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

api/routers.py

@@ -11,6 +11,7 @@ from domain.processors import api as processors
 from domain.share import api as share
 from domain.tasks import api as tasks
 from domain.ai import api as ai
+from domain.agent import api as agent
 from domain.virtual_fs import api as virtual_fs
 from domain.virtual_fs.mapping import s3_api, webdav_api
 from domain.virtual_fs.search import search_api
@@ -30,6 +31,7 @@ def include_routers(app: FastAPI):
     app.include_router(backup.router)
     app.include_router(ai.router_vector_db)
     app.include_router(ai.router_ai)
+    app.include_router(agent.router)
     app.include_router(plugins.router)
     app.include_router(webdav_api.router)
     app.include_router(s3_api.router)

domain/agent/__init__.py

@@ -0,0 +1,4 @@
+from .api import router
+
+__all__ = ["router"]
+

domain/agent/api.py

@@ -0,0 +1,39 @@
+from typing import Annotated
+
+from fastapi import APIRouter, Depends, Request
+from fastapi.responses import StreamingResponse
+
+from api.response import success
+from domain.agent.service import AgentService
+from domain.agent.types import AgentChatRequest
+from domain.audit import AuditAction, audit
+from domain.auth.service import get_current_active_user
+from domain.auth.types import User
+
+
+router = APIRouter(prefix="/api/agent", tags=["agent"])
+
+
+@router.post("/chat")
+@audit(action=AuditAction.CREATE, description="Agent 对话", body_fields=["auto_execute"])
+async def chat(
+    request: Request,
+    payload: AgentChatRequest,
+    current_user: Annotated[User, Depends(get_current_active_user)],
+):
+    data = await AgentService.chat(payload, current_user)
+    return success(data)
+
+
+@router.post("/chat/stream")
+@audit(action=AuditAction.CREATE, description="Agent 对话（SSE）", body_fields=["auto_execute"])
+async def chat_stream(
+    request: Request,
+    payload: AgentChatRequest,
+    current_user: Annotated[User, Depends(get_current_active_user)],
+):
+    return StreamingResponse(
+        AgentService.chat_stream(payload, current_user),
+        media_type="text/event-stream",
+        headers={"Cache-Control": "no-cache"},
+    )

domain/agent/service.py

@@ -0,0 +1,448 @@
+import asyncio
+import json
+import uuid
+from typing import Any, Dict, List, Optional, Tuple
+
+import httpx
+from fastapi import HTTPException
+
+from domain.agent.tools import get_tool, openai_tools, tool_result_to_content
+from domain.agent.types import AgentChatRequest, PendingToolCall
+from domain.ai.inference import MissingModelError, chat_completion, chat_completion_stream
+from domain.ai.service import AIProviderService
+from domain.auth.types import User
+
+
+def _normalize_path(p: Optional[str]) -> Optional[str]:
+    if not p:
+        return None
+    s = str(p).strip()
+    if not s:
+        return None
+    s = s.replace("\\", "/")
+    if not s.startswith("/"):
+        s = "/" + s
+    s = s.rstrip("/") or "/"
+    return s
+
+
+def _build_system_prompt(current_path: Optional[str]) -> str:
+    lines = [
+        "你是 Foxel 的 AI 助手。",
+        "你可以通过工具对文件/目录进行查询、读写、移动、复制、删除，以及运行处理器（processor）。",
+        "",
+        "可用工具：",
+        "- vfs_list_dir：浏览目录（列出 entries + pagination）。",
+        "- vfs_stat：查看文件/目录信息。",
+        "- vfs_read_text：读取文本文件内容（不支持二进制）。",
+        "- vfs_search：搜索文件（vector/filename）。",
+        "- vfs_write_text：写入文本文件内容（覆盖）。",
+        "- vfs_mkdir：创建目录。",
+        "- vfs_delete：删除文件或目录。",
+        "- vfs_move：移动路径。",
+        "- vfs_copy：复制路径。",
+        "- vfs_rename：重命名路径。",
+        "- processors_list：获取可用处理器列表（含 type/name/config_schema/produces_file/supports_directory）。",
+        "- processors_run：运行处理器处理文件或目录（会返回 task_id 或 task_ids）。",
+        "",
+        "规则：",
+        "1) 读操作（vfs_list_dir/vfs_stat/vfs_read_text/vfs_search）可直接调用工具。",
+        "2) 写/改/删操作（vfs_write_text/vfs_mkdir/vfs_delete/vfs_move/vfs_copy/vfs_rename/processors_run）默认需要用户确认；只有在开启自动执行时才应直接执行。",
+        "3) 用户未给出明确路径时先追问；若提供了“当前文件管理目录”，可以基于它把相对描述补全为绝对路径（以 / 开头）。",
+        "4) 修改文件内容：先读取（vfs_read_text）→给出改动点→确认后再写入（vfs_write_text）。",
+        "5) processors_run 返回任务 id 后，说明任务已提交，可在任务队列查看进度。",
+        "6) 回答保持简洁中文。",
+    ]
+    if current_path:
+        lines.append("")
+        lines.append(f"当前文件管理目录：{current_path}")
+    return "\n".join(lines)
+
+
+def _ensure_tool_call_ids(message: Dict[str, Any]) -> Dict[str, Any]:
+    tool_calls = message.get("tool_calls")
+    if not isinstance(tool_calls, list):
+        return message
+
+    changed = False
+    for idx, call in enumerate(tool_calls):
+        if not isinstance(call, dict):
+            continue
+        call_id = call.get("id")
+        if isinstance(call_id, str) and call_id.strip():
+            continue
+        call["id"] = f"call_{idx}"
+        changed = True
+
+    if changed:
+        message["tool_calls"] = tool_calls
+    return message
+
+
+def _extract_pending(tool_call: Dict[str, Any], requires_confirmation: bool) -> PendingToolCall:
+    call_id = str(tool_call.get("id") or "")
+    fn = tool_call.get("function") or {}
+    name = str((fn.get("name") if isinstance(fn, dict) else None) or "")
+    raw_args = fn.get("arguments") if isinstance(fn, dict) else None
+    arguments: Dict[str, Any] = {}
+    if isinstance(raw_args, str) and raw_args.strip():
+        try:
+            parsed = json.loads(raw_args)
+            if isinstance(parsed, dict):
+                arguments = parsed
+        except json.JSONDecodeError:
+            arguments = {}
+    return PendingToolCall(
+        id=call_id,
+        name=name,
+        arguments=arguments,
+        requires_confirmation=requires_confirmation,
+    )
+
+
+def _find_last_assistant_tool_calls(messages: List[Dict[str, Any]]) -> Tuple[int, Dict[str, Any]]:
+    for idx in range(len(messages) - 1, -1, -1):
+        msg = messages[idx]
+        if not isinstance(msg, dict):
+            continue
+        if msg.get("role") != "assistant":
+            continue
+        tool_calls = msg.get("tool_calls")
+        if isinstance(tool_calls, list) and tool_calls:
+            return idx, msg
+    raise HTTPException(status_code=400, detail="没有可确认的待执行操作")
+
+
+def _existing_tool_result_ids(messages: List[Dict[str, Any]]) -> set[str]:
+    ids: set[str] = set()
+    for msg in messages:
+        if not isinstance(msg, dict):
+            continue
+        if msg.get("role") != "tool":
+            continue
+        tool_call_id = msg.get("tool_call_id")
+        if isinstance(tool_call_id, str) and tool_call_id.strip():
+            ids.add(tool_call_id)
+    return ids
+
+
+async def _choose_chat_ability() -> str:
+    tools_model = await AIProviderService.get_default_model("tools")
+    return "tools" if tools_model else "chat"
+
+
+def _sse(event: str, data: Any) -> bytes:
+    payload = json.dumps(data, ensure_ascii=False, separators=(",", ":"))
+    return f"event: {event}\ndata: {payload}\n\n".encode("utf-8")
+
+
+class AgentService:
+    @classmethod
+    async def chat(cls, req: AgentChatRequest, user: Optional[User]) -> Dict[str, Any]:
+        history: List[Dict[str, Any]] = list(req.messages or [])
+        current_path = _normalize_path(req.context.current_path if req.context else None)
+
+        system_prompt = _build_system_prompt(current_path)
+        internal_messages: List[Dict[str, Any]] = [{"role": "system", "content": system_prompt}] + history
+
+        new_messages: List[Dict[str, Any]] = []
+        pending: List[PendingToolCall] = []
+
+        approved_ids = {i for i in (req.approved_tool_call_ids or []) if isinstance(i, str) and i.strip()}
+        rejected_ids = {i for i in (req.rejected_tool_call_ids or []) if isinstance(i, str) and i.strip()}
+
+        if approved_ids or rejected_ids:
+            _, last_call_msg = _find_last_assistant_tool_calls(internal_messages)
+            last_call_msg = _ensure_tool_call_ids(last_call_msg)
+            tool_calls = last_call_msg.get("tool_calls") or []
+            call_map: Dict[str, Dict[str, Any]] = {
+                str(c.get("id")): c
+                for c in tool_calls
+                if isinstance(c, dict) and isinstance(c.get("id"), str)
+            }
+
+            existing_ids = _existing_tool_result_ids(internal_messages)
+            for call_id in approved_ids | rejected_ids:
+                if call_id in existing_ids:
+                    continue
+                tool_call = call_map.get(call_id)
+                if not tool_call:
+                    continue
+                fn = tool_call.get("function") or {}
+                name = fn.get("name") if isinstance(fn, dict) else None
+                args_raw = fn.get("arguments") if isinstance(fn, dict) else None
+                args: Dict[str, Any] = {}
+                if isinstance(args_raw, str) and args_raw.strip():
+                    try:
+                        parsed = json.loads(args_raw)
+                        if isinstance(parsed, dict):
+                            args = parsed
+                    except json.JSONDecodeError:
+                        args = {}
+
+                spec = get_tool(str(name or ""))
+                if call_id in rejected_ids:
+                    content = tool_result_to_content({"canceled": True, "reason": "user_rejected"})
+                    tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
+                    internal_messages.append(tool_msg)
+                    new_messages.append(tool_msg)
+                    continue
+
+                if not spec:
+                    content = tool_result_to_content({"error": f"unknown_tool: {name}"})
+                    tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
+                    internal_messages.append(tool_msg)
+                    new_messages.append(tool_msg)
+                    continue
+
+                try:
+                    result = await spec.handler(args)
+                    content = tool_result_to_content(result)
+                except Exception as exc:  # noqa: BLE001
+                    content = tool_result_to_content({"error": str(exc)})
+                tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
+                internal_messages.append(tool_msg)
+                new_messages.append(tool_msg)
+
+        tools_schema = openai_tools()
+        ability = await _choose_chat_ability()
+        max_loops = 4
+
+        for _ in range(max_loops):
+            try:
+                assistant = await chat_completion(
+                    internal_messages,
+                    ability=ability,
+                    tools=tools_schema,
+                    tool_choice="auto",
+                    timeout=60.0,
+                )
+            except MissingModelError as exc:
+                raise HTTPException(status_code=400, detail=str(exc)) from exc
+            except httpx.HTTPStatusError as exc:
+                raise HTTPException(status_code=502, detail=f"对话请求失败: {exc}") from exc
+            except httpx.RequestError as exc:
+                raise HTTPException(status_code=502, detail=f"对话请求异常: {exc}") from exc
+
+            assistant = _ensure_tool_call_ids(assistant)
+            internal_messages.append(assistant)
+            new_messages.append(assistant)
+
+            tool_calls = assistant.get("tool_calls")
+            if not isinstance(tool_calls, list) or not tool_calls:
+                break
+
+            pending = []
+            for call in tool_calls:
+                if not isinstance(call, dict):
+                    continue
+                call_id = str(call.get("id") or "")
+                fn = call.get("function") or {}
+                name = fn.get("name") if isinstance(fn, dict) else None
+                args_raw = fn.get("arguments") if isinstance(fn, dict) else None
+                args: Dict[str, Any] = {}
+                if isinstance(args_raw, str) and args_raw.strip():
+                    try:
+                        parsed = json.loads(args_raw)
+                        if isinstance(parsed, dict):
+                            args = parsed
+                    except json.JSONDecodeError:
+                        args = {}
+
+                spec = get_tool(str(name or ""))
+                if not spec:
+                    content = tool_result_to_content({"error": f"unknown_tool: {name}"})
+                    tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
+                    internal_messages.append(tool_msg)
+                    new_messages.append(tool_msg)
+                    continue
+
+                if spec.requires_confirmation and not req.auto_execute:
+                    pending.append(_extract_pending(call, True))
+                    continue
+
+                try:
+                    result = await spec.handler(args)
+                    content = tool_result_to_content(result)
+                except Exception as exc:  # noqa: BLE001
+                    content = tool_result_to_content({"error": str(exc)})
+                tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
+                internal_messages.append(tool_msg)
+                new_messages.append(tool_msg)
+
+            if pending:
+                break
+
+        payload: Dict[str, Any] = {"messages": new_messages}
+        if pending:
+            payload["pending_tool_calls"] = [p.model_dump() for p in pending]
+        return payload
+
+    @classmethod
+    async def chat_stream(cls, req: AgentChatRequest, user: Optional[User]):
+        history: List[Dict[str, Any]] = list(req.messages or [])
+        current_path = _normalize_path(req.context.current_path if req.context else None)
+
+        system_prompt = _build_system_prompt(current_path)
+        internal_messages: List[Dict[str, Any]] = [{"role": "system", "content": system_prompt}] + history
+
+        new_messages: List[Dict[str, Any]] = []
+        pending: List[PendingToolCall] = []
+
+        approved_ids = {i for i in (req.approved_tool_call_ids or []) if isinstance(i, str) and i.strip()}
+        rejected_ids = {i for i in (req.rejected_tool_call_ids or []) if isinstance(i, str) and i.strip()}
+
+        try:
+            if approved_ids or rejected_ids:
+                _, last_call_msg = _find_last_assistant_tool_calls(internal_messages)
+                last_call_msg = _ensure_tool_call_ids(last_call_msg)
+                tool_calls = last_call_msg.get("tool_calls") or []
+                call_map: Dict[str, Dict[str, Any]] = {
+                    str(c.get("id")): c
+                    for c in tool_calls
+                    if isinstance(c, dict) and isinstance(c.get("id"), str)
+                }
+
+                existing_ids = _existing_tool_result_ids(internal_messages)
+                for call_id in approved_ids | rejected_ids:
+                    if call_id in existing_ids:
+                        continue
+                    tool_call = call_map.get(call_id)
+                    if not tool_call:
+                        continue
+                    fn = tool_call.get("function") or {}
+                    name = fn.get("name") if isinstance(fn, dict) else None
+                    args_raw = fn.get("arguments") if isinstance(fn, dict) else None
+                    args: Dict[str, Any] = {}
+                    if isinstance(args_raw, str) and args_raw.strip():
+                        try:
+                            parsed = json.loads(args_raw)
+                            if isinstance(parsed, dict):
+                                args = parsed
+                        except json.JSONDecodeError:
+                            args = {}
+
+                    spec = get_tool(str(name or ""))
+                    if call_id in rejected_ids:
+                        content = tool_result_to_content({"canceled": True, "reason": "user_rejected"})
+                        tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
+                        internal_messages.append(tool_msg)
+                        new_messages.append(tool_msg)
+                        yield _sse("tool_end", {"tool_call_id": call_id, "name": str(name or ""), "message": tool_msg})
+                        continue
+
+                    if not spec:
+                        content = tool_result_to_content({"error": f"unknown_tool: {name}"})
+                        tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
+                        internal_messages.append(tool_msg)
+                        new_messages.append(tool_msg)
+                        yield _sse("tool_end", {"tool_call_id": call_id, "name": str(name or ""), "message": tool_msg})
+                        continue
+
+                    yield _sse("tool_start", {"tool_call_id": call_id, "name": spec.name})
+                    try:
+                        result = await spec.handler(args)
+                        content = tool_result_to_content(result)
+                    except Exception as exc:  # noqa: BLE001
+                        content = tool_result_to_content({"error": str(exc)})
+                    tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
+                    internal_messages.append(tool_msg)
+                    new_messages.append(tool_msg)
+                    yield _sse("tool_end", {"tool_call_id": call_id, "name": spec.name, "message": tool_msg})
+
+            tools_schema = openai_tools()
+            ability = await _choose_chat_ability()
+            max_loops = 4
+
+            for _ in range(max_loops):
+                assistant_event_id = uuid.uuid4().hex
+                yield _sse("assistant_start", {"id": assistant_event_id})
+
+                assistant_message: Dict[str, Any] | None = None
+                try:
+                    async for event in chat_completion_stream(
+                        internal_messages,
+                        ability=ability,
+                        tools=tools_schema,
+                        tool_choice="auto",
+                        timeout=60.0,
+                    ):
+                        if event.get("type") == "delta":
+                            delta = event.get("delta")
+                            if isinstance(delta, str) and delta:
+                                yield _sse("assistant_delta", {"id": assistant_event_id, "delta": delta})
+                        elif event.get("type") == "message":
+                            msg = event.get("message")
+                            if isinstance(msg, dict):
+                                assistant_message = msg
+                except MissingModelError as exc:
+                    raise HTTPException(status_code=400, detail=str(exc)) from exc
+                except httpx.HTTPStatusError as exc:
+                    raise HTTPException(status_code=502, detail=f"对话请求失败: {exc}") from exc
+                except httpx.RequestError as exc:
+                    raise HTTPException(status_code=502, detail=f"对话请求异常: {exc}") from exc
+
+                if not assistant_message:
+                    assistant_message = {"role": "assistant", "content": ""}
+
+                assistant_message = _ensure_tool_call_ids(assistant_message)
+                internal_messages.append(assistant_message)
+                new_messages.append(assistant_message)
+                yield _sse("assistant_end", {"id": assistant_event_id, "message": assistant_message})
+
+                tool_calls = assistant_message.get("tool_calls")
+                if not isinstance(tool_calls, list) or not tool_calls:
+                    break
+
+                pending = []
+                for call in tool_calls:
+                    if not isinstance(call, dict):
+                        continue
+                    call_id = str(call.get("id") or "")
+                    fn = call.get("function") or {}
+                    name = fn.get("name") if isinstance(fn, dict) else None
+                    args_raw = fn.get("arguments") if isinstance(fn, dict) else None
+                    args: Dict[str, Any] = {}
+                    if isinstance(args_raw, str) and args_raw.strip():
+                        try:
+                            parsed = json.loads(args_raw)
+                            if isinstance(parsed, dict):
+                                args = parsed
+                        except json.JSONDecodeError:
+                            args = {}
+
+                    spec = get_tool(str(name or ""))
+                    if not spec:
+                        content = tool_result_to_content({"error": f"unknown_tool: {name}"})
+                        tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
+                        internal_messages.append(tool_msg)
+                        new_messages.append(tool_msg)
+                        yield _sse("tool_end", {"tool_call_id": call_id, "name": str(name or ""), "message": tool_msg})
+                        continue
+
+                    if spec.requires_confirmation and not req.auto_execute:
+                        pending.append(_extract_pending(call, True))
+                        continue
+
+                    yield _sse("tool_start", {"tool_call_id": call_id, "name": spec.name})
+                    try:
+                        result = await spec.handler(args)
+                        content = tool_result_to_content(result)
+                    except Exception as exc:  # noqa: BLE001
+                        content = tool_result_to_content({"error": str(exc)})
+                    tool_msg = {"role": "tool", "tool_call_id": call_id, "content": content}
+                    internal_messages.append(tool_msg)
+                    new_messages.append(tool_msg)
+                    yield _sse("tool_end", {"tool_call_id": call_id, "name": spec.name, "message": tool_msg})
+
+                if pending:
+                    yield _sse("pending", {"pending_tool_calls": [p.model_dump() for p in pending]})
+                    break
+
+            payload: Dict[str, Any] = {"messages": new_messages}
+            if pending:
+                payload["pending_tool_calls"] = [p.model_dump() for p in pending]
+            yield _sse("done", payload)
+
+        except asyncio.CancelledError:
+            return

