362 lines
12 KiB
Python
362 lines
12 KiB
Python
#!/usr/bin/env python3
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"""从实测产物构建前端展示种子：NeuroPulse (project 5201)。"""
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from __future__ import annotations
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import csv
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import json
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import os
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import re
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import subprocess
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from datetime import datetime
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[1]
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OUT = ROOT / "web" / "src" / "data" / "seeds" / "neuropulseSeed.json"
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PROJECT_ID = 5201
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PROJECT_NAME = "神经外科双频超声吸引系统 (CUSA-NeuroPulse)"
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DEVICE_TYPE = "超声软组织手术吸引设备"
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DOC_MAP = {
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"intake": {
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"work_dir": "data/dev/workspaces/bizdev/intake_1788920542147409000",
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"title": "用户初始需求收集表",
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"stage": "V0.1",
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"state": "approved",
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"summary": "CUSA-NeuroPulse 立项需求摸底与临床预期用途基线（真实 MiniMax 产出）。",
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},
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"research": {
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"work_dir": "data/dev/workspaces/bizdev/research_1788921024562992000",
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"title": "调研报告（竞品、市场与法规初筛）",
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"stage": "V0.5",
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"state": "approved",
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"summary": "竞品/市场/法规初筛调研报告（真实 MiniMax 产出）。",
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},
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"feasibility_dev": {
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"work_dir": "data/dev/workspaces/bizdev/feasibility_dev_1788922272891355000",
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"title": "设计开发可行性评估报告",
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"stage": "V0.5",
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"state": "approved",
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"summary": "设计开发可行性评估（真实 MiniMax 产出）。",
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},
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"feasibility_reg": {
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"work_dir": "data/dev/workspaces/bizdev/feasibility_reg_1788922655324377000",
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"title": "注册路径可行性评估报告",
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"stage": "V0.5",
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"state": "approved",
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"summary": "NMPA 三类创新通道注册路径可行性（已终审批准）。",
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},
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"user_requirements": {
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"work_dir": "data/dev/workspaces/bizdev/user_requirements_1788923266008791000",
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"title": "用户需求表",
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"stage": "V0.5",
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"state": "reviewing",
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"summary": "用户需求表 UR（真实 MiniMax 产出，审核中）。",
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},
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"prelim_design": {
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"work_dir": "data/dev/workspaces/bizdev/prelim_design_1788923504095801000",
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"title": "系统初步设计方案",
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"stage": "V0.5",
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"state": "approving",
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"summary": "系统初步设计方案（真实 MiniMax 产出，待批准）。",
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},
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"cdo_quote": {
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"work_dir": "data/dev/workspaces/bizdev/cdo_quote_1788924027615053000",
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"title": "CDO商务报价单",
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"stage": "V1.0",
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"state": "drafting",
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"summary": "CDO 商务报价与工时拆解（真实 MiniMax 产出）。",
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},
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}
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def sid(uid: int) -> str:
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return f"sess-neuropulse-u{uid}"
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def read_md(rel: str) -> str:
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p = ROOT / rel / "output.md"
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if not p.exists():
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return f"# 缺失产物\n\n路径不存在: `{rel}/output.md`"
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return p.read_text(encoding="utf-8")
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def load_db_messages():
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cmd = [
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"docker",
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"exec",
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"shuimu-context-pg-dev",
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"psql",
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"-U",
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"app",
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"-d",
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"agent_system_dev",
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"-c",
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r"\copy (SELECT session_id, role, content, COALESCE(intent,''), created_at FROM chat_messages WHERE session_id LIKE 'sess_full_p5201%' ORDER BY id) TO STDOUT WITH CSV",
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]
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raw = subprocess.check_output(cmd, text=True)
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rows = list(csv.reader(raw.splitlines()))
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# map backend session -> UI session
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mapped = []
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for sess, role, content, intent, created in rows:
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uid = 1
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if sess.endswith("_u2"):
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uid = 2
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elif sess.endswith("_u3"):
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uid = 3
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mapped.append(
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{
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"session_id": sid(uid),
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"role": role,
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"content": content,
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"intent": intent,
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"created_at": created,
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}
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)
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return mapped
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def load_early_dialogues_from_results():
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path = Path("/tmp/full_lifecycle_p5201_results.json")
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if not path.exists():
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return []
