🔄 卡若AI 同步 2026-02-22 11:58 | 更新：金仓、水桥平台对接、卡木、运营中枢工作台 | 排除 >20MB: 8 个

2026-02-22 11:58:14 +08:00
parent 8b434da135
commit 4e13af2f79
7 changed files with 221 additions and 266 deletions
--- a/01_卡资（金）/金仓_存储备份/服务器管理/scripts/腾讯云_TAT_kr宝塔_全量修复.py
+++ b/01_卡资（金）/金仓_存储备份/服务器管理/scripts/腾讯云_TAT_kr宝塔_全量修复.py
@@ -0,0 +1,179 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+腾讯云 TAT：kr宝塔 全量修复
+1. Nginx：确保使用宝塔 Nginx（若系统 Nginx 在运行则 kill 后启动宝塔 Nginx）
+2. Node 项目：全部在宝塔 Node 下启动（run=False 的逐一 stop→清端口→start）
+凭证：00_账号与API索引.md
+"""
+import base64
+import os
+import re
+import sys
+import time
+
+KR_INSTANCE_ID = "ins-aw0tnqjo"
+REGION = "ap-guangzhou"
+
+SHELL_SCRIPT = r'''#!/bin/bash
+set -e
+echo "=== kr宝塔 全量修复：Nginx(宝塔) + 全部 Node 项目 ==="
+
+# 1. Nginx：确认使用宝塔 Nginx，非系统 Nginx
+echo ""
+echo "【1】Nginx 检查与修复"
+NGX=$(ps aux | grep -E "nginx|nginx:" | grep -v grep | head -1 || true)
+if echo "$NGX" | grep -q "/usr/sbin/nginx"; then
+  echo "  检测到系统 Nginx，切换为宝塔 Nginx..."
+  killall nginx 2>/dev/null || true
+  sleep 2
+fi
+# 若无 nginx 或需确保宝塔 nginx
+if ! pgrep -f "/www/server/nginx" >/dev/null 2>&1; then
+  /www/server/nginx/sbin/nginx -c /www/server/nginx/conf/nginx.conf 2>/dev/null && echo "  宝塔 Nginx 已启动" || echo "  Nginx 可能已在运行"
+fi
+nginx -t 2>/dev/null && nginx -s reload 2>/dev/null && echo "  Nginx 重载完成"
+echo "  当前 Nginx: $(ps aux | grep nginx | grep -v grep | head -1 | awk '{print $11}')"
+
+# 2. 全部 Node 项目批量启动（宝塔 API）
+echo ""
+echo "【2】Node 项目批量启动（宝塔 API）"
+python3 - << 'PYEOF'
+import hashlib, json, os, re, subprocess, time, urllib.request, urllib.parse, ssl
+ssl._create_default_https_context = ssl._create_unverified_context
+PANEL, K = "https://127.0.0.1:9988", "qcWubCdlfFjS2b2DMT1lzPFaDfmv1cBT"
+def sign():
+    t = int(time.time())
+    s = str(t) + hashlib.md5(K.encode()).hexdigest()
+    return {"request_time": t, "request_token": hashlib.md5(s.encode()).hexdigest()}
+def post(p, d=None):
+    pl = sign()
+    if d: pl.update(d)
+    r = urllib.request.Request(PANEL + p, data=urllib.parse.urlencode(pl).encode())
+    with urllib.request.urlopen(r, timeout=30) as resp:
+        return json.loads(resp.read().decode())
+def pids(port):
+    try:
+        o = subprocess.check_output("ss -tlnp 2>/dev/null | grep ':%s ' || true" % port, shell=True, universal_newlines=True)
+        return sorted({int(x) for x in re.findall(r"pid=(\d+)", o)})
+    except: return []
+def ports(it):
+    cfg = it.get("project_config") or {}
+    if isinstance(cfg, str):
+        try: cfg = json.loads(cfg)
+        except: cfg = {}
+    ps = []
+    if cfg.get("port"): ps.append(int(cfg["port"]))
+    for m in re.findall(r"-p\s*(\d+)", str(cfg.get("project_script",""))): ps.append(int(m))
+    return sorted(set(ps))
+
+items = post("/project/nodejs/get_project_list").get("data") or post("/project/nodejs/get_project_list").get("list") or []
+to_start = [it for it in items if it.get("name") and it.get("run") is not True]
+print("  未运行项目数: %d / %d" % (len(to_start), len(items)))
+for it in to_start:
+    name = it.get("name") or it.get("project_name")
+    if not name: continue
+    try:
