headroom/tests/test_proxy_openai.py
Tejas Chopra 3145242645
Unify savings attribution across stats, perf, metrics, and dashboard (#2976)
## Summary

Adds a small provider-neutral savings attribution seam. Named sources
can attach realized or projected token/USD deltas to a request without
changing headline arithmetic or introducing private-package inventory
into OSS.

Also fixes the Anthropic buffered lifecycle so normal successful
responses run response hooks, applies stream-safety filtering, includes
tool savings in per-model perf totals, and surfaces the same breakdown
in request logs, `/stats`, `headroom perf`, Prometheus, OTEL, and the
dashboard.

## Why

Request-local savings were split between canonical token deltas,
process-global extension counters, and tool-only tags. This made correct
headline totals possible while losing attribution in perf, recent
requests, metrics, and the dashboard. Normal Anthropic responses also
skipped response hooks unless CCR ran.

## Validation

- 74 focused tests passed: turn hooks, OpenAI hook lifecycle, outcome
funnel, perf formats, and tool-search repair
- Ruff passes on all changed Python files
- Existing compression-observability suite: 11 passed; 2 tokenizer-cache
tests require network access to fetch the tiktoken vocabulary

## Compatibility

No named private packages or private inventory are encoded in OSS.
Existing hooks remain source-compatible because all new TurnContext
fields are optional.

---------

Co-authored-by: Tejas Chopra <tejas@Tejass-MacBook-Pro.local>
2026-08-13 17:13:23 -07:00

