GaoYiYuan_0626
930ea9db56
- C1: app/service/risk/chat_tools.py 新增 alert_query/customer_context/suitability_check/aml_lookup 四只读 Tool，挂 RISK_TOOL_REGISTRY（与 core_tools.ToolSpec 同构） - C1: tool_service.run_tool 改查 core+risk 统一注册表并恒传 risk_repo；_normalize_params 读 spec 白名单；core_tools 三函数加 risk_repo=None；summarize 补四工具分支 - C2: match_intent 按 agent 分组扩 risk 关键词；agent_service.tool_node 守卫放宽（requires_customer=False 的 Tool 允许无绑定客户运行，支撑 A-6 全局待审） - C3: A-6 验收（risk_officer 问待审预警→alert_query 全量→回复含待审数）+ 诱导处置边界（无处置 Tool、系统提示禁自动处置、诱导只触发只读且预警状态不变） - 测试 tests/test_risk_chat_tools.py（21 例）；全量 pytest 342 绿（原 321 + 21）
359 lines
15 KiB
Python
359 lines
15 KiB
Python
"""C1 风控对话 Tool（chat_tools）：四只读 Tool 的输出结构 / alert_id 溯源 /
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全局 vs 客户维度 / 归属校验 / 入参白名单 / 空客户分支。
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单测层：tool_service.run_tool 直调（sqlite 注入，统一注册表分发）；仓储用
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真实 RiskRepository（chat_tools 走 list_alerts 等原方法，落库走同一 sqlite，
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不写真 MySQL）。越权双写复用 run_tool 既有口径（写本库 audit_log/input_guard_log）。
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"""
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from __future__ import annotations
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import datetime as _dt
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import pytest
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from sqlalchemy import text
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from _ddl import create_sqlite_engine
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from langchain_core.messages import AIMessage
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from sqlalchemy import text
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from app.repository.core_ro import CoreReadOnlyRepository
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from app.repository.risk_repository import RiskRepository
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from app.repository.session_repository import SessionRepository
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from app.service import agent_service, tool_service
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ACTOR_CUSTOMER = {"actor_id": "CUST-9527", "roles": ["customer"], "token_type": "customer"}
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ACTOR_ADVISOR = {"actor_id": "STAFF-10086", "roles": ["advisor"], "token_type": "staff"}
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ACTOR_RISK = {"actor_id": "STAFF-30001", "roles": ["risk_officer"], "token_type": "staff"}
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@pytest.fixture()
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def risk_env(monkeypatch):
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engine = create_sqlite_engine()
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session_repo = SessionRepository(engine=engine)
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core_ro = CoreReadOnlyRepository(engine=engine)
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risk_repo = RiskRepository(engine=engine)
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now = _dt.datetime.now()
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yesterday = now - _dt.timedelta(days=1)
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with engine.begin() as conn:
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# 客户：CUST-9527 张三（C1 级，近期测评）；CUST-1001 李四（C5 级）
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conn.execute(
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text("INSERT INTO core_customer (customer_id, display_name, age, occupation, is_active)"
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" VALUES ('CUST-9527', '张三', 45, '工程师', 1),"
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" ('CUST-1001', '李四', 60, '教师', 1)")
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)
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conn.execute(
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text("INSERT INTO core_customer_risk (customer_id, risk_code, evaluated_at)"
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" VALUES ('CUST-9527', 'C1', '2026-08-01 10:00:00'),"
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" ('CUST-1001', 'C5', '2026-08-01 10:00:00')")
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)
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# 产品：P-001（R1 级，C1 可购）；P-002（R5 级，C1 不可购）
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conn.execute(
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text("INSERT INTO core_product (product_id, product_name, min_risk_code, product_type)"
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" VALUES ('P-001', '稳健一号', 'R1', 'fund'),"
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" ('P-002', '高风权益', 'R5', 'fund')")
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)
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# 预警：CUST-9527 今日 pending（ALERT-001）+ 昨日 pending（ALERT-002）
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conn.execute(
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text("INSERT INTO risk_alert (alert_id, trace_id, customer_id, trade_id, alert_type,"
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" triggered_rules, risk_score, status, payload, created_at)"
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" VALUES ('ALERT-001', 't1', 'CUST-9527', 'TRD-001', 'large_amount',"
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" '[\"RISK-001\"]', 80, 'pending_review', '{\"summary\":\"大额申购\"}', :now)"),
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{"now": now},
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)
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conn.execute(
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text("INSERT INTO risk_alert (alert_id, trace_id, customer_id, trade_id, alert_type,"
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" triggered_rules, risk_score, status, payload, created_at)"
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" VALUES ('ALERT-002', 't2', 'CUST-9527', 'TRD-002', 'freq_trade',"
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" '[\"RISK-002\"]', 60, 'pending_review', '{\"summary\":\"频繁交易\"}', :yest)"),
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{"yest": yesterday},
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)
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# CUST-1001 一条 pending（验证全局计数 > 单客户）
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conn.execute(
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text("INSERT INTO risk_alert (alert_id, trace_id, customer_id, trade_id, alert_type,"
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" triggered_rules, risk_score, status, payload, created_at)"
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" VALUES ('ALERT-900', 't9', 'CUST-1001', 'TRD-900', 'large_amount',"