domain/agent/tools.py

@@ -0,0 +1,413 @@
+import json
+from dataclasses import dataclass
+from typing import Any, Awaitable, Callable, Dict, List, Optional
+
+from domain.processors.service import ProcessorService
+from domain.processors.types import ProcessDirectoryRequest, ProcessRequest
+from domain.virtual_fs.service import VirtualFSService
+from domain.virtual_fs.search.search_service import VirtualFSSearchService
+
+
+@dataclass(frozen=True)
+class ToolSpec:
+    name: str
+    description: str
+    parameters: Dict[str, Any]
+    requires_confirmation: bool
+    handler: Callable[[Dict[str, Any]], Awaitable[Any]]
+
+
+async def _processors_list(_: Dict[str, Any]) -> Dict[str, Any]:
+    return {"processors": ProcessorService.list_processors()}
+
+
+async def _processors_run(args: Dict[str, Any]) -> Dict[str, Any]:
+    path = str(args.get("path") or "")
+    processor_type = str(args.get("processor_type") or "")
+    config = args.get("config")
+    if not isinstance(config, dict):
+        config = {}
+
+    save_to = args.get("save_to")
+    save_to = str(save_to) if isinstance(save_to, str) and save_to.strip() else None
+
+    max_depth = args.get("max_depth")
+    max_depth_value: Optional[int] = None
+    if max_depth is not None:
+        try:
+            max_depth_value = int(max_depth)
+        except (TypeError, ValueError):
+            max_depth_value = None
+
+    suffix = args.get("suffix")
+    suffix_value = str(suffix) if isinstance(suffix, str) and suffix.strip() else None
+
+    overwrite_value = args.get("overwrite")
+    overwrite = bool(overwrite_value) if overwrite_value is not None else None
+
+    is_dir = await VirtualFSService.path_is_directory(path)
+    if is_dir and (max_depth_value is not None or suffix_value is not None):
+        req = ProcessDirectoryRequest(
+            path=path,
+            processor_type=processor_type,
+            config=config,
+            overwrite=True if overwrite is None else overwrite,
+            max_depth=max_depth_value,
+            suffix=suffix_value,
+        )
+        result = await ProcessorService.process_directory(req)
+        return {"mode": "directory", **result}
+
+    req = ProcessRequest(
+        path=path,
+        processor_type=processor_type,
+        config=config,
+        save_to=save_to,
+        overwrite=False if overwrite is None else overwrite,
+    )
+    result = await ProcessorService.process_file(req)
+    return {"mode": "file", **result}
+
+
+def _normalize_vfs_path(value: Any) -> str:
+    s = str(value or "").strip().replace("\\", "/")
+    if not s:
+        return ""
+    if not s.startswith("/"):
+        s = "/" + s
+    s = s.rstrip("/") or "/"
+    return s
+
+
+def _require_vfs_path(value: Any, field: str) -> str:
+    path = _normalize_vfs_path(value)
+    if not path:
+        raise ValueError(f"missing_{field}")
+    return path
+
+
+async def _vfs_list_dir(args: Dict[str, Any]) -> Dict[str, Any]:
+    path = _normalize_vfs_path(args.get("path") or "/") or "/"
+    page = int(args.get("page") or 1)
+    page_size = int(args.get("page_size") or 50)
+    sort_by = str(args.get("sort_by") or "name")
+    sort_order = str(args.get("sort_order") or "asc")
+    return await VirtualFSService.list_directory(path, page, page_size, sort_by, sort_order)
+
+
+async def _vfs_stat(args: Dict[str, Any]) -> Any:
+    path = _require_vfs_path(args.get("path"), "path")
+    return await VirtualFSService.stat(path)
+
+
+async def _vfs_read_text(args: Dict[str, Any]) -> Dict[str, Any]:
+    path = _require_vfs_path(args.get("path"), "path")
+    encoding = str(args.get("encoding") or "utf-8")
+    max_chars = int(args.get("max_chars") or 8000)
+
+    data = await VirtualFSService.read_file(path)
+    if isinstance(data, (bytes, bytearray)):
+        try:
+            text = bytes(data).decode(encoding)
+        except UnicodeDecodeError:
+            return {"error": "binary_or_invalid_text", "path": path}
+    elif isinstance(data, str):
+        text = data
+    else:
+        text = str(data)
+
+    original_len = len(text)
+    truncated = original_len > max_chars
+    if truncated:
+        text = text[:max_chars]
+    return {
+        "path": path,
+        "encoding": encoding,
+        "content": text,
+        "truncated": truncated,
+        "length": original_len,
+    }
+
+
+async def _vfs_write_text(args: Dict[str, Any]) -> Dict[str, Any]:
+    path = _require_vfs_path(args.get("path"), "path")
+    if path == "/":
+        raise ValueError("invalid_path")
+    encoding = str(args.get("encoding") or "utf-8")
+    content = str(args.get("content") or "")
+    data = content.encode(encoding)
+    await VirtualFSService.write_file(path, data)
+    return {"written": True, "path": path, "encoding": encoding, "bytes": len(data)}
+
+
+async def _vfs_mkdir(args: Dict[str, Any]) -> Dict[str, Any]:
+    path = _require_vfs_path(args.get("path"), "path")
+    return await VirtualFSService.mkdir(path)
+
+
+async def _vfs_delete(args: Dict[str, Any]) -> Dict[str, Any]:
+    path = _require_vfs_path(args.get("path"), "path")
+    return await VirtualFSService.delete(path)
+
+
+async def _vfs_move(args: Dict[str, Any]) -> Dict[str, Any]:
+    src = _require_vfs_path(args.get("src"), "src")
+    dst = _require_vfs_path(args.get("dst"), "dst")
+    if src == "/" or dst == "/":
+        raise ValueError("invalid_path")
+    overwrite = bool(args.get("overwrite") or False)
+    return await VirtualFSService.move(src, dst, overwrite)
+
+
+async def _vfs_copy(args: Dict[str, Any]) -> Dict[str, Any]:
+    src = _require_vfs_path(args.get("src"), "src")
+    dst = _require_vfs_path(args.get("dst"), "dst")
+    if src == "/" or dst == "/":
+        raise ValueError("invalid_path")
+    overwrite = bool(args.get("overwrite") or False)
+    return await VirtualFSService.copy(src, dst, overwrite)
+
+
+async def _vfs_rename(args: Dict[str, Any]) -> Dict[str, Any]:
+    src = _require_vfs_path(args.get("src"), "src")
+    dst = _require_vfs_path(args.get("dst"), "dst")
+    if src == "/" or dst == "/":
+        raise ValueError("invalid_path")
+    overwrite = bool(args.get("overwrite") or False)
+    return await VirtualFSService.rename(src, dst, overwrite)
+
+
+async def _vfs_search(args: Dict[str, Any]) -> Dict[str, Any]:
+    q = str(args.get("q") or "").strip()
+    if not q:
+        raise ValueError("missing_q")
+    mode = str(args.get("mode") or "vector")
+    top_k = int(args.get("top_k") or 10)
+    page = int(args.get("page") or 1)
+    page_size = int(args.get("page_size") or 10)
+    return await VirtualFSSearchService.search(q, top_k, mode, page, page_size)
+
+
+TOOLS: Dict[str, ToolSpec] = {
+    "processors_list": ToolSpec(
+        name="processors_list",
+        description="获取可用处理器列表（type/name/config_schema 等）。",
+        parameters={
+            "type": "object",
+            "properties": {},
+            "additionalProperties": False,
+        },
+        requires_confirmation=False,
+        handler=_processors_list,
+    ),
+    "processors_run": ToolSpec(
+        name="processors_run",
+        description=(
+            "运行处理器处理文件或目录。"
+            " 对目录可选 max_depth/suffix；对文件可选 overwrite/save_to。"
+            " 返回任务 id（去任务队列查看进度）。"
+        ),
+        parameters={
+            "type": "object",
+            "properties": {
+                "path": {"type": "string", "description": "文件或目录路径（绝对路径，如 /foo/bar）"},
+                "processor_type": {"type": "string", "description": "处理器类型（例如 image_watermark）"},
+                "config": {"type": "object", "description": "处理器配置，按 processors_list 返回的 config_schema 填写"},
+                "overwrite": {"type": "boolean", "description": "是否覆盖原文件/目录内文件"},
+                "save_to": {"type": "string", "description": "保存到指定路径（仅文件模式，且 overwrite=false 时使用）"},
+                "max_depth": {"type": "integer", "description": "目录遍历深度（仅目录模式）"},
+                "suffix": {"type": "string", "description": "目录批处理时的输出后缀（仅 produces_file 且 overwrite=false）"},
+            },
+            "required": ["path", "processor_type"],
+        },
+        requires_confirmation=True,
+        handler=_processors_run,
+    ),
+    "vfs_list_dir": ToolSpec(
+        name="vfs_list_dir",
+        description="浏览目录（列出 entries + pagination）。",
+        parameters={
+            "type": "object",
+            "properties": {
+                "path": {"type": "string", "description": "目录路径（绝对路径，如 /foo/bar）"},
+                "page": {"type": "integer", "description": "页码（从 1 开始）"},
+                "page_size": {"type": "integer", "description": "每页条数"},
+                "sort_by": {"type": "string", "description": "排序字段：name/size/mtime"},
+                "sort_order": {"type": "string", "description": "排序顺序：asc/desc"},
+            },
+            "required": ["path"],
+            "additionalProperties": False,
+        },
+        requires_confirmation=False,
+        handler=_vfs_list_dir,
+    ),
+    "vfs_stat": ToolSpec(
+        name="vfs_stat",
+        description="查看文件/目录信息（size/mtime/is_dir/has_thumbnail/vector_index 等）。",
+        parameters={
+            "type": "object",
+            "properties": {
+                "path": {"type": "string", "description": "路径（绝对路径，如 /foo/bar.txt）"},
+            },
+            "required": ["path"],
+            "additionalProperties": False,
+        },
+        requires_confirmation=False,
+        handler=_vfs_stat,
+    ),
+    "vfs_read_text": ToolSpec(
+        name="vfs_read_text",
+        description="读取文本文件内容（解码失败视为二进制，返回 error）。",
+        parameters={
+            "type": "object",
+            "properties": {
+                "path": {"type": "string", "description": "文件路径（绝对路径，如 /foo/bar.md）"},
+                "encoding": {"type": "string", "description": "文本编码（默认 utf-8）"},
+                "max_chars": {"type": "integer", "description": "最多返回的字符数（默认 8000）"},
+            },
+            "required": ["path"],
+            "additionalProperties": False,
+        },
+        requires_confirmation=False,
+        handler=_vfs_read_text,
+    ),
+    "vfs_write_text": ToolSpec(
+        name="vfs_write_text",
+        description="写入文本文件内容（会覆盖目标文件）。",
+        parameters={
+            "type": "object",
+            "properties": {
+                "path": {"type": "string", "description": "文件路径（绝对路径，如 /foo/bar.md）"},
+                "content": {"type": "string", "description": "要写入的文本内容"},
+                "encoding": {"type": "string", "description": "文本编码（默认 utf-8）"},
+            },
+            "required": ["path", "content"],
+            "additionalProperties": False,
+        },
+        requires_confirmation=True,
+        handler=_vfs_write_text,
+    ),
+    "vfs_mkdir": ToolSpec(
+        name="vfs_mkdir",
+        description="创建目录。",
+        parameters={
+            "type": "object",
+            "properties": {
+                "path": {"type": "string", "description": "目录路径（绝对路径，如 /foo/bar）"},
+            },
+            "required": ["path"],
+            "additionalProperties": False,
+        },
+        requires_confirmation=True,
+        handler=_vfs_mkdir,
+    ),
+    "vfs_delete": ToolSpec(
+        name="vfs_delete",
+        description="删除文件或目录（由底层适配器决定是否递归）。",
+        parameters={
+            "type": "object",
+            "properties": {
+                "path": {"type": "string", "description": "路径（绝对路径，如 /foo/bar 或 /foo/bar.txt）"},
+            },
+            "required": ["path"],
+            "additionalProperties": False,
+        },
+        requires_confirmation=True,
+        handler=_vfs_delete,
+    ),
+    "vfs_move": ToolSpec(
+        name="vfs_move",
+        description="移动路径（可能进入任务队列）。",
+        parameters={
+            "type": "object",
+            "properties": {
+                "src": {"type": "string", "description": "源路径（绝对路径）"},
+                "dst": {"type": "string", "description": "目标路径（绝对路径）"},
+                "overwrite": {"type": "boolean", "description": "是否允许覆盖已存在目标（默认 false）"},
+            },
+            "required": ["src", "dst"],
+            "additionalProperties": False,
+        },
+        requires_confirmation=True,
+        handler=_vfs_move,
+    ),
+    "vfs_copy": ToolSpec(
+        name="vfs_copy",
+        description="复制路径（可能进入任务队列）。",
+        parameters={
+            "type": "object",
+            "properties": {
+                "src": {"type": "string", "description": "源路径（绝对路径）"},
+                "dst": {"type": "string", "description": "目标路径（绝对路径）"},
+                "overwrite": {"type": "boolean", "description": "是否覆盖已存在目标（默认 false）"},
+            },
+            "required": ["src", "dst"],
+            "additionalProperties": False,
+        },
+        requires_confirmation=True,
+        handler=_vfs_copy,
+    ),
+    "vfs_rename": ToolSpec(
+        name="vfs_rename",
+        description="重命名路径（本质是同目录 move）。",
+        parameters={
+            "type": "object",
+            "properties": {
+                "src": {"type": "string", "description": "源路径（绝对路径）"},
+                "dst": {"type": "string", "description": "目标路径（绝对路径）"},
+                "overwrite": {"type": "boolean", "description": "是否允许覆盖已存在目标（默认 false）"},
+            },
+            "required": ["src", "dst"],
+            "additionalProperties": False,
+        },
+        requires_confirmation=True,
+        handler=_vfs_rename,
+    ),
+    "vfs_search": ToolSpec(
+        name="vfs_search",
+        description="搜索文件（mode=vector 或 filename）。",
+        parameters={
+            "type": "object",
+            "properties": {
+                "q": {"type": "string", "description": "搜索关键词"},
+                "mode": {"type": "string", "description": "搜索模式：vector/filename（默认 vector）"},
+                "top_k": {"type": "integer", "description": "返回数量（vector 模式使用，默认 10）"},
+                "page": {"type": "integer", "description": "页码（filename 模式使用，默认 1）"},
+                "page_size": {"type": "integer", "description": "分页大小（filename 模式使用，默认 10）"},
+            },
+            "required": ["q"],
+            "additionalProperties": False,
+        },
+        requires_confirmation=False,
+        handler=_vfs_search,
+    ),
+}
+
+
+def get_tool(name: str) -> Optional[ToolSpec]:
+    return TOOLS.get(name)
+
+
+def openai_tools() -> List[Dict[str, Any]]:
+    out: List[Dict[str, Any]] = []
+    for spec in TOOLS.values():
+        out.append({
+            "type": "function",
+            "function": {
+                "name": spec.name,
+                "description": spec.description,
+                "parameters": spec.parameters,
+            },
+        })
+    return out
+
+
+def tool_result_to_content(result: Any) -> str:
+    if result is None:
+        return ""
+    if isinstance(result, str):
+        return result
+    try:
+        return json.dumps(result, ensure_ascii=False)
+    except TypeError:
+        return json.dumps({"result": str(result)}, ensure_ascii=False)

domain/agent/types.py

@@ -0,0 +1,23 @@
+from typing import Any, Dict, List, Optional
+
+from pydantic import BaseModel, Field
+
+
+class AgentChatContext(BaseModel):
+    current_path: Optional[str] = None
+
+
+class AgentChatRequest(BaseModel):
+    messages: List[Dict[str, Any]] = Field(default_factory=list)
+    auto_execute: bool = False
+    approved_tool_call_ids: List[str] = Field(default_factory=list)
+    rejected_tool_call_ids: List[str] = Field(default_factory=list)
+    context: Optional[AgentChatContext] = None
+
+
+class PendingToolCall(BaseModel):
+    id: str
+    name: str
+    arguments: Dict[str, Any] = Field(default_factory=dict)
+    requires_confirmation: bool = True
+

domain/ai/inference.py

@@ -1,5 +1,7 @@
+import json
+
 import httpx
-from typing import List, Sequence, Tuple
+from typing import Any, AsyncIterator, Dict, List, Sequence, Tuple
 
