OpenAI
models](https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-openai.html)
lists the Bedrock model IDs, text input/output modalities, and `128,000`
token context window for `gpt-oss-20b` and `gpt-oss-120b`.
- [Amazon Bedrock `gpt-oss-120b` model
card](https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-oss-120b.html)
lists the `bedrock-runtime` model ID `openai.gpt-oss-120b-1:0`, the
`bedrock-mantle` model ID `openai.gpt-oss-120b`, text-only modalities,
and `128K` context window.
- [OpenAI `gpt-oss-120b` model
docs](https://developers.openai.com/api/docs/models/gpt-oss-120b)
document configurable reasoning effort with `low`, `medium`, and `high`,
plus text input/output modality.
The display names, default reasoning effort, and priority ordering are
Codex-local catalog choices.
## Test Plan
- Manually verified app-server model listing with an AWS profile:
```shell
CODEX_HOME="$(mktemp -d)" cargo run -p codex-app-server-test-client -- \
--codex-bin ./target/debug/codex \
-c 'model_provider="amazon-bedrock"' \
-c 'model_providers.amazon-bedrock.aws.profile="codex-bedrock"' \
-c 'model_providers.amazon-bedrock.aws.region="us-west-2"' \
model-list
```
The response returned the Bedrock catalog with `openai.gpt-oss-120b-1:0`
as the default model and `openai.gpt-oss-20b-1:0` as the second listed
model, both text-only and supporting low/medium/high reasoning effort.
## Why
AWS/Bedrock mode currently reports `account: null` with
`requiresOpenaiAuth: false` from `account/read`. That suppresses the
OpenAI-auth requirement, but it does not let app clients distinguish AWS
auth from any other non-OpenAI custom provider. For the prototype AWS
provider UX, clients need a simple provider-derived signal so they can
suppress ChatGPT/API-key login and token-refresh paths without
hardcoding Bedrock checks.
## What changed
- Adds an `aws` variant to the v2 `Account` protocol union.
- Adds `ProviderAccountKind` to `codex-model-provider` so the runtime
provider owns the app-visible account classification.
- Makes Amazon Bedrock return `ProviderAccountKind::Aws` from the
model-provider layer.
- Updates app-server `account/read` to map `ProviderAccountKind` to the
existing `GetAccountResponse` wire shape.
- Preserves the existing `account: null, requiresOpenaiAuth: false`
behavior for other non-OpenAI providers.
- Regenerates the app-server protocol schema fixtures.
- Adds coverage for provider account classification and for the Amazon
Bedrock `account/read` response.
## Testing
- `cargo test -p codex-model-provider`
- `cargo test -p codex-app-server-protocol`
- `cargo test -p codex-app-server get_account_with_aws_provider`
## Notes
I attempted `just bazel-lock-update` and `just bazel-lock-check`, but
both are blocked in my local environment because `bazel` is not
installed.
## Summary
The Bedrock Mantle SigV4 auth provider currently looks like it can
lazily load `AwsAuthContext`, but the provider is only constructed after
`resolve_auth_method` has already loaded that context. Because
`with_context` always pre-populates the `OnceCell`, the
`get_or_try_init` fallback is unused in normal operation and makes the
provider lifecycle harder to reason about.
This change removes that dead lazy-loading path and makes the actual
behavior explicit:
- `BedrockAuthMethod::AwsSdkAuth` carries only the resolved
`AwsAuthContext`.
- `BedrockMantleSigV4AuthProvider` stores the resolved context directly.
- request signing uses the stored context without going through
`OnceCell`.
The existing eager AWS auth resolution behavior is unchanged; this is a
simplification of the provider state, not a behavior change.
## Testing
- `cargo shear`
- `cargo test -p codex-model-provider`
- `just bazel-lock-check`
## Summary
Add first-class Amazon Bedrock Mantle provider support so Codex can keep
using its existing Responses API transport with OpenAI-compatible
AWS-hosted endpoints such as AOA/Mantle.
This is needed for the AWS launch path, where provider traffic should
authenticate with AWS credentials instead of OpenAI bearer credentials.
Requests are authenticated immediately before transport send, so SigV4
signs the final method, URL, headers, and body bytes that `reqwest` will
send.
## What Changed
- Added a new `codex-aws-auth` crate for loading AWS SDK config,
resolving credentials, and signing finalized HTTP requests with AWS
SigV4.
- Added a built-in `amazon-bedrock` provider that targets Bedrock Mantle
Responses endpoints, defaults to `us-east-1`, supports region/profile
overrides, disables WebSockets, and does not require OpenAI auth.
- Added Amazon Bedrock auth resolution in `codex-model-provider`: prefer
`AWS_BEARER_TOKEN_BEDROCK` when set, otherwise use AWS SDK credentials
and SigV4 signing.
- Added `AuthProvider::apply_auth` and `Request::prepare_body_for_send`
so request-signing providers can sign the exact outbound request after
JSON serialization/compression.
- Determine the region by taking the `aws.region` config first (required
for bearer token codepath), and fallback to SDK default region.
## Testing
Amazon Bedrock Mantle Responses paths:
- Built the local Codex binary with `cargo build`.
- Verified the custom proxy-backed `aws` provider using `env_key =
"AWS_BEARER_TOKEN_BEDROCK"` streamed raw `responses` output with
`response.output_text.delta`, `response.completed`, and `mantle-env-ok`.
