headroom/tests/test_openai_codex_routing.py
Michael Sam 6d3f39f213
feat: add dashboard agent usage stats (#814)
## 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.
2026-06-12 14:12:22 -05:00

464 lines
15 KiB
Python

import asyncio
import base64
import json
import sys
from types import SimpleNamespace
from unittest.mock import MagicMock, patch
import anyio
import pytest
from fastapi import Request
from headroom.proxy.handlers.openai import (
OpenAIHandlerMixin,
_openai_responses_unit_cache_key,
_resolve_codex_routing_headers,
)
def _jwt(payload: dict) -> str:
header = {"alg": "none", "typ": "JWT"}
def encode(part: dict) -> str:
raw = json.dumps(part, separators=(",", ":")).encode("utf-8")
return base64.urlsafe_b64encode(raw).decode("ascii").rstrip("=")
return f"{encode(header)}.{encode(payload)}."
def test_resolve_codex_routing_prefers_explicit_header():
headers, is_chatgpt = _resolve_codex_routing_headers(
{
"Authorization": "Bearer sk-test",
"ChatGPT-Account-ID": "acct-explicit",
}
)
assert is_chatgpt is True
assert headers["ChatGPT-Account-ID"] == "acct-explicit"
def test_resolve_codex_routing_derives_account_id_from_oauth_jwt():
token = _jwt(
{
"https://api.openai.com/auth": {
"chatgpt_account_id": "acct-from-jwt",
}
}
)
headers, is_chatgpt = _resolve_codex_routing_headers(
{
"authorization": f"Bearer {token}",
}
)
assert is_chatgpt is True
assert headers["ChatGPT-Account-ID"] == "acct-from-jwt"
def test_resolve_codex_routing_leaves_regular_openai_bearer_tokens_unchanged():
token = _jwt({"aud": ["https://api.openai.com/v1"]})
headers, is_chatgpt = _resolve_codex_routing_headers(
{
"authorization": f"Bearer {token}",
}
)
assert is_chatgpt is False
assert "ChatGPT-Account-ID" not in headers
def test_resolve_codex_routing_returns_none_without_bearer_auth():
headers, is_chatgpt = _resolve_codex_routing_headers({})
assert is_chatgpt is False
assert headers == {}
def test_resolve_codex_routing_ignores_non_jwt_bearer_tokens():
headers, is_chatgpt = _resolve_codex_routing_headers(
{
"authorization": "Bearer not-a-jwt",
}
)
assert is_chatgpt is False
assert headers["authorization"] == "Bearer not-a-jwt"
def test_resolve_codex_routing_ignores_invalid_jwt_payloads():
invalid_payload = base64.urlsafe_b64encode(b"not-json").decode("ascii").rstrip("=")
token = f"test-header.{invalid_payload}.signature"
headers, is_chatgpt = _resolve_codex_routing_headers(
{
"authorization": f"Bearer {token}",
}
)
assert is_chatgpt is False
assert headers["authorization"] == f"Bearer {token}"
def test_openai_responses_unit_cache_key_includes_target_ratio() -> None:
unit = SimpleNamespace(
text="large tool output",
provider="openai",
endpoint="responses",
role="tool",
item_type="function_call_output",
cache_zone="live",
mutable=True,
min_bytes=100,
context=None,
question=None,
bias=None,
metadata={},
)
default_key = _openai_responses_unit_cache_key(unit, model="gpt-5.4")
aggressive_key = _openai_responses_unit_cache_key(
unit,
model="gpt-5.4",
target_ratio=0.10,
)
balanced_key = _openai_responses_unit_cache_key(
unit,
model="gpt-5.4",
target_ratio=0.50,
)
assert aggressive_key != default_key
assert aggressive_key != balanced_key
class _DummyMetrics:
async def record_request(self, **kwargs): # noqa: ANN003
return None
async def record_failed(self, **kwargs): # noqa: ANN003
return None
class _DummyTokenizer:
def count_messages(self, messages):
return len(messages)
class _ResponseStub:
status_code = 200
headers = {"content-type": "application/json", "content-length": "42"}
content = b'{"id":"resp_123","output":[{"type":"message"}]}'
def json(self):
return {"usage": {"input_tokens": 2, "output_tokens": 1}}
class _DummyOpenAIHandler(OpenAIHandlerMixin):
OPENAI_API_URL = "https://api.openai.com"
def __init__(self) -> None:
self.rate_limiter = None
self.metrics = _DummyMetrics()
self.config = SimpleNamespace(
optimize=False,
retry_max_attempts=3,
retry_base_delay_ms=10,
retry_max_delay_ms=50,
connect_timeout_seconds=10,
)
self.usage_reporter = None
self.openai_provider = SimpleNamespace(get_context_limit=lambda model: 128_000)
self.openai_pipeline = SimpleNamespace(apply=MagicMock())