 from models.database import AIModel, AIProvider
 from domain.ai.service import AIProviderService
@@ -243,3 +245,195 @@ async def _rerank_with_gemini(
         except (TypeError, ValueError):
             scores.append(0.0)
     return scores
+
+
+async def chat_completion(
+    messages: List[Dict[str, Any]],
+    *,
+    ability: str = "chat",
+    tools: List[Dict[str, Any]] | None = None,
+    tool_choice: Any | None = None,
+    temperature: float | None = None,
+    timeout: float = 60.0,
+) -> Dict[str, Any]:
+    model, provider = await _require_model(ability)
+    if provider.api_format != "openai":
+        raise MissingModelError("当前仅支持 OpenAI 兼容接口的对话模型。")
+    return await _chat_with_openai(
+        provider,
+        model,
+        messages,
+        tools=tools,
+        tool_choice=tool_choice,
+        temperature=temperature,
+        timeout=timeout,
+    )
+
+
+async def _chat_with_openai(
+    provider: AIProvider,
+    model: AIModel,
+    messages: List[Dict[str, Any]],
+    *,
+    tools: List[Dict[str, Any]] | None,
+    tool_choice: Any | None,
+    temperature: float | None,
+    timeout: float,
+) -> Dict[str, Any]:
+    url = _openai_endpoint(provider, "/chat/completions")
+    payload: Dict[str, Any] = {
+        "model": model.name,
+        "messages": messages,
+    }
+    if tools:
+        payload["tools"] = tools
+        payload["tool_choice"] = tool_choice or "auto"
+    if temperature is not None:
+        payload["temperature"] = float(temperature)
+
+    async with httpx.AsyncClient(timeout=timeout) as client:
+        response = await client.post(url, headers=_openai_headers(provider), json=payload)
+        response.raise_for_status()
+        body = response.json()
+
+    choices = body.get("choices") or []
+    if not choices:
+        raise RuntimeError("对话接口返回为空")
+    message = choices[0].get("message")
+    if not isinstance(message, dict):
+        raise RuntimeError("对话接口返回格式异常")
+    return message
+
+
+async def chat_completion_stream(
+    messages: List[Dict[str, Any]],
+    *,
+    ability: str = "chat",
+    tools: List[Dict[str, Any]] | None = None,
+    tool_choice: Any | None = None,
+    temperature: float | None = None,
+    timeout: float = 60.0,
+) -> AsyncIterator[Dict[str, Any]]:
+    model, provider = await _require_model(ability)
+    if provider.api_format != "openai":
+        raise MissingModelError("当前仅支持 OpenAI 兼容接口的对话模型。")
+    async for event in _chat_stream_with_openai(
+        provider,
+        model,
+        messages,
+        tools=tools,
+        tool_choice=tool_choice,
+        temperature=temperature,
+        timeout=timeout,
+    ):
+        yield event
+
+
+async def _chat_stream_with_openai(
+    provider: AIProvider,
+    model: AIModel,
+    messages: List[Dict[str, Any]],
+    *,
+    tools: List[Dict[str, Any]] | None,
+    tool_choice: Any | None,
+    temperature: float | None,
+    timeout: float,
+) -> AsyncIterator[Dict[str, Any]]:
+    url = _openai_endpoint(provider, "/chat/completions")
+    payload: Dict[str, Any] = {
+        "model": model.name,
+        "messages": messages,
+        "stream": True,
+    }
+    if tools:
+        payload["tools"] = tools
+        payload["tool_choice"] = tool_choice or "auto"
+    if temperature is not None:
+        payload["temperature"] = float(temperature)
+
+    content_parts: List[str] = []
+    tool_call_map: Dict[int, Dict[str, Any]] = {}
+    role = "assistant"
+    finish_reason: str | None = None
+
+    async with httpx.AsyncClient(timeout=timeout) as client:
+        async with client.stream("POST", url, headers=_openai_headers(provider), json=payload) as response:
+            response.raise_for_status()
+            async for line in response.aiter_lines():
+                if not line:
+                    continue
+                if not line.startswith("data:"):
+                    continue
+                data = line[5:].strip()
+                if not data:
+                    continue
+                if data == "[DONE]":
+                    break
+                try:
+                    chunk = json.loads(data)
+                except json.JSONDecodeError:
+                    continue
+
+                choices = chunk.get("choices") or []
+                if not choices:
+                    continue
+                choice = choices[0] if isinstance(choices[0], dict) else {}
+                delta = choice.get("delta") if isinstance(choice, dict) else None
+                delta = delta if isinstance(delta, dict) else {}
+
+                if isinstance(delta.get("role"), str):
+                    role = delta["role"]
+
+                delta_content = delta.get("content")
+                if isinstance(delta_content, str) and delta_content:
+                    content_parts.append(delta_content)
+                    yield {"type": "delta", "delta": delta_content}
+
+                delta_tool_calls = delta.get("tool_calls")
+                if isinstance(delta_tool_calls, list):
+                    for item in delta_tool_calls:
+                        if not isinstance(item, dict):
+                            continue
+                        idx = item.get("index")
+                        if not isinstance(idx, int):
+                            continue
+                        entry = tool_call_map.setdefault(
+                            idx,
+                            {"id": None, "type": None, "function": {"name": None, "arguments": ""}},
+                        )
+                        if isinstance(item.get("id"), str) and item["id"].strip():
+                            entry["id"] = item["id"]
+                        if isinstance(item.get("type"), str) and item["type"].strip():
+                            entry["type"] = item["type"]
+                        fn = item.get("function")
+                        if isinstance(fn, dict):
+                            if isinstance(fn.get("name"), str) and fn["name"].strip():
+                                entry["function"]["name"] = fn["name"]
+                            args_part = fn.get("arguments")
+                            if isinstance(args_part, str) and args_part:
+                                entry["function"]["arguments"] += args_part
+
+                fr = choice.get("finish_reason") if isinstance(choice, dict) else None
+                if isinstance(fr, str) and fr:
+                    finish_reason = fr
+
+    content = "".join(content_parts)
+    message: Dict[str, Any] = {"role": role, "content": content}
+    if tool_call_map:
+        tool_calls: List[Dict[str, Any]] = []
+        for idx in sorted(tool_call_map.keys()):
+            item = tool_call_map[idx]
+            fn = item.get("function") if isinstance(item.get("function"), dict) else {}
+            call_id = item.get("id") if isinstance(item.get("id"), str) and item.get("id") else f"call_{idx}"
+            call_type = item.get("type") if isinstance(item.get("type"), str) and item.get("type") else "function"
+            tool_calls.append({
+                "id": call_id,
+                "type": call_type,
+                "function": {
+                    "name": fn.get("name") or "",
+                    "arguments": fn.get("arguments") or "",
+                },
+            })
+        message["tool_calls"] = tool_calls
+
+    yield {"type": "message", "message": message, "finish_reason": finish_reason}

web/src/api/agent.ts

@@ -0,0 +1,121 @@
+import request, { API_BASE_URL } from './client';
+
+export type AgentChatMessage = Record<string, any>;
+
+export interface AgentChatContext {
+  current_path?: string | null;
+}
+
+export interface AgentChatRequest {
+  messages: AgentChatMessage[];
+  auto_execute?: boolean;
+  approved_tool_call_ids?: string[];
+  rejected_tool_call_ids?: string[];
+  context?: AgentChatContext;
+}
+
+export interface PendingToolCall {
+  id: string;
+  name: string;
+  arguments: Record<string, any>;
+  requires_confirmation: boolean;
+}
+
+export interface AgentChatResponse {
+  messages: AgentChatMessage[];
+  pending_tool_calls?: PendingToolCall[];
+}
+
+export type AgentSseEvent =
+  | { event: 'assistant_start'; data: { id: string } }
+  | { event: 'assistant_delta'; data: { id: string; delta: string } }
+  | { event: 'assistant_end'; data: { id: string; message: AgentChatMessage } }
+  | { event: 'tool_start'; data: { tool_call_id: string; name: string } }
+  | { event: 'tool_end'; data: { tool_call_id: string; name: string; message: AgentChatMessage } }
+  | { event: 'pending'; data: { pending_tool_calls: PendingToolCall[] } }
+  | { event: 'done'; data: AgentChatResponse };
+
+export const agentApi = {
+  chat: (payload: AgentChatRequest) =>
+    request<AgentChatResponse>('/agent/chat', {
+      method: 'POST',
+      json: payload,
+    }),
+  chatStream: async (
+    payload: AgentChatRequest,
+    onEvent: (evt: AgentSseEvent) => void,
+    options?: { signal?: AbortSignal }
+  ) => {
+    const headers: Record<string, string> = {
+      'Content-Type': 'application/json',
+      'Accept': 'text/event-stream',
+    };
+    const token = localStorage.getItem('token');
+    if (token) headers['Authorization'] = `Bearer ${token}`;
+
+    const resp = await fetch(`${API_BASE_URL}/agent/chat/stream`, {
+      method: 'POST',
+      headers,
+      body: JSON.stringify(payload),
+      signal: options?.signal,
+    });
+
+    if (!resp.ok) {
+      let errMsg = resp.statusText;
+      try {
+        const data = await resp.json();
+        if (Array.isArray((data as any)?.detail)) {
+          errMsg = (data as any).detail.map((e: any) => e.msg || JSON.stringify(e)).join('; ');
+        } else {
+          errMsg = (typeof (data as any)?.detail === 'string') ? (data as any).detail : JSON.stringify(data);
+        }
+      } catch {
+        try {
+          errMsg = await resp.text();
+        } catch { void 0; }
+      }
+      throw new Error(errMsg || `Request failed: ${resp.status}`);
+    }
+
+    const reader = resp.body?.getReader();
+    if (!reader) throw new Error('Stream not supported');
+
+    const decoder = new TextDecoder();
+    let buffer = '';
+
+    const flush = (raw: string) => {
+      const lines = raw.split(/\r?\n/);
+      let eventName = 'message';
+      const dataLines: string[] = [];
+      for (const line of lines) {
+        if (line.startsWith('event:')) {
+          eventName = line.slice(6).trim();
+        } else if (line.startsWith('data:')) {
+          dataLines.push(line.slice(5).trimStart());
+        }
+      }
+      const dataStr = dataLines.join('\n').trim();
+      if (!eventName || !dataStr) return;
+      try {
+        const data = JSON.parse(dataStr);
+        onEvent({ event: eventName as any, data } as any);
+      } catch {
+        // ignore parse error
+      }
+    };
+
+    while (true) {
+      const { value, done } = await reader.read();
+      if (done) break;
+      buffer += decoder.decode(value, { stream: true });
+      while (true) {
+        const idx = buffer.indexOf('\n\n');
+        if (idx === -1) break;
+        const chunk = buffer.slice(0, idx);
+        buffer = buffer.slice(idx + 2);
+        if (chunk.trim()) flush(chunk);
+      }
+    }
+    if (buffer.trim()) flush(buffer);
+  },
+};

