## Why
This PR adds a configurable `<context_window_guidance>` developer
section immediately after `<context_window>`. Harness integrations need
this section to give the model deployment-specific instructions for
preparing for context-window transitions.
## What changed
- Add an optional `features.token_budget.guidance_message` config with a
1,000-byte runtime cap and generated schema support.
- Render configured guidance as a developer `ContextualUserFragment`
wrapped in `<context_window_guidance>` immediately after
`<context_window>`.
- Omit the section when guidance is unset, empty, or whitespace-only.
- Preserve the resolved value in config locks and classify persisted
guidance as contextual developer content.
- Add integration coverage for rendered content and ordering.
Token-budget initial context carries thread and context-window lineage
that the model should treat as one structured context-window block.
Wrapping it in `<context_window>` makes that boundary explicit while
preserving the existing window id content.
Before this change, the window identifiers were injected as an untagged
developer text fragment:
```text
Thread id <THREAD_ID>.
First context window id: <FIRST_WINDOW_ID>
Current context window id: <WINDOW_ID>
Previous context window id: <PREVIOUS_WINDOW_ID>
```
After this change, the same payload is wrapped as a context-window
block:
```text
<context_window>
Thread id: <THREAD_ID>
First context window id: <FIRST_WINDOW_ID>
Current context window id: <WINDOW_ID>
Previous context window id: <PREVIOUS_WINDOW_ID>
</context_window>
```
This adds shared `CONTEXT_WINDOW_*_TAG` protocol constants, updates
`TokenBudgetContext` to render with those markers, treats the new
wrapper as contextual developer content when mapping history, and
refreshes the token-budget request-shape assertions and snapshot.
Verification:
- `just test -p codex-core token_budget`
- `just test -p codex-core
recognizes_context_window_as_contextual_developer_content`
## Why
The token-budget feature currently adds remaining-token messages
whenever usage crosses the 25%, 50%, and 75% thresholds. Those periodic
inserts create prompt churn without requiring action, while the
near-compaction reminder and explicit `get_context_remaining` tool
already cover actionable and on-demand budget information.
The context-window lineage block is also easier to scan as plain labeled
text than as a `<token_budget>`-wrapped fragment.
## What changed
- Stop recording automatic remaining-token messages at percentage
thresholds.
- Render context-window lineage in `First`, `Current`, `Previous` order
with colon-separated labels.
- Omit the `Previous` line for the first context window.
- Remove `<token_budget>` wrappers from newly rendered lineage,
near-compaction reminders, and `get_context_remaining` output.
- Keep recognizing legacy wrapped fragments so existing rollouts remain
compatible.
- Remove the post-sampling token snapshot that was only needed by the
periodic threshold path.
## Testing
- `just test -p codex-core token_budget` (11 tests passed)
## Why
Multi-agent v2 currently carries an explicit-request-only delegation
rule in its static usage hint. That provides a safe default, but it
prevents clients from selecting proactive delegation per turn without
changing static guidance or rewriting prior model context.
This change makes delegation mode a session selection that can be
updated through `turn/start`, while deriving the effective model-visible
mode separately for each turn. Eligible multi-agent v2 turns remain
explicit-request-only unless proactive mode is both selected and
enabled.
## What changed
- Add the experimental `turn/start.multiAgentMode` parameter with
`explicitRequestOnly` and `proactive` values. Omission retains the
loaded session's current optional selection.
- Add the default-off `features.multi_agent_mode` feature gate. Eligible
multi-agent v2 turns use the selected mode when enabled; an unset
selection or disabled gate resolves to `explicitRequestOnly`.
- Treat mode prompting as inapplicable for multi-agent v1 and other
unsupported session configurations, producing no multi-agent mode
developer message rather than rejecting the turn.
- Move the explicit-request-only rule out of the static v2 usage hint
and into a bounded, tagged developer context fragment.
- Emit the effective mode in initial context and only when that
effective mode changes on later turns.
- Persist the effective mode in `TurnContextItem` as the durable
baseline for resume and context-update comparisons.