+        for port in ports(it):
+            for pid in pids(port):
+                try: subprocess.call("kill -9 %s 2>/dev/null" % pid, shell=True)
+                except: pass
+        pf = "/www/server/nodejs/vhost/pids/%s.pid" % name
+        if os.path.exists(pf):
+            try: open(pf,"w").write("0")
+            except: pass
+        post("/project/nodejs/stop_project", {"project_name": name})
+        time.sleep(0.5)
+        r = post("/project/nodejs/start_project", {"project_name": name})
+        ok = r.get("status") is True or "成功" in str(r.get("msg",""))
+        print("  %s: %s" % (name, "OK" if ok else "FAIL"))
+    except Exception as e:
+        print("  %s: ERR %s" % (name, str(e)[:60]))
+    time.sleep(1)
+
+time.sleep(5)
+items2 = post("/project/nodejs/get_project_list").get("data") or []
+run_c = sum(1 for x in items2 if x.get("run"))
+print("  结果: 运行 %d / 共 %d" % (run_c, len(items2)))
+PYEOF
+
+echo ""
+echo "=== 完成 ==="
+'''
+
+def _read_creds():
+    d = os.path.dirname(os.path.abspath(__file__))
+    for _ in range(6):
+        root = d
+        if os.path.isfile(os.path.join(root, "运营中枢", "工作台", "00_账号与API索引.md")):
+            path = os.path.join(root, "运营中枢", "工作台", "00_账号与API索引.md")
+            with open(path, "r", encoding="utf-8") as f:
+                text = f.read()
+            sid = skey = None
+            in_tx = False
+            for line in text.splitlines():
+                if "### 腾讯云" in line:
+                    in_tx = True
+                    continue
+                if in_tx and line.strip().startswith("###"):
+                    break
+                if not in_tx:
+                    continue
+                m = re.search(r"\|\s*[^|]*(?:SecretId|密钥)[^|]*\|\s*`([^`]+)`", line, re.I)
+                if m and m.group(1).strip().startswith("AKID"):
+                    sid = m.group(1).strip()
+                m = re.search(r"\|\s*SecretKey\s*\|\s*`([^`]+)`", line, re.I)
+                if m:
+                    skey = m.group(1).strip()
+            return sid or None, skey or None
+        d = os.path.dirname(d)
+    return None, None
+
+
+def main():
+    sid = os.environ.get("TENCENTCLOUD_SECRET_ID")
+    skey = os.environ.get("TENCENTCLOUD_SECRET_KEY")
+    if not sid or not skey:
+        sid, skey = _read_creds()
+    if not sid or not skey:
+        print("❌ 未配置腾讯云 SecretId/SecretKey")
+        return 1
+    try:
+        from tencentcloud.common import credential
+        from tencentcloud.tat.v20201028 import tat_client, models
+    except ImportError:
+        print("pip install tencentcloud-sdk-python-tat")
+        return 1
+
+    cred = credential.Credential(sid, skey)
+    client = tat_client.TatClient(cred, REGION)
+    req = models.RunCommandRequest()
+    req.Content = base64.b64encode(SHELL_SCRIPT.encode()).decode()
+    req.InstanceIds = [KR_INSTANCE_ID]
+    req.CommandType = "SHELL"
+    req.Timeout = 180
+    req.CommandName = "kr宝塔_全量修复"
+    resp = client.RunCommand(req)
+    print("✅ TAT 已下发 InvocationId:", resp.InvocationId)
+    print("  步骤: Nginx 强制宝塔 → 全部 Node 项目启动")
+    print("  等待 90s...")
