chore: bump version to 4.14.7

chore: update Python version requirements to 3.12 (#4963 )
feat: enhance package.json with resource filters and compression settings
2026-02-08 23:20:34 +08:00 · 2026-02-08 23:13:51 +08:00 · 2026-02-08 22:58:58 +08:00 · 2026-02-08 22:18:13 +08:00 · 2026-02-08 21:49:54 +08:00 · 2026-02-08 21:13:38 +08:00
111 changed files with 14210 additions and 594 deletions
@@ -0,0 +1,227 @@
+name: Desktop Release
+
+on:
+  push:
+    tags:
+      - "v*"
+  workflow_dispatch:
+    inputs:
+      ref:
+        description: "Git ref to build (branch/tag/SHA)"
+        required: false
+        default: "master"
+      tag:
+        description: "Release tag to upload assets to (for example: v4.14.6)"
+        required: false
+
+permissions:
+  contents: write
+
+jobs:
+  build-desktop:
+    name: Build ${{ matrix.name }}
+    runs-on: ${{ matrix.runner }}
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - name: linux-x64
+            runner: ubuntu-24.04
+            os: linux
+            arch: amd64
+          - name: linux-arm64
+            runner: ubuntu-24.04-arm
+            os: linux
+            arch: arm64
+          - name: windows-x64
+            runner: windows-2022
+            os: win
+            arch: amd64
+          - name: windows-arm64
+            runner: windows-11-arm
+            os: win
+            arch: arm64
+          - name: macos-x64
+            runner: macos-15-intel
+            os: mac
+            arch: amd64
+          - name: macos-arm64
+            runner: macos-15
+            os: mac
+            arch: arm64
+    env:
+      CSC_IDENTITY_AUTO_DISCOVERY: "false"
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+          ref: ${{ inputs.ref || github.ref }}
+
+      - name: Setup uv
+        uses: astral-sh/setup-uv@v6
+
+      - name: Setup Python
+        uses: actions/setup-python@v6
+        with:
+          python-version: "3.11"
+
+      - name: Setup pnpm
+        uses: pnpm/action-setup@v4
+        with:
+          version: 10.28.2
+
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: 20
+          cache: "pnpm"
+          cache-dependency-path: |
+            dashboard/pnpm-lock.yaml
+            desktop/pnpm-lock.yaml
+
+      - name: Install dependencies
+        run: |
+          uv sync
+          pnpm --dir dashboard install --frozen-lockfile
+          pnpm --dir desktop install --frozen-lockfile
+
+      - name: Build desktop package
+        run: |
+          pnpm --dir dashboard run build
+          pnpm --dir desktop run build:webui
+          pnpm --dir desktop run build:backend
+          pnpm --dir desktop run sync:version
+          pnpm --dir desktop exec electron-builder --publish never
+
+      - name: Resolve artifact tag
+        id: tag
+        shell: bash
+        run: |
+          if [ "${{ github.event_name }}" = "push" ]; then
+            tag="${GITHUB_REF_NAME}"
+          elif [ -n "${{ inputs.tag }}" ]; then
+            tag="${{ inputs.tag }}"
+          else
+            tag="$(git describe --tags --abbrev=0)"
+          fi
+          if [ -z "$tag" ]; then
+            echo "Failed to resolve artifact tag." >&2
+            exit 1
+          fi
+          echo "tag=$tag" >> "$GITHUB_OUTPUT"
+
+      - name: Normalize artifact names
+        shell: bash
+        env:
+          NAME_PREFIX: AstrBot-${{ steps.tag.outputs.tag }}-${{ matrix.arch }}-${{ matrix.os }}
+        run: |
+          shopt -s nullglob
+          out_dir="desktop/dist/release"
+          mkdir -p "$out_dir"
+          files=(
+            desktop/dist/*.AppImage
+            desktop/dist/*.dmg
+            desktop/dist/*.zip
+            desktop/dist/*.exe
+          )
+          if [ ${#files[@]} -eq 0 ]; then
+            echo "No desktop artifacts found to rename." >&2
+            exit 1
+          fi
+          for src in "${files[@]}"; do
+            file="$(basename "$src")"
+            case "$file" in
+              *.AppImage)
+                dest="$out_dir/${NAME_PREFIX}.AppImage"
+                ;;
+              *.dmg)
+                dest="$out_dir/${NAME_PREFIX}.dmg"
+                ;;
+              *.exe)
+                dest="$out_dir/${NAME_PREFIX}.exe"
+                ;;
+              *.zip)
+                dest="$out_dir/${NAME_PREFIX}.zip"
+                ;;
+              *)
+                continue
+                ;;
+            esac
+            cp "$src" "$dest"
+          done
+          ls -la "$out_dir"
+
+      - name: Upload desktop artifacts
+        uses: actions/upload-artifact@v6
+        with:
+          name: AstrBot-${{ steps.tag.outputs.tag }}-${{ matrix.arch }}-${{ matrix.os }}
+          if-no-files-found: error
+          path: desktop/dist/release/*
+
+  publish-release:
+    name: Publish Release Assets
+    runs-on: ubuntu-24.04
+    needs: build-desktop
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+          ref: ${{ inputs.ref || github.ref }}
+
+      - name: Resolve release tag
+        id: tag
+        shell: bash
+        run: |
+          if [ "${{ github.event_name }}" = "push" ]; then
+            tag="${GITHUB_REF_NAME}"
+          elif [ -n "${{ inputs.tag }}" ]; then
+            tag="${{ inputs.tag }}"
+          else
+            tag="$(git describe --tags --abbrev=0)"
+          fi
+          if [ -z "$tag" ]; then
+            echo "Failed to resolve release tag." >&2
+            exit 1
+          fi
+          echo "tag=$tag" >> "$GITHUB_OUTPUT"
+
+      - name: Download built artifacts
+        uses: actions/download-artifact@v6
+        with:
+          pattern: AstrBot-${{ steps.tag.outputs.tag }}-*
+          path: release-assets
+          merge-multiple: true
+
+      - name: Ensure release exists
+        env:
+          GH_TOKEN: ${{ github.token }}
+        shell: bash
+        run: |
+          tag="${{ steps.tag.outputs.tag }}"
+          if ! gh release view "$tag" >/dev/null 2>&1; then
+            gh release create "$tag" --title "$tag" --notes ""
+          fi
+
+      - name: Remove stale desktop assets from release
+        env:
+          GH_TOKEN: ${{ github.token }}
+        shell: bash
+        run: |
+          tag="${{ steps.tag.outputs.tag }}"
+          while IFS= read -r asset; do
+            case "$asset" in
+              *.AppImage|*.dmg|*.zip|*.exe|*.blockmap)
+                gh release delete-asset "$tag" "$asset" -y || true
+                ;;
+            esac
+          done < <(gh release view "$tag" --json assets --jq '.assets[].name')
+
+      - name: Upload assets to release
+        env:
+          GH_TOKEN: ${{ github.token }}
+        shell: bash
+        run: |
+          tag="${{ steps.tag.outputs.tag }}"
+          gh release upload "$tag" release-assets/* --clobber
@@ -32,8 +32,15 @@ tests/astrbot_plugin_openai
 # Dashboard
 dashboard/node_modules/
 dashboard/dist/
+.pnpm-store/
+desktop/node_modules/
+desktop/dist/
+desktop/out/
+desktop/resources/backend/astrbot-backend*
+desktop/resources/backend/*.exe
+desktop/resources/webui/*
+desktop/resources/.pyinstaller/
 package-lock.json
-package.json
 yarn.lock

 # Operating System
@@ -53,4 +60,4 @@ IFLOW.md

 # genie_tts data
 CharacterModels/
-GenieData/
+GenieData/
@@ -1 +1 @@
-3.10
+3.12
@@ -26,6 +26,7 @@ Runs on `http://localhost:3000` by default.
 3. After finishing, use `ruff format .` and `ruff check .` to format and check the code.
 4. When committing, ensure to use conventional commits messages, such as `feat: add new agent for data analysis` or `fix: resolve bug in provider manager`.
 5. Use English for all new comments.
+6. For path handling, use `pathlib.Path` instead of string paths, and use `astrbot.core.utils.path_utils` to get the AstrBot data and temp directory.

 ## PR instructions

@@ -1,18 +0,0 @@
-我需要让 Agent 能够在未来提醒自己去做某些事情，这样 Agent 能够主动地去完成一些任务，而不是等用户主动来下达命令。
-
-你需要实现一个 CronJob 系统，允许 Agent 创建未来任务，并且在未来的某个时间点自动触发这些任务的执行.
-
-CronJob 系统分为 BasicCronJob 和 ActiveAgentCronJob 两种类型。前者只是简单的提供一个定时任务功能（给插件用），而后者则允许 Agent 主动地去完成一些任务。BasicCronJob 不必多说，就是定时执行某个函数。对于 ActiveAgentCronJob，Agent 应该可以主动管理（比如通过Tool来管理）这些 CronJobs，当添加的时候，Agent 可以给 CronJob 捎一段文字，以说明未来的自己需要做什么事情。比如说，Agent 在听到用户 “每天早上都给我整理一份今日早报” 之后，应该可以创建 Cron Job，并且自己写脚本来完成这个任务，并且注册 cron job。Agent 给未来的自己捎去的信息应该只是呈现为一段文字，这样可以保持设计简约。当触发后， CronJobManager 会调用 MainAgent 的一轮循环，MainAgent 通过上下文知道这是一个定时任务触发的循环，从而执行相应的操作。
-
-此外，我还有一个需求，后台长任务。需要给当前的 FunctionTool 类增加一个属性，is_background_task: bool = False，插件可以通过这个属性来声明这是一个异步任务。这是为了解决一些 Tool 需要长时间运行的问题，比如 Deep Search tool 需要长时间搜索网页内容、Sub Agent 需要长时间运行来完成一个复杂任务。
-
-基于上面的讨论，我觉得，应该：
-
-1. 需要给当前的 FunctionTool 类增加一个属性is_background_task: bool = False，tool runner 在执行这个 tool 的时候，如果发现是后台任务，就不等待结果返回，而是直接返回一个任务 ID （已经创建成功提示）的结果，tool runner 在后台继续执行这个任务。当任务完成之后，任务的结果回传给 MainAgent（其实就是再执行一次 main agent loop，但是上下文应该是最新的），并且 MainAgent 此时应该有 send_message_to_user 的工具，通过这个工具可以选择是否主动通知用户任务完成的结果。
-2. 增加一个 CronJobManager 类，负责管理所有的定时任务。Agent 可以通过调用这个类的方法来创建、删除、修改定时任务。通过 cron expression 来定义触发条件。
-3. CronJobManager 除了管理普通的定时任务（比如插件可能有一些自己的定时任务），还有一种特殊的任务类型，就是上面提到的主动型 Agent 任务。用户提需求，MainAgent 选择性地调用 CronJobManager 的方法来创建这些任务，并且在任务触发时，CronJobManager 的回调就是执行 MainAgent 的一轮循环（需要加 send_message_to_user tool），MainAgent 通过上下文知道这是一个定时任务触发的循环，从而执行相应的操作。
-4. WebUI 需要增加 Cron Job 管理界面，用户可以在界面上查看、创建、修改、删除定时任务。对于主动型 Agent 任务，用户可以看到任务的描述、触发条件等信息。
-5. 除此之外，现在的代码中已经有了 subagent 的管理。WebUI 可以创建 SubAgent，但是还没写完。除了结合上面我说的之外，你还需要将 SubAgent 与 Persona 结合起来——因为 Persona 是一个包含了 tool、skills、name、description 的完整体，所以 SubAgent 应该直接继承 Persona 的定义，而不是单独定义 SubAgent。SubAgent 本质上就是一个有特定角色和能力的 Persona！多么美妙的设计啊！
-6. 为了实现大一统，is_background_task = True 的时候，后台任务也挂到 CronJobManager 上去管理，只不过这个是立即触发的任务，不需要等到未来某个时间点才触发罢了。
-
-我希望设计尽可能简单，但是强大。
@@ -1,4 +1,4 @@
-FROM python:3.11-slim
+FROM python:3.12-slim
 WORKDIR /AstrBot

 COPY . /AstrBot/
@@ -23,7 +23,7 @@ RUN apt-get update && apt-get install -y curl gnupg \
    && apt-get install -y nodejs

 RUN python -m pip install uv \
-    && echo "3.11" > .python-version
+    && echo "3.12" > .python-version
 RUN uv pip install -r requirements.txt --no-cache-dir --system
 RUN uv pip install socksio uv pilk --no-cache-dir --system

@@ -132,6 +132,10 @@ uv run main.py

 或者请参阅官方文档 [通过源码部署 AstrBot](https://astrbot.app/deploy/astrbot/cli.html) 。

+#### 桌面端 Electron 打包
+
+桌面端（Electron 打包，`pnpm` 工作流）构建流程请参阅：[`desktop/README.md`](desktop/README.md)。
+
 ## 支持的消息平台

 **官方维护**
@@ -264,8 +268,8 @@ pre-commit install

 <div align="center">

+_陪伴与能力从来不应该是对立面。我们希望创造的是一个既能理解情绪、给予陪伴，也能可靠完成工作的机器人。_
+
 _私は、高性能ですから!_

-陪伴与能力从来不应该是对立面。我们希望创造的是一个既能理解情绪、给予陪伴，也能可靠完成工作的机器人。
-
-
+<img src="https://files.astrbot.app/watashiwa-koseino-desukara.gif" width="100"/>
@@ -117,6 +117,10 @@ uv run main.py

 Or refer to the official documentation: [Deploy AstrBot from Source](https://astrbot.app/deploy/astrbot/cli.html).

+#### Desktop Electron Build
+
+For desktop build steps (Electron packaging, `pnpm` workflow), see [`desktop/README.md`](desktop/README.md).
+
 ## Supported Messaging Platforms

 **Officially Maintained**
@@ -23,6 +23,7 @@ class Main(star.Star):
        "fetch_url",
        "web_search_tavily",
        "tavily_extract_web_page",
+        "web_search_bocha",
    ]

    def __init__(self, context: star.Context) -> None:
@@ -30,6 +31,9 @@ class Main(star.Star):
        self.tavily_key_index = 0
        self.tavily_key_lock = asyncio.Lock()

+        self.bocha_key_index = 0
+        self.bocha_key_lock = asyncio.Lock()
+
        # 将 str 类型的 key 迁移至 list[str]，并保存
        cfg = self.context.get_config()
        provider_settings = cfg.get("provider_settings")
@@ -45,6 +49,14 @@ class Main(star.Star):
                    provider_settings["websearch_tavily_key"] = []
                cfg.save_config()

+            bocha_key = provider_settings.get("websearch_bocha_key")
+            if isinstance(bocha_key, str):
+                if bocha_key:
+                    provider_settings["websearch_bocha_key"] = [bocha_key]
+                else:
+                    provider_settings["websearch_bocha_key"] = []
+                cfg.save_config()
+
        self.bing_search = Bing()
        self.sogo_search = Sogo()
        self.baidu_initialized = False
@@ -341,7 +353,7 @@ class Main(star.Star):
                }
            )
            if result.favicon:
-                sp.temorary_cache["_ws_favicon"][result.url] = result.favicon
+                sp.temporary_cache["_ws_favicon"][result.url] = result.favicon
        # ret = "\n".join(ret_ls)
        ret = json.dumps({"results": ret_ls}, ensure_ascii=False)
        return ret
@@ -382,6 +394,160 @@ class Main(star.Star):
            return "Error: Tavily web searcher does not return any results."
        return ret

+    async def _get_bocha_key(self, cfg: AstrBotConfig) -> str:
+        """并发安全的从列表中获取并轮换BoCha API密钥。"""
+        bocha_keys = cfg.get("provider_settings", {}).get("websearch_bocha_key", [])
+        if not bocha_keys:
+            raise ValueError("错误：BoCha API密钥未在AstrBot中配置。")
+
+        async with self.bocha_key_lock:
+            key = bocha_keys[self.bocha_key_index]
+            self.bocha_key_index = (self.bocha_key_index + 1) % len(bocha_keys)
+            return key
+
+    async def _web_search_bocha(
+        self,
+        cfg: AstrBotConfig,
+        payload: dict,
+    ) -> list[SearchResult]:
+        """使用 BoCha 搜索引擎进行搜索"""
+        bocha_key = await self._get_bocha_key(cfg)
+        url = "https://api.bochaai.com/v1/web-search"
+        header = {
+            "Authorization": f"Bearer {bocha_key}",
+            "Content-Type": "application/json",
+        }
+        async with aiohttp.ClientSession(trust_env=True) as session:
+            async with session.post(
+                url,
+                json=payload,
+                headers=header,
+            ) as response:
+                if response.status != 200:
+                    reason = await response.text()
+                    raise Exception(
+                        f"BoCha web search failed: {reason}, status: {response.status}",
+                    )
+                data = await response.json()
+                data = data["data"]["webPages"]["value"]
+                results = []
+                for item in data:
+                    result = SearchResult(
+                        title=item.get("name"),
+                        url=item.get("url"),
+                        snippet=item.get("snippet"),
+                        favicon=item.get("siteIcon"),
+                    )
+                    results.append(result)
+                return results
+
+    @llm_tool("web_search_bocha")
+    async def search_from_bocha(
+        self,
+        event: AstrMessageEvent,
+        query: str,
+        freshness: str = "noLimit",
+        summary: bool = False,
+        include: str = "",
+        exclude: str = "",
+        count: int = 10,
+    ) -> str:
+        """
+        A web search tool based on Bocha Search API, used to retrieve web pages
+        related to the user's query.
+
+        Args:
+            query (string): Required. User's search query.
+
+            freshness (string): Optional. Specifies the time range of the search.
+                Supported values:
+                - "noLimit": No time limit (default, recommended).
+                - "oneDay": Within one day.
+                - "oneWeek": Within one week.
+                - "oneMonth": Within one month.
+                - "oneYear": Within one year.
+                - "YYYY-MM-DD..YYYY-MM-DD": Search within a specific date range.
+                  Example: "2025-01-01..2025-04-06".
+                - "YYYY-MM-DD": Search on a specific date.
+                  Example: "2025-04-06".
+                It is recommended to use "noLimit", as the search algorithm will
+                automatically optimize time relevance. Manually restricting the
+                time range may result in no search results.
+
+            summary (boolean): Optional. Whether to include a text summary
+                for each search result.
+                - True: Include summary.
+                - False: Do not include summary (default).
+
+            include (string): Optional. Specifies the domains to include in
+                the search. Multiple domains can be separated by "|" or ",".
+                A maximum of 100 domains is allowed.
+                Examples:
+                - "qq.com"
+                - "qq.com|m.163.com"
+
+            exclude (string): Optional. Specifies the domains to exclude from
+                the search. Multiple domains can be separated by "|" or ",".
+                A maximum of 100 domains is allowed.
+                Examples:
+                - "qq.com"
+                - "qq.com|m.163.com"
+
+            count (number): Optional. Number of search results to return.
+                - Range: 1–50
+                - Default: 10
+                The actual number of returned results may be less than the
+                specified count.
+        """
+        logger.info(f"web_searcher - search_from_bocha: {query}")
+        cfg = self.context.get_config(umo=event.unified_msg_origin)
+        # websearch_link = cfg["provider_settings"].get("web_search_link", False)
+        if not cfg.get("provider_settings", {}).get("websearch_bocha_key", []):
+            raise ValueError("Error: BoCha API key is not configured in AstrBot.")
+
+        # build payload
+        payload = {
+            "query": query,
+            "count": count,
+        }
+
+        # freshness：时间范围
+        if freshness:
+            payload["freshness"] = freshness
+
+        # 是否返回摘要
+        payload["summary"] = summary
+
+        # include：限制搜索域
+        if include:
+            payload["include"] = include
+
+        # exclude：排除搜索域
+        if exclude:
+            payload["exclude"] = exclude
+
+        results = await self._web_search_bocha(cfg, payload)
+        if not results:
+            return "Error: BoCha web searcher does not return any results."
+
+        ret_ls = []
+        ref_uuid = str(uuid.uuid4())[:4]
+        for idx, result in enumerate(results, 1):
+            index = f"{ref_uuid}.{idx}"
+            ret_ls.append(
+                {
+                    "title": f"{result.title}",
+                    "url": f"{result.url}",
+                    "snippet": f"{result.snippet}",
+                    "index": index,
+                }
+            )
+            if result.favicon:
+                sp.temporary_cache["_ws_favicon"][result.url] = result.favicon
+        # ret = "\n".join(ret_ls)
+        ret = json.dumps({"results": ret_ls}, ensure_ascii=False)
+        return ret
+
    @filter.on_llm_request(priority=-10000)
    async def edit_web_search_tools(
        self,
@@ -419,6 +585,7 @@ class Main(star.Star):
            tool_set.remove_tool("web_search_tavily")
            tool_set.remove_tool("tavily_extract_web_page")
            tool_set.remove_tool("AIsearch")
+            tool_set.remove_tool("web_search_bocha")
        elif provider == "tavily":
            web_search_tavily = func_tool_mgr.get_func("web_search_tavily")
            tavily_extract_web_page = func_tool_mgr.get_func("tavily_extract_web_page")
@@ -429,6 +596,7 @@ class Main(star.Star):
            tool_set.remove_tool("web_search")
            tool_set.remove_tool("fetch_url")
            tool_set.remove_tool("AIsearch")
+            tool_set.remove_tool("web_search_bocha")
        elif provider == "baidu_ai_search":
            try:
                await self.ensure_baidu_ai_search_mcp(event.unified_msg_origin)
@@ -440,5 +608,15 @@ class Main(star.Star):
                tool_set.remove_tool("fetch_url")
                tool_set.remove_tool("web_search_tavily")
                tool_set.remove_tool("tavily_extract_web_page")
+                tool_set.remove_tool("web_search_bocha")
            except Exception as e:
                logger.error(f"Cannot Initialize Baidu AI Search MCP Server: {e}")
+        elif provider == "bocha":
+            web_search_bocha = func_tool_mgr.get_func("web_search_bocha")
+            if web_search_bocha:
+                tool_set.add_tool(web_search_bocha)
+            tool_set.remove_tool("web_search")
+            tool_set.remove_tool("fetch_url")
+            tool_set.remove_tool("AIsearch")
+            tool_set.remove_tool("web_search_tavily")
+            tool_set.remove_tool("tavily_extract_web_page")
@@ -1 +1 @@
-__version__ = "4.14.2"
+__version__ = "4.14.7"
@@ -3,7 +3,13 @@

 from typing import Any, ClassVar, Literal, cast

-from pydantic import BaseModel, GetCoreSchemaHandler, model_serializer, model_validator
+from pydantic import (
+    BaseModel,
+    GetCoreSchemaHandler,
+    PrivateAttr,
+    model_serializer,
+    model_validator,
+)
 from pydantic_core import core_schema


@@ -178,6 +184,8 @@ class Message(BaseModel):
    tool_call_id: str | None = None
    """The ID of the tool call."""

+    _no_save: bool = PrivateAttr(default=False)
+
    @model_validator(mode="after")
    def check_content_required(self):
        # assistant + tool_calls is not None: allow content to be None
@@ -3,6 +3,7 @@ import sys
 import time
 import traceback
 import typing as T
+from dataclasses import dataclass

 from mcp.types import (
    BlobResourceContents,
@@ -14,8 +15,9 @@ from mcp.types import (
 )

 from astrbot import logger
-from astrbot.core.agent.message import TextPart, ThinkPart
+from astrbot.core.agent.message import ImageURLPart, TextPart, ThinkPart
 from astrbot.core.agent.tool import ToolSet
+from astrbot.core.agent.tool_image_cache import tool_image_cache
 from astrbot.core.message.components import Json
 from astrbot.core.message.message_event_result import (
    MessageChain,
@@ -44,6 +46,28 @@ else:
    from typing_extensions import override


+@dataclass(slots=True)
+class _HandleFunctionToolsResult:
+    kind: T.Literal["message_chain", "tool_call_result_blocks", "cached_image"]
+    message_chain: MessageChain | None = None
+    tool_call_result_blocks: list[ToolCallMessageSegment] | None = None
+    cached_image: T.Any = None
+
+    @classmethod
+    def from_message_chain(cls, chain: MessageChain) -> "_HandleFunctionToolsResult":
+        return cls(kind="message_chain", message_chain=chain)
+
+    @classmethod
+    def from_tool_call_result_blocks(
+        cls, blocks: list[ToolCallMessageSegment]
+    ) -> "_HandleFunctionToolsResult":
+        return cls(kind="tool_call_result_blocks", tool_call_result_blocks=blocks)
+
+    @classmethod
+    def from_cached_image(cls, image: T.Any) -> "_HandleFunctionToolsResult":
+        return cls(kind="cached_image", cached_image=image)
+
+
 class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
    @override
    async def reset(
@@ -125,7 +149,10 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
        messages = []
        # append existing messages in the run context
        for msg in request.contexts:
-            messages.append(Message.model_validate(msg))
+            m = Message.model_validate(msg)
+            if isinstance(msg, dict) and msg.get("_no_save"):
+                m._no_save = True
+            messages.append(m)
        if request.prompt is not None:
            m = await request.assemble_context()
            messages.append(Message.model_validate(m))
@@ -213,6 +240,8 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
            if not llm_response.is_chunk and llm_response.usage:
                # only count the token usage of the final response for computation purpose
                self.stats.token_usage += llm_response.usage
+                if self.req.conversation:
+                    self.req.conversation.token_usage = llm_response.usage.total
            break  # got final response

        if not llm_resp_result:
@@ -252,6 +281,10 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                )
            if llm_resp.completion_text:
                parts.append(TextPart(text=llm_resp.completion_text))
+            if len(parts) == 0:
+                logger.warning(
+                    "LLM returned empty assistant message with no tool calls."
+                )
            self.run_context.messages.append(Message(role="assistant", content=parts))

            # call the on_agent_done hook
@@ -280,20 +313,27 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                llm_resp, _ = await self._resolve_tool_exec(llm_resp)

            tool_call_result_blocks = []
+            cached_images = []  # Collect cached images for LLM visibility
            async for result in self._handle_function_tools(self.req, llm_resp):
-                if isinstance(result, list):
-                    tool_call_result_blocks = result
-                elif isinstance(result, MessageChain):
-                    if result.type is None:
+                if result.kind == "tool_call_result_blocks":
+                    if result.tool_call_result_blocks is not None:
+                        tool_call_result_blocks = result.tool_call_result_blocks
+                elif result.kind == "cached_image":
+                    if result.cached_image is not None:
+                        # Collect cached image info
+                        cached_images.append(result.cached_image)
+                elif result.kind == "message_chain":
+                    chain = result.message_chain
+                    if chain is None or chain.type is None:
                        # should not happen
                        continue
-                    if result.type == "tool_direct_result":
+                    if chain.type == "tool_direct_result":
                        ar_type = "tool_call_result"
                    else:
-                        ar_type = result.type
+                        ar_type = chain.type
                    yield AgentResponse(
                        type=ar_type,
-                        data=AgentResponseData(chain=result),
+                        data=AgentResponseData(chain=chain),
                    )

            # 将结果添加到上下文中
@@ -307,6 +347,8 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                )
            if llm_resp.completion_text:
                parts.append(TextPart(text=llm_resp.completion_text))
+            if len(parts) == 0:
+                parts = None
            tool_calls_result = ToolCallsResult(
                tool_calls_info=AssistantMessageSegment(
                    tool_calls=llm_resp.to_openai_to_calls_model(),
@@ -319,6 +361,41 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                tool_calls_result.to_openai_messages_model()
            )

+            # If there are cached images and the model supports image input,
+            # append a user message with images so LLM can see them
+            if cached_images:
+                modalities = self.provider.provider_config.get("modalities", [])
+                supports_image = "image" in modalities
+                if supports_image:
+                    # Build user message with images for LLM to review
+                    image_parts = []
+                    for cached_img in cached_images:
+                        img_data = tool_image_cache.get_image_base64_by_path(
+                            cached_img.file_path, cached_img.mime_type
+                        )
+                        if img_data:
+                            base64_data, mime_type = img_data
+                            image_parts.append(
+                                TextPart(
+                                    text=f"[Image from tool '{cached_img.tool_name}', path='{cached_img.file_path}']"
+                                )
+                            )
+                            image_parts.append(
+                                ImageURLPart(
+                                    image_url=ImageURLPart.ImageURL(
+                                        url=f"data:{mime_type};base64,{base64_data}",
+                                        id=cached_img.file_path,
+                                    )
+                                )
+                            )
+                    if image_parts:
+                        self.run_context.messages.append(
+                            Message(role="user", content=image_parts)
+                        )
+                        logger.debug(
+                            f"Appended {len(cached_images)} cached image(s) to context for LLM review"
+                        )
+
            self.req.append_tool_calls_result(tool_calls_result)

    async def step_until_done(
@@ -354,7 +431,7 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
        self,
        req: ProviderRequest,
        llm_response: LLMResponse,
-    ) -> T.AsyncGenerator[MessageChain | list[ToolCallMessageSegment], None]:
+    ) -> T.AsyncGenerator[_HandleFunctionToolsResult, None]:
        """处理函数工具调用。"""
        tool_call_result_blocks: list[ToolCallMessageSegment] = []
        logger.info(f"Agent 使用工具: {llm_response.tools_call_name}")
@@ -365,18 +442,20 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
            llm_response.tools_call_args,
            llm_response.tools_call_ids,
        ):
-            yield MessageChain(
-                type="tool_call",
-                chain=[
-                    Json(
-                        data={
-                            "id": func_tool_id,
-                            "name": func_tool_name,
-                            "args": func_tool_args,
-                            "ts": time.time(),
-                        }
-                    )
-                ],
+            yield _HandleFunctionToolsResult.from_message_chain(
+                MessageChain(
+                    type="tool_call",
+                    chain=[
+                        Json(
+                            data={
+                                "id": func_tool_id,
+                                "name": func_tool_name,
+                                "args": func_tool_args,
+                                "ts": time.time(),
+                            }
+                        )
+                    ],
+                )
            )
            try:
                if not req.func_tool:
@@ -462,15 +541,28 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                                ),
                            )
                        elif isinstance(res.content[0], ImageContent):
+                            # Cache the image instead of sending directly
+                            cached_img = tool_image_cache.save_image(
+                                base64_data=res.content[0].data,
+                                tool_call_id=func_tool_id,
+                                tool_name=func_tool_name,
+                                index=0,
+                                mime_type=res.content[0].mimeType or "image/png",
+                            )
                            tool_call_result_blocks.append(
                                ToolCallMessageSegment(
                                    role="tool",
                                    tool_call_id=func_tool_id,
-                                    content="The tool has successfully returned an image and sent directly to the user. You can describe it in your next response.",
+                                    content=(
+                                        f"Image returned and cached at path='{cached_img.file_path}'. "
+                                        f"Review the image below. Use send_message_to_user to send it to the user if satisfied, "
+                                        f"with type='image' and path='{cached_img.file_path}'."
+                                    ),
                                ),
                            )
-                            yield MessageChain(type="tool_direct_result").base64_image(
-                                res.content[0].data,
+                            # Yield image info for LLM visibility (will be handled in step())
+                            yield _HandleFunctionToolsResult.from_cached_image(
+                                cached_img
                            )
                        elif isinstance(res.content[0], EmbeddedResource):
                            resource = res.content[0].resource
@@ -487,16 +579,29 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
                                and resource.mimeType
                                and resource.mimeType.startswith("image/")
                            ):
+                                # Cache the image instead of sending directly
+                                cached_img = tool_image_cache.save_image(
+                                    base64_data=resource.blob,
+                                    tool_call_id=func_tool_id,
+                                    tool_name=func_tool_name,
+                                    index=0,
+                                    mime_type=resource.mimeType,
+                                )
                                tool_call_result_blocks.append(
                                    ToolCallMessageSegment(
                                        role="tool",
                                        tool_call_id=func_tool_id,
-                                        content="The tool has successfully returned an image and sent directly to the user. You can describe it in your next response.",
+                                        content=(
+                                            f"Image returned and cached at path='{cached_img.file_path}'. "
+                                            f"Review the image below. Use send_message_to_user to send it to the user if satisfied, "
+                                            f"with type='image' and path='{cached_img.file_path}'."
+                                        ),
                                    ),
                                )
-                                yield MessageChain(
-                                    type="tool_direct_result",
-                                ).base64_image(resource.blob)
+                                # Yield image info for LLM visibility
+                                yield _HandleFunctionToolsResult.from_cached_image(
+                                    cached_img
+                                )
                            else:
                                tool_call_result_blocks.append(
                                    ToolCallMessageSegment(
@@ -557,23 +662,27 @@ class ToolLoopAgentRunner(BaseAgentRunner[TContext]):
        # yield the last tool call result
        if tool_call_result_blocks:
            last_tcr_content = str(tool_call_result_blocks[-1].content)
-            yield MessageChain(
-                type="tool_call_result",
-                chain=[
-                    Json(
-                        data={
-                            "id": func_tool_id,
-                            "ts": time.time(),
-                            "result": last_tcr_content,
-                        }
-                    )
-                ],
+            yield _HandleFunctionToolsResult.from_message_chain(
+                MessageChain(
+                    type="tool_call_result",
+                    chain=[
+                        Json(
+                            data={
+                                "id": func_tool_id,
+                                "ts": time.time(),
+                                "result": last_tcr_content,
+                            }
+                        )
+                    ],
+                )
            )
            logger.info(f"Tool `{func_tool_name}` Result: {last_tcr_content}")