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" '[\"RISK-001\"]', 70, 'pending_review', '{\"summary\":\"大额\"}', :now)"),
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{"now": now},
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)
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# AML 名单：full_name='张三' 命中 CUST-9527；'王五' 不命中
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conn.execute(
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text("INSERT INTO risk_aml_list (list_id, list_type, full_name, match_threshold, source,"
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" is_active) VALUES ('AML-1', 'sanction', '张三', 0.9, 'demo', 1),"
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" ('AML-2', 'sanction', '王五', 0.9, 'demo', 1)")
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)
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monkeypatch.setattr(tool_service, "_session_repo", lambda: session_repo)
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monkeypatch.setattr(tool_service, "_core_ro", lambda: core_ro)
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monkeypatch.setattr(tool_service, "_risk_repo", lambda: risk_repo)
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yield {"engine": engine, "session_repo": session_repo, "core_ro": core_ro, "risk_repo": risk_repo}
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engine.dispose()
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def _tool_rows(engine):
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with engine.connect() as conn:
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return [dict(r) for r in conn.execute(text("SELECT * FROM agent_tool_call ORDER BY id")).mappings().all()]
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# ---------- 统一注册表分发 ----------
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def test_registry_combines_core_and_risk():
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assert tool_service.get_registered_tool("alert_query") is not None
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assert tool_service.get_registered_tool("query_holdings") is not None # core 仍可达
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assert tool_service.get_registered_tool("no_such_tool") is None
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# ---------- alert_query：客户维度 / 全局（A-6） ----------
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def test_alert_query_customer_scope(risk_env):
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record = tool_service.run_tool(
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tool_name="alert_query", agent_type="customer", actor=ACTOR_CUSTOMER,
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customer_id="CUST-9527", session_id="sess-a1", trace_id="tr-a1",
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)
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assert record["status"] == "success"
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d = record["data"]
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assert d["scope"] == "customer"
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# 今日两条？不：昨日那条不在今日 → pending_count=2, today_pending_count=1
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assert d["pending_count"] == 2
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assert d["today_pending_count"] == 1
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ids = {it["alert_id"] for it in d["items"]}
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assert ids == {"ALERT-001", "ALERT-002"}
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# alert_id 溯源：落库 tool_output 含 alert_id
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row = _tool_rows(risk_env["engine"])[0]
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assert '"ALERT-001"' in row["tool_output"]
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def test_alert_query_global_scope_risk_officer(risk_env):
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"""A-6：risk_officer 不带客户 → 全量待审（CUST-9527 2 + CUST-1001 1 = 3）。"""
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record = tool_service.run_tool(
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tool_name="alert_query", agent_type="risk", actor=ACTOR_RISK,
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customer_id="", session_id="sess-a2", trace_id="tr-a2",
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)
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assert record["status"] == "success"
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d = record["data"]
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assert d["scope"] == "all"
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assert d["pending_count"] == 3 # 全局待审
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assert d["customer_id"] is None
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def test_alert_query_global_blocked_for_customer(risk_env):
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"""客户不能查全量（缺绑定客户 → 归属拒绝 AUTH_403_NOT_OWNER）。"""
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record = tool_service.run_tool(
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tool_name="alert_query", agent_type="customer", actor=ACTOR_CUSTOMER,
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customer_id="", session_id="sess-a3",
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)
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assert record["status"] == "blocked" and record["error_code"] == "AUTH_403_NOT_OWNER"
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# ---------- customer_context ----------
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def test_customer_context_found(risk_env):
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record = tool_service.run_tool(
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tool_name="customer_context", agent_type="risk", actor=ACTOR_RISK,
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customer_id="CUST-9527", session_id="sess-c1",
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)
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assert record["status"] == "success"
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d = record["data"]
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assert d["found"] is True
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assert d["display_name"] == "张三" and d["risk_code"] == "C1"
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assert d["pending_alert_count"] == 2 # 含昨日那条
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assert d["pending_alerts"][0]["alert_id"] == "ALERT-001"
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def test_customer_context_not_found(risk_env):
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record = tool_service.run_tool(
