headroom/tests/test_proxy_handler_helpers.py
Tejas Chopra 248ae0f3e0
fix(proxy): freeze must forward cached (compressed) prefix byte-identical — stop token-mode cache busting (#1850)
The freeze path (both providers) emits the agent's ORIGINAL bytes for a
frozen message, but the provider cached whatever we FORWARDED last turn
(the compressed form). Forwarding original then mismatches the cached
prefix and busts it from that point — re-creating the whole suffix.
Measured on a real SWE-bench run: 100% of attributed misses were
prefix_change, ~56% of ALL cache-writes were bust-induced (2.8M tokens),
driving cache_create +150% and cost +41% vs baseline.

Cache mode already avoided this via _extract_cache_stable_delta (replay
the previously-forwarded prefix, compress only the delta). Token mode
called apply(frozen_count) directly, which forwards original for the
frozen region.

Fix: add a shared, provider-agnostic overlay_cached_prefix() that
replays the previously-forwarded (cached, compressed) prefix
byte-identical, append-only guarded and idempotent, and apply it in BOTH
the Anthropic and OpenAI handlers right before forwarding. This makes
freezing byte-identical in every mode, so the only remaining difference
between "token" and "cache" mode is how large a mutable
(still-compressible) tail each leaves — not whether the frozen prefix
busts the cache.

Tests:
- test_cache_prefix_overlay.py: the helper (replay, append-only guard,
idempotence).
- test_cross_turn_cache_safety.py: the invariant that was missing —
drive the REAL tracker + freeze + overlay over multiple append-only
turns against a simulated provider prefix cache and assert the forwarded
prefix stays byte-identical turn-over-turn. Load-bearing: it fails
(detects the bust) without the overlay.

## Description

<!-- Briefly explain the change and why it is needed. -->

Closes #

## Type of Change

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

- 

## Testing

<!-- Check what you actually ran, then paste the real command output
below. -->

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

### Test Output

```text
# Paste relevant command output or artifact links here
```

## Real Behavior Proof

- Environment:
- Exact command / steps:
- Observed result:
- Not tested:

## Review Readiness

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

## Checklist

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

## Screenshots (if applicable)

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## Additional Notes

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maintainer context. -->
2026-07-06 14:54:39 -07:00