Historical rollout items are not rewritten. Later mode developer
messages establish the current rule incrementally.
## Not covered
- Initial selection through `thread/start` and selected-mode reporting
from thread lifecycle/settings APIs; those are isolated in the stacked
#28792.
- A TUI control or slash command for selecting the mode.
- Persisting a preferred mode to `config.toml`; selection remains
session/turn scoped.
- Changes to multi-agent concurrency limits, tool availability, or model
catalog capability declarations.
- Rewriting historical rollout prompt items. Cold resume restores the
latest persisted effective mode when available while leaving historical
developer messages intact.
## Verification
- `CARGO_INCREMENTAL=0 just test -p codex-core multi_agent_mode`
- Focused app-server coverage verifies that `turn/start.multiAgentMode`
produces proactive developer instructions for an eligible v2 turn.
## Stack
Followed by #28792, which adds `thread/start` initialization and
lifecycle/settings observability.
## Stack
Depends on #28746. This PR implements shared rollout-budget accounting
and model-visible reminders using the configuration defined in #28746.
# Description / Main changes to Core:
`AgentControl` will now be the area where "rollout level" features &
accounting will have to live. It is incorrectly named for this
responsibility, but I think it can hold all the necessary shared state &
features (rollout token budget, mutliple thread interruption
responsibilitym etc)
In this PR, we have one "token ledger" that each thread will subtract
from when sampling. The "charge" will occur when response.completed() is
done and the calculation will be done on the responses api usage
carrier. The calculation will weigh sampling and pre-fill tokens as
specified.
Every time the budget crosses the configured reminder threshold, a
developer message is appended before the thread's next request
This remaining budget will _always_ be restated/reminded after a
compaction event.
Expiration and fan-out interruption will be in the stacked follow-up
(and also live in Agent Control).
## Reminders
"You have weighted {session_tokens_left} tokens left in the shared
session token budget."
The first request in each thread context receives the current remainder.
Later reminders are emitted after aggregate weighted usage crosses a
configured interval. If several intervals are crossed before a thread
sends another request, Core inserts one reminder with the latest
remainder.
Compaction response usage is charged before the next context starts. The
next reminder is appended after the compaction summary, leaving the
initial context content stable.
## Tests
Integration coverage verifies:
- weighted output and non-cached input accounting
- initial and periodic reminders
- shared accounting between a root and sub-agent
- post-compaction remainder and message placement
Local checks:
- `just fmt`
- `just test -p codex-core rollout_budget`
- `git diff --check`
The full workspace test suite was not run locally.
## Why
`ResponseItem` variants do not have a consistent internal ID shape: some
variants carry required IDs, some carry optional IDs, and some cannot
represent an ID at all. The existing fields also use inconsistent serde,
TypeScript, and JSON-schema annotations. A single enum-level access path
is needed before history recording can assign and retain IDs.
This PR establishes that internal model only. It intentionally does not
generate or serialize IDs; allocation and wire persistence are isolated
in the stacked follow-up.
## What changed
- Give every concrete `ResponseItem` variant an `Option<String>` ID
field.
- Apply the same internal-only annotations to every ID field:
`#[serde(default, skip_serializing)]`, `#[ts(skip)]`, and
`#[schemars(skip)]`.
- Add `ResponseItem::id()` and `ResponseItem::set_id()` as the shared
accessors.
- Preserve IDs when history items are rewritten for truncation.
- Adapt consumers that previously assumed reasoning and image-generation
IDs were required.
- Regenerate app-server schemas so the hidden fields are represented
consistently.
The serde catch-all `ResponseItem::Other` remains ID-less because it
must remain a unit variant.
## Test plan
- `cargo check --tests -p codex-core -p codex-api -p codex-rollout-trace
-p codex-image-generation-extension`
- `just test -p codex-protocol`
- `just test -p codex-app-server-protocol`
- `just test -p codex-api -p codex-rollout-trace -p
codex-image-generation-extension`
- `just test -p codex-core event_mapping`
## Description
This PR adds an optional `metadata` field to `ResponseItem` for
Responses API calls. Only mechanical plumbing, no actual values
populated and sent yet. Turns out just adding a new field to
`ResponseItem` has quite a large blast radius already.
