mirror of
https://github.com/DrizzleTime/Foxel.git
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feat: Implement AI Agent with enhanced tool processing capabilities (#89)
* feat: Implement AI Agent with tool processing capabilities - Added tools for listing and running processors in the agent. - Created data models for agent chat requests and tool calls. - Developed API integration for agent chat and streaming responses. - Built the AI Agent widget with a user interface for interaction. - Styled the agent components for better user experience. * feat: 增强 AI 助手工具功能，添加文件操作和搜索功能，更新界面显示 * feat: 更新 AI 助手组件 * feat: 更新 AiAgentWidget 组件样式，调整背景和边距以提升界面一致性
This commit is contained in:
时雨
413
domain/agent/tools.py
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413
domain/agent/tools.py
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import json
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from dataclasses import dataclass
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from typing import Any, Awaitable, Callable, Dict, List, Optional
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from domain.processors.service import ProcessorService
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from domain.processors.types import ProcessDirectoryRequest, ProcessRequest
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from domain.virtual_fs.service import VirtualFSService
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from domain.virtual_fs.search.search_service import VirtualFSSearchService
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@dataclass(frozen=True)
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class ToolSpec:
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name: str
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description: str
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parameters: Dict[str, Any]
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requires_confirmation: bool
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handler: Callable[[Dict[str, Any]], Awaitable[Any]]
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async def _processors_list(_: Dict[str, Any]) -> Dict[str, Any]:
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return {"processors": ProcessorService.list_processors()}
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async def _processors_run(args: Dict[str, Any]) -> Dict[str, Any]:
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path = str(args.get("path") or "")
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processor_type = str(args.get("processor_type") or "")
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config = args.get("config")
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if not isinstance(config, dict):
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config = {}
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save_to = args.get("save_to")
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save_to = str(save_to) if isinstance(save_to, str) and save_to.strip() else None
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max_depth = args.get("max_depth")
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max_depth_value: Optional[int] = None
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if max_depth is not None:
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try:
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max_depth_value = int(max_depth)
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except (TypeError, ValueError):
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max_depth_value = None
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suffix = args.get("suffix")
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suffix_value = str(suffix) if isinstance(suffix, str) and suffix.strip() else None
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overwrite_value = args.get("overwrite")
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overwrite = bool(overwrite_value) if overwrite_value is not None else None
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is_dir = await VirtualFSService.path_is_directory(path)
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if is_dir and (max_depth_value is not None or suffix_value is not None):
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req = ProcessDirectoryRequest(
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path=path,
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processor_type=processor_type,
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config=config,
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overwrite=True if overwrite is None else overwrite,
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max_depth=max_depth_value,
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suffix=suffix_value,
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)
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result = await ProcessorService.process_directory(req)
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return {"mode": "directory", **result}
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req = ProcessRequest(
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path=path,
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processor_type=processor_type,
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config=config,
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save_to=save_to,
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overwrite=False if overwrite is None else overwrite,
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)
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result = await ProcessorService.process_file(req)
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return {"mode": "file", **result}
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def _normalize_vfs_path(value: Any) -> str:
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s = str(value or "").strip().replace("\\", "/")
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if not s:
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return ""
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if not s.startswith("/"):
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s = "/" + s
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s = s.rstrip("/") or "/"
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return s
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def _require_vfs_path(value: Any, field: str) -> str:
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path = _normalize_vfs_path(value)
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if not path:
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raise ValueError(f"missing_{field}")
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return path
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async def _vfs_list_dir(args: Dict[str, Any]) -> Dict[str, Any]:
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path = _normalize_vfs_path(args.get("path") or "/") or "/"
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page = int(args.get("page") or 1)
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page_size = int(args.get("page_size") or 50)
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sort_by = str(args.get("sort_by") or "name")
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sort_order = str(args.get("sort_order") or "asc")
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return await VirtualFSService.list_directory(path, page, page_size, sort_by, sort_order)
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async def _vfs_stat(args: Dict[str, Any]) -> Any:
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path = _require_vfs_path(args.get("path"), "path")
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return await VirtualFSService.stat(path)
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async def _vfs_read_text(args: Dict[str, Any]) -> Dict[str, Any]:
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path = _require_vfs_path(args.get("path"), "path")
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encoding = str(args.get("encoding") or "utf-8")
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max_chars = int(args.get("max_chars") or 8000)
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data = await VirtualFSService.read_file(path)
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if isinstance(data, (bytes, bytearray)):
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try:
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text = bytes(data).decode(encoding)
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except UnicodeDecodeError:
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return {"error": "binary_or_invalid_text", "path": path}
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elif isinstance(data, str):
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text = data
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else:
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text = str(data)
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original_len = len(text)
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truncated = original_len > max_chars
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if truncated:
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text = text[:max_chars]
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return {
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"path": path,
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"encoding": encoding,
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"content": text,
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"truncated": truncated,
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"length": original_len,
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}
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async def _vfs_write_text(args: Dict[str, Any]) -> Dict[str, Any]:
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path = _require_vfs_path(args.get("path"), "path")
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if path == "/":
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raise ValueError("invalid_path")
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encoding = str(args.get("encoding") or "utf-8")
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content = str(args.get("content") or "")
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data = content.encode(encoding)
