feat: 添加自然语言触发支持
- 支持'保存到知识库'/'订阅到知识库'触发词 - 自动检测链接并处理 - 更新SKILL.md文档
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OpenClaw Agent
@@ -19,6 +19,27 @@ KB Workflow 是一个完整的知识库管理系统，包含：
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- 🧹 **自动清理** - 定期清理临时文件
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- 📊 **汇报生成** - 生成处理统计
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## 触发方式
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### 自然语言触发
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当用户发送包含以下模式的消息时，技能会自动触发：
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| 触发词 | 行为 | 示例 |
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|--------|------|------|
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| `保存到知识库` + 链接 | 添加到收件箱并处理 | "保存到知识库 https://www.bilibili.com/video/BVxxx" |
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| `添加到知识库` + 链接 | 添加到收件箱并处理 | "添加到知识库 https://www.bilibili.com/video/BVxxx" |
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| `订阅到知识库` + 链接 | 添加到订阅列表 | "订阅到知识库 https://www.bilibili.com/video/BVxxx" |
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| `订阅知识库` + 链接 | 添加到订阅列表 | "订阅知识库 https://www.bilibili.com/video/BVxxx" |
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### 支持的平台
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| 平台 | 保存 | 订阅 |
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|------|------|------|
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| Bilibili | ✅ | ✅ |
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| YouTube | ✅ | ❌ |
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| 知乎 | ✅ | ❌ |
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## 目录结构
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```
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@@ -4,6 +4,10 @@ Auto-trigger handler for obsidian-kb skill.
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Detects video/article links in user messages and automatically processes them.
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Supports Bilibili, YouTube, and Zhihu.
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## 触发词
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- "保存到知识库" + 链接 → 添加到收件箱并处理
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- "订阅到知识库" + 链接 → 添加订阅
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"""
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import re
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@@ -41,6 +45,12 @@ PATTERNS = {
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'zhihu_answer': re.compile(r'https?://(?:www\.)?zhihu\.com/question/\d+/answer/(\d+)'),
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}
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# 触发词模式
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TRIGGER_PATTERNS = {
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'save': re.compile(r'(保存到知识库|加入知识库|添加到知识库)', re.IGNORECASE),
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'subscribe': re.compile(r'(订阅到知识库|订阅知识库|关注到知识库)', re.IGNORECASE),
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}
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def detect_links(text: str) -> List[Dict[str, str]]:
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"""
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@@ -196,6 +206,96 @@ def get_action_prompt(detected: List[Dict[str, str]]) -> str:
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return f"是否将上述 {count} 个内容添加到收件箱？(y/n)"
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def detect_triggers(text: str) -> Optional[str]:
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"""
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检测用户消息中的触发词。
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Args:
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text: 用户消息
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Returns:
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'save' | 'subscribe' | None
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"""
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# 检测"保存到知识库"
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if TRIGGER_PATTERNS['save'].search(text):
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return 'save'
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# 检测"订阅到知识库"
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if TRIGGER_PATTERNS['subscribe'].search(text):
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return 'subscribe'
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return None
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def handle_save_to_kb(detected: List[Dict[str, str]]) -> str:
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"""
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处理"保存到知识库"命令：将链接添加到收件箱并处理。
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Args:
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detected: 检测到的链接列表
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Returns:
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处理结果消息
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"""
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if not detected:
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return "❌ 未检测到任何链接，请提供要保存的链接"
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results = []
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for item in detected:
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if item['is_short']:
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results.append(f"⚠️ 短链接无法处理: {item['url']}")
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continue
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# 调用保存处理
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success, msg = process_link(item['url'], item['platform'], auto_process=True)
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results.append(msg)
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return "\n".join(results)
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def handle_subscribe_to_kb(detected: List[Dict[str, str]]) -> str:
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"""
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处理"订阅到知识库"命令：将链接添加到订阅列表。
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Args:
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detected: 检测到的链接列表
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Returns:
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处理结果消息
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"""
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if not detected:
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return "❌ 未检测到任何链接，请提供要订阅的链接"
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results = []
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for item in detected:
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if item['platform'] != 'bilibili':
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results.append(f"⚠️ 暂不支持订阅 {item['platform']}: {item['url']}")
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continue
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if item['is_short']:
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results.append(f"⚠️ 短链接无法订阅: {item['url']}")
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continue
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try:
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# 调用订阅命令
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import subprocess
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cmd = [
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sys.executable,
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os.path.join(os.path.dirname(__file__), 'kb_workflow.py'),
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'--trigger', 'subscriptions',
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'--add', 'bilibili', 'video', item['id'], item.get('url', '')
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]
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result = subprocess.run(cmd, capture_output=True, text=True)
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if result.returncode == 0:
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results.append(f"✅ 已订阅: {item['id']}")
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else:
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results.append(f"❌ 订阅失败: {result.stderr}")
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except Exception as e:
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results.append(f"❌ 订阅失败: {e}")
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return "\n".join(results)
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def should_auto_process(text: str) -> bool:
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"""
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Check if user wants to auto-process based on their message.
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@@ -326,21 +426,45 @@ def handle_message(text: str) -> Optional[str]:
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"""
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Main entry point: handle incoming message and return response.
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## 触发条件
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- 检测到"保存到知识库"/"订阅到知识库"触发词 + 链接 → 自动处理
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- 仅检测到链接 → 询问用户是否处理
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Args:
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text: User's message text
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Returns:
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Response message, or None if no action needed
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"""
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# First, check for short links and provide help
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has_short, short_msg = detect_and_format(text)
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# 首先检测触发词
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trigger = detect_triggers(text)
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# Detect all links (including short ones)
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# 检测链接
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detected = detect_links(text)
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if not detected:
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# 如果没有链接，也没有触发词，返回 None
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if not detected and not trigger:
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return None
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# 如果有触发词（save/subscribe），但没有链接
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if trigger and not detected:
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if trigger == 'save':
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return "请提供要保存到知识库的链接"
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elif trigger == 'subscribe':
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return "请提供要订阅到知识库的链接"
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# 处理"保存到知识库"触发
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if trigger == 'save':
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return handle_save_to_kb(detected)
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# 处理"订阅到知识库"触发
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if trigger == 'subscribe':
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return handle_subscribe_to_kb(detected)
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# 以下是原有的仅链接检测逻辑
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# First, check for short links and provide help
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has_short, short_msg = detect_and_format(text)
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# If we have short links, show help message first
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if has_short:
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return short_msg
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