957 lines
32 KiB
Python

from __future__ import annotations
import asyncio
import base64
import builtins
import json
from types import SimpleNamespace
from unittest.mock import patch
import httpx
from fastapi.responses import StreamingResponse
from headroom.proxy.handlers.anthropic import AnthropicHandlerMixin
from headroom.proxy.handlers.openai import (
OpenAIHandlerMixin,
_decode_openai_bearer_payload,
_passthrough_usage_from_json,
_prefers_http1_passthrough,
)
from headroom.proxy.helpers import _headroom_bypass_enabled
from headroom.proxy.server import HeadroomProxy
def _jwt(payload: object) -> str:
header = {"alg": "none", "typ": "JWT"}
def encode(part: object) -> str:
raw = json.dumps(part, separators=(",", ":")).encode("utf-8")
return base64.urlsafe_b64encode(raw).decode("ascii").rstrip("=")
return f"{encode(header)}.{encode(payload)}."
class _ImageCompressor:
def __init__(self, compressed_message):
self._compressed_message = compressed_message
def compress(self, messages, provider): # noqa: ANN001, ANN201
assert provider == "anthropic"
return [self._compressed_message]
class _FreshCompressor:
instances = 0
def __init__(self):
type(self).instances += 1
class _TimeoutHttpClient:
async def request(self, **kwargs): # noqa: ANN001, ANN201
raise httpx.ConnectTimeout("connect timed out")
class _RecordingHttpClient:
def __init__(self, label: str) -> None:
self.label = label
self.calls = 0
async def request(self, **kwargs): # noqa: ANN001, ANN201
self.calls += 1
request = httpx.Request(kwargs["method"], kwargs["url"])
return httpx.Response(
200,
request=request,
headers={"content-type": "application/json"},
json={"client": self.label},
)
class _ChatGPTAccountRequest:
method = "GET"
headers = {}
url = SimpleNamespace(path="/backend-api/me", query="")
async def body(self) -> bytes:
return b""
class _PassthroughRequest:
method = "GET"
headers = {}
url = SimpleNamespace(path="/favicon.ico", query="")
async def body(self) -> bytes:
return b""
class _VertexPassthroughRequest:
method = "POST"
headers = {}
url = SimpleNamespace(
path="/v1/projects/p/locations/us-central1/publishers/google/models/gemini-2.0-flash:generateContent",
query="",
)
async def body(self) -> bytes:
return b'{"contents":[]}'
class _VertexStreamPassthroughRequest:
method = "POST"
headers = {}
url = SimpleNamespace(
path="/v1/projects/p/locations/us-central1/publishers/google/models/gemini-2.0-flash:streamGenerateContent",
query="alt=sse",
)
async def body(self) -> bytes:
return b'{"contents":[]}'
class _VertexGeminiImageRequest:
method = "POST"
headers = {}
query_params = {}
url = SimpleNamespace(
path="/v1/projects/p/locations/us-central1/publishers/google/models/gemini-2.0-flash:generateContent",
query="",
)
async def body(self) -> bytes:
return json.dumps(
{
"contents": [
{
"role": "user",
"parts": [
{
"inlineData": {
"mimeType": "image/png",
"data": "aW1hZ2U=",
}
}
],
}
]
}
).encode("utf-8")
class _VertexUsageClient:
async def request(self, **kwargs): # noqa: ANN001, ANN201
request = httpx.Request(kwargs["method"], kwargs["url"], content=kwargs["content"])
return httpx.Response(
200,
request=request,
headers={"content-type": "application/json"},
json={
"candidates": [{"content": {"parts": [{"text": "ok"}]}}],
"usageMetadata": {
"promptTokenCount": 11,
"candidatesTokenCount": 7,
"cachedContentTokenCount": 3,
},
},
)
class _AsyncChunks(httpx.AsyncByteStream):
def __init__(self, chunks: list[bytes]) -> None:
self._chunks = chunks
async def __aiter__(self): # noqa: ANN204
for chunk in self._chunks:
yield chunk
class _VertexStreamClient:
def __init__(self) -> None:
self.sent_url = ""
def build_request(self, method, url, headers, content): # noqa: ANN001, ANN201
self.sent_url = str(url)
return httpx.Request(method, url, headers=headers, content=content)
async def send(self, request, stream=False): # noqa: ANN001, ANN201
assert stream is True
return httpx.Response(
200,
request=request,
headers={"content-type": "text/event-stream"},