        # 处理函数调用响应
        if tool_call_result_blocks:
-            yield tool_call_result_blocks
+            yield _HandleFunctionToolsResult.from_tool_call_result_blocks(
+                tool_call_result_blocks
+            )

    def _build_tool_requery_context(
        self, tool_names: list[str]
@@ -246,8 +246,18 @@ class ToolSet:

            result = {}

-            if "type" in schema and schema["type"] in supported_types:
-                result["type"] = schema["type"]
+            # Avoid side effects by not modifying the original schema
+            origin_type = schema.get("type")
+            target_type = origin_type
+
+            # Compatibility fix: Gemini API expects 'type' to be a string (enum),
+            # but standard JSON Schema (MCP) allows lists (e.g. ["string", "null"]).
+            # We fallback to the first non-null type.
+            if isinstance(origin_type, list):
+                target_type = next((t for t in origin_type if t != "null"), "string")
+
+            if target_type in supported_types:
+                result["type"] = target_type
                if "format" in schema and schema["format"] in supported_formats.get(
                    result["type"],
                    set(),
@@ -0,0 +1,162 @@
+"""Tool image cache module for storing and retrieving images returned by tools.
+
+This module allows LLM to review images before deciding whether to send them to users.
+"""
+
+import base64
+import os
+import time
+from dataclasses import dataclass, field
+from typing import ClassVar
+
+from astrbot import logger
+from astrbot.core.utils.astrbot_path import get_astrbot_temp_path
+
+
+@dataclass
+class CachedImage:
+    """Represents a cached image from a tool call."""
+
+    tool_call_id: str
+    """The tool call ID that produced this image."""
+    tool_name: str
+    """The name of the tool that produced this image."""
+    file_path: str
+    """The file path where the image is stored."""
+    mime_type: str
+    """The MIME type of the image."""
+    created_at: float = field(default_factory=time.time)
+    """Timestamp when the image was cached."""
+
+
+class ToolImageCache:
+    """Manages cached images from tool calls.
+
+    Images are stored in data/temp/tool_images/ and can be retrieved by file path.
+    """
+
+    _instance: ClassVar["ToolImageCache | None"] = None
+    CACHE_DIR_NAME: ClassVar[str] = "tool_images"
+    # Cache expiry time in seconds (1 hour)
+    CACHE_EXPIRY: ClassVar[int] = 3600
+
+    def __new__(cls) -> "ToolImageCache":
+        if cls._instance is None:
+            cls._instance = super().__new__(cls)
+            cls._instance._initialized = False
+        return cls._instance
+
+    def __init__(self) -> None:
+        if self._initialized:
+            return
+        self._initialized = True
+        self._cache_dir = os.path.join(get_astrbot_temp_path(), self.CACHE_DIR_NAME)
+        os.makedirs(self._cache_dir, exist_ok=True)
+        logger.debug(f"ToolImageCache initialized, cache dir: {self._cache_dir}")
+
+    def _get_file_extension(self, mime_type: str) -> str:
+        """Get file extension from MIME type."""
+        mime_to_ext = {
+            "image/png": ".png",
+            "image/jpeg": ".jpg",
+            "image/jpg": ".jpg",
+            "image/gif": ".gif",
+            "image/webp": ".webp",
+            "image/bmp": ".bmp",
+            "image/svg+xml": ".svg",
+        }
+        return mime_to_ext.get(mime_type.lower(), ".png")
+
+    def save_image(
+        self,
+        base64_data: str,
+        tool_call_id: str,
+        tool_name: str,
+        index: int = 0,
+        mime_type: str = "image/png",
+    ) -> CachedImage:
+        """Save an image to cache and return the cached image info.
+
+        Args:
+            base64_data: Base64 encoded image data.
+            tool_call_id: The tool call ID that produced this image.
+            tool_name: The name of the tool that produced this image.
+            index: The index of the image (for multiple images from same tool call).
+            mime_type: The MIME type of the image.
+
+        Returns:
+            CachedImage object with file path.
+        """
+        ext = self._get_file_extension(mime_type)
+        file_name = f"{tool_call_id}_{index}{ext}"
+        file_path = os.path.join(self._cache_dir, file_name)
+
+        # Decode and save the image
+        try:
+            image_bytes = base64.b64decode(base64_data)
+            with open(file_path, "wb") as f:
+                f.write(image_bytes)
+            logger.debug(f"Saved tool image to: {file_path}")
+        except Exception as e:
+            logger.error(f"Failed to save tool image: {e}")
+            raise
+
+        return CachedImage(
+            tool_call_id=tool_call_id,
+            tool_name=tool_name,
+            file_path=file_path,
+            mime_type=mime_type,
+        )
+
+    def get_image_base64_by_path(
+        self, file_path: str, mime_type: str = "image/png"
+    ) -> tuple[str, str] | None:
+        """Read an image file and return its base64 encoded data.
+
+        Args:
+            file_path: The file path of the cached image.
+            mime_type: The MIME type of the image.
+
+        Returns:
+            Tuple of (base64_data, mime_type) if found, None otherwise.
+        """
+        if not os.path.exists(file_path):
+            return None
+
+        try:
+            with open(file_path, "rb") as f:
+                image_bytes = f.read()
+            base64_data = base64.b64encode(image_bytes).decode("utf-8")
+            return base64_data, mime_type
+        except Exception as e:
+            logger.error(f"Failed to read cached image {file_path}: {e}")
+            return None
+
+    def cleanup_expired(self) -> int:
+        """Clean up expired cached images.
+
+        Returns:
+            Number of images cleaned up.
+        """
+        now = time.time()
+        cleaned = 0
+
+        try:
+            for file_name in os.listdir(self._cache_dir):
+                file_path = os.path.join(self._cache_dir, file_name)
+                if os.path.isfile(file_path):
+                    file_age = now - os.path.getmtime(file_path)
+                    if file_age > self.CACHE_EXPIRY:
+                        os.remove(file_path)
+                        cleaned += 1
+        except Exception as e:
+            logger.warning(f"Error during cache cleanup: {e}")
+
+        if cleaned:
+            logger.info(f"Cleaned up {cleaned} expired cached images")
+
+        return cleaned
+
+
+# Global singleton instance
+tool_image_cache = ToolImageCache()
@@ -59,7 +59,7 @@ class MainAgentHooks(BaseAgentRunHooks[AstrAgentContext]):
        platform_name = run_context.context.event.get_platform_name()
        if (
            platform_name == "webchat"
-            and tool.name == "web_search_tavily"
+            and tool.name in ["web_search_tavily", "web_search_bocha"]
            and len(run_context.messages) > 0
            and tool_result
            and len(tool_result.content)
@@ -7,6 +7,7 @@ import datetime
 import json
 import os
 import zoneinfo
+from collections.abc import Coroutine
 from dataclasses import dataclass, field

 from astrbot.api import sp
@@ -114,6 +115,7 @@ class MainAgentBuildResult:
    agent_runner: AgentRunner
    provider_request: ProviderRequest
    provider: Provider
+    reset_coro: Coroutine | None = None


 def _select_provider(
@@ -837,8 +839,12 @@ async def build_main_agent(
    config: MainAgentBuildConfig,
    provider: Provider | None = None,
    req: ProviderRequest | None = None,
+    apply_reset: bool = True,
 ) -> MainAgentBuildResult | None:
-    """构建主对话代理（Main Agent），并且自动 reset。"""
+    """构建主对话代理（Main Agent），并且自动 reset。
+
+    If apply_reset is False, will not call reset on the agent runner.
+    """
    provider = provider or _select_provider(event, plugin_context)
    if provider is None:
        logger.info("未找到任何对话模型（提供商），跳过 LLM 请求处理。")
@@ -955,7 +961,7 @@ async def build_main_agent(
    if action_type == "live":
        req.system_prompt += f"\n{LIVE_MODE_SYSTEM_PROMPT}\n"

-    await agent_runner.reset(
+    reset_coro = agent_runner.reset(
        provider=provider,
        request=req,
        run_context=AgentContextWrapper(
@@ -973,8 +979,12 @@ async def build_main_agent(
        tool_schema_mode=config.tool_schema_mode,
    )

+    if apply_reset:
+        await reset_coro
+
    return MainAgentBuildResult(
        agent_runner=agent_runner,
        provider_request=req,
        provider=provider,
+        reset_coro=reset_coro if not apply_reset else None,
    )
@@ -5,7 +5,7 @@ from typing import Any, TypedDict

 from astrbot.core.utils.astrbot_path import get_astrbot_data_path

-VERSION = "4.14.2"
+VERSION = "4.14.7"
 DB_PATH = os.path.join(get_astrbot_data_path(), "data_v4.db")

 WEBHOOK_SUPPORTED_PLATFORMS = [
@@ -74,6 +74,7 @@ DEFAULT_CONFIG = {
        "web_search": False,
        "websearch_provider": "default",
        "websearch_tavily_key": [],
+        "websearch_bocha_key": [],
        "websearch_baidu_app_builder_key": "",
        "web_search_link": False,
        "display_reasoning_text": False,
@@ -176,7 +177,7 @@ DEFAULT_CONFIG = {
    "t2i_use_file_service": False,
    "t2i_active_template": "base",
    "http_proxy": "",
-    "no_proxy": ["localhost", "127.0.0.1", "::1"],
+    "no_proxy": ["localhost", "127.0.0.1", "::1", "10.*", "192.168.*"],
    "dashboard": {
        "enable": True,
        "username": "astrbot",
@@ -912,6 +913,7 @@ CONFIG_METADATA_2 = {
                        "key": [],
                        "api_base": "https://api.openai.com/v1",
                        "timeout": 120,
+                        "proxy": "",
                        "custom_headers": {},
                    },
                    "Google Gemini": {
@@ -934,6 +936,7 @@ CONFIG_METADATA_2 = {
                            "dangerous_content": "BLOCK_MEDIUM_AND_ABOVE",
                        },
                        "gm_thinking_config": {"budget": 0, "level": "HIGH"},
+                        "proxy": "",
                    },
                    "Anthropic": {
                        "id": "anthropic",
@@ -944,6 +947,7 @@ CONFIG_METADATA_2 = {
                        "key": [],
                        "api_base": "https://api.anthropic.com/v1",
                        "timeout": 120,
+                        "proxy": "",
                        "anth_thinking_config": {"budget": 0},
                    },
                    "Moonshot": {
@@ -955,6 +959,7 @@ CONFIG_METADATA_2 = {
                        "key": [],
                        "timeout": 120,
                        "api_base": "https://api.moonshot.cn/v1",
+                        "proxy": "",
                        "custom_headers": {},
                    },
                    "xAI": {
@@ -966,6 +971,7 @@ CONFIG_METADATA_2 = {
                        "key": [],
                        "api_base": "https://api.x.ai/v1",
                        "timeout": 120,
+                        "proxy": "",
                        "custom_headers": {},
                        "xai_native_search": False,
                    },
@@ -978,6 +984,7 @@ CONFIG_METADATA_2 = {
                        "key": [],
                        "api_base": "https://api.deepseek.com/v1",
                        "timeout": 120,
+                        "proxy": "",
                        "custom_headers": {},
                    },
                    "Zhipu": {
@@ -989,6 +996,7 @@ CONFIG_METADATA_2 = {
                        "key": [],
                        "timeout": 120,
                        "api_base": "https://open.bigmodel.cn/api/paas/v4/",
+                        "proxy": "",
                        "custom_headers": {},
                    },
                    "Azure OpenAI": {
@@ -1001,6 +1009,7 @@ CONFIG_METADATA_2 = {
                        "key": [],
                        "api_base": "",
                        "timeout": 120,
+                        "proxy": "",
                        "custom_headers": {},
                    },
                    "Ollama": {
@@ -1011,6 +1020,7 @@ CONFIG_METADATA_2 = {
                        "enable": True,
                        "key": ["ollama"],  # ollama 的 key 默认是 ollama
                        "api_base": "http://127.0.0.1:11434/v1",
+                        "proxy": "",
                        "custom_headers": {},
                    },
                    "LM Studio": {
@@ -1021,6 +1031,7 @@ CONFIG_METADATA_2 = {
                        "enable": True,
                        "key": ["lmstudio"],
                        "api_base": "http://127.0.0.1:1234/v1",
+                        "proxy": "",
                        "custom_headers": {},
                    },
                    "Gemini_OpenAI_API": {
@@ -1032,6 +1043,7 @@ CONFIG_METADATA_2 = {
                        "key": [],
                        "api_base": "https://generativelanguage.googleapis.com/v1beta/openai/",
                        "timeout": 120,
+                        "proxy": "",
                        "custom_headers": {},
                    },
                    "Groq": {
@@ -1043,6 +1055,7 @@ CONFIG_METADATA_2 = {
                        "key": [],
                        "api_base": "https://api.groq.com/openai/v1",
                        "timeout": 120,
+                        "proxy": "",
                        "custom_headers": {},
                    },
                    "302.AI": {
@@ -1054,6 +1067,7 @@ CONFIG_METADATA_2 = {
                        "key": [],
                        "api_base": "https://api.302.ai/v1",
                        "timeout": 120,
+                        "proxy": "",
                        "custom_headers": {},
                    },
                    "SiliconFlow": {
@@ -1065,6 +1079,7 @@ CONFIG_METADATA_2 = {
                        "key": [],
                        "timeout": 120,
                        "api_base": "https://api.siliconflow.cn/v1",
+                        "proxy": "",
                        "custom_headers": {},
                    },
                    "PPIO": {
@@ -1076,6 +1091,7 @@ CONFIG_METADATA_2 = {
                        "key": [],
                        "api_base": "https://api.ppinfra.com/v3/openai",
                        "timeout": 120,
+                        "proxy": "",
                        "custom_headers": {},
                    },
                    "TokenPony": {
@@ -1087,6 +1103,7 @@ CONFIG_METADATA_2 = {
                        "key": [],
                        "api_base": "https://api.tokenpony.cn/v1",
                        "timeout": 120,
+                        "proxy": "",
                        "custom_headers": {},
                    },
                    "Compshare": {
@@ -1098,6 +1115,7 @@ CONFIG_METADATA_2 = {
                        "key": [],
                        "api_base": "https://api.modelverse.cn/v1",
                        "timeout": 120,
+                        "proxy": "",
                        "custom_headers": {},
                    },
                    "ModelScope": {
@@ -1109,6 +1127,7 @@ CONFIG_METADATA_2 = {
                        "key": [],
                        "timeout": 120,
                        "api_base": "https://api-inference.modelscope.cn/v1",
+                        "proxy": "",
                        "custom_headers": {},
                    },
                    "Dify": {
@@ -1124,6 +1143,7 @@ CONFIG_METADATA_2 = {
                        "dify_query_input_key": "astrbot_text_query",
                        "variables": {},
                        "timeout": 60,
+                        "proxy": "",
                    },
                    "Coze": {
                        "id": "coze",
@@ -1135,6 +1155,7 @@ CONFIG_METADATA_2 = {
                        "bot_id": "",
                        "coze_api_base": "https://api.coze.cn",
                        "timeout": 60,
+                        "proxy": "",
                        # "auto_save_history": True,
                    },
                    "阿里云百炼应用": {
@@ -1153,6 +1174,7 @@ CONFIG_METADATA_2 = {
                        },
                        "variables": {},
                        "timeout": 60,
+                        "proxy": "",
                    },
                    "FastGPT": {
                        "id": "fastgpt",
@@ -1163,6 +1185,7 @@ CONFIG_METADATA_2 = {
                        "key": [],
                        "api_base": "https://api.fastgpt.in/api/v1",
                        "timeout": 60,
+                        "proxy": "",
                        "custom_headers": {},
                        "custom_extra_body": {},
                    },
@@ -1175,6 +1198,7 @@ CONFIG_METADATA_2 = {
                        "api_key": "",
                        "api_base": "",
                        "model": "whisper-1",
+                        "proxy": "",
                    },
                    "Whisper(Local)": {
                        "provider": "openai",
@@ -1204,6 +1228,7 @@ CONFIG_METADATA_2 = {
                        "model": "tts-1",
                        "openai-tts-voice": "alloy",
                        "timeout": "20",
+                        "proxy": "",
                    },
                    "Genie TTS": {
                        "id": "genie_tts",
@@ -1284,6 +1309,7 @@ CONFIG_METADATA_2 = {
                        "fishaudio-tts-character": "可莉",
                        "fishaudio-tts-reference-id": "",
                        "timeout": "20",
+                        "proxy": "",
                    },
                    "阿里云百炼 TTS(API)": {
                        "hint": "API Key 从 https://bailian.console.aliyun.com/?tab=model#/api-key 获取。模型和音色的选择文档请参考: 阿里云百炼语音合成音色名称。具体可参考 https://help.aliyun.com/zh/model-studio/speech-synthesis-and-speech-recognition",
@@ -1310,6 +1336,7 @@ CONFIG_METADATA_2 = {
                        "azure_tts_volume": "100",
                        "azure_tts_subscription_key": "",
                        "azure_tts_region": "eastus",
+                        "proxy": "",
                    },
                    "MiniMax TTS(API)": {
                        "id": "minimax_tts",
@@ -1332,6 +1359,7 @@ CONFIG_METADATA_2 = {
                        "minimax-voice-latex": False,
                        "minimax-voice-english-normalization": False,
                        "timeout": 20,
+                        "proxy": "",
                    },
                    "火山引擎_TTS(API)": {
                        "id": "volcengine_tts",
@@ -1346,6 +1374,7 @@ CONFIG_METADATA_2 = {
                        "volcengine_speed_ratio": 1.0,
                        "api_base": "https://openspeech.bytedance.com/api/v1/tts",
                        "timeout": 20,
+                        "proxy": "",
                    },
                    "Gemini TTS": {
                        "id": "gemini_tts",
@@ -1359,6 +1388,7 @@ CONFIG_METADATA_2 = {
                        "gemini_tts_model": "gemini-2.5-flash-preview-tts",
                        "gemini_tts_prefix": "",
                        "gemini_tts_voice_name": "Leda",
+                        "proxy": "",
                    },
                    "OpenAI Embedding": {
                        "id": "openai_embedding",
@@ -1371,6 +1401,7 @@ CONFIG_METADATA_2 = {
                        "embedding_model": "",
                        "embedding_dimensions": 1024,
                        "timeout": 20,
+                        "proxy": "",
                    },
                    "Gemini Embedding": {
                        "id": "gemini_embedding",
@@ -1383,6 +1414,7 @@ CONFIG_METADATA_2 = {
                        "embedding_model": "gemini-embedding-exp-03-07",
                        "embedding_dimensions": 768,
                        "timeout": 20,
+                        "proxy": "",
                    },
                    "vLLM Rerank": {
                        "id": "vllm_rerank",
@@ -2079,6 +2111,11 @@ CONFIG_METADATA_2 = {
                        "description": "API Base URL",
                        "type": "string",
                    },
+                    "proxy": {
+                        "description": "代理地址",
+                        "type": "string",
+                        "hint": "HTTP/HTTPS 代理地址，格式如 http://127.0.0.1:7890。仅对该提供商的 API 请求生效，不影响 Docker 内网通信。",
+                    },
                    "model": {
                        "description": "模型 ID",
                        "type": "string",
@@ -2563,7 +2600,7 @@ CONFIG_METADATA_3 = {
                    "provider_settings.websearch_provider": {
                        "description": "网页搜索提供商",
                        "type": "string",
-                        "options": ["default", "tavily", "baidu_ai_search"],
+                        "options": ["default", "tavily", "baidu_ai_search", "bocha"],
                        "condition": {
                            "provider_settings.web_search": True,
                        },
@@ -2578,6 +2615,16 @@ CONFIG_METADATA_3 = {
                            "provider_settings.web_search": True,
                        },
                    },
+                    "provider_settings.websearch_bocha_key": {
+                        "description": "BoCha API Key",
+                        "type": "list",
+                        "items": {"type": "string"},
+                        "hint": "可添加多个 Key 进行轮询。",
+                        "condition": {
+                            "provider_settings.websearch_provider": "bocha",
+                            "provider_settings.web_search": True,
+                        },
+                    },
                    "provider_settings.websearch_baidu_app_builder_key": {
                        "description": "百度千帆智能云 APP Builder API Key",
                        "type": "string",
@@ -42,6 +42,55 @@ class ConfigMetadataI18n:
        """
        result = {}

+        def convert_items(
+            group: str, section: str, items: dict[str, Any], prefix: str = ""
+        ) -> dict[str, Any]:
+            items_result: dict[str, Any] = {}
+
+            for field_key, field_data in items.items():
+                if not isinstance(field_data, dict):
+                    items_result[field_key] = field_data
+                    continue
+
+                field_name = field_key
+                field_path = f"{prefix}.{field_name}" if prefix else field_name
+
+                field_result = {
+                    key: value
+                    for key, value in field_data.items()
+                    if key not in {"description", "hint", "labels", "name"}
+                }
+
+                if "description" in field_data:
+                    field_result["description"] = (
+                        f"{group}.{section}.{field_path}.description"
+                    )
+                if "hint" in field_data:
+                    field_result["hint"] = f"{group}.{section}.{field_path}.hint"
+                if "labels" in field_data:
+                    field_result["labels"] = f"{group}.{section}.{field_path}.labels"
+                if "name" in field_data:
+                    field_result["name"] = f"{group}.{section}.{field_path}.name"
+
+                if "items" in field_data and isinstance(field_data["items"], dict):
+                    field_result["items"] = convert_items(
+                        group, section, field_data["items"], field_path
+                    )
+
+                if "template_schema" in field_data and isinstance(
+                    field_data["template_schema"], dict
+                ):
+                    field_result["template_schema"] = convert_items(
+                        group,
+                        section,
+                        field_data["template_schema"],
+                        f"{field_path}.template_schema",
+                    )
+
+                items_result[field_key] = field_result
+
+            return items_result
+
        for group_key, group_data in metadata.items():
            group_result = {
                "name": f"{group_key}.name",
@@ -50,59 +99,19 @@ class ConfigMetadataI18n:

            for section_key, section_data in group_data.get("metadata", {}).items():
                section_result = {
-                    "description": f"{group_key}.{section_key}.description",
-                    "type": section_data.get("type"),
+                    key: value
+                    for key, value in section_data.items()
+                    if key not in {"description", "hint", "labels", "name"}
                }
+                section_result["description"] = f"{group_key}.{section_key}.description"

-                # 复制其他属性
-                for key in ["items", "condition", "_special", "invisible"]:
-                    if key in section_data:
-                        section_result[key] = section_data[key]
-
-                # 处理 hint
                if "hint" in section_data:
                    section_result["hint"] = f"{group_key}.{section_key}.hint"

-                # 处理 items 中的字段
                if "items" in section_data and isinstance(section_data["items"], dict):
-                    items_result = {}
-                    for field_key, field_data in section_data["items"].items():
-                        # 处理嵌套的点号字段名（如 provider_settings.enable）
-                        field_name = field_key
-
-                        field_result = {}
-
-                        # 复制基本属性
-                        for attr in [
-                            "type",
-                            "condition",
-                            "_special",
-                            "invisible",
-                            "options",
-                            "slider",
-                        ]:
-                            if attr in field_data:
-                                field_result[attr] = field_data[attr]
-
-                        # 转换文本属性为国际化键
-                        if "description" in field_data:
-                            field_result["description"] = (
-                                f"{group_key}.{section_key}.{field_name}.description"
-                            )
-
-                        if "hint" in field_data:
-                            field_result["hint"] = (
-                                f"{group_key}.{section_key}.{field_name}.hint"
-                            )
-
-                        if "labels" in field_data:
-                            field_result["labels"] = (
-                                f"{group_key}.{section_key}.{field_name}.labels"
-                            )
-
-                        items_result[field_key] = field_result
-
-                    section_result["items"] = items_result
+                    section_result["items"] = convert_items(
+                        group_key, section_key, section_data["items"]
+                    )

                group_result["metadata"][section_key] = section_result

@@ -310,6 +310,7 @@ class CronJobManager:
        config = MainAgentBuildConfig(
            tool_call_timeout=3600,
            llm_safety_mode=False,
+            streaming_response=False,
        )
        req = ProviderRequest()
        conv = await _get_session_conv(event=cron_event, plugin_context=self.ctx)
@@ -313,7 +313,7 @@ class PersonaManager:
                        {
                            "role": "user" if user_turn else "assistant",
                            "content": dialog,
-                            "_no_save": None,  # 不持久化到 db
+                            "_no_save": True,  # 不持久化到 db
                        },
                    )
                    user_turn = not user_turn
@@ -1,5 +1,7 @@
 """使用此功能应该先 pip install baidu-aip"""

+from typing import Any, cast
+
 from aip import AipContentCensor

 from . import ContentSafetyStrategy
@@ -23,7 +25,8 @@ class BaiduAipStrategy(ContentSafetyStrategy):
        count = len(res["data"])
        parts = [f"百度审核服务发现 {count} 处违规：\n"]
        for i in res["data"]:
-            parts.append(f"{i['msg']}；\n")
+            # 百度 AIP 返回结构是动态 dict；类型检查时 i 可能被推断为序列，转成 dict 后用 get 取字段
+            parts.append(f"{cast(dict[str, Any], i).get('msg', '')}；\n")
        parts.append("\n判断结果：" + res["conclusion"])
        info = "".join(parts)
        return False, info
@@ -164,6 +164,7 @@ class InternalAgentSubStage(Stage):
                    event=event,
                    plugin_context=self.ctx.plugin_manager.context,
                    config=build_cfg,
+                    apply_reset=False,
                )

                if build_result is None:
@@ -172,6 +173,7 @@ class InternalAgentSubStage(Stage):
                agent_runner = build_result.agent_runner
                req = build_result.provider_request
                provider = build_result.provider
+                reset_coro = build_result.reset_coro

                api_base = provider.provider_config.get("api_base", "")
                for host in decoded_blocked:
@@ -190,6 +192,10 @@ class InternalAgentSubStage(Stage):
                if await call_event_hook(event, EventType.OnLLMRequestEvent, req):
                    return

+                # apply reset
+                if reset_coro:
+                    await reset_coro
+
                action_type = event.get_extra("action_type")

                event.trace.record(
@@ -349,15 +355,14 @@ class InternalAgentSubStage(Stage):
            if message.role == "system" and not skipped_initial_system:
                skipped_initial_system = True
                continue
-            if message.role in ["assistant", "user"] and getattr(
-                message, "_no_save", None
-            ):
+            if message.role in ["assistant", "user"] and message._no_save:
                continue
            message_to_save.append(message.model_dump())

        token_usage = None
        if runner_stats:
-            token_usage = runner_stats.token_usage.total
+            # token_usage = runner_stats.token_usage.total
+            token_usage = llm_response.usage.total if llm_response.usage else None

        await self.conv_manager.update_conversation(
            event.unified_msg_origin,
@@ -1,4 +1,4 @@
-from dataclasses import dataclass
+from dataclasses import dataclass, field

 from astrbot.core.platform.message_type import MessageType

@@ -13,7 +13,7 @@ class MessageSession:
    """平台适配器实例的唯一标识符。自 AstrBot v4.0.0 起，该字段实际为 platform_id。"""
    message_type: MessageType
    session_id: str
-    platform_id: str | None = None
+    platform_id: str = field(init=False)

    def __str__(self):
        return f"{self.platform_id}:{self.message_type.value}:{self.session_id}"
@@ -444,9 +444,20 @@ class DiscordPlatformAdapter(Platform):
                logger.warning(f"[Discord] 指令 '{cmd_name}' defer 失败: {e}")

            # 2. 构建 AstrBotMessage
+            channel = ctx.channel
            abm = AstrBotMessage()
-            abm.type = self._get_message_type(ctx.channel, ctx.guild_id)
-            abm.group_id = self._get_channel_id(ctx.channel)
+            if channel is not None:
+                abm.type = self._get_message_type(channel, ctx.guild_id)
+                abm.group_id = self._get_channel_id(channel)
+            else:
+                # 防守式兜底：channel 取不到时，仍能根据 guild_id/channel_id 推断会话信息
+                abm.type = (
+                    MessageType.GROUP_MESSAGE
+                    if ctx.guild_id is not None
+                    else MessageType.FRIEND_MESSAGE
+                )
+                abm.group_id = str(ctx.channel_id)
+
            abm.message_str = message_str_for_filter
            abm.sender = MessageMember(
                user_id=str(ctx.author.id),
@@ -3,13 +3,10 @@ import base64
 import json
 import re
 import time
-import uuid
 from typing import Any, cast

 import lark_oapi as lark
 from lark_oapi.api.im.v1 import (
-    CreateMessageRequest,
-    CreateMessageRequestBody,
    GetMessageResourceRequest,
 )
 from lark_oapi.api.im.v1.processor import P2ImMessageReceiveV1Processor
@@ -125,44 +122,23 @@ class LarkPlatformAdapter(Platform):
        session: MessageSesion,
        message_chain: MessageChain,
    ):
-        if self.lark_api.im is None:
-            logger.error("[Lark] API Client im 模块未初始化，无法发送消息")
-            return
-
-        res = await LarkMessageEvent._convert_to_lark(message_chain, self.lark_api)
-        wrapped = {
-            "zh_cn": {
-                "title": "",
-                "content": res,
-            },
-        }
-
        if session.message_type == MessageType.GROUP_MESSAGE:
            id_type = "chat_id"
-            if "%" in session.session_id:
-                session.session_id = session.session_id.split("%")[1]
+            receive_id = session.session_id
+            if "%" in receive_id:
+                receive_id = receive_id.split("%")[1]
        else:
            id_type = "open_id"
+            receive_id = session.session_id

-        request = (
-            CreateMessageRequest.builder()
-            .receive_id_type(id_type)
-            .request_body(
-                CreateMessageRequestBody.builder()
-                .receive_id(session.session_id)
-                .content(json.dumps(wrapped))
-                .msg_type("post")
-                .uuid(str(uuid.uuid4()))
-                .build(),
-            )
-            .build()
+        # 复用 LarkMessageEvent 中的通用发送逻辑
+        await LarkMessageEvent.send_message_chain(
+            message_chain,
+            self.lark_api,
+            receive_id=receive_id,
+            receive_id_type=id_type,
        )