web/src/components/AiAgentWidget.tsx

@@ -0,0 +1,932 @@
+import { memo, useCallback, useEffect, useMemo, useRef, useState } from 'react';
+import { Avatar, Button, Divider, Drawer, Flex, Input, List, Space, Switch, Tag, Typography, message, theme } from 'antd';
+import { RobotOutlined, SendOutlined, FolderOpenOutlined, DeleteOutlined, ToolOutlined, DownOutlined, UpOutlined, CodeOutlined, CopyOutlined, LoadingOutlined } from '@ant-design/icons';
+import ReactMarkdown from 'react-markdown';
+import PathSelectorModal from './PathSelectorModal';
+import { agentApi, type AgentChatMessage, type PendingToolCall } from '../api/agent';
+import { useI18n } from '../i18n';
+import '../styles/ai-agent.css';
+
+const { Text, Paragraph } = Typography;
+
+function normalizePath(p?: string | null): string | null {
+  if (!p) return null;
+  const s = ('/' + p).replace(/\/+/, '/').replace(/\\/g, '/').replace(/\/+$/, '') || '/';
+  return s;
+}
+
+function extractTextContent(content: any): string {
+  if (content == null) return '';
+  if (typeof content === 'string') return content;
+  if (Array.isArray(content)) {
+    const parts: string[] = [];
+    for (const item of content) {
+      if (typeof item === 'string') {
+        if (item.trim()) parts.push(item);
+        continue;
+      }
+      const text = typeof item?.text === 'string' ? item.text : '';
+      if (text.trim()) parts.push(text);
+    }
+    return parts.join('\n');
+  }
+  try {
+    return JSON.stringify(content, null, 2);
+  } catch {
+    return String(content);
+  }
+}
+
+function tryParseJson<T = any>(raw: string): T | null {
+  if (typeof raw !== 'string') return null;
+  const s = raw.trim();
+  if (!s) return null;
+  try {
+    return JSON.parse(s) as T;
+  } catch {
+    return null;
+  }
+}
+
+function shortId(id: string, keep: number = 6): string {
+  const s = String(id || '');
+  if (s.length <= keep * 2 + 3) return s;
+  return `${s.slice(0, keep)}…${s.slice(-keep)}`;
+}
+
+interface AiAgentWidgetProps {
+  currentPath?: string | null;
+  open: boolean;
+  onOpenChange(open: boolean): void;
+}
+
+const AiAgentWidget = memo(function AiAgentWidget({ currentPath, open, onOpenChange }: AiAgentWidgetProps) {
+  const { t } = useI18n();
+  const { token } = theme.useToken();
+  const [autoExecute, setAutoExecute] = useState(false);
+  const [input, setInput] = useState('');
+  const [loading, setLoading] = useState(false);
+  const [messages, setMessages] = useState<AgentChatMessage[]>([]);
+  const [pending, setPending] = useState<PendingToolCall[]>([]);
+  const [pathModalOpen, setPathModalOpen] = useState(false);
+  const [expandedTools, setExpandedTools] = useState<Record<string, boolean>>({});
+  const [expandedRaw, setExpandedRaw] = useState<Record<string, boolean>>({});
+  const [runningTools, setRunningTools] = useState<Record<string, string>>({});
+  const scrollRef = useRef<HTMLDivElement | null>(null);
+  const streamControllerRef = useRef<AbortController | null>(null);
+  const streamSeqRef = useRef(0);
+  const baseMessagesRef = useRef<AgentChatMessage[]>([]);
+  const assistantIndexRef = useRef<Record<string, number>>({});
+  const toolNameByIdRef = useRef<Record<string, string>>({});
+
+  const effectivePath = useMemo(() => normalizePath(currentPath), [currentPath]);
+
+  const scrollToBottom = useCallback(() => {
+    const el = scrollRef.current;
+    if (!el) return;
+    el.scrollTop = el.scrollHeight;
+  }, []);
+
+  useEffect(() => {
+    if (!open) return;
+    const t = window.setTimeout(scrollToBottom, 0);
+    return () => window.clearTimeout(t);
+  }, [messages, open, pending, scrollToBottom]);
+
+  useEffect(() => {
+    return () => {
+      streamControllerRef.current?.abort();
+    };
+  }, []);
+
+  const toolCallsById = useMemo(() => {
+    const map = new Map<string, { name: string; args: Record<string, any> }>();
+    for (const msg of messages) {
+      if (!msg || typeof msg !== 'object') continue;
+      if (msg.role !== 'assistant') continue;
+      const toolCalls = (msg as any).tool_calls;
+      if (!Array.isArray(toolCalls)) continue;
+      for (const call of toolCalls) {
+        const id = typeof call?.id === 'string' ? call.id : '';
+        const fn = call?.function;
+        const name = typeof fn?.name === 'string' ? fn.name : '';
+        const rawArgs = typeof fn?.arguments === 'string' ? fn.arguments : '';
+        if (!id || !name) continue;
+        const parsedArgs = tryParseJson<Record<string, any>>(rawArgs) || {};
+        map.set(id, { name, args: parsedArgs });
+      }
+    }
+    return map;
+  }, [messages]);
+
+  const runStream = useCallback(async (payload: Partial<Parameters<typeof agentApi.chat>[0]> & { messages: AgentChatMessage[] }) => {
+    streamControllerRef.current?.abort();
+    const controller = new AbortController();
+    streamControllerRef.current = controller;
+    streamSeqRef.current += 1;
+    const seq = streamSeqRef.current;
+
+    baseMessagesRef.current = payload.messages;
+    assistantIndexRef.current = {};
+
+    setLoading(true);
+    const approvedIds = payload.approved_tool_call_ids || [];
+    if (Array.isArray(approvedIds) && approvedIds.length > 0) {
+      const preRunning: Record<string, string> = {};
+      approvedIds.forEach((id) => {
+        if (typeof id === 'string' && id.trim()) preRunning[id] = '';
+      });
+      setRunningTools(preRunning);
+    } else {
+      setRunningTools({});
+    }
+
+    try {
+      await agentApi.chatStream(
+        {
+          messages: payload.messages,
+          auto_execute: autoExecute,
+          context: effectivePath ? { current_path: effectivePath } : undefined,
+          approved_tool_call_ids: payload.approved_tool_call_ids,
+          rejected_tool_call_ids: payload.rejected_tool_call_ids,
+        },
+        (evt) => {
+          if (seq !== streamSeqRef.current) return;
+          switch (evt.event) {
+            case 'assistant_start': {
+              const id = String((evt.data as any)?.id || '');
+              if (!id) return;
+              setMessages((prev) => {
+                const idx = prev.length;
+                assistantIndexRef.current[id] = idx;
+                return [...prev, { role: 'assistant', content: '' }];
+              });
+              return;
+            }
+            case 'assistant_delta': {
+              const id = String((evt.data as any)?.id || '');
+              const delta = String((evt.data as any)?.delta || '');
+              if (!id || !delta) return;
+              setMessages((prev) => {
+                const idx = assistantIndexRef.current[id];
+                if (idx === undefined || idx < 0 || idx >= prev.length) return prev;
+                const cur = prev[idx] as any;
+                const curContent = typeof cur?.content === 'string' ? cur.content : extractTextContent(cur?.content);
+                const next = prev.slice();
+                next[idx] = { ...cur, content: (curContent || '') + delta };
+                return next;
+              });
+              return;
+            }
+            case 'assistant_end': {
+              const id = String((evt.data as any)?.id || '');
+              const msg = (evt.data as any)?.message;
+              if (!id || !msg || typeof msg !== 'object') return;
+              setMessages((prev) => {
+                const idx = assistantIndexRef.current[id];
+                if (idx === undefined || idx < 0 || idx >= prev.length) return prev;
+                const next = prev.slice();
+                next[idx] = msg;
+                return next;
+              });
+              delete assistantIndexRef.current[id];
+              return;
+            }
+            case 'tool_start': {
+              const toolCallId = String((evt.data as any)?.tool_call_id || '');
+              const name = String((evt.data as any)?.name || '');
+              if (!toolCallId) return;
+              if (name) toolNameByIdRef.current[toolCallId] = name;
+              setRunningTools((prev) => ({ ...prev, [toolCallId]: name || prev[toolCallId] || '' }));
+              return;
+            }
+            case 'tool_end': {
+              const toolCallId = String((evt.data as any)?.tool_call_id || '');
+              const name = String((evt.data as any)?.name || '');
+              const msg = (evt.data as any)?.message;
+              if (toolCallId && name) toolNameByIdRef.current[toolCallId] = name;
+              if (toolCallId) {
+                setRunningTools((prev) => {
+                  const next = { ...prev };
+                  delete next[toolCallId];
+                  return next;
+                });
+              }
+              if (msg && typeof msg === 'object') {
+                setMessages((prev) => [...prev, msg]);
+              }
+              return;
+            }
+            case 'pending': {
+              const items = Array.isArray((evt.data as any)?.pending_tool_calls) ? (evt.data as any).pending_tool_calls : [];
+              setPending(items);
+              return;
+            }
+            case 'done': {
+              const base = baseMessagesRef.current || [];
+              const newMessages = Array.isArray((evt.data as any)?.messages) ? (evt.data as any).messages : [];
+              const nextPending = Array.isArray((evt.data as any)?.pending_tool_calls) ? (evt.data as any).pending_tool_calls : [];
+              setMessages([...base, ...newMessages]);
+              setPending(nextPending);
+              setRunningTools({});
+              assistantIndexRef.current = {};
+              return;
+            }
+            default:
+              return;
+          }
+        },
+        { signal: controller.signal }
+      );
+    } catch (err: any) {
+      if (controller.signal.aborted) return;
+      message.error(err?.message || t('Operation failed'));
+    } finally {
+      if (seq === streamSeqRef.current) {
+        setLoading(false);
+        if (controller.signal.aborted) {
+          setRunningTools({});
+          assistantIndexRef.current = {};
+        }
+      }
+    }
+  }, [autoExecute, effectivePath, t]);
+
+  const handleSend = useCallback(async () => {
+    const text = input.trim();
+    if (!text) return;
+    if (pending.length > 0) {
+      message.warning(t('Please confirm pending actions first'));
+      return;
+    }
+    const nextUserMsg: AgentChatMessage = { role: 'user', content: text };
+    setInput('');
+    const base = [...messages, nextUserMsg];
+    setMessages(base);
+    setPending([]);
+    await runStream({ messages: base });
+  }, [input, messages, pending.length, runStream, t]);
+
+  const clearChat = useCallback(() => {
+    streamControllerRef.current?.abort();
+    setMessages([]);
+    setPending([]);
+    setExpandedTools({});
+    setExpandedRaw({});
+    setRunningTools({});
+  }, []);
+
+  const approveOne = useCallback(async (id: string) => {
+    await runStream({ messages, approved_tool_call_ids: [id] });
+  }, [messages, runStream]);
+
+  const rejectOne = useCallback(async (id: string) => {
+    await runStream({ messages, rejected_tool_call_ids: [id] });
+  }, [messages, runStream]);
+
+  const approveAll = useCallback(async () => {
+    const ids = pending.map((p) => p.id).filter(Boolean);
+    if (ids.length === 0) return;
+    await runStream({ messages, approved_tool_call_ids: ids });
+  }, [messages, pending, runStream]);
+
+  const rejectAll = useCallback(async () => {
+    const ids = pending.map((p) => p.id).filter(Boolean);
+    if (ids.length === 0) return;
+    await runStream({ messages, rejected_tool_call_ids: ids });
+  }, [messages, pending, runStream]);
+
+  const handlePathSelected = useCallback((path: string) => {
+    const p = normalizePath(path) || '/';
+    setInput((prev) => (prev.trim() ? `${prev.trim()} ${p}` : p));
+    setPathModalOpen(false);
+  }, []);
+
+  const messageItems = useMemo(() => {
+    return messages.filter((m) => {
+      if (!m || typeof m !== 'object') return false;
+      const role = typeof (m as any).role === 'string' ? String((m as any).role) : '';
+      if (!role || role === 'system') return false;
+      if (role === 'assistant') {
+        const text = extractTextContent((m as any).content);
+        return !!text.trim();
+      }
+      return true;
+    });
+  }, [messages]);
+
+  const runningToolEntries = useMemo(() => Object.entries(runningTools).filter(([id]) => !!id), [runningTools]);
+  const runningToolCount = runningToolEntries.length;
+
+  const copyToClipboard = useCallback(async (raw: string) => {
+    try {
+      await navigator.clipboard.writeText(raw);
+      message.success(t('Copied'));
+    } catch (err: any) {
+      message.error(err?.message || t('Operation failed'));
+    }
+  }, [t]);
+
+  const renderToolResultSummary = useCallback((toolName: string, rawContent: string, toolArgs?: Record<string, any> | null) => {
+    const data = tryParseJson<Record<string, any>>(rawContent);
+    if (!data) return '';
+
+    if (data.canceled) return t('Canceled');
+    if (data.error) return `${t('Error')}: ${String(data.error)}`;
+
+    if (toolName === 'processors_list') {