448 lines
15 KiB
Python

"""Responses tool-search deferral is skipped for harnesses that cannot run it (GH #2660)."""
from __future__ import annotations
import asyncio
import json
from types import SimpleNamespace
import httpx
import pytest
from starlette.datastructures import Headers
from headroom.proxy.auth_mode import classify_client
from headroom.proxy.handlers.openai import OpenAIHandlerMixin
from headroom.proxy.helpers import (
inject_tool_search_deferral_openai,
openai_tool_search_client_supported,
)
TOOL_SEARCH_MODEL = "gpt-5.5"
def _tool_payload() -> list[dict[str, object]]:
"""Six core coding tools plus ten non-core ones, over the injection minimum."""
names = ["bash", "read", "write", "edit", "grep", "glob"]
names += [f"slack_{index}" for index in range(10)]
return [
{"type": "function", "name": name, "parameters": {"type": "object", "properties": {}}}
for name in names
]
@pytest.mark.parametrize(
("headers", "expected_client", "supported"),
[
({"user-agent": "opencode/0.4.2"}, "opencode", False),
({"x-client": "opencode"}, "opencode", False),
({"user-agent": "codex-cli/1.2.3"}, "codex", False),
({"user-agent": "claude-code/2.0"}, "claude-code", True),
({"user-agent": "cursor/1.0"}, "cursor", True),
({}, None, True),
({"user-agent": "some-unknown-sdk/1.0"}, None, True),
# CLIENT_UA_MAP matches by substring, so a wrapper that embeds the
# opencode UA is classified as opencode and excluded with it.
({"user-agent": "acme-wrapper opencode/1.0"}, "opencode", False),
],
)
def test_only_the_reported_harness_is_excluded(
headers: dict[str, str], expected_client: str | None, supported: bool
) -> None:
"""The exclusion keys on the client name the proxy already resolves."""
assert classify_client(headers) == expected_client
assert openai_tool_search_client_supported(classify_client(headers)) is supported
def test_a_similar_client_name_does_not_match() -> None:
"""The exclusion set is exact membership on the resolved client name.
Substring matching happens upstream in ``CLIENT_UA_MAP``; this pins that the
set itself does not widen a name that already classified.
"""
assert openai_tool_search_client_supported("opencode-fork") is True
assert openai_tool_search_client_supported("open") is True
assert openai_tool_search_client_supported("opencode") is False
def test_request_headers_decide_the_outbound_tools_payload() -> None:
"""End of the route: real request headers in, final Responses tools out.
This is the symptom the issue reports. An opencode request must not find an
injected ``{"type": "tool_search"}`` tool it cannot execute, and every other
client must still get the deferral it got before.
"""
tools = _tool_payload()
opencode = Headers({"user-agent": "opencode/0.4.2", "content-type": "application/json"})
forwarded = inject_tool_search_deferral_openai(
tools,
TOOL_SEARCH_MODEL,
client=classify_client(opencode),
)
assert forwarded is tools
assert not any(tool.get("type") == "tool_search" for tool in forwarded)
assert not any(tool.get("defer_loading") for tool in forwarded)
codex = Headers({"user-agent": "codex-cli/1.2.3", "content-type": "application/json"})
forwarded = inject_tool_search_deferral_openai(
tools,
TOOL_SEARCH_MODEL,
client=classify_client(codex),
)
assert forwarded is tools
assert not any(tool.get("type") == "tool_search" for tool in forwarded)
assert not any(tool.get("defer_loading") for tool in tools)
def test_websocket_and_http_header_shapes_classify_alike() -> None:
"""The WebSocket path builds a plain dict from the same multidict."""
multidict = Headers({"user-agent": "opencode/0.4.2"})
assert classify_client(multidict) == "opencode"
assert classify_client(dict(multidict)) == "opencode"
def test_native_responses_compressor_scopes_the_exclusion_per_call() -> None:
"""The flag rides one request; a later request is unaffected by an earlier one."""
seen: list[dict[str, object]] = []
handler = object.__new__(OpenAIHandlerMixin)
async def _run_compression(fn, *, timeout): # noqa: ANN001, ANN202
return fn()
def _compress(payload, *, model, request_id, **kwargs): # noqa: ANN001, ANN202
seen.append(kwargs)
return (payload, False, 0, [], "no-op", 0, 0, 0, {})
handler._run_compression_in_executor = _run_compression
handler._compress_openai_responses_payload = _compress
async def _run() -> None:
await handler._compress_openai_responses_payload_in_executor(
{"input": "hello"},
model=TOOL_SEARCH_MODEL,
request_id="req-opencode",
client="opencode",
)
await handler._compress_openai_responses_payload_in_executor(
{"input": "hello"},
