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