9 Commits

• [tool search] support namespaced deferred dynamic tools (#18413)

  Deferred dynamic tools need to round-trip a namespace so a tool returned
  by `tool_search` can be called through the same registry key that core
  uses for dispatch.
  
  This change adds namespace support for dynamic tool specs/calls,
  persists it through app-server thread state, and routes dynamic tool
  calls by full `ToolName` while still sending the app the leaf tool name.
  Deferred dynamic tools must provide a namespace; non-deferred dynamic
  tools may remain top-level.
  
  It also introduces `LoadableToolSpec` as the shared
  function-or-namespace Responses shape used by both `tool_search` output
  and dynamic tool registration, so dynamic tools use the same wrapping
  logic in both paths.
  
  Validation:
  - `cargo test -p codex-tools`
  - `cargo test -p codex-core tool_search`
  
  ---------
  
  Co-authored-by: Sayan Sisodiya <sayan@openai.com>

  pash-openai · 2026-04-21 14:13:08 +08:00
  dc1a8f2190
• Update image outputs to default to high detail (#18386)

  Do not assume the default `detail`.

  pakrym-oai · 2026-04-18 11:01:12 -07:00
  53b1570367
• Stabilize Bazel tests (timeout tweaks and flake fixes) (#17791)
  David de Regt · 2026-04-16 07:57:51 -07:00
  6adba99f4d
• dynamic tool calls: add param exposeToContext to optionally hide tool (#14501)

  This extends dynamic_tool_calls to allow us to hide a tool from the
  model context but still use it as part of the general tool calling
  runtime (for ex from js_repl/code_mode)

  Channing Conger · 2026-03-14 01:58:43 -07:00
  70eddad6b0
• Enforce single tool output type in codex handlers (#14157)

  We'll need to associate output schema with each tool. Each tool can only
  have on output type.

  pakrym-oai · 2026-03-09 21:49:44 -07:00
  d71e042694
• Add under-development original-resolution view_image support (#13050)

  ## Summary
  
  Add original-resolution support for `view_image` behind the
  under-development `view_image_original_resolution` feature flag.
  
  When the flag is enabled and the target model is `gpt-5.3-codex` or
  newer, `view_image` now preserves original PNG/JPEG/WebP bytes and sends
  `detail: "original"` to the Responses API instead of using the legacy
  resize/compress path.
  
  ## What changed
  
  - Added `view_image_original_resolution` as an under-development feature
  flag.
  - Added `ImageDetail` to the protocol models and support for serializing
  `detail: "original"` on tool-returned images.
  - Added `PromptImageMode::Original` to `codex-utils-image`.
    - Preserves original PNG/JPEG/WebP bytes.
    - Keeps legacy behavior for the resize path.
  - Updated `view_image` to:
  - use the shared `local_image_content_items_with_label_number(...)`
  helper in both code paths
    - select original-resolution mode only when:
      - the feature flag is enabled, and
      - the model slug parses as `gpt-5.3-codex` or newer
  - Kept local user image attachments on the existing resize path; this
  change is specific to `view_image`.
  - Updated history/image accounting so only `detail: "original"` images
  use the docs-based GPT-5 image cost calculation; legacy images still use
  the old fixed estimate.
  - Added JS REPL guidance, gated on the same feature flag, to prefer JPEG
  at 85% quality unless lossless is required, while still allowing other
  formats when explicitly requested.
  - Updated tests and helper code that construct
  `FunctionCallOutputContentItem::InputImage` to carry the new `detail`
  field.
  
  ## Behavior
  
  ### Feature off
  - `view_image` keeps the existing resize/re-encode behavior.
  - History estimation keeps the existing fixed-cost heuristic.
  
  ### Feature on + `gpt-5.3-codex+`
  - `view_image` sends original-resolution images with `detail:
  "original"`.
  - PNG/JPEG/WebP source bytes are preserved when possible.
  - History estimation uses the GPT-5 docs-based image-cost calculation
  for those `detail: "original"` images.
  