model=TOOL_SEARCH_MODEL,
request_id="req-codex",
)
asyncio.run(_run())
assert [{key: value for key, value in call.items() if key != "timing"} for call in seen] == [
{"client": "opencode"},
{"client": None},
]
def test_supported_clients_send_no_extra_compressor_argument() -> None:
"""A compressor override written before this change keeps its exact signature."""
calls: list[str] = []
handler = object.__new__(OpenAIHandlerMixin)
async def _run_compression(fn, *, timeout): # noqa: ANN001, ANN202
return fn()
def _narrow_compress(payload, *, model, request_id, timing=None): # noqa: ANN001, ANN202
calls.append(request_id)
return (payload, False, 0, [], "no-op", 0, 0, 0, {})
handler._run_compression_in_executor = _run_compression
handler._compress_openai_responses_payload = _narrow_compress
asyncio.run(
handler._compress_openai_responses_payload_in_executor(
{"input": "hello"},
model=TOOL_SEARCH_MODEL,
request_id="req-codex",
)
)
assert calls == ["req-codex"]
def test_a_narrow_compressor_override_still_works_for_an_excluded_client() -> None:
"""The retry drops the optional keywords rather than failing the request."""
calls: list[str] = []
handler = object.__new__(OpenAIHandlerMixin)
async def _run_compression(fn, *, timeout): # noqa: ANN001, ANN202
return fn()
def _narrow_compress(payload, *, model, request_id): # noqa: ANN001, ANN202
calls.append(request_id)
return (payload, False, 0, [], "no-op", 0, 0, 0, {})
handler._run_compression_in_executor = _run_compression
handler._compress_openai_responses_payload = _narrow_compress
asyncio.run(
handler._compress_openai_responses_payload_in_executor(
{"input": "hello"},
model=TOOL_SEARCH_MODEL,
request_id="req-opencode",
client="opencode",
)
)
assert calls == ["req-opencode"]
def test_native_responses_compressor_reraises_internal_type_error() -> None:
"""An internal compressor TypeError is propagated without a signature retry."""
calls = 0
handler = object.__new__(OpenAIHandlerMixin)
sentinel = TypeError("internal compressor failure")
async def _run_compression(fn, *, timeout): # noqa: ANN001, ANN202
return fn()
def _compress(payload, *, model, request_id, client, timing=None): # noqa: ANN001, ANN202
nonlocal calls
calls += 1
raise sentinel
handler._run_compression_in_executor = _run_compression
handler._compress_openai_responses_payload = _compress
with pytest.raises(TypeError) as exc_info:
asyncio.run(
handler._compress_openai_responses_payload_in_executor(
{"input": "hello"},
model=TOOL_SEARCH_MODEL,
request_id="req-opencode",
client="opencode",
)
)
assert exc_info.value is sentinel
assert calls == 1
class _ResponsesRequest:
method = "POST"
url = SimpleNamespace(path="/custom/v1/responses", query="")
def __init__(self, headers: dict[str, str]) -> None:
self.headers = headers
async def body(self) -> bytes:
return json.dumps({"model": TOOL_SEARCH_MODEL, "input": "hello"}).encode()
class _UpstreamClient:
async def request(self, **kwargs): # noqa: ANN001, ANN201
request = httpx.Request(kwargs["method"], kwargs["url"])
return httpx.Response(200, request=request, json={"ok": True})
def _passthrough_handler(seen: list[dict[str, object]]) -> OpenAIHandlerMixin:
handler = object.__new__(OpenAIHandlerMixin)
handler.config = SimpleNamespace(
optimize=True,
compress_passthrough=True,
openai_extra_headers=None,
)
handler.http_client = _UpstreamClient()
handler.http_client_h1 = None
async def _next_request_id() -> str:
return "req-test"
async def _compress(payload, *, model, request_id, **kwargs): # noqa: ANN001, ANN202
seen.append(kwargs)
return (payload, False, 0, [], "no-op", 0, len(json.dumps(payload)), 0, {})
handler._next_request_id = _next_request_id
handler._compress_openai_responses_payload_in_executor = _compress
return handler
def test_custom_base_path_excludes_the_reported_harness() -> None:
seen: list[dict[str, object]] = []
asyncio.run(
_passthrough_handler(seen).handle_passthrough(
_ResponsesRequest({"user-agent": "opencode/0.4.2", "content-type": "application/json"}),
"https://api.example.com",
)
)
assert seen == [{"client": "opencode"}]
def test_custom_base_path_leaves_other_clients_alone() -> None:
seen: list[dict[str, object]] = []
asyncio.run(
_passthrough_handler(seen).handle_passthrough(
_ResponsesRequest(
{"user-agent": "codex-cli/1.2.3", "content-type": "application/json"}
),
"https://api.example.com",
)
)
assert seen == [{"client": "codex"}]
# --- production route: the native /v1/responses handler -----------------------
_OPENAI_OK_RESPONSE = {
"id": "resp_test",
"object": "response",
