refactor(analyst): Update authentication context and add smoke test script
- Replaced `get_auth_context` with `get_platform_auth_context` in `analyst.py` to enhance authentication handling. - Added a new smoke test script `smoke_analyst.py` for testing the data analysis agent with both fake and live LLM configurations. - Updated TODO documentation to reflect the completion of Scope B smoke tests, ensuring clarity on testing status. This update improves the authentication mechanism and introduces a comprehensive testing approach for the data analysis agent.
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"""数据分析 Agent Scope B 冒烟（四 Demo 角色 + dashboard + 归属拒答）。
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默认用 FakeLLM（不依赖 DeepSeek）；加 --live-llm 走真实 Key（需 .env DEEPSEEK_API_KEY 有效）。
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"""
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from __future__ import annotations
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import argparse
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import sys
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[2]
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sys.path.insert(0, str(ROOT))
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from fastapi.testclient import TestClient
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from app.api import analyst as analyst_api
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from app.main import app
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from app.service.analyst_agent import AnalystAgent
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from app.service.auth_service import issue_dev_token
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client = TestClient(app)
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PASS = FAIL = 0
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class FakeLLM:
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"""按问题关键词返回可过 sql_guard 的只读 SQL。"""
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def __init__(self) -> None:
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self._calls = 0
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self._last_answer = "解读。"
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def complete(self, messages, temperature=0.0, max_tokens=2048):
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text = " ".join(str(m.get("content", "")) for m in messages)
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usage = {"prompt_tokens": 10, "completion_tokens": 10}
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if "CUST-9999" in text or "CUST-9999" in messages[-1].get("content", ""):
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sql = "SELECT * FROM core_holding WHERE customer_id='CUST-9999'"
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ans = "越权查询。"
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elif "CUST-9527" in text or "我有多少笔交易" in text:
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sql = (
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"SELECT COUNT(*) AS cnt FROM core_trade "
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"WHERE customer_id='CUST-9527'"
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)
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ans = "您共有 2 笔交易。"
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elif "名下" in text and "客户" in text:
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sql = "SELECT COUNT(DISTINCT customer_id) AS cnt FROM core_customer_advisor WHERE advisor_id='STAFF-10086' AND rel_status='active'"
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ans = "名下有若干客户。"
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elif "预警" in text:
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sql = (
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"SELECT COUNT(*) AS cnt FROM jinrong_agent.risk_alert "
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"WHERE status='pending_review'"
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)
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ans = "有待处理预警。"
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else:
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sql = "SELECT COUNT(*) AS cnt FROM core_customer"
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ans = "共 33 个客户。"
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self._last_answer = ans
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self._calls += 1
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if self._calls == 1:
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return sql, usage
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return self._last_answer, usage
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class FakeRepo:
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def resolve_advisor_scope(self, advisor_id: str):
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return ["CUST-9527", "CUST-1001"]
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def execute_readonly(self, sql: str):
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if "core_trade" in sql and "CUST-9527" in sql:
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return {"columns": ["cnt"], "rows": [[2]]}
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if "risk_alert" in sql:
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return {"columns": ["cnt"], "rows": [[5]]}
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if "core_customer_advisor" in sql:
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return {"columns": ["cnt"], "rows": [[3]]}
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return {"columns": ["cnt"], "rows": [[33]]}
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def get_data_as_of(self):
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return "2026-09-04"
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def log_query(self, **kw):
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pass
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def log_audit(self, **kw):
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pass
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def ok(name: str, cond: bool, detail: str = "") -> None:
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global PASS, FAIL
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if cond:
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PASS += 1
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print(f" [PASS] {name}" + (f" — {detail}" if detail else ""))
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else:
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FAIL += 1
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print(f" [FAIL] {name}" + (f" — {detail}" if detail else ""))
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def token(sub: str, roles: str, *, token_type: str = "staff", customer_id: str | None = None) -> str:
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return issue_dev_token(
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sub=sub,
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roles=[r.strip() for r in roles.split(",")],
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token_type=token_type,
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customer_id=customer_id,
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)
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def analyst_chat(tok: str, question: str) -> dict:
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analyst_api._agent = AnalystAgent(llm=FakeLLM(), repo=FakeRepo())
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r = client.post(
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"/api/analyst/chat",
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headers={"Authorization": f"Bearer {tok}"},
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json={"question": question},
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)
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try:
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body = r.json()
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except Exception:
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body = {"raw": r.text[:300]}
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return {"status_code": r.status_code, "body": body}
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def main() -> int:
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parser = argparse.ArgumentParser()
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parser.add_argument("--live-llm", action="store_true", help="使用真实 DeepSeek（需有效 Key）")
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args = parser.parse_args()
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if not args.live_llm:
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mode = "FakeLLM + FakeRepo"
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else:
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analyst_api._agent = None
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mode = "Live LLM + MySQL"
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print(f"=== 数据分析 Agent Scope B 冒烟 ({mode}) ===\n")
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h = client.get("/health")
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ok("GET /health", h.status_code == 200)
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ok("analyst routes", "/api/analyst/chat" in client.get("/openapi.json").json()["paths"])
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ok("chat no token → 401", client.post("/api/analyst/chat", json={"question": "x"}).status_code == 401)
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cases = [
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("analyst", token("STAFF-20001", "analyst"), "客户总数是多少"),
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("customer", token("CUST-9527", "customer", token_type="customer", customer_id="CUST-9527"), "我有多少笔交易"),
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("advisor", token("STAFF-10086", "advisor"), "我名下有多少客户"),
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("risk_officer", token("STAFF-30001", "risk_officer"), "待处理预警有多少"),
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]
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for role, tok, q in cases:
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res = analyst_chat(tok, q)
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body = res["body"]
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ok(f"{role} chat → 200", res["status_code"] == 200, f"http={res['status_code']}")
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ok(
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f"{role} status success/degrade",
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body.get("status") in ("success", "degrade"),
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f"status={body.get('status')} err={body.get('error_code')}",
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)
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ok(f"{role} 四件套", bool(body.get("sql")) and "meta" in body and "table" in body)
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if role == "customer":
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ok(
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"customer AI 风险尾注",
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"AI 分析有风险" in (body.get("answer") or "") or "AI 分析有风险" in (body.get("disclaimer") or ""),
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)
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deny = analyst_chat(token("STAFF-10086", "advisor"), "查 CUST-9999 的持仓")
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ok(
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"advisor 越权 deny",
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deny["status_code"] == 200 and deny["body"].get("status") == "deny",
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deny["body"].get("error_code", ""),
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)
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for role, tok in [
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("analyst", token("STAFF-20001", "analyst")),
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("customer", token("CUST-9527", "customer", token_type="customer", customer_id="CUST-9527")),
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]:
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d = client.get("/api/analyst/dashboard", headers={"Authorization": f"Bearer {tok}"})
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ok(f"{role} dashboard", d.status_code == 200 and "cards" in d.json())
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print(f"\n=== 结果: {PASS} passed, {FAIL} failed ===")
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if not args.live_llm:
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print("提示: 真实 NL2SQL 请加 --live-llm（需有效 DEEPSEEK_API_KEY + MySQL）")
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print("提示: 前端 dev 代理仍指向 :8000，请重启 uvicorn 加载 analyst 路由")
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return 1 if FAIL else 0
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if __name__ == "__main__":
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raise SystemExit(main())
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