+    time.sleep(90)
+    try:
+        req2 = models.DescribeInvocationTasksRequest()
+        f = models.Filter()
+        f.Name = "invocation-id"
+        f.Values = [resp.InvocationId]
+        req2.Filters = [f]
+        r2 = client.DescribeInvocationTasks(req2)
+        for t in (r2.InvocationTaskSet or []):
+            print("  状态:", getattr(t, "TaskStatus", ""))
+            out = getattr(t, "Output", None) or ""
+            if out:
+                print("  输出:\n", out[:4000])
+    except Exception as e:
+        print("  查询:", e)
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
--- a/02_卡人（水）/水桥_平台对接/飞书管理/脚本/feishu_md_to_wiki_一键流程.md
+++ b/02_卡人（水）/水桥_平台对接/飞书管理/脚本/feishu_md_to_wiki_一键流程.md
@@ -55,3 +55,13 @@ python3 "02_卡人（水）/水桥_平台对接/飞书管理/脚本/feishu_wiki_

 - 图片块（block_type 18 gallery）若飞书 API 报 `invalid param`，会退化为文本说明，图片仍上传至文档素材，用户可手动「插入 → 图片 → 文档素材」插入
 - `image_paths` 建议用相对路径，便于 JSON 迁移
+
+## 图片块调试
+
+若需尝试 file 块（block_type 12）代替 gallery 插入图片：
+
+```bash
+FEISHU_IMG_BLOCK=file python3 "02_卡人（水）/水桥_平台对接/飞书管理/脚本/feishu_wiki_gene_capsule_article.py"
+```
+
+脚本会打印 API 错误详情（code、msg、debug）便于排查。
--- a/02_卡人（水）/水桥_平台对接/飞书管理/脚本/feishu_wiki_gene_capsule_article.py
+++ b/02_卡人（水）/水桥_平台对接/飞书管理/脚本/feishu_wiki_gene_capsule_article.py
@@ -50,7 +50,8 @@ def upload_image_to_doc(token: str, doc_token: str, img_path: Path) -> str | Non


 def _make_image_block(file_token: str) -> dict:
-    """生成飞书图片块，尝试 gallery 与 file 两种格式"""
+    """生成飞书图片块。优先 gallery(18)，备选 file(12) 行内展示"""
+    # 格式参考飞书文档：Gallery imageList 每项需 fileToken
    return {
        "block_type": 18,
        "gallery": {
@@ -60,6 +61,14 @@ def _make_image_block(file_token: str) -> dict:
    }


+def _make_file_block(file_token: str, filename: str = "image.png") -> dict:
+    """备选：file 块行内展示图片（viewType=inline）"""
+    return {
+        "block_type": 12,
+        "file": {"fileToken": file_token, "viewType": "inline", "fileName": filename},
+    }
+
+
 def _title_matches(node_title: str, target: str) -> bool:
    """判断节点标题是否与目标相似（含关键词即视为匹配）"""
    if not node_title or not target:
@@ -207,10 +216,11 @@ def create_doc_with_images():
        for b in raw_blocks:
            c = (b.get("text") or {}).get("elements") or []
            content = (c[0].get("text_run") or {}).get("content", "") if c else ""
+            use_file_block = os.environ.get("FEISHU_IMG_BLOCK") == "file"
            if "【配图 1" in content and tokens[0]:
-                blocks.append(_make_image_block(tokens[0]))
+                blocks.append(_make_file_block(tokens[0], "基因胶囊_概念与流程.png") if use_file_block else _make_image_block(tokens[0]))
            elif "【配图 2" in content and len(tokens) > 1 and tokens[1]:
-                blocks.append(_make_image_block(tokens[1]))
+                blocks.append(_make_file_block(tokens[1], "基因胶囊_完整工作流程图.png") if use_file_block else _make_image_block(tokens[1]))
            elif "【配图 1" in content or "【配图 2" in content:
                blocks.append(b)
            else:
@@ -229,9 +239,11 @@ def create_doc_with_images():
            timeout=30)
        res = wr.json()
        if res.get("code") != 0:
+            if any(b.get("block_type") in (12, 13, 18) for b in batch):
+                print(f"⚠️ API 错误: code={res.get('code')} msg={res.get('msg')} debug={res.get('debug', '')}")
            # 若含图片的批次失败，则跳过图片仅写文本
-            if any(b.get("block_type") in (13, 18) for b in batch):
-                safe = [b for b in batch if b.get("block_type") not in (13, 18)]
+            if any(b.get("block_type") in (12, 13, 18) for b in batch):
+                safe = [b for b in batch if b.get("block_type") not in (12, 13, 18)]
                if safe:
                    wr2 = requests.post(
                        f"https://open.feishu.cn/open-apis/docx/v1/documents/{doc_token}/blocks/{doc_token}/children",
--- a/03_卡木（木）/木叶_视频内容/视频切片/脚本/identify_theme_segments.py
+++ b/03_卡木（木）/木叶_视频内容/视频切片/脚本/identify_theme_segments.py
@@ -1,234 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-按完整主题切片 - 分析 transcript，找出每个主题的完整起止时间
-
-与 identify_highlights 不同：本脚本按「视频剪辑方案」的 7 个主题类型分析，
-时间节点非固定，需结合视频内容分析出每个主题的完整段落。
-
-主题类型（来自剪辑方案图片）：
-1. 引出问题 - 建立共鸣，问用户痛点
-2. 解决方案 - 核心方法、干货
-3. 案例分享 - 真实案例、数据
-4. 未来展望 - 接下来怎么做
-5. 痛点强调 - 避坑、踩坑警告
-6. 福利展示 - 限时福利、福利放送
-7. 权威背书 - 专业背书、可信证明
-
-用法：
-  python3 identify_theme_segments.py -t transcript.srt -o highlights.json
-"""
-import argparse
-import json
-import re
-import sys
-from pathlib import Path
-
-OLLAMA_URL = "http://localhost:11434"
-DEFAULT_CTA = "关注我，每天学一招私域干货"
-
-THEME_DEFINITIONS = """
-【主题类型定义，按视频剪辑方案】
-1. 引出问题：开场建立共鸣，提出用户普遍遇到的问题或痛点
-2. 解决方案：讲解核心方法、干货、具体做法
-3. 案例分享：真实案例、数据佐证、用户证言
-4. 未来展望：接下来这样做、未来趋势、行动建议
-5. 痛点强调：这个坑千万别踩、常见误区、避坑指南
-6. 福利展示：限时福利、福利放送、赠送、优惠
-7. 权威背书：专业背书、可信证明、资质、成果展示
-
-参考时间顺序（非固定）：引出问题→解决方案→案例分享→未来展望→痛点强调→福利展示→权威背书
-"""
-
-
-def parse_srt_segments(srt_path: str) -> list:
-    """解析 SRT 为 [{start_sec, end_sec, start_time, end_time, text}, ...]"""
-    with open(srt_path, "r", encoding="utf-8") as f:
-        content = f.read()
-    segments = []
-    pattern = r"(\d+)\n(\d{2}):(\d{2}):(\d{2}),(\d{3}) --> (\d{2}):(\d{2}):(\d{2}),(\d{3})\n(.*?)(?=\n\n|\Z)"
-    for m in re.findall(pattern, content, re.DOTALL):
-        sh, sm, ss = int(m[1]), int(m[2]), int(m[3])
-        eh, em, es = int(m[5]), int(m[6]), int(m[7])
-        start_sec = sh * 3600 + sm * 60 + ss
-        end_sec = eh * 3600 + em * 60 + es
-        text = m[9].strip().replace("\n", " ")
-        if len(text) > 2:
-            segments.append({
-                "start_sec": start_sec, "end_sec": end_sec,
-                "start_time": f"{sh:02d}:{sm:02d}:{ss:02d}",
-                "end_time": f"{eh:02d}:{em:02d}:{es:02d}",
-                "text": text,
-            })
-    return segments
-
-
-def srt_to_timestamped_text(srt_path: str) -> str:
-    """将 SRT 转为带时间戳的纯文本"""
-    segments = parse_srt_segments(srt_path)
-    return "\n".join(f"[{s['start_time']}] {s['text']}" for s in segments)
-
-
-def _build_theme_prompt(transcript: str) -> str:
-    txt = transcript[:15000] if len(transcript) > 15000 else transcript
-    return f"""你是短视频内容策划师。根据「视频剪辑方案」，分析以下视频文字稿，找出 7 类主题各自的**完整段落**。
-
-{THEME_DEFINITIONS}
-
-【关键】时间节点非固定！需结合视频实际内容分析：
- 每个主题只取一段，且必须是**完整主题**（不中断、语义完整）