"status": "completed",
"model": TOOL_SEARCH_MODEL,
"output": [],
"usage": {"input_tokens": 10, "output_tokens": 2},
}
class _NativeCapturingTransport(httpx.AsyncBaseTransport):
def __init__(self) -> None:
self.call_count = 0
async def handle_async_request(self, request: httpx.Request) -> httpx.Response:
self.call_count += 1
async for _ in request.stream:
pass
return httpx.Response(200, json=_OPENAI_OK_RESPONSE)
def _native_responses_client(): # noqa: ANN202
"""Boot the real app and observe what the Responses compressor is handed.
The transport and the spy are installed after the lifespan runs, because
startup builds the proxy's HTTP clients.
"""
pytest.importorskip("fastapi")
from fastapi.testclient import TestClient
from headroom.proxy.server import ProxyConfig, create_app
config = ProxyConfig(
optimize=True,
cache_enabled=False,
rate_limit_enabled=False,
cost_tracking_enabled=False,
log_requests=False,
ccr_inject_tool=False,
ccr_handle_responses=False,
ccr_context_tracking=False,
image_optimize=False,
)
app = create_app(config)
seen: list[dict[str, object]] = []
# Loopback client so the proxy-token middleware treats this as a local call.
with TestClient(app, client=("127.0.0.1", 50000)) as client:
proxy = app.state.proxy
transport = _NativeCapturingTransport()
proxy.http_client = httpx.AsyncClient(transport=transport)
proxy.http_client_h1 = httpx.AsyncClient(transport=transport)
original = proxy._compress_openai_responses_payload_in_executor
async def _spy(payload, **kwargs): # noqa: ANN001, ANN202
seen.append({k: v for k, v in kwargs.items() if k not in {"model", "request_id"}})
return await original(payload, **kwargs)
proxy._compress_openai_responses_payload_in_executor = _spy
yield client, seen, transport
def _responses_body() -> dict[str, object]:
return {"model": TOOL_SEARCH_MODEL, "input": "hello", "tools": _tool_payload()}
@pytest.mark.parametrize(
("user_agent", "expected"),
[
("opencode/0.4.2", {"client": "opencode"}),
("codex-cli/1.2.3", {"client": "codex"}),
],
)
def test_native_responses_route_carries_the_client_decision(
user_agent: str, expected: dict[str, object]
) -> None:
"""Drives POST /v1/responses on the real app, not a handler method in isolation.
Deleting the kwargs splat at the native call site leaves every other test in
this file green; this one fails.
"""
for client, seen, transport in _native_responses_client():
response = client.post(
"/v1/responses",
headers={
"content-type": "application/json",
"authorization": "Bearer sk-test-0000000000000000000000000000000000000000000",
"user-agent": user_agent,
},
json=_responses_body(),
)
assert transport.call_count == 1, response.text
assert response.status_code == 200, response.text
assert seen, "the Responses compressor was never reached"
assert {k: v for k, v in seen[0].items() if k not in {"timing", "savings_tags"}} == expected
# --- production route: the Codex WebSocket handler ---------------------------
@pytest.mark.parametrize(
("user_agent", "expected"),
[
("opencode/0.4.2", {"client": "opencode"}),
("codex-cli/1.2.3", {"client": "codex"}),
],
)
def test_websocket_route_carries_the_client_decision(
user_agent: str, expected: dict[str, object]
) -> None:
"""The WS frame path resolves the client the same way the HTTP path does.
Reuses the repo's existing Codex WS harness so the real
``handle_openai_responses_ws`` ingress runs, rather than asserting the
wiring structurally.
"""
import sys
from unittest.mock import patch
from tests.test_openai_codex_ws_lifecycle import (
_DummyOpenAIHandler,
_FakeUpstream,
_FakeWebSocket,
_first_frame,
_make_fake_websockets_module,
)
upstream = _FakeUpstream(
[
json.dumps({"type": "response.created", "response": {"id": "r_1"}}),
json.dumps({"type": "response.completed", "response": {"id": "r_1"}}),
]
)
client_ws = _FakeWebSocket(
frames=[_first_frame()],
headers={"authorization": "Bearer test", "user-agent": user_agent},
)
handler = _DummyOpenAIHandler()
handler.config.optimize = True
seen: list[dict[str, object]] = []
def _compress(payload, *, model, request_id, **kwargs): # noqa: ANN001, ANN202
seen.append(kwargs)
return (payload, False, 0, [], "router_no_compression", 10, 10)
handler._compress_openai_responses_payload = _compress
with patch.dict(sys.modules, {"websockets": _make_fake_websockets_module(upstream)}):
asyncio.run(handler.handle_openai_responses_ws(client_ws))
assert seen, "the Responses compressor was never reached on the WS path"
assert {k: v for k, v in seen[0].items() if k != "timing"} == expected