This change is backwards compatible because `metadata` is optional and
omitted when absent, so existing response items and rollout history
without it still deserialize and requests that do not set it keep the
same wire shape. For provider compatibility, we strip out `metadata`
before non-OpenAI Responses requests so Azure and AWS Bedrock never see
this field.
My followup PR here will actually make use of it to start storing and
passing along `turn_id`: https://github.com/openai/codex/pull/28360
## What changed
- Added `ResponseItemMetadata` with optional `turn_id`, plus optional
`metadata` on Responses API item variants and inter-agent communication.
- Preserved item metadata through response-item rewrites such as
truncation, missing tool-output synthesis, compaction history
rebuilding, visible-history conversion, rollout/resume, and generated
app-server schemas/types.
- Strip item metadata from non-OpenAI Responses requests while
preserving it for OpenAI-shaped requests.
- Updated the mechanical fixture/test construction churn required by the
new optional field.
## Why
#27198 made the extension-owned `codex_apps` MCP connection the hosted
plugin runtime, but its `mcp/skill` resources still bypassed the skills
extension. App-server could list and read those resources through
generic MCP APIs, but a thread with no selected environment did not
expose them in the model's skills catalog or load their `SKILL.md`
through `$skill`.
Hosted skills should stay remote while using the same typed catalog,
source authority, deduplication, bounded contextual catalog, and
selected-skill prompt injection as host and executor skills. They should
not be downloaded or exposed as ambient filesystem paths.
## What changed
- Add a session-scoped `McpResourceClient` over the replaceable MCP
connection manager so resource list/read calls follow startup and
refresh replacements.
- Add a `BackendSkillProvider` that pages `codex_apps` resources,
accepts bounded and validated `mcp/skill` entries, and reads a selected
skill's `SKILL.md` through the same MCP connection.
- Register the remote provider in app-server and include it in the
skills catalog even when a thread has no selected capability roots or
executor.
- Contribute hosted skill metadata through the bounded
`AvailableSkillsInstructions` developer-context path, exclude remote
entries from per-turn catalog injection, and classify `<skills>`
messages as contextual developer content so rollback can trim and
rebuild them correctly.
## Testing
- Extend the app-server MCP resource integration test with
`environments: []` to exercise two-page discovery, filter a
non-`mcp/skill` resource, verify the escaped developer catalog entry and
user-role `<skill>` fragment containing the fetched `SKILL.md`, and
preserve generic MCP resource reads.
- Add core event-mapping coverage that classifies `<skills>` developer
messages as contextual history.
## Why
The model should be able to see bounded context-window budget metadata
when the `token_budget` feature is enabled. The full-window message is
only injected with full context, while normal turns get a smaller
follow-up only when reported usage first crosses a budget threshold.
## What changed
- Added the `TokenBudget` feature flag.
- Added `<token_budget>` developer fragments for full context-window
metadata and current-window remaining tokens.
- Inserted the threshold message during normal turn handling by
comparing token usage before and after sampling, avoiding persistent
threshold bookkeeping.
- Added core integration coverage for full-context-only metadata and
25/50/75 percent threshold messages.
## Verification
- `just test -p codex-core token_budget`
- `git diff --check`
## Summary
- Add optional image detail to user image inputs across core, app-server
v2, thread history/event mapping, and the generated app-server
schemas/types.
- Preserve requested detail when serializing Responses image inputs:
omitted detail stays on the existing `high` default, while explicit
`original` keeps local images on the original-resolution path.
- Support `high`/`original` consistently for tool image outputs,
including MCP `codex/imageDetail`, code-mode image helpers, and
`view_image`.