- 从文字稿中精确找出该主题开始和结束的时间点
- 若某类主题在视频中未出现，可跳过，不强制凑齐 7 段
- 参考顺序帮助理解，实际顺序按内容出现顺序
-
-【输出格式】严格 JSON 数组，每项含：
- theme: 主题类型名（如"引出问题"）
- title: 简短标题（简体中文）
- start_time: "HH:MM:SS"
- end_time: "HH:MM:SS"
- hook_3sec: 前3秒Hook，15字内
- cta_ending: 结尾CTA（可用"{DEFAULT_CTA}"）
- transcript_excerpt: 该段内容前60字
-
-只输出 JSON 数组，不要```包裹，不要其他文字。所有文字必须简体中文。
-
-视频文字稿：
---
-{txt}
---"""
-
-
-def _parse_ai_json(text: str) -> list:
-    text = text.strip()
-    if text.startswith("```"):
-        text = re.sub(r"^```(?:json)?\s*", "", text)
-        text = re.sub(r"\s*```\s*$", "", text)
-    m = re.search(r"\[[\s\S]*\]", text)
-    if m:
-        return json.loads(m.group())
-    return json.loads(text)
-
-
-def call_ollama(transcript: str) -> str:
-    """调用 Ollama 分析主题"""
-    import requests
-    prompt = _build_theme_prompt(transcript)
-    try:
-        r = requests.post(
-            f"{OLLAMA_URL}/api/generate",
-            json={
-                "model": "qwen2.5:1.5b",
-                "prompt": prompt,
-                "stream": False,
-                "options": {"temperature": 0.2, "num_predict": 8192},
-            },
-            timeout=120,
-        )
-        if r.status_code != 200:
-            raise RuntimeError(f"Ollama {r.status_code}")
-        return r.json().get("response", "").strip()
-    except Exception as e:
-        raise RuntimeError(f"Ollama 调用失败: {e}") from e
-
-
-def fallback_by_keywords(transcript_path: str) -> list:
-    """规则备用：按关键词粗分主题段，每段限制 45-120 秒"""
-    segments = parse_srt_segments(transcript_path)
-    if not segments:
-        return []
-    total_duration = segments[-1]["end_sec"] if segments else 0
-    theme_keywords = {
-        "引出问题": ["问题", "遇到", "痛点", "为什么", "困惑", "难题"],
-        "解决方案": ["方法", "解决", "怎么做", "技巧", "核心", "干货"],
-        "案例分享": ["案例", "例子", "数据", "客户", "赚了", "做了"],
-        "未来展望": ["接下来", "未来", "行动", "去做", "试试"],
-        "痛点强调": ["坑", "避坑", "千万别", "误区", "踩雷"],
-        "福利展示": ["福利", "限时", "赠送", "优惠", "免费"],
-        "权威背书": ["专业", "背书", "资质", "成果", "证明"],
-    }
-    MIN_SEG = 45
-    MAX_SEG = 120
-    result = []
-    used_until = 0  # 已使用到的时间点，避免重叠
-    for theme, kws in theme_keywords.items():
-        cands = [s for s in segments if s["start_sec"] >= used_until and any(kw in s["text"] for kw in kws)]
-        if not cands:
-            continue
-        first = cands[0]
-        start_sec = first["start_sec"]
-        # 合并相邻字幕，但限制在 MAX_SEG 秒内
-        end_sec = first["end_sec"]
-        for s in segments:
-            if s["start_sec"] < start_sec:
-                continue
-            if s["start_sec"] > start_sec + MAX_SEG:
-                break
-            if s["end_sec"] <= end_sec + 15:  # 连续/接近
-                end_sec = max(end_sec, s["end_sec"])
-            elif s["start_sec"] <= end_sec + 5:  # 间隙小于5秒
-                end_sec = min(s["end_sec"], start_sec + MAX_SEG)
-        end_sec = min(end_sec, start_sec + MAX_SEG)
-        if end_sec - start_sec < MIN_SEG:
-            end_sec = min(start_sec + MIN_SEG, total_duration)
-        used_until = end_sec + 10  # 下一段至少间隔10秒
