### 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
**Goal**: Prevent response.failed events with `invalid_prompt` from
being treated as retryable errors so the UI shows the actual error
message instead of continually retrying.
**Before**: Codex would continue to retry despite the prompt being
marked as disallowed
**After**: Codex will stop retrying once prompt is marked disallowed
- capture the header from SSE/WS handshakes, store it per
ModelClientSession using `Oncelock`, echo it on turn-scoped requests,
and add SSE+WS integration tests for within-turn persistence +
cross-turn reset.
- keep `x-codex-turn-state` sticky within a user turn to maintain
routing continuity for retries/tool follow-ups.
Adds a new feature
`enable_request_compression` that will compress using zstd requests to
the codex-backend. Currently only enabled for codex-backend so only enabled for openai providers when using chatgpt::auth even when the feature is enabled
Added a new info log line too for evaluating the compression ratio and
overhead off compressing before requesting. You can enable with
`RUST_LOG=$RUST_LOG,codex_client::transport=info`
```
2026-01-06T00:09:48.272113Z INFO codex_client::transport: Compressed request body with zstd pre_compression_bytes=28914 post_compression_bytes=11485 compression_duration_ms=0
```
- Merge ModelFamily into ModelInfo
- Remove logic for adding instructions to apply patch
- Add compaction limit and visible context window to `ModelInfo`
Context
- This code parses Server-Sent Events (SSE) from the legacy Chat
Completions streaming API (wire_api = "chat").
- The upstream protocol terminates a stream with a final sentinel event:
data: [DONE].
- Some of our test stubs/helpers historically end the stream with data:
DONE (no brackets).
How this was found
- GitHub Actions on Windows failed in codex-app-server integration tests
with wiremock verification errors (expected multiple POSTs, got 1).
Diagnosis
- The job logs included: codex_api::sse::chat: Failed to parse
ChatCompletions SSE event ... data: DONE.
- eventsource_stream surfaces the sentinel as a normal SSE event; it
does not automatically close the stream.
- The parser previously attempted to JSON-decode every data: payload.
The sentinel is not JSON, so we logged and skipped it, then continued
polling.
- On servers that keep the HTTP connection open after emitting the
sentinel (notably wiremock on Windows), skipping the sentinel meant we
never emitted ResponseEvent::Completed.
- Higher layers wait for completion before progressing (emitting
approval requests and issuing follow-up model calls), so the test never
reached the subsequent requests and wiremock panicked when its
expected-call count was not met.
Fix
- Treat both data: [DONE] and data: DONE as explicit end-of-stream
sentinels.
- When a sentinel is seen, flush any pending assistant/reasoning items
and emit ResponseEvent::Completed once.
Tests
- Add a regression unit test asserting we complete on the sentinel even
if the underlying connection is not closed.
Fix this: https://github.com/openai/codex/issues/8479
The issue is that chat completion API expect all the tool calls in a
single assistant message and then all the tool call output in a single
response message
This isn't very useful parameter.
logic:
```
if model puts `**` in their reasoning, trim it and visualize the header.
if couldn't trim: don't render
if model doesn't support: don't render
```
We can simplify to:
```
if could trim, visualize header.
if not, don't render
```
# 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.
# 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.
- Introduce `openai_models` in `/core`
- Move `PRESETS` under it
- Move `ModelPreset`, `ModelUpgrade`, `ReasoningEffortPreset`,
`ReasoningEffortPreset`, and `ReasoningEffortPreset` to `protocol`
- Introduce `Op::ListModels` and `EventMsg::AvailableModels`
Next steps:
- migrate `app-server` and `tui` to use the introduced Operation
