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https://github.com/headroomlabs-ai/headroom.git
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## Description Add a clear dashboard view for per-agent token usage so end users can see Cursor, Claude, Codex, and other detected clients with before/after token counts, tokens saved, and savings percentages. The stats API now exposes a stable `agent_usage` object that the dashboard renders near the top of the session view. Fixes # ## Type of Change - [ ] Bug fix (non-breaking change that fixes an issue) - [x] New feature (non-breaking change that adds functionality) - [ ] Breaking change (fix or feature that would cause existing functionality to change) - [ ] Documentation update - [ ] Performance improvement - [ ] Code refactoring (no functional changes) ## Changes Made ### New Files **Tests:** - `tests/test_dashboard_agent_usage.py` — Covers agent classification, exact per-request aggregation, and aggregate fallback behavior. ### Modified Files - `headroom/proxy/server.py` — Adds per-agent usage aggregation to `/stats` with before tokens, after tokens, output tokens, saved tokens, savings percentage, source, providers, and models. - `headroom/dashboard/templates/dashboard.html` — Adds a prominent Agent Usage panel with totals, coverage status, per-agent token-flow bars, request counts, before/after tokens, saved tokens, and share of savings. ## Testing - [x] Unit tests pass: `.venv312/bin/pytest tests/test_dashboard_agent_usage.py` - [x] Linting passes: `.venv312/bin/ruff check headroom/proxy/server.py tests/test_dashboard_agent_usage.py` - [x] Diff whitespace check passes: `git diff --check origin/main...HEAD` - [x] Dashboard smoke render: local proxy on `127.0.0.1:8790`, captured Chrome headless screenshot of `/dashboard` - [x] New tests added for new functionality ## 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 - [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 relevant unit tests pass locally with my changes - [ ] I have made corresponding changes to the documentation - [ ] I have updated the CHANGELOG.md if applicable ## Additional Notes The agent usage panel uses exact request-log data when available. If detailed request logs are empty, it falls back to aggregate provider/model request counts and labels the coverage as aggregate fallback so users are not misled.
464 lines
15 KiB
Python
464 lines
15 KiB
Python
import asyncio
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import base64
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import json
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import sys
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from types import SimpleNamespace
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from unittest.mock import MagicMock, patch
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import anyio
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import pytest
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from fastapi import Request
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from headroom.proxy.handlers.openai import (
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OpenAIHandlerMixin,
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_openai_responses_unit_cache_key,
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_resolve_codex_routing_headers,
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)
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def _jwt(payload: dict) -> str:
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header = {"alg": "none", "typ": "JWT"}
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def encode(part: dict) -> str:
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raw = json.dumps(part, separators=(",", ":")).encode("utf-8")
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return base64.urlsafe_b64encode(raw).decode("ascii").rstrip("=")
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return f"{encode(header)}.{encode(payload)}."
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def test_resolve_codex_routing_prefers_explicit_header():
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headers, is_chatgpt = _resolve_codex_routing_headers(
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{
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"Authorization": "Bearer sk-test",
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"ChatGPT-Account-ID": "acct-explicit",
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}
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)
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assert is_chatgpt is True
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assert headers["ChatGPT-Account-ID"] == "acct-explicit"
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def test_resolve_codex_routing_derives_account_id_from_oauth_jwt():
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token = _jwt(
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{
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"https://api.openai.com/auth": {
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"chatgpt_account_id": "acct-from-jwt",
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}
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}
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)
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headers, is_chatgpt = _resolve_codex_routing_headers(
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{
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"authorization": f"Bearer {token}",
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}
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)
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assert is_chatgpt is True
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assert headers["ChatGPT-Account-ID"] == "acct-from-jwt"
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def test_resolve_codex_routing_leaves_regular_openai_bearer_tokens_unchanged():
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token = _jwt({"aud": ["https://api.openai.com/v1"]})
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headers, is_chatgpt = _resolve_codex_routing_headers(
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{
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"authorization": f"Bearer {token}",
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}
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)
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assert is_chatgpt is False
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assert "ChatGPT-Account-ID" not in headers
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def test_resolve_codex_routing_returns_none_without_bearer_auth():
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headers, is_chatgpt = _resolve_codex_routing_headers({})
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assert is_chatgpt is False
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assert headers == {}
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def test_resolve_codex_routing_ignores_non_jwt_bearer_tokens():
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headers, is_chatgpt = _resolve_codex_routing_headers(
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{
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"authorization": "Bearer not-a-jwt",
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}
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)
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assert is_chatgpt is False
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assert headers["authorization"] == "Bearer not-a-jwt"
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def test_resolve_codex_routing_ignores_invalid_jwt_payloads():
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invalid_payload = base64.urlsafe_b64encode(b"not-json").decode("ascii").rstrip("=")
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token = f"test-header.{invalid_payload}.signature"