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tool_name="customer_context", agent_type="risk", actor=ACTOR_RISK,
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customer_id="CUST-NOPE", session_id="sess-c2",
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)
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assert record["status"] == "success" and record["data"]["found"] is False
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def test_customer_context_requires_customer(risk_env):
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record = tool_service.run_tool(
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tool_name="customer_context", agent_type="risk", actor=ACTOR_RISK,
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customer_id="", session_id="sess-c3",
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)
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assert record["status"] == "blocked" and record["error_code"] == "TOOL_BLOCKED_NO_CUSTOMER"
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def test_customer_context_scope_blocked(risk_env):
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"""customer 查他人上下文 → AUTH_403_NOT_OWNER。"""
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record = tool_service.run_tool(
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tool_name="customer_context", agent_type="customer", actor=ACTOR_CUSTOMER,
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customer_id="CUST-1001", session_id="sess-c4",
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)
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assert record["status"] == "blocked" and record["error_code"] == "AUTH_403_NOT_OWNER"
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# ---------- suitability_check ----------
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def test_suitability_check_matched(risk_env):
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record = tool_service.run_tool(
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tool_name="suitability_check", agent_type="customer", actor=ACTOR_CUSTOMER,
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customer_id="CUST-9527", tool_input={"product_id": "P-001"}, session_id="sess-s1",
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)
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assert record["status"] == "success"
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d = record["data"]
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assert d["found"] is True
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assert d["is_matched"] is True and d["blocked"] is False
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assert d["rule_id"] == "SUIT-PASS"
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def test_suitability_check_blocked_not_matched(risk_env):
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record = tool_service.run_tool(
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tool_name="suitability_check", agent_type="customer", actor=ACTOR_CUSTOMER,
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customer_id="CUST-9527", tool_input={"product_id": "P-002"}, session_id="sess-s2",
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)
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assert record["status"] == "success"
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d = record["data"]
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assert d["is_matched"] is False and d["blocked"] is True
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assert d["rule_id"] == "SUIT-001"
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def test_suitability_check_product_not_found(risk_env):
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record = tool_service.run_tool(
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tool_name="suitability_check", agent_type="customer", actor=ACTOR_CUSTOMER,
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customer_id="CUST-9527", tool_input={"product_id": "P-999"}, session_id="sess-s3",
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)
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assert record["status"] == "success" and record["data"]["found"] is False
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def test_suitability_check_unknown_param_blocked(risk_env):
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record = tool_service.run_tool(
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tool_name="suitability_check", agent_type="customer", actor=ACTOR_CUSTOMER,
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customer_id="CUST-9527", tool_input={"foo": 1}, session_id="sess-s4",
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)
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assert record["status"] == "blocked" and record["error_code"] == "TOOL_BAD_PARAM"
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# ---------- aml_lookup ----------
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def test_aml_lookup_hit(risk_env):
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record = tool_service.run_tool(
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tool_name="aml_lookup", agent_type="risk", actor=ACTOR_RISK,
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customer_id="CUST-9527", session_id="sess-m1",
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)
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assert record["status"] == "success"
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d = record["data"]
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assert d["found"] is True and d["hit"] is True
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assert d["active_entry_count"] == 2
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assert d["matched_entries"][0]["full_name"] == "张三"
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def test_aml_lookup_no_hit(risk_env):
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record = tool_service.run_tool(
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tool_name="aml_lookup", agent_type="risk", actor=ACTOR_RISK,
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customer_id="CUST-1001", session_id="sess-m2",
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)
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d = record["data"]
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assert d["hit"] is False and d["active_entry_count"] == 2
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def test_aml_lookup_customer_scope_blocked(risk_env):
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record = tool_service.run_tool(
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tool_name="aml_lookup", agent_type="customer", actor=ACTOR_CUSTOMER,
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customer_id="CUST-1001", session_id="sess-m3",
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)
