AI 直接解析 PDF 文档！OpenClaw 2026.3.3 新功能实测太强了

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# OpenClaw 本地文件查询方法详解

OpenClaw 作为一个本地运行的 AI 助手，其文件系统查询功能是核心能力之一。以下是完整的本地文件查询方法和实践指南。

🔍 文件查询的核心方法

1. 基础文件系统查询

# <em>OpenClaw</em> 内置的文件查询工具示例 import os import glob def search_files(directory, pattern=&quot;*&quot;, recursive=True): &quot;&quot;&quot; 在指定目录中搜索文件 Args: directory: 搜索目录路径 pattern: 文件匹配模式 recursive: 是否递归搜索子目录 &quot;&quot;&quot; if recursive: # 递归搜索所有子目录 matches = [] for root, dirs, files in os<em>.</em>walk(directory): for file in files: if glob<em>.</em>fnmatch<em>.</em>fnmatch(file, pattern): matches<em>.</em>append(os<em>.</em>path<em>.</em>join(root, file)) return matches else: # 仅搜索当前目录 return glob<em>.</em>glob(os<em>.</em>path<em>.</em>join(directory, pattern)) # 示例：搜索所有 <em>.</em>md 文件 markdown_files = search_files(&quot;/path/to/documents&quot;, &quot;*<em>.</em>md&quot;)

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2. 通过 OpenClaw Gateway 查询

OpenClaw Gateway 作为控制平面，提供了统一的文件访问接口 [ref_1]：

讯享网// 通过 WebSocket 连接 Gateway 进行文件查询 const ws = new WebSocket(&amp;#<em>3</em>9;ws://127<em>.</em>0<em>.</em>0<em>.</em>1:18789&amp;#<em>3</em>9;); // 文件查询请求 const fileQueryRequest = { &quot;type&quot;: &quot;file_query&quot;, &quot;payload&quot;: { &quot;operation&quot;: &quot;search&quot;, &quot;path&quot;: &quot;~/Documents&quot;, &quot;pattern&quot;: &quot;*<em>.</em><em>pdf</em>&quot;, &quot;max_depth&quot;: <em>3</em> } }; ws<em>.</em>send(JSON<em>.</em>stringify(fileQueryRequest));

📁 文件查询的具体应用场景

1. 文档管理系统

class DocumentManager: def __init__(self, base_path=&quot;~/Documents&quot;): self<em>.</em>base_path = os<em>.</em>path<em>.</em>expanduser(base_path) def find_documents_by_type(self, doc_type): &quot;&quot;&quot;根据<em>文档</em>类型查找文件&quot;&quot;&quot; extensions = { &quot;<em>pdf</em>&quot;: &quot;*<em>.</em><em>pdf</em>&quot;, &quot;word&quot;: &quot;*<em>.</em>docx&quot;, &quot;excel&quot;: &quot;*<em>.</em>xlsx&quot;, &quot;markdown&quot;: &quot;*<em>.</em>md&quot; } pattern = extensions<em>.</em>get(doc_type, &quot;*&quot;) return self<em>.</em>search_files(self<em>.</em>base_path, pattern) def search_by_content(self, keywords, file_types=[&quot;*<em>.</em>txt&quot;, &quot;*<em>.</em>md&quot;, &quot;*<em>.</em><em>pdf</em>&quot;]): &quot;&quot;&quot;根据内容关键词搜索文件&quot;&quot;&quot; results = [] for file_type in file_types: files = self<em>.</em>search_files(self<em>.</em>base_path, file_type) for file_path in files: if self<em>.</em>cont<em>ai</em>ns_keywords(file_path, keywords): results<em>.</em>append(file_path) return results def cont<em>ai</em>ns_keywords(self, file_path, keywords): &quot;&quot;&quot;检查文件是否包含关键词&quot;&quot;&quot; try: with open(file_path, &amp;#<em>3</em>9;r&amp;#<em>3</em>9;, encoding=&amp;#<em>3</em>9;utf-8&amp;#<em>3</em>9;) as f: content = f<em>.</em>read()<em>.</em>lower() return any(keyword<em>.</em>lower() in content for keyword in keywords) except: return False