- Verified a full `codex exec --profile aws` turn returned
`mantle-env-ok`.
- Confirmed the custom provider used the bearer env var, not AWS profile
auth: bogus `AWS_PROFILE` still passed, empty env var failed locally,
and malformed env var reached Mantle and failed with `401
invalid_api_key`.
- Verified built-in `amazon-bedrock` with `AWS_BEARER_TOKEN_BEDROCK` set
passed despite bogus AWS profiles, returning `amazon-bedrock-env-ok`.
- Verified built-in `amazon-bedrock` SDK/SigV4 auth passed with
`AWS_BEARER_TOKEN_BEDROCK` unset and temporary AWS session env
credentials, returning `amazon-bedrock-sdk-env-ok`.
## Summary
This PR fully reverts the previously merged Agent Identity runtime
integration from the old stack:
https://github.com/openai/codex/pull/17387/changes
It removes the Codex-side task lifecycle wiring, rollout/session
persistence, feature flag plumbing, lazy `auth.json` mutation,
background task auth paths, and request callsite changes introduced by
that stack.
This leaves the repo in a clean pre-AgentIdentity integration state so
the follow-up PRs can reintroduce the pieces in smaller reviewable
layers.
## Stack
1. This PR: full revert
2. https://github.com/openai/codex/pull/18871: move Agent Identity
business logic into a crate
3. https://github.com/openai/codex/pull/18785: add explicit
AgentIdentity auth mode and startup task allocation
4. https://github.com/openai/codex/pull/18811: migrate auth callsites
through AuthProvider
## Testing
Tests: targeted Rust checks, cargo-shear, Bazel lock check, and CI.
## Summary
This is the AgentAssertion downstream slice for feature-gated agent
identity support, replacing the oversized AgentAssertion slice from PR
#17807.
It isolates task-scoped downstream AgentAssertion wiring on top of the
merged PR3.1 work without re-carrying the earlier agent registration,
task registration, or task-state history.
This PR includes the task-scoped bug-fix call sites from the review:
generic file upload auth, MCP OpenAI file upload auth, and ARC monitor
auth. Broader user/control-plane calls move to PR4.1 and PR4.2.
## Stack
- PR1: https://github.com/openai/codex/pull/17385 - add
`features.use_agent_identity`
- PR2: https://github.com/openai/codex/pull/17386 - register agent
identities when enabled
- PR3: https://github.com/openai/codex/pull/17387 - register agent tasks
when enabled
- PR3.1: https://github.com/openai/codex/pull/17978 - persist and
prewarm registered tasks per thread
- PR4: this PR - use task-scoped `AgentAssertion` downstream when
enabled
- PR4.1: https://github.com/openai/codex/pull/18094 - introduce
AuthManager-owned background/control-plane `AgentAssertion` auth
- PR4.2: https://github.com/openai/codex/pull/18260 - use background
task auth for additional backend/control-plane calls
## What Changed
- add AgentAssertion envelope generation in `codex-core`
- route downstream HTTP and websocket auth through AgentAssertion when
an agent task is present
- extend the model-provider auth provider so non-bearer authorization
schemes can be passed through cleanly
- make generic file uploads attach the full authorization header value
- make MCP OpenAI file uploads use the cached thread agent task
assertion when present
- make ARC monitor calls use the cached thread agent task assertion when
present
## Why
The original PR had drifted ancestry and showed a much larger diff than
the semantic change actually required. Restacking it onto PR3.1 keeps
the reviewable surface down to the downstream assertion slice.
## Validation
- `just fmt`
- `cargo check -p codex-core -p codex-login -p codex-analytics -p
codex-app-server -p codex-cloud-requirements -p codex-cloud-tasks -p
codex-models-manager -p codex-chatgpt -p codex-model-provider -p
codex-mcp -p codex-core-skills`
- `cargo test -p codex-model-provider bearer_auth_provider`
- `cargo test -p codex-core agent_assertion`
- `cargo test -p codex-app-server remote_control`
- `cargo test -p codex-cloud-requirements fetch_cloud_requirements`
- `cargo test -p codex-models-manager manager::tests`
- `cargo test -p codex-chatgpt`
- `cargo test -p codex-cloud-tasks`
- `cargo test -p codex-login agent_identity`
- `just fix -p codex-core -p codex-login -p codex-analytics -p
codex-app-server -p codex-cloud-requirements -p codex-cloud-tasks -p
codex-models-manager -p codex-chatgpt -p codex-model-provider -p
codex-mcp -p codex-core-skills`
- `just fix -p codex-app-server`
- `git diff --check`
## Summary
- Add `codex-model-provider` as the runtime home for model-provider
behavior that does not belong in `codex-core`, `codex-login`, or
`codex-api`.
- The new crate wraps configured `ModelProviderInfo` in a
`ModelProvider` trait object that can resolve the API provider config,
provider-scoped auth manager, and request auth provider for each call.
- This centralizes provider auth behavior in one place today, and gives
us an extension point for future provider-specific auth, model listing,
request setup, and related runtime behavior.
## Tests
Ran tests manually to make sure that provider auth under different
configs still work as expected.
---------
Co-authored-by: pakrym-oai <pakrym@openai.com>
Celia Chen ·
efrazer-oai ·
Adrian ·