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await VirtualFSService.write_file(path, data)
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return {"written": True, "path": path, "encoding": encoding, "bytes": len(data)}
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async def _vfs_mkdir(args: Dict[str, Any]) -> Dict[str, Any]:
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path = _require_vfs_path(args.get("path"), "path")
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return await VirtualFSService.mkdir(path)
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async def _vfs_delete(args: Dict[str, Any]) -> Dict[str, Any]:
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path = _require_vfs_path(args.get("path"), "path")
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return await VirtualFSService.delete(path)
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async def _vfs_move(args: Dict[str, Any]) -> Dict[str, Any]:
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src = _require_vfs_path(args.get("src"), "src")
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dst = _require_vfs_path(args.get("dst"), "dst")
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if src == "/" or dst == "/":
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raise ValueError("invalid_path")
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overwrite = bool(args.get("overwrite") or False)
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return await VirtualFSService.move(src, dst, overwrite)
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async def _vfs_copy(args: Dict[str, Any]) -> Dict[str, Any]:
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src = _require_vfs_path(args.get("src"), "src")
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dst = _require_vfs_path(args.get("dst"), "dst")
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if src == "/" or dst == "/":
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raise ValueError("invalid_path")
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overwrite = bool(args.get("overwrite") or False)
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return await VirtualFSService.copy(src, dst, overwrite)
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async def _vfs_rename(args: Dict[str, Any]) -> Dict[str, Any]:
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src = _require_vfs_path(args.get("src"), "src")
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dst = _require_vfs_path(args.get("dst"), "dst")
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if src == "/" or dst == "/":
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raise ValueError("invalid_path")
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overwrite = bool(args.get("overwrite") or False)
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return await VirtualFSService.rename(src, dst, overwrite)
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async def _vfs_search(args: Dict[str, Any]) -> Dict[str, Any]:
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q = str(args.get("q") or "").strip()
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if not q:
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raise ValueError("missing_q")
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mode = str(args.get("mode") or "vector")
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top_k = int(args.get("top_k") or 10)
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page = int(args.get("page") or 1)
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page_size = int(args.get("page_size") or 10)
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return await VirtualFSSearchService.search(q, top_k, mode, page, page_size)
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TOOLS: Dict[str, ToolSpec] = {
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"processors_list": ToolSpec(
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name="processors_list",
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description="获取可用处理器列表（type/name/config_schema 等）。",
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parameters={
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"type": "object",
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"properties": {},
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"additionalProperties": False,
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},
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requires_confirmation=False,
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handler=_processors_list,
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),
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"processors_run": ToolSpec(
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name="processors_run",
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description=(
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"运行处理器处理文件或目录。"
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" 对目录可选 max_depth/suffix；对文件可选 overwrite/save_to。"
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" 返回任务 id（去任务队列查看进度）。"
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),
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parameters={
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"type": "object",
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"properties": {
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"path": {"type": "string", "description": "文件或目录路径（绝对路径，如 /foo/bar）"},
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"processor_type": {"type": "string", "description": "处理器类型（例如 image_watermark）"},
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"config": {"type": "object", "description": "处理器配置，按 processors_list 返回的 config_schema 填写"},
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"overwrite": {"type": "boolean", "description": "是否覆盖原文件/目录内文件"},
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"save_to": {"type": "string", "description": "保存到指定路径（仅文件模式，且 overwrite=false 时使用）"},
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"max_depth": {"type": "integer", "description": "目录遍历深度（仅目录模式）"},
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"suffix": {"type": "string", "description": "目录批处理时的输出后缀（仅 produces_file 且 overwrite=false）"},
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},
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"required": ["path", "processor_type"],
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},
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requires_confirmation=True,
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handler=_processors_run,
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),
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"vfs_list_dir": ToolSpec(
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name="vfs_list_dir",
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description="浏览目录（列出 entries + pagination）。",
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parameters={
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"type": "object",
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"properties": {
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"path": {"type": "string", "description": "目录路径（绝对路径，如 /foo/bar）"},
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"page": {"type": "integer", "description": "页码（从 1 开始）"},
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"page_size": {"type": "integer", "description": "每页条数"},
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"sort_by": {"type": "string", "description": "排序字段：name/size/mtime"},
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"sort_order": {"type": "string", "description": "排序顺序：asc/desc"},
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},
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"required": ["path"],
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"additionalProperties": False,
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},
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requires_confirmation=False,
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handler=_vfs_list_dir,
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),
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"vfs_stat": ToolSpec(
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name="vfs_stat",
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description="查看文件/目录信息（size/mtime/is_dir/has_thumbnail/vector_index 等）。",
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parameters={
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"type": "object",
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"properties": {
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"path": {"type": "string", "description": "路径（绝对路径，如 /foo/bar.txt）"},
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},
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"required": ["path"],
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"additionalProperties": False,
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},
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requires_confirmation=False,
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handler=_vfs_stat,
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),
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"vfs_read_text": ToolSpec(
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name="vfs_read_text",
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description="读取文本文件内容（解码失败视为二进制，返回 error）。",
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parameters={
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"type": "object",
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"properties": {
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"path": {"type": "string", "description": "文件路径（绝对路径，如 /foo/bar.md）"},
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"encoding": {"type": "string", "description": "文本编码（默认 utf-8）"},
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"max_chars": {"type": "integer", "description": "最多返回的字符数（默认 8000）"},
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},
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"required": ["path"],
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"additionalProperties": False,
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},
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requires_confirmation=False,
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handler=_vfs_read_text,
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),