-        response = await self.lark_api.im.v1.message.acreate(request)
-
-        if not response.success():
-            logger.error(f"发送飞书消息失败({response.code}): {response.msg}")
-
        await super().send_by_session(session, message_chain)

    def meta(self) -> PlatformMetadata:
@@ -6,6 +6,8 @@ from io import BytesIO

 import lark_oapi as lark
 from lark_oapi.api.im.v1 import (
+    CreateFileRequest,
+    CreateFileRequestBody,
    CreateImageRequest,
    CreateImageRequestBody,
    CreateMessageReactionRequest,
@@ -17,10 +19,15 @@ from lark_oapi.api.im.v1 import (

 from astrbot import logger
 from astrbot.api.event import AstrMessageEvent, MessageChain
-from astrbot.api.message_components import At, Plain
+from astrbot.api.message_components import At, File, Plain, Record, Video
 from astrbot.api.message_components import Image as AstrBotImage
 from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 from astrbot.core.utils.io import download_image_by_url
+from astrbot.core.utils.media_utils import (
+    convert_audio_to_opus,
+    convert_video_format,
+    get_media_duration,
+)


 class LarkMessageEvent(AstrMessageEvent):
@@ -35,6 +42,144 @@ class LarkMessageEvent(AstrMessageEvent):
        super().__init__(message_str, message_obj, platform_meta, session_id)
        self.bot = bot

+    @staticmethod
+    async def _send_im_message(
+        lark_client: lark.Client,
+        *,
+        content: str,
+        msg_type: str,
+        reply_message_id: str | None = None,
+        receive_id: str | None = None,
+        receive_id_type: str | None = None,
+    ) -> bool:
+        """发送飞书 IM 消息的通用辅助函数
+
+        Args:
+            lark_client: 飞书客户端
+            content: 消息内容（JSON字符串）
+            msg_type: 消息类型（post/file/audio/media等）
+            reply_message_id: 回复的消息ID（用于回复消息）
+            receive_id: 接收者ID（用于主动发送）
+            receive_id_type: 接收者ID类型（用于主动发送）
+
+        Returns:
+            是否发送成功
+        """
+        if lark_client.im is None:
+            logger.error("[Lark] API Client im 模块未初始化")
+            return False
+
+        if reply_message_id:
+            request = (
+                ReplyMessageRequest.builder()
+                .message_id(reply_message_id)
+                .request_body(
+                    ReplyMessageRequestBody.builder()
+                    .content(content)
+                    .msg_type(msg_type)
+                    .uuid(str(uuid.uuid4()))
+                    .reply_in_thread(False)
+                    .build()
+                )
+                .build()
+            )
+            response = await lark_client.im.v1.message.areply(request)
+        else:
+            from lark_oapi.api.im.v1 import (
+                CreateMessageRequest,
+                CreateMessageRequestBody,
+            )
+
+            if receive_id_type is None or receive_id is None:
+                logger.error(
+                    "[Lark] 主动发送消息时，receive_id 和 receive_id_type 不能为空",
+                )
+                return False
+
+            request = (
+                CreateMessageRequest.builder()
+                .receive_id_type(receive_id_type)
+                .request_body(
+                    CreateMessageRequestBody.builder()
+                    .receive_id(receive_id)
+                    .content(content)
+                    .msg_type(msg_type)
+                    .uuid(str(uuid.uuid4()))
+                    .build()
+                )
+                .build()
+            )
+            response = await lark_client.im.v1.message.acreate(request)
+
+        if not response.success():
+            logger.error(f"[Lark] 发送飞书消息失败({response.code}): {response.msg}")
+            return False
+
+        return True
+
+    @staticmethod
+    async def _upload_lark_file(
+        lark_client: lark.Client,
+        *,
+        path: str,
+        file_type: str,
+        duration: int | None = None,
+    ) -> str | None:
+        """上传文件到飞书的通用辅助函数
+
+        Args:
+            lark_client: 飞书客户端
+            path: 文件路径
+            file_type: 文件类型（stream/opus/mp4等）
+            duration: 媒体时长（毫秒），可选
+
+        Returns:
+            成功返回file_key，失败返回None
+        """
+        if not path or not os.path.exists(path):
+            logger.error(f"[Lark] 文件不存在: {path}")
+            return None
+
+        if lark_client.im is None:
+            logger.error("[Lark] API Client im 模块未初始化，无法上传文件")
+            return None
+
+        try:
+            with open(path, "rb") as file_obj:
+                body_builder = (
+                    CreateFileRequestBody.builder()
+                    .file_type(file_type)
+                    .file_name(os.path.basename(path))
+                    .file(file_obj)
+                )
+                if duration is not None:
+                    body_builder.duration(duration)
+
+                request = (
+                    CreateFileRequest.builder()
+                    .request_body(body_builder.build())
+                    .build()
+                )
+                response = await lark_client.im.v1.file.acreate(request)
+
+                if not response.success():
+                    logger.error(
+                        f"[Lark] 无法上传文件({response.code}): {response.msg}"
+                    )
+                    return None
+
+                if response.data is None:
+                    logger.error("[Lark] 上传文件成功但未返回数据(data is None)")
+                    return None
+
+                file_key = response.data.file_key
+                logger.debug(f"[Lark] 文件上传成功: {file_key}")
+                return file_key
+
+        except Exception as e:
+            logger.error(f"[Lark] 无法打开或上传文件: {e}")
+            return None
+
    @staticmethod
    async def _convert_to_lark(message: MessageChain, lark_client: lark.Client) -> list:
        ret = []
@@ -103,6 +248,18 @@ class LarkMessageEvent(AstrMessageEvent):
                ret.append(_stage)
                ret.append([{"tag": "img", "image_key": image_key}])
                _stage.clear()
+            elif isinstance(comp, File):
+                # 文件将通过 _send_file_message 方法单独发送，这里跳过
+                logger.debug("[Lark] 检测到文件组件，将单独发送")
+                continue
+            elif isinstance(comp, Record):
+                # 音频将通过 _send_audio_message 方法单独发送，这里跳过
+                logger.debug("[Lark] 检测到音频组件，将单独发送")
+                continue
+            elif isinstance(comp, Video):
+                # 视频将通过 _send_media_message 方法单独发送，这里跳过
+                logger.debug("[Lark] 检测到视频组件，将单独发送")
+                continue
            else:
                logger.warning(f"飞书 暂时不支持消息段: {comp.type}")

@@ -110,40 +267,270 @@ class LarkMessageEvent(AstrMessageEvent):
            ret.append(_stage)
        return ret

-    async def send(self, message: MessageChain):
-        res = await LarkMessageEvent._convert_to_lark(message, self.bot)
-        wrapped = {
-            "zh_cn": {
-                "title": "",
-                "content": res,
-            },
-        }
+    @staticmethod
+    async def send_message_chain(
+        message_chain: MessageChain,
+        lark_client: lark.Client,
+        reply_message_id: str | None = None,
+        receive_id: str | None = None,
+        receive_id_type: str | None = None,
+    ):
+        """通用的消息链发送方法

-        request = (
-            ReplyMessageRequest.builder()
-            .message_id(self.message_obj.message_id)
-            .request_body(
-                ReplyMessageRequestBody.builder()
-                .content(json.dumps(wrapped))
-                .msg_type("post")
-                .uuid(str(uuid.uuid4()))
-                .reply_in_thread(False)
-                .build(),
-            )
-            .build()
-        )
-
-        if self.bot.im is None:
-            logger.error("[Lark] API Client im 模块未初始化，无法回复消息")
+        Args:
+            message_chain: 要发送的消息链
+            lark_client: 飞书客户端
+            reply_message_id: 回复的消息ID（用于回复消息）
+            receive_id: 接收者ID（用于主动发送）
+            receive_id_type: 接收者ID类型，如 'open_id', 'chat_id'（用于主动发送）
+        """
+        if lark_client.im is None:
+            logger.error("[Lark] API Client im 模块未初始化")
            return

-        response = await self.bot.im.v1.message.areply(request)
+        # 分离文件、音频、视频组件和其他组件
+        file_components: list[File] = []
+        audio_components: list[Record] = []
+        media_components: list[Video] = []
+        other_components = []

-        if not response.success():
-            logger.error(f"回复飞书消息失败({response.code}): {response.msg}")
+        for comp in message_chain.chain:
+            if isinstance(comp, File):
+                file_components.append(comp)
+            elif isinstance(comp, Record):
+                audio_components.append(comp)
+            elif isinstance(comp, Video):
+                media_components.append(comp)
+            else:
+                other_components.append(comp)

+        # 先发送非文件内容（如果有）
+        if other_components:
+            temp_chain = MessageChain()
+            temp_chain.chain = other_components
+            res = await LarkMessageEvent._convert_to_lark(temp_chain, lark_client)
+
+            if res:  # 只在有内容时发送
+                wrapped = {
+                    "zh_cn": {
+                        "title": "",
+                        "content": res,
+                    },
+                }
+                await LarkMessageEvent._send_im_message(
+                    lark_client,
+                    content=json.dumps(wrapped),
+                    msg_type="post",
+                    reply_message_id=reply_message_id,
+                    receive_id=receive_id,
+                    receive_id_type=receive_id_type,
+                )
+
+        # 发送附件
+        for file_comp in file_components:
+            await LarkMessageEvent._send_file_message(
+                file_comp, lark_client, reply_message_id, receive_id, receive_id_type
+            )
+
+        for audio_comp in audio_components:
+            await LarkMessageEvent._send_audio_message(
+                audio_comp, lark_client, reply_message_id, receive_id, receive_id_type
+            )
+
+        for media_comp in media_components:
+            await LarkMessageEvent._send_media_message(
+                media_comp, lark_client, reply_message_id, receive_id, receive_id_type
+            )
+
+    async def send(self, message: MessageChain):
+        """发送消息链到飞书，然后交给父类做框架级发送/记录"""
+        await LarkMessageEvent.send_message_chain(
+            message,
+            self.bot,
+            reply_message_id=self.message_obj.message_id,
+        )
        await super().send(message)

+    @staticmethod
+    async def _send_file_message(
+        file_comp: File,
+        lark_client: lark.Client,
+        reply_message_id: str | None = None,
+        receive_id: str | None = None,
+        receive_id_type: str | None = None,
+    ):
+        """发送文件消息
+
+        Args:
+            file_comp: 文件组件
+            lark_client: 飞书客户端
+            reply_message_id: 回复的消息ID（用于回复消息）
+            receive_id: 接收者ID（用于主动发送）
+            receive_id_type: 接收者ID类型（用于主动发送）
+        """
+        file_path = file_comp.file or ""
+        file_key = await LarkMessageEvent._upload_lark_file(
+            lark_client, path=file_path, file_type="stream"
+        )
+        if not file_key:
+            return
+
+        content = json.dumps({"file_key": file_key})
+        await LarkMessageEvent._send_im_message(
+            lark_client,
+            content=content,
+            msg_type="file",
+            reply_message_id=reply_message_id,
+            receive_id=receive_id,
+            receive_id_type=receive_id_type,
+        )
+
+    @staticmethod
+    async def _send_audio_message(
+        audio_comp: Record,
+        lark_client: lark.Client,
+        reply_message_id: str | None = None,
+        receive_id: str | None = None,
+        receive_id_type: str | None = None,
+    ):
+        """发送音频消息
+
+        Args:
+            audio_comp: 音频组件
+            lark_client: 飞书客户端
+            reply_message_id: 回复的消息ID（用于回复消息）
+            receive_id: 接收者ID（用于主动发送）
+            receive_id_type: 接收者ID类型（用于主动发送）
+        """
+        # 获取音频文件路径
+        try:
+            original_audio_path = await audio_comp.convert_to_file_path()
+        except Exception as e:
+            logger.error(f"[Lark] 无法获取音频文件路径: {e}")
+            return
+
+        if not original_audio_path or not os.path.exists(original_audio_path):
+            logger.error(f"[Lark] 音频文件不存在: {original_audio_path}")
+            return
+
+        # 转换为opus格式
+        converted_audio_path = None
+        try:
+            audio_path = await convert_audio_to_opus(original_audio_path)
+            # 如果转换后路径与原路径不同，说明生成了新文件
+            if audio_path != original_audio_path:
+                converted_audio_path = audio_path
+            else:
+                audio_path = original_audio_path
+        except Exception as e:
+            logger.error(f"[Lark] 音频格式转换失败，将尝试直接上传: {e}")
+            # 如果转换失败，继续尝试直接上传原始文件
+            audio_path = original_audio_path
+
+        # 获取音频时长
+        duration = await get_media_duration(audio_path)
+
+        # 上传音频文件
+        file_key = await LarkMessageEvent._upload_lark_file(
+            lark_client,
+            path=audio_path,
+            file_type="opus",
+            duration=duration,
+        )
+
+        # 清理转换后的临时音频文件
+        if converted_audio_path and os.path.exists(converted_audio_path):
+            try:
+                os.remove(converted_audio_path)
+                logger.debug(f"[Lark] 已删除转换后的音频文件: {converted_audio_path}")
+            except Exception as e:
+                logger.warning(f"[Lark] 删除转换后的音频文件失败: {e}")
+
+        if not file_key:
+            return
+
+        await LarkMessageEvent._send_im_message(
+            lark_client,
+            content=json.dumps({"file_key": file_key}),
+            msg_type="audio",
+            reply_message_id=reply_message_id,
+            receive_id=receive_id,
+            receive_id_type=receive_id_type,
+        )
+
+    @staticmethod
+    async def _send_media_message(
+        media_comp: Video,
+        lark_client: lark.Client,
+        reply_message_id: str | None = None,
+        receive_id: str | None = None,
+        receive_id_type: str | None = None,
+    ):
+        """发送视频消息
+
+        Args:
+            media_comp: 视频组件
+            lark_client: 飞书客户端
+            reply_message_id: 回复的消息ID（用于回复消息）
+            receive_id: 接收者ID（用于主动发送）
+            receive_id_type: 接收者ID类型（用于主动发送）
+        """
+        # 获取视频文件路径
+        try:
+            original_video_path = await media_comp.convert_to_file_path()
+        except Exception as e:
+            logger.error(f"[Lark] 无法获取视频文件路径: {e}")
+            return
+
+        if not original_video_path or not os.path.exists(original_video_path):
+            logger.error(f"[Lark] 视频文件不存在: {original_video_path}")
+            return
+
+        # 转换为mp4格式
+        converted_video_path = None
+        try:
+            video_path = await convert_video_format(original_video_path, "mp4")
+            # 如果转换后路径与原路径不同，说明生成了新文件
+            if video_path != original_video_path:
+                converted_video_path = video_path
+            else:
+                video_path = original_video_path
+        except Exception as e:
+            logger.error(f"[Lark] 视频格式转换失败，将尝试直接上传: {e}")
+            # 如果转换失败，继续尝试直接上传原始文件
+            video_path = original_video_path
+
+        # 获取视频时长
+        duration = await get_media_duration(video_path)
+
+        # 上传视频文件
+        file_key = await LarkMessageEvent._upload_lark_file(
+            lark_client,
+            path=video_path,
+            file_type="mp4",
+            duration=duration,
+        )
+
+        # 清理转换后的临时视频文件
+        if converted_video_path and os.path.exists(converted_video_path):
+            try:
+                os.remove(converted_video_path)
+                logger.debug(f"[Lark] 已删除转换后的视频文件: {converted_video_path}")
+            except Exception as e:
+                logger.warning(f"[Lark] 删除转换后的视频文件失败: {e}")
+
+        if not file_key:
+            return
+
+        await LarkMessageEvent._send_im_message(
+            lark_client,
+            content=json.dumps({"file_key": file_key}),
+            msg_type="media",
+            reply_message_id=reply_message_id,
+            receive_id=receive_id,
+            receive_id_type=receive_id_type,
+        )
+
    async def react(self, emoji: str):
        if self.bot.im is None:
            logger.error("[Lark] API Client im 模块未初始化，无法发送表情")
@@ -89,6 +89,16 @@ class TelegramPlatformAdapter(Platform):

        self.scheduler = AsyncIOScheduler()

+        # Media group handling
+        # Cache structure: {media_group_id: {"created_at": datetime, "items": [(update, context), ...]}}
+        self.media_group_cache: dict[str, dict] = {}
+        self.media_group_timeout = self.config.get(
+            "telegram_media_group_timeout", 2.5
+        )  # seconds - debounce delay between messages
+        self.media_group_max_wait = self.config.get(
+            "telegram_media_group_max_wait", 10.0
+        )  # max seconds - hard cap to prevent indefinite delay
+
    @override
    async def send_by_session(
        self,
@@ -225,6 +235,13 @@ class TelegramPlatformAdapter(Platform):

    async def message_handler(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
        logger.debug(f"Telegram message: {update.message}")
+
+        # Handle media group messages
+        if update.message and update.message.media_group_id:
+            await self.handle_media_group_message(update, context)
+            return
+
+        # Handle regular messages
        abm = await self.convert_message(update, context)
        if abm:
            await self.handle_msg(abm)
@@ -399,6 +416,113 @@ class TelegramPlatformAdapter(Platform):

        return message

+    async def handle_media_group_message(
+        self, update: Update, context: ContextTypes.DEFAULT_TYPE
+    ):
+        """Handle messages that are part of a media group (album).
+
+        Caches incoming messages and schedules delayed processing to collect all
+        media items before sending to the pipeline. Uses debounce mechanism with
+        a hard cap (max_wait) to prevent indefinite delay.
+        """
+        from datetime import datetime, timedelta
+
+        if not update.message:
+            return
+
+        media_group_id = update.message.media_group_id
+        if not media_group_id:
+            return
+
+        # Initialize cache for this media group if needed
+        if media_group_id not in self.media_group_cache:
+            self.media_group_cache[media_group_id] = {
+                "created_at": datetime.now(),
+                "items": [],
+            }
+            logger.debug(f"Create media group cache: {media_group_id}")
+
+        # Add this message to the cache
+        entry = self.media_group_cache[media_group_id]
+        entry["items"].append((update, context))
+        logger.debug(
+            f"Add message to media group {media_group_id}, "
+            f"currently has {len(entry['items'])} items.",
+        )
+
+        # Calculate delay: if already waited too long, process immediately;
+        # otherwise use normal debounce timeout
+        elapsed = (datetime.now() - entry["created_at"]).total_seconds()
+        if elapsed >= self.media_group_max_wait:
+            delay = 0
+            logger.debug(
+                f"Media group {media_group_id} has reached max wait time "
+                f"({elapsed:.1f}s >= {self.media_group_max_wait}s), processing immediately.",
+            )
+        else:
+            delay = self.media_group_timeout
+            logger.debug(
+                f"Scheduled media group {media_group_id} to be processed in {delay} seconds "
+                f"(already waited {elapsed:.1f}s)"
+            )
+
+        # Schedule/reschedule processing (replace_existing=True handles debounce)
+        job_id = f"media_group_{media_group_id}"
+        self.scheduler.add_job(
+            self.process_media_group,
+            "date",
+            run_date=datetime.now() + timedelta(seconds=delay),
+            args=[media_group_id],
+            id=job_id,
+            replace_existing=True,
+        )
+
+    async def process_media_group(self, media_group_id: str):
+        """Process a complete media group by merging all collected messages.
+
+        Args:
+            media_group_id: The unique identifier for this media group
+        """
+        if media_group_id not in self.media_group_cache:
+            logger.warning(f"Media group {media_group_id} not found in cache")
+            return
+
+        entry = self.media_group_cache.pop(media_group_id)
+        updates_and_contexts = entry["items"]
+        if not updates_and_contexts:
+            logger.warning(f"Media group {media_group_id} is empty")
+            return
+
+        logger.info(
+            f"Processing media group {media_group_id}, total {len(updates_and_contexts)} items"
+        )
+
+        # Use the first update to create the base message (with reply, caption, etc.)
+        first_update, first_context = updates_and_contexts[0]
+        abm = await self.convert_message(first_update, first_context)
+
+        if not abm:
+            logger.warning(
+                f"Failed to convert the first message of media group {media_group_id}"
+            )
+            return
+
+        # Add additional media from remaining updates by reusing convert_message
+        for update, context in updates_and_contexts[1:]:
+            # Convert the message but skip reply chains (get_reply=False)
+            extra = await self.convert_message(update, context, get_reply=False)
+            if not extra:
+                continue
+
+            # Merge only the message components (keep base session/meta from first)
+            abm.message.extend(extra.message)
+            logger.debug(
+                f"Added {len(extra.message)} components to media group {media_group_id}"
+            )
+
+        # Process the merged message
+        await self.handle_msg(abm)
+
    async def handle_msg(self, message: AstrBotMessage):
        message_event = TelegramPlatformEvent(
            message_str=message.message_str,
@@ -426,6 +550,6 @@ class TelegramPlatformAdapter(Platform):
            if self.application.updater is not None:
                await self.application.updater.stop()

-            logger.info("Telegram 适配器已被关闭")
+            logger.info("Telegram adapter has been closed.")
        except Exception as e:
-            logger.error(f"Telegram 适配器关闭时出错: {e}")
+            logger.error(f"Error occurred while closing Telegram adapter: {e}")
@@ -29,43 +29,11 @@ class QueueListener:
    def __init__(self, webchat_queue_mgr: WebChatQueueMgr, callback: Callable) -> None:
        self.webchat_queue_mgr = webchat_queue_mgr
        self.callback = callback
-        self.running_tasks = set()
-
-    async def listen_to_queue(self, conversation_id: str):
-        """Listen to a specific conversation queue"""
-        queue = self.webchat_queue_mgr.get_or_create_queue(conversation_id)
-        while True:
-            try:
-                data = await queue.get()
-                await self.callback(data)
-            except Exception as e:
-                logger.error(
-                    f"Error processing message from conversation {conversation_id}: {e}",
-                )
-                break

    async def run(self):
-        """Monitor for new conversation queues and start listeners"""
-        monitored_conversations = set()
-
-        while True:
-            # Check for new conversations
-            current_conversations = set(self.webchat_queue_mgr.queues.keys())
-            new_conversations = current_conversations - monitored_conversations
-
-            # Start listeners for new conversations
-            for conversation_id in new_conversations:
-                task = asyncio.create_task(self.listen_to_queue(conversation_id))
-                self.running_tasks.add(task)
-                task.add_done_callback(self.running_tasks.discard)
-                monitored_conversations.add(conversation_id)
-                logger.debug(f"Started listener for conversation: {conversation_id}")
-
-            # Clean up monitored conversations that no longer exist
-            removed_conversations = monitored_conversations - current_conversations
-            monitored_conversations -= removed_conversations
-
-            await asyncio.sleep(1)  # Check for new conversations every second
+        """Register callback and keep adapter task alive."""
+        self.webchat_queue_mgr.set_listener(self.callback)
+        await asyncio.Event().wait()


@register_platform_adapter("webchat", "webchat")
@@ -26,8 +26,12 @@ class WebChatMessageEvent(AstrMessageEvent):
        session_id: str,
        streaming: bool = False,
    ) -> str | None:
-        cid = session_id.split("!")[-1]
-        web_chat_back_queue = webchat_queue_mgr.get_or_create_back_queue(cid)
+        request_id = str(message_id)
+        conversation_id = session_id.split("!")[-1]
+        web_chat_back_queue = webchat_queue_mgr.get_or_create_back_queue(
+            request_id,
+            conversation_id,
+        )
        if not message:
            await web_chat_back_queue.put(
                {
@@ -124,9 +128,13 @@ class WebChatMessageEvent(AstrMessageEvent):
    async def send_streaming(self, generator, use_fallback: bool = False):
        final_data = ""
        reasoning_content = ""
-        cid = self.session_id.split("!")[-1]
-        web_chat_back_queue = webchat_queue_mgr.get_or_create_back_queue(cid)
        message_id = self.message_obj.message_id
+        request_id = str(message_id)
+        conversation_id = self.session_id.split("!")[-1]
+        web_chat_back_queue = webchat_queue_mgr.get_or_create_back_queue(
+            request_id,
+            conversation_id,
+        )
        async for chain in generator:
            # 处理音频流（Live Mode）
            if chain.type == "audio_chunk":
@@ -1,35 +1,147 @@
 import asyncio
+from collections.abc import Awaitable, Callable
+
+from astrbot import logger


 class WebChatQueueMgr:
-    def __init__(self) -> None:
-        self.queues = {}
+    def __init__(self, queue_maxsize: int = 128, back_queue_maxsize: int = 512) -> None:
+        self.queues: dict[str, asyncio.Queue] = {}
        """Conversation ID to asyncio.Queue mapping"""
-        self.back_queues = {}
-        """Conversation ID to asyncio.Queue mapping for responses"""
+        self.back_queues: dict[str, asyncio.Queue] = {}
+        """Request ID to asyncio.Queue mapping for responses"""
+        self._conversation_back_requests: dict[str, set[str]] = {}
+        self._request_conversation: dict[str, str] = {}
+        self._queue_close_events: dict[str, asyncio.Event] = {}
+        self._listener_tasks: dict[str, asyncio.Task] = {}
+        self._listener_callback: Callable[[tuple], Awaitable[None]] | None = None
+        self.queue_maxsize = queue_maxsize
+        self.back_queue_maxsize = back_queue_maxsize

    def get_or_create_queue(self, conversation_id: str) -> asyncio.Queue:
        """Get or create a queue for the given conversation ID"""
        if conversation_id not in self.queues:
-            self.queues[conversation_id] = asyncio.Queue()
+            self.queues[conversation_id] = asyncio.Queue(maxsize=self.queue_maxsize)
+            self._queue_close_events[conversation_id] = asyncio.Event()
+            self._start_listener_if_needed(conversation_id)
        return self.queues[conversation_id]

-    def get_or_create_back_queue(self, conversation_id: str) -> asyncio.Queue:
-        """Get or create a back queue for the given conversation ID"""
-        if conversation_id not in self.back_queues:
-            self.back_queues[conversation_id] = asyncio.Queue()
-        return self.back_queues[conversation_id]
+    def get_or_create_back_queue(
+        self,
+        request_id: str,
+        conversation_id: str | None = None,
+    ) -> asyncio.Queue:
+        """Get or create a back queue for the given request ID"""
+        if request_id not in self.back_queues:
+            self.back_queues[request_id] = asyncio.Queue(
+                maxsize=self.back_queue_maxsize
+            )
+        if conversation_id:
+            self._request_conversation[request_id] = conversation_id
+            if conversation_id not in self._conversation_back_requests:
+                self._conversation_back_requests[conversation_id] = set()
+            self._conversation_back_requests[conversation_id].add(request_id)
+        return self.back_queues[request_id]
+
+    def remove_back_queue(self, request_id: str):
+        """Remove back queue for the given request ID"""
+        self.back_queues.pop(request_id, None)
+        conversation_id = self._request_conversation.pop(request_id, None)
+        if conversation_id:
+            request_ids = self._conversation_back_requests.get(conversation_id)
+            if request_ids is not None:
+                request_ids.discard(request_id)
+                if not request_ids:
+                    self._conversation_back_requests.pop(conversation_id, None)

    def remove_queues(self, conversation_id: str):
        """Remove queues for the given conversation ID"""
-        if conversation_id in self.queues:
-            del self.queues[conversation_id]
-        if conversation_id in self.back_queues:
-            del self.back_queues[conversation_id]
+        for request_id in list(
+            self._conversation_back_requests.get(conversation_id, set())
+        ):
+            self.remove_back_queue(request_id)
+        self._conversation_back_requests.pop(conversation_id, None)
+        self.remove_queue(conversation_id)
+
+    def remove_queue(self, conversation_id: str):
+        """Remove input queue and listener for the given conversation ID"""
+        self.queues.pop(conversation_id, None)
+
+        close_event = self._queue_close_events.pop(conversation_id, None)
+        if close_event is not None:
+            close_event.set()
+
+        task = self._listener_tasks.pop(conversation_id, None)
+        if task is not None:
+            task.cancel()

    def has_queue(self, conversation_id: str) -> bool:
        """Check if a queue exists for the given conversation ID"""
        return conversation_id in self.queues

+    def set_listener(
+        self,
+        callback: Callable[[tuple], Awaitable[None]],
+    ):
+        self._listener_callback = callback
+        for conversation_id in list(self.queues.keys()):
+            self._start_listener_if_needed(conversation_id)
+
+    def _start_listener_if_needed(self, conversation_id: str):
+        if self._listener_callback is None:
+            return
+        if conversation_id in self._listener_tasks:
+            task = self._listener_tasks[conversation_id]
+            if not task.done():
+                return
+        queue = self.queues.get(conversation_id)
+        close_event = self._queue_close_events.get(conversation_id)
+        if queue is None or close_event is None:
+            return
+        task = asyncio.create_task(
+            self._listen_to_queue(conversation_id, queue, close_event),
+            name=f"webchat_listener_{conversation_id}",
+        )
+        self._listener_tasks[conversation_id] = task
+        task.add_done_callback(
+            lambda _: self._listener_tasks.pop(conversation_id, None)
+        )
+        logger.debug(f"Started listener for conversation: {conversation_id}")
+
+    async def _listen_to_queue(
+        self,
+        conversation_id: str,
+        queue: asyncio.Queue,
+        close_event: asyncio.Event,
+    ):
+        while True:
+            get_task = asyncio.create_task(queue.get())
+            close_task = asyncio.create_task(close_event.wait())
+            try:
+                done, pending = await asyncio.wait(
+                    {get_task, close_task},
+                    return_when=asyncio.FIRST_COMPLETED,
+                )
+                for task in pending:
+                    task.cancel()
+                if close_task in done:
+                    break
+                data = get_task.result()
+                if self._listener_callback is None:
+                    continue
+                try:
+                    await self._listener_callback(data)
+                except Exception as e:
+                    logger.error(
+                        f"Error processing message from conversation {conversation_id}: {e}"
+                    )
+            except asyncio.CancelledError:
+                break
+            finally:
+                if not get_task.done():
+                    get_task.cancel()
+                if not close_task.done():
+                    close_task.cancel()
+

 webchat_queue_mgr = WebChatQueueMgr()
@@ -51,44 +51,13 @@ class WecomAIQueueListener:
    ) -> None:
        self.queue_mgr = queue_mgr
        self.callback = callback
-        self.running_tasks = set()
-
-    async def listen_to_queue(self, session_id: str):
-        """监听特定会话的队列"""
-        queue = self.queue_mgr.get_or_create_queue(session_id)
-        while True:
-            try:
-                data = await queue.get()
-                await self.callback(data)
-            except Exception as e:
-                logger.error(f"处理会话 {session_id} 消息时发生错误: {e}")
-                break

    async def run(self):
-        """监控新会话队列并启动监听器"""
-        monitored_sessions = set()
-
+        """注册监听回调并定期清理过期响应。"""
+        self.queue_mgr.set_listener(self.callback)
        while True:
-            # 检查新会话
-            current_sessions = set(self.queue_mgr.queues.keys())
-            new_sessions = current_sessions - monitored_sessions
-
-            # 为新会话启动监听器
-            for session_id in new_sessions:
-                task = asyncio.create_task(self.listen_to_queue(session_id))
-                self.running_tasks.add(task)
-                task.add_done_callback(self.running_tasks.discard)
-                monitored_sessions.add(session_id)
-                logger.debug(f"[WecomAI] 为会话启动监听器: {session_id}")
-
-            # 清理已不存在的会话
-            removed_sessions = monitored_sessions - current_sessions
-            monitored_sessions -= removed_sessions
-
-            # 清理过期的待处理响应
            self.queue_mgr.cleanup_expired_responses()
-
-            await asyncio.sleep(1)  # 每秒检查一次新会话
+            await asyncio.sleep(1)