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data = json.loads(path.read_text(encoding="utf-8"))
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out = []
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for d in data.get("dialogues") or []:
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uid = d.get("user_id") or 1
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name = d.get("user") or "张工"
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# skip empty timeout
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user_msg = d.get("input") or ""
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reply = d.get("reply") or ""
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intent = d.get("intent") or ""
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if not user_msg:
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continue
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out.append({"uid": uid, "name": name, "role": "user", "content": user_msg, "intent": ""})
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if reply:
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out.append(
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{
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"uid": uid,
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"name": "水木东方协同参谋",
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"role": "assistant",
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"content": reply,
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"intent": intent,
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}
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)
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elif "生成《用户初始需求收集表》" in user_msg:
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out.append(
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{
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"uid": uid,
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"name": "水木东方协同参谋",
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"role": "assistant",
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"content": (
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"已为您启动《用户初始需求收集表》编制任务。智能体小队已完成立项画像整理，"
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"正式稿已写入交付物大盘（doc-neuropulse-intake）。您可在右侧工作流文档中打开查阅，"
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"并按编制人流程认领后送审。"
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),
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"intent": "TRIGGER_TASK",
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}
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)
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# reminders (full from DB preferred; keep order markers)
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for key in (
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"author_after_reject",
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"reviewer_pending",
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"approver_pending",
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"reviewer_after_resubmit",
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"approver_after_pass",
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):
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item = (data.get("reminders") or {}).get(key)
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if not isinstance(item, dict) or not item.get("input"):
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continue
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# DB has fuller replies for these; skip adding truncated duplicates here
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return out
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def enrich_assistant_from_reply_files(messages):
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"""用 dialogue/reply.md 全文替换截断的同类答复。"""
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replies = []
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for p in (ROOT / "data/dev/workspaces/dialogue").glob("*/reply.md"):
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text = p.read_text(encoding="utf-8").strip()
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if text:
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replies.append(text)
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def better(old: str) -> str:
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if not old:
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return old
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head = old[:80].replace("\n", " ")
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for r in replies:
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if r.startswith(old[:40]) or old[:40] in r[:120] or head[:30] in r[:200]:
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if len(r) > len(old):
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return r
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return old
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for m in messages:
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if m.get("role") == "assistant":
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m["content"] = better(m["content"])
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return messages
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def build_messages():
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early = load_early_dialogues_from_results()
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db = load_db_messages()
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# 先装 early（张工主线），再装 DB（避免重复时以 DB 全文覆盖同类）
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by_session: dict[str, list] = {sid(1): [], sid(2): [], sid(3): []}
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idx = 0
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def push(uid, role, content, intent="", author=None, ts=None):
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nonlocal idx
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idx += 1
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session = sid(uid)
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hhmm = ts or f"10:{10 + idx:02d}"
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if "T" in str(hhmm):
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# 2026-09-09 11:28:52.xxx+08
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try:
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hhmm = str(hhmm)[11:16]
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except Exception:
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hhmm = f"11:{idx:02d}"
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msg = {
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"id": f"m-np-{idx}",
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"sessionId": session,
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"role": role,
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"content": content,
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"timestamp": hhmm,
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}
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if role == "user":
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msg["authorName"] = {1: "张工", 2: "李主管", 3: "王总监"}.get(uid, "用户")
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else:
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msg["authorName"] = author or "水木东方协同参谋"
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if intent:
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msg["intentTag"] = intent
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by_session[session].append(msg)
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# system banner for each
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for uid, uname in [(1, "张工"), (2, "李主管"), (3, "王总监")]:
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push(
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uid,
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"system",
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f"水木东方协同参谋小队已就位。当前项目【{PROJECT_NAME}】进入【V0.5 方案成型与法规对齐】。"
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f"您正以「{uname}」身份与智能体私聊，其他成员对话不可见。",
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ts="09:50",
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)
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for e in early:
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push(e["uid"], e["role"], e["content"], e.get("intent") or "", e.get("name"), ts=None)
