chore: 从汽车AI客服项目拷贝骨架并清理(blog页/redis)

Co-Authored-By: Claude Code <noreply@anthropic.com>
2026-09-29 14:15:12 +08:00
parent 90860b8bfd
commit 49c0e5559c
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+"""批次0.5 基线统计：上线前存档，上线后同口径对比。只读。"""
+import re
+import sqlite3
+import sys
+from itertools import groupby
+from pathlib import Path
+
+DB = sys.argv[1] if len(sys.argv) > 1 else "./data/cc_ai_kefu.db"
+
+EMAIL_RE = re.compile(r"[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Za-z]{2,}")
+INTL_RE = re.compile(r"\+\d{6,15}")
+
+
+def main() -> None:
+    # mode=ro：路径写错时直接报错，而不是新建空库
+    uri = f"file:{Path(DB).resolve().as_posix()}?mode=ro"
+    try:
+        conn = sqlite3.connect(uri, uri=True)
+    except sqlite3.OperationalError as exc:
+        print(f"无法只读打开数据库 {DB}: {exc}", file=sys.stderr)
+        sys.exit(1)
+    cur = conn.cursor()
+
+    print("# 注意: 本文件为开发库占位数据, 生产基线需在部署机覆盖重跑")
+
+    # 1) 历史已发邮件中无联系方式占比（按 source）
+    rows = cur.execute(
+        """SELECT c.source,
+                  COUNT(*) AS sent,
+                  SUM(CASE WHEN COALESCE(e.contact_info, '{}') IN ('{}', 'null', '')
+                           OR e.contact_info IS NULL THEN 1 ELSE 0 END) AS no_contact
+           FROM evaluations e JOIN conversations c ON c.id = e.conversation_id
+           WHERE e.email_sent = 1 GROUP BY c.source"""
+    ).fetchall()
+    print("== 已发邮件联系方式缺失（按来源）==")
+    if not rows:
+        print("  (无记录)")
+    for source, sent, no_contact in rows:
+        pct = (no_contact / sent * 100) if sent else 0
+        print(f"  {source}: 发送 {sent}, 缺失 {no_contact} ({pct:.0f}%)")
+
+    # 2) 用户消息中含联系方式样式的会话占比（新策略邮件量预估）
+    # messages.conversation_id 无索引：单次全表扫描 + groupby，避免逐会话 N+1 查询
+    with_contact = early_contact = total = 0
+    msgs = cur.execute(
+        """SELECT conversation_id, role, content FROM messages
+           ORDER BY conversation_id, created_at, id"""
+    )
+    for _cid, convo_msgs in groupby(msgs, key=lambda m: m[0]):
+        user_msgs = [m[2] for m in convo_msgs if m[1] == "user"]
+        if not user_msgs:
+            continue
+        total += 1
+        hit_idx = next(
+            (i for i, content in enumerate(user_msgs)
+             if EMAIL_RE.search(content) or INTL_RE.search(content)),
+            None,
+        )
+        if hit_idx is not None:
+            with_contact += 1
+            if hit_idx < 2:
+                early_contact += 1
+    print("== 新策略邮件量预估 ==")
+    print(f"  有用户消息的会话: {total}")
+    print(f"  消息中含联系方式样式: {with_contact}"
+          f" ({with_contact / total * 100 if total else 0:.0f}%) ← 样式上界")
+    print(f"  联系方式出现在前2条消息内: {early_contact}"
+          f" ({early_contact / total * 100 if total else 0:.0f}%) ← 即时触发增量")
+
+    conn.close()
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,41 @@
+"""职能边界破防率观测(只读): AI 回复中出现"价格形态数字"的轮次占比。
+方案B(输出过滤)的启动依据: >10% 即砌墙。锚定式匹配,年份/续航数字天然不命中。"""
+import re
+import sqlite3
+import sys
+
+DB = sys.argv[1] if len(sys.argv) > 1 else "./data/cc_ai_kefu.db"
+
+PATTERNS = [
+    (r"\$\s?\d", "美元符"),
+    (r"\d[\d,.]*\s*(usd|美元|万块?|块钱)", "货币单位"),
+    (r"(price|cost|quote)[^.\d]{0,20}(?<![a-z])(?!(?:19|20)\d\d(?!\d))\d",
+     "价格动词邻接(年份/车型编号排除)"),
+    (r"\d[\d,.]*\s*k\b(?!\w)", "25k形式"),
+]
+COMPILED = [(re.compile(p, re.I), name) for p, name in PATTERNS]
+
+
+def main() -> None:
+    conn = sqlite3.connect(f"file:{DB}?mode=ro", uri=True)
+    rows = conn.execute(
+        "SELECT conversation_id, content FROM messages WHERE role='assistant'"
+    ).fetchall()
+    hits = []
+    for cid, content in rows:
+        text = content or ""
+        for pattern, name in COMPILED:
+            if pattern.search(text):
+                hits.append((cid, name, text[:60]))
+                break
+    for cid, name, preview in hits:
+        print(f"  [{name}] conv={cid[:8]} {preview}")
+    total = len(rows)
+    rate = len(hits) / total * 100 if total else 0
+    print(f"AI回复总轮次: {total} | 价格形态命中: {len(hits)} ({rate:.0f}%)")
+    print("← 破防率。>10% 启动方案B(输出过滤)")
+    conn.close()
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,39 @@
+"""本地联调假 UniService 接收端(仅测试用,不进生产)。
+
+用法: python scripts/mock_uniservice.py [端口,默认9099]
+预期请求头 X-Api-Key: test-key-123;收到推送打印前 2000 字符,回 accepted。
+"""
+import json
+import sys
+from http.server import BaseHTTPRequestHandler, HTTPServer
+
+KEY = "test-key-123"
+
+
+class Handler(BaseHTTPRequestHandler):
+    def do_POST(self):
+        n = int(self.headers.get("Content-Length", 0))
+        body = json.loads(self.rfile.read(n) or b"{}")
+        msgs = body.get("messages", [])
+        print(f"\n=== 收到推送 {len(msgs)} 条 (X-Api-Key={self.headers.get('X-Api-Key')}) ===")
+        print(json.dumps(msgs, ensure_ascii=False, indent=2)[:2000])
+        if self.headers.get("X-Api-Key") != KEY:
+            code, resp = 401, {"success": False, "error": "unauthorized"}
+        else:
+            code, resp = 200, {"success": True, "data": {
+                "accepted": len(msgs), "duplicated": 0, "failed": []}}
+        data = json.dumps(resp).encode()
+        self.send_response(code)
+        self.send_header("Content-Type", "application/json")
+        self.send_header("Content-Length", str(len(data)))
+        self.end_headers()
+        self.wfile.write(data)
+
+    def log_message(self, *a):   # 静默默认访问日志,只留推送打印
+        pass
+
+
+if __name__ == "__main__":
+    port = int(sys.argv[1]) if len(sys.argv) > 1 else 9099
+    print(f"mock UniService on http://127.0.0.1:{port} (期待 X-Api-Key: {KEY})")
+    HTTPServer(("127.0.0.1", port), Handler).serve_forever()