@register_platform_adapter(
@@ -212,7 +181,12 @@ class WecomAIBotAdapter(Platform):
            # wechat server is requesting for updates of a stream
            stream_id = message_data["stream"]["id"]
            if not self.queue_mgr.has_back_queue(stream_id):
-                logger.error(f"Cannot find back queue for stream_id: {stream_id}")
+                if self.queue_mgr.is_stream_finished(stream_id):
+                    logger.debug(
+                        f"Stream already finished, returning end message: {stream_id}"
+                    )
+                else:
+                    logger.warning(f"Cannot find back queue for stream_id: {stream_id}")

                # 返回结束标志，告诉微信服务器流已结束
                end_message = WecomAIBotStreamMessageBuilder.make_text_stream(
@@ -243,10 +217,10 @@ class WecomAIBotAdapter(Platform):
                    latest_plain_content = msg["data"] or ""
                elif msg["type"] == "image":
                    image_base64.append(msg["image_data"])
-                elif msg["type"] == "end":
+                elif msg["type"] in {"end", "complete"}:
                    # stream end
                    finish = True
-                    self.queue_mgr.remove_queues(stream_id)
+                    self.queue_mgr.remove_queues(stream_id, mark_finished=True)
                    break

            logger.debug(
@@ -4,6 +4,7 @@
 """

 import asyncio
+from collections.abc import Awaitable, Callable
 from typing import Any

 from astrbot.api import logger
@@ -12,7 +13,7 @@ from astrbot.api import logger
 class WecomAIQueueMgr:
    """企业微信智能机器人队列管理器"""

-    def __init__(self) -> None:
+    def __init__(self, queue_maxsize: int = 128, back_queue_maxsize: int = 512) -> None:
        self.queues: dict[str, asyncio.Queue] = {}
        """StreamID 到输入队列的映射 - 用于接收用户消息"""

@@ -21,6 +22,13 @@ class WecomAIQueueMgr:

        self.pending_responses: dict[str, dict[str, Any]] = {}
        """待处理的响应缓存，用于流式响应"""
+        self.completed_streams: dict[str, float] = {}
+        """已结束的 stream 缓存，用于兼容平台后续重复轮询"""
+        self._queue_close_events: dict[str, asyncio.Event] = {}
+        self._listener_tasks: dict[str, asyncio.Task] = {}
+        self._listener_callback: Callable[[dict], Awaitable[None]] | None = None
+        self.queue_maxsize = queue_maxsize
+        self.back_queue_maxsize = back_queue_maxsize

    def get_or_create_queue(self, session_id: str) -> asyncio.Queue:
        """获取或创建指定会话的输入队列
@@ -33,7 +41,9 @@ class WecomAIQueueMgr:

        """
        if session_id not in self.queues:
-            self.queues[session_id] = asyncio.Queue()
+            self.queues[session_id] = asyncio.Queue(maxsize=self.queue_maxsize)
+            self._queue_close_events[session_id] = asyncio.Event()
+            self._start_listener_if_needed(session_id)
            logger.debug(f"[WecomAI] 创建输入队列: {session_id}")
        return self.queues[session_id]

@@ -48,20 +58,21 @@ class WecomAIQueueMgr:

        """
        if session_id not in self.back_queues:
-            self.back_queues[session_id] = asyncio.Queue()
+            self.back_queues[session_id] = asyncio.Queue(
+                maxsize=self.back_queue_maxsize
+            )
            logger.debug(f"[WecomAI] 创建输出队列: {session_id}")
        return self.back_queues[session_id]

-    def remove_queues(self, session_id: str):
+    def remove_queues(self, session_id: str, mark_finished: bool = False):
        """移除指定会话的所有队列

        Args:
            session_id: 会话ID
+            mark_finished: 是否标记为已正常结束

        """
-        if session_id in self.queues:
-            del self.queues[session_id]
-            logger.debug(f"[WecomAI] 移除输入队列: {session_id}")
+        self.remove_queue(session_id)

        if session_id in self.back_queues:
            del self.back_queues[session_id]
@@ -70,6 +81,23 @@ class WecomAIQueueMgr:
        if session_id in self.pending_responses:
            del self.pending_responses[session_id]
            logger.debug(f"[WecomAI] 移除待处理响应: {session_id}")
+        if mark_finished:
+            self.completed_streams[session_id] = asyncio.get_event_loop().time()
+            logger.debug(f"[WecomAI] 标记流已结束: {session_id}")
+
+    def remove_queue(self, session_id: str):
+        """仅移除输入队列和对应监听任务"""
+        if session_id in self.queues:
+            del self.queues[session_id]
+            logger.debug(f"[WecomAI] 移除输入队列: {session_id}")
+
+        close_event = self._queue_close_events.pop(session_id, None)
+        if close_event is not None:
+            close_event.set()
+
+        task = self._listener_tasks.pop(session_id, None)
+        if task is not None:
+            task.cancel()

    def has_queue(self, session_id: str) -> bool:
        """检查是否存在指定会话的队列
@@ -121,6 +149,20 @@ class WecomAIQueueMgr:
        """
        return self.pending_responses.get(session_id)

+    def is_stream_finished(
+        self,
+        session_id: str,
+        max_age_seconds: int = 60,
+    ) -> bool:
+        """判断 stream 是否在短期内已结束"""
+        finished_at = self.completed_streams.get(session_id)
+        if finished_at is None:
+            return False
+        if asyncio.get_event_loop().time() - finished_at > max_age_seconds:
+            self.completed_streams.pop(session_id, None)
+            return False
+        return True
+
    def cleanup_expired_responses(self, max_age_seconds: int = 300):
        """清理过期的待处理响应

@@ -136,8 +178,75 @@ class WecomAIQueueMgr:
                expired_sessions.append(session_id)

        for session_id in expired_sessions:
-            del self.pending_responses[session_id]
-            logger.debug(f"[WecomAI] 清理过期响应: {session_id}")
+            self.remove_queues(session_id)
+            logger.debug(f"[WecomAI] 清理过期响应及队列: {session_id}")
+        expired_finished = [
+            session_id
+            for session_id, finished_at in self.completed_streams.items()
+            if current_time - finished_at > 60
+        ]
+        for session_id in expired_finished:
+            self.completed_streams.pop(session_id, None)
+
+    def set_listener(
+        self,
+        callback: Callable[[dict], Awaitable[None]],
+    ):
+        self._listener_callback = callback
+        for session_id in list(self.queues.keys()):
+            self._start_listener_if_needed(session_id)
+
+    def _start_listener_if_needed(self, session_id: str):
+        if self._listener_callback is None:
+            return
+        if session_id in self._listener_tasks:
+            task = self._listener_tasks[session_id]
+            if not task.done():
+                return
+        queue = self.queues.get(session_id)
+        close_event = self._queue_close_events.get(session_id)
+        if queue is None or close_event is None:
+            return
+        task = asyncio.create_task(
+            self._listen_to_queue(session_id, queue, close_event),
+            name=f"wecomai_listener_{session_id}",
+        )
+        self._listener_tasks[session_id] = task
+        task.add_done_callback(lambda _: self._listener_tasks.pop(session_id, None))
+        logger.debug(f"[WecomAI] 为会话启动监听器: {session_id}")
+
+    async def _listen_to_queue(
+        self,
+        session_id: str,
+        queue: asyncio.Queue,
+        close_event: asyncio.Event,
+    ):
+        while True:
+            get_task = asyncio.create_task(queue.get())
+            close_task = asyncio.create_task(close_event.wait())
+            try:
+                done, pending = await asyncio.wait(
+                    {get_task, close_task},
+                    return_when=asyncio.FIRST_COMPLETED,
+                )
+                for task in pending:
+                    task.cancel()
+                if close_task in done:
+                    break
+                data = get_task.result()
+                if self._listener_callback is None:
+                    continue
+                try:
+                    await self._listener_callback(data)
+                except Exception as e:
+                    logger.error(f"处理会话 {session_id} 消息时发生错误: {e}")
+            except asyncio.CancelledError:
+                break
+            finally:
+                if not get_task.done():
+                    get_task.cancel()
+                if not close_task.done():
+                    close_task.cancel()

    def get_stats(self) -> dict[str, int]:
        """获取队列统计信息
@@ -3,6 +3,7 @@ import json
 from collections.abc import AsyncGenerator

 import anthropic
+import httpx
 from anthropic import AsyncAnthropic
 from anthropic.types import Message
 from anthropic.types.message_delta_usage import MessageDeltaUsage
@@ -14,6 +15,11 @@ from astrbot.core.agent.message import ContentPart, ImageURLPart, TextPart
 from astrbot.core.provider.entities import LLMResponse, TokenUsage
 from astrbot.core.provider.func_tool_manager import ToolSet
 from astrbot.core.utils.io import download_image_by_url
+from astrbot.core.utils.network_utils import (
+    create_proxy_client,
+    is_connection_error,
+    log_connection_failure,
+)

 from ..register import register_provider_adapter

@@ -45,12 +51,18 @@ class ProviderAnthropic(Provider):
            api_key=self.chosen_api_key,
            timeout=self.timeout,
            base_url=self.base_url,
+            http_client=self._create_http_client(provider_config),
        )

        self.thinking_config = provider_config.get("anth_thinking_config", {})

        self.set_model(provider_config.get("model", "unknown"))

+    def _create_http_client(self, provider_config: dict) -> httpx.AsyncClient | None:
+        """创建带代理的 HTTP 客户端"""
+        proxy = provider_config.get("proxy", "")
+        return create_proxy_client("Anthropic", proxy)
+
    def _prepare_payload(self, messages: list[dict]):
        """准备 Anthropic API 的请求 payload

@@ -207,9 +219,19 @@ class ProviderAnthropic(Provider):
                "type": "enabled",
            }

-        completion = await self.client.messages.create(
-            **payloads, stream=False, extra_body=extra_body
-        )
+        try:
+            completion = await self.client.messages.create(
+                **payloads, stream=False, extra_body=extra_body
+            )
+        except httpx.RequestError as e:
+            proxy = self.provider_config.get("proxy", "")
+            log_connection_failure("Anthropic", e, proxy)
+            raise
+        except Exception as e:
+            if is_connection_error(e):
+                proxy = self.provider_config.get("proxy", "")
+                log_connection_failure("Anthropic", e, proxy)
+            raise

        assert isinstance(completion, Message)
        logger.debug(f"completion: {completion}")
@@ -622,3 +644,7 @@ class ProviderAnthropic(Provider):

    def set_key(self, key: str):
        self.chosen_api_key = key
+
+    async def terminate(self):
+        if self.client:
+            await self.client.close()
@@ -10,6 +10,7 @@ from xml.sax.saxutils import escape

 from httpx import AsyncClient, Timeout

+from astrbot import logger
 from astrbot.core.config.default import VERSION

 from ..entities import ProviderType
@@ -29,6 +30,9 @@ class OTTSProvider:
        self.last_sync_time = 0
        self.timeout = Timeout(10.0)
        self.retry_count = 3
+        self.proxy = config.get("proxy", "")
+        if self.proxy:
+            logger.info(f"[Azure TTS] 使用代理: {self.proxy}")
        self._client: AsyncClient | None = None

    @property
@@ -40,7 +44,9 @@ class OTTSProvider:
        return self._client

    async def __aenter__(self):
-        self._client = AsyncClient(timeout=self.timeout)
+        self._client = AsyncClient(
+            timeout=self.timeout, proxy=self.proxy if self.proxy else None
+        )
        return self

    async def __aexit__(self, exc_type, exc_val, exc_tb):
@@ -125,6 +131,9 @@ class AzureNativeProvider(TTSProvider):
            "rate": provider_config.get("azure_tts_rate", "1"),
            "volume": provider_config.get("azure_tts_volume", "100"),
        }
+        self.proxy = provider_config.get("proxy", "")
+        if self.proxy:
+            logger.info(f"[Azure TTS Native] 使用代理: {self.proxy}")

    @property
    def client(self) -> AsyncClient:
@@ -141,6 +150,7 @@ class AzureNativeProvider(TTSProvider):
                "Content-Type": "application/ssml+xml",
                "X-Microsoft-OutputFormat": "riff-48khz-16bit-mono-pcm",
            },
+            proxy=self.proxy if self.proxy else None,
        )
        return self

@@ -7,6 +7,7 @@ import ormsgpack
 from httpx import AsyncClient
 from pydantic import BaseModel, conint

+from astrbot import logger
 from astrbot.core.utils.astrbot_path import get_astrbot_data_path

 from ..entities import ProviderType
@@ -60,10 +61,13 @@ class ProviderFishAudioTTSAPI(TTSProvider):
            self.timeout: int = int(provider_config.get("timeout", 20))
        except ValueError:
            self.timeout = 20
+        self.proxy: str = provider_config.get("proxy", "")
+        if self.proxy:
+            logger.info(f"[FishAudio TTS] 使用代理: {self.proxy}")
        self.headers = {
            "Authorization": f"Bearer {self.chosen_api_key}",
        }
-        self.set_model(provider_config.get("model", None))
+        self.set_model(provider_config.get("model", ""))

    async def _get_reference_id_by_character(self, character: str) -> str | None:
        """获取角色的reference_id
@@ -79,7 +83,10 @@ class ProviderFishAudioTTSAPI(TTSProvider):

        """
        sort_options = ["score", "task_count", "created_at"]
-        async with AsyncClient(base_url=self.api_base.replace("/v1", "")) as client:
+        async with AsyncClient(
+            base_url=self.api_base.replace("/v1", ""),
+            proxy=self.proxy if self.proxy else None,
+        ) as client:
            for sort_by in sort_options:
                params = {"title": character, "sort_by": sort_by}
                response = await client.get(
@@ -139,7 +146,11 @@ class ProviderFishAudioTTSAPI(TTSProvider):
        path = os.path.join(temp_dir, f"fishaudio_tts_api_{uuid.uuid4()}.wav")
        self.headers["content-type"] = "application/msgpack"
        request = await self._generate_request(text)
-        async with AsyncClient(base_url=self.api_base, timeout=self.timeout).stream(
+        async with AsyncClient(
+            base_url=self.api_base,
+            timeout=self.timeout,
+            proxy=self.proxy if self.proxy else None,
+        ).stream(
            "POST",
            "/tts",
            headers=self.headers,
@@ -4,6 +4,8 @@ from google import genai
 from google.genai import types
 from google.genai.errors import APIError

+from astrbot import logger
+
 from ..entities import ProviderType
 from ..provider import EmbeddingProvider
 from ..register import register_provider_adapter
@@ -28,6 +30,10 @@ class GeminiEmbeddingProvider(EmbeddingProvider):
        if api_base:
            api_base = api_base.removesuffix("/")
            http_options.base_url = api_base
+        proxy = provider_config.get("proxy", "")
+        if proxy:
+            http_options.async_client_args = {"proxy": proxy}
+            logger.info(f"[Gemini Embedding] 使用代理: {proxy}")

        self.client = genai.Client(api_key=api_key, http_options=http_options).aio

@@ -69,3 +75,7 @@ class GeminiEmbeddingProvider(EmbeddingProvider):
    def get_dim(self) -> int:
        """获取向量的维度"""
        return int(self.provider_config.get("embedding_dimensions", 768))
+
+    async def terminate(self):
+        if self.client:
+            await self.client.aclose()
@@ -18,6 +18,7 @@ from astrbot.core.message.message_event_result import MessageChain
 from astrbot.core.provider.entities import LLMResponse, TokenUsage
 from astrbot.core.provider.func_tool_manager import ToolSet
 from astrbot.core.utils.io import download_image_by_url
+from astrbot.core.utils.network_utils import is_connection_error, log_connection_failure

 from ..register import register_provider_adapter

@@ -74,12 +75,17 @@ class ProviderGoogleGenAI(Provider):

    def _init_client(self) -> None:
        """初始化Gemini客户端"""
+        proxy = self.provider_config.get("proxy", "")
+        http_options = types.HttpOptions(
+            base_url=self.api_base,
+            timeout=self.timeout * 1000,  # 毫秒
+        )
+        if proxy:
+            http_options.async_client_args = {"proxy": proxy}
+            logger.info(f"[Gemini] 使用代理: {proxy}")
        self.client = genai.Client(
            api_key=self.chosen_api_key,
-            http_options=types.HttpOptions(
-                base_url=self.api_base,
-                timeout=self.timeout * 1000,  # 毫秒
-            ),
+            http_options=http_options,
        ).aio

    def _init_safety_settings(self) -> None:
@@ -113,9 +119,12 @@ class ProviderGoogleGenAI(Provider):
                f"检测到 Key 异常({e.message})，且已没有可用的 Key。 当前 Key: {self.chosen_api_key[:12]}...",
            )
            raise Exception("达到了 Gemini 速率限制, 请稍后再试...")
-        # logger.error(
-        #     f"发生了错误(gemini_source)。Provider 配置如下: {self.provider_config}",
-        # )
+
+        # 连接错误处理
+        if is_connection_error(e):
+            proxy = self.provider_config.get("proxy", "")
+            log_connection_failure("Gemini", e, proxy)
+
        raise e

    async def _prepare_query_config(
@@ -920,4 +929,5 @@ class ProviderGoogleGenAI(Provider):
            return "data:image/jpeg;base64," + image_bs64

    async def terminate(self):
-        logger.info("Google GenAI 适配器已终止。")
+        if self.client:
+            await self.client.aclose()
@@ -5,6 +5,7 @@ import wave
 from google import genai
 from google.genai import types

+from astrbot import logger
 from astrbot.core.utils.astrbot_path import get_astrbot_data_path

 from ..entities import ProviderType
@@ -32,6 +33,10 @@ class ProviderGeminiTTSAPI(TTSProvider):
        if api_base:
            api_base = api_base.removesuffix("/")
            http_options.base_url = api_base
+        proxy = provider_config.get("proxy", "")
+        if proxy:
+            http_options.async_client_args = {"proxy": proxy}
+            logger.info(f"[Gemini TTS] 使用代理: {proxy}")

        self.client = genai.Client(api_key=api_key, http_options=http_options).aio
        self.model: str = provider_config.get(
@@ -79,3 +84,7 @@ class ProviderGeminiTTSAPI(TTSProvider):
            wf.writeframes(response.candidates[0].content.parts[0].inline_data.data)

        return path
+
+    async def terminate(self):
+        if self.client:
+            await self.client.aclose()
@@ -1,5 +1,8 @@
+import httpx
 from openai import AsyncOpenAI

+from astrbot import logger
+
 from ..entities import ProviderType
 from ..provider import EmbeddingProvider
 from ..register import register_provider_adapter
@@ -15,6 +18,11 @@ class OpenAIEmbeddingProvider(EmbeddingProvider):
        super().__init__(provider_config, provider_settings)
        self.provider_config = provider_config
        self.provider_settings = provider_settings
+        proxy = provider_config.get("proxy", "")
+        http_client = None
+        if proxy:
+            logger.info(f"[OpenAI Embedding] 使用代理: {proxy}")
+            http_client = httpx.AsyncClient(proxy=proxy)
        self.client = AsyncOpenAI(
            api_key=provider_config.get("embedding_api_key"),
            base_url=provider_config.get(
@@ -22,6 +30,7 @@ class OpenAIEmbeddingProvider(EmbeddingProvider):
                "https://api.openai.com/v1",
            ),
            timeout=int(provider_config.get("timeout", 20)),
+            http_client=http_client,
        )
        self.model = provider_config.get("embedding_model", "text-embedding-3-small")

@@ -38,3 +47,7 @@ class OpenAIEmbeddingProvider(EmbeddingProvider):
    def get_dim(self) -> int:
        """获取向量的维度"""
        return int(self.provider_config.get("embedding_dimensions", 1024))
+
+    async def terminate(self):
+        if self.client:
+            await self.client.close()
@@ -2,11 +2,11 @@ import asyncio
 import base64
 import inspect
 import json
-import os
 import random
 import re
 from collections.abc import AsyncGenerator

+import httpx
 from openai import AsyncAzureOpenAI, AsyncOpenAI
 from openai._exceptions import NotFoundError
 from openai.lib.streaming.chat._completions import ChatCompletionStreamState
@@ -22,6 +22,11 @@ from astrbot.core.agent.tool import ToolSet
 from astrbot.core.message.message_event_result import MessageChain
 from astrbot.core.provider.entities import LLMResponse, TokenUsage, ToolCallsResult
 from astrbot.core.utils.io import download_image_by_url
+from astrbot.core.utils.network_utils import (
+    create_proxy_client,
+    is_connection_error,
+    log_connection_failure,
+)

 from ..register import register_provider_adapter

@@ -31,6 +36,11 @@ from ..register import register_provider_adapter
    "OpenAI API Chat Completion 提供商适配器",
 )
 class ProviderOpenAIOfficial(Provider):
+    def _create_http_client(self, provider_config: dict) -> httpx.AsyncClient | None:
+        """创建带代理的 HTTP 客户端"""
+        proxy = provider_config.get("proxy", "")
+        return create_proxy_client("OpenAI", proxy)
+
    def __init__(self, provider_config, provider_settings) -> None:
        super().__init__(provider_config, provider_settings)
        self.chosen_api_key = None
@@ -55,6 +65,7 @@ class ProviderOpenAIOfficial(Provider):
                default_headers=self.custom_headers,
                base_url=provider_config.get("api_base", ""),
                timeout=self.timeout,
+                http_client=self._create_http_client(provider_config),
            )
        else:
            # Using OpenAI Official API
@@ -63,6 +74,7 @@ class ProviderOpenAIOfficial(Provider):
                base_url=provider_config.get("api_base", None),
                default_headers=self.custom_headers,
                timeout=self.timeout,
+                http_client=self._create_http_client(provider_config),
            )

        self.default_params = inspect.signature(
@@ -455,12 +467,9 @@ class ProviderOpenAIOfficial(Provider):
        if "tool" in str(e).lower() and "support" in str(e).lower():
            logger.error("疑似该模型不支持函数调用工具调用。请输入 /tool off_all")

-        if "Connection error." in str(e):
-            proxy = os.environ.get("http_proxy", None)
-            if proxy:
-                logger.error(
-                    f"可能为代理原因，请检查代理是否正常。当前代理: {proxy}",
-                )
+        if is_connection_error(e):
+            proxy = self.provider_config.get("proxy", "")
+            log_connection_failure("OpenAI", e, proxy)

        raise e

@@ -697,3 +706,7 @@ class ProviderOpenAIOfficial(Provider):
        with open(image_url, "rb") as f:
            image_bs64 = base64.b64encode(f.read()).decode("utf-8")
            return "data:image/jpeg;base64," + image_bs64
+
+    async def terminate(self):
+        if self.client:
+            await self.client.close()
@@ -1,8 +1,10 @@
 import os
 import uuid

+import httpx
 from openai import NOT_GIVEN, AsyncOpenAI

+from astrbot import logger
 from astrbot.core.utils.astrbot_path import get_astrbot_data_path

 from ..entities import ProviderType
@@ -29,10 +31,16 @@ class ProviderOpenAITTSAPI(TTSProvider):
        if isinstance(timeout, str):
            timeout = int(timeout)

+        proxy = provider_config.get("proxy", "")
+        http_client = None
+        if proxy:
+            logger.info(f"[OpenAI TTS] 使用代理: {proxy}")
+            http_client = httpx.AsyncClient(proxy=proxy)
        self.client = AsyncOpenAI(
            api_key=self.chosen_api_key,
            base_url=provider_config.get("api_base"),
            timeout=timeout,
+            http_client=http_client,
        )

        self.set_model(provider_config.get("model", ""))
@@ -50,3 +58,7 @@ class ProviderOpenAITTSAPI(TTSProvider):
                async for chunk in response.iter_bytes(chunk_size=1024):
                    f.write(chunk)
        return path
+
+    async def terminate(self):
+        if self.client:
+            await self.client.close()
@@ -107,3 +107,7 @@ class ProviderOpenAIWhisperAPI(STTProvider):
            except Exception as e:
                logger.error(f"Failed to remove temp file {audio_url}: {e}")
        return result.text
+
+    async def terminate(self):
+        if self.client:
+            await self.client.close()
@@ -4,6 +4,7 @@ from collections import defaultdict
 from dataclasses import dataclass, field
 from typing import Any

+from astrbot.api import sp
 from astrbot.core import db_helper, logger
 from astrbot.core.db.po import CommandConfig
 from astrbot.core.star.filter.command import CommandFilter
@@ -139,6 +140,51 @@ async def rename_command(
    return descriptor


+async def update_command_permission(
+    handler_full_name: str,
+    permission_type: str,
+) -> CommandDescriptor:
+    descriptor = _build_descriptor_by_full_name(handler_full_name)
+    if not descriptor:
+        raise ValueError("指定的处理函数不存在或不是指令。")
+
+    if permission_type not in ["admin", "member"]:
+        raise ValueError("权限类型必须为 admin 或 member。")
+
+    handler = descriptor.handler
+    found_plugin = star_map.get(handler.handler_module_path)
+    if not found_plugin:
+        raise ValueError("未找到指令所属插件")
+
+    # 1. Update Persistent Config (alter_cmd)
+    alter_cmd_cfg = await sp.global_get("alter_cmd", {})
+    plugin_ = alter_cmd_cfg.get(found_plugin.name, {})
+    cfg = plugin_.get(handler.handler_name, {})
+    cfg["permission"] = permission_type
+    plugin_[handler.handler_name] = cfg
+    alter_cmd_cfg[found_plugin.name] = plugin_
+
+    await sp.global_put("alter_cmd", alter_cmd_cfg)
+
+    # 2. Update Runtime Filter
+    found_permission_filter = False
+    target_perm_type = (
+        PermissionType.ADMIN if permission_type == "admin" else PermissionType.MEMBER
+    )
+
+    for filter_ in handler.event_filters:
+        if isinstance(filter_, PermissionTypeFilter):
+            filter_.permission_type = target_perm_type
+            found_permission_filter = True
+            break
+
+    if not found_permission_filter:
+        handler.event_filters.insert(0, PermissionTypeFilter(target_perm_type))
+
+    # Re-build descriptor to reflect changes
+    return _build_descriptor(handler) or descriptor
+
+
 async def list_commands() -> list[dict[str, Any]]:
    descriptors = _collect_descriptors(include_sub_commands=True)
    config_records = await db_helper.get_command_configs()
@@ -57,14 +57,20 @@ class AstrBotUpdator(RepoZipUpdator):
            py = sys.executable

        try:
-            if "astrbot" in os.path.basename(sys.argv[0]):  # 兼容cli
+            # 仅 CLI 模式走 `python -m astrbot.cli.__main__`，
+            # 打包后的后端可执行文件需要直接 exec 自身。
+            if os.environ.get("ASTRBOT_CLI") == "1":
                if os.name == "nt":
                    args = [f'"{arg}"' if " " in arg else arg for arg in sys.argv[1:]]
                else:
                    args = sys.argv[1:]
                os.execl(sys.executable, py, "-m", "astrbot.cli.__main__", *args)
            else:
-                os.execl(sys.executable, py, *sys.argv)
+                if getattr(sys, "frozen", False):
+                    # Frozen executable should not receive argv[0] as a positional argument.
+                    os.execl(sys.executable, py, *sys.argv[1:])
+                else:
+                    os.execl(sys.executable, py, *sys.argv)
        except Exception as e:
            logger.error(f"重启失败（{py}, {e}），请尝试手动重启。")
            raise e
@@ -10,6 +10,7 @@ T2I 模板目录路径：固定为数据目录下的 t2i_templates 目录
 WebChat 数据目录路径：固定为数据目录下的 webchat 目录
 临时文件目录路径：固定为数据目录下的 temp 目录
 Skills 目录路径：固定为数据目录下的 skills 目录
+第三方依赖目录路径：固定为数据目录下的 site-packages 目录
 """

 import os
@@ -69,6 +70,11 @@ def get_astrbot_skills_path() -> str:
    return os.path.realpath(os.path.join(get_astrbot_data_path(), "skills"))