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headers, is_chatgpt = _resolve_codex_routing_headers(
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{
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"authorization": f"Bearer {token}",
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}
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)
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assert is_chatgpt is False
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assert headers["authorization"] == f"Bearer {token}"
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def test_openai_responses_unit_cache_key_includes_target_ratio() -> None:
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unit = SimpleNamespace(
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text="large tool output",
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provider="openai",
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endpoint="responses",
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role="tool",
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item_type="function_call_output",
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cache_zone="live",
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mutable=True,
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min_bytes=100,
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context=None,
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question=None,
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bias=None,
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metadata={},
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)
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default_key = _openai_responses_unit_cache_key(unit, model="gpt-5.4")
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aggressive_key = _openai_responses_unit_cache_key(
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unit,
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model="gpt-5.4",
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target_ratio=0.10,
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)
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balanced_key = _openai_responses_unit_cache_key(
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unit,
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model="gpt-5.4",
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target_ratio=0.50,
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)
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assert aggressive_key != default_key
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assert aggressive_key != balanced_key
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class _DummyMetrics:
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async def record_request(self, **kwargs): # noqa: ANN003
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return None
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async def record_failed(self, **kwargs): # noqa: ANN003
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return None
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class _DummyTokenizer:
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def count_messages(self, messages):
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return len(messages)
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class _ResponseStub:
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status_code = 200
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headers = {"content-type": "application/json", "content-length": "42"}
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content = b'{"id":"resp_123","output":[{"type":"message"}]}'
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def json(self):
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return {"usage": {"input_tokens": 2, "output_tokens": 1}}
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class _DummyOpenAIHandler(OpenAIHandlerMixin):
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OPENAI_API_URL = "https://api.openai.com"
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def __init__(self) -> None:
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self.rate_limiter = None
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self.metrics = _DummyMetrics()
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self.config = SimpleNamespace(
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optimize=False,
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retry_max_attempts=3,
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retry_base_delay_ms=10,
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retry_max_delay_ms=50,
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connect_timeout_seconds=10,
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)
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self.usage_reporter = None
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self.openai_provider = SimpleNamespace(get_context_limit=lambda model: 128_000)
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self.openai_pipeline = SimpleNamespace(apply=MagicMock())
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self.anthropic_backend = None
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self.cost_tracker = None
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self.memory_handler = None
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# PR-A6 wires session-sticky `OpenAI-Beta` merging into the
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# responses HTTP handler — it reads `compute_session_id` to key
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# the SessionBetaTracker. The routing tests don't exercise the
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# tracker semantics themselves, so a fixed-id stub is enough.
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self.session_tracker_store = SimpleNamespace(
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compute_session_id=lambda *a, **k: "sess-openai-1",
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)
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self.captured_request: tuple[str, str, dict, dict] | None = None
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self.captured_stream_request: tuple[str, dict, dict] | None = None
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async def _next_request_id(self) -> str:
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return "req-1"
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def _extract_tags(self, headers: dict[str, str]) -> dict[str, str]:
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return {}
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async def _retry_request(self, method: str, url: str, headers: dict, body: dict):
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self.captured_request = (method, url, headers, body)
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return _ResponseStub()
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async def _run_compression_in_executor(self, fn, *, timeout: float):
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# Test stub for HeadroomProxy._run_compression_in_executor.
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# The real implementation runs `fn` on a bounded thread pool with
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# a wall-clock timeout; tests just need the callable invoked
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# synchronously so MagicMock call_count assertions fire.
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return fn()
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async def _record_request_outcome(self, outcome) -> None:
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# Test stub: delegates to the production funnel so wire shape
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# matches HeadroomProxy._record_request_outcome.
