Files
Open_Ultra_SAST/tests/test_model_endpoint.py
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Marius CiepluchandClaude Opus 5 9ed0e45c5f feat(model-grounded-detection): group 1, subtract the noise architecture
99 source modules -> 81. 832 tests -> 646. The whole learning/ package (16
modules, ~4,100 lines) and six semantic/ modules removed, with the three gates
byte-identical to 2026-09-06-gate-baseline.txt at every step.

The sequence is what made it safe: vocabularies ported first (1.1), importers
detached second (1.2-1.3), deletion third (1.4). Every import break during the
deletion was therefore a detachment miss in the importer and was fixed there --
no module was restored to satisfy one. Both misses were the same shape and were
fixed as a class: operations.py and shapes.py each imported trailing_name from
the deleted variants.py, so it moved to semantic/ir.py, its natural home, and
both importers changed in one edit.

Ported before deleting: the closed guard vocabulary (verbatim, nothing else
holds it) into model/specs.py, which derives TaintSpec and DominanceSpec from
the retained ruleset facts rather than copying them. Re-homed: families ->
model/taxonomy, candidates -> model/candidates, endpoint -> model/endpoint,
plus Region, labeled_family and labeled_spans. labeled_family no longer falls
back to the LLM classifier -- an unlabeled pair is honestly unknown.

Four deviations, each recorded in the spec notes with its reason. improve/
evolve.py and validator.py were stripped, not deleted: each mixes the mechanism
lever (gone) with the deterministic rule-status loop `ousast improve` still
runs, which has no LLM in it; a test now asserts the lever's absence by symbol
so it cannot creep back. The learning CLI group became `model candidates`,
because deleting it outright would have orphaned the retained enumerator by
removing its only entry point. thinking moved from [learning] to [models].

A gap named rather than papered over: no retained sink fact routes by CWE to
path, output_encoding, untrusted_destination or prototype -- the same hole the
entailment ceiling diagnosed. The test asserts the seeded set and the gap set
exactly, so task 4.2 must update it when it authors those sinks.

The audit found exactly one genuine orphan: vectorstore.py, a bakeoff harness
with no production caller and no CLI, alive only through its own test. The five
named subsystems each carry an explicit decision. Manifest committed, with a
test asserting the tree still matches it.

Group 2 (the Joern go/no-go) has not started.

Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
2026-09-08 12:15:54 +02:00

225 lines
11 KiB
Python

"""learning-harness task 1.2: the chat endpoint resolves independently of embeddings (offline)."""
from __future__ import annotations
import json
import urllib.request
from pathlib import Path
from typing import Any
import pytest
from openultrasast.config import ResolvedConfig
from openultrasast.provider import openrouter as provider
class _Recorder:
"""Stands in for OpenRouterChatClient.complete_chat and records what the adapter asked for."""
def __init__(self, replies: list[dict[str, object]]) -> None:
self.replies = replies
self.calls: list[dict[str, Any]] = []
def complete_chat(self, **kwargs: Any) -> dict[str, object]:
self.calls.append(kwargs)
return self.replies[min(len(self.calls) - 1, len(self.replies) - 1)]
def _endpoint_env(monkeypatch: pytest.MonkeyPatch, **values: str | None) -> None:
for name in ("DEEPSEEK_API_KEY", "DEEPSEEK_BASE_URL", "OPENROUTER_API_KEY", "OPENROUTER_BASE_URL", "OPENULTRASAST_HUNTER_CLIENT"):
monkeypatch.delenv(name, raising=False)
for name, value in values.items():
if value is not None:
monkeypatch.setenv(name, value)
def test_deepseek_wins_over_openrouter_and_never_touches_the_embedding_endpoint(monkeypatch: pytest.MonkeyPatch) -> None:
from openultrasast.model.endpoint import DEEPSEEK_BASE_URL, resolve_chat_endpoint
_endpoint_env(monkeypatch, DEEPSEEK_API_KEY="ds-key", OPENROUTER_API_KEY="or-key", OPENROUTER_BASE_URL="https://openrouter.ai/api/v1")
resolved = resolve_chat_endpoint(ResolvedConfig())
assert resolved is not None
_client, endpoint = resolved
assert endpoint.provider == "deepseek" and endpoint.base_url == DEEPSEEK_BASE_URL
assert not endpoint.base_url.endswith("/v1") # DeepSeek rejects the version suffix
assert "api_key" not in {field for field in endpoint.__dict__} # the key stays on the client, never in a journaled record
embedding = provider.OpenRouterEmbeddingClient.from_env()
assert embedding.base_url == "https://openrouter.ai/api/v1" and embedding.api_key == "or-key"
def test_resolution_order_override_then_scripted_then_openrouter_then_none(monkeypatch: pytest.MonkeyPatch) -> None:
from openultrasast.model.endpoint import resolve_chat_endpoint
from openultrasast.tool_hunter import ChatResponse, ScriptedChatClient
injected = ScriptedChatClient([ChatResponse(content="{}")])
_endpoint_env(monkeypatch, DEEPSEEK_API_KEY="ds-key")
resolved = resolve_chat_endpoint(ResolvedConfig(), override=injected)
assert resolved is not None and resolved[0] is injected and resolved[1].provider == "scripted"
_endpoint_env(monkeypatch, DEEPSEEK_API_KEY="ds-key", OPENULTRASAST_HUNTER_CLIENT="scripted")
resolved = resolve_chat_endpoint(ResolvedConfig())
assert resolved is not None and resolved[1].provider == "scripted"
_endpoint_env(monkeypatch, OPENROUTER_API_KEY="or-key")
resolved = resolve_chat_endpoint(ResolvedConfig())
assert resolved is not None and resolved[1].provider == "openrouter" and resolved[1].base_url.endswith("/api/v1")
_endpoint_env(monkeypatch)
assert resolve_chat_endpoint(ResolvedConfig()) is None
def test_a_provider_that_refuses_to_build_degrades_to_no_endpoint(monkeypatch: pytest.MonkeyPatch) -> None:
from openultrasast.model.endpoint import resolve_chat_endpoint
_endpoint_env(monkeypatch, OPENROUTER_API_KEY="or-key")
def _refuse() -> provider.OpenRouterChatClient:
raise provider.OpenRouterError("no key after all")
monkeypatch.setattr(provider.OpenRouterChatClient, "from_env", staticmethod(_refuse))
assert resolve_chat_endpoint(ResolvedConfig()) is None # a caller degrades; nothing raises into a scan
def test_the_config_can_point_the_chat_endpoint_somewhere_else(monkeypatch: pytest.MonkeyPatch, tmp_path: Any) -> None:
from openultrasast.config import load_config
from openultrasast.model.endpoint import resolve_chat_endpoint, resolve_models
_endpoint_env(monkeypatch, MY_KEY="local-key")
monkeypatch.setenv("MY_KEY", "local-key")
(tmp_path / "ousast.toml").write_text(
'[models]\njudge = "deepseek-v4-pro"\nchat_base_url = "http://localhost:11434/v1"\nchat_api_key_env = "MY_KEY"\n'
)
config = load_config(tmp_path / "ousast.toml")
resolved = resolve_chat_endpoint(config)
assert resolved is not None and resolved[1].base_url == "http://localhost:11434/v1"
detector, judge = resolve_models(config)
assert detector == "deepseek-v4-flash" and judge == "deepseek-v4-pro"
def test_the_adapter_disables_thinking_asks_for_json_and_keeps_the_reasoning_field() -> None:
from openultrasast.model.endpoint import DeepSeekChatClient
recorder = _Recorder([{"content": '{"intent": "public"}', "reasoning_content": "step one"}])
client = DeepSeekChatClient(recorder) # type: ignore[arg-type]
response = client.complete(model="deepseek-v4-flash", messages=[{"role": "user", "content": "json please"}], tools=[], json_object=True)
assert response.content == '{"intent": "public"}' and response.reasoning == "step one"
body = recorder.calls[0]["extra_body"]
assert body["thinking"] == {"type": "disabled"} # otherwise temperature is silently ignored
assert body["response_format"] == {"type": "json_object"} and "logprobs" not in body