## Summary
- trim contiguous developer/contextual-user pre-turn updates when
rollback cuts back to a user turn
- add a focused history regression test for the trim behavior
- update the rollback request-boundary snapshots to show the fixed
non-duplicating context shape
---------
Co-authored-by: Codex <noreply@openai.com>
Send input now sends messages as assistant message and with this format:
```
author: /root/worker_a
recipient: /root/worker_a/tester
other_recipients: []
Content: bla bla bla. Actual content. Only text for now
```
## Summary
Persist Stop-hook continuation prompts as `user` messages instead of
hidden `developer` messages + some requested integration tests
This is a followup to @pakrym 's comment in
https://github.com/openai/codex/pull/14532 to make sure stop-block
continuation prompts match training for turn loops
- Stop continuation now writes `<hook_prompt hook_run_id="...">stop
hook's user prompt<hook_prompt>`
- Introduces quick-xml dependency, though we already indirectly depended
on it anyway via syntect
- This PR only has about 500 lines of actual logic changes, the rest is
tests/schema
## Testing
Example run (with a sessionstart hook and 3 stop hooks) - this shows
context added by session start, then two stop hooks sending their own
additional prompts in a new turn. The model responds with a single
message addressing both. Then when that turn ends, the hooks detect that
they just ran using `stop_hook_active` and decide not to infinite loop
test files for this (unzip, move codex -> .codex):
[codex.zip](https://github.com/user-attachments/files/26075806/codex.zip)
```
› cats
• Running SessionStart hook: lighting the observatory
SessionStart hook (completed)
warning: Hi, I'm a session start hook for wizard-tower (startup).
hook context: A wimboltine stonpet is an exotic cuisine from hyperspace
• Cats are tiny zen wizards, my friend: equal parts nap, mystery, and chaos. If you want, we can talk
cat facts, cat breeds, cat names, or build something cat-themed in this repo.
• Running Stop hook: checking the tower wards
• Running Stop hook: sacking the guards
• Running Stop hook: hiring the guards
Stop hook (completed)
warning: Wizard Tower Stop hook reviewed the completed reply (177 chars).
Stop hook (blocked)
warning: Wizard Tower Stop hook continuing conversation
feedback: cook the stonpet
Stop hook (blocked)
warning: Wizard Tower Stop hook continuing conversation
feedback: eat the cooked stonpet
• Stonpet’s cooked, aloha style: flash-seared over a blue quasiflame, glazed with nebula salt, and
rested until the hyperspace juices settle.
Now we eat with gratitude, my friend. One mindful bite in, and the flavor is pure cosmic surf:
smoky, bright, and totally out of this dimension.
• Running Stop hook: checking the tower wards
• Running Stop hook: sacking the guards
• Running Stop hook: hiring the guards
Stop hook (completed)
warning: Wizard Tower Stop hook reviewed the completed reply (285 chars).
Stop hook (completed)
warning: Wizard Tower Stop hook saw a second pass and stayed calm to avoid a loop.
Stop hook (completed)
warning: Wizard Tower Stop hook saw a second pass and stayed calm to avoid a loop.
```
## Why
PR #13783 moved the `codex.rs` unit tests into `codex_tests.rs`. This
applies the same extraction pattern across the rest of `codex-rs/core`
so the production modules stay focused on runtime code instead of large
inline test blocks.
Keeping the tests in sibling files also makes follow-up edits easier to
review because product changes no longer have to share a file with
hundreds or thousands of lines of test scaffolding.
## What changed
- replaced each inline `mod tests { ... }` in `codex-rs/core/src/**`
with a path-based module declaration
- moved each extracted unit test module into a sibling `*_tests.rs`
file, using `mod_tests.rs` for `mod.rs` modules
- preserved the existing `cfg(...)` guards and module-local structure so
the refactor remains structural rather than behavioral
## Testing
- `cargo test -p codex-core --lib` (`1653 passed; 0 failed; 5 ignored`)
- `just fix -p codex-core`
- `cargo fmt --check`
- `cargo shear`
## Summary
- bundle contextual prompt injection into at most one developer message
plus one contextual user message in both:
- per-turn settings updates
- initial context insertion
- preserve `<model_switch>` across compaction by rebuilding it through
canonical initial-context injection, instead of relying on
strip/reattach hacks
- centralize contextual user fragment detection in one shared definition
table and reuse it for parsing/compaction logic
- keep `AGENTS.md` in its natural serialized format:
- `# AGENTS.md instructions for {dirname}`
- `<INSTRUCTIONS>...</INSTRUCTIONS>`
- simplify related tests/helpers and accept the expected snapshot/layout
updates from bundled multi-part messages
## Why
The goal is to converge toward a simpler, more intentional prompt shape
where contextual updates are consistently represented as one developer
envelope plus one contextual user envelope, while keeping parsing and
compaction behavior aligned with that representation.