2. 记忆系统文件查询

OpenClaw 的记忆系统使用本地文件存储，查询方法如下 [ref_1]：

讯享网# 记忆系统文件结构查询 memory_system = { &quot;short_term&quot;: &quot;当前会话记忆&quot;, &quot;long_term&quot;: &quot;MEMORY<em>.</em>md&quot;, &quot;d<em>ai</em>ly_notes&quot;: &quot;memory/YYYY-MM-DD<em>.</em>md&quot;, &quot;cross_session&quot;: &quot;跨智能体共享记忆&quot; } def query_memory_files(date=None, topic=None): &quot;&quot;&quot;查询记忆系统文件&quot;&quot;&quot; base_path = &quot;<em>.</em>/memory&quot; if date: # 查询特定日期的记忆文件 file_path = f&quot;{base_path}/{date}<em>.</em>md&quot; if os<em>.</em>path<em>.</em>exists(file_path): return [file_path] elif topic: # 基于主题搜索所有记忆文件 return search_files(base_path, &quot;*<em>.</em>md&quot;) return [] # 示例：查询今天的记忆文件 today_memory = query_memory_files(date=&quot;2024-01-15&quot;)

🛠️ 实用的文件查询技能

1. 文件搜索技能实现

class FileSearchSkill: &quot;&quot;&quot;<em>OpenClaw</em> 文件搜索技能&quot;&quot;&quot; def setup(self): self<em>.</em>supported_operations = [ &quot;search_by_name&quot;, &quot;search_by_content&quot;, &quot;search_by_type&quot;, &quot;recent_files&quot; ] def execute(self, operation, kwargs): if operation == &quot;search_by_name&quot;: return self<em>.</em>search_by_name(kwargs<em>.</em>get(&amp;#<em>3</em>9;pattern&amp;#<em>3</em>9;), kwargs<em>.</em>get(&amp;#<em>3</em>9;directory&amp;#<em>3</em>9;)) elif operation == &quot;search_by_content&quot;: return self<em>.</em>search_by_content(kwargs<em>.</em>get(&amp;#<em>3</em>9;keywords&amp;#<em>3</em>9;), kwargs<em>.</em>get(&amp;#<em>3</em>9;file_types&amp;#<em>3</em>9;)) elif operation == &quot;search_by_type&quot;: return self<em>.</em>search_by_type(kwargs<em>.</em>get(&amp;#<em>3</em>9;file_type&amp;#<em>3</em>9;)) elif operation == &quot;recent_files&quot;: return self<em>.</em>get_recent_files(kwargs<em>.</em>get(&amp;#<em>3</em>9;limit&amp;#<em>3</em>9;, 10)) def search_by_name(self, pattern, directory=&quot;~&quot;): &quot;&quot;&quot;按文件名模式搜索&quot;&quot;&quot; import fnmatch results = [] search_path = os<em>.</em>path<em>.</em>expanduser(directory) for root, dirs, files in os<em>.</em>walk(search_path): for file in files: if fnmatch<em>.</em>fnmatch(file, pattern): results<em>.</em>append(os<em>.</em>path<em>.</em>join(root, file)) return results def get_recent_files(self, limit=10): &quot;&quot;&quot;获取最近访问的文件&quot;&quot;&quot; import time all_files = [] # 搜索常见<em>文档</em>目录 common_dirs = [ &quot;~/Documents&quot;, &quot;~/Downloads&quot;, &quot;~/Desktop&quot; ] for directory in common_dirs: dir_path = os<em>.</em>path<em>.</em>expanduser(directory) if os<em>.</em>path<em>.</em>exists(dir_path): for root, dirs, files in os<em>.</em>walk(dir_path): for file in files: file_path = os<em>.</em>path<em>.</em>join(root, file) stat = os<em>.</em>stat(file_path) all_files<em>.</em>append() # 按访问时间排序 all_files<em>.</em>sort(key=lambda x: x[&amp;#<em>3</em>9;accessed&amp;#<em>3</em>9;], reverse=True) return all_files[:limit]

2. 集成到自动化工作流

讯享网# 自动化文件管理工作流示例 def automated_file_organization(): &quot;&quot;&quot;自动文件整理工作流&quot;&quot;&quot; # 1<em>.</em> 搜索未分类的<em>文档</em> unorganized_files = search_files(&quot;~/Downloads&quot;, &quot;*&quot;) # 2<em>.</em> 按类型分类 file_categories = for category, patterns in file_categories<em>.</em>items(): category_dir = f&quot;~/Documents/{category}&quot; os<em>.</em>makedirs(os<em>.</em>path<em>.</em>expanduser(category_dir), exist_ok=True) for pattern in patterns: matching_files = search_files(&quot;~/Downloads&quot;, pattern) for file_path in matching_files: # 移动文件到对应分类目录 filename = os<em>.</em>path<em>.</em>basename(file_path) dest_path = os<em>.</em>path<em>.</em>join(category_dir, filename) os<em>.</em>rename(file_path, dest_path)