+def get_astrbot_site_packages_path() -> str:
+    """获取Astrbot第三方依赖目录路径"""
+    return os.path.realpath(os.path.join(get_astrbot_data_path(), "site-packages"))
+
+
 def get_astrbot_knowledge_base_path() -> str:
    """获取Astrbot知识库根目录路径"""
    return os.path.realpath(os.path.join(get_astrbot_data_path(), "knowledge_base"))
@@ -0,0 +1,207 @@
+"""媒体文件处理工具
+
+提供音视频格式转换、时长获取等功能。
+"""
+
+import asyncio
+import os
+import subprocess
+import uuid
+
+from astrbot import logger
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
+
+
+async def get_media_duration(file_path: str) -> int | None:
+    """使用ffprobe获取媒体文件时长
+
+    Args:
+        file_path: 媒体文件路径
+
+    Returns:
+        时长（毫秒），如果获取失败返回None
+    """
+    try:
+        # 使用ffprobe获取时长
+        process = await asyncio.create_subprocess_exec(
+            "ffprobe",
+            "-v",
+            "error",
+            "-show_entries",
+            "format=duration",
+            "-of",
+            "default=noprint_wrappers=1:nokey=1",
+            file_path,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.PIPE,
+        )
+
+        stdout, stderr = await process.communicate()
+
+        if process.returncode == 0 and stdout:
+            duration_seconds = float(stdout.decode().strip())
+            duration_ms = int(duration_seconds * 1000)
+            logger.debug(f"[Media Utils] 获取媒体时长: {duration_ms}ms")
+            return duration_ms
+        else:
+            logger.warning(f"[Media Utils] 无法获取媒体文件时长: {file_path}")
+            return None
+
+    except FileNotFoundError:
+        logger.warning(
+            "[Media Utils] ffprobe未安装或不在PATH中，无法获取媒体时长。请安装ffmpeg: https://ffmpeg.org/"
+        )
+        return None
+    except Exception as e:
+        logger.warning(f"[Media Utils] 获取媒体时长时出错: {e}")
+        return None
+
+
+async def convert_audio_to_opus(audio_path: str, output_path: str | None = None) -> str:
+    """使用ffmpeg将音频转换为opus格式
+
+    Args:
+        audio_path: 原始音频文件路径
+        output_path: 输出文件路径，如果为None则自动生成
+
+    Returns:
+        转换后的opus文件路径
+
+    Raises:
+        Exception: 转换失败时抛出异常
+    """
+    # 如果已经是opus格式，直接返回
+    if audio_path.lower().endswith(".opus"):
+        return audio_path
+
+    # 生成输出文件路径
+    if output_path is None:
+        temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+        os.makedirs(temp_dir, exist_ok=True)
+        output_path = os.path.join(temp_dir, f"{uuid.uuid4()}.opus")
+
+    try:
+        # 使用ffmpeg转换为opus格式
+        # -y: 覆盖输出文件
+        # -i: 输入文件
+        # -acodec libopus: 使用opus编码器
+        # -ac 1: 单声道
+        # -ar 16000: 采样率16kHz
+        process = await asyncio.create_subprocess_exec(
+            "ffmpeg",
+            "-y",
+            "-i",
+            audio_path,
+            "-acodec",
+            "libopus",
+            "-ac",
+            "1",
+            "-ar",
+            "16000",
+            output_path,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.PIPE,
+        )
+
+        stdout, stderr = await process.communicate()
+
+        if process.returncode != 0:
+            # 清理可能已生成但无效的临时文件
+            if output_path and os.path.exists(output_path):
+                try:
+                    os.remove(output_path)
+                    logger.debug(
+                        f"[Media Utils] 已清理失败的opus输出文件: {output_path}"
+                    )
+                except OSError as e:
+                    logger.warning(f"[Media Utils] 清理失败的opus输出文件时出错: {e}")
+
+            error_msg = stderr.decode() if stderr else "未知错误"
+            logger.error(f"[Media Utils] ffmpeg转换音频失败: {error_msg}")
+            raise Exception(f"ffmpeg conversion failed: {error_msg}")
+
+        logger.debug(f"[Media Utils] 音频转换成功: {audio_path} -> {output_path}")
+        return output_path
+
+    except FileNotFoundError:
+        logger.error(
+            "[Media Utils] ffmpeg未安装或不在PATH中，无法转换音频格式。请安装ffmpeg: https://ffmpeg.org/"
+        )
+        raise Exception("ffmpeg not found")
+    except Exception as e:
+        logger.error(f"[Media Utils] 转换音频格式时出错: {e}")
+        raise
+
+
+async def convert_video_format(
+    video_path: str, output_format: str = "mp4", output_path: str | None = None
+) -> str:
+    """使用ffmpeg转换视频格式
+
+    Args:
+        video_path: 原始视频文件路径
+        output_format: 目标格式，默认mp4
+        output_path: 输出文件路径，如果为None则自动生成
+
+    Returns:
+        转换后的视频文件路径
+
+    Raises:
+        Exception: 转换失败时抛出异常
+    """
+    # 如果已经是目标格式，直接返回
+    if video_path.lower().endswith(f".{output_format}"):
+        return video_path
+
+    # 生成输出文件路径
+    if output_path is None:
+        temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+        os.makedirs(temp_dir, exist_ok=True)
+        output_path = os.path.join(temp_dir, f"{uuid.uuid4()}.{output_format}")
+
+    try:
+        # 使用ffmpeg转换视频格式
+        process = await asyncio.create_subprocess_exec(
+            "ffmpeg",
+            "-y",
+            "-i",
+            video_path,
+            "-c:v",
+            "libx264",
+            "-c:a",
+            "aac",
+            output_path,
+            stdout=subprocess.PIPE,
+            stderr=subprocess.PIPE,
+        )
+
+        stdout, stderr = await process.communicate()
+
+        if process.returncode != 0:
+            # 清理可能已生成但无效的临时文件
+            if output_path and os.path.exists(output_path):
+                try:
+                    os.remove(output_path)
+                    logger.debug(
+                        f"[Media Utils] 已清理失败的{output_format}输出文件: {output_path}"
+                    )
+                except OSError as e:
+                    logger.warning(
+                        f"[Media Utils] 清理失败的{output_format}输出文件时出错: {e}"
+                    )
+
+            error_msg = stderr.decode() if stderr else "未知错误"
+            logger.error(f"[Media Utils] ffmpeg转换视频失败: {error_msg}")
+            raise Exception(f"ffmpeg conversion failed: {error_msg}")
+
+        logger.debug(f"[Media Utils] 视频转换成功: {video_path} -> {output_path}")
+        return output_path
+
+    except FileNotFoundError:
+        logger.error(
+            "[Media Utils] ffmpeg未安装或不在PATH中，无法转换视频格式。请安装ffmpeg: https://ffmpeg.org/"
+        )
+        raise Exception("ffmpeg not found")
+    except Exception as e:
+        logger.error(f"[Media Utils] 转换视频格式时出错: {e}")
+        raise
@@ -0,0 +1,104 @@
+"""Network error handling utilities for providers."""
+
+import httpx
+
+from astrbot import logger
+
+
+def is_connection_error(exc: BaseException) -> bool:
+    """Check if an exception is a connection/network related error.
+
+    Uses explicit exception type checking instead of brittle string matching.
+    Handles httpx network errors, timeouts, and common Python network exceptions.
+
+    Args:
+        exc: The exception to check
+
+    Returns:
+        True if the exception is a connection/network error
+    """
+    # Check for httpx network errors
+    if isinstance(
+        exc,
+        (
+            httpx.ConnectError,
+            httpx.ConnectTimeout,
+            httpx.ReadTimeout,
+            httpx.WriteTimeout,
+            httpx.PoolTimeout,
+            httpx.NetworkError,
+            httpx.ProxyError,
+            httpx.RequestError,
+        ),
+    ):
+        return True
+
+    # Check for common Python network errors
+    if isinstance(exc, (TimeoutError, OSError, ConnectionError)):
+        return True
+
+    # Check the __cause__ chain for wrapped connection errors
+    cause = getattr(exc, "__cause__", None)
+    if cause is not None and cause is not exc:
+        return is_connection_error(cause)
+
+    return False
+
+
+def log_connection_failure(
+    provider_label: str,
+    error: Exception,
+    proxy: str | None = None,
+) -> None:
+    """Log a connection failure with proxy information.
+
+    If proxy is not provided, will fallback to check os.environ for
+    http_proxy/https_proxy environment variables.
+
+    Args:
+        provider_label: The provider name for log prefix (e.g., "OpenAI", "Gemini")
+        error: The exception that occurred
+        proxy: The proxy address if configured, or None/empty string
+    """
+    import os
+
+    error_type = type(error).__name__
+
+    # Fallback to environment proxy if not configured
+    effective_proxy = proxy
+    if not effective_proxy:
+        effective_proxy = os.environ.get(
+            "http_proxy", os.environ.get("https_proxy", "")
+        )
+
+    if effective_proxy:
+        logger.error(
+            f"[{provider_label}] 网络/代理连接失败 ({error_type})。"
+            f"代理地址: {effective_proxy}，错误: {error}"
+        )
+    else:
+        logger.error(
+            f"[{provider_label}] 网络连接失败 ({error_type})，未配置代理。错误: {error}"
+        )
+
+
+def create_proxy_client(
+    provider_label: str,
+    proxy: str | None = None,
+) -> httpx.AsyncClient | None:
+    """Create an httpx AsyncClient with proxy configuration if provided.
+
+    Note: The caller is responsible for closing the client when done.
+    Consider using the client as a context manager or calling aclose() explicitly.
+
+    Args:
+        provider_label: The provider name for log prefix (e.g., "OpenAI", "Gemini")
+        proxy: The proxy address (e.g., "http://127.0.0.1:7890"), or None/empty
+
+    Returns:
+        An httpx.AsyncClient configured with the proxy, or None if no proxy
+    """
+    if proxy:
+        logger.info(f"[{provider_label}] 使用代理: {proxy}")
+        return httpx.AsyncClient(proxy=proxy)
+    return None
@@ -1,8 +1,14 @@
 import asyncio
+import contextlib
+import importlib
+import io
 import locale
 import logging
+import os
 import sys

+from astrbot.core.utils.astrbot_path import get_astrbot_site_packages_path
+
 logger = logging.getLogger("astrbot")


@@ -24,6 +30,36 @@ def _robust_decode(line: bytes) -> str:
    return line.decode("utf-8", errors="replace").strip()


+def _is_frozen_runtime() -> bool:
+    return bool(getattr(sys, "frozen", False))
+
+
+def _get_pip_main():
+    try:
+        from pip._internal.cli.main import main as pip_main
+    except ImportError:
+        from pip import main as pip_main
+    return pip_main
+
+
+def _run_pip_main_with_output(pip_main, args: list[str]) -> tuple[int, str]:
+    stream = io.StringIO()
+    with contextlib.redirect_stdout(stream), contextlib.redirect_stderr(stream):
+        result_code = pip_main(args)
+    return result_code, stream.getvalue()
+
+
+def _cleanup_added_root_handlers(original_handlers: list[logging.Handler]) -> None:
+    root_logger = logging.getLogger()
+    original_handler_ids = {id(handler) for handler in original_handlers}
+
+    for handler in list(root_logger.handlers):
+        if id(handler) not in original_handler_ids:
+            root_logger.removeHandler(handler)
+            with contextlib.suppress(Exception):
+                handler.close()
+
+
 class PipInstaller:
    def __init__(self, pip_install_arg: str, pypi_index_url: str | None = None):
        self.pip_install_arg = pip_install_arg
@@ -45,37 +81,59 @@ class PipInstaller:

        args.extend(["--trusted-host", "mirrors.aliyun.com", "-i", index_url])

+        target_site_packages = None
+        if _is_frozen_runtime():
+            target_site_packages = get_astrbot_site_packages_path()
+            os.makedirs(target_site_packages, exist_ok=True)
+            args.extend(["--target", target_site_packages])
+
        if self.pip_install_arg:
            args.extend(self.pip_install_arg.split())

        logger.info(f"Pip 包管理器: pip {' '.join(args)}")
-        try:
-            process = await asyncio.create_subprocess_exec(
-                sys.executable,
-                "-m",
-                "pip",
-                *args,
-                stdout=asyncio.subprocess.PIPE,
-                stderr=asyncio.subprocess.STDOUT,
-            )
+        result_code = None
+        if _is_frozen_runtime():
+            result_code = await self._run_pip_in_process(args)
+        else:
+            try:
+                result_code = await self._run_pip_subprocess(args)
+            except FileNotFoundError:
+                result_code = await self._run_pip_in_process(args)

-            assert process.stdout is not None
-            async for line in process.stdout:
-                logger.info(_robust_decode(line))
+        if result_code != 0:
+            raise Exception(f"安装失败，错误码：{result_code}")

-            await process.wait()
+        if target_site_packages and target_site_packages not in sys.path:
+            sys.path.insert(0, target_site_packages)
+        importlib.invalidate_caches()

-            if process.returncode != 0:
-                raise Exception(f"安装失败，错误码：{process.returncode}")
-        except FileNotFoundError:
-            # 没有 pip
-            from pip import main as pip_main
+    async def _run_pip_subprocess(self, args: list[str]) -> int:
+        process = await asyncio.create_subprocess_exec(
+            sys.executable,
+            "-m",
+            "pip",
+            *args,
+            stdout=asyncio.subprocess.PIPE,
+            stderr=asyncio.subprocess.STDOUT,
+        )

-            result_code = await asyncio.to_thread(pip_main, args)
+        assert process.stdout is not None
+        async for line in process.stdout:
+            logger.info(_robust_decode(line))

-            # 清除 pip.main 导致的多余的 logging handlers
-            for handler in logging.root.handlers[:]:
-                logging.root.removeHandler(handler)
+        await process.wait()
+        return process.returncode

-            if result_code != 0:
-                raise Exception(f"安装失败，错误码：{result_code}")
+    async def _run_pip_in_process(self, args: list[str]) -> int:
+        pip_main = _get_pip_main()
+        original_handlers = list(logging.getLogger().handlers)
+        result_code, output = await asyncio.to_thread(
+            _run_pip_main_with_output, pip_main, args
+        )
+        for line in output.splitlines():
+            line = line.strip()
+            if line:
+                logger.info(line)
+
+        _cleanup_added_root_handlers(original_handlers)
+        return result_code
@@ -23,7 +23,7 @@ class SharedPreferences:
            )
        self.path = json_storage_path
        self.db_helper = db_helper
-        self.temorary_cache: dict[str, dict[str, Any]] = defaultdict(dict)
+        self.temporary_cache: dict[str, dict[str, Any]] = defaultdict(dict)
        """automatically clear per 24 hours. Might be helpful in some cases XD"""

        self._sync_loop = asyncio.new_event_loop()
@@ -37,7 +37,7 @@ class SharedPreferences:
        self._scheduler.start()

    def _clear_temporary_cache(self):
-        self.temorary_cache.clear()
+        self.temporary_cache.clear()

    async def get_async(
        self,
@@ -238,6 +238,7 @@ class ChatRoute(Route):
        Returns:
            包含 used 列表的字典，记录被引用的搜索结果
        """
+        supported = ["web_search_tavily", "web_search_bocha"]
        # 从 accumulated_parts 中找到所有 web_search_tavily 的工具调用结果
        web_search_results = {}
        tool_call_parts = [
@@ -248,7 +249,7 @@ class ChatRoute(Route):

        for part in tool_call_parts:
            for tool_call in part["tool_calls"]:
-                if tool_call.get("name") != "web_search_tavily" or not tool_call.get(
+                if tool_call.get("name") not in supported or not tool_call.get(
                    "result"
                ):
                    continue
@@ -278,7 +279,7 @@ class ChatRoute(Route):
            if ref_index not in web_search_results:
                continue
            payload = {"index": ref_index, **web_search_results[ref_index]}
-            if favicon := sp.temorary_cache.get("_ws_favicon", {}).get(payload["url"]):
+            if favicon := sp.temporary_cache.get("_ws_favicon", {}).get(payload["url"]):
                payload["favicon"] = favicon
            used_refs.append(payload)

@@ -353,12 +354,15 @@ class ChatRoute(Route):
            return Response().error("session_id is empty").__dict__

        webchat_conv_id = session_id
-        back_queue = webchat_queue_mgr.get_or_create_back_queue(webchat_conv_id)

        # 构建用户消息段（包含 path 用于传递给 adapter）
        message_parts = await self._build_user_message_parts(message)

        message_id = str(uuid.uuid4())
+        back_queue = webchat_queue_mgr.get_or_create_back_queue(
+            message_id,
+            webchat_conv_id,
+        )

        async def stream():
            client_disconnected = False
@@ -531,6 +535,8 @@ class ChatRoute(Route):
                            refs = {}
            except BaseException as e:
                logger.exception(f"WebChat stream unexpected error: {e}", exc_info=True)
+            finally:
+                webchat_queue_mgr.remove_back_queue(message_id)

        # 将消息放入会话特定的队列
        chat_queue = webchat_queue_mgr.get_or_create_queue(webchat_conv_id)
@@ -10,6 +10,9 @@ from astrbot.core.star.command_management import (
 from astrbot.core.star.command_management import (
    toggle_command as toggle_command_service,
 )
+from astrbot.core.star.command_management import (
+    update_command_permission as update_command_permission_service,
+)

 from .route import Response, Route, RouteContext

@@ -22,6 +25,7 @@ class CommandRoute(Route):
            "/commands/conflicts": ("GET", self.get_conflicts),
            "/commands/toggle": ("POST", self.toggle_command),
            "/commands/rename": ("POST", self.rename_command),
+            "/commands/permission": ("POST", self.update_permission),
        }
        self.register_routes()

@@ -74,6 +78,24 @@ class CommandRoute(Route):
        payload = await _get_command_payload(handler_full_name)
        return Response().ok(payload).__dict__

+    async def update_permission(self):
+        data = await request.get_json()
+        handler_full_name = data.get("handler_full_name")
+        permission = data.get("permission")
+
+        if not handler_full_name or not permission:
+            return (
+                Response().error("handler_full_name 与 permission 均为必填。").__dict__
+            )
+
+        try:
+            await update_command_permission_service(handler_full_name, permission)
+        except ValueError as exc:
+            return Response().error(str(exc)).__dict__
+
+        payload = await _get_command_payload(handler_full_name)
+        return Response().ok(payload).__dict__
+

 async def _get_command_payload(handler_full_name: str):
    commands = await list_commands()
@@ -1,4 +1,5 @@
 import asyncio
+import copy
 import inspect
 import os
 import traceback
@@ -407,8 +408,19 @@ class ConfigRoute(Route):
        return Response().ok(message="更新 provider source 成功").__dict__

    async def get_provider_template(self):
+        provider_metadata = ConfigMetadataI18n.convert_to_i18n_keys(
+            {
+                "provider_group": {
+                    "metadata": {
+                        "provider": CONFIG_METADATA_2["provider_group"]["metadata"][
+                            "provider"
+                        ]
+                    }
+                }
+            }
+        )
        config_schema = {
-            "provider": CONFIG_METADATA_2["provider_group"]["metadata"]["provider"]
+            "provider": provider_metadata["provider_group"]["metadata"]["provider"]
        }
        data = {
            "config_schema": config_schema,
@@ -1278,11 +1290,24 @@ class ConfigRoute(Route):

    async def _get_astrbot_config(self):
        config = self.config
+        metadata = copy.deepcopy(CONFIG_METADATA_2)
+        platform_i18n = ConfigMetadataI18n.convert_to_i18n_keys(
+            {
+                "platform_group": {
+                    "metadata": {
+                        "platform": metadata["platform_group"]["metadata"]["platform"]
+                    }
+                }
+            }
+        )
+        metadata["platform_group"]["metadata"]["platform"] = platform_i18n[
+            "platform_group"
+        ]["metadata"]["platform"]

        # 平台适配器的默认配置模板注入
-        platform_default_tmpl = CONFIG_METADATA_2["platform_group"]["metadata"][
-            "platform"
-        ]["config_template"]
+        platform_default_tmpl = metadata["platform_group"]["metadata"]["platform"][
+            "config_template"
+        ]

        # 收集需要注册logo的平台
        logo_registration_tasks = []
@@ -1300,14 +1325,14 @@ class ConfigRoute(Route):
            await asyncio.gather(*logo_registration_tasks, return_exceptions=True)

        # 服务提供商的默认配置模板注入
-        provider_default_tmpl = CONFIG_METADATA_2["provider_group"]["metadata"][
-            "provider"
-        ]["config_template"]
+        provider_default_tmpl = metadata["provider_group"]["metadata"]["provider"][
+            "config_template"
+        ]
        for provider in provider_registry:
            if provider.default_config_tmpl:
                provider_default_tmpl[provider.type] = provider.default_config_tmpl

-        return {"metadata": CONFIG_METADATA_2, "config": config}
+        return {"metadata": metadata, "config": config}

    async def _get_plugin_config(self, plugin_name: str):
        ret: dict = {"metadata": None, "config": None}
@@ -23,7 +23,7 @@ class CronRoute(Route):
        ]
        self.register_routes()

-    def _serialize_job(self, job):
+    def _serialize_job(self, job) -> dict:
        data = job.model_dump() if hasattr(job, "model_dump") else job.__dict__
        for k in ["created_at", "updated_at", "last_run_at", "next_run_time"]:
            if isinstance(data.get(k), datetime):
@@ -4,6 +4,7 @@ import asyncio
 import os
 import traceback
 import uuid
+from typing import Any

 import aiofiles
 from quart import request
@@ -75,7 +76,7 @@ class KnowledgeBaseRoute(Route):
        }

    def _set_task_result(
-        self, task_id: str, status: str, result: any = None, error: str | None = None
+        self, task_id: str, status: str, result: Any = None, error: str | None = None
    ) -> None:
        self.upload_tasks[task_id] = {
            "status": status,
@@ -256,143 +256,148 @@ class LiveChatRoute(Route):
            await queue.put((session.username, cid, payload))

            # 3. 等待响应并流式发送 TTS 音频
-            back_queue = webchat_queue_mgr.get_or_create_back_queue(cid)
+            back_queue = webchat_queue_mgr.get_or_create_back_queue(message_id, cid)

            bot_text = ""
            audio_playing = False

-            while True:
-                if session.should_interrupt:
-                    # 用户打断，停止处理
-                    logger.info("[Live Chat] 检测到用户打断")
-                    await websocket.send_json({"t": "stop_play"})
-                    # 保存消息并标记为被打断
-                    await self._save_interrupted_message(session, user_text, bot_text)
-                    # 清空队列中未处理的消息
-                    while not back_queue.empty():
+            try:
+                while True:
+                    if session.should_interrupt:
+                        # 用户打断，停止处理
+                        logger.info("[Live Chat] 检测到用户打断")
+                        await websocket.send_json({"t": "stop_play"})
+                        # 保存消息并标记为被打断
+                        await self._save_interrupted_message(
+                            session, user_text, bot_text
+                        )
+                        # 清空队列中未处理的消息
+                        while not back_queue.empty():
+                            try:
+                                back_queue.get_nowait()
+                            except asyncio.QueueEmpty:
+                                break
+                        break
+
+                    try:
+                        result = await asyncio.wait_for(back_queue.get(), timeout=0.5)
+                    except asyncio.TimeoutError:
+                        continue
+
+                    if not result:
+                        continue
+
+                    result_message_id = result.get("message_id")
+                    if result_message_id != message_id:
+                        logger.warning(
+                            f"[Live Chat] 消息 ID 不匹配: {result_message_id} != {message_id}"
+                        )
+                        continue
+
+                    result_type = result.get("type")
+                    result_chain_type = result.get("chain_type")
+                    data = result.get("data", "")
+
+                    if result_chain_type == "agent_stats":
                        try:
-                            back_queue.get_nowait()
-                        except asyncio.QueueEmpty:
-                            break
-                    break
+                            stats = json.loads(data)
+                            await websocket.send_json(
+                                {
+                                    "t": "metrics",
+                                    "data": {
+                                        "llm_ttft": stats.get("time_to_first_token", 0),
+                                        "llm_total_time": stats.get("end_time", 0)
+                                        - stats.get("start_time", 0),
+                                    },
+                                }
+                            )
+                        except Exception as e:
+                            logger.error(f"[Live Chat] 解析 AgentStats 失败: {e}")
+                        continue

-                try:
-                    result = await asyncio.wait_for(back_queue.get(), timeout=0.5)
-                except asyncio.TimeoutError:
-                    continue
+                    if result_chain_type == "tts_stats":
+                        try:
+                            stats = json.loads(data)
+                            await websocket.send_json(
+                                {
+                                    "t": "metrics",
+                                    "data": stats,
+                                }
+                            )
+                        except Exception as e:
+                            logger.error(f"[Live Chat] 解析 TTSStats 失败: {e}")
+                        continue

-                if not result:
-                    continue
+                    if result_type == "plain":
+                        # 普通文本消息
+                        bot_text += data

-                result_message_id = result.get("message_id")
-                if result_message_id != message_id:
-                    logger.warning(
-                        f"[Live Chat] 消息 ID 不匹配: {result_message_id} != {message_id}"
-                    )
-                    continue
+                    elif result_type == "audio_chunk":
+                        # 流式音频数据
+                        if not audio_playing:
+                            audio_playing = True
+                            logger.debug("[Live Chat] 开始播放音频流")

-                result_type = result.get("type")
-                result_chain_type = result.get("chain_type")
-                data = result.get("data", "")
+                            # Calculate latency from wav assembly finish to first audio chunk
+                            speak_to_first_frame_latency = (
+                                time.time() - wav_assembly_finish_time
+                            )
+                            await websocket.send_json(
+                                {
+                                    "t": "metrics",
+                                    "data": {
+                                        "speak_to_first_frame": speak_to_first_frame_latency
+                                    },
+                                }
+                            )

-                if result_chain_type == "agent_stats":
-                    try:
-                        stats = json.loads(data)
+                        text = result.get("text")
+                        if text:
+                            await websocket.send_json(
+                                {
+                                    "t": "bot_text_chunk",
+                                    "data": {"text": text},
+                                }
+                            )
+
+                        # 发送音频数据给前端
+                        await websocket.send_json(
+                            {
+                                "t": "response",
+                                "data": data,  # base64 编码的音频数据
+                            }
+                        )
+
+                    elif result_type in ["complete", "end"]:
+                        # 处理完成
+                        logger.info(f"[Live Chat] Bot 回复完成: {bot_text}")
+
+                        # 如果没有音频流，发送 bot 消息文本
+                        if not audio_playing:
+                            await websocket.send_json(
+                                {
+                                    "t": "bot_msg",
+                                    "data": {
+                                        "text": bot_text,
+                                        "ts": int(time.time() * 1000),
+                                    },
+                                }
+                            )
+
+                        # 发送结束标记
+                        await websocket.send_json({"t": "end"})
+
+                        # 发送总耗时
+                        wav_to_tts_duration = time.time() - wav_assembly_finish_time
                        await websocket.send_json(
                            {
                                "t": "metrics",
-                                "data": {
-                                    "llm_ttft": stats.get("time_to_first_token", 0),
-                                    "llm_total_time": stats.get("end_time", 0)
-                                    - stats.get("start_time", 0),
-                                },
+                                "data": {"wav_to_tts_total_time": wav_to_tts_duration},
                            }
                        )
-                    except Exception as e:
-                        logger.error(f"[Live Chat] 解析 AgentStats 失败: {e}")
-                    continue
-
-                if result_chain_type == "tts_stats":
-                    try:
-                        stats = json.loads(data)
-                        await websocket.send_json(
-                            {
-                                "t": "metrics",
-                                "data": stats,
-                            }
-                        )
-                    except Exception as e:
-                        logger.error(f"[Live Chat] 解析 TTSStats 失败: {e}")
-                    continue
-
-                if result_type == "plain":
-                    # 普通文本消息
-                    bot_text += data
-
-                elif result_type == "audio_chunk":
-                    # 流式音频数据
-                    if not audio_playing:
-                        audio_playing = True
-                        logger.debug("[Live Chat] 开始播放音频流")
-
-                        # Calculate latency from wav assembly finish to first audio chunk
-                        speak_to_first_frame_latency = (
-                            time.time() - wav_assembly_finish_time
-                        )
-                        await websocket.send_json(
-                            {
-                                "t": "metrics",
-                                "data": {
-                                    "speak_to_first_frame": speak_to_first_frame_latency
-                                },
-                            }
-                        )
-
-                    text = result.get("text")
-                    if text:
-                        await websocket.send_json(
-                            {
-                                "t": "bot_text_chunk",
-                                "data": {"text": text},
-                            }
-                        )
-
-                    # 发送音频数据给前端
-                    await websocket.send_json(
-                        {
-                            "t": "response",
-                            "data": data,  # base64 编码的音频数据
-                        }
-                    )
-
-                elif result_type in ["complete", "end"]:
-                    # 处理完成
-                    logger.info(f"[Live Chat] Bot 回复完成: {bot_text}")
-
-                    # 如果没有音频流，发送 bot 消息文本
-                    if not audio_playing:
-                        await websocket.send_json(
-                            {
-                                "t": "bot_msg",
-                                "data": {
-                                    "text": bot_text,
-                                    "ts": int(time.time() * 1000),
-                                },
-                            }
-                        )
-
-                    # 发送结束标记
-                    await websocket.send_json({"t": "end"})
-
-                    # 发送总耗时
-                    wav_to_tts_duration = time.time() - wav_assembly_finish_time
-                    await websocket.send_json(
-                        {
-                            "t": "metrics",
-                            "data": {"wav_to_tts_total_time": wav_to_tts_duration},
-                        }
-                    )
-                    break
+                        break
+            finally:
+                webchat_queue_mgr.remove_back_queue(message_id)

        except Exception as e:
            logger.error(f"[Live Chat] 处理音频失败: {e}", exc_info=True)
@@ -2,14 +2,13 @@ import asyncio
 import logging
 import os
 import socket
-from typing import cast
+from typing import Protocol, cast

 import jwt
 import psutil
 from flask.json.provider import DefaultJSONProvider
 from hypercorn.asyncio import serve
 from hypercorn.config import Config as HyperConfig
-from psutil._common import addr as psutil_addr
 from quart import Quart, g, jsonify, request
 from quart.logging import default_handler

@@ -29,6 +28,11 @@ from .routes.session_management import SessionManagementRoute
 from .routes.subagent import SubAgentRoute
 from .routes.t2i import T2iRoute

+
+class _AddrWithPort(Protocol):
+    port: int
+
+
 APP: Quart


@@ -168,7 +172,7 @@ class AstrBotDashboard:
        """获取占用端口的进程详细信息"""
        try:
            for conn in psutil.net_connections(kind="inet"):
-                if cast(psutil_addr, conn.laddr).port == port:
+                if cast(_AddrWithPort, conn.laddr).port == port:
                    try:
                        process = psutil.Process(conn.pid)
                        # 获取详细信息
@@ -0,0 +1,4 @@
+## What's Changed
+
+### 修复
+- 修复 `on_llm_request` 钩子可能无法应用效果的问题
@@ -0,0 +1,4 @@
+## What's Changed
+
+### 修复
+- 修复 token 统计错误的问题，修复在多轮 tool call 情况下或者其他极端情况下可能造成 tool 无限调用的问题。
@@ -0,0 +1,11 @@
+## What's Changed
+
+### Fix
+- fix: `fix: messages[x] assistant content must contain at least one part` after tool calling ([#4928](https://github.com/AstrBotDevs/AstrBot/issues/4928)) after tool calls.
+- fix: TypeError when MCP schema type is a list ([#4867](https://github.com/AstrBotDevs/AstrBot/issues/4867))
+- fix: Fixed an issue that caused scheduled task execution failures with specific providers 修复特定提供商导致的定时任务执行失败的问题 ([#4872](https://github.com/AstrBotDevs/AstrBot/issues/4872))
+
+
+### Feature
+- feat: add bocha web search tool ([#4902](https://github.com/AstrBotDevs/AstrBot/issues/4902))
+- feat: systemd support ([#4880](https://github.com/AstrBotDevs/AstrBot/issues/4880))
@@ -0,0 +1,10 @@
+## What's Changed
+
+### 修复
+- 修复一些原因导致 Tavily WebSearch、Bocha WebSearch 无法使用的问题
+
+### xinzeng
+- 飞书支持 Bot 发送文件、图片和视频消息类型。
+
+### 优化
+- 优化 WebChat 和 企业微信 AI 会话队列生命周期管理，减少内存泄漏，提高性能。
@@ -0,0 +1,31 @@
+## What's Changed
+
+### 修复
+- 人格预设对话可能会重复添加到上下文 ([#4961](https://github.com/AstrBotDevs/AstrBot/issues/4961))
+
+### 新增
+- 增加提供商级别的代理支持 ([#4949](https://github.com/AstrBotDevs/AstrBot/issues/4949))
+- WebUI 管理行为增加插件指令权限管理功能 ([#4887](https://github.com/AstrBotDevs/AstrBot/issues/4887))
+- 允许 LLM 预览工具返回的图片并自主决定是否发送 ([#4895](https://github.com/AstrBotDevs/AstrBot/issues/4895))
+- Telegram 平台添加媒体组（相册）支持 ([#4893](https://github.com/AstrBotDevs/AstrBot/issues/4893))
+- 增加欢迎功能，支持本地化内容和新手引导步骤
+- 支持 Electron 桌面应用部署 ([#4952](https://github.com/AstrBotDevs/AstrBot/issues/4952))
+
+### 注意
+- 更新 AstrBot Python 版本要求至 3.12 ([#4963](https://github.com/AstrBotDevs/AstrBot/issues/4963))
+
+## What's Changed
+
+### Fixes
+- Fixed issue where persona preset conversations could be duplicated in context ([#4961](https://github.com/AstrBotDevs/AstrBot/issues/4961))
+
+### Features
+- Added provider-level proxy support ([#4949](https://github.com/AstrBotDevs/AstrBot/issues/4949))
+- Added plugin command permission management to WebUI management behavior ([#4887](https://github.com/AstrBotDevs/AstrBot/issues/4887))
+- Allowed LLMs to preview images returned by tools and autonomously decide whether to send them ([#4895](https://github.com/AstrBotDevs/AstrBot/issues/4895))
+- Added media group (album) support for Telegram platform ([#4893](https://github.com/AstrBotDevs/AstrBot/issues/4893))
+- Added welcome feature with support for localized content and onboarding steps
+- Supported Electron desktop application deployment ([#4952](https://github.com/AstrBotDevs/AstrBot/issues/4952))
+
+### Notice
+- Updated AstrBot Python version requirement to 3.12 ([#4963](https://github.com/AstrBotDevs/AstrBot/issues/4963))
@@ -18,6 +18,7 @@ const emit = defineEmits<{
  (e: 'toggle-command', cmd: CommandItem): void;
  (e: 'rename', cmd: CommandItem): void;
  (e: 'view-details', cmd: CommandItem): void;
+  (e: 'update-permission', cmd: CommandItem, permission: 'admin' | 'member'): void;
 }>();

 // 表格表头
@@ -146,9 +147,36 @@ const getRowProps = ({ item }: { item: CommandItem }) => {
      </template>

      <template v-slot:item.permission="{ item }">
-        <v-chip :color="getPermissionColor(item.permission)" size="small" class="font-weight-medium">
-          {{ getPermissionLabel(item.permission) }}
-        </v-chip>
+        <v-menu location="bottom">
+          <template v-slot:activator="{ props }">
+            <v-chip
+              v-bind="props"
+              :color="getPermissionColor(item.permission)"
+              size="small"
+              class="font-weight-medium cursor-pointer"
+              link
+            >
+              {{ getPermissionLabel(item.permission) }}
+              <v-icon end size="14">mdi-chevron-down</v-icon>
+            </v-chip>
+          </template>
+          <v-list density="compact">
+            <v-list-item
+              :value="'member'"
+              @click="$emit('update-permission', item, 'member')"
+              :active="item.permission !== 'admin'"
+            >
+              <v-list-item-title>{{ tm('permission.everyone') }}</v-list-item-title>
+            </v-list-item>
+            <v-list-item
+              :value="'admin'"
+              @click="$emit('update-permission', item, 'admin')"
+              :active="item.permission === 'admin'"
+            >
+              <v-list-item-title>{{ tm('permission.admin') }}</v-list-item-title>
+            </v-list-item>
+          </v-list>
+        </v-menu>
      </template>