+      const processors = Array.isArray(data.processors) ? data.processors : [];
+      return `${t('Processors')}: ${processors.length}`;
+    }
+    if (toolName === 'processors_run') {
+      const ctx = (() => {
+        const processorType = typeof toolArgs?.processor_type === 'string' ? toolArgs.processor_type.trim() : '';
+        const path = typeof toolArgs?.path === 'string' ? toolArgs.path.trim() : '';
+        const parts = [processorType, path].filter(Boolean);
+        return parts.length ? parts.join(' · ') : '';
+      })();
+      if (typeof data.task_id === 'string') {
+        return ctx ? `${t('Task submitted')}: ${ctx} · ${shortId(data.task_id)}` : `${t('Task submitted')}: ${shortId(data.task_id)}`;
+      }
+      const taskIds = Array.isArray(data.task_ids) ? data.task_ids : [];
+      const scheduled = typeof data.scheduled === 'number' ? data.scheduled : taskIds.length;
+      if (scheduled) return ctx ? `${t('Tasks submitted')}: ${ctx} · ${scheduled}` : `${t('Tasks submitted')}: ${scheduled}`;
+      return t('Task submitted');
+    }
+    if (toolName === 'vfs_list_dir') {
+      const path = typeof data.path === 'string' ? data.path : '';
+      const entries = Array.isArray(data.entries) ? data.entries : [];
+      const names = entries
+        .map((it: any) => String(it?.name || '').trim())
+        .filter(Boolean)
+        .slice(0, 3);
+      const head = `${t('Directory')}: ${path || '/'}`;
+      const tail = `${entries.length} ${t('items')}`;
+      const sample = names.length ? ` · ${names.join(', ')}` : '';
+      return `${head} · ${tail}${sample}`;
+    }
+    if (toolName === 'vfs_search') {
+      const query = typeof data.query === 'string' ? data.query : '';
+      const items = Array.isArray(data.items) ? data.items : [];
+      return `${t('Search')}: ${query || '-'} · ${items.length} ${t('results')}`;
+    }
+    if (toolName === 'vfs_stat') {
+      const isDir = Boolean(data.is_dir);
+      const path = typeof data.path === 'string' ? data.path : '';
+      return `${t('Info')}: ${path || '-'} · ${isDir ? t('Folder') : t('File')}`;
+    }
+    if (toolName === 'vfs_read_text') {
+      const path = typeof data.path === 'string' ? data.path : '';
+      const length = typeof data.length === 'number' ? data.length : undefined;
+      const truncated = Boolean(data.truncated);
+      const tail = length != null ? ` · ${length} ${t('chars')}${truncated ? `(${t('Truncated')})` : ''}` : '';
+      return `${t('Read')}: ${path || '-'}${tail}`;
+    }
+    if (toolName === 'vfs_write_text') {
+      const path = typeof data.path === 'string' ? data.path : '';
+      const bytes = typeof data.bytes === 'number' ? data.bytes : undefined;
+      return `${t('Write')}: ${path || '-'}${bytes != null ? ` · ${bytes} bytes` : ''}`;
+    }
+    if (toolName === 'vfs_mkdir') {
+      const path = typeof data.path === 'string' ? data.path : '';
+      return `${t('Created')}: ${path || '-'}`;
+    }
+    if (toolName === 'vfs_delete') {
+      const path = typeof data.path === 'string' ? data.path : '';
+      return `${t('Deleted')}: ${path || '-'}`;
+    }
+    if (toolName === 'vfs_move') {
+      const src = typeof data.src === 'string' ? data.src : '';
+      const dst = typeof data.dst === 'string' ? data.dst : '';
+      return `${t('Moved')}: ${src || '-'} → ${dst || '-'}`;
+    }
+    if (toolName === 'vfs_copy') {
+      const src = typeof data.src === 'string' ? data.src : '';
+      const dst = typeof data.dst === 'string' ? data.dst : '';
+      return `${t('Copied')}: ${src || '-'} → ${dst || '-'}`;
+    }
+    if (toolName === 'vfs_rename') {
+      const src = typeof data.src === 'string' ? data.src : '';
+      const dst = typeof data.dst === 'string' ? data.dst : '';
+      return `${t('Renamed')}: ${src || '-'} → ${dst || '-'}`;
+    }
+    return '';
+  }, [t]);
+
+  const renderToolDetails = useCallback((toolKey: string, toolName: string, rawContent: string) => {
+    const data = tryParseJson<Record<string, any>>(rawContent);
+    const showRaw = !!expandedRaw[toolKey];
+    const toggleRaw = () => setExpandedRaw((prev) => ({ ...prev, [toolKey]: !prev[toolKey] }));
+
+    const rawJson = (() => {
+      if (!rawContent?.trim()) return '';
+      const parsed = tryParseJson<any>(rawContent);
+      if (!parsed) return rawContent;
+      try {
+        return JSON.stringify(parsed, null, 2);
+      } catch {
+        return rawContent;
+      }
+    })();
+
+    const header = (
+      <Space size={10} wrap>
+        <Button
+          type="text"
+          size="small"
+          icon={<CodeOutlined />}
+          onClick={(e) => { e.stopPropagation(); toggleRaw(); }}
+        >
+          {t('Raw JSON')}
+        </Button>
+        {showRaw && (
+          <Button
+            type="text"
+            size="small"
+            icon={<CopyOutlined />}
+            onClick={(e) => { e.stopPropagation(); void copyToClipboard(rawJson); }}
+          >
+            {t('Copy')}
+          </Button>
+        )}
+      </Space>
+    );
+
+    if (toolName === 'processors_list') {
+      const processors = Array.isArray(data?.processors) ? data!.processors : [];
+      return (
+        <div className="fx-agent-tool-details">
+          {header}
+          <Divider style={{ margin: '10px 0' }} />
+          <List
+            size="small"
+            dataSource={processors}
+            locale={{ emptyText: t('No results') }}
+            renderItem={(item: any) => (
+              <List.Item>
+                <Space size={10} wrap>
+                  <Text code style={{ fontVariantNumeric: 'tabular-nums' }}>{String(item?.type || '')}</Text>
+                  <Text>{String(item?.name || '')}</Text>
+                </Space>
+              </List.Item>
+            )}
+            style={{ background: 'transparent' }}
+          />
+          {showRaw && (
+            <>
+              <Divider style={{ margin: '10px 0' }} />
+              <pre className="fx-agent-pre">{rawJson}</pre>
+            </>
+          )}
+        </div>
+      );
+    }
+
+    if (toolName === 'vfs_list_dir') {
+      const path = typeof data?.path === 'string' ? data!.path : '/';
+      const entries = Array.isArray(data?.entries) ? data!.entries : [];
+      const pagination = data?.pagination && typeof data.pagination === 'object' ? data.pagination : null;
+      return (
+        <div className="fx-agent-tool-details">
+          {header}
+          <Divider style={{ margin: '10px 0' }} />
+          <Space direction="vertical" size={6} style={{ width: '100%' }}>
+            <Text type="secondary" style={{ fontSize: 12 }}>{t('Directory')}: {path}</Text>
+            {pagination?.total != null ? (
+              <Text type="secondary" style={{ fontSize: 12 }}>
+                {t('Total')}: {String(pagination.total)}
+              </Text>
+            ) : null}
+          </Space>
+          <Divider style={{ margin: '10px 0' }} />
+          <List
+            size="small"
+            dataSource={entries}
+            locale={{ emptyText: t('No results') }}
+            renderItem={(item: any) => {
+              const name = String(item?.name || '');
+              const type = String(item?.type || (item?.is_dir ? 'dir' : 'file'));
+              return (
+                <List.Item>
+                  <Space size={10} wrap style={{ width: '100%', justifyContent: 'space-between' }}>
+                    <Space size={10} wrap>
+                      <Text code style={{ fontVariantNumeric: 'tabular-nums' }}>{type}</Text>
+                      <Text>{name}</Text>
+                    </Space>
+                    {!item?.is_dir && typeof item?.size === 'number' ? (
+                      <Text type="secondary" style={{ fontSize: 12 }}>{item.size} bytes</Text>
+                    ) : null}
+                  </Space>
+                </List.Item>
+              );
+            }}
+            style={{ background: 'transparent' }}
+          />
+          {showRaw && (
+            <>
+              <Divider style={{ margin: '10px 0' }} />
+              <pre className="fx-agent-pre">{rawJson}</pre>
+            </>
+          )}
+        </div>
+      );
+    }
+
+    if (toolName === 'vfs_search') {
+      const query = typeof data?.query === 'string' ? data!.query : '';
+      const mode = typeof data?.mode === 'string' ? data!.mode : '';
+      const items = Array.isArray(data?.items) ? data!.items : [];
+      const pagination = data?.pagination && typeof data.pagination === 'object' ? data.pagination : null;
+      return (
+        <div className="fx-agent-tool-details">
+          {header}
+          <Divider style={{ margin: '10px 0' }} />
+          <Space direction="vertical" size={6} style={{ width: '100%' }}>
+            <Text type="secondary" style={{ fontSize: 12 }}>{t('Search')}: {query || '-'}</Text>
+            <Text type="secondary" style={{ fontSize: 12 }}>{t('Mode')}: {mode || '-'}</Text>
+            {pagination?.has_more != null ? (
+              <Text type="secondary" style={{ fontSize: 12 }}>
+                {t('Page')}: {String(pagination.page)} · {t('Has more')}: {String(Boolean(pagination.has_more))}
+              </Text>
+            ) : null}
+          </Space>
+          <Divider style={{ margin: '10px 0' }} />
+          <List
+            size="small"
+            dataSource={items}
+            locale={{ emptyText: t('No results') }}
+            renderItem={(item: any) => {
+              const type = String(item?.source_type || item?.mime || '');
+              const path = String(item?.path || '');
+              const score = item?.score != null ? Number(item.score) : null;
+              return (
+                <List.Item>
+                  <Space size={10} wrap style={{ width: '100%', justifyContent: 'space-between' }}>
+                    <Space size={10} wrap>
+                      {type ? <Text code style={{ fontVariantNumeric: 'tabular-nums' }}>{type}</Text> : null}
+                      <Text>{path}</Text>
+                    </Space>
+                    {score != null && !Number.isNaN(score) ? (
+                      <Text type="secondary" style={{ fontSize: 12 }}>{score.toFixed(3)}</Text>
+                    ) : null}
+                  </Space>
+                </List.Item>
+              );
+            }}
+            style={{ background: 'transparent' }}
+          />
+          {showRaw && (
+            <>
+              <Divider style={{ margin: '10px 0' }} />
+              <pre className="fx-agent-pre">{rawJson}</pre>
+            </>
+          )}
+        </div>
+      );
+    }
+
+    if (toolName === 'vfs_read_text') {
+      const path = typeof data?.path === 'string' ? data!.path : '';
+      const content = typeof data?.content === 'string' ? data!.content : '';
+      return (
+        <div className="fx-agent-tool-details">
+          {header}
+          <Divider style={{ margin: '10px 0' }} />
+          <Text type="secondary" style={{ fontSize: 12 }}>{t('File')}: {path || '-'}</Text>
+          <pre className="fx-agent-pre" style={{ marginTop: 10 }}>{content || ''}</pre>
+          {showRaw && (
+            <>
+              <Divider style={{ margin: '10px 0' }} />
+              <pre className="fx-agent-pre">{rawJson}</pre>
+            </>
+          )}
+        </div>
+      );
+    }
+
+    return (
+      <div className="fx-agent-tool-details">
+        {header}
+        <Divider style={{ margin: '10px 0' }} />
+        {showRaw ? (
+          <pre className="fx-agent-pre">{rawJson}</pre>
+        ) : (
+          <Paragraph style={{ marginBottom: 0, whiteSpace: 'pre-wrap' }}>
+            {extractTextContent(data ?? rawContent) || <Text type="secondary">{t('No content')}</Text>}
+          </Paragraph>
+        )}
+      </div>
+    );
+  }, [copyToClipboard, expandedRaw, t]);
+
+  const renderToolArgsSummary = useCallback((toolName: string, args?: Record<string, any> | null) => {
+    const a = args || {};
+    if (toolName === 'processors_run') {
+      const path = typeof a.path === 'string' ? a.path : '';
+      return path ? `${t('Path')}: ${path}` : '';
+    }
+    if (toolName === 'vfs_read_text' || toolName === 'vfs_list_dir' || toolName === 'vfs_stat' || toolName === 'vfs_delete' || toolName === 'vfs_mkdir') {
+      const path = typeof a.path === 'string' ? a.path : '';
+      return path ? `${t('Path')}: ${path}` : '';
+    }
+    if (toolName === 'vfs_search') {
+      const query = typeof a.query === 'string' ? a.query : '';
+      return query ? `${t('Search')}: ${query}` : '';
+    }
+    if (toolName === 'vfs_write_text') {
+      const path = typeof a.path === 'string' ? a.path : '';
+      return path ? `${t('Path')}: ${path}` : '';
+    }
+    if (toolName === 'vfs_move' || toolName === 'vfs_copy' || toolName === 'vfs_rename') {
+      const src = typeof a.src === 'string' ? a.src : '';
+      const dst = typeof a.dst === 'string' ? a.dst : '';
+      if (src && dst) return `${src} → ${dst}`;
+      if (src) return src;
+      if (dst) return dst;
+      return '';
+    }
+    return '';