self.anthropic_backend = None
self.cost_tracker = None
self.memory_handler = None
# PR-A6 wires session-sticky `OpenAI-Beta` merging into the
# responses HTTP handler — it reads `compute_session_id` to key
# the SessionBetaTracker. The routing tests don't exercise the
# tracker semantics themselves, so a fixed-id stub is enough.
self.session_tracker_store = SimpleNamespace(
compute_session_id=lambda *a, **k: "sess-openai-1",
)
self.captured_request: tuple[str, str, dict, dict] | None = None
self.captured_stream_request: tuple[str, dict, dict] | None = None
async def _next_request_id(self) -> str:
return "req-1"
def _extract_tags(self, headers: dict[str, str]) -> dict[str, str]:
return {}
async def _retry_request(self, method: str, url: str, headers: dict, body: dict):
self.captured_request = (method, url, headers, body)
return _ResponseStub()
async def _run_compression_in_executor(self, fn, *, timeout: float):
# Test stub for HeadroomProxy._run_compression_in_executor.
# The real implementation runs `fn` on a bounded thread pool with
# a wall-clock timeout; tests just need the callable invoked
# synchronously so MagicMock call_count assertions fire.
return fn()
async def _record_request_outcome(self, outcome) -> None:
# Test stub: delegates to the production funnel so wire shape
# matches HeadroomProxy._record_request_outcome.
from headroom.proxy.outcome import emit_request_outcome
await emit_request_outcome(self, outcome)
async def _stream_response(
self,
url: str,
headers: dict,
body: dict,
provider: str,
model: str,
request_id: str,
original_tokens: int,
optimized_tokens: int,
tokens_saved: int,
transforms_applied: list[str],
tags: dict[str, str],
optimization_latency: float,
memory_user_id: str | None = None,
**kwargs,
):
self.captured_stream_request = (url, headers, body)
return SimpleNamespace(
status_code=200,
url=url,
headers=headers,
body=body,
memory_user_id=memory_user_id,
)
def _build_request(body: dict, headers: dict[str, str]) -> Request:
payload = json.dumps(body).encode("utf-8")
async def receive():
return {"type": "http.request", "body": payload, "more_body": False}
scope = {
"type": "http",
"asgi": {"version": "3.0"},
"http_version": "1.1",
"method": "POST",
"scheme": "https",
"path": "/v1/responses",
"raw_path": b"/v1/responses",
"query_string": b"",
"headers": [
(key.lower().encode("utf-8"), value.encode("utf-8")) for key, value in headers.items()
],
"client": ("127.0.0.1", 12345),
"server": ("testserver", 443),
}
return Request(scope, receive)
def test_handle_openai_responses_routes_chatgpt_auth_to_backend_api(monkeypatch):
token = _jwt(
{
"https://api.openai.com/auth": {
"chatgpt_account_id": "acct-from-jwt",
}
}
)
request = _build_request(
{"model": "gpt-5.4", "input": "hello"},
{"Authorization": f"Bearer {token}"},
)
handler = _DummyOpenAIHandler()
monkeypatch.setattr("headroom.tokenizers.get_tokenizer", lambda model: _DummyTokenizer())
response = anyio.run(handler.handle_openai_responses, request)
assert handler.captured_request is not None
method, url, headers, body = handler.captured_request
assert method == "POST"
assert url == "https://chatgpt.com/backend-api/codex/responses"
assert headers["ChatGPT-Account-ID"] == "acct-from-jwt"
assert body["input"] == "hello"
assert response.status_code == 200
def test_handle_openai_responses_chatgpt_codex_timeout_fails_open(monkeypatch):
token = _jwt(
{
"https://api.openai.com/auth": {
"chatgpt_account_id": "acct-from-jwt",
}
}
)
request = _build_request(
{"model": "gpt-5.4", "input": "large context"},
{"Authorization": f"Bearer {token}"},
)
handler = _DummyOpenAIHandler()
handler.config.optimize = True
async def timeout_compression(*args, **kwargs): # noqa: ANN002, ANN003
raise asyncio.TimeoutError()
handler._compress_openai_responses_payload_in_executor = timeout_compression
monkeypatch.setattr("headroom.tokenizers.get_tokenizer", lambda model: _DummyTokenizer())
response = anyio.run(handler.handle_openai_responses, request)
assert response.status_code == 200
assert handler.captured_request is not None
method, url, headers, body = handler.captured_request
assert method == "POST"
assert url == "https://chatgpt.com/backend-api/codex/responses"
assert body["input"] == "large context"
def test_handle_openai_responses_routes_api_key_auth_direct_to_openai(monkeypatch):
request = _build_request(
{"model": "gpt-4o-mini", "input": "hello"},
{"Authorization": "Bearer sk-test"},
)
handler = _DummyOpenAIHandler()
monkeypatch.setattr("headroom.tokenizers.get_tokenizer", lambda model: _DummyTokenizer())
response = anyio.run(handler.handle_openai_responses, request)
assert handler.captured_request is not None
method, url, headers, body = handler.captured_request
assert method == "POST"
assert url == "https://api.openai.com/v1/responses"
assert headers.get("ChatGPT-Account-ID") is None
assert body["input"] == "hello"
assert response.status_code == 200
def test_handle_openai_responses_stream_skips_python_compression(monkeypatch):
"""PR-C5: Python no longer compresses /v1/responses (Rust handles it
natively). The streaming forward path must still fire — only the
Python compression dispatch is retired."""