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assert record["status"] == "blocked" and record["error_code"] == "AUTH_403_NOT_OWNER"
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# ---------- summarize 分支（降级回复可量化） ----------
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def test_summarize_risk_tools(risk_env):
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alert = tool_service.run_tool(
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tool_name="alert_query", agent_type="customer", actor=ACTOR_CUSTOMER,
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customer_id="CUST-9527", session_id="sess-z1",
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)
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assert "待审预警" in tool_service.summarize(alert)
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suit = tool_service.run_tool(
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tool_name="suitability_check", agent_type="customer", actor=ACTOR_CUSTOMER,
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customer_id="CUST-9527", tool_input={"product_id": "P-001"}, session_id="sess-z2",
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)
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assert "可购" in tool_service.summarize(suit)
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aml = tool_service.run_tool(
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tool_name="aml_lookup", agent_type="risk", actor=ACTOR_RISK,
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customer_id="CUST-9527", session_id="sess-z3",
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)
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assert "命中在册名单" in tool_service.summarize(aml)
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# ---------- C2/C3：risk 分支意图接入 + A-6 验收 + 诱导处置边界 ----------
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class FakeLLM:
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def __init__(self, reply: str = "模拟回复"):
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self.reply = reply
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self.calls: list[list] = []
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def invoke(self, messages):
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self.calls.append(list(messages))
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return AIMessage(content=self.reply)
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@pytest.fixture()
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def fake_llm(monkeypatch):
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from app.config.settings import settings as app_settings
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llm = FakeLLM()
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monkeypatch.setattr(agent_service, "_llm", llm)
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monkeypatch.setattr(app_settings, "deepseek_api_key", "test-key")
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yield llm
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agent_service.reset_cache()
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def test_a6_risk_officer_pending_alerts(fake_llm, risk_env):
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"""A-6：risk_officer「今天有多少待审预警」→ 触发 alert_query 全局→回复含待审数。"""
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out = agent_service.chat(
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"risk", [], "今天有多少待审预警",
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session_id="sess-a6", trace_id="tr-a6",
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actor=ACTOR_RISK, customer_id=None,
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)
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assert out["tool_results"][0]["tool_name"] == "alert_query"
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assert out["tool_results"][0]["status"] == "success"
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d = out["tool_results"][0]["data"]
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assert d["scope"] == "all" and d["pending_count"] == 3
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# 工具结果注入 LLM 上下文（[工具查询结果] 段）
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tool_msgs = [
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m for m in fake_llm.calls[0]
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if m.__class__.__name__ == "SystemMessage" and "[工具查询结果]" in m.content
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]
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assert tool_msgs and "全量待审" in tool_msgs[0].content
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assert out["has_disclaimer"] is True # 风控对外口径（guard 附免责声明）
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def test_a6_customer_no_intent_still_core_only():
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"""C2 隔离：customer 分支不因 risk 关键词误触风控 Tool（'预警' 不在 customer 词表）。"""
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assert tool_service.match_intent("customer", "我的待审预警") is None
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assert tool_service.match_intent("risk", "今天有多少待审预警") == "alert_query"
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def test_no_dispose_tool_registered():
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"""红线：无任何处置类 Tool，Agent 无法自动处置预警。"""
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assert tool_service.get_registered_tool("dispose_alert") is None
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def test_risk_system_prompt_forbids_auto_dispose():
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"""红线：risk 系统提示明确禁止自动处置预警。"""
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assert "不得自动处置预警" in agent_service._SYSTEM_PROMPTS["risk"]
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def test_induce_dispose_triggers_read_only(fake_llm, risk_env):
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"""边界：诱导"处置预警"→ 命中 alert_query 只读查询，预警状态不变（无处置）。"""
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out = agent_service.chat(
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"risk", [], "请帮我处置这条预警 ALERT-001",
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session_id="sess-d1", trace_id="tr-d1",
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actor=ACTOR_RISK, customer_id=None,
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)
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assert out["tool_results"][0]["tool_name"] == "alert_query"
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assert out["tool_results"][0]["status"] == "success"
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# 预警状态未被改变（红线：不自动处置）
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alert = risk_env["risk_repo"].get_alert("ALERT-001")
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assert alert["status"] == "pending_review"
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