## Summary
Support updating Personality mid-Thread via UserTurn/OverwriteTurn. This
is explicitly unused by the clients so far, to simplify PRs - app-server
and tui implementations will be follow-ups.
## Testing
- [x] added integration tests
## Summary
- add optional `collaboration_mode` to `TurnContextItem` in rollouts
- persist the current collaboration mode when recording turn context
(sampling + compaction)
## Rationale
We already persist turn context data for resume logic. Capturing
collaboration mode in the rollout gives us the mode context for each
turn, enabling follow‑up work to diff mode instructions correctly on
resume.
## Changes
- protocol: add optional `collaboration_mode` field to `TurnContextItem`
- core: persist collaboration mode alongside other turn context settings
in rollouts
## 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
This PR consolidates base_instructions onto SessionMeta /
SessionConfiguration, so we ensure `base_instructions` is set once per
session and should be (mostly) immutable, unless:
- overridden by config on resume / fork
- sub-agent tasks, like review or collab
In a future PR, we should convert all references to `base_instructions`
to consistently used the typed struct, so it's less likely that we put
other strings there. See #9423. However, this PR is already quite
complex, so I'm deferring that to a follow-up.
## Testing
- [x] Added a resume test to assert that instructions are preserved. In
particular, `resume_switches_models_preserves_base_instructions` fails
against main.
Existing test coverage thats assert base instructions are preserved
across multiple requests in a session:
- Manual compact keeps baseline instructions:
core/tests/suite/compact.rs:199
- Auto-compact keeps baseline instructions:
core/tests/suite/compact.rs:1142
- Prompt caching reuses the same instructions across two requests:
core/tests/suite/prompt_caching.rs:150 and
core/tests/suite/prompt_caching.rs:157
- Prompt caching with explicit expected string across two requests:
core/tests/suite/prompt_caching.rs:213 and
core/tests/suite/prompt_caching.rs:222
- Resume with model switch keeps original instructions:
core/tests/suite/resume.rs:136
- Compact/resume/fork uses request 0 instructions for later expected
payloads: core/tests/suite/compact_resume_fork.rs:215
### Motivation
- Persist richer per-turn configuration in rollouts so resumed/forked
sessions and tooling can reason about the exact instruction inputs and
output constraints used for a turn.
### Description
- Extend `TurnContextItem` to include optional `base_instructions`,
`user_instructions`, and `developer_instructions`.
- Record the optional `final_output_json_schema` associated with a turn.
- Add an optional `truncation_policy` to `TurnContextItem` and populate
it when writing turn-context rollout items.
- Introduce a protocol-level `TruncationPolicy` representation and
convert from core truncation policy when recording.
### Testing
- `cargo test -p codex-protocol` (pass)
I noticed that `features: Features` was defined on `struct
SessionConfiguration`, which is commonly owned by `SessionState`, which
is in turn owned by `Session`.
Though I do not believe that `Features` should be allowed to be modified
over the course of a session (if the feature state is not invariant, it
makes it harder to reason about), which argues that it should live on
`Session` rather than `SessionState` or `SessionConfiguration`.
This PR moves `Features` to `Session` and updates all call sites. It
appears the only place we were mutating `Features` was:
- in tests
- the sub-agent config for a review task:
3ef76ff29d/codex-rs/core/src/tasks/review.rs (L86-L89)
Note this change also means it is no longer an `async` call to check the
state of a feature, eliminating the possibility of a
[TOCTTOU](https://en.wikipedia.org/wiki/Time-of-check_to_time-of-use)
error between checking the state of a feature and acting on it:
3ef76ff29d/codex-rs/core/src/codex.rs (L1069-L1076)
This reverts commit c2ec477d93.
# 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.
- This PR is to make it on path for truncating by tokens. This path will
be initially used by unified exec and context manager (responsible for
MCP calls mainly).
- We are exposing new config `calls_output_max_tokens`
- Use `tokens` as the main budget unit but truncate based on the model
family by Introducing `TruncationPolicy`.
- Introduce `truncate_text` as a router for truncation based on the
mode.
In next PRs:
- remove truncate_with_line_bytes_budget
- Add the ability to the model to override the token budget.
This PR does the following:
- Add compact prefix to the summary
- Change the compaction prompt
- Allow multiple compaction for long running tasks
- Filter out summary messages on the following compaction
Considerations:
- Filtering out the summary message isn't the most clean
- Theoretically, we can end up in infinite compaction loop if the user
messages > compaction limit . However, that's not possible in today's
code because we have hard cap on user messages.
- We need to address having multiple user messages because it confuses
the model.
Testing:
- Making sure that after compact we always end up with one user message
(task) and one summary, even on multiple compaction.