      <template v-slot:item.enabled="{ item }">
@@ -253,5 +281,9 @@ code.sub-command-code {
 .v-data-table .sub-command-row:hover {
  background-color: rgba(var(--v-theme-info), 0.08) !important;
 }
+
+.cursor-pointer {
+  cursor: pointer;
+}
 </style>

@@ -28,8 +28,8 @@ export function useCommandActions(
   * 切换指令启用/禁用状态
   */
  const toggleCommand = async (
-    cmd: CommandItem, 
-    successMessage: string, 
+    cmd: CommandItem,
+    successMessage: string,
    errorMessage: string
  ) => {
    try {
@@ -131,7 +131,7 @@ export function useCommandActions(
   * 获取状态显示信息
   */
  const getStatusInfo = (
-    cmd: CommandItem, 
+    cmd: CommandItem,
    translations: { conflict: string; enabled: string; disabled: string }
  ): StatusInfo => {
    if (cmd.has_conflict) {
@@ -160,13 +160,39 @@ export function useCommandActions(
    return classes.length > 0 ? { class: classes.join(' ') } : {};
  };

+  /**
+   * 更新指令权限
+   */
+  const updatePermission = async (
+    cmd: CommandItem,
+    permission: 'admin' | 'member',
+    successMessage: string,
+    errorMessage: string
+  ) => {
+    try {
+      const res = await axios.post('/api/commands/permission', {
+        handler_full_name: cmd.handler_full_name,
+        permission: permission
+      });
+      if (res.data.status === 'ok') {
+        toast(successMessage, 'success');
+        await fetchCommands();
+      } else {
+        toast(res.data.message || errorMessage, 'error');
+      }
+    } catch (err: any) {
+      toast(err?.message || errorMessage, 'error');
+    }
+  };
+
  return {
    // 状态
    renameDialog,
    detailsDialog,
-    
+
    // 方法
    toggleCommand,
+    updatePermission,
    openRenameDialog,
    confirmRename,
    openDetailsDialog,
@@ -76,6 +76,7 @@ const {
  renameDialog,
  detailsDialog,
  toggleCommand,
+  updatePermission,
  openRenameDialog,
  confirmRename,
  openDetailsDialog
@@ -95,6 +96,10 @@ const handleToggleCommand = async (cmd: CommandItem) => {
  await toggleCommand(cmd, tm('messages.toggleSuccess'), tm('messages.toggleFailed'));
 };

+const handleUpdatePermission = async (cmd: CommandItem, permission: 'admin' | 'member') => {
+  await updatePermission(cmd, permission, tm('messages.updateSuccess'), tm('messages.updateFailed'));
+};
+
 const handleToggleTool = async (tool: ToolItem) => {
  const previous = tool.active;
  tool.active = !tool.active;
@@ -240,6 +245,7 @@ watch(viewMode, async (mode) => {
              @toggle-command="handleToggleCommand"
              @rename="openRenameDialog"
              @view-details="openDetailsDialog"
+              @update-permission="handleUpdatePermission"
            />
          </div>

@@ -1,5 +1,5 @@
 <template>
-  <v-dialog v-model="showDialog" max-width="800px" height="90%" @after-enter="prepareData">
+  <v-dialog v-model="showDialog" max-width="800px" max-height="90%" @after-enter="prepareData">
    <v-card
      :title="updatingMode ? `${tm('dialog.edit')} ${updatingPlatformConfig.id} ${tm('dialog.adapter')}` : tm('dialog.addPlatform')">
  <v-card-text ref="dialogScrollContainer" class="pa-4 ml-2" style="overflow-y: auto;">
@@ -9,14 +9,14 @@
          </div>
          <div style="flex: 1;">
            <h3>
-              选择消息平台类别
+              {{ tm('createDialog.step1Title') }}
            </h3>
-            <small style="color: grey;">想把机器人接入到哪里？如 QQ、企业微信、飞书、Discord、Telegram 等。</small>
+            <small style="color: grey;">{{ tm('createDialog.step1Hint') }}</small>
            <div>

              <div v-if="!updatingMode">
                <v-select v-model="selectedPlatformType" :items="Object.keys(platformTemplates)" item-title="name"
-                  item-value="name" label="消息平台类别" variant="outlined" rounded="md" dense hide-details class="mt-6"
+                  item-value="name" :label="tm('createDialog.platformTypeLabel')" variant="outlined" rounded="md" dense hide-details class="mt-6"
                  style="max-width: 30%; min-width: 300px;">

                  <template v-slot:item="{ props: itemProps, item }">
@@ -41,7 +41,7 @@
                </div>
              </div>
              <div v-else>
-                <v-text-field label="消息平台类别" variant="outlined" rounded="md" dense hide-details class="mt-6"
+                <v-text-field :label="tm('createDialog.platformTypeLabel')" variant="outlined" rounded="md" dense hide-details class="mt-6"
                  style="max-width: 30%; min-width: 300px;" v-model="updatingPlatformConfig.type"
                  disabled></v-text-field>
                <div class="mt-3">
@@ -65,13 +65,13 @@
              <div>
                <div class="d-flex align-center">
                  <h3>
-                    配置文件
+                    {{ tm('createDialog.configFileTitle') }}
                  </h3>
                  <v-chip size="x-small" color="primary" variant="tonal" rounded="sm" class="ml-2"
-                    v-if="!updatingMode">可选</v-chip>
+                    v-if="!updatingMode">{{ tm('createDialog.optional') }}</v-chip>
                </div>
-                <small style="color: grey;">想如何配置机器人？配置文件包含了聊天模型、人格、知识库、插件范围等丰富的机器人配置项。</small>
-                <small style="color: grey;" v-if="!updatingMode">默认使用默认配置文件 “default”。您也可以稍后配置。</small>
+                <small style="color: grey;">{{ tm('createDialog.configHint') }}</small>
+                <small style="color: grey;" v-if="!updatingMode">{{ tm('createDialog.configDefaultHint') }}</small>
              </div>
              <div>
                <v-btn variant="plain" icon @click="toggleConfigSection" class="mt-2">
@@ -86,12 +86,12 @@
                <v-radio-group class="mt-2" v-model="aBConfigRadioVal" hide-details="true">
                  <v-radio value="0">
                    <template v-slot:label>
-                      <span>使用现有配置文件</span>
+                      <span>{{ tm('createDialog.useExistingConfig') }}</span>
                    </template>
                  </v-radio>
                  <div class="d-flex align-center ml-10 my-2" v-if="aBConfigRadioVal === '0'">
                    <v-select v-model="selectedAbConfId" :items="configInfoList" item-title="name"
-                      item-value="id" label="选择配置文件" variant="outlined" rounded="md" dense hide-details
+                      item-value="id" :label="tm('createDialog.selectConfigLabel')" variant="outlined" rounded="md" dense hide-details
                      style="max-width: 30%; min-width: 200px;">
                    </v-select>
                    <v-btn icon variant="text" density="comfortable" class="ml-2"
@@ -99,10 +99,10 @@
                      <v-icon>mdi-arrow-top-right-thick</v-icon>
                    </v-btn>
                  </div>
-                  <v-radio value="1" label="创建新配置文件">
+                  <v-radio value="1" :label="tm('createDialog.createNewConfig')">
                  </v-radio>
                  <div class="d-flex align-center" v-if="aBConfigRadioVal === '1'">
-                    <v-text-field v-model="selectedAbConfId" label="新配置文件名称" variant="outlined" rounded="md" dense
+                    <v-text-field v-model="selectedAbConfId" :label="tm('createDialog.newConfigNameLabel')" variant="outlined" rounded="md" dense
                      hide-details style="max-width: 30%; min-width: 200px;" class="ml-10 my-2">
                    </v-text-field>
                  </div>
@@ -131,12 +131,12 @@
                    <v-progress-circular indeterminate color="primary"></v-progress-circular>
                  </div>
                  <div v-else-if="newConfigData && newConfigMetadata" class="config-preview-container">
-                    <h4 class="mb-3">使用新的配置文件</h4>
+                    <h4 class="mb-3">{{ tm('createDialog.newConfigTitle') }}</h4>
                    <AstrBotCoreConfigWrapper :metadata="newConfigMetadata" :config_data="newConfigData" />
                  </div>
                  <div v-else class="text-center py-4 text-grey">
                    <v-icon>mdi-information-outline</v-icon>
-                    <p class="mt-2">无法加载默认配置模板</p>
+                    <p class="mt-2">{{ tm('createDialog.newConfigLoadFailed') }}</p>
                  </div>
                </div>

@@ -147,18 +147,18 @@
                  <div>
                    <v-btn v-if="isEditingRoutes" color="primary" variant="tonal" @click="addNewRoute" size="small">
                      <v-icon start>mdi-plus</v-icon>
-                      添加路由规则
+                      {{ tm('createDialog.addRouteRule') }}
                    </v-btn>
                  </div>
                  <v-btn :color="isEditingRoutes ? 'grey' : 'primary'" variant="tonal" size="small"
                    @click="toggleEditMode">
                    <v-icon start>{{ isEditingRoutes ? 'mdi-eye' : 'mdi-pencil' }}</v-icon>
-                    {{ isEditingRoutes ? '查看' : '编辑' }}
+                    {{ isEditingRoutes ? tm('createDialog.viewMode') : tm('createDialog.editMode') }}
                  </v-btn>
                </div>

                <v-data-table :headers="routeTableHeaders" :items="platformRoutes" item-value="umop"
-                  no-data-text="该平台暂无路由规则，将使用默认配置文件" hide-default-footer :items-per-page="-1" class="mt-2"
+                  :no-data-text="tm('createDialog.noRouteRules')" hide-default-footer :items-per-page="-1" class="mt-2"
                  variant="outlined">

                  <template v-slot:item.source="{ item }">
@@ -170,9 +170,9 @@
                      <small v-else>{{ getMessageTypeLabel(item.messageType) }}</small>
                      <small class="mx-1">:</small>
                      <v-text-field v-if="isEditingRoutes" v-model="item.sessionId" variant="outlined" density="compact"
-                        hide-details placeholder="会话ID或*">
+                        hide-details :placeholder="tm('createDialog.sessionIdPlaceholder')">
                      </v-text-field>
-                      <small v-else>{{ item.sessionId === '*' ? '全部会话' : item.sessionId }}</small>
+                      <small v-else>{{ item.sessionId === '*' ? tm('createDialog.allSessions') : item.sessionId }}</small>
                    </div>
                  </template>

@@ -191,7 +191,7 @@
                      </v-btn>
                    </div>
                    <small v-if="configInfoList.findIndex(c => c.id === item.configId) === -1" style="color: red;"
-                      class="ml-2">配置文件不存在</small>
+                      class="ml-2">{{ tm('createDialog.configMissing') }}</small>
                  </template>

                  <template v-slot:item.actions="{ item, index }">
@@ -211,8 +211,7 @@
                  </template>

                </v-data-table>
-                <small class="ml-2 mt-2 d-block" style="color: grey">*消息下发时，根据会话来源按顺序从上到下匹配首个符合条件的配置文件。使用 * 表示匹配所有。使用 /sid 指令获取会话
-                  ID。全部不匹配时将使用默认配置文件。</small>
+                <small class="ml-2 mt-2 d-block" style="color: grey">{{ tm('createDialog.routeHint') }}</small>
              </div>
            </div>

@@ -266,10 +265,10 @@
      <v-card-actions class="px-4 pb-4">
        <v-spacer></v-spacer>
        <v-btn color="error" @click="handleOneBotEmptyTokenWarningDismiss(true)">
-          无视警告并继续创建
+          {{ tm('createDialog.warningContinue') }}
        </v-btn>
        <v-btn color="primary" @click="handleOneBotEmptyTokenWarningDismiss(false)">
-          重新修改
+          {{ tm('createDialog.warningEditAgain') }}
        </v-btn>
      </v-card-actions>
    </v-card>
@@ -286,9 +285,9 @@
    <v-card class="config-drawer-card" elevation="12">
      <div class="config-drawer-header">
        <div>
-          <span class="text-h6">配置文件管理</span>
+          <span class="text-h6">{{ tm('createDialog.configDrawerTitle') }}</span>
          <div v-if="configDrawerTargetId" class="text-caption text-grey">
-            ID: {{ configDrawerTargetId }}
+            {{ tm('createDialog.configDrawerIdLabel') }}: {{ configDrawerTargetId }}
          </div>
        </div>
        <v-btn icon variant="text" @click="closeConfigDrawer">
@@ -359,23 +358,9 @@ export default {

      // 平台配置文件表格（已弃用，改用 platformRoutes）
      platformConfigs: [],
-      configTableHeaders: [
-        { title: '与此实例关联的配置文件 ID', key: 'name', sortable: false },
-        { title: '在此实例下的应用范围', key: 'scope', sortable: false },
-      ],

      // 平台路由表
      platformRoutes: [],
-      routeTableHeaders: [
-        { title: '消息会话来源(消息类型:会话 ID)', key: 'source', sortable: false, width: '60%' },
-        { title: '使用配置文件', key: 'configId', sortable: false, width: '20%' },
-        { title: '操作', key: 'actions', sortable: false, align: 'center', width: '20%' },
-      ],
-      messageTypeOptions: [
-        { label: '全部消息', value: '*' },
-        { label: '群组消息(GroupMessage)', value: 'GroupMessage' },
-        { label: '私聊消息(FriendMessage)', value: 'FriendMessage' },
-      ],
      isEditingRoutes: false, // 编辑模式开关

      // ID冲突确认对话框
@@ -437,6 +422,26 @@ export default {
      }

      return false;
+    },
+    configTableHeaders() {
+      return [
+        { title: this.tm('createDialog.configTableHeaders.configId'), key: 'name', sortable: false },
+        { title: this.tm('createDialog.configTableHeaders.scope'), key: 'scope', sortable: false },
+      ];
+    },
+    routeTableHeaders() {
+      return [
+        { title: this.tm('createDialog.routeTableHeaders.source'), key: 'source', sortable: false, width: '60%' },
+        { title: this.tm('createDialog.routeTableHeaders.config'), key: 'configId', sortable: false, width: '20%' },
+        { title: this.tm('createDialog.routeTableHeaders.actions'), key: 'actions', sortable: false, align: 'center', width: '20%' },
+      ];
+    },
+    messageTypeOptions() {
+      return [
+        { label: this.tm('createDialog.messageTypeOptions.all'), value: '*' },
+        { label: this.tm('createDialog.messageTypeOptions.group'), value: 'GroupMessage' },
+        { label: this.tm('createDialog.messageTypeOptions.friend'), value: 'FriendMessage' },
+      ];
    }
  },
  watch: {
@@ -603,7 +608,7 @@ export default {
      const targetId = configId || 'default';

      if (configId && this.configInfoList.findIndex(c => c.id === configId) === -1) {
-        this.showError('目标配置文件不存在，已打开配置页面以便检查。');
+        this.showError(this.tm('messages.configNotFoundOpenConfig'));
      }

      this.configDrawerTargetId = targetId;
@@ -637,7 +642,7 @@ export default {
      const id = this.originalUpdatingPlatformId || this.updatingPlatformConfig.id;
      if (!id) {
        this.loading = false;
-        this.showError('更新失败，缺少平台 ID。');
+        this.showError(this.tm('messages.updateMissingPlatformId'));
        return;
      }

@@ -655,7 +660,7 @@ export default {
        })

        if (resp.data.status === 'error') {
-          throw new Error(resp.data.message || '平台更新失败');
+          throw new Error(resp.data.message || this.tm('messages.platformUpdateFailed'));
        }
        
        // 同时更新路由表
@@ -665,7 +670,7 @@ export default {
        this.showDialog = false;
        this.resetForm();
        this.$emit('refresh-config');
-        this.showSuccess('更新成功');
+        this.showSuccess(this.tm('messages.updateSuccess'));
      } catch (err) {
        this.loading = false;
        this.showError(err.response?.data?.message || err.message);
@@ -710,7 +715,7 @@ export default {
        this.showDialog = false;
        this.resetForm();
        this.$emit('refresh-config');
-        this.showSuccess(res.data.message || '平台添加成功，配置文件已更新');
+        this.showSuccess(res.data.message || this.tm('messages.addSuccessWithConfig'));
      } catch (err) {
        this.loading = false;
        this.showError(err.response?.data?.message || err.message);
@@ -738,7 +743,7 @@ export default {
      }

      if (!configId) {
-        throw new Error('无法获取配置文件ID');
+        throw new Error(this.tm('messages.configIdMissing'));
      }

      // 第二步：统一更新路由表
@@ -755,7 +760,8 @@ export default {
        console.log(`成功更新路由表: ${umop} -> ${configId}`);
      } catch (err) {
        console.error('更新路由表失败:', err);
-        throw new Error(`更新路由表失败: ${err.response?.data?.message || err.message}`);
+        const errorMessage = err.response?.data?.message || err.message;
+        throw new Error(this.tm('messages.routingUpdateFailed', { message: errorMessage }));
      }
    },

@@ -778,7 +784,8 @@ export default {
        return newConfigId;
      } catch (err) {
        console.error('创建新配置文件失败:', err);
-        throw new Error(`创建新配置文件失败: ${err.response?.data?.message || err.message}`);
+        const errorMessage = err.response?.data?.message || err.message;
+        throw new Error(this.tm('messages.createConfigFailed', { message: errorMessage }));
      }
    },

@@ -922,7 +929,7 @@ export default {
      const newPlatformId = this.updatingPlatformConfig?.id || originalPlatformId;

      if (!originalPlatformId && !newPlatformId) {
-        throw new Error('无法获取平台 ID');
+        throw new Error(this.tm('messages.platformIdMissing'));
      }

      try {
@@ -958,7 +965,8 @@ export default {
        });
      } catch (err) {
        console.error('保存路由表失败:', err);
-        throw new Error(`保存路由表失败: ${err.response?.data?.message || err.message}`);
+        const errorMessage = err.response?.data?.message || err.message;
+        throw new Error(this.tm('messages.routingSaveFailed', { message: errorMessage }));
      }
    },

@@ -987,10 +995,10 @@ export default {
    // 获取消息类型标签
    getMessageTypeLabel(messageType) {
      const typeMap = {
-        '*': '全部消息',
-        '': '全部消息',
-        'GroupMessage': '群组消息',
-        'FriendMessage': '私聊消息'
+        '*': this.tm('createDialog.messageTypeLabels.all'),
+        '': this.tm('createDialog.messageTypeLabels.all'),
+        'GroupMessage': this.tm('createDialog.messageTypeLabels.group'),
+        'FriendMessage': this.tm('createDialog.messageTypeLabels.friend')
      };
      return typeMap[messageType] || messageType;
    },
@@ -14,7 +14,7 @@
            rounded="xl"
            size="small"
          >
-            新增
+            {{ tm('providerSources.add') }}
          </v-btn>
        </template>
        <v-list density="compact">
@@ -3,7 +3,7 @@ import { VueMonacoEditor } from '@guolao/vue-monaco-editor'
 import { ref, computed } from 'vue'
 import ConfigItemRenderer from './ConfigItemRenderer.vue'
 import TemplateListEditor from './TemplateListEditor.vue'
-import { useI18n } from '@/i18n/composables'
+import { useI18n, useModuleI18n } from '@/i18n/composables'
 import axios from 'axios'
 import { useToast } from '@/utils/toast'

@@ -35,6 +35,12 @@ const props = defineProps({
 })

 const { t } = useI18n()
+const { tm, getRaw } = useModuleI18n('features/config-metadata')
+
+const translateIfKey = (value) => {
+  if (!value || typeof value !== 'string') return value
+  return getRaw(value) ? tm(value) : value
+}

 const filteredIterable = computed(() => {
  if (!props.iterable) return {}
@@ -134,11 +140,11 @@ function hasVisibleItemsAfter(items, currentIndex) {
 <template>
  <div class="config-section" v-if="iterable && metadata[metadataKey]?.type === 'object'">
    <v-list-item-title class="config-title">
-      {{ metadata[metadataKey]?.description }} <span class="metadata-key">({{ metadataKey }})</span>
+      {{ translateIfKey(metadata[metadataKey]?.description) }} <span class="metadata-key">({{ metadataKey }})</span>
    </v-list-item-title>
    <v-list-item-subtitle class="config-hint">
      <span v-if="metadata[metadataKey]?.obvious_hint && metadata[metadataKey]?.hint" class="important-hint">‼️</span>
-      {{ metadata[metadataKey]?.hint }}
+      {{ translateIfKey(metadata[metadataKey]?.hint) }}
    </v-list-item-subtitle>
  </div>

@@ -180,14 +186,14 @@ function hasVisibleItemsAfter(items, currentIndex) {
            <div class="config-section mb-2">
              <v-list-item-title class="config-title">
                <span v-if="metadata[metadataKey].items[key]?.description">
-                  {{ metadata[metadataKey].items[key]?.description }}
+                  {{ translateIfKey(metadata[metadataKey].items[key]?.description) }}
                  <span class="property-key">({{ key }})</span>
                </span>
                <span v-else>{{ key }}</span>
              </v-list-item-title>
              <v-list-item-subtitle class="config-hint">
                <span v-if="metadata[metadataKey].items[key]?.obvious_hint && metadata[metadataKey].items[key]?.hint" class="important-hint">‼️</span>
-                {{ metadata[metadataKey].items[key]?.hint }}
+                {{ translateIfKey(metadata[metadataKey].items[key]?.hint) }}
              </v-list-item-subtitle>
            </div>
            <TemplateListEditor
@@ -205,7 +211,7 @@ function hasVisibleItemsAfter(items, currentIndex) {
              <v-list-item density="compact">
                <v-list-item-title class="property-name">
                  <span v-if="metadata[metadataKey].items[key]?.description">
-                    {{ metadata[metadataKey].items[key]?.description }}
+                    {{ translateIfKey(metadata[metadataKey].items[key]?.description) }}
                    <span class="property-key">({{ key }})</span>
                  </span>
                  <span v-else>{{ key }}</span>
@@ -214,7 +220,7 @@ function hasVisibleItemsAfter(items, currentIndex) {
                <v-list-item-subtitle class="property-hint">
                  <span v-if="metadata[metadataKey].items[key]?.obvious_hint && metadata[metadataKey].items[key]?.hint"
                        class="important-hint">‼️</span>
-                  {{ metadata[metadataKey].items[key]?.hint }}
+                  {{ translateIfKey(metadata[metadataKey].items[key]?.hint) }}
                </v-list-item-subtitle>
              </v-list-item>
            </v-col>
@@ -33,9 +33,15 @@ export default {
    methods: {
        async check() {
            this.newStartTime = -1
-            this.startTime = useCommonStore().getStartTime()
+            this.cnt = 0
            this.visible = true
            this.status = ""
+            const commonStore = useCommonStore()
+            try {
+                this.startTime = await commonStore.fetchStartTime()
+            } catch (_error) {
+                this.startTime = commonStore.getStartTime()
+            }
            console.log('start wfr')
            setTimeout(() => {
                this.timeoutInternal()
@@ -50,7 +56,7 @@ export default {
                    this.timeoutInternal()
                }, 1000)
            } else {
-                if (this.cnt == 10) {
+                if (this.cnt >= 60) {
                    this.status = this.t('core.common.restart.maxRetriesReached')
                }
                this.cnt = 0
@@ -60,18 +66,22 @@ export default {
            }
        },
        async checkStartTime() {
-            let res = await axios.get('/api/stat/start-time', { timeout: 3000 })
-            let newStartTime = res.data.data.start_time
-            console.log('wfr: checkStartTime', this.newStartTime, this.startTime)
-            if (this.newStartTime !== this.startTime) {
-                this.newStartTime = newStartTime
-                console.log('wfr: restarted')
-                this.visible = false
-                // reload 
-                window.location.reload()
+            try {
+                let res = await axios.get('/api/stat/start-time', { timeout: 3000 })
+                let newStartTime = res.data.data.start_time
+                console.log('wfr: checkStartTime', newStartTime, this.startTime)
+                if (this.startTime !== -1 && newStartTime !== this.startTime) {
+                    this.newStartTime = newStartTime
+                    console.log('wfr: restarted')
+                    this.visible = false
+                    // reload
+                    window.location.reload()
+                }
+            } catch (_error) {
+                // backend may be unavailable during restart window
            }
            return this.newStartTime
        }
    }
 }
-</script>
+</script>
@@ -59,14 +59,14 @@ export function useProviderSources(options: UseProviderSourcesOptions) {

  let suppressSourceWatch = false

-  const providerTypes = [
+  const providerTypes = computed(() => [
    { value: 'chat_completion', label: tm('providers.tabs.chatCompletion'), icon: 'mdi-message-text' },
    { value: 'agent_runner', label: tm('providers.tabs.agentRunner'), icon: 'mdi-robot' },
    { value: 'speech_to_text', label: tm('providers.tabs.speechToText'), icon: 'mdi-microphone-message' },
    { value: 'text_to_speech', label: tm('providers.tabs.textToSpeech'), icon: 'mdi-volume-high' },
    { value: 'embedding', label: tm('providers.tabs.embedding'), icon: 'mdi-code-json' },
    { value: 'rerank', label: tm('providers.tabs.rerank'), icon: 'mdi-compare-vertical' }
-  ]
+  ])

  // ===== Computed =====
  const availableSourceTypes = computed(() => {
@@ -233,6 +233,11 @@ export function useProviderSources(options: UseProviderSourcesOptions) {
      customSchema.provider.items.key.hint = tm('providerSources.hints.key')
      customSchema.provider.items.api_base.hint = tm('providerSources.hints.apiBase')
    }
+    // 为 proxy 字段添加描述和提示
+    if (customSchema.provider?.items?.proxy) {
+      customSchema.provider.items.proxy.description = tm('providerSources.labels.proxy')
+      customSchema.provider.items.proxy.hint = tm('providerSources.hints.proxy')
+    }

    return customSchema
  })
@@ -59,6 +59,7 @@ export class I18nLoader {
      { name: 'features/alkaid/memory', path: 'features/alkaid/memory.json' },
      { name: 'features/persona', path: 'features/persona.json' },
      { name: 'features/migration', path: 'features/migration.json' },
+      { name: 'features/welcome', path: 'features/welcome.json' },
      