stream=_AsyncChunks(
[
b'data: {"candidates":[{"content":{"parts":[{"text":"hello"}]}}]}\n\n',
b'data: {"usageMetadata":{"promptTokenCount":13,'
b'"candidatesTokenCount":5,"cachedContentTokenCount":2}}\n\n',
]
),
)
class _RetryThenSuccessClient:
def __init__(self) -> None:
self.attempts = 0
async def post(self, url, content, headers, timeout=None): # noqa: ANN001, ANN201
self.attempts += 1
if self.attempts == 1:
raise httpx.ConnectTimeout("connect timed out")
del timeout
request = httpx.Request("POST", url, headers=headers, content=content)
return httpx.Response(200, request=request, content=b"{}")
def test_decode_openai_bearer_payload_handles_missing_and_non_mapping_payloads() -> None:
assert _decode_openai_bearer_payload({}) is None
assert _decode_openai_bearer_payload({"authorization": "Basic abc"}) is None
assert (
_decode_openai_bearer_payload({"authorization": f"Bearer {_jwt(['not', 'a', 'dict'])}"})
is None
)
def test_openai_handler_prefix_helpers_cover_edge_cases() -> None:
assert OpenAIHandlerMixin._strict_previous_turn_frozen_count([], 2) == 2
assert (
OpenAIHandlerMixin._strict_previous_turn_frozen_count(
[{"role": "assistant"}, {"role": "user"}],
0,
)
== 1
)
assert (
OpenAIHandlerMixin._strict_previous_turn_frozen_count(
[{"role": "user"}, {"role": "assistant"}],
0,
)
== 2
)
original = [{"role": "system", "content": "keep"}, {"role": "user", "content": "hello"}]
restored, changed = OpenAIHandlerMixin._restore_frozen_prefix(
original,
[],
frozen_message_count=1,
)
assert restored == [{"role": "system", "content": "keep"}]
assert changed == 1
restored, changed = OpenAIHandlerMixin._restore_frozen_prefix(
original,
[{"role": "system", "content": "changed"}, {"role": "user", "content": "hello"}],
frozen_message_count=1,
)
assert restored == original
assert changed == 1
def test_headroom_bypass_helper_is_transport_neutral() -> None:
assert _headroom_bypass_enabled({"x-headroom-bypass": "true"}) is True
assert _headroom_bypass_enabled({"x-headroom-bypass": " TRUE "}) is True
assert _headroom_bypass_enabled({"x-headroom-mode": "passthrough"}) is True
assert _headroom_bypass_enabled({"x-headroom-mode": " PASSTHROUGH "}) is True
assert _headroom_bypass_enabled({"x-headroom-bypass": "false"}) is False
assert _headroom_bypass_enabled({}) is False
assert _headroom_bypass_enabled(None) is False
assert OpenAIHandlerMixin._headroom_bypass_enabled({"x-headroom-bypass": "true"}) is True
def test_openai_passthrough_connect_timeout_returns_502() -> None:
handler = object.__new__(OpenAIHandlerMixin)
handler.http_client = _TimeoutHttpClient()
async def run():
return await handler.handle_passthrough(
_PassthroughRequest(),
"https://api.openai.com",
)
response = asyncio.run(run())
assert response.status_code == 502
payload = json.loads(response.body)
assert payload["error"]["type"] == "connection_error"
assert "Failed to connect to upstream API" in payload["error"]["message"]
def test_prefers_http1_passthrough_matches_chatgpt_hosts_only() -> None:
assert _prefers_http1_passthrough("https://chatgpt.com") is True
assert _prefers_http1_passthrough("https://chatgpt.com/backend-api/me") is True
assert _prefers_http1_passthrough("https://api.chatgpt.com") is True
assert _prefers_http1_passthrough("https://CHATGPT.COM/backend-api/me") is True
assert _prefers_http1_passthrough("https://api.openai.com") is False
assert _prefers_http1_passthrough("https://notchatgpt.com") is False
assert _prefers_http1_passthrough("https://chatgpt.com.evil.com") is False
assert _prefers_http1_passthrough("") is False
def test_chatgpt_passthrough_uses_http1_client() -> None:
handler = object.__new__(OpenAIHandlerMixin)
handler.http_client = _RecordingHttpClient("h2")
handler.http_client_h1 = _RecordingHttpClient("h1")
response = asyncio.run(
handler.handle_passthrough(_ChatGPTAccountRequest(), "https://chatgpt.com")
)
assert response.status_code == 200
assert json.loads(response.body)["client"] == "h1"
assert handler.http_client.calls == 0
