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11
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
  AdrianandGitHub
|
51864b0b4b |
feat: use run agent task auth for inference (#19051)
## Stack This is PR 3 of the simplified HAI single-run-task stack: - [#19047](https://github.com/openai/codex/pull/19047) Agent Identity assertion and task-registration primitives, including the shared run-task helper used by existing Agent Identity JWT auth. - [#19049](https://github.com/openai/codex/pull/19049) Disabled-by-default ChatGPT auth opt-in that provisions/reuses persisted Agent Identity runtime auth and its single run task. - [#19051](https://github.com/openai/codex/pull/19051) Run-scoped provider auth that uses one backend-owned task id for first-party inference and compaction requests. [#19054](https://github.com/openai/codex/pull/19054) collapsed out of the active stack because the simplified design no longer needs a separate background/control-plane task helper. ## Summary This PR moves Agent Identity usage into provider auth resolution. That keeps `AgentAssertion` auth tied to first-party OpenAI provider requests instead of applying a late session-wide override that could affect local, custom, Bedrock, API-key, or external-bearer providers. What changed: - adds a small `ProviderAuthScope` struct carrying the run auth policy and session source needed by provider-scoped auth resolution - lets `Session` opt the existing `ModelClient` into `ChatGptAuth` policy when `use_agent_identity` is enabled, without adding a second model-client constructor - resolves Agent Identity only for first-party OpenAI provider auth paths - uses the persisted run task id from the `AgentIdentityAuth` record to build `AgentAssertion` auth for Responses requests - routes shared request setup through scoped provider auth so unary compact requests use the same run-task assertion path as inference turns - keeps local/custom/Bedrock/env-key/external-bearer provider auth unchanged - lets missing run-task state surface through the existing model-request error path instead of silently falling back to bearer auth This PR intentionally does not create thread-scoped, target-scoped, or background-scoped task identities. The run task is the only task Codex registers in this POC shape. ## Testing - `just test -p codex-model-provider` - `just test -p codex-core client::tests::provider_auth_scope_uses` - `just test -p codex-core remote_compact_uses_agent_identity_assertion` |
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 Ahmed IbrahimandGitHub
|
f8937b7d86 |
Represent MCP authentication with an enum (#29924)
## Why MCP authentication has distinct OAuth and ChatGPT-session flows. Representing that choice as `use_chatgpt_auth` makes one flow implicit and allows the configuration model to express the distinction only through a boolean. ChatGPT credential forwarding also needs a first-party trust boundary. A configurable `chatgpt_base_url` controls routing, but must not grant an MCP server permission to receive session credentials. This change builds on #29733, where the boolean was introduced. ## What changed - Replace `use_chatgpt_auth` with an `auth` field backed by the exhaustive `McpServerAuth` enum. - Support `auth = "oauth"` and `auth = "chatgpt"`, with OAuth remaining the default. - Trust only the origin derived from the existing hardcoded `CHATGPT_CODEX_BASE_URL` when granting ChatGPT auth to an MCP server. - Keep configured bearer tokens and authorization headers ahead of the selected authentication flow. - Update config writers, schema output, fixtures, and integration-test setup to use the enum. ## Verification Integration coverage exercises the complete streamable HTTP startup path in two independent configurations: - A directly constructed MCP configuration verifies that matching an overridden `chatgpt_base_url` does not grant ChatGPT auth. - A persisted `config.toml` containing an attacker-controlled `chatgpt_base_url` and `auth = "chatgpt"` verifies the same boundary through normal config parsing. Both tests complete MCP initialization and tool listing and assert that the full captured request sequence contains no authorization headers. Separate integration coverage verifies that configured authorization takes precedence over ChatGPT auth. |
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 Adam Perry @ OpenAIandGitHub
|
5a56caf18c |
[codex] Remove async_trait from first-party code (#27475)
## Why First-party async traits should expose their `Send` contracts explicitly without requiring `async_trait`. This completes the migration pattern established in #27303 and #27304. ## What changed - Replaced the remaining first-party `async_trait` traits with native return-position `impl Future + Send` where statically dispatched and explicit boxed `Send` futures where object safety is required. - Kept implementations behavior-preserving, outlining existing async bodies into inherent methods where that keeps the diff reviewable. - Removed all direct first-party `async-trait` dependencies and the workspace dependency declaration. - Added a cargo-deny policy that permits `async-trait` only through the remaining transitive wrapper crates. - Updated `rand` from 0.8.5 to 0.8.6 to resolve RUSTSEC-2026-0097 and keep the full cargo-deny check passing. ## Validation - `just test -p codex-exec-server`: 216 passed, 2 skipped. - `just test -p codex-model-provider`: 39 passed. - `just test -p codex-core` and `just test`: changed tests passed; remaining failures are environment-sensitive suites unrelated to this migration. - `cargo deny check` - `just fix` - `just fmt` - `cargo shear` - `just bazel-lock-check` |
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 Celia ChenandGitHub