+  }, [t]);
+
+  return (
+    <>
+      <Drawer
+        title={t('AI Agent')}
+        open={open}
+        onClose={() => { streamControllerRef.current?.abort(); onOpenChange(false); }}
+        width={520}
+        mask={false}
+        destroyOnHidden
+        styles={{
+          body: {
+            padding: 8,
+            background: token.colorBgContainer,
+          },
+        }}
+        extra={
+          <Space align="center">
+            <Text type="secondary">{t('Auto execute')}</Text>
+            <Switch size="small" checked={autoExecute} onChange={setAutoExecute} />
+            <Button
+              type="text"
+              size="small"
+              icon={<DeleteOutlined />}
+              onClick={clearChat}
+              disabled={loading || messageItems.length === 0}
+            >
+              {t('Clear')}
+            </Button>
+          </Space>
+        }
+      >
+        <Flex vertical gap={0} style={{ height: '100%' }} className="fx-agent-container">
+          <div
+            ref={scrollRef}
+            className="fx-agent-chat-scroll"
+          >
+            {messageItems.length === 0 ? (
+              <div className="fx-agent-empty">
+                <Avatar size={36} icon={<RobotOutlined />} style={{ background: token.colorPrimary }} />
+                <div style={{ marginTop: 8 }}>
+                  <Text type="secondary">{t('Start a conversation')}</Text>
+                </div>
+              </div>
+            ) : (
+              <div className="fx-agent-messages">
+                {messageItems.map((m, idx) => {
+                  const role = String((m as any).role);
+                  const isUser = role === 'user';
+                  const isTool = role === 'tool';
+                  const toolCallId = typeof (m as any).tool_call_id === 'string' ? String((m as any).tool_call_id) : '';
+                  const toolInfo = toolCallId ? toolCallsById.get(toolCallId) : null;
+                  const toolName = toolInfo?.name || (toolCallId ? toolNameByIdRef.current[toolCallId] : '') || '';
+                  const msgKey = toolCallId ? `tool:${toolCallId}` : `${role}:${idx}`;
+
+                  if (isTool) {
+                    const rawContent = extractTextContent((m as any).content);
+                    const expanded = !!expandedTools[msgKey];
+                    const summary = toolName ? renderToolResultSummary(toolName, rawContent, toolInfo?.args || null) : '';
+                    return (
+                      <div key={msgKey} className="fx-agent-msg fx-agent-msg-tool">
+                        <div className="fx-agent-tool-block">
+                          <div className="fx-agent-tool-bar">
+                            <Space size={6} wrap className="fx-agent-tool-pills">
+                              <Tag className="fx-agent-pill" bordered={false} icon={<ToolOutlined />}>
+                                {t('MCP Tool')}
+                              </Tag>
+                              <Tag className="fx-agent-pill fx-agent-pill-strong" bordered={false} icon={<CodeOutlined />}>
+                                {toolName || t('Tool')}
+                              </Tag>
+                            </Space>
+                            <Button
+                              type="text"
+                              size="small"
+                              icon={expanded ? <UpOutlined /> : <DownOutlined />}
+                              onClick={() => setExpandedTools((prev) => ({ ...prev, [msgKey]: !prev[msgKey] }))}
+                            >
+                              {expanded ? t('Collapse') : t('Expand')}
+                              </Button>
+                          </div>
+                          {summary ? (
+                            <div className="fx-agent-tool-summary-line">
+                              <Text type="secondary">{summary}</Text>
+                            </div>
+                          ) : null}
+                          {expanded && (
+                            <div className="fx-agent-tool-expanded">
+                              {toolInfo?.args && Object.keys(toolInfo.args).length > 0 && (
+                                <div style={{ marginBottom: 10 }}>
+                                  <Text type="secondary" style={{ fontSize: 12 }}>{t('Arguments')}</Text>
+                                  <pre className="fx-agent-pre fx-agent-pre-compact">
+                                    {JSON.stringify(toolInfo.args, null, 2)}
+                                  </pre>
+                                </div>
+                              )}
+                              {renderToolDetails(msgKey, toolName || t('Tool'), rawContent)}
+                            </div>
+                          )}
+                        </div>
+                      </div>
+                    );
+                  }
+
+                  const text = extractTextContent((m as any).content);
+                  if (isUser) {
+                    return (
+                      <div key={msgKey} className="fx-agent-msg fx-agent-msg-user">
+                        <div className="fx-agent-user-block fx-agent-content">
+                          {text.trim() ? <div className="fx-agent-text">{text}</div> : <Text type="secondary">{t('No content')}</Text>}
+                        </div>
+                      </div>
+                    );
+                  }
+
+                  return (
+                    <div key={msgKey} className="fx-agent-msg fx-agent-msg-assistant">
+                      <div className="fx-agent-assistant-block fx-agent-content">
+                        {text.trim() ? (
+                          <div className="fx-agent-md">
+                            <ReactMarkdown>{text}</ReactMarkdown>
+                          </div>
+                        ) : (
+                          <Text type="secondary">{t('No content')}</Text>
+                        )}
+                      </div>
+                    </div>
+                  );
+                })}
+                {runningToolCount > 0 && (
+                  <div className="fx-agent-running">
+                    <LoadingOutlined spin />
+                    <Text type="secondary">{t('Calling tools')}</Text>
+                    <Space size={6} wrap>
+                      {runningToolEntries.slice(0, 2).map(([id, name]) => (
+                        <Tag key={id} bordered={false} color="blue">
+                          {(name || t('Tool'))} #{shortId(id, 4)}
+                        </Tag>
+                      ))}
+                      {runningToolCount > 2 && (
+                        <Text type="secondary">+{runningToolCount - 2}</Text>
+                      )}
+                    </Space>
+                  </div>
+                )}
+                {pending.length > 0 && (
+                  <div className="fx-agent-pending-group">
+                    <div className="fx-agent-pending-head">
+                      <Space size={8} wrap>
+                        <Tag className="fx-agent-pill fx-agent-pill-warn" bordered={false}>
+                          {t('Pending actions')}
+                        </Tag>
+                        <Text type="secondary">{pending.length}</Text>
+                      </Space>
+                      <Space size={6}>
+                        <Button size="small" type="primary" onClick={approveAll} loading={loading}>
+                          {t('Execute all')}
+                        </Button>
+                        <Button size="small" onClick={rejectAll} disabled={loading}>
+                          {t('Cancel all')}
+                        </Button>
+                      </Space>
+                    </div>
+
+                    <div className="fx-agent-pending-list">
+                      {pending.map((p) => {
+                        const args = p.arguments || {};
+                        const key = `pending:${p.id}`;
+                        const expanded = !!expandedTools[key];
+                        const running = Object.prototype.hasOwnProperty.call(runningTools, p.id);
+                        const summary = renderToolArgsSummary(p.name, args);
+                        return (
+                          <div key={p.id} className="fx-agent-tool-block fx-agent-pending-item">
+                            <div className="fx-agent-tool-bar">
+                              <Space size={6} wrap className="fx-agent-tool-pills">
+                                <Tag className="fx-agent-pill" bordered={false} icon={<ToolOutlined />}>
+                                  {t('MCP Tool')}
+                                </Tag>
+                                <Tag className="fx-agent-pill fx-agent-pill-strong" bordered={false} icon={<CodeOutlined />}>
+                                  {p.name}
+                                </Tag>
+                                {running ? <LoadingOutlined spin style={{ color: token.colorPrimary }} /> : null}
+                              </Space>
+                              <Space size={6}>
+                                <Button
+                                  size="small"
+                                  type="primary"
+                                  onClick={() => void approveOne(p.id)}
+                                  loading={loading && running}
+                                  disabled={loading && !running}
+                                >
+                                  {t('Execute')}
+                                </Button>
+                                <Button
+                                  size="small"
+                                  onClick={() => void rejectOne(p.id)}
+                                  disabled={loading && !running}
+                                >
+                                  {t('Cancel')}
+                                </Button>
+                                <Button
+                                  type="text"
+                                  size="small"
+                                  icon={expanded ? <UpOutlined /> : <DownOutlined />}
+                                  onClick={() => setExpandedTools((prev) => ({ ...prev, [key]: !prev[key] }))}
+                                />
+                              </Space>
+                            </div>
+                            {summary ? (
+                              <div className="fx-agent-tool-summary-line">
+                                <Text type="secondary">{summary}</Text>
+                              </div>
+                            ) : null}
+                            {expanded && (
+                              <div className="fx-agent-tool-expanded">
+                                <Text type="secondary" style={{ fontSize: 12 }}>{t('Arguments')}</Text>
+                                <pre className="fx-agent-pre">
+                                  {JSON.stringify(args, null, 2)}
+                                </pre>
+                              </div>
+                            )}
+                          </div>
+                        );
+                      })}
+                    </div>
+                  </div>
+                )}
+              </div>
+            )}
+          </div>
+
+          <div className="fx-agent-composer">
+            <Flex vertical gap={8}>
+              <Space wrap>
+                <Button size="small" icon={<FolderOpenOutlined />} onClick={() => setPathModalOpen(true)} disabled={loading}>
+                  {t('Select Path')}
+                </Button>
+                {effectivePath && (
+                  <Tag bordered={false} color="blue">{t('Current')}: {effectivePath}</Tag>
+                )}
+              </Space>
+
+              <Input.TextArea
+                value={input}
+                onChange={(e) => setInput(e.target.value)}
+                placeholder={t('Type a message')}
+                autoSize={{ minRows: 2, maxRows: 6 }}
+                disabled={loading || pending.length > 0}
+                variant="borderless"
+                onPressEnter={(e) => {
+                  if (e.shiftKey) return;
+                  e.preventDefault();
+                  void handleSend();
+                }}
+              />
+              <div style={{ display: 'flex', justifyContent: 'flex-end' }}>
+                <Button
+                  type="primary"
+                  size="small"
+                  icon={<SendOutlined />}
+                  onClick={handleSend}
+                  loading={loading}
+                  disabled={loading || pending.length > 0 || !input.trim()}
+                >
+                  {t('Send')}
+                </Button>
+              </div>
+            </Flex>
+          </div>
+        </Flex>
+      </Drawer>
+
+      <PathSelectorModal
+        open={pathModalOpen}
+        mode="any"
+        initialPath={effectivePath || '/'}
+        onOk={handlePathSelected}
+        onCancel={() => setPathModalOpen(false)}
+      />
+    </>
+  );
+});
+
+export default AiAgentWidget;