## Notable details
- the temporary `SettingsUpdateEnvelope` wrapper was removed; these
paths now return `Vec<ResponseItem>` directly
- local/remote compaction no longer rely on model-switch strip/restore
helpers
- contextual user detection is now driven by shared fragment definitions
instead of ad hoc matcher assembly
- AGENTS/user instructions are still the same logical context; only the
synthetic `<user_instructions>` wrapper was replaced by the natural
AGENTS text format
## Testing
- `just fmt`
- `cargo test -p codex-app-server
codex_message_processor::tests::extract_conversation_summary_prefers_plain_user_messages
-- --exact`
- `cargo test -p codex-core
compact::tests::collect_user_messages_filters_session_prefix_entries
--lib -- --exact`
- `cargo test -p codex-core --test all
'suite::compact::snapshot_request_shape_pre_turn_compaction_strips_incoming_model_switch'
-- --exact`
- `cargo test -p codex-core --test all
'suite::compact_remote::snapshot_request_shape_remote_pre_turn_compaction_strips_incoming_model_switch'
-- --exact`
- `cargo test -p codex-core --test all
'suite::client::includes_apps_guidance_as_developer_message_when_enabled'
-- --exact`
- `cargo test -p codex-core --test all
'suite::client::includes_developer_instructions_message_in_request' --
--exact`
- `cargo test -p codex-core --test all
'suite::client::includes_user_instructions_message_in_request' --
--exact`
- `cargo test -p codex-core --test all
'suite::client::resume_includes_initial_messages_and_sends_prior_items'
-- --exact`
- `cargo test -p codex-core --test all
'suite::review::review_input_isolated_from_parent_history' -- --exact`
- `cargo test -p codex-exec --test all
'suite::resume::exec_resume_last_respects_cwd_filter_and_all_flag' --
--exact`
- `cargo test -p core_test_support
context_snapshot::tests::full_text_mode_preserves_unredacted_text --
--exact`
## Notes
- I also ran several targeted `compact`, `compact_remote`,
`prompt_caching`, `model_visible_layout`, and `event_mapping` tests
while iterating on prompt-shape changes.
- I have not claimed a clean full-workspace `cargo test` from this
environment because local sandbox/resource conditions have previously
produced unrelated failures in large workspace runs.
TLDR: use new message phase field emitted by preamble-supported models
to determine whether an AgentMessage is mid-turn commentary. if so,
restore the status indicator afterwards to indicate the turn has not
completed.
### Problem
`commit_tick` hides the status indicator while streaming assistant text.
For preamble-capable models, that text can be commentary mid-turn, so
hiding was correct during streaming but restore timing mattered:
- restoring too aggressively caused jitter/flashing
- not restoring caused indicator to stay hidden before subsequent work
(tool calls, web search, etc.)
### Fix
- Add optional `phase` to `AgentMessageItem` and propagate it from
`ResponseItem::Message`
- Keep indicator hidden during streamed commit ticks, restore only when:
- assistant item completes as `phase=commentary`, and
- stream queues are idle + task is still running.
- Treat `phase=None` as final-answer behavior (no restore) to keep
existing behavior for non-preamble models
### Tests
Add/update tests for:
- no idle-tick restore without commentary completion
- commentary completion restoring status before tool begin
- snapshot coverage for preamble/status behavior
---------
Co-authored-by: Josh McKinney <joshka@openai.com>
### What
add wiring for `phase` field on `ResponseItem::Message` to lay
groundwork for differentiating model preambles and final messages.
currently optional.
follows pattern in #9698.
updated schemas with `just write-app-server-schema` so we can see type
changes.
