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breakpilot-compliance/backend-compliance/tests/test_specialist_agent_routes.py
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fix(agents): Impressum+Cookie delegieren MC-Laden ans Main Tool — Scope-Filter + Maßnahmen
Regression: Der v3-Agent-Pfad baute eine parallele MC-Pipeline
(_load_impressum_mcs / _load_cookie_mcs, Roh-SELECT) und lief damit an
allen Schutzmechanismen der Engine vorbei → GOV/Branchen-MCs als HIGH bei
OEM/Zulieferer, fremde MCs (Bestellbestätigung), und action=check_question
(Fragen statt Maßnahmen im Frontend).

- Agent delegiert MC-Laden an rag_document_checker._load_controls
  (P72-Scope, check_type='text', fits_doc_type/scope_requires).
- Subtraktives Sektor-Gate (SECTOR_PREFIXES) + Themen-Gate am Agent-Rand.
- action = konkrete Maßnahme (Imperativ) statt check_question.
- rag_document_checker: from __future__ import annotations (3.9-Import).
- mcs: Name-Pattern erkennt "Aktiengesellschaft" (OEM-Impressums).
- Tote GT-/Semantic-/Routes-Tests wiederbelebt (v3-Mismatch +
  agent.cascade-Patch-Target). Alle 72 Specialist-Tests grün.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-09 11:30:16 +02:00

160 lines
5.5 KiB
Python

"""Tests für SSE-Endpoints des Specialist-Agent-Test-Harness."""
from __future__ import annotations
import asyncio
import json
from unittest.mock import AsyncMock, patch
import pytest
from fastapi.testclient import TestClient
from tests.fixtures.impressum_groundtruth import make_mc
@pytest.fixture
def app(tmp_path, monkeypatch):
monkeypatch.setenv("EVIDENCE_VAULT_ROOT", str(tmp_path / "vault"))
from fastapi import FastAPI
from compliance.api.specialist_agent_routes import router
app = FastAPI()
app.include_router(router, prefix="/api/v1")
return app
@pytest.fixture
def client(app):
return TestClient(app)
def test_list_agents(client):
r = client.get("/api/v1/specialist-agent/agents")
assert r.status_code == 200
data = r.json()
agent_ids = {a["agent_id"] for a in data["agents"]}
assert "impressum" in agent_ids
assert "cookie_policy" in agent_ids
def test_start_test_invalid_agent(client):
r = client.post("/api/v1/specialist-agent/test/start",
json={"agent_id": "ghost",
"raw_texts": ["test"]})
assert r.status_code == 404
def test_start_test_no_input(client):
r = client.post("/api/v1/specialist-agent/test/start",
json={"agent_id": "impressum"})
assert r.status_code == 400
def test_start_test_with_raw_text(client):
r = client.post("/api/v1/specialist-agent/test/start",
json={"agent_id": "impressum",
"raw_texts": ["Tesla Germany GmbH "
"Berlin Email: x@y.com "
"HRB 123 Charlottenburg"]})
assert r.status_code == 200
data = r.json()
assert data["agent_id"] == "impressum"
assert data["slot_count"] == 1
assert data["run_id"]
def test_stream_unknown_run(client):
r = client.get("/api/v1/specialist-agent/test/stream/ghost")
assert r.status_code == 404
def test_run_result_after_text_input(client, monkeypatch):
# Skip LLM
async def _no_cascade(*a, **kw): return None, []
monkeypatch.setattr(
"compliance.services.specialist_agents._semantic_validator.cascade",
_no_cascade,
)
# Agent delegiert MC-Laden ans Main Tool → _load_controls mocken.
# Tesla nennt 'Management' (engl.) statt deutschem GF-Label → das
# label_korrekt-MC schlaegt fehl → erwartetes Finding.
async def _fake_load(doc_type, db_url, limit, business_scope=None):
# pass_criteria nur mit label_korrekt-eigenen Keywords (deutsche/
# Bezeichnung/Rechtsform) — NICHT 'Geschäftsführer/Vorstand', sonst
# boostet das aktive vertretungsberechtigte-Feld (Tesla: 'Management')
# das MC faelschlich auf PASS.
return [make_mc(
"vertretungsberechtigte_label_korrekt",
["deutsche Bezeichnung Rechtsform Pflicht angeben"],
)]
monkeypatch.setattr(
"compliance.services.rag_document_checker._load_controls",
_fake_load,
)
async def _no_match(*a, **kw): return set()
monkeypatch.setattr(
"compliance.services.mc_embedding_matcher.embedding_match",
_no_match, raising=False,
)
async def _no_embed(*a, **kw): return None
monkeypatch.setattr(
"compliance.services.mc_embedding_matcher.ensure_mc_embeddings",
_no_embed, raising=False,
)
r = client.post("/api/v1/specialist-agent/test/start",
json={"agent_id": "impressum",
"raw_texts": [
"Tesla Germany GmbH\nLudwig-Prandtl-Strasse 25\n"
"12526 Berlin\nDeutschland\nEmail: x@y.com\n"
"Tel: +49 89 1250 16 800\n"
"Management: Elon Musk\n"
"HRB 218904 B Charlottenburg",
]})
run_id = r.json()["run_id"]
# Give async task time to finish (small text → fast)
for _ in range(40):
rr = client.get(
f"/api/v1/specialist-agent/run/{run_id}/result",
)
if rr.json().get("finished"):
break
import time; time.sleep(0.05)
res = client.get(f"/api/v1/specialist-agent/run/{run_id}/result")
body = res.json()
assert body["finished"]
assert "text1" in body["results"]
out = body["results"]["text1"]
field_ids = {f["field_id"] for f in out["findings"]}
# Tesla pattern: German-label fehlt + USt fehlt
assert "vertretungsberechtigte_label_korrekt" in field_ids
def test_artifacts_listing(client, monkeypatch):
async def _no_cascade(*a, **kw): return None, []
monkeypatch.setattr(
"compliance.services.specialist_agents._semantic_validator.cascade",
_no_cascade,
)
r = client.post("/api/v1/specialist-agent/test/start",
json={"agent_id": "impressum",
"raw_texts": ["Tesla Germany GmbH "
"Berlin Email: x@y.com "
"HRB 123 Charlottenburg"]})
run_id = r.json()["run_id"]
for _ in range(40):
rr = client.get(
f"/api/v1/specialist-agent/run/{run_id}/result",
)
if rr.json().get("finished"):
break
import time; time.sleep(0.05)
arts = client.get(
f"/api/v1/specialist-agent/run/{run_id}/artifacts",
)
assert arts.status_code == 200
manifest = arts.json()["manifest"]
kinds = {a["kind"] for a in manifest["assets"]}
assert "finding" in kinds
assert "raw" in kinds