web/src/i18n/locales/en.json

@@ -690,5 +690,40 @@
   "App \"{key}\" not found.": "App \"{key}\" not found.",
   "Open with {app}": "Open with {app}",
   "Set as default for .{ext}": "Set as default for .{ext}",
-  "Advanced tokens must be valid JSON": "Advanced tokens must be valid JSON"
+  "AI Agent": "AI Agent",
+  "Auto execute": "Auto execute",
+  "Start a conversation": "Start a conversation",
+  "No content": "No content",
+  "Pending actions": "Pending actions",
+  "Execute": "Execute",
+  "Execute all": "Execute all",
+  "Cancel all": "Cancel all",
+  "Type a message": "Type a message",
+  "Send": "Send",
+  "Please confirm pending actions first": "Please confirm pending actions first",
+  "You": "You",
+  "Tool": "Tool",
+  "MCP Tool": "MCP Tool",
+  "Arguments": "Arguments",
+  "Raw JSON": "Raw JSON",
+  "Collapse": "Collapse",
+  "Copied": "Copied",
+  "Canceled": "Canceled",
+  "Tasks submitted": "Tasks submitted",
+  "Calling tools": "Calling tools",
+  "Advanced tokens must be valid JSON": "Advanced tokens must be valid JSON",
+  "Search": "Search",
+  "Total": "Total",
+  "Mode": "Mode",
+  "Has more": "Has more",
+  "Page": "Page",
+  "results": "results",
+  "chars": "chars",
+  "Truncated": "Truncated",
+  "Write": "Write",
+  "Read": "Read",
+  "Created": "Created",
+  "Moved": "Moved",
+  "Renamed": "Renamed",
+  "Info": "Info"
 }