### Tests
Updated existing tests for SSE parsing and hydrating from history
### Summary
- Parse all `web_search` tool actions (`search`, `find_in_page`,
`open_page`).
- Previously we only parsed + displayed `search`, which made the TUI
appear to pause when the other actions were being used.
- Show in progress `web_search` calls as `Searching the web`
- Previously we only showed completed tool calls
<img width="308" height="149" alt="image"
src="https://github.com/user-attachments/assets/90a4e8ff-b06a-48ff-a282-b57b31121845"
/>
### Tests
Added + updated tests, tested locally
### Follow ups
Update VSCode extension to display these as well
## What
Record a model-visible `<turn_aborted>` marker in history when a turn is
interrupted, and treat it as a session prefix.
## Why
When a turn is interrupted, Codex emits `TurnAborted` but previously did
not persist anything model-visible in the conversation history. On the
next user turn, the model can’t tell the previous work was aborted and
may resume/repeat earlier actions (including duplicated side effects
like re-opening PRs).
Fixes: https://github.com/openai/codex/issues/9042
## How
On `TurnAbortReason::Interrupted`, append a hidden user message
containing a `<turn_aborted>…</turn_aborted>` marker and flush.
Treat `<turn_aborted>` like `<environment_context>` for session-prefix
filtering.
Add a regression test to ensure follow-up turns don’t repeat side
effects from an aborted turn.
## Testing
`just fmt`
`just fix -p codex-core`
`cargo test -p codex-core -- --test-threads=1`
`cargo test --all-features -- --test-threads=1`
---------
Co-authored-by: Skylar Graika <sgraika127@gmail.com>
Co-authored-by: jif-oai <jif@openai.com>
Co-authored-by: Eric Traut <etraut@openai.com>
Continuation of breaking up this PR
https://github.com/openai/codex/pull/9116
## Summary
- Thread user text element ranges through TUI/TUI2 input, submission,
queueing, and history so placeholders survive resume/edit flows.
- Preserve local image attachments alongside text elements and rehydrate
placeholders when restoring drafts.
- Keep model-facing content shapes clean by attaching UI metadata only
to user input/events (no API content changes).
## Key Changes
- TUI/TUI2 composer now captures text element ranges, trims them with
text edits, and restores them when submission is suppressed.
- User history cells render styled spans for text elements and keep
local image paths for future rehydration.
- Initial chat widget bootstraps accept empty `initial_text_elements` to
keep initialization uniform.
- Protocol/core helpers updated to tolerate the new InputText field
shape without changing payloads sent to the API.
## Summary
We have a variety of things we refer to as instructions in the code
base: our current canonical terms are:
- base instructions (raw string)
- developer instructions (has a type in protocol)
- user instructions
We also have `instructions` floating around in various places. We should
standardize on the above, and start using types to prevent them from
ending up in the wrong place. There will be additional PRs, but I'm
going to keep these small so we can easily follow them!
## Testing
- [x] Tests pass, this is purely a file move
Agent wouldn't "see" attached images and would instead try to use the
view_file tool:
<img width="1516" height="504" alt="image"
src="https://github.com/user-attachments/assets/68a705bb-f962-4fc1-9087-e932a6859b12"
/>
In this PR, we wrap image content items in XML tags with the name of
each image (now just a numbered name like `[Image #1]`), so that the
model can understand inline image references (based on name). We also
put the image content items above the user message which the model seems
to prefer (maybe it's more used to definitions being before references).