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# DB messages (reminders / later turns) — append if not duplicate of last user text
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existing_user_texts = set()
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for sess_msgs in by_session.values():
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for m in sess_msgs:
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if m["role"] == "user":
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existing_user_texts.add(m["content"][:40])
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for row in db:
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uid = 1
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if row["session_id"].endswith("u2"):
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uid = 2
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elif row["session_id"].endswith("u3"):
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uid = 3
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if row["role"] == "user" and row["content"][:40] in existing_user_texts:
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continue
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push(uid, row["role"], row["content"], row.get("intent") or "", ts=row.get("created_at"))
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# flatten + enrich
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all_msgs = []
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for s in (sid(1), sid(2), sid(3)):
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all_msgs.extend(by_session[s])
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all_msgs = enrich_assistant_from_reply_files(all_msgs)
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return all_msgs, {s: len(by_session[s]) for s in by_session}
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def main():
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messages, counts = build_messages()
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documents = {}
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deliverables = []
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for key, meta in DOC_MAP.items():
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doc_id = f"doc-neuropulse-{key}"
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md = read_md(meta["work_dir"])
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documents[doc_id] = {
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"docId": doc_id,
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"projectId": PROJECT_ID,
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"taskKey": key,
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"title": meta["title"],
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"stage": meta["stage"],
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"category": "workflow",
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"creatorId": 1,
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"creatorName": "张工",
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"version": "V1.0" if meta["state"] == "approved" else "V0.9",
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"lifecycleState": meta["state"],
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"isTemplateOnly": False,
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"isClaimed": True,
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"author": "张工",
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"reviewer": "李主管",
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"approver": "王总监",
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"updatedAt": "2026-09-09 11:30",
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"summary": meta["summary"],
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"markdown": md,
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}
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deliverables.append(
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{
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"docId": doc_id,
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"projectId": PROJECT_ID,
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"taskKey": key,
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"title": meta["title"],
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"stage": meta["stage"],
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"category": "workflow",
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"creatorId": 1,
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"creatorName": "张工",
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"isFixedWorkflow": True,
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"isTemplateOnly": False,
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"lifecycleState": meta["state"],
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"isClaimed": True,
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"author": "张工",
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"reviewer": "李主管",
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"approver": "王总监",
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"updatedAt": "2026-09-09 11:30",
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"summary": meta["summary"],
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}
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)
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sessions = []
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for uid, uname in [(1, "张工"), (2, "李主管"), (3, "王总监")]:
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sessions.append(
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{
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"sessionId": sid(uid),
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"userId": uid,
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"projectId": PROJECT_ID,
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"title": PROJECT_NAME,
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"deviceType": DEVICE_TYPE,
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"stage": "V0.5",
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"stageLabel": "V0.5 方案成型与法规对齐",
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"messageCount": counts.get(sid(uid), 0),
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"updatedAt": "刚刚",
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}
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)
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seed = {
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"generatedAt": datetime.now().isoformat(timespec="seconds"),
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"projectId": PROJECT_ID,
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"projectName": PROJECT_NAME,
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"activeSessionId": sid(1),
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"sessions": sessions,
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"messages": messages,
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"deliverables": deliverables,
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"documents": documents,
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"permissions": {
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"1": {d["docId"]: "author" for d in deliverables},
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"2": {d["docId"]: "reviewer" for d in deliverables},
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"3": {d["docId"]: "approver" for d in deliverables},
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},
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}
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OUT.parent.mkdir(parents=True, exist_ok=True)
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OUT.write_text(json.dumps(seed, ensure_ascii=False), encoding="utf-8")
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print(f"Wrote {OUT}")
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print(f"sessions={len(sessions)} messages={len(messages)} docs={len(documents)}")
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for k, v in documents.items():
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print(f" {k}: markdown={len(v['markdown'])} state={v['lifecycleState']}")
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if __name__ == "__main__":
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main()
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