web/src/i18n/locales/zh.json

@@ -683,5 +683,40 @@
   "App \"{key}\" not found.": "应用 \"{key}\" 不存在。",
   "Open with {app}": "使用 {app} 打开",
   "Set as default for .{ext}": "设为该类型(.{ext})默认应用",
-  "Advanced tokens must be valid JSON": "高级 Token 需为合法 JSON"
+  "AI Agent": "AI 助手",
+  "Auto execute": "自动执行",
+  "Start a conversation": "开始对话",
+  "No content": "无内容",
+  "Pending actions": "待确认操作",
+  "Execute": "执行",
+  "Execute all": "全部执行",
+  "Cancel all": "全部取消",
+  "Type a message": "输入消息",
+  "Send": "发送",
+  "Please confirm pending actions first": "请先确认待执行操作",
+  "You": "你",
+  "Tool": "工具",
+  "MCP Tool": "MCP 工具",
+  "Arguments": "参数",
+  "Raw JSON": "原始 JSON",
+  "Collapse": "收起",
+  "Copied": "已复制",
+  "Canceled": "已取消",
+  "Tasks submitted": "已提交任务",
+  "Calling tools": "正在调用工具",
+  "Advanced tokens must be valid JSON": "高级 Token 需为合法 JSON",
+  "Search": "搜索",
+  "Total": "总计",
+  "Mode": "模式",
+  "Has more": "更多",
+  "Page": "页",
+  "results": "条结果",
+  "chars": "字符",
+  "Truncated": "已截断",
+  "Write": "写入",
+  "Read": "读取",
+  "Created": "已创建",
+  "Moved": "已移动",
+  "Renamed": "已重命名",
+  "Info": "信息"
 }

web/src/layout/TopHeader.tsx

@@ -1,5 +1,5 @@
-import { Layout, Button, Dropdown, theme, Flex, Avatar, Typography } from 'antd';
-import { SearchOutlined, MenuUnfoldOutlined, LogoutOutlined, UserOutlined } from '@ant-design/icons';
+import { Layout, Button, Dropdown, theme, Flex, Avatar, Typography, Tooltip } from 'antd';
+import { SearchOutlined, MenuUnfoldOutlined, LogoutOutlined, UserOutlined, RobotOutlined } from '@ant-design/icons';
 import { memo, useState } from 'react';
 import SearchDialog from './SearchDialog.tsx';
 import { authApi } from '../api/auth.ts';
@@ -14,9 +14,10 @@ const { Header } = Layout;
 export interface TopHeaderProps {
   collapsed: boolean;
   onToggle(): void;
+  onOpenAiAgent(): void;
 }
 
-const TopHeader = memo(function TopHeader({ collapsed, onToggle }: TopHeaderProps) {
+const TopHeader = memo(function TopHeader({ collapsed, onToggle, onOpenAiAgent }: TopHeaderProps) {
   const { token } = theme.useToken();
   const [searchOpen, setSearchOpen] = useState(false);
   const navigate = useNavigate();
@@ -50,6 +51,15 @@ const TopHeader = memo(function TopHeader({ collapsed, onToggle }: TopHeaderProp
       </Button>
       <SearchDialog open={searchOpen} onClose={() => setSearchOpen(false)} />
       <Flex style={{ marginLeft: 'auto' }} align="center" gap={12}>
+        <Tooltip title={t('AI Agent')}>
+          <Button
+            type="text"
+            icon={<RobotOutlined />}
+            aria-label={t('AI Agent')}
+            onClick={onOpenAiAgent}
+            style={{ paddingInline: 8, height: 40 }}
+          />
+        </Tooltip>
         <LanguageSwitcher />
         <Dropdown
           menu={{

web/src/router/LayoutShell.tsx

@@ -16,6 +16,7 @@ import BackupPage from '../pages/SystemSettingsPage/BackupPage.tsx';
 import PluginsPage from '../pages/PluginsPage.tsx';
 import { AppWindowsProvider, useAppWindows } from '../contexts/AppWindowsContext';
 import { AppWindowsLayer } from '../apps/AppWindowsLayer';
+import AiAgentWidget from '../components/AiAgentWidget';
 
 const ShellBody = memo(function ShellBody() {
   const params = useParams<{ navKey?: string; '*': string }>();
@@ -24,11 +25,13 @@ const ShellBody = memo(function ShellBody() {
   const navigate = useNavigate();
   const COLLAPSED_KEY = 'layout.siderCollapsed';
   const [collapsed, setCollapsed] = useState(() => localStorage.getItem(COLLAPSED_KEY) === '1');
+  const [agentOpen, setAgentOpen] = useState(false);
   useEffect(() => {
     localStorage.setItem(COLLAPSED_KEY, collapsed ? '1' : '0');
   }, [collapsed]);
   const { windows, closeWindow, toggleMax, bringToFront, updateWindow } = useAppWindows();
   const settingsTab = navKey === 'settings' ? (subPath.split('/')[0] || undefined) : undefined;
+  const agentCurrentPath = navKey === 'files' ? ('/' + subPath).replace(/\/+/g, '/').replace(/\/+$/, '') || '/' : null;
   return (
     <Layout style={{ minHeight: '100vh', background: 'var(--ant-color-bg-layout)' }}>
       <SideNav
@@ -44,7 +47,7 @@ const ShellBody = memo(function ShellBody() {
         }}
       />
       <Layout style={{ background: 'var(--ant-color-bg-layout)' }}>
-        <TopHeader collapsed={collapsed} onToggle={() => setCollapsed(c => !c)} />
+        <TopHeader collapsed={collapsed} onToggle={() => setCollapsed(c => !c)} onOpenAiAgent={() => setAgentOpen(true)} />
         <Layout.Content style={{ padding: 16, background: 'var(--ant-color-bg-layout)' }}>
           <div style={{ minHeight: 'calc(100vh - 56px - 32px)', background: 'var(--ant-color-bg-layout)' }}>
             <Flex vertical gap={16}>
@@ -76,6 +79,7 @@ const ShellBody = memo(function ShellBody() {
         onBringToFront={bringToFront}
         onUpdateWindow={updateWindow}
       />
+      <AiAgentWidget currentPath={agentCurrentPath} open={agentOpen} onOpenChange={setAgentOpen} />
     </Layout>
   );
 });

web/src/styles/ai-agent.css

@@ -0,0 +1,244 @@
+.fx-agent-container {
+  height: 100%;
+}
+
+.fx-agent-chat-scroll {
+  flex: 1;
+  overflow-y: auto;
+  padding: 0;
+  border-radius: 0;
+  background: transparent;
+  border: 0;
+  box-shadow: none;
+}
+
+.fx-agent-empty {
+  height: 100%;
+  min-height: 240px;
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+  justify-content: center;
+}
+
+.fx-agent-messages {
+  display: flex;
+  flex-direction: column;
+  gap: 14px;
+}
+
+.fx-agent-msg {
+  display: flex;
+  flex-direction: column;
+}
+
+.fx-agent-msg-user {
+  align-items: flex-end;
+}
+
+.fx-agent-msg-assistant {
+  align-items: flex-start;
+}
+
+.fx-agent-msg-tool {
+  align-items: stretch;
+}
+
+.fx-agent-user-block {
+  max-width: 85%;
+  padding: 10px 12px;
+  border-radius: 12px;
+  border: 1px solid var(--ant-color-border-secondary);
+  background: var(--ant-color-fill-quaternary);
+  box-shadow: 0 1px 0 rgba(0, 0, 0, 0.03);
+}
+
+.fx-agent-assistant-block {
+  max-width: 100%;
+  padding: 2px 2px;
+}
+
+.fx-agent-tool-block {
+  width: 100%;
+  padding: 10px 12px;
+  border-radius: 12px;
+  border: 1px solid var(--ant-color-border-secondary);
+  background: var(--ant-color-bg-container);
+  box-shadow: 0 1px 0 rgba(0, 0, 0, 0.03);
+}
+
+.fx-agent-tool-bar {
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  gap: 12px;
+}
+
+.fx-agent-content {
+  font-size: 13px;
+  line-height: 1.75;
+  word-break: break-word;
+}
+
+.fx-agent-tool-pills .ant-tag {
+  margin-inline-end: 0;
+}
+
+.fx-agent-pill {
+  border-radius: 999px;
+  padding-inline: 10px;
+  padding-block: 2px;
+  border: 0;
+  background: rgba(0, 0, 0, 0.04);
+}
+
+.fx-agent-pill-strong {
+  background: var(--ant-color-primary-bg);
+  color: var(--ant-color-primary);
+}
+
+.fx-agent-pill-warn {
+  background: var(--ant-color-warning-bg);
+  color: var(--ant-color-warning);
+}
+
+.fx-agent-tool-summary-line {
+  margin-top: 6px;
+  font-size: 12px;
+  line-height: 1.6;
+  color: var(--ant-color-text-tertiary);
+}
+
+.fx-agent-tool-expanded {
+  margin-top: 10px;
+}
+
+.fx-agent-text {
+  white-space: pre-wrap;
+}
+
+.fx-agent-md {
+  white-space: normal;
+}
+
+.fx-agent-md p {
+  margin: 0 0 0.5em;
+}
+
+.fx-agent-md p:last-child {
+  margin-bottom: 0;
+}
+
+.fx-agent-md ul,
+.fx-agent-md ol {
+  margin: 0 0 0.5em;
+  padding-left: 1.2em;
+}
+
+.fx-agent-md code {
+  padding: 1px 6px;
+  border-radius: 6px;
+  background: rgba(0, 0, 0, 0.04);
+  border: 1px solid var(--ant-color-border-secondary);
+  font-family: ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace;
+  font-size: 11px;
+}
+
+.fx-agent-md pre {
+  margin: 0 0 0.5em;
+  padding: 8px 10px;
+  border-radius: 10px;
+  background: var(--ant-color-bg-container);
+  border: 1px solid var(--ant-color-border-secondary);
+  overflow: auto;
+}
+
+.fx-agent-md pre code {
+  display: block;
+  padding: 0;
+  border: 0;
+  background: transparent;
+  font-size: 11px;
+  line-height: 1.55;
+}
+
+.fx-agent-md blockquote {
+  margin: 0 0 0.65em;
+  padding: 0 0 0 10px;
+  border-left: 3px solid var(--ant-color-border);
+  color: var(--ant-color-text-tertiary);
+}
+
+.fx-agent-md a {
+  color: var(--ant-color-primary);
+}
+
+.fx-agent-tool-details {
+  padding: 8px;
+  border-radius: 10px;
+  background: rgba(0, 0, 0, 0.02);
+  border: 1px solid var(--ant-color-border-secondary);
+}
+
+.fx-agent-pre {
+  margin: 8px 0 0;
+  padding: 8px 10px;
+  border-radius: 10px;
+  background: var(--ant-color-bg-container);
+  border: 1px solid var(--ant-color-border-secondary);
+  font-size: 11px;
+  line-height: 1.5;
+  white-space: pre;
+  overflow: auto;
+  max-height: 260px;
+}
+
+.fx-agent-pre.fx-agent-pre-compact {
+  max-height: 200px;
+}
+
+.fx-agent-pending-group {
+  margin-top: 6px;
+  display: flex;
+  flex-direction: column;
+  gap: 10px;
+}
+
+.fx-agent-pending-head {
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  gap: 10px;
+  padding: 8px 10px;
+  border-radius: 12px;
+  border: 1px solid var(--ant-color-border-secondary);
+  background: rgba(0, 0, 0, 0.02);
+}
+
+.fx-agent-pending-list {
+  display: flex;
+  flex-direction: column;
+  gap: 10px;
+}
+
+.fx-agent-composer {
+  padding: 8px 0 0;
+  background: transparent;
+  border-top: 1px solid var(--ant-color-border-secondary);
+}
+
+.fx-agent-composer .ant-input {
+  font-size: 12px;
+  line-height: 1.6;
+}
+
+.fx-agent-running {
+  margin-top: 4px;
+  padding: 6px 8px;
+  border-radius: 10px;
+  background: rgba(0, 0, 0, 0.03);
+  border: 1px dashed var(--ant-color-border-secondary);
+  display: flex;
+  align-items: center;
+  gap: 10px;
+}