refactor: split websocket flows and add brain action decision pipeline
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181
core/websocket_followup_flow.py
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181
core/websocket_followup_flow.py
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import asyncio
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import os
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import time
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from datetime import datetime, timedelta
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import logging
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logger = logging.getLogger("cs_agent")
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async def unreplied_followup_loop(client):
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"""定时补偿：对“最后一条是客户消息且长时间未回复”的会话，补发一次自然跟进。"""
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if not client.enable_agent or not client.agent:
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return
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while client.running:
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try:
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await asyncio.sleep(max(30, int(os.getenv("UNREPLIED_FOLLOWUP_SCAN_SECONDS", "90"))))
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await scan_and_send_unreplied_followups(client)
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except asyncio.CancelledError:
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break
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except Exception as e:
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client._activity_log("unreplied_followup_loop_error", error=str(e))
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async def scan_and_send_unreplied_followups(client):
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from db import chat_log_db as cdb
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try:
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idle_minutes = max(5, int(os.getenv("UNREPLIED_FOLLOWUP_IDLE_MINUTES", "12")))
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max_age_minutes = max(idle_minutes, int(os.getenv("UNREPLIED_FOLLOWUP_MAX_AGE_MINUTES", "180")))
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followup_cd = max(300, int(os.getenv("UNREPLIED_FOLLOWUP_COOLDOWN_SECONDS", "3600")))
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limit = max(10, int(os.getenv("UNREPLIED_FOLLOWUP_LIMIT", "40")))
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except Exception:
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idle_minutes, max_age_minutes, followup_cd, limit = 12, 180, 3600, 40
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now = datetime.now()
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window_start = (now - timedelta(minutes=max_age_minutes)).strftime("%Y-%m-%d %H:%M:%S")
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conn = None
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try:
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conn = cdb._get_conn()
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rows = conn.execute(
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cdb._sql(
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"""
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SELECT acc_id, customer_id, MAX(id) AS last_id
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FROM chat_logs
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WHERE timestamp >= ?
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GROUP BY acc_id, customer_id
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ORDER BY MAX(id) DESC
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LIMIT ?
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"""
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),
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(window_start, limit * 6),
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).fetchall()
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sessions = [dict(r) for r in rows]
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sent = 0
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for s in sessions:
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if sent >= limit:
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break
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acc_id = str(s.get("acc_id", "") or "")
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cid = str(s.get("customer_id", "") or "")
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if not acc_id or not cid:
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continue
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ckey = f"{acc_id}:{cid}"
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if not client._is_owned_by_this_worker(ckey):
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continue
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last = conn.execute(
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cdb._sql(
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"""
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SELECT id, direction, message, timestamp, customer_name, acc_id, platform
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FROM chat_logs
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WHERE acc_id = ? AND customer_id = ?
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ORDER BY id DESC
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LIMIT 1
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"""
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),
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(acc_id, cid),
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).fetchone()
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if not last:
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continue
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last = dict(last)
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if str(last.get("direction", "")) != "in":
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continue
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last_ts = last.get("timestamp")
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if isinstance(last_ts, datetime):
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last_dt = last_ts
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else:
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last_dt = datetime.strptime(str(last_ts)[:19], "%Y-%m-%d %H:%M:%S")
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idle_s = (now - last_dt).total_seconds()
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if idle_s < idle_minutes * 60 or idle_s > max_age_minutes * 60:
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continue
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now_mono = time.monotonic()
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if (now_mono - client._unreplied_followup_sent.get(ckey, 0.0)) < followup_cd:
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continue
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last_msg = str(last.get("message", "") or "").strip().lower()
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if last_msg in {"好的", "好", "ok", "收到", "嗯", "哦"}:
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continue
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followup = await compose_ai_scene_reply(
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client,
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original_msg={
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"acc_id": acc_id,
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"from_id": cid,
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"from_name": client.to_chinese(last.get("customer_name", "") or cid),
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"acc_type": str(last.get("platform", "") or "AliWorkbench"),
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"msg": str(last.get("message", "") or ""),
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},
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scene="unreplied_followup",
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intent_hint="客户上一条消息还没接上，先自然承接并请对方补一句当前要处理的图或要求。",
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fallback="刚看到你消息了，我在的。你把要处理的图或要求再发我一下，我马上接着看。",
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)
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fake = {
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"acc_id": acc_id,
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"from_id": cid,
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"from_name": client.to_chinese(last.get("customer_name", "") or cid),
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"cy_id": cid,
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"cy_name": client.to_chinese(last.get("customer_name", "") or cid),
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"acc_type": str(last.get("platform", "") or "AliWorkbench"),
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"msg": str(last.get("message", "") or ""),
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"msg_type": 0,
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}
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await client.send_reply(fake, followup)
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client._unreplied_followup_sent[ckey] = now_mono
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sent += 1
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client._activity_log(
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"unreplied_followup_sent",
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acc_id=acc_id,
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customer_id=cid,
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idle_seconds=int(idle_s),
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last_msg=str(last.get("message", "") or "")[:120],
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reply=followup,
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)
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finally:
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try:
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if conn:
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conn.close()
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except Exception:
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logger.debug("关闭数据库连接失败", exc_info=True)
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async def compose_ai_scene_reply(client, *, original_msg: dict, scene: str, intent_hint: str, fallback: str) -> str:
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"""场景化 AI 直接生成回复（不依赖固定模板）。"""
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if not client.enable_agent or not client.agent or not client.AgentDeps:
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return fallback
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try:
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deps = client.AgentDeps(
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msg_id=str(original_msg.get("msg_id", "") or f"{scene}_gen"),
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acc_id=str(original_msg.get("acc_id", "") or ""),
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from_id=str(original_msg.get("from_id", "") or ""),
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platform=str(original_msg.get("acc_type", "") or ""),
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)
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customer_msg = client.to_chinese(str(original_msg.get("msg", "") or ""))
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prompt = (
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"你是淘宝客服，直接生成一条发给客户的话。\n"
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f"场景: {scene}\n"
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f"意图: {intent_hint}\n"
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f"客户原话: {customer_msg}\n"
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"要求: 1-2句，自然口语，不要模板腔，不要新增价格/承诺；只输出最终回复。\n"
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)
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result = await client.agent.agent_natural_reply.run(prompt, deps=deps, message_history=[])
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out = str(getattr(result, "output", "") or "").strip()
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if not out:
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return fallback
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if out.startswith("话术|") or "[转移会话]" in out or "TRANSFER_REQUESTED" in out:
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return fallback
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client._activity_log(
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"ai_scene_reply_generated",
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acc_id=str(original_msg.get("acc_id", "") or ""),
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customer_id=str(original_msg.get("from_id", "") or ""),
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scene=scene,
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generated=out[:160],
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)
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return out
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except Exception as e:
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client._activity_log(
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"ai_scene_reply_error",
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acc_id=str(original_msg.get("acc_id", "") or ""),
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customer_id=str(original_msg.get("from_id", "") or ""),
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scene=scene,
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error=str(e),
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)
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return fallback
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