Merge branch 'data-analysis-agent-work' into merger

2026-09-09 20:53:59 +08:00
parent bf8f271840 b19a2415f9
commit aa23e1ae1d
39 changed files with 3430 additions and 6 deletions
@@ -0,0 +1,39 @@
+"""演示：用真实 LLM + 真实 MySQL 跑数据分析 Agent 的典型问答。"""
+import json
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).resolve().parents[2]))
+
+from app.service.analyst_agent import AnalystAgent
+from app.utils.auth import AuthContext
+
+
+def run(question, roles, subject):
+    agent = AnalystAgent()
+    ctx = AuthContext(subject_id=subject, token_type="staff", roles=roles, staff_type=roles[0])
+    resp = agent.run(question, ctx)
+    print(f"\n=== 问题：{question}（角色 {roles[0]}）===")
+    print(f"状态：{resp.status}  缓存命中：{resp.meta.cache_hit}")
+    print(f"解读：{resp.answer}")
+    print(f"表格：{json.dumps(resp.table.model_dump(), ensure_ascii=False, default=str)}")
+    print(f"SQL：{resp.sql}")
+    if resp.error_code:
+        print(f"错误码：{resp.error_code}  建议：{resp.suggestions}")
+    return resp
+
+
+if __name__ == "__main__":
+    # 先拿到一个顾问和他的非名下客户
+    agent = AnalystAgent()
+    advisor = agent.repo.execute_readonly(
+        "SELECT staff_id FROM core_staff WHERE staff_type='advisor' AND is_active=1 LIMIT 1"
+    )["rows"][0][0]
+    scope = agent.repo.resolve_advisor_scope(advisor)
+    out_customer = next(
+        c for c in agent.repo.execute_readonly("SELECT customer_id FROM core_customer LIMIT 100")["rows"]
+        if c[0] not in scope
+    )[0]
+
+    run("按产品类型统计总持仓规模", ["analyst"], "STAFF-20001")
+    run(f"查 {out_customer} 的持仓", ["advisor"], advisor)
@@ -0,0 +1,30 @@
+"""诊断单个问题的 SQL 生成与执行（用法：python scripts/dev/diag_question.py "问题" 角色）。"""
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).resolve().parents[2]))
+
+from app.service.analyst_agent import AnalystAgent
+from app.utils.auth import AuthContext
+
+
+def main():
+    question = sys.argv[1] if len(sys.argv) > 1 else "近30天申购金额总额"
+    role = sys.argv[2] if len(sys.argv) > 2 else "ops"
+    agent = AnalystAgent()
+    ctx = AuthContext(subject_id=f"STAFF-{role}", token_type="staff", roles=[role], staff_type=role)
+    domain = {"analyst": "full", "advisor": "assigned", "risk_officer": "risk", "ops": "aggregate"}[role]
+    scope = []
+    if domain == "assigned":
+        scope = agent.repo.resolve_advisor_scope(ctx.subject_id)
+    sql, _ = agent._generate_sql(question, domain, scope)
+    print("SQL:", sql)
+    try:
+        res = agent.repo.execute_readonly(sql)
+        print("OK cols=", res["columns"], "rows[:3]=", res["rows"][:3])
+    except Exception as exc:  # noqa: BLE001
+        print("EXEC ERROR:", type(exc).__name__, exc)
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,55 @@
+"""导出数据分析 Agent 可读表的列结构（用于 NL2SQL 的 schema 元数据注入）。"""
+import pathlib
+
+import pymysql
+
+
+def load_env(path=".env"):
+    env = {}
+    for line in pathlib.Path(path).read_text(encoding="utf-8").splitlines():
+        line = line.strip()
+        if not line or line.startswith("#") or "=" not in line:
+            continue
+        k, v = line.split("=", 1)
+        env[k.strip()] = v.strip()
+    return env
+
+
+TABLES = [
+    ("jinrong_core", "core_customer"),
+    ("jinrong_core", "core_customer_risk"),
+    ("jinrong_core", "core_customer_advisor"),
+    ("jinrong_core", "core_holding"),
+    ("jinrong_core", "core_trade"),
+    ("jinrong_core", "core_cash_flow"),
+    ("jinrong_core", "core_product"),
+    ("jinrong_core", "core_product_nav"),
+    ("jinrong_core", "core_staff"),
+    ("jinrong_core", "core_risk_grade"),
+    ("jinrong_agent", "risk_alert"),
+]
+
+
+def main():
+    env = load_env()
+    conn = pymysql.connect(
+        host=env.get("MYSQL_HOST", "127.0.0.1"),
+        port=int(env.get("MYSQL_PORT", "3306")),
+        user=env.get("MYSQL_USER", "root"),
+        password=env.get("MYSQL_PASSWORD", ""),
+        charset="utf8mb4",
+    )
+    with conn.cursor() as cur:
+        for db, tbl in TABLES:
+            cur.execute(
+                "SELECT column_name, data_type FROM information_schema.columns "
+                "WHERE table_schema=%s AND table_name=%s ORDER BY ordinal_position",
+                (db, tbl),
+            )
+            cols = [f"{c[0]}:{c[1]}" for c in cur.fetchall()]
+            print(f"{tbl} ({db}) -> {', '.join(cols)}")
+    conn.close()
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,24 @@
+"""查看种子数据关键事实（用于集成测试与演示）。"""
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).resolve().parents[2]))
+
+from app.service.analytics_repo import AnalyticsRepo
+
+
+def main():
+    repo = AnalyticsRepo()
+    q = lambda sql: repo.execute_readonly(sql)  # noqa: E731
+    print("advisor ids:", [r[0] for r in q("SELECT staff_id FROM core_staff WHERE staff_type='advisor' AND is_active=1 LIMIT 5")["rows"]])
+    print("risk_officer ids:", [r[0] for r in q("SELECT staff_id FROM core_staff WHERE staff_type='risk_officer' AND is_active=1 LIMIT 5")["rows"]])
+    print("ops ids:", [r[0] for r in q("SELECT staff_id FROM core_staff WHERE staff_type='ops' AND is_active=1 LIMIT 5")["rows"]])
+    print("analyst ids:", [r[0] for r in q("SELECT staff_id FROM core_staff WHERE staff_type='analyst' AND is_active=1 LIMIT 5")["rows"]])
+    print("risk codes:", q("SELECT risk_code, COUNT(*) c FROM core_customer_risk GROUP BY risk_code ORDER BY risk_code")["rows"])
+    print("product types:", q("SELECT product_type, COUNT(*) c FROM core_product GROUP BY product_type")["rows"])
+    print("alert status:", q("SELECT status, COUNT(*) c FROM jinrong_agent.risk_alert GROUP BY status")["rows"])
+    print("customers sample:", [r[0] for r in q("SELECT customer_id FROM core_customer LIMIT 8")["rows"]])
+
+
+if __name__ == "__main__":
+    main()