🔧 高级查询技巧

1. 使用 Canvas 可视化文件查询结果

OpenClaw 的 Canvas 功能可以可视化展示文件查询结果 [ref_1]：

&lt;<em>!</em>-- Canvas 文件查询结果可视化 --&gt; &lt;div class=&quot;file-browser&quot;&gt; &lt;h<em>3</em>&gt;文件查询结果&lt;/h<em>3</em>&gt; &lt;div class=&quot;search-results&quot;&gt; &lt;div class=&quot;file-item&quot; v-for=&quot;file in files&quot;&gt; &lt;span class=&quot;file-icon&quot;&gt;}&lt;/span&gt; &lt;span class=&quot;file-name&quot;&gt;{{ file<em>.</em>name }}&lt;/span&gt; &lt;span class=&quot;file-path&quot;&gt;{{ file<em>.</em>path }}&lt;/span&gt; &lt;span class=&quot;file-size&quot;&gt;{{ file<em>.</em>size }}&lt;/span&gt; &lt;span class=&quot;file-modified&quot;&gt;}&lt;/span&gt; &lt;/div&gt; &lt;/div&gt; &lt;/div&gt;

2. 多节点文件系统同步查询

当 OpenClaw 运行在多个节点时，可以跨设备查询文件 [ref_1]：

讯享网class CrossDeviceFileQuery: &quot;&quot;&quot;跨设备文件查询&quot;&quot;&quot; def __init__(self): self<em>.</em>nodes = { &quot;macos&quot;: &quot;macOS节点&quot;, &quot;ios&quot;: &quot;iOS节点&quot;, &quot;android&quot;: &quot;Android节点&quot; } def query_across_devices(self, pattern, node_types=None): &quot;&quot;&quot;跨节点查询文件&quot;&quot;&quot; if node_types is None: node_types = list(self<em>.</em>nodes<em>.</em>keys()) results = {} for node_type in node_types: if node_type == &quot;macos&quot;: results[node_type] = self<em>.</em>query_macos_files(pattern) elif node_type == &quot;ios&quot;: results[node_type] = self<em>.</em>query_ios_files(pattern) elif node_type == &quot;android&quot;: results[node_type] = self<em>.</em>query_android_files(pattern) return results def query_macos_files(self, pattern): &quot;&quot;&quot;查询 macOS 节点文件&quot;&quot;&quot; # 实现 macOS 特定文件查询逻辑 return search_files(&quot;~/&quot;, pattern)

📊 文件查询**实践

查询场景	推荐方法	工具/技能
快速文件查找	文件名模式匹配	`search_by_name` 技能
内容搜索	全文检索	`search_by_content` 技能
最近文件	访问时间排序	`recent_files` 技能
类型分类	扩展名过滤	`search_by_type` 技能
跨设备查询	多节点协调	CrossDeviceFileQuery 类

性能优化建议

# 文件查询缓存机制 import pickle import hashlib class CachedFileSearch: &quot;&quot;&quot;带缓存的文件搜索&quot;&quot;&quot; def __init__(self, cache_file=&quot;file_search_cache<em>.</em>pkl&quot;): self<em>.</em>cache_file = cache_file self<em>.</em>cache = self<em>.</em>load_cache() def load_cache(self): &quot;&quot;&quot;加载缓存&quot;&quot;&quot; try: with open(self<em>.</em>cache_file, &amp;#<em>3</em>9;rb&amp;#<em>3</em>9;) as f: return pickle<em>.</em>load(f) except: return {} def save_cache(self): &quot;&quot;&quot;保存缓存&quot;&quot;&quot; with open(self<em>.</em>cache_file, &amp;#<em>3</em>9;wb&amp;#<em>3</em>9;) as f: pickle<em>.</em>dump(self<em>.</em>cache, f) def search_with_cache(self, directory, pattern): &quot;&quot;&quot;带缓存的搜索&quot;&quot;&quot; cache_key = hashlib<em>.</em>md5(f&quot;{directory}:{pattern}&quot;<em>.</em>encode())<em>.</em>hexdigest() if cache_key in self<em>.</em>cache: return self<em>.</em>cache[cache_key] # 执行实际搜索 results = search_files(directory, pattern) self<em>.</em>cache[cache_key] = results self<em>.</em>save_cache() return results

通过上述方法，您可以在 OpenClaw 中高效地进行本地文件查询，无论是简单的文件查找还是复杂的跨设备内容搜索，都能得到满意的结果。OpenClaw 的文件查询能力是其作为"真正做事情的AI"的重要组成部分 [ref_1]。