assert handler.http_client_h1.calls == 1
def test_non_chatgpt_passthrough_uses_default_client() -> None:
handler = object.__new__(OpenAIHandlerMixin)
handler.http_client = _RecordingHttpClient("h2")
handler.http_client_h1 = _RecordingHttpClient("h1")
response = asyncio.run(
handler.handle_passthrough(_PassthroughRequest(), "https://api.openai.com")
)
assert response.status_code == 200
assert json.loads(response.body)["client"] == "h2"
assert handler.http_client.calls == 1
assert handler.http_client_h1.calls == 0
def test_chatgpt_passthrough_falls_back_when_h1_client_missing() -> None:
handler = object.__new__(OpenAIHandlerMixin)
handler.http_client = _RecordingHttpClient("h2")
handler.http_client_h1 = None
response = asyncio.run(
handler.handle_passthrough(_ChatGPTAccountRequest(), "https://chatgpt.com")
)
assert response.status_code == 200
assert json.loads(response.body)["client"] == "h2"
assert handler.http_client.calls == 1
def test_passthrough_usage_normalizes_vertex_usage_metadata() -> None:
usage = _passthrough_usage_from_json(
{
"usageMetadata": {
"promptTokenCount": 11,
"candidatesTokenCount": 7,
"cachedContentTokenCount": 3,
}
}
)
assert usage == {
"input_tokens": 11,
"output_tokens": 7,
"cache_read_input_tokens": 3,
}
def test_vertex_passthrough_records_usage_metadata_for_dashboard() -> None:
handler = object.__new__(HeadroomProxy)
handler.http_client = _VertexUsageClient()
outcomes = []
async def next_request_id(): # noqa: ANN202
return "req_vertex"
async def record(outcome): # noqa: ANN001, ANN202
outcomes.append(outcome)
handler._next_request_id = next_request_id
handler._record_request_outcome = record
response = asyncio.run(
handler.handle_passthrough(
_VertexPassthroughRequest(),
"https://vertex.test",
"generateContent",
"vertex:google",
)
)
assert response.status_code == 200
assert len(outcomes) == 1
outcome = outcomes[0]
assert outcome.provider == "vertex:google"
assert outcome.model == "gemini-2.0-flash"
assert outcome.optimized_tokens == 11
assert outcome.output_tokens == 7
assert outcome.cache_read_tokens == 3
def test_vertex_stream_passthrough_preserves_chunks_and_records_usage() -> None:
handler = object.__new__(HeadroomProxy)
handler.http_client = _VertexStreamClient()
outcomes = []
async def next_request_id(): # noqa: ANN202
return "req_vertex_stream"
async def record(outcome): # noqa: ANN001, ANN202
outcomes.append(outcome)
handler._next_request_id = next_request_id
handler._record_request_outcome = record
response = asyncio.run(
handler.handle_passthrough(
_VertexStreamPassthroughRequest(),
"https://vertex.test",
"streamGenerateContent",
"vertex:google",
)
)
assert isinstance(response, StreamingResponse)
async def collect(): # noqa: ANN202
return [chunk async for chunk in response.body_iterator]
chunks = asyncio.run(collect())
assert len(chunks) == 2
assert chunks[0].startswith(b'data: {"candidates"')
assert b'"usageMetadata"' in chunks[1]
assert len(outcomes) == 1
outcome = outcomes[0]
assert outcome.provider == "vertex:google"
assert outcome.model == "gemini-2.0-flash"
assert outcome.optimized_tokens == 13
assert outcome.output_tokens == 5
assert outcome.cache_read_tokens == 2
def test_stream_finalizer_records_vertex_provider_for_dashboard() -> None:
handler = object.__new__(HeadroomProxy)
handler.config = SimpleNamespace(log_full_messages=False)
outcomes = []
async def record(outcome): # noqa: ANN001, ANN202
outcomes.append(outcome)
handler._record_request_outcome = record
asyncio.run(
handler._finalize_stream_response(
body={"contents": [{"role": "user", "parts": [{"text": "hello"}]}]},
provider="gemini",
outcome_provider="vertex:google",
model="gemini-2.0-flash",
request_id="req_vertex_stream_final",
original_tokens=20,
optimized_tokens=12,
tokens_saved=8,
transforms_applied=["test-transform"],
optimization_latency=3.0,
stream_state={
"input_tokens": 12,
"output_tokens": 5,
"cache_read_input_tokens": 2,
"cache_creation_input_tokens": 0,
"cache_creation_ephemeral_5m_input_tokens": 0,