def test_the_adapter_retries_once_on_empty_json_content_then_gives_up() -> None:
from openultrasast.model.endpoint import DeepSeekChatClient
recorder = _Recorder([{"content": ""}, {"content": '{"ok": true}'}])
client = DeepSeekChatClient(recorder) # type: ignore[arg-type]
assert client.complete(model="m", messages=[], tools=[], json_object=True).content == '{"ok": true}'
assert len(recorder.calls) == 2
empty = _Recorder([{"content": ""}, {"content": ""}])
client = DeepSeekChatClient(empty) # type: ignore[arg-type]
assert client.complete(model="m", messages=[], tools=[], json_object=True).content == ""
assert len(empty.calls) == 2 # one retry, never a loop
def test_log_probabilities_are_requested_only_when_asked_for() -> None:
from openultrasast.model.endpoint import DeepSeekChatClient
recorder = _Recorder([{"content": "{}", "logprobs": {"content": [{"logprob": -0.1}, {"logprob": -0.3}]}}])
client = DeepSeekChatClient(recorder) # type: ignore[arg-type]
response = client.complete(model="m", messages=[], tools=[], json_object=True, logprobs=True)
assert recorder.calls[0]["extra_body"]["logprobs"] is True
assert response.mean_logprob is not None and -0.3 < response.mean_logprob < -0.1
def test_cost_comes_from_the_providers_own_usage_fields() -> None:
from openultrasast.model.endpoint import ChatEndpoint, price_of
flash = ChatEndpoint(provider="deepseek", base_url="https://api.deepseek.com", thinking=False, prices=price_of("deepseek-v4-flash"))
cost = flash.cost({"prompt_cache_hit_tokens": 1_000_000, "prompt_cache_miss_tokens": 1_000_000, "completion_tokens": 1_000_000})
assert cost is not None and abs(cost - (0.014 + 0.44 + 1.32)) < 1e-9
openrouter_shape = flash.cost({"prompt_tokens": 1_000_000, "completion_tokens": 0})
assert openrouter_shape is not None and abs(openrouter_shape - 0.44) < 1e-9 # no cache split reported: all miss
unpriced = ChatEndpoint(provider="openrouter", base_url="x", thinking=False, prices=price_of("some/unknown-model"))
assert unpriced.cost({"prompt_tokens": 10}) is None # never claim a cost we cannot source
def test_the_underlying_client_forwards_extra_body_and_keeps_usage(monkeypatch: pytest.MonkeyPatch) -> None:
sent: dict[str, object] = {}
class _Response:
def __enter__(self) -> _Response:
return self
def __exit__(self, *_: object) -> None:
return None
def read(self) -> bytes:
return json.dumps(
{"choices": [{"message": {"content": "hi", "reasoning_content": "because"}}], "usage": {"prompt_tokens": 7}}
).encode()
def _urlopen(request: Any, timeout: int = 0) -> _Response: # noqa: ARG001
sent.update(json.loads(request.data.decode()))
return _Response()
monkeypatch.setattr(urllib.request, "urlopen", _urlopen)
client = provider.OpenRouterChatClient(api_key="k", base_url="https://api.deepseek.com")
payload = client.complete_chat_raw(
model="deepseek-v4-flash", messages=[{"role": "user", "content": "x"}], extra_body={"thinking": {"type": "disabled"}}
)
assert sent["thinking"] == {"type": "disabled"} and sent["temperature"] == 0
assert payload["usage"] == {"prompt_tokens": 7}
message = provider._extract_message(payload)
assert message["reasoning_content"] == "because" # retained for the caller to replay
def test_logprobs_are_read_off_the_choice_where_the_provider_puts_them() -> None:
"""OpenAI-shaped providers put `logprobs` on the choice, not on the message.
`_message_of` returned only `choices[0].message`, so the confidence signal the classifier is supposed to
abstain on was always `None` — a knob that reads as "never unsure" whatever the model said."""
from openultrasast.model.endpoint import _message_of
payload = {
"choices": [
{
"message": {"content": "yes", "role": "assistant"},
"logprobs": {"content": [{"token": "yes", "logprob": -0.5}, {"token": "!", "logprob": -1.5}]},
}
]
}
message = _message_of(payload)
assert message["content"] == "yes"
from openultrasast.tool_hunter import chat_response_from_message
assert chat_response_from_message(message).mean_logprob == pytest.approx(-1.0)
def test_a_reply_without_logprobs_reports_none_rather_than_a_number() -> None:
from openultrasast.model.endpoint import _message_of
from openultrasast.tool_hunter import chat_response_from_message
message = _message_of({"choices": [{"message": {"content": "yes"}}]})
assert chat_response_from_message(message).mean_logprob is None
def test_thinking_is_a_measured_condition_on_the_models_section() -> None:
"""The knob moved from `[learning]` to `[models]` with the noise architecture's removal.
Thinking is off by default because that is what the committed baseline was measured under — the provider
silently ignores `temperature` while thinking — not because it is known to be better.
"""
from openultrasast.config import load_config
assert load_config(None).models.thinking is False
def test_the_config_can_turn_thinking_on(tmp_path: Path) -> None:
from openultrasast.config import load_config
path = tmp_path / "ousast.toml"
path.write_text("[models]\nthinking = true\n")
assert load_config(path).models.thinking is True
path.write_text("[models]\nthinking = false\n")
assert load_config(path).models.thinking is False