We also tweak the view_file tool description which seemed to help a bit
Results on a simple eval set of images:
Before
<img width="980" height="310" alt="image"
src="https://github.com/user-attachments/assets/ba838651-2565-4684-a12e-81a36641bf86"
/>
After
<img width="918" height="322" alt="image"
src="https://github.com/user-attachments/assets/10a81951-7ee6-415e-a27e-e7a3fd0aee6f"
/>
```json
[
{
"id": "single_describe",
"prompt": "Describe the attached image in one sentence.",
"images": ["image_a.png"]
},
{
"id": "single_color",
"prompt": "What is the dominant color in the image? Answer with a single color word.",
"images": ["image_b.png"]
},
{
"id": "orientation_check",
"prompt": "Is the image portrait or landscape? Answer in one sentence.",
"images": ["image_c.png"]
},
{
"id": "detail_request",
"prompt": "Look closely at the image and call out any small details you notice.",
"images": ["image_d.png"]
},
{
"id": "two_images_compare",
"prompt": "I attached two images. Are they the same or different? Briefly explain.",
"images": ["image_a.png", "image_b.png"]
},
{
"id": "two_images_captions",
"prompt": "Provide a short caption for each image (Image 1, Image 2).",
"images": ["image_c.png", "image_d.png"]
},
{
"id": "multi_image_rank",
"prompt": "Rank the attached images from most colorful to least colorful.",
"images": ["image_a.png", "image_b.png", "image_c.png"]
},
{
"id": "multi_image_choice",
"prompt": "Which image looks more vibrant? Answer with 'Image 1' or 'Image 2'.",
"images": ["image_b.png", "image_d.png"]
}
]
```
1. Skills load once in core at session start; the cached outcome is
reused across core and surfaced to TUI via SessionConfigured.
2. TUI detects explicit skill selections, and core injects the matching
SKILL.md content into the turn when a selected skill is present.
Adds AgentMessageContentDelta, ReasoningContentDelta,
ReasoningRawContentDelta item streaming events while maintaining
compatibility for old events.
---------
Co-authored-by: Owen Lin <owen@openai.com>
1. Adds AgentMessage, Reasoning, WebSearch items.
2. Switches the ResponseItem parsing to use new items and then also emit
3. Removes user-item kind and filters out "special" (environment) user
items when returning to clients.
Created this PR by:
- adding `redundant_clone` to `[workspace.lints.clippy]` in
`cargo-rs/Cargol.toml`
- running `cargo clippy --tests --fix`
- running `just fmt`
Though I had to clean up one instance of the following that resulted:
```rust
let codex = codex;
```
This PR adds an `images` field to the existing `UserMessageEvent` so we
can encode zero or more images associated with a user message. This
allows images to be restored when conversations are restored.
This PR does the following:
- divides user msgs into 3 categories: plain, user instructions, and
environment context
- Centralizes adding user instructions and environment context to a
degree
- Improve the integration testing
Building on top of #3123
Specifically this
[comment](https://github.com/openai/codex/pull/3123#discussion_r2319885089).
We need to send the user message while ignoring the User Instructions
and Environment Context we attach.
### Overview
This PR introduces the following changes:
1. Adds a unified mechanism to convert ResponseItem into EventMsg.
2. Ensures that when a session is initialized with initial history, a
vector of EventMsg is sent along with the session configuration. This
allows clients to re-render the UI accordingly.
3. Added integration testing
### Caveats
This implementation does not send every EventMsg that was previously
dispatched to clients. The excluded events fall into two categories:
• “Arguably” rolled-out events
Examples include tool calls and apply-patch calls. While these events
are conceptually rolled out, we currently only roll out ResponseItems.
These events are already being handled elsewhere and transformed into
EventMsg before being sent.
• Non-rolled-out events
Certain events such as TurnDiff, Error, and TokenCount are not rolled
out at all.
### Future Directions
At present, resuming a session involves maintaining two states:
• UI State
Clients can replay most of the important UI from the provided EventMsg
history.
• Model State
The model receives the complete session history to reconstruct its
internal state.
This design provides a solid foundation. If, in the future, more precise
UI reconstruction is needed, we have two potential paths:
1. Introduce a third data structure that allows us to derive both
ResponseItems and EventMsgs.
2. Clearly divide responsibilities: the core system ensures the
integrity of the model state, while clients are responsible for
reconstructing the UI.