fix(proxy/openai): thread savings-profile kwargs into chat completions (#1606)

## Description

OpenAI-compatible `/v1/chat/completions` requests didn't receive the
same proxy
savings/profile kwargs as the other compression paths. The live chat
handler
(`handle_openai_chat` in `headroom/proxy/handlers/openai.py`) called
`openai_pipeline.apply()` with only `model_limit` / `context` /
`frozen_message_count` / `biases` / `compression_policy` — it never
passed
`proxy_pipeline_kwargs(self.config)`.

So when the proxy runs with `HEADROOM_SAVINGS_PROFILE=agent-90`, the
effective
config reports user/system-message compression and `target_ratio=0.10`,
but the
real chat path silently dropped all of it. OpenAI-compatible clients
such as
OpenCode kept protecting user messages and missed the configured
profile.

For contrast, `handlers/anthropic.py` passes
`**proxy_pipeline_kwargs(self.config)`
to every `apply()` call, and so does the dedicated OpenAI compress
endpoint in
this same module — only the two chat-completions `apply()` sites were
missing it.

Closes #1534

## Fix

Add `**proxy_pipeline_kwargs(self.config)` to both chat-path `apply()`
calls (the
token-mode branch and the non-token branch):

```python
lambda: self.openai_pipeline.apply(
    messages=messages,
    model=model,
    model_limit=context_limit,
    context=extract_user_query(messages),
    frozen_message_count=openai_frozen_count,
    biases=_hook_biases,
    compression_policy=compression_policy,
    **proxy_pipeline_kwargs(self.config),   # ← added
)
```

`proxy_pipeline_kwargs` is already imported in the module and is the
exact
helper the Anthropic handler and the OpenAI compress endpoint use, so
the chat
path now matches them.

## Type of Change

- [x] Bug fix (non-breaking change that fixes an issue)

## Changes Made

- `headroom/proxy/handlers/openai.py`: pass
`**proxy_pipeline_kwargs(self.config)` on both `apply()` call sites in
`handle_openai_chat` (token-mode and non-token branches).
- `tests/test_proxy/test_openai_chat_savings_profile.py`: new regression
test driving the chat handler with `savings_profile="agent-90"` and
asserting the profile knobs reach `apply()`.
- `CHANGELOG.md`: Bug Fixes entry under Unreleased.

## Testing

- [x] Unit tests pass (`pytest`)
- [x] Linting passes (`ruff check .`)
- [ ] Type checking passes (`mypy headroom`)
- [x] New tests added for new functionality
- [x] Manual testing performed

### Test Output

The new test drives the real chat handler through the `create_app` +
`TestClient`
harness with a recording `apply()` stub. Before the fix it captures
exactly the
five kwargs the issue describes (no profile knobs); after the fix the
profile
knobs are present:

```text
# before the fix (openai.py reverted, test kept)
E   AssertionError: assert None is True
E    +  where None = {...}.get('compress_user_messages')
# captured kwargs were: biases, compression_policy, messages, model,
# model_limit, context, frozen_message_count  — no profile knobs
FAILED tests/test_proxy/test_openai_chat_savings_profile.py::test_chat_completions_threads_savings_profile_kwargs_into_apply

# after the fix
tests\test_proxy\test_openai_chat_savings_profile.py .
======================== 1 passed, 1 warning in 39.44s ========================
```

No regression in the existing chat backend-path suite:

```text
$ uv run pytest tests/test_proxy/test_openai_backend_path.py
======================== 5 passed, 1 warning in 15.78s ========================
$ uv run ruff check headroom/proxy/handlers/openai.py tests/test_proxy/test_openai_chat_savings_profile.py
All checks passed!
```

## Real Behavior Proof

- Environment: Windows 11, Python 3.12.11, headroom built from this
branch (`uv sync --extra dev`), proxy config
`savings_profile="agent-90"`, `optimize=True`, `backend="anyllm"` with a
mocked OpenAI upstream.
- Exact command / steps: started the app with `create_app(config)`,
replaced `proxy.openai_pipeline.apply` with a recording stub, and POSTed
a real `/v1/chat/completions` request with a large user message so the
compression decision fires. Inspected the kwargs the handler actually
passed to `apply()`.
- Observed result: before the fix the recorded `apply()` kwargs were
`{biases, compression_policy, messages, model, model_limit, context,
frozen_message_count}` — no profile knobs. After the fix the same call
also carries `compress_user_messages=True`,
`compress_system_messages=True`, `target_ratio=0.10`,
`min_tokens_to_compress=120` (the agent-90 profile), matching the
issue's "Expected".
- Not tested: did not stand up a real OpenAI/OpenCode upstream
end-to-end (no live key in this environment); the upstream is mocked and
the assertion is on the kwargs the proxy threads into the compression
pipeline, which is exactly what the bug was about. Did not run the full
`mypy headroom` pass (two-line kwarg addition, no new types).