"cache_creation_ephemeral_1h_input_tokens": 0,
"total_bytes": 100,
"sse_buffer": bytearray(),
"ttfb_ms": 4.0,
},
start_time=0.0,
tags={"route": "vertex"},
)
)
assert len(outcomes) == 1
outcome = outcomes[0]
assert outcome.provider == "vertex:google"
assert outcome.model == "gemini-2.0-flash"
assert outcome.optimized_tokens == 12
assert outcome.output_tokens == 5
assert outcome.tokens_saved == 8
assert outcome.cache_read_tokens == 2
def test_vertex_gemini_non_text_generate_records_dashboard_outcome() -> None:
handler = object.__new__(HeadroomProxy)
handler.memory_handler = None
handler.rate_limiter = None
outcomes = []
upstream_urls = []
async def next_request_id(): # noqa: ANN202
return "req_vertex_image"
async def record(outcome): # noqa: ANN001, ANN202
outcomes.append(outcome)
async def retry_request(method, url, headers, body): # noqa: ANN001, ANN202
upstream_urls.append(url)
request = httpx.Request(method, url, headers=headers)
return httpx.Response(
200,
request=request,
headers={"content-type": "application/json"},
json={
"usageMetadata": {
"promptTokenCount": 31,
"candidatesTokenCount": 4,
"cachedContentTokenCount": 6,
}
},
)
handler._next_request_id = next_request_id
handler._record_request_outcome = record
handler._retry_request = retry_request
response = asyncio.run(
handler.handle_gemini_generate_content(
_VertexGeminiImageRequest(),
"gemini-2.0-flash",
"https://vertex.test",
"vertex:google",
)
)
assert response.status_code == 200
assert upstream_urls == [
"https://vertex.test/v1/projects/p/locations/us-central1/publishers/google/models/gemini-2.0-flash:generateContent"
]
assert response.headers["x-headroom-tokens-before"] == "31"
assert response.headers["x-headroom-tokens-after"] == "31"
assert response.headers["x-headroom-tokens-saved"] == "0"
assert len(outcomes) == 1
outcome = outcomes[0]
assert outcome.provider == "vertex:google"
assert outcome.model == "gemini-2.0-flash"
assert outcome.original_tokens == 31
assert outcome.optimized_tokens == 31
assert outcome.output_tokens == 4
assert outcome.cache_read_tokens == 6
assert outcome.num_messages == 1
def test_retry_request_retries_connect_timeout() -> None:
proxy = object.__new__(HeadroomProxy)
proxy.http_client = _RetryThenSuccessClient()
proxy.config = SimpleNamespace(
retry_enabled=True,
retry_max_attempts=2,
retry_base_delay_ms=0,
retry_max_delay_ms=0,
)
response = asyncio.run(
proxy._retry_request(
"POST",
"https://api.openai.com/v1/responses",
{},
{"model": "gpt-5"},
)
)
assert response.status_code == 200
assert proxy.http_client.attempts == 2
def test_retry_request_returns_503_when_shutdown_interrupts_retry_sleep() -> None:
class _Always429Client:
def __init__(self) -> None:
self.attempts = 0
async def post(self, url, **kwargs): # type: ignore[no-untyped-def]
self.attempts += 1
return httpx.Response(
429,
request=httpx.Request("POST", url),
json={"error": {"message": "slow down"}},
headers={"retry-after": "30"},
)
proxy = object.__new__(HeadroomProxy)
proxy.http_client = _Always429Client()
proxy.config = SimpleNamespace(
retry_enabled=True,
retry_max_attempts=3,
retry_base_delay_ms=30000,
retry_max_delay_ms=30000,
)
proxy._shutdown_event = asyncio.Event()
proxy._shutdown_event.set()
response = asyncio.run(
proxy._retry_request(
"POST",
"https://api.anthropic.test/v1/messages",
{},
{"model": "claude-3-5-sonnet"},
)
)
assert response.status_code == 503
assert response.json() == {
"error": {
"type": "shutdown",
"message": "Proxy is shutting down; retry backoff cancelled.",
}
}
assert response.headers["retry-after"] == "0"
assert proxy.http_client.attempts == 1
def test_anthropic_tool_sort_and_context_append_helpers() -> None:
tools = [
{"type": "function", "function": {"name": "beta"}},
{"name": "alpha"},
{"type": "tool"},
]
sorted_tools = AnthropicHandlerMixin._sort_tools_deterministically(tools)
assert [AnthropicHandlerMixin._tool_sort_key(tool)[0] for tool in sorted_tools] == [
"alpha",
"beta",
"tool",
]