      // 消息模块
      { name: 'messages/errors', path: 'messages/errors.json' },
@@ -1,4 +1,5 @@
 {
+  "welcome": "Welcome",
  "dashboard": "Dashboard",
  "platforms": "Platforms",
  "providers": "Providers",
@@ -69,7 +69,9 @@
    "toggleFailed": "Failed to update command status",
    "renameSuccess": "Command renamed",
    "renameFailed": "Rename failed",
-    "loadFailed": "Failed to load commands"
+    "loadFailed": "Failed to load commands",
+    "updateSuccess": "Updated successfully",
+    "updateFailed": "Update failed"
  },
  "search": {
    "placeholder": "Search commands..."
@@ -108,6 +108,10 @@
          "description": "Tavily API Key",
          "hint": "Multiple keys can be added for rotation."
        },
+        "websearch_bocha_key": {
+          "description": "BoCha API Key",
+          "hint": "Multiple keys can be added for rotation."
+        },
        "websearch_baidu_app_builder_key": {
          "description": "Baidu Qianfan Smart Cloud APP Builder API Key",
          "hint": "Reference: [https://console.bce.baidu.com/iam/#/iam/apikey/list](https://console.bce.baidu.com/iam/#/iam/apikey/list)"
@@ -290,6 +294,235 @@
  },
  "platform_group": {
    "name": "Platform",
+    "platform": {
+      "description": "Message Platform Adapters",
+      "active_send_mode": {
+        "description": "Use Proactive Send API"
+      },
+      "appid": {
+        "description": "App ID",
+        "hint": "Required. App ID for the QQ Official Bot platform. See the docs for how to obtain it."
+      },
+      "callback_server_host": {
+        "description": "Callback Server Host",
+        "hint": "Callback server host. Leave empty to disable the callback server."
+      },
+      "card_template_id": {
+        "description": "Card Template ID",
+        "hint": "Optional. DingTalk interactive card template ID. When enabled, streaming replies will use interactive cards."
+      },
+      "discord_activity_name": {
+        "description": "Discord Activity Name",
+        "hint": "Optional Discord activity name. Leave empty to disable."
+      },
+      "discord_command_register": {
+        "description": "Auto-register plugin commands as Discord slash commands"
+      },
+      "discord_proxy": {
+        "description": "Discord Proxy URL",
+        "hint": "Optional proxy URL: http://ip:port"
+      },
+      "discord_token": {
+        "description": "Discord Bot Token",
+        "hint": "Enter your Discord Bot Token here."
+      },
+      "enable": {
+        "description": "Enable",
+        "hint": "Whether to enable this adapter. Disabled adapters will not receive messages."
+      },
+      "enable_group_c2c": {
+        "description": "Enable Message List Private Chat",
+        "hint": "When enabled, the bot can receive private chats from QQ message list. You may need to add the bot as a friend by scanning a QR code in the QQ bot platform. See docs."
+      },
+      "enable_guild_direct_message": {
+        "description": "Enable Guild Direct Messages",
+        "hint": "When enabled, the bot can receive guild direct messages."
+      },
+      "id": {
+        "description": "Bot Name",
+        "hint": "Bot name"
+      },
+      "is_sandbox": {
+        "description": "Sandbox Mode"
+      },
+      "kf_name": {
+        "description": "WeChat Customer Service Account Name",
+        "hint": "Optional. Customer service account name (not ID). Get it at https://kf.weixin.qq.com/kf/frame#/accounts"
+      },
+      "lark_bot_name": {
+        "description": "Lark Bot Name",
+        "hint": "Must be correct; otherwise @ mentions will not wake the bot and only prefix wake will work."
+      },
+      "lark_connection_mode": {
+        "description": "Subscription Mode",
+        "labels": [
+          "Long Connection Mode",
+          "Webhook Server Mode"
+        ]
+      },
+      "lark_encrypt_key": {
+        "description": "Encrypt Key",
+        "hint": "Encryption key for decrypting Lark callback data."
+      },
+      "lark_verification_token": {
+        "description": "Verification Token",
+        "hint": "Token for verifying Lark callback requests."
+      },
+      "misskey_allow_insecure_downloads": {
+        "description": "Allow Insecure Downloads (Disable SSL Verification)",
+        "hint": "If remote servers have certificate issues, SSL verification will be disabled as a fallback. Use only when necessary due to security risks."
+      },
+      "misskey_default_visibility": {
+        "description": "Default Post Visibility",
+        "hint": "Default visibility for bot posts. public: public, home: home timeline, followers: followers only."
+      },
+      "misskey_download_chunk_size": {
+        "description": "Stream Download Chunk Size (bytes)",
+        "hint": "Bytes read per chunk during streaming download and MD5 calculation. Too small increases overhead; too large uses more memory."
+      },
+      "misskey_download_timeout": {
+        "description": "Remote Download Timeout (seconds)",
+        "hint": "Timeout for downloading remote files (seconds), used when falling back to local upload."
+      },
+      "misskey_enable_chat": {
+        "description": "Enable Chat Message Responses",
+        "hint": "When enabled, the bot listens and responds to private chat messages."
+      },
+      "misskey_enable_file_upload": {
+        "description": "Enable File Upload to Misskey",
+        "hint": "When enabled, the adapter uploads files in message chains to Misskey. URL files try server-side upload first; if async upload fails, it falls back to local download and upload."
+      },
+      "misskey_instance_url": {
+        "description": "Misskey Instance URL",
+        "hint": "e.g. https://misskey.example. The Misskey instance where the bot account lives."
+      },
+      "misskey_local_only": {
+        "description": "Local Only (No Federation)",
+        "hint": "When enabled, bot posts are visible only on this instance and are not federated."
+      },
+      "misskey_max_download_bytes": {
+        "description": "Max Download Size (bytes)",
+        "hint": "To limit download size to prevent OOM, set the maximum bytes; empty or null means no limit."
+      },
+      "misskey_token": {
+        "description": "Misskey Access Token",
+        "hint": "API access token generated in the connection service settings."
+      },
+      "misskey_upload_concurrency": {
+        "description": "Upload Concurrency Limit",
+        "hint": "Max number of concurrent upload tasks (integer, default 3)."
+      },
+      "misskey_upload_folder": {
+        "description": "Target Drive Folder ID",
+        "hint": "Optional: ID of the target folder in Misskey drive. Leave empty to use the root folder."
+      },
+      "port": {
+        "description": "Callback Server Port",
+        "hint": "Callback server port. Leave empty to disable the callback server."
+      },
+      "satori_api_base_url": {
+        "description": "Satori API Endpoint",
+        "hint": "Base URL for the Satori API."
+      },
+      "satori_auto_reconnect": {
+        "description": "Enable Auto Reconnect",
+        "hint": "Automatically reconnect the WebSocket when disconnected."
+      },
+      "satori_endpoint": {
+        "description": "Satori WebSocket Endpoint",
+        "hint": "WebSocket endpoint for Satori events."
+      },
+      "satori_heartbeat_interval": {
+        "description": "Satori Heartbeat Interval",
+        "hint": "Interval in seconds between heartbeat messages."
+      },
+      "satori_reconnect_delay": {
+        "description": "Satori Reconnect Delay",
+        "hint": "Delay before attempting to reconnect (seconds)."
+      },
+      "satori_token": {
+        "description": "Satori Token",
+        "hint": "Token for Satori API authentication."
+      },
+      "secret": {
+        "description": "Secret",
+        "hint": "Required."
+      },
+      "slack_connection_mode": {
+        "description": "Slack Connection Mode",
+        "hint": "The connection mode for Slack. `webhook` uses a webhook server, `socket` uses Slack's Socket Mode."
+      },
+      "slack_webhook_host": {
+        "description": "Slack Webhook Host",
+        "hint": "Only valid when Slack connection mode is `webhook`."
+      },
+      "slack_webhook_path": {
+        "description": "Slack Webhook Path",
+        "hint": "Only valid when Slack connection mode is `webhook`."
+      },
+      "slack_webhook_port": {
+        "description": "Slack Webhook Port",
+        "hint": "Only valid when Slack connection mode is `webhook`."
+      },
+      "telegram_command_auto_refresh": {
+        "description": "Telegram Command Auto Refresh",
+        "hint": "When enabled, AstrBot automatically refreshes Telegram commands at runtime. (Setting this alone has no effect)"
+      },
+      "telegram_command_register": {
+        "description": "Telegram Command Registration",
+        "hint": "When enabled, AstrBot automatically registers Telegram commands."
+      },
+      "telegram_command_register_interval": {
+        "description": "Telegram Command Auto Refresh Interval",
+        "hint": "Telegram command auto-refresh interval in seconds."
+      },
+      "telegram_token": {
+        "description": "Bot Token",
+        "hint": "If you are in mainland China, set a proxy or change api_base in Other Settings."
+      },
+      "type": {
+        "description": "Adapter Type"
+      },
+      "unified_webhook_mode": {
+        "description": "Unified Webhook Mode",
+        "hint": "When enabled, use AstrBot unified webhook entry without opening a separate port. Callback URL is /api/platform/webhook/{webhook_uuid}."
+      },
+      "webhook_uuid": {
+        "description": "Webhook UUID",
+        "hint": "Unique identifier for unified webhook mode; generated when creating the platform."
+      },
+      "wecom_ai_bot_name": {
+        "description": "WeCom AI Bot Name",
+        "hint": "Must be correct; otherwise some commands won't work."
+      },
+      "wecomaibot_friend_message_welcome_text": {
+        "description": "WeCom AI Bot DM Welcome Message",
+        "hint": "When a user enters a DM session on that day, reply with a welcome message. Leave empty to disable."
+      },
+      "wecomaibot_init_respond_text": {
+        "description": "WeCom AI Bot Initial Response Text",
+        "hint": "First reply when the bot receives a message. Leave empty to use default."
+      },
+      "wpp_active_message_poll": {
+        "description": "Enable Proactive Message Polling",
+        "hint": "Only enable if WeChat messages are not syncing to AstrBot on time. Disabled by default."
+      },
+      "wpp_active_message_poll_interval": {
+        "description": "Proactive Message Poll Interval",
+        "hint": "Interval in seconds, default 3, should not exceed 60 or it may be considered old messages."
+      },
+      "ws_reverse_host": {
+        "description": "Reverse WebSocket Host",
+        "hint": "AstrBot acts as the server."
+      },
+      "ws_reverse_port": {
+        "description": "Reverse WebSocket Port"
+      },
+      "ws_reverse_token": {
+        "description": "Reverse WebSocket Token",
+        "hint": "Reverse WebSocket token. If not set, token verification is disabled."
+      }
+    },
    "general": {
      "description": "General",
      "admins_id": {
@@ -615,6 +848,443 @@
      }
    }
  },
+  "provider_group": {
+    "provider": {
+      "genie_onnx_model_dir": {
+        "description": "ONNX Model Directory",
+        "hint": "The directory path containing the ONNX model files"
+      },
+      "genie_language": {
+        "description": "Language"
+      },
+      "xai_native_search": {
+        "description": "Enable native search",
+        "hint": "When enabled, uses xAI Chat Completions native Live Search for web queries (billed on demand). Only applies to xAI providers."
+      },
+      "rerank_api_base": {
+        "description": "Rerank Model API Base URL",
+        "hint": "AstrBot appends /v1/rerank to the request URL."
+      },
+      "rerank_api_key": {
+        "description": "API Key",
+        "hint": "Leave empty if no API key is required."
+      },
+      "rerank_model": {
+        "description": "Rerank model name"
+      },
+      "return_documents": {
+        "description": "Return source documents in rerank results",
+        "hint": "Default is false to reduce network overhead."
+      },
+      "instruct": {
+        "description": "Custom rerank task description",
+        "hint": "Only effective for qwen3-rerank models. Recommended to write in English."
+      },
+      "launch_model_if_not_running": {
+        "description": "Auto-start model if not running",
+        "hint": "If the model is not running in Xinference, attempt to start it automatically. Recommended to disable in production."
+      },
+      "modalities": {
+        "description": "Model capabilities",
+        "hint": "Modalities supported by the model. If the model does not support images, uncheck image.",
+        "labels": [
+          "Text",
+          "Image",
+          "Tool use"
+        ]
+      },
+      "custom_headers": {
+        "description": "Custom request headers",
+        "hint": "Key/value pairs added here are merged into the OpenAI SDK default_headers for custom HTTP headers. Values must be strings."
+      },
+      "custom_extra_body": {
+        "description": "Custom request body parameters",
+        "hint": "Add extra parameters to requests, such as temperature, top_p, max_tokens, etc.",
+        "template_schema": {
+          "temperature": {
+            "description": "Temperature",
+            "hint": "Controls randomness, typically 0-2. Higher is more random.",
+            "name": "Temperature"
+          },
+          "top_p": {
+            "description": "Top-p sampling",
+            "hint": "Nucleus sampling parameter, usually 0-1. Controls probability mass considered.",
+            "name": "Top-p"
+          },
+          "max_tokens": {
+            "description": "Max tokens",
+            "hint": "Maximum number of generated tokens.",
+            "name": "Max Tokens"
+          }
+        }
+      },
+      "gpt_weights_path": {
+        "description": "GPT model file path",
+        "hint": "The .ckpt file. Use an absolute path without quotes. Leave empty to use the GPT_SoVITS built-in SoVITS model (recommended to change defaults in GPT_SoVITS)."
+      },
+      "sovits_weights_path": {
+        "description": "SoVITS model file path",
+        "hint": "The .pth file. Use an absolute path without quotes. Leave empty to use the GPT_SoVITS built-in SoVITS model (recommended to change defaults in GPT_SoVITS)."
+      },
+      "gsv_default_parms": {
+        "description": "GPT_SoVITS default parameters",
+        "hint": "Reference audio file path and text are required; other parameters are optional.",
+        "gsv_ref_audio_path": {
+          "description": "Reference audio file path",
+          "hint": "Required! Use an absolute path without quotes."
+        },
+        "gsv_prompt_text": {
+          "description": "Reference audio text",
+          "hint": "Required! Provide the transcript of the reference audio."
+        },
+        "gsv_prompt_lang": {
+          "description": "Reference audio text language",
+          "hint": "Language of the reference audio text; default is Chinese."
+        },
+        "gsv_aux_ref_audio_paths": {
+          "description": "Auxiliary reference audio file paths",
+          "hint": "Auxiliary reference audio files; optional."
+        },
+        "gsv_text_lang": {
+          "description": "Text language",
+          "hint": "Default is Chinese."
+        },
+        "gsv_top_k": {
+          "description": "Speech diversity",
+          "hint": ""
+        },
+        "gsv_top_p": {
+          "description": "Nucleus sampling threshold",
+          "hint": ""
+        },
+        "gsv_temperature": {
+          "description": "Speech randomness",
+          "hint": ""
+        },
+        "gsv_text_split_method": {
+          "description": "Text splitting method",
+          "hint": "Options: `cut0` no split, `cut1` split every 4 sentences, `cut2` split every 50 chars, `cut3` split by Chinese period, `cut4` split by English period, `cut5` split by punctuation."
+        },
+        "gsv_batch_size": {
+          "description": "Batch size",
+          "hint": ""
+        },
+        "gsv_batch_threshold": {
+          "description": "Batch threshold",
+          "hint": ""
+        },
+        "gsv_split_bucket": {
+          "description": "Split text into buckets for parallel processing",
+          "hint": ""
+        },
+        "gsv_speed_factor": {
+          "description": "Speech playback speed",
+          "hint": "1 is the original speed."
+        },
+        "gsv_fragment_interval": {
+          "description": "Interval between speech segments",
+          "hint": ""
+        },
+        "gsv_streaming_mode": {
+          "description": "Enable streaming mode",
+          "hint": ""
+        },
+        "gsv_seed": {
+          "description": "Random seed",
+          "hint": "For reproducible results."
+        },
+        "gsv_parallel_infer": {
+          "description": "Run inference in parallel",
+          "hint": ""
+        },
+        "gsv_repetition_penalty": {
+          "description": "Repetition penalty",
+          "hint": ""
+        },
+        "gsv_media_type": {
+          "description": "Output media type",
+          "hint": "Recommended: wav"
+        }
+      },
+      "embedding_dimensions": {
+        "description": "Embedding dimensions",
+        "hint": "Embedding vector dimensions. May need adjustment per model; see model documentation. This must be correct or the vector database will not work."
+      },
+      "embedding_model": {
+        "description": "Embedding model",
+        "hint": "Embedding model name."
+      },
+      "embedding_api_key": {
+        "description": "API Key"
+      },
+      "embedding_api_base": {
+        "description": "API Base URL"
+      },
+      "volcengine_cluster": {
+        "description": "Volcengine cluster",
+        "hint": "For voice cloning models, choose volcano_icl or volcano_icl_concurr; default is volcano_tts."
+      },
+      "volcengine_voice_type": {
+        "description": "Volcengine voice",
+        "hint": "Enter voice id (Voice_type)."
+      },
+      "volcengine_speed_ratio": {
+        "description": "Speech rate",
+        "hint": "Speech rate, range 0.2 to 3.0, default 1.0."
+      },
+      "volcengine_volume_ratio": {
+        "description": "Volume",
+        "hint": "Volume, range 0.0 to 2.0, default 1.0."
+      },
+      "azure_tts_voice": {
+        "description": "Voice style",
+        "hint": "API voice name"
+      },
+      "azure_tts_style": {
+        "description": "Style",
+        "hint": "A voice-specific speaking style. Can express emotions like happy, sympathetic, and calm."
+      },
+      "azure_tts_role": {
+        "description": "Role (optional)",
+        "hint": "Speaking role-play. The voice can emulate different ages and genders without changing the voice name. For example, a male voice can raise pitch to simulate a female voice, but the voice name does not change. If the role is missing or unsupported, this attribute is ignored."
+      },
+      "azure_tts_rate": {
+        "description": "Speech rate",
+        "hint": "Controls speaking rate. You can apply the rate at word or sentence level. Rate should be 0.5x to 2x of original audio."
+      },
+      "azure_tts_volume": {
+        "description": "Speech volume",
+        "hint": "Controls volume level. You can apply changes at sentence level. Use 0.0 to 100.0 (quiet to loud, e.g., 75). Default is 100.0."
+      },
+      "azure_tts_region": {
+        "description": "API region",
+        "hint": "Region where Azure TTS processes data. See https://learn.microsoft.com/zh-cn/azure/ai-services/speech-service/regions"
+      },
+      "azure_tts_subscription_key": {
+        "description": "Service subscription key",
+        "hint": "Azure TTS subscription key (not a token)."
+      },
+      "dashscope_tts_voice": {
+        "description": "Voice"
+      },
+      "gm_resp_image_modal": {
+        "description": "Enable image modality",
+        "hint": "When enabled, responses can include images. Requires model support or it will error. See the Google Gemini website for supported models. Tip: if you need image generation, disable the `Enable member recognition` setting for better results."
+      },
+      "gm_native_search": {
+        "description": "Enable native search",
+        "hint": "When enabled, all function tools are disabled. Check official docs for free quota limits."
+      },
+      "gm_native_coderunner": {
+        "description": "Enable native code runner",
+        "hint": "When enabled, all function tools are disabled."
+      },
+      "gm_url_context": {
+        "description": "Enable URL context",
+        "hint": "When enabled, all function tools are disabled."
+      },
+      "gm_safety_settings": {
+        "description": "Safety filters",
+        "hint": "Set the safety filtering level for model input. Levels: NONE (no blocking), HIGH (block high risk), MEDIUM_AND_ABOVE (block medium risk and above), LOW_AND_ABOVE (block low risk and above). See Gemini API docs.",
+        "harassment": {
+          "description": "Harassment",
+          "hint": "Negative or harmful comments"
+        },
+        "hate_speech": {
+          "description": "Hate speech",
+          "hint": "Rude, disrespectful, or profane content"
+        },
+        "sexually_explicit": {
+          "description": "Sexually explicit content",
+          "hint": "References to sexual acts or other obscene content"
+        },
+        "dangerous_content": {
+          "description": "Dangerous content",
+          "hint": "Content that promotes, encourages, or assists harmful behavior"
+        }
+      },
+      "gm_thinking_config": {
+        "description": "Thinking Config",
+        "budget": {
+          "description": "Thinking Budget",
+          "hint": "Guides the model on the specific number of thinking tokens to use for reasoning. See: https://ai.google.dev/gemini-api/docs/thinking#set-budget"
+        },
+        "level": {
+          "description": "Thinking Level",
+          "hint": "Recommended for Gemini 3 models and onwards, lets you control reasoning behavior.See: https://ai.google.dev/gemini-api/docs/thinking#thinking-levels"
+        }
+      },
+      "anth_thinking_config": {
+        "description": "Thinking Config",
+        "budget": {
+          "description": "Thinking Budget",
+          "hint": "Anthropic thinking.budget_tokens param. Must >= 1024. See: https://platform.claude.com/docs/en/build-with-claude/extended-thinking"
+        }
+      },
+      "minimax-group-id": {
+        "description": "User group",
+        "hint": "Visible in Account Management -> Basic Info."
+      },
+      "minimax-langboost": {
+        "description": "Target language/dialect",
+        "hint": "Enhances recognition for specified languages/dialects and improves speech performance in those scenarios."
+      },
+      "minimax-voice-speed": {
+        "description": "Speech rate",
+        "hint": "Speech speed for synthesis, range [0.5, 2], default 1.0. Higher is faster."
+      },
+      "minimax-voice-vol": {
+        "description": "Volume",
+        "hint": "Volume for synthesis, range (0, 10], default 1.0. Higher is louder."
+      },
+      "minimax-voice-pitch": {
+        "description": "Pitch",
+        "hint": "Pitch for synthesis, range [-12, 12], default 0."
+      },
+      "minimax-is-timber-weight": {
+        "description": "Enable mixed voices",
+        "hint": "Enable mixing up to four voices with custom weights. When enabled, single voice settings are ignored."
+      },
+      "minimax-timber-weight": {
+        "description": "Mixed voices",
+        "hint": "Mixed voices and their weights. Up to four voices, integer weights in [1, 100]. Get presets and templates from the official API TTS debug console. Must be a JSON string; check the console to confirm parsing. See defaults and the official code preview for structure."
+      },
+      "minimax-voice-id": {
+        "description": "Single voice",
+        "hint": "Single voice ID; see the official documentation."
+      },
+      "minimax-voice-emotion": {
+        "description": "Emotion",
+        "hint": "Controls emotion of synthesized speech. When set to auto, it selects emotion based on text."
+      },
+      "minimax-voice-latex": {
+        "description": "Read LaTeX formulas",
+        "hint": "Read LaTeX formulas, but ensure input text is formatted per the official requirements."
+      },
+      "minimax-voice-english-normalization": {
+        "description": "English text normalization",
+        "hint": "Improves number-reading performance but slightly increases latency."
+      },
+      "rag_options": {
+        "description": "RAG options",
+        "hint": "Knowledge base retrieval settings, optional. Only supported for Agent app types (agent apps, including RAG apps). For Bailian apps, enabling this disables multi-turn conversations.",
+        "pipeline_ids": {
+          "description": "Knowledge base ID list",
+          "hint": "Retrieve all documents in the specified knowledge bases. Go to https://bailian.console.aliyun.com/ Data Apps -> Knowledge Index to create and get IDs."
+        },
+        "file_ids": {
+          "description": "Unstructured document IDs",
+          "hint": "Retrieve specified unstructured documents. Go to https://bailian.console.aliyun.com/ Data Management to create and get IDs."
+        },
+        "output_reference": {
+          "description": "Output knowledge base/document references",
+          "hint": "Append reference sources to the end of each answer. Default is False."
+        }
+      },
+      "sensevoice_hint": {
+        "description": "Deploy SenseVoice",
+        "hint": "Before enabling, install funasr, funasr_onnx, torchaudio, torch, modelscope, and jieba (CPU by default, about 1 GB download), and install ffmpeg. Otherwise STT will not work."
+      },
+      "is_emotion": {
+        "description": "Emotion recognition",
+        "hint": "Enable emotion recognition. happy?sad?angry?neutral?fearful?disgusted?surprised?unknown"
+      },
+      "stt_model": {
+        "description": "Model name",
+        "hint": "Model name on modelscope. Default: iic/SenseVoiceSmall."
+      },
+      "variables": {
+        "description": "Workflow fixed input variables",
+        "hint": "Optional. Fixed workflow input variables are used as workflow inputs. You can also set variables dynamically with /set during a chat. If names conflict, dynamic settings take precedence."
+      },
+      "dashscope_app_type": {
+        "description": "App type",
+        "hint": "Bailian app type."
+      },
+      "timeout": {
+        "description": "Timeout",
+        "hint": "Timeout in seconds."
+      },
+      "openai-tts-voice": {
+        "description": "voice",
+        "hint": "OpenAI TTS voice. OpenAI defaults: 'alloy', 'echo', 'fable', 'onyx', 'nova', 'shimmer'."
+      },
+      "fishaudio-tts-character": {
+        "description": "character",
+        "hint": "Fishaudio TTS character. Default is Klee. More roles: https://fish.audio/zh-CN/discovery"
+      },
+      "fishaudio-tts-reference-id": {
+        "description": "reference_id",
+        "hint": "Fishaudio TTS reference model ID (optional). If set, the model ID is used directly instead of looking up by role name. Example: 626bb6d3f3364c9cbc3aa6a67300a664. More models: https://fish.audio/zh-CN/discovery; open a model detail page to copy the model ID."
+      },
+      "whisper_hint": {
+        "description": "Notes for local Whisper deployment",
+        "hint": "Before enabling, install the openai-whisper library (NVIDIA users download ~2GB mainly for torch and cuda; CPU users download ~1GB), and install ffmpeg. Otherwise STT will not work."
+      },
+      "id": {
+        "description": "ID"
+      },
+      "type": {
+        "description": "Provider category"
+      },
+      "provider_type": {
+        "description": "Provider capability type"
+      },
+      "enable": {
+        "description": "Enable"
+      },
+      "key": {
+        "description": "API Key"
+      },
+      "api_base": {
+        "description": "API Base URL"
+      },
+      "model": {
+        "description": "Model ID",
+        "hint": "Model name, e.g., gpt-4o-mini, deepseek-chat."
+      },
+      "max_context_tokens": {
+        "description": "Model context window size",
+        "hint": "Maximum context tokens. If 0, it auto-fills from model metadata (if available); you can also edit manually."
+      },
+      "dify_api_key": {
+        "description": "API Key",
+        "hint": "Dify API Key. This field is required."
+      },
+      "dify_api_base": {
+        "description": "API Base URL",
+        "hint": "Dify API Base URL. Default: https://api.dify.ai/v1"
+      },
+      "dify_api_type": {
+        "description": "Dify app type",
+        "hint": "Dify API type. According to Dify docs, supported types are chat, chatflow, agent, workflow."
+      },
+      "dify_workflow_output_key": {
+        "description": "Dify workflow output variable name",
+        "hint": "Dify workflow output variable name. Only used when app type is workflow. Default: astrbot_wf_output."
+      },
+      "dify_query_input_key": {
+        "description": "Prompt input variable name",
+        "hint": "Input variable name for the message text. Default: astrbot_text_query."
+      },
+      "coze_api_key": {
+        "description": "Coze API Key",
+        "hint": "Coze API key for accessing Coze services."
+      },
+      "bot_id": {
+        "description": "Bot ID",
+        "hint": "Coze bot ID, obtained after creating a bot on the Coze platform."
+      },
+      "coze_api_base": {
+        "description": "API Base URL",
+        "hint": "Base URL for the Coze API. Default: https://api.coze.cn"
+      },
+      "auto_save_history": {
+        "description": "Conversation history managed by Coze",
+        "hint": "When enabled, Coze manages conversation history. AstrBot's locally saved context will not take effect (read-only), and operations on AstrBot context will not apply. If disabled, AstrBot manages the context."
+      }
+    }
+  },
  "help": {
    "documentation": "Official Documentation",
    "support": "Join Support Group",
@@ -45,12 +45,67 @@
    },
    "invalidPlatformId": "Platform ID cannot contain ':' or '!'."
  },
+  "createDialog": {
+    "step1Title": "Choose Platform Category",
+    "step1Hint": "Where do you want to connect the bot? e.g. QQ, WeCom, Feishu, Discord, Telegram.",
+    "platformTypeLabel": "Platform Category",
+    "configFileTitle": "Config File",
+    "optional": "Optional",
+    "configHint": "How do you want to configure the bot? The config file includes model, persona, knowledge base, plugins, and more.",