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"vfs_write_text": ToolSpec(
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name="vfs_write_text",
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description="写入文本文件内容（会覆盖目标文件）。",
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parameters={
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"type": "object",
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"properties": {
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"path": {"type": "string", "description": "文件路径（绝对路径，如 /foo/bar.md）"},
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"content": {"type": "string", "description": "要写入的文本内容"},
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"encoding": {"type": "string", "description": "文本编码（默认 utf-8）"},
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},
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"required": ["path", "content"],
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"additionalProperties": False,
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},
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requires_confirmation=True,
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handler=_vfs_write_text,
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),
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"vfs_mkdir": ToolSpec(
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name="vfs_mkdir",
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description="创建目录。",
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parameters={
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"type": "object",
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"properties": {
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"path": {"type": "string", "description": "目录路径（绝对路径，如 /foo/bar）"},
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},
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"required": ["path"],
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"additionalProperties": False,
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},
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requires_confirmation=True,
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handler=_vfs_mkdir,
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),
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"vfs_delete": ToolSpec(
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name="vfs_delete",
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description="删除文件或目录（由底层适配器决定是否递归）。",
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parameters={
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"type": "object",
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"properties": {
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"path": {"type": "string", "description": "路径（绝对路径，如 /foo/bar 或 /foo/bar.txt）"},
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},
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"required": ["path"],
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"additionalProperties": False,
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},
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requires_confirmation=True,
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handler=_vfs_delete,
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),
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"vfs_move": ToolSpec(
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name="vfs_move",
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description="移动路径（可能进入任务队列）。",
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parameters={
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"type": "object",
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"properties": {
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"src": {"type": "string", "description": "源路径（绝对路径）"},
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"dst": {"type": "string", "description": "目标路径（绝对路径）"},
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"overwrite": {"type": "boolean", "description": "是否允许覆盖已存在目标（默认 false）"},
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},
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"required": ["src", "dst"],
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"additionalProperties": False,
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},
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requires_confirmation=True,
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handler=_vfs_move,
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),
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"vfs_copy": ToolSpec(
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name="vfs_copy",
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description="复制路径（可能进入任务队列）。",
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parameters={
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"type": "object",
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"properties": {
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"src": {"type": "string", "description": "源路径（绝对路径）"},
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"dst": {"type": "string", "description": "目标路径（绝对路径）"},
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"overwrite": {"type": "boolean", "description": "是否覆盖已存在目标（默认 false）"},
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},
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"required": ["src", "dst"],
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"additionalProperties": False,
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},
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requires_confirmation=True,
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handler=_vfs_copy,
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),
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"vfs_rename": ToolSpec(
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name="vfs_rename",
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description="重命名路径（本质是同目录 move）。",
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parameters={
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"type": "object",
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"properties": {
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"src": {"type": "string", "description": "源路径（绝对路径）"},
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"dst": {"type": "string", "description": "目标路径（绝对路径）"},
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"overwrite": {"type": "boolean", "description": "是否允许覆盖已存在目标（默认 false）"},
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},
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"required": ["src", "dst"],
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"additionalProperties": False,
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},
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requires_confirmation=True,
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handler=_vfs_rename,
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),
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"vfs_search": ToolSpec(
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name="vfs_search",
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description="搜索文件（mode=vector 或 filename）。",
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parameters={
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"type": "object",
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"properties": {
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"q": {"type": "string", "description": "搜索关键词"},
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"mode": {"type": "string", "description": "搜索模式：vector/filename（默认 vector）"},
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"top_k": {"type": "integer", "description": "返回数量（vector 模式使用，默认 10）"},
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"page": {"type": "integer", "description": "页码（filename 模式使用，默认 1）"},
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"page_size": {"type": "integer", "description": "分页大小（filename 模式使用，默认 10）"},
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},
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"required": ["q"],
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"additionalProperties": False,
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},
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requires_confirmation=False,
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handler=_vfs_search,
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),
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}
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def get_tool(name: str) -> Optional[ToolSpec]:
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return TOOLS.get(name)
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def openai_tools() -> List[Dict[str, Any]]:
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out: List[Dict[str, Any]] = []
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for spec in TOOLS.values():
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out.append({
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"type": "function",
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"function": {
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"name": spec.name,
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"description": spec.description,
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"parameters": spec.parameters,
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},
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})
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return out
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def tool_result_to_content(result: Any) -> str:
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if result is None:
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return ""
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if isinstance(result, str):
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return result
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try:
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return json.dumps(result, ensure_ascii=False)
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except TypeError:
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return json.dumps({"result": str(result)}, ensure_ascii=False)
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