## Review Readiness

- [x] I have performed a self-review
- [x] This PR is ready for human review

## Checklist

- [x] My code follows the project's style guidelines
- [x] I have performed a self-review of my code
- [x] I have commented my code, particularly in hard-to-understand areas
- [ ] I have made corresponding changes to the documentation
- [x] My changes generate no new warnings
- [x] I have added tests that prove my fix is effective or that my
feature works
- [x] New and existing unit tests pass locally with my changes
- [x] I have updated the CHANGELOG.md if applicable

## Additional Notes

- Two-line change plus comments; no new dependencies. Reuses the
existing `proxy_pipeline_kwargs` helper, so behavior is consistent
across Anthropic, the OpenAI compress endpoint, and now the OpenAI chat
path.
- @chopratejas flagging you for review — this aligns the OpenAI chat
path with the savings-profile handling the other providers already had.

Co-authored-by: JD Davis <mxjerrett@gmail.com>

CHANGELOG.md

@@ -108,6 +108,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Bug Fixes
 
+* **proxy/openai:** thread the savings-profile kwargs into the live `/v1/chat/completions` compression path. The chat handler called `openai_pipeline.apply()` without `proxy_pipeline_kwargs(config)`, so `HEADROOM_SAVINGS_PROFILE=agent-90` (and the individual `compress_user_messages`/`target_ratio`/`min_tokens_to_compress`/... knobs) were silently dropped — OpenAI-compatible clients like OpenCode kept protecting user messages and missed the configured profile. Both the token-mode and non-token chat branches now pass the profile kwargs, matching `handlers/anthropic.py` and the dedicated OpenAI compress endpoint ([#1534](https://github.com/headroomlabs-ai/headroom/issues/1534)).
 * **proxy:** forward Codex Desktop `/v1/responses` posts byte-faithfully so they stop returning upstream `400 {"detail":"Bad Request"}`. `handle_openai_responses` decoded the inbound body to inspect it but always re-serialized a canonical body on the way out, and it never stripped the inbound `content-encoding` header — so a `content-encoding: zstd` Codex Desktop request was forwarded as already-decoded JSON still advertising `zstd`, and the upstream ChatGPT Codex endpoint rejected it. The handler now keeps the original decoded bytes and forwards them verbatim whenever nothing (compression or memory injection) mutated the request, and drops the stale `content-encoding` header, mirroring the byte-faithful passthrough the chat and Anthropic paths already use ([#1542](https://github.com/headroomlabs-ai/headroom/issues/1542)).
 * **wrap/codex:** `headroom unwrap codex` now removes the Headroom rtk instruction block from the Codex global `AGENTS.md`. `wrap codex` injects it there, but unwrap only restored `config.toml` and MCP state, so a plain `codex` launch kept following the "prefix shell commands with `rtk`" guidance and failed once the managed rtk binary was off PATH. Unwrap now strips the marker-fenced block (preserving the rest of the file), mirroring `unwrap copilot` ([#1421](https://github.com/headroomlabs-ai/headroom/issues/1421)).
 * **proxy/auth:** classify real Anthropic OAuth tokens correctly. `classify_auth_mode` matched OAuth on the `sk-ant-oat-` prefix, but real access tokens are `sk-ant-oat01-...` (a version number, no dash after `oat`), so every real subscription/OAuth token fell through to the `sk-` branch and was tagged `PAYG` — enabling aggressive lossy compression, auto `cache_control`, and `prompt_cache_key` injection on subscription-bound requests the classifier is meant to route to the passthrough-prefer path. The prefix is now the dash-less `sk-ant-oat` (still matches the legacy dashed shape). The existing parity tests only passed because they used a synthetic `sk-ant-oat-01-` fixture; a regression test now covers the real `sk-ant-oat01-` format.