  
  #### [git stack](https://github.com/magus/git-stack-cli)
  - 👉 `1` https://github.com/openai/codex/pull/13050
  - ⏳ `2` https://github.com/openai/codex/pull/13331
  - ⏳ `3` https://github.com/openai/codex/pull/13049

  Curtis 'Fjord' Hawthorne · 2026-03-03 15:56:54 -08:00
  b92146d48b
• feat(app-server): add ThreadItem::DynamicToolCall (#12732)

  Previously, clients would call `thread/start` with dynamic_tools set,
  and when a model invokes a dynamic tool, it would just make the
  server->client `item/tool/call` request and wait for the client's
  response to complete the tool call. This works, but it doesn't have an
  `item/started` or `item/completed` event.
  
  Now we are doing this:
  - [new] emit `item/started` with `DynamicToolCall` populated with the
  call arguments
  - send an `item/tool/call` server request
  - [new] once the client responds, emit `item/completed` with
  `DynamicToolCall` populated with the response.
  
  Also, with `persistExtendedHistory: true`, dynamic tool calls are now
  reconstructable in `thread/read` and `thread/resume` as
  `ThreadItem::DynamicToolCall`.

  Owen Lin · 2026-02-25 12:00:10 -08:00
  a0fd94bde6
• feat(app-server, core): allow text + image content items for dynamic tool outputs (#10567)

  Took over the work that @aaronl-openai started here:
  https://github.com/openai/codex/pull/10397
  
  Now that app-server clients are able to set up custom tools (called
  `dynamic_tools` in app-server), we should expose a way for clients to
  pass in not just text, but also image outputs. This is something the
  Responses API already supports for function call outputs, where you can
  pass in either a string or an array of content outputs (text, image,
  file):
  https://platform.openai.com/docs/api-reference/responses/create#responses_create-input-input_item_list-item-function_tool_call_output-output-array-input_image
  
  So let's just plumb it through in Codex (with the caveat that we only
  support text and image for now). This is implemented end-to-end across
  app-server v2 protocol types and core tool handling.
  
  ## Breaking API change
  NOTE: This introduces a breaking change with dynamic tools, but I think
  it's ok since this concept was only recently introduced
  (https://github.com/openai/codex/pull/9539) and it's better to get the
  API contract correct. I don't think there are any real consumers of this
  yet (not even the Codex App).
  
  Old shape:
  `{ "output": "dynamic-ok", "success": true }`
  
  New shape:
  ```
  {
      "contentItems": [
        { "type": "inputText", "text": "dynamic-ok" },
        { "type": "inputImage", "imageUrl": "data:image/png;base64,AAA" }
      ]
    "success": true
  }
  ```

  Owen Lin · 2026-02-04 16:12:47 -08:00
  5ea107a088
• feat: dynamic tools injection (#9539)

  ## Summary
  Add dynamic tool injection to thread startup in API v2, wire dynamic
  tool calls through the app server to clients, and plumb responses back
  into the model tool pipeline.
  
  ### Flow (high level)
  - Thread start injects `dynamic_tools` into the model tool list for that
  thread (validation is done here).
  - When the model emits a tool call for one of those names, core raises a
  `DynamicToolCallRequest` event.
  - The app server forwards it to the client as `item/tool/call`, waits
  for the client’s response, then submits a `DynamicToolResponse` back to
  core.
  - Core turns that into a `function_call_output` in the next model
  request so the model can continue.
  
  ### What changed
  - Added dynamic tool specs to v2 thread start params and protocol types;
  introduced `item/tool/call` (request/response) for dynamic tool
  execution.
  - Core now registers dynamic tool specs at request time and routes those
  calls via a new dynamic tool handler.
  - App server validates tool names/schemas, forwards dynamic tool call
  requests to clients, and publishes tool outputs back into the session.
  - Integration tests

  jif-oai · 2026-01-26 10:06:44 +00:00
  d594693d1a