request = _build_request(
{
"model": "gpt-5.4",
"stream": True,
"instructions": "Keep it short",
"input": [
{
"type": "message",
"role": "user",
"content": [{"type": "input_text", "text": "hello"}],
}
],
},
{"Authorization": "Bearer sk-test"},
)
handler = _DummyOpenAIHandler()
handler.config.optimize = True
monkeypatch.setattr("headroom.tokenizers.get_tokenizer", lambda model: _DummyTokenizer())
response = anyio.run(handler.handle_openai_responses, request)
assert response.status_code == 200
assert handler.captured_stream_request is not None
assert handler.openai_pipeline.apply.call_count == 0
assert handler.captured_stream_request[2]["stream"] is True
def test_handle_openai_responses_memory_timeout_fails_open(monkeypatch):
class _SlowMemoryHandler:
def __init__(self):
self.config = SimpleNamespace(inject_context=True, inject_tools=False)
async def search_and_format_context(self, memory_user_id, messages, **_kwargs):
return "should not be used"
def has_memory_tool_calls(self, response, provider):
return False
async def _timeout_wait_for(awaitable, timeout):
close = getattr(awaitable, "close", None)
if callable(close):
close()
raise TimeoutError
request = _build_request(
{"model": "gpt-5.4", "input": "hello"},
{"Authorization": "Bearer sk-test", "x-headroom-user-id": "user-1"},
)
handler = _DummyOpenAIHandler()
handler.memory_handler = _SlowMemoryHandler()
monkeypatch.setattr("headroom.tokenizers.get_tokenizer", lambda model: _DummyTokenizer())
monkeypatch.setattr("headroom.proxy.handlers.openai.asyncio.wait_for", _timeout_wait_for)
response = anyio.run(handler.handle_openai_responses, request)
assert response.status_code == 200
assert handler.captured_request is not None
_, _, _, body = handler.captured_request
assert body.get("instructions") is None
def test_codex_responses_timeout_fails_open_in_standalone_proxy(monkeypatch):
"""Codex users running only the proxy still get fail-open on timeout."""
request = _build_request(
{
"model": "gpt-5.4",
"input": [
{
"type": "function_call_output",
"call_id": "call-1",
"output": "large tool output",
}
],
},
{"Authorization": "Bearer sk-test", "x-client": "codex"},
)
handler = _DummyOpenAIHandler()
handler.config.optimize = True
monkeypatch.setattr("headroom.tokenizers.get_tokenizer", lambda model: _DummyTokenizer())
monkeypatch.setattr(
handler,
"_compress_openai_responses_payload",
lambda *args, **kwargs: (_ for _ in ()).throw(TimeoutError()),
)
response = anyio.run(handler.handle_openai_responses, request)
assert response.status_code == 200
assert handler.captured_request is not None
_, url, _, body = handler.captured_request
assert url == "https://api.openai.com/v1/responses"
assert body["input"][0]["output"] == "large tool output"
class _DummyWebSocket:
def __init__(self, headers: dict[str, str]):
self.headers = headers
self.accepted_subprotocol = None
async def accept(self, subprotocol=None):
self.accepted_subprotocol = subprotocol
def test_handle_openai_responses_ws_resolves_codex_routing_headers():
class SentinelError(RuntimeError):
pass
handler = _DummyOpenAIHandler()
websocket = _DummyWebSocket({"authorization": "Bearer token"})
with patch.dict(sys.modules, {"websockets": MagicMock()}):
with patch(
"headroom.proxy.handlers.openai._resolve_codex_routing_headers",
side_effect=SentinelError("resolved"),
):
with pytest.raises(SentinelError, match="resolved"):
anyio.run(handler.handle_openai_responses_ws, websocket)