|
f8fe96d548 |
feat: disable capabilities by model provider (#19442)
## Why Unsupported features must fail closed and Codex must not expose OpenAI-hosted fallback paths when the active provider cannot support them. In practice, Bedrock should not surface app connectors, MCP servers, tool search/suggestions, image generation, web search, or JS REPL until those paths are explicitly supported for that provider. This PR moves that decision into provider-owned capability metadata instead of scattering Bedrock-specific checks across callers. ## What changed - Adds `ProviderCapabilities` to `codex-model-provider`, with default support for existing providers and a Bedrock override that disables unsupported launch surfaces. - Adds `ToolCapabilityBounds` to `codex-tools` so provider capability limits can clamp otherwise-enabled tool config. - Applies capability bounds when building session and review-thread tool config. - Routes MCP/app connector configuration through `McpManager::mcp_config`, which filters configured MCP servers and app connectors based on the active provider. - Updates app-server MCP list/read paths to use the filtered MCP config. - Adds coverage for default provider capabilities, Bedrock disabled capabilities, and optional tool-surface clamping. ## Testing built locally and verified that bedrock responses api now return without errors calling unsupported tools. |
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Celia ChenandGitHub
|
e8d8080818 |
feat: let model providers own model discovery (#18950)
## 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. |
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Celia ChenandGitHub
|
432771c5fd |
feat: expose AWS account state from account/read (#19048)
## 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. |
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 efrazer-oaiandGitHub
|
5882f3f95e |
refactor: route Codex auth through AuthProvider (#18811)
## Summary This PR moves Codex backend request authentication from direct bearer-token handling to `AuthProvider`. The new `codex-auth-provider` crate defines the shared request-auth trait. `CodexAuth::provider()` returns a provider that can apply all headers needed for the selected auth mode. This lets ChatGPT token auth and AgentIdentity auth share the same callsite path: - ChatGPT token auth applies bearer auth plus account/FedRAMP headers where needed. - AgentIdentity auth applies AgentAssertion plus account/FedRAMP headers where needed. Reference old stack: https://github.com/openai/codex/pull/17387/changes ## Callsite Migration | Area | Change | | --- | --- | | backend-client | accepts an `AuthProvider` instead of a raw token/header | | chatgpt client/connectors | applies auth through `CodexAuth::provider()` | | cloud tasks | keeps Codex-backend gating, applies auth through provider | | cloud requirements | uses Codex-backend auth checks and provider headers | | app-server remote control | applies provider headers for backend calls | | MCP Apps/connectors | gates on `uses_codex_backend()` and keys caches from generic account getters | | model refresh | treats AgentIdentity as Codex-backend auth | | OpenAI file upload path | rejects non-Codex-backend auth before applying headers | | core client setup | keeps model-provider auth flow and allows AgentIdentity through provider-backed OpenAI auth | ## Stack 1. https://github.com/openai/codex/pull/18757: full revert 2. https://github.com/openai/codex/pull/18871: isolated Agent Identity crate 3. https://github.com/openai/codex/pull/18785: explicit AgentIdentity auth mode and startup task allocation 4. This PR: migrate Codex backend auth callsites through AuthProvider 5. https://github.com/openai/codex/pull/18904: accept AgentIdentity JWTs and load `CODEX_AGENT_IDENTITY` ## Testing Tests: targeted Rust checks, cargo-shear, Bazel lock check, and CI. |
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Celia ChenandGitHub
|
1cd3ad1f49 |
feat: add AWS SigV4 auth for OpenAI-compatible model providers (#17820)
## 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`. |
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|
efrazer-oaiandGitHub
|
be75785504 |
fix: fully revert agent identity runtime wiring (#18757)
## 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. |
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AdrianandGitHub
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b44d2851cf |
[codex] Use AgentAssertion downstream behind use_agent_identity (#17980)
## 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` |
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|
a803790a10 |
feat: add opt-in provider runtime abstraction (#17713)
## 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> |