-        h, m, s_ = int(start_sec // 3600), int((start_sec % 3600) // 60), int(start_sec % 60)
-        eh, em, es = int(end_sec // 3600), int((end_sec % 3600) // 60), int(end_sec % 60)
-        result.append({
-            "theme": theme,
-            "title": theme,
-            "start_time": f"{h:02d}:{m:02d}:{s_:02d}",
-            "end_time": f"{eh:02d}:{em:02d}:{es:02d}",
-            "hook_3sec": f"精彩{theme}",
-            "cta_ending": DEFAULT_CTA,
-            "transcript_excerpt": first["text"][:60],
-        })
-    return result
-
-
-def main():
-    parser = argparse.ArgumentParser(description="按完整主题分析 transcript")
-    parser.add_argument("--transcript", "-t", required=True, help="transcript.srt")
-    parser.add_argument("--output", "-o", required=True, help="highlights.json")
-    args = parser.parse_args()
-    transcript_path = Path(args.transcript)
-    if not transcript_path.exists():
-        print(f"❌ 不存在: {transcript_path}", file=sys.stderr)
-        sys.exit(1)
-    text = srt_to_timestamped_text(str(transcript_path))
-    if len(text) < 100:
-        print("❌ 文字稿过短", file=sys.stderr)
-        sys.exit(1)
-
-    data = None
-    try:
-        print("正在分析完整主题（Ollama）...")
-        raw = call_ollama(text)
-        data = _parse_ai_json(raw)
-        if data and isinstance(data, list):
-            # 校验时间格式
-            for i, h in enumerate(data):
-                if isinstance(h, dict):
-                    if "start" in h and "start_time" not in h:
-                        h["start_time"] = h.pop("start", "")
-                    if "end" in h and "end_time" not in h:
-                        h["end_time"] = h.pop("end", "")
-                    h.setdefault("title", h.get("theme", f"主题{i+1}"))
-                    h.setdefault("hook_3sec", h.get("title", "")[:15])
-                    h.setdefault("cta_ending", DEFAULT_CTA)
-            data = [h for h in data if isinstance(h, dict) and h.get("start_time") and h.get("end_time")]
-    except Exception as e:
-        print(f"Ollama 失败 ({e})，使用规则备用", file=sys.stderr)
-
-    if not data or not isinstance(data, list):
-        print("使用规则备用（按关键词）", file=sys.stderr)
-        data = fallback_by_keywords(str(transcript_path))
-
-    out_path = Path(args.output)
-    out_path.parent.mkdir(parents=True, exist_ok=True)
-    with open(out_path, "w", encoding="utf-8") as f:
-        json.dump(data, f, ensure_ascii=False, indent=2)
-    print(f"✅ 已输出 {len(data)} 个完整主题: {out_path}")
-
-
-if __name__ == "__main__":
-    main()
--- a/03_卡木（木）/木叶_视频内容/视频切片/脚本/soul_slice_pipeline.py
+++ b/03_卡木（木）/木叶_视频内容/视频切片/脚本/soul_slice_pipeline.py
@@ -89,10 +89,8 @@ def main():
    parser.add_argument("--video", "-v", required=True, help="输入视频路径")
    parser.add_argument("--output", "-o", help="输出目录（默认：视频同目录下 视频名_output）")
    parser.add_argument("--clips", "-n", type=int, default=8, help="切片数量")
-    parser.add_argument("--mode", "-m", choices=["highlights", "theme"], default="highlights",
-                        help="highlights=高光识别(默认); theme=按完整主题分析(时间节点非固定)")
    parser.add_argument("--skip-transcribe", action="store_true", help="跳过转录（已有 transcript.srt）")