assert AnthropicHandlerMixin._sort_tools_deterministically(None) is None
assert AnthropicHandlerMixin._tools_for_forwarding(tools, preserve_order=True) == tools
assert [
AnthropicHandlerMixin._tool_sort_key(tool)[0]
for tool in AnthropicHandlerMixin._tools_for_forwarding(tools, preserve_order=False) or []
] == [
"alpha",
"beta",
"tool",
]
assert (
AnthropicHandlerMixin._append_context_to_latest_non_frozen_user_turn(
[], "ctx", frozen_message_count=0
)
== []
)
assert AnthropicHandlerMixin._append_context_to_latest_non_frozen_user_turn(
[{"role": "user", "content": "hello"}],
"ctx",
frozen_message_count=0,
) == [{"role": "user", "content": "hello\n\nctx"}]
# PR-A2 semantics: list-content user messages get the context appended
# to the first text block (live-zone-tail injection).
assert AnthropicHandlerMixin._append_context_to_latest_non_frozen_user_turn(
[{"role": "user", "content": [{"type": "text", "text": "hello"}]}],
"ctx",
frozen_message_count=0,
) == [{"role": "user", "content": [{"type": "text", "text": "hello\n\nctx"}]}]
def test_anthropic_image_compression_helper_only_rewrites_latest_eligible_turn() -> None:
image_message = {
"role": "user",
"content": [{"type": "image", "source": {"type": "base64", "data": "abc"}}],
}
compressed = {
"role": "user",
"content": [{"type": "image", "source": {"type": "base64", "data": "xyz"}}],
}
assert (
AnthropicHandlerMixin._compress_latest_user_turn_images_cache_safe(
[],
frozen_message_count=0,
compressor=_ImageCompressor(compressed),
)
== []
)
assert AnthropicHandlerMixin._compress_latest_user_turn_images_cache_safe(
[image_message],
frozen_message_count=1,
compressor=_ImageCompressor(compressed),
) == [image_message]
assert AnthropicHandlerMixin._compress_latest_user_turn_images_cache_safe(
[{"role": "assistant", "content": image_message["content"]}],
frozen_message_count=0,
compressor=_ImageCompressor(compressed),
) == [{"role": "assistant", "content": image_message["content"]}]
assert AnthropicHandlerMixin._compress_latest_user_turn_images_cache_safe(
[{"role": "user", "content": "no-image"}],
frozen_message_count=0,
compressor=_ImageCompressor(compressed),
) == [{"role": "user", "content": "no-image"}]
assert AnthropicHandlerMixin._compress_latest_user_turn_images_cache_safe(
[image_message],
frozen_message_count=0,
compressor=_ImageCompressor(image_message),
) == [image_message]
assert AnthropicHandlerMixin._compress_latest_user_turn_images_cache_safe(
[image_message],
frozen_message_count=0,
compressor=_ImageCompressor(compressed),
) == [compressed]
def test_proxy_helper_creates_fresh_image_compressors(monkeypatch) -> None:
from headroom.proxy import helpers
monkeypatch.setattr(helpers, "_image_compressor_available", None)
_FreshCompressor.instances = 0
with patch("headroom.image.ImageCompressor", _FreshCompressor):
first = helpers._get_image_compressor()
second = helpers._get_image_compressor()
assert isinstance(first, _FreshCompressor)
assert isinstance(second, _FreshCompressor)
assert first is not second
assert _FreshCompressor.instances == 2
def test_proxy_helper_caches_image_stack_import_failure(monkeypatch) -> None:
from headroom.proxy import helpers
real_import = builtins.__import__
calls = 0
def fake_import(name, *args, **kwargs): # noqa: ANN001, ANN202
nonlocal calls
if name == "headroom.image":
calls += 1
raise ImportError("image extras unavailable")
return real_import(name, *args, **kwargs)
monkeypatch.setattr(helpers, "_image_compressor_available", None)
monkeypatch.setattr(builtins, "__import__", fake_import)
assert helpers._get_image_compressor() is None
assert helpers._get_image_compressor() is None
assert calls == 1
assert helpers._image_compressor_available is False
def test_anthropic_cache_delta_helpers_cover_string_list_and_role_mismatch() -> None:
previous_original = [{"role": "user", "content": "hello"}]
previous_forwarded = [{"role": "user", "content": "HELLO"}]
assert AnthropicHandlerMixin._extract_cache_stable_delta(