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from headroom.proxy.outcome import emit_request_outcome
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await emit_request_outcome(self, outcome)
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async def _stream_response(
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self,
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url: str,
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headers: dict,
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body: dict,
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provider: str,
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model: str,
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request_id: str,
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original_tokens: int,
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optimized_tokens: int,
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tokens_saved: int,
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transforms_applied: list[str],
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tags: dict[str, str],
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optimization_latency: float,
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memory_user_id: str | None = None,
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**kwargs,
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):
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self.captured_stream_request = (url, headers, body)
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return SimpleNamespace(
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status_code=200,
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url=url,
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headers=headers,
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body=body,
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memory_user_id=memory_user_id,
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)
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def _build_request(body: dict, headers: dict[str, str]) -> Request:
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payload = json.dumps(body).encode("utf-8")
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async def receive():
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return {"type": "http.request", "body": payload, "more_body": False}
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scope = {
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"type": "http",
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"asgi": {"version": "3.0"},
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"http_version": "1.1",
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"method": "POST",
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"scheme": "https",
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"path": "/v1/responses",
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"raw_path": b"/v1/responses",
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"query_string": b"",
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"headers": [
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(key.lower().encode("utf-8"), value.encode("utf-8")) for key, value in headers.items()
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],
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"client": ("127.0.0.1", 12345),
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"server": ("testserver", 443),
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}
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return Request(scope, receive)
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def test_handle_openai_responses_routes_chatgpt_auth_to_backend_api(monkeypatch):
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token = _jwt(
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{
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"https://api.openai.com/auth": {
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"chatgpt_account_id": "acct-from-jwt",
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}
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}
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)
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request = _build_request(
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{"model": "gpt-5.4", "input": "hello"},
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{"Authorization": f"Bearer {token}"},
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)
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handler = _DummyOpenAIHandler()
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monkeypatch.setattr("headroom.tokenizers.get_tokenizer", lambda model: _DummyTokenizer())
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response = anyio.run(handler.handle_openai_responses, request)
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assert handler.captured_request is not None
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method, url, headers, body = handler.captured_request
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assert method == "POST"
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assert url == "https://chatgpt.com/backend-api/codex/responses"
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assert headers["ChatGPT-Account-ID"] == "acct-from-jwt"
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assert body["input"] == "hello"
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assert response.status_code == 200
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def test_handle_openai_responses_chatgpt_codex_timeout_fails_open(monkeypatch):
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token = _jwt(
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{
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"https://api.openai.com/auth": {
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"chatgpt_account_id": "acct-from-jwt",
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}
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}
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)
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request = _build_request(
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{"model": "gpt-5.4", "input": "large context"},
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{"Authorization": f"Bearer {token}"},
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)
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handler = _DummyOpenAIHandler()
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handler.config.optimize = True
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async def timeout_compression(*args, **kwargs): # noqa: ANN002, ANN003
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raise asyncio.TimeoutError()
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handler._compress_openai_responses_payload_in_executor = timeout_compression
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monkeypatch.setattr("headroom.tokenizers.get_tokenizer", lambda model: _DummyTokenizer())
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response = anyio.run(handler.handle_openai_responses, request)
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assert response.status_code == 200
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assert handler.captured_request is not None
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method, url, headers, body = handler.captured_request
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assert method == "POST"
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assert url == "https://chatgpt.com/backend-api/codex/responses"
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assert body["input"] == "large context"
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def test_handle_openai_responses_routes_api_key_auth_direct_to_openai(monkeypatch):
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request = _build_request(
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{"model": "gpt-4o-mini", "input": "hello"},
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{"Authorization": "Bearer sk-test"},
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)
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handler = _DummyOpenAIHandler()
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monkeypatch.setattr("headroom.tokenizers.get_tokenizer", lambda model: _DummyTokenizer())
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response = anyio.run(handler.handle_openai_responses, request)
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assert handler.captured_request is not None
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method, url, headers, body = handler.captured_request
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assert method == "POST"
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assert url == "https://api.openai.com/v1/responses"
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assert headers.get("ChatGPT-Account-ID") is None
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assert body["input"] == "hello"
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assert response.status_code == 200
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def test_handle_openai_responses_stream_skips_python_compression(monkeypatch):
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"""PR-C5: Python no longer compresses /v1/responses (Rust handles it
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natively). The streaming forward path must still fire — only the
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Python compression dispatch is retired."""