-    parser.add_argument("--skip-highlights", action="store_true", help="跳过高光/主题识别（已有 highlights.json）")
+    parser.add_argument("--skip-highlights", action="store_true", help="跳过高光识别（已有 highlights.json）")
    parser.add_argument("--skip-clips", action="store_true", help="跳过切片（已有 clips/，仅重新增强）")
    args = parser.parse_args()

@@ -156,31 +154,19 @@ def main():
    transcript_to_simplified(transcript_path)
    print("  ✓ 字幕已转简体")

-    # 2. 高光/主题识别
+    # 2. 高光识别
    if not args.skip_highlights:
-        if args.mode == "theme":
-            run(
-                [
-                    sys.executable,
-                    str(SCRIPT_DIR / "identify_theme_segments.py"),
-                    "--transcript", str(transcript_path),
-                    "--output", str(highlights_path),
-                ],
-                "完整主题分析（Ollama→规则，时间节点非固定）",
-                timeout=120,
-            )
-        else:
-            run(
-                [
-                    sys.executable,
-                    str(SCRIPT_DIR / "identify_highlights.py"),
-                    "--transcript", str(transcript_path),
-                    "--output", str(highlights_path),
-                    "--clips", str(args.clips),
-                ],
-                "高光识别（Ollama→规则）",
-                timeout=60,
-            )
+        run(
+            [
+                sys.executable,
+                str(SCRIPT_DIR / "identify_highlights.py"),
+                "--transcript", str(transcript_path),
+                "--output", str(highlights_path),
+                "--clips", str(args.clips),
+            ],
+            "高光识别（Ollama→规则）",
+            timeout=60,
+        )
    if not highlights_path.exists():
        print(f"❌ 需要 highlights.json: {highlights_path}")
        sys.exit(1)
--- a/运营中枢/工作台/gitea_push_log.md
+++ b/运营中枢/工作台/gitea_push_log.md
@@ -84,3 +84,4 @@
 | 2026-02-22 11:32:57 | 🔄 卡若AI 同步 2026-02-22 11:32 | 更新：金仓、运营中枢工作台 | 排除 >20MB: 8 个 |
 | 2026-02-22 11:40:59 | 🔄 卡若AI 同步 2026-02-22 11:40 | 更新：水桥平台对接、卡木、运营中枢工作台 | 排除 >20MB: 8 个 |
 | 2026-02-22 11:44:40 | 🔄 卡若AI 同步 2026-02-22 11:44 | 更新：水桥平台对接、卡木、运营中枢工作台 | 排除 >20MB: 8 个 |
+| 2026-02-22 11:47:38 | 🔄 卡若AI 同步 2026-02-22 11:47 | 更新：水桥平台对接、运营中枢工作台 | 排除 >20MB: 8 个 |
--- a/运营中枢/工作台/代码管理.md
+++ b/运营中枢/工作台/代码管理.md
@@ -87,3 +87,4 @@
 | 2026-02-22 11:32:57 | 成功 | 成功 | 🔄 卡若AI 同步 2026-02-22 11:32 | 更新：金仓、运营中枢工作台 | 排除 >20MB: 8 个 | [仓库](http://open.quwanzhi.com:3000/fnvtk/karuo-ai) [百科](http://open.quwanzhi.com:3000/fnvtk/karuo-ai/wiki) |
 | 2026-02-22 11:40:59 | 成功 | 成功 | 🔄 卡若AI 同步 2026-02-22 11:40 | 更新：水桥平台对接、卡木、运营中枢工作台 | 排除 >20MB: 8 个 | [仓库](http://open.quwanzhi.com:3000/fnvtk/karuo-ai) [百科](http://open.quwanzhi.com:3000/fnvtk/karuo-ai/wiki) |
 | 2026-02-22 11:44:40 | 成功 | 成功 | 🔄 卡若AI 同步 2026-02-22 11:44 | 更新：水桥平台对接、卡木、运营中枢工作台 | 排除 >20MB: 8 个 | [仓库](http://open.quwanzhi.com:3000/fnvtk/karuo-ai) [百科](http://open.quwanzhi.com:3000/fnvtk/karuo-ai/wiki) |
+| 2026-02-22 11:47:38 | 成功 | 成功 | 🔄 卡若AI 同步 2026-02-22 11:47 | 更新：水桥平台对接、运营中枢工作台 | 排除 >20MB: 8 个 | [仓库](http://open.quwanzhi.com:3000/fnvtk/karuo-ai) [百科](http://open.quwanzhi.com:3000/fnvtk/karuo-ai/wiki) |