[{"role": "user", "content": "hello"}, {"role": "assistant", "content": "next"}],
previous_original,
previous_forwarded,
) == (previous_forwarded, [{"role": "assistant", "content": "next"}])
assert (
AnthropicHandlerMixin._extract_cache_stable_delta(
[{"role": "assistant", "content": "hello"}],
previous_original,
previous_forwarded,
)
is None
)
string_suffix = AnthropicHandlerMixin._extract_cache_stable_last_message_suffix(
[{"role": "user", "content": "hello world"}],
previous_original,
previous_forwarded,
)
assert string_suffix == ([], previous_forwarded[0], [{"role": "user", "content": " world"}])
list_suffix = AnthropicHandlerMixin._extract_cache_stable_last_message_suffix(
[
{
"role": "user",
"content": [{"type": "text", "text": "a"}, {"type": "text", "text": "b"}],
}
],
[{"role": "user", "content": [{"type": "text", "text": "a"}]}],
[{"role": "user", "content": [{"type": "text", "text": "A"}]}],
)
assert list_suffix == (
[],
{"role": "user", "content": [{"type": "text", "text": "A"}]},
[{"role": "user", "content": [{"type": "text", "text": "b"}]}],
)
assert AnthropicHandlerMixin._merge_appended_message_delta(
{"role": "user", "content": "HELLO"},
{"role": "user", "content": " world"},
) == {"role": "user", "content": "HELLO world"}
assert AnthropicHandlerMixin._merge_appended_message_delta(
{"role": "user", "content": [{"type": "text", "text": "A"}]},
{"role": "user", "content": [{"type": "text", "text": "b"}]},
) == {"role": "user", "content": [{"type": "text", "text": "A"}, {"type": "text", "text": "b"}]}
assert (
AnthropicHandlerMixin._merge_appended_message_delta(
{"role": "user", "content": "A"},
{"role": "assistant", "content": "B"},
)
is None
)
def test_anthropic_assistant_message_helper_requires_assistant_role() -> None:
assert AnthropicHandlerMixin._assistant_message_from_response_json(None) is None
assert AnthropicHandlerMixin._assistant_message_from_response_json({"role": "user"}) is None
assert AnthropicHandlerMixin._assistant_message_from_response_json(
{"role": "assistant", "content": [{"type": "text", "text": "ok"}]}
) == {"role": "assistant", "content": [{"type": "text", "text": "ok"}]}
# ============================================================================
# CCR workspace resolution (cross-project leak fix, 2026-05-26).
#
# These tests pin the `_resolve_ccr_workspace` static helper that the
# anthropic handler uses to scope the proactive-expansion cache by
# project identity. The resolver shares its tier order with the memory
# subsystem's ProjectResolver: x-headroom-project-id → x-headroom-cwd →
# system-prompt `cwd:` line. Returns `("", None)` on no signal — the
# fail-closed signal that callers gate on.
# ============================================================================
def _fake_request(headers: dict[str, str]) -> SimpleNamespace:
"""Minimal Starlette/FastAPI-shaped request object for resolver tests."""
return SimpleNamespace(headers=headers)
def test_resolve_ccr_workspace_explicit_project_id_wins() -> None:
"""x-headroom-project-id is the highest-priority signal."""
request = _fake_request({"x-headroom-project-id": "my-cool-project"})
body = {}
key, label = AnthropicHandlerMixin._resolve_ccr_workspace(request, body)
assert key == "my-cool-project"
assert label == "my-cool-project"
def test_resolve_ccr_workspace_cwd_header() -> None:
"""x-headroom-cwd produces a stable per-cwd key + basename label."""
request = _fake_request({"x-headroom-cwd": "/home/user/code/daphni-rails"})
body = {}
key, label = AnthropicHandlerMixin._resolve_ccr_workspace(request, body)
# Key format: "{basename}-{sha256[:16]}" — stable per absolute cwd.
assert key.startswith("daphni-rails-")
assert len(key) >= len("daphni-rails-") + 16
assert label == "daphni-rails"
def test_resolve_ccr_workspace_two_cwds_get_distinct_keys() -> None:
"""Two different cwds produce different workspace keys (cross-leak prevention)."""
key_a, _ = AnthropicHandlerMixin._resolve_ccr_workspace(