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request = _build_request(
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{
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"model": "gpt-5.4",
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"stream": True,
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"instructions": "Keep it short",
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"input": [
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{
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"type": "message",
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"role": "user",
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"content": [{"type": "input_text", "text": "hello"}],
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}
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],
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},
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{"Authorization": "Bearer sk-test"},
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)
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handler = _DummyOpenAIHandler()
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handler.config.optimize = True
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monkeypatch.setattr("headroom.tokenizers.get_tokenizer", lambda model: _DummyTokenizer())
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response = anyio.run(handler.handle_openai_responses, request)
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assert response.status_code == 200
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assert handler.captured_stream_request is not None
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assert handler.openai_pipeline.apply.call_count == 0
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assert handler.captured_stream_request[2]["stream"] is True
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def test_handle_openai_responses_memory_timeout_fails_open(monkeypatch):
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class _SlowMemoryHandler:
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def __init__(self):
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self.config = SimpleNamespace(inject_context=True, inject_tools=False)
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async def search_and_format_context(self, memory_user_id, messages, **_kwargs):
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return "should not be used"
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def has_memory_tool_calls(self, response, provider):
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return False
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async def _timeout_wait_for(awaitable, timeout):
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close = getattr(awaitable, "close", None)
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if callable(close):
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close()
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raise TimeoutError
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request = _build_request(
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{"model": "gpt-5.4", "input": "hello"},
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{"Authorization": "Bearer sk-test", "x-headroom-user-id": "user-1"},
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)
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handler = _DummyOpenAIHandler()
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handler.memory_handler = _SlowMemoryHandler()
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monkeypatch.setattr("headroom.tokenizers.get_tokenizer", lambda model: _DummyTokenizer())
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monkeypatch.setattr("headroom.proxy.handlers.openai.asyncio.wait_for", _timeout_wait_for)
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response = anyio.run(handler.handle_openai_responses, request)
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assert response.status_code == 200
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assert handler.captured_request is not None
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_, _, _, body = handler.captured_request
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assert body.get("instructions") is None
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def test_codex_responses_timeout_fails_open_in_standalone_proxy(monkeypatch):
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"""Codex users running only the proxy still get fail-open on timeout."""
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request = _build_request(
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{
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"model": "gpt-5.4",
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"input": [
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{
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"type": "function_call_output",
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"call_id": "call-1",
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"output": "large tool output",
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}
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],
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},
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{"Authorization": "Bearer sk-test", "x-client": "codex"},
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)
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handler = _DummyOpenAIHandler()
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handler.config.optimize = True
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monkeypatch.setattr("headroom.tokenizers.get_tokenizer", lambda model: _DummyTokenizer())
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monkeypatch.setattr(
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handler,
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"_compress_openai_responses_payload",
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lambda *args, **kwargs: (_ for _ in ()).throw(TimeoutError()),
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)
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response = anyio.run(handler.handle_openai_responses, request)
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assert response.status_code == 200
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assert handler.captured_request is not None
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_, url, _, body = handler.captured_request
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assert url == "https://api.openai.com/v1/responses"
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assert body["input"][0]["output"] == "large tool output"
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class _DummyWebSocket:
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def __init__(self, headers: dict[str, str]):
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self.headers = headers
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self.accepted_subprotocol = None
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async def accept(self, subprotocol=None):
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self.accepted_subprotocol = subprotocol
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def test_handle_openai_responses_ws_resolves_codex_routing_headers():
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class SentinelError(RuntimeError):
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pass
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handler = _DummyOpenAIHandler()
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websocket = _DummyWebSocket({"authorization": "Bearer token"})
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with patch.dict(sys.modules, {"websockets": MagicMock()}):
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with patch(
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"headroom.proxy.handlers.openai._resolve_codex_routing_headers",
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side_effect=SentinelError("resolved"),
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):
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with pytest.raises(SentinelError, match="resolved"):
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anyio.run(handler.handle_openai_responses_ws, websocket)
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