_fake_request({"x-headroom-cwd": "/home/user/code/daphni-rails"}), {}
)
key_b, _ = AnthropicHandlerMixin._resolve_ccr_workspace(
_fake_request({"x-headroom-cwd": "/home/user/code/tamag0"}), {}
)
assert key_a != key_b, "different cwds must yield different workspace keys"
def test_resolve_ccr_workspace_no_signal_returns_empty() -> None:
"""No project-id, no cwd header, no system prompt → fail-closed signal."""
request = _fake_request({})
body = {}
key, label = AnthropicHandlerMixin._resolve_ccr_workspace(request, body)
assert key == ""
assert label is None
def test_resolve_ccr_workspace_system_prompt_cwd_fallback() -> None:
"""System prompt with `cwd:` line is the lowest-tier fallback."""
request = _fake_request({})
body = {
"system": [{"type": "text", "text": "You are helpful.\ncwd: /home/u/code/my-project\nGo."}]
}
key, label = AnthropicHandlerMixin._resolve_ccr_workspace(request, body)
# The label is the basename of the cwd extracted from the prompt.
assert label == "my-project"
assert key.startswith("my-project-")
def test_resolve_ccr_workspace_malformed_request_returns_empty() -> None:
"""A request whose headers attribute can't be dict()-ed fails closed, not crashes."""
class _BrokenHeaders:
def __iter__(self):
raise RuntimeError("boom")
request = SimpleNamespace(headers=_BrokenHeaders())
body = {}
# The helper catches the exception, logs it, and returns the fail-
# closed sentinel ("", None). Critically, it does NOT raise — the
# proxy must continue serving the request even if CCR scoping fails.
key, label = AnthropicHandlerMixin._resolve_ccr_workspace(request, body)
assert key == ""
assert label is None
class TestHasNewCcrMarkers:
"""#1850: replayed (overlay) markers must not count as new-this-turn.
``overlay_cached_prefix`` replays the previously-forwarded compressed prefix
byte-identical to keep the messages cache warm — which reintroduces its old
``hash=…`` markers. If those replayed markers counted as "new", the handler
would re-inject the retrieve tool every frozen turn and bust the *tools*
cache. ``has_new_ccr_markers`` filters them out.
"""
@staticmethod
def _hashes(*contents: str) -> list[str]:
from headroom.ccr.tool_injection import CCRToolInjector
inj = CCRToolInjector(
provider="anthropic", inject_tool=False, inject_system_instructions=False
)
inj.scan_for_markers([{"role": "user", "content": c} for c in contents])
return inj.detected_hashes
def test_replayed_markers_are_not_new(self):
from headroom.proxy.helpers import has_new_ccr_markers
marker = "[100 items compressed to 10. Retrieve more: hash=abc123def456abc123def456]"
current = self._hashes(marker)
assert current, "sanity: the marker must be detected"
# Every marker was already in what we forwarded last turn → nothing new.
assert (
has_new_ccr_markers(
current_detected_hashes=current,
previous_forwarded_messages=[{"role": "user", "content": marker}],
provider="anthropic",
)
is False
)
def test_genuinely_new_marker_is_detected(self):
from headroom.proxy.helpers import has_new_ccr_markers
old = "[100 items compressed to 10. Retrieve more: hash=abc123def456abc123def456]"
new = "[50 items compressed to 5. Retrieve more: hash=deadbeefdeadbeefdeadbeef]"
current = self._hashes(old, new)
# Only `old` was forwarded before; `new` is fresh → override must fire.
assert (
has_new_ccr_markers(
current_detected_hashes=current,
previous_forwarded_messages=[{"role": "user", "content": old}],
provider="anthropic",
)
is True
)
def test_no_previous_forward_means_all_new(self):
from headroom.proxy.helpers import has_new_ccr_markers
marker = "[100 items compressed to 10. Retrieve more: hash=abc123def456abc123def456]"
assert (
has_new_ccr_markers(
current_detected_hashes=self._hashes(marker),
previous_forwarded_messages=None,
provider="anthropic",
)
is True
)
def test_no_markers_means_nothing_new(self):
from headroom.proxy.helpers import has_new_ccr_markers
assert (
has_new_ccr_markers(
current_detected_hashes=[],
previous_forwarded_messages=None,
provider="anthropic",
)
is False
)