+    "configDefaultHint": "Uses the default config file \"default\" by default. You can configure it later.",
+    "useExistingConfig": "Use existing config file",
+    "selectConfigLabel": "Select config file",
+    "createNewConfig": "Create new config file",
+    "newConfigNameLabel": "New config name",
+    "newConfigTitle": "Use new config file",
+    "newConfigLoadFailed": "Failed to load default config template",
+    "addRouteRule": "Add route rule",
+    "viewMode": "View",
+    "editMode": "Edit",
+    "noRouteRules": "No route rules for this platform. The default config file will be used.",
+    "sessionIdPlaceholder": "Session ID or *",
+    "allSessions": "All sessions",
+    "configMissing": "Config file not found",
+    "routeHint": "When delivering messages, the first matching config file from top to bottom is used based on session source. Use * to match all. Use /sid to get the session ID. If none match, the default config file is used.",
+    "warningContinue": "Ignore warning and continue",
+    "warningEditAgain": "Edit again",
+    "configDrawerTitle": "Config File Management",
+    "configDrawerIdLabel": "ID",
+    "configTableHeaders": {
+      "configId": "Config ID linked to this instance",
+      "scope": "Scope in this instance"
+    },
+    "routeTableHeaders": {
+      "source": "Message Source (Type: Session ID)",
+      "config": "Config File",
+      "actions": "Actions"
+    },
+    "messageTypeOptions": {
+      "all": "All messages",
+      "group": "Group messages (GroupMessage)",
+      "friend": "Direct messages (FriendMessage)"
+    },
+    "messageTypeLabels": {
+      "all": "All messages",
+      "group": "Group messages",
+      "friend": "Direct messages"
+    }
+  },
  "messages": {
    "updateSuccess": "Update successful!",
    "addSuccess": "Add successful!",
    "deleteSuccess": "Delete successful!",
    "statusUpdateSuccess": "Status update successful!",
-    "deleteConfirm": "Are you sure you want to delete platform adapter"
+    "deleteConfirm": "Are you sure you want to delete platform adapter",
+    "configNotFoundOpenConfig": "Target config file not found. Opened the config page for review.",
+    "updateMissingPlatformId": "Update failed: missing platform ID.",
+    "platformUpdateFailed": "Platform update failed.",
+    "addSuccessWithConfig": "Platform added. Config file updated.",
+    "configIdMissing": "Unable to get config file ID.",
+    "routingUpdateFailed": "Failed to update routing table: {message}",
+    "createConfigFailed": "Failed to create config file: {message}",
+    "platformIdMissing": "Unable to get platform ID.",
+    "routingSaveFailed": "Failed to save routing table: {message}"
  },
  "status": {
    "enabled": "Enabled",
@@ -91,6 +91,7 @@
  },
  "providerSources": {
    "title": "Provider Sources",
+    "add": "Add",
    "empty": "No provider sources",
    "selectHint": "Please select a provider source",
    "save": "Save Configuration",
@@ -112,7 +113,11 @@
    "hints": {
      "id": "Provider source ID (not provider ID)",
      "key": "API key for authentication",
-      "apiBase": "Custom API endpoint URL"
+      "apiBase": "Custom API endpoint URL",
+      "proxy": "HTTP/HTTPS proxy address, e.g. http://127.0.0.1:7890. Only affects this provider's API requests, doesn't interfere with Docker internal networking."
+    },
+    "labels": {
+      "proxy": "Proxy"
    }
  },
  "models": {
@@ -141,4 +146,4 @@
      "modelId": "Model ID"
    }
  }
-} 
+}
@@ -0,0 +1,32 @@
+{
+  "greeting": {
+    "morning": "Good morning, welcome to AstrBot",
+    "afternoon": "Good afternoon, welcome to AstrBot",
+    "evening": "Good evening, welcome to AstrBot",
+    "newYear": "Happy New Year!"
+  },
+  "subtitle": "You can complete the basic onboarding first. Platform and chat provider setup can both be skipped.",
+  "onboard": {
+    "title": "Quick Onboarding",
+    "subtitle": "Complete initialization directly on the welcome page.",
+    "step1Title": "Configure Platform Bot",
+    "step1Desc": "Connect AstrBot to IM platforms like QQ, Lark, Slack, Telegram, etc.",
+    "step2Title": "Configure AI Model",
+    "step2Desc": "Configure AI models for AstrBot.",
+    "configure": "Configure",
+    "skip": "Skip",
+    "pending": "Pending",
+    "completed": "Completed",
+    "skipped": "Skipped",
+    "platformLoadFailed": "Failed to load platform configuration",
+    "providerLoadFailed": "Failed to load provider configuration",
+    "providerUpdateFailed": "Failed to update default chat provider in config file \"default\"",
+    "providerDefaultUpdated": "Default chat provider in config file \"default\" has been set to {id}"
+  },
+  "resources": {
+    "title": "Resources",
+    "githubDesc": "Give us a Star!",
+    "docsTitle": "Documentation",
+    "docsDesc": "Read the official AstrBot documentation."
+  }
+}
@@ -1,4 +1,5 @@
 {
+  "welcome": "欢迎",
  "dashboard": "数据统计",
  "platforms": "机器人",
  "providers": "模型提供商",
@@ -69,7 +69,9 @@
    "toggleFailed": "更新指令状态失败",
    "renameSuccess": "指令已重命名",
    "renameFailed": "重命名失败",
-    "loadFailed": "加载指令列表失败"
+    "loadFailed": "加载指令列表失败",
+    "updateSuccess": "更新成功",
+    "updateFailed": "更新失败"
  },
  "search": {
    "placeholder": "搜索指令..."
@@ -111,6 +111,10 @@
          "description": "Tavily API Key",
          "hint": "可添加多个 Key 进行轮询。"
        },
+        "websearch_bocha_key": {
+          "description": "BoCha API Key",
+          "hint": "可添加多个 Key 进行轮询。"
+        },
        "websearch_baidu_app_builder_key": {
          "description": "百度千帆智能云 APP Builder API Key",
          "hint": "参考:[https://console.bce.baidu.com/iam/#/iam/apikey/list](https://console.bce.baidu.com/iam/#/iam/apikey/list)"
@@ -193,7 +197,10 @@
        },
        "context_limit_reached_strategy": {
          "description": "超出模型上下文窗口时的处理方式",
-          "labels": ["按对话轮数截断", "由 LLM 压缩上下文"],
+          "labels": [
+            "按对话轮数截断",
+            "由 LLM 压缩上下文"
+          ],
          "hint": "当按对话轮数截断时，会根据上面\"丢弃对话轮数\"的配置丢弃最旧的 N 轮对话。当由 LLM 压缩上下文时，会使用指定的模型进行上下文压缩。"
        },
        "llm_compress_instruction": {
@@ -268,7 +275,6 @@
            "关闭流式回复"
          ]
        },
-
        "wake_prefix": {
          "description": "LLM 聊天额外唤醒前缀",
          "hint": "如果唤醒前缀为 /, 额外聊天唤醒前缀为 chat,则需要 /chat 才会触发 LLM 请求"
@@ -291,6 +297,235 @@
  },
  "platform_group": {
    "name": "平台配置",
+    "platform": {
+      "description": "消息平台适配器",
+      "active_send_mode": {
+        "description": "是否换用主动发送接口"
+      },
+      "appid": {
+        "description": "appid",
+        "hint": "必填项。QQ 官方机器人平台的 appid。如何获取请参考文档。"
+      },
+      "callback_server_host": {
+        "description": "回调服务器主机",
+        "hint": "回调服务器主机。留空则不启用回调服务器。"
+      },
+      "card_template_id": {
+        "description": "卡片模板 ID",
+        "hint": "可选。钉钉互动卡片模板 ID。启用后将使用互动卡片进行流式回复。"
+      },
+      "discord_activity_name": {
+        "description": "Discord 活动名称",
+        "hint": "可选的 Discord 活动名称。留空则不设置活动。"
+      },
+      "discord_command_register": {
+        "description": "是否自动将插件指令注册为 Discord 斜杠指令"
+      },
+      "discord_proxy": {
+        "description": "Discord 代理地址",
+        "hint": "可选的代理地址：http://ip:port"
+      },
+      "discord_token": {
+        "description": "Discord Bot Token",
+        "hint": "在此处填入你的 Discord Bot Token"
+      },
+      "enable": {
+        "description": "启用",
+        "hint": "是否启用该适配器。未启用的适配器对应的消息平台将不会接收到消息。"
+      },
+      "enable_group_c2c": {
+        "description": "启用消息列表单聊",
+        "hint": "启用后，机器人可以接收到 QQ 消息列表中的私聊消息。你可能需要在 QQ 机器人平台上通过扫描二维码的方式添加机器人为你的好友。详见文档。"
+      },
+      "enable_guild_direct_message": {
+        "description": "启用频道私聊",
+        "hint": "启用后，机器人可以接收到频道的私聊消息。"
+      },
+      "id": {
+        "description": "机器人名称",
+        "hint": "机器人名称"
+      },
+      "is_sandbox": {
+        "description": "沙箱模式"
+      },
+      "kf_name": {
+        "description": "微信客服账号名",
+        "hint": "可选。微信客服账号名(不是 ID)。可在 https://kf.weixin.qq.com/kf/frame#/accounts 获取"
+      },
+      "lark_bot_name": {
+        "description": "飞书机器人的名字",
+        "hint": "请务必填写正确，否则 @ 机器人将无法唤醒，只能通过前缀唤醒。"
+      },
+      "lark_connection_mode": {
+        "description": "订阅方式",
+        "labels": [
+          "长连接模式",
+          "推送至服务器模式"
+        ]
+      },
+      "lark_encrypt_key": {
+        "description": "Encrypt Key",
+        "hint": "用于解密飞书回调数据的加密密钥"
+      },
+      "lark_verification_token": {
+        "description": "Verification Token",
+        "hint": "用于验证飞书回调请求的令牌"
+      },
+      "misskey_allow_insecure_downloads": {
+        "description": "允许不安全下载（禁用 SSL 验证）",
+        "hint": "当远端服务器存在证书问题导致无法正常下载时，自动禁用 SSL 验证作为回退方案。适用于某些图床的证书配置问题。启用有安全风险，仅在必要时使用。"
+      },
+      "misskey_default_visibility": {
+        "description": "默认帖子可见性",
+        "hint": "机器人发帖时的默认可见性设置。public：公开，home：主页时间线，followers：仅关注者。"
+      },
+      "misskey_download_chunk_size": {
+        "description": "流式下载分块大小（字节）",
+        "hint": "流式下载和计算 MD5 时使用的每次读取字节数，过小会增加开销，过大会占用内存。"
+      },
+      "misskey_download_timeout": {
+        "description": "远端下载超时时间（秒）",
+        "hint": "下载远程文件时的超时时间（秒），用于异步上传回退到本地上传的场景。"
+      },
+      "misskey_enable_chat": {
+        "description": "启用聊天消息响应",
+        "hint": "启用后，机器人将会监听和响应私信聊天消息"
+      },
+      "misskey_enable_file_upload": {
+        "description": "启用文件上传到 Misskey",
+        "hint": "启用后，适配器会尝试将消息链中的文件上传到 Misskey。URL 文件会先尝试服务器端上传，异步上传失败时会回退到下载后本地上传。"
+      },
+      "misskey_instance_url": {
+        "description": "Misskey 实例 URL",
+        "hint": "例如 https://misskey.example，填写 Bot 账号所在的 Misskey 实例地址"
+      },
+      "misskey_local_only": {
+        "description": "仅限本站（不参与联合）",
+        "hint": "启用后，机器人发出的帖子将仅在本实例可见，不会联合到其他实例"
+      },
+      "misskey_max_download_bytes": {
+        "description": "最大允许下载字节数（超出则中止）",
+        "hint": "如果希望限制下载文件的最大大小以防止 OOM，请填写最大字节数；留空或 null 表示不限制。"
+      },
+      "misskey_token": {
+        "description": "Misskey Access Token",
+        "hint": "连接服务设置生成的 API 鉴权访问令牌（Access token）"
+      },
+      "misskey_upload_concurrency": {
+        "description": "并发上传限制",
+        "hint": "同时进行的文件上传任务上限（整数，默认 3）。"
+      },
+      "misskey_upload_folder": {
+        "description": "上传到网盘的目标文件夹 ID",
+        "hint": "可选：填写 Misskey 网盘中目标文件夹的 ID，上传的文件将放置到该文件夹内。留空则使用账号网盘根目录。"
+      },
+      "port": {
+        "description": "回调服务器端口",
+        "hint": "回调服务器端口。留空则不启用回调服务器。"
+      },
+      "satori_api_base_url": {
+        "description": "Satori API 终结点",
+        "hint": "Satori API 的基础地址。"
+      },
+      "satori_auto_reconnect": {
+        "description": "启用自动重连",
+        "hint": "断开连接时是否自动重新连接 WebSocket。"
+      },
+      "satori_endpoint": {
+        "description": "Satori WebSocket 终结点",
+        "hint": "Satori 事件的 WebSocket 端点。"
+      },
+      "satori_heartbeat_interval": {
+        "description": "Satori 心跳间隔",
+        "hint": "发送心跳消息的间隔（秒）。"
+      },
+      "satori_reconnect_delay": {
+        "description": "Satori 重连延迟",
+        "hint": "尝试重新连接前的延迟时间（秒）。"
+      },
+      "satori_token": {
+        "description": "Satori 令牌",
+        "hint": "用于 Satori API 身份验证的令牌。"
+      },
+      "secret": {
+        "description": "secret",
+        "hint": "必填项。"
+      },
+      "slack_connection_mode": {
+        "description": "Slack Connection Mode",
+        "hint": "The connection mode for Slack. `webhook` uses a webhook server, `socket` uses Slack's Socket Mode."
+      },
+      "slack_webhook_host": {
+        "description": "Slack Webhook Host",
+        "hint": "Only valid when Slack connection mode is `webhook`."
+      },
+      "slack_webhook_path": {
+        "description": "Slack Webhook Path",
+        "hint": "Only valid when Slack connection mode is `webhook`."
+      },
+      "slack_webhook_port": {
+        "description": "Slack Webhook Port",
+        "hint": "Only valid when Slack connection mode is `webhook`."
+      },
+      "telegram_command_auto_refresh": {
+        "description": "Telegram 命令自动刷新",
+        "hint": "启用后，AstrBot 将会在运行时自动刷新 Telegram 命令。(单独设置此项无效)"
+      },
+      "telegram_command_register": {
+        "description": "Telegram 命令注册",
+        "hint": "启用后，AstrBot 将会自动注册 Telegram 命令。"
+      },
+      "telegram_command_register_interval": {
+        "description": "Telegram 命令自动刷新间隔",
+        "hint": "Telegram 命令自动刷新间隔，单位为秒。"
+      },
+      "telegram_token": {
+        "description": "Bot Token",
+        "hint": "如果你的网络环境为中国大陆，请在 `其他配置` 处设置代理或更改 api_base。"
+      },
+      "type": {
+        "description": "适配器类型"
+      },
+      "unified_webhook_mode": {
+        "description": "统一 Webhook 模式",
+        "hint": "启用后，将使用 AstrBot 统一 Webhook 入口，无需单独开启端口。回调地址为 /api/platform/webhook/{webhook_uuid}。"
+      },
+      "webhook_uuid": {
+        "description": "Webhook UUID",
+        "hint": "统一 Webhook 模式下的唯一标识符，创建平台时自动生成。"
+      },
+      "wecom_ai_bot_name": {
+        "description": "企业微信智能机器人的名字",
+        "hint": "请务必填写正确，否则无法使用一些指令。"
+      },
+      "wecomaibot_friend_message_welcome_text": {
+        "description": "企业微信智能机器人私聊欢迎语",
+        "hint": "当用户当天进入智能机器人单聊会话，回复欢迎语，留空则不回复。"
+      },
+      "wecomaibot_init_respond_text": {
+        "description": "企业微信智能机器人初始响应文本",
+        "hint": "当机器人收到消息时，首先回复的文本内容。留空则使用默认值。"
+      },
+      "wpp_active_message_poll": {
+        "description": "是否启用主动消息轮询",
+        "hint": "只有当你发现微信消息没有按时同步到 AstrBot 时，才需要启用这个功能，默认不启用。"
+      },
+      "wpp_active_message_poll_interval": {
+        "description": "主动消息轮询间隔",
+        "hint": "主动消息轮询间隔，单位为秒，默认 3 秒，最大不要超过 60 秒，否则可能被认为是旧消息。"
+      },
+      "ws_reverse_host": {
+        "description": "反向 Websocket 主机",
+        "hint": "AstrBot 将作为服务器端。"
+      },
+      "ws_reverse_port": {
+        "description": "反向 Websocket 端口"
+      },
+      "ws_reverse_token": {
+        "description": "反向 Websocket Token",
+        "hint": "反向 Websocket Token。未设置则不启用 Token 验证。"
+      }
+    },
    "general": {
      "description": "基本",
      "admins_id": {
@@ -616,6 +851,443 @@
      }
    }
  },
+  "provider_group": {
+    "provider": {
+      "genie_onnx_model_dir": {
+        "description": "ONNX Model Directory",
+        "hint": "The directory path containing the ONNX model files"
+      },
+      "genie_language": {
+        "description": "Language"
+      },
+      "xai_native_search": {
+        "description": "启用原生搜索功能",
+        "hint": "启用后，将通过 xAI 的 Chat Completions 原生 Live Search 进行联网检索（按需计费）。仅对 xAI 提供商生效。"
+      },
+      "rerank_api_base": {
+        "description": "重排序模型 API Base URL",
+        "hint": "AstrBot 会在请求时在末尾加上 /v1/rerank。"
+      },
+      "rerank_api_key": {
+        "description": "API Key",
+        "hint": "如果不需要 API Key, 请留空。"
+      },
+      "rerank_model": {
+        "description": "重排序模型名称"
+      },
+      "return_documents": {
+        "description": "是否在排序结果中返回文档原文",
+        "hint": "默认值false，以减少网络传输开销。"
+      },
+      "instruct": {
+        "description": "自定义排序任务类型说明",
+        "hint": "仅在使用 qwen3-rerank 模型时生效。建议使用英文撰写。"
+      },
+      "launch_model_if_not_running": {
+        "description": "模型未运行时自动启动",
+        "hint": "如果模型当前未在 Xinference 服务中运行，是否尝试自动启动它。在生产环境中建议关闭。"
+      },
+      "modalities": {
+        "description": "模型能力",
+        "hint": "模型支持的模态。如所填写的模型不支持图像，请取消勾选图像。",
+        "labels": [
+          "文本",
+          "图像",
+          "工具使用"
+        ]
+      },
+      "custom_headers": {
+        "description": "自定义添加请求头",
+        "hint": "此处添加的键值对将被合并到 OpenAI SDK 的 default_headers 中，用于自定义 HTTP 请求头。值必须为字符串。"
+      },
+      "custom_extra_body": {
+        "description": "自定义请求体参数",
+        "hint": "用于在请求时添加额外的参数，如 temperature、top_p、max_tokens 等。",
+        "template_schema": {
+          "temperature": {
+            "description": "温度参数",
+            "hint": "控制输出的随机性，范围通常为 0-2。值越高越随机。",
+            "name": "Temperature"
+          },
+          "top_p": {
+            "description": "Top-p 采样",
+            "hint": "核采样参数，范围通常为 0-1。控制模型考虑的概率质量。",
+            "name": "Top-p"
+          },
+          "max_tokens": {
+            "description": "最大令牌数",
+            "hint": "生成的最大令牌数。",
+            "name": "Max Tokens"
+          }
+        }
+      },
+      "gpt_weights_path": {
+        "description": "GPT模型文件路径",
+        "hint": "即“.ckpt”后缀的文件，请使用绝对路径，路径两端不要带双引号，不填则默认用GPT_SoVITS内置的SoVITS模型(建议直接在GPT_SoVITS中改默认模型)"
+      },
+      "sovits_weights_path": {
+        "description": "SoVITS模型文件路径",
+        "hint": "即“.pth”后缀的文件，请使用绝对路径，路径两端不要带双引号，不填则默认用GPT_SoVITS内置的SoVITS模型(建议直接在GPT_SoVITS中改默认模型)"
+      },
+      "gsv_default_parms": {
+        "description": "GPT_SoVITS默认参数",
+        "hint": "参考音频文件路径、参考音频文本必填，其他参数根据个人爱好自行填写",
+        "gsv_ref_audio_path": {
+          "description": "参考音频文件路径",
+          "hint": "必填！请使用绝对路径！路径两端不要带双引号！"
+        },
+        "gsv_prompt_text": {
+          "description": "参考音频文本",
+          "hint": "必填！请填写参考音频讲述的文本"
+        },
+        "gsv_prompt_lang": {
+          "description": "参考音频文本语言",
+          "hint": "请填写参考音频讲述的文本的语言，默认为中文"
+        },
+        "gsv_aux_ref_audio_paths": {
+          "description": "辅助参考音频文件路径",
+          "hint": "辅助参考音频文件，可不填"
+        },
+        "gsv_text_lang": {
+          "description": "文本语言",
+          "hint": "默认为中文"
+        },
+        "gsv_top_k": {
+          "description": "生成语音的多样性",
+          "hint": ""
+        },
+        "gsv_top_p": {
+          "description": "核采样的阈值",
+          "hint": ""
+        },
+        "gsv_temperature": {
+          "description": "生成语音的随机性",
+          "hint": ""
+        },
+        "gsv_text_split_method": {
+          "description": "切分文本的方法",
+          "hint": "可选值：  `cut0`：不切分    `cut1`：四句一切   `cut2`：50字一切    `cut3`：按中文句号切    `cut4`：按英文句号切    `cut5`：按标点符号切"
+        },
+        "gsv_batch_size": {
+          "description": "批处理大小",
+          "hint": ""
+        },
+        "gsv_batch_threshold": {
+          "description": "批处理阈值",
+          "hint": ""
+        },
+        "gsv_split_bucket": {
+          "description": "将文本分割成桶以便并行处理",
+          "hint": ""
+        },
+        "gsv_speed_factor": {
+          "description": "语音播放速度",
+          "hint": "1为原始语速"
+        },
+        "gsv_fragment_interval": {
+          "description": "语音片段之间的间隔时间",
+          "hint": ""
+        },
+        "gsv_streaming_mode": {
+          "description": "启用流模式",
+          "hint": ""
+        },
+        "gsv_seed": {
+          "description": "随机种子",
+          "hint": "用于结果的可重复性"
+        },
+        "gsv_parallel_infer": {
+          "description": "并行执行推理",
+          "hint": ""
+        },
+        "gsv_repetition_penalty": {
+          "description": "重复惩罚因子",
+          "hint": ""
+        },
+        "gsv_media_type": {
+          "description": "输出媒体的类型",
+          "hint": "建议用wav"
+        }
+      },
+      "embedding_dimensions": {
+        "description": "嵌入维度",
+        "hint": "嵌入向量的维度。根据模型不同，可能需要调整，请参考具体模型的文档。此配置项请务必填写正确，否则将导致向量数据库无法正常工作。"
+      },
+      "embedding_model": {
+        "description": "嵌入模型",
+        "hint": "嵌入模型名称。"
+      },
+      "embedding_api_key": {
+        "description": "API Key"
+      },
+      "embedding_api_base": {
+        "description": "API Base URL"
+      },
+      "volcengine_cluster": {
+        "description": "火山引擎集群",
+        "hint": "若使用语音复刻大模型，可选volcano_icl或volcano_icl_concurr，默认使用volcano_tts"
+      },
+      "volcengine_voice_type": {
+        "description": "火山引擎音色",
+        "hint": "输入声音id(Voice_type)"
+      },
+      "volcengine_speed_ratio": {
+        "description": "语速设置",
+        "hint": "语速设置，范围为 0.2 到 3.0,默认值为 1.0"
+      },
+      "volcengine_volume_ratio": {
+        "description": "音量设置",
+        "hint": "音量设置，范围为 0.0 到 2.0,默认值为 1.0"
+      },
+      "azure_tts_voice": {
+        "description": "音色设置",
+        "hint": "API 音色"
+      },
+      "azure_tts_style": {
+        "description": "风格设置",
+        "hint": "声音特定的讲话风格。 可以表达快乐、同情和平静等情绪。"
+      },
+      "azure_tts_role": {
+        "description": "模仿设置（可选）",
+        "hint": "讲话角色扮演。 声音可以模仿不同的年龄和性别，但声音名称不会更改。 例如，男性语音可以提高音调和改变语调来模拟女性语音，但语音名称不会更改。 如果角色缺失或不受声音的支持，则会忽略此属性。"
+      },
+      "azure_tts_rate": {
+        "description": "语速设置",
+        "hint": "指示文本的讲出速率。可在字词或句子层面应用语速。 速率变化应为原始音频的 0.5 到 2 倍。"
+      },
+      "azure_tts_volume": {
+        "description": "语音音量设置",
+        "hint": "指示语音的音量级别。 可在句子层面应用音量的变化。以从 0.0 到 100.0（从最安静到最大声，例如 75）的数字表示。 默认值为 100.0。"
+      },
+      "azure_tts_region": {
+        "description": "API 地区",
+        "hint": "Azure_TTS 处理数据所在区域，具体参考 https://learn.microsoft.com/zh-cn/azure/ai-services/speech-service/regions"
+      },
+      "azure_tts_subscription_key": {
+        "description": "服务订阅密钥",
+        "hint": "Azure_TTS 服务的订阅密钥（注意不是令牌）"
+      },
+      "dashscope_tts_voice": {
+        "description": "音色"
+      },
+      "gm_resp_image_modal": {
+        "description": "启用图片模态",
+        "hint": "启用后，将支持返回图片内容。需要模型支持，否则会报错。具体支持模型请查看 Google Gemini 官方网站。温馨提示，如果您需要生成图片，请关闭 `启用群员识别` 配置获得更好的效果。"
+      },
+      "gm_native_search": {
+        "description": "启用原生搜索功能",
+        "hint": "启用后所有函数工具将全部失效，免费次数限制请查阅官方文档"
+      },
+      "gm_native_coderunner": {
+        "description": "启用原生代码执行器",
+        "hint": "启用后所有函数工具将全部失效"
+      },
+      "gm_url_context": {
+        "description": "启用URL上下文功能",
+        "hint": "启用后所有函数工具将全部失效"
+      },
+      "gm_safety_settings": {
+        "description": "安全过滤器",
+        "hint": "设置模型输入的内容安全过滤级别。过滤级别分类为NONE(不屏蔽)、HIGH(高风险时屏蔽)、MEDIUM_AND_ABOVE(中等风险及以上屏蔽)、LOW_AND_ABOVE(低风险及以上时屏蔽)，具体参见Gemini API文档。",
+        "harassment": {
+          "description": "骚扰内容",
+          "hint": "负面或有害评论"
+        },
+        "hate_speech": {
+          "description": "仇恨言论",
+          "hint": "粗鲁、无礼或亵渎性质内容"
+        },
+        "sexually_explicit": {
+          "description": "露骨色情内容",
+          "hint": "包含性行为或其他淫秽内容的引用"
+        },
+        "dangerous_content": {
+          "description": "危险内容",
+          "hint": "宣扬、助长或鼓励有害行为的信息"
+        }
+      },
+      "gm_thinking_config": {
+        "description": "思考配置",
+        "budget": {
+          "description": "思考预算",
+          "hint": "用于指定模型推理时使用的思考 token 数量上限。参见: https://ai.google.dev/gemini-api/docs/thinking#set-budget"
+        },
+        "level": {
+          "description": "思考级别",
+          "hint": "推荐用于 Gemini 3 及以上模型，可控制推理行为。参见: https://ai.google.dev/gemini-api/docs/thinking#thinking-levels"
+        }
+      },
+      "anth_thinking_config": {
+        "description": "思考配置",
+        "budget": {
+          "description": "思考预算",
+          "hint": "Anthropic thinking.budget_tokens 参数。必须 >= 1024。参见: https://platform.claude.com/docs/en/build-with-claude/extended-thinking"
+        }
+      },
+      "minimax-group-id": {
+        "description": "用户组",
+        "hint": "于账户管理->基本信息中可见"
+      },
+      "minimax-langboost": {
+        "description": "指定语言/方言",
+        "hint": "增强对指定的小语种和方言的识别能力，设置后可以提升在指定小语种/方言场景下的语音表现"
+      },
+      "minimax-voice-speed": {
+        "description": "语速",
+        "hint": "生成声音的语速, 取值[0.5, 2], 默认为1.0, 取值越大，语速越快"
+      },
+      "minimax-voice-vol": {
+        "description": "音量",
+        "hint": "生成声音的音量, 取值(0, 10], 默认为1.0, 取值越大，音量越高"
+      },
+      "minimax-voice-pitch": {
+        "description": "语调",
+        "hint": "生成声音的语调, 取值[-12, 12], 默认为0"
+      },
+      "minimax-is-timber-weight": {
+        "description": "启用混合音色",
+        "hint": "启用混合音色, 支持以自定义权重混合最多四种音色, 启用后自动忽略单一音色设置"
+      },
+      "minimax-timber-weight": {
+        "description": "混合音色",
+        "hint": "混合音色及其权重, 最多支持四种音色, 权重为整数, 取值[1, 100]. 可在官网API语音调试台预览代码获得预设以及编写模板, 需要严格按照json字符串格式编写, 可以查看控制台判断是否解析成功. 具体结构可参照默认值以及官网代码预览."
+      },
+      "minimax-voice-id": {
+        "description": "单一音色",
+        "hint": "单一音色编号, 详见官网文档"
+      },
+      "minimax-voice-emotion": {
+        "description": "情绪",
+        "hint": "控制合成语音的情绪。当为 auto 时，将根据文本内容自动选择情绪。"
+      },
+      "minimax-voice-latex": {
+        "description": "支持朗读latex公式",
+        "hint": "朗读latex公式, 但是需要确保输入文本按官网要求格式化"
+      },
+      "minimax-voice-english-normalization": {
+        "description": "支持英语文本规范化",
+        "hint": "可提升数字阅读场景的性能，但会略微增加延迟"
+      },
+      "rag_options": {
+        "description": "RAG 选项",
+        "hint": "检索知识库设置, 非必填。仅 Agent 应用类型支持(智能体应用, 包括 RAG 应用)。阿里云百炼应用开启此功能后将无法多轮对话。",
+        "pipeline_ids": {
+          "description": "知识库 ID 列表",
+          "hint": "对指定知识库内所有文档进行检索, 前往 https://bailian.console.aliyun.com/ 数据应用->知识索引创建和获取 ID。"
+        },
+        "file_ids": {
+          "description": "非结构化文档 ID, 传入该参数将对指定非结构化文档进行检索。",
+          "hint": "对指定非结构化文档进行检索。前往 https://bailian.console.aliyun.com/ 数据管理创建和获取 ID。"
+        },
+        "output_reference": {
+          "description": "是否输出知识库/文档的引用",
+          "hint": "在每次回答尾部加上引用源。默认为 False。"
+        }
+      },
+      "sensevoice_hint": {
+        "description": "部署SenseVoice",
+        "hint": "启用前请 pip 安装 funasr、funasr_onnx、torchaudio、torch、modelscope、jieba 库（默认使用CPU，大约下载 1 GB），并且安装 ffmpeg。否则将无法正常转文字。"
+      },
+      "is_emotion": {
+        "description": "情绪识别",
+        "hint": "是否开启情绪识别。happy｜sad｜angry｜neutral｜fearful｜disgusted｜surprised｜unknown"
+      },
+      "stt_model": {
+        "description": "模型名称",
+        "hint": "modelscope 上的模型名称。默认：iic/SenseVoiceSmall。"
+      },
+      "variables": {
+        "description": "工作流固定输入变量",
+        "hint": "可选。工作流固定输入变量，将会作为工作流的输入。也可以在对话时使用 /set 指令动态设置变量。如果变量名冲突，优先使用动态设置的变量。"
+      },
+      "dashscope_app_type": {
+        "description": "应用类型",
+        "hint": "百炼应用的应用类型。"
+      },
+      "timeout": {
+        "description": "超时时间",
+        "hint": "超时时间，单位为秒。"
+      },
+      "openai-tts-voice": {
+        "description": "voice",
+        "hint": "OpenAI TTS 的声音。OpenAI 默认支持：'alloy', 'echo', 'fable', 'onyx', 'nova', 'shimmer'"
+      },
+      "fishaudio-tts-character": {
+        "description": "character",
+        "hint": "fishaudio TTS 的角色。默认为可莉。更多角色请访问：https://fish.audio/zh-CN/discovery"
+      },
+      "fishaudio-tts-reference-id": {
+        "description": "reference_id",
+        "hint": "fishaudio TTS 的参考模型ID（可选）。如果填入此字段，将直接使用模型ID而不通过角色名称查询。例如：626bb6d3f3364c9cbc3aa6a67300a664。更多模型请访问：https://fish.audio/zh-CN/discovery，进入模型详情界面后可复制模型ID"
+      },
+      "whisper_hint": {
+        "description": "本地部署 Whisper 模型须知",
+        "hint": "启用前请 pip 安装 openai-whisper 库（N卡用户大约下载 2GB，主要是 torch 和 cuda，CPU 用户大约下载 1 GB），并且安装 ffmpeg。否则将无法正常转文字。"
+      },
+      "id": {
+        "description": "ID"
+      },
+      "type": {
+        "description": "模型提供商种类"
+      },
+      "provider_type": {
+        "description": "模型提供商能力种类"
+      },
+      "enable": {
+        "description": "启用"
+      },
+      "key": {
+        "description": "API Key"
+      },
+      "api_base": {
+        "description": "API Base URL"
+      },
+      "model": {
+        "description": "模型 ID",
+        "hint": "模型名称，如 gpt-4o-mini, deepseek-chat。"
+      },
+      "max_context_tokens": {
+        "description": "模型上下文窗口大小",
+        "hint": "模型最大上下文 Token 大小。如果为 0，则会自动从模型元数据填充（如有），也可手动修改。"
+      },
+      "dify_api_key": {
+        "description": "API Key",
+        "hint": "Dify API Key。此项必填。"
+      },
+      "dify_api_base": {
+        "description": "API Base URL",
+        "hint": "Dify API Base URL。默认为 https://api.dify.ai/v1"
+      },
+      "dify_api_type": {
+        "description": "Dify 应用类型",
+        "hint": "Dify API 类型。根据 Dify 官网，目前支持 chat, chatflow, agent, workflow 三种应用类型。"
+      },
+      "dify_workflow_output_key": {
+        "description": "Dify Workflow 输出变量名",
+        "hint": "Dify Workflow 输出变量名。当应用类型为 workflow 时才使用。默认为 astrbot_wf_output。"
+      },
+      "dify_query_input_key": {
+        "description": "Prompt 输入变量名",
+        "hint": "发送的消息文本内容对应的输入变量名。默认为 astrbot_text_query。"
+      },
+      "coze_api_key": {
+        "description": "Coze API Key",
+        "hint": "Coze API 密钥，用于访问 Coze 服务。"
+      },
+      "bot_id": {
+        "description": "Bot ID",
+        "hint": "Coze 机器人的 ID，在 Coze 平台上创建机器人后获得。"
+      },
+      "coze_api_base": {
+        "description": "API Base URL",
+        "hint": "Coze API 的基础 URL 地址，默认为 https://api.coze.cn"
+      },
+      "auto_save_history": {
+        "description": "由 Coze 管理对话记录",
+        "hint": "启用后，将由 Coze 进行对话历史记录管理, 此时 AstrBot 本地保存的上下文不会生效(仅供浏览), 对 AstrBot 的上下文进行的操作也不会生效。如果为禁用, 则使用 AstrBot 管理上下文。"
+      }
+    }
+  },
  "help": {
    "documentation": "官方文档",
    "support": "加群询问",
@@ -45,12 +45,67 @@
    },
    "invalidPlatformId": "平台 ID 不能包含 ':' 或 '!'。"
  },
+  "createDialog": {
+    "step1Title": "选择消息平台类别",
+    "step1Hint": "想把机器人接入到哪里？如 QQ、企业微信、飞书、Discord、Telegram 等。",
+    "platformTypeLabel": "消息平台类别",
+    "configFileTitle": "配置文件",
+    "optional": "可选",
+    "configHint": "想如何配置机器人？配置文件包含了聊天模型、人格、知识库、插件范围等丰富的机器人配置项。",
+    "configDefaultHint": "默认使用默认配置文件 “default”。您也可以稍后配置。",
+    "useExistingConfig": "使用现有配置文件",
+    "selectConfigLabel": "选择配置文件",
+    "createNewConfig": "创建新配置文件",
+    "newConfigNameLabel": "新配置文件名称",
+    "newConfigTitle": "使用新的配置文件",
+    "newConfigLoadFailed": "无法加载默认配置模板",
+    "addRouteRule": "添加路由规则",
+    "viewMode": "查看",
+    "editMode": "编辑",
+    "noRouteRules": "该平台暂无路由规则，将使用默认配置文件",
+    "sessionIdPlaceholder": "会话ID或*",
+    "allSessions": "全部会话",
+    "configMissing": "配置文件不存在",
+    "routeHint": "*消息下发时，根据会话来源按顺序从上到下匹配首个符合条件的配置文件。使用 * 表示匹配所有。使用 /sid 指令获取会话 ID。全部不匹配时将使用默认配置文件。",
+    "warningContinue": "无视警告并继续创建",
+    "warningEditAgain": "重新修改",
+    "configDrawerTitle": "配置文件管理",
+    "configDrawerIdLabel": "ID",
+    "configTableHeaders": {
+      "configId": "与此实例关联的配置文件 ID",
+      "scope": "在此实例下的应用范围"
+    },
+    "routeTableHeaders": {
+      "source": "消息会话来源(消息类型:会话 ID)",
+      "config": "使用配置文件",
+      "actions": "操作"
+    },
+    "messageTypeOptions": {
+      "all": "全部消息",
+      "group": "群组消息(GroupMessage)",
+      "friend": "私聊消息(FriendMessage)"
+    },
+    "messageTypeLabels": {
+      "all": "全部消息",
+      "group": "群组消息",
+      "friend": "私聊消息"
+    }
+  },
  "messages": {
    "updateSuccess": "更新成功!",
    "addSuccess": "添加成功!",
    "deleteSuccess": "删除成功!",
    "statusUpdateSuccess": "状态更新成功!",
-    "deleteConfirm": "确定要删除平台适配器"
+    "deleteConfirm": "确定要删除平台适配器",
+    "configNotFoundOpenConfig": "目标配置文件不存在，已打开配置页面以便检查。",
+    "updateMissingPlatformId": "更新失败，缺少平台 ID。",
+    "platformUpdateFailed": "平台更新失败。",
+    "addSuccessWithConfig": "平台添加成功，配置文件已更新",
+    "configIdMissing": "无法获取配置文件ID。",
+    "routingUpdateFailed": "更新路由表失败: {message}",
+    "createConfigFailed": "创建新配置文件失败: {message}",
+    "platformIdMissing": "无法获取平台 ID。",
+    "routingSaveFailed": "保存路由表失败: {message}"
  },
  "status": {
    "enabled": "已启用",
@@ -92,6 +92,7 @@
  },
  "providerSources": {
    "title": "提供商源",
+    "add": "新增",
    "empty": "暂无提供商源",
    "selectHint": "请选择一个提供商源",
    "save": "保存配置",
@@ -113,7 +114,11 @@
    "hints": {
      "id": "提供商源唯一 ID（不是提供商 ID）",
      "key": "API 密钥",
-      "apiBase": "自定义 API 端点 URL"
+      "apiBase": "自定义 API 端点 URL",
+      "proxy": "HTTP/HTTPS 代理地址，格式如 http://127.0.0.1:7890。仅对该提供商的 API 请求生效，不影响 Docker 内网通信。"
+    },
+    "labels": {
+      "proxy": "代理地址"
    }
  },
  "models": {
@@ -142,4 +147,4 @@
      "modelId": "模型 ID"
    }
  }
-} 
+}
@@ -0,0 +1,32 @@
+{
+  "greeting": {
+    "morning": "上午好，欢迎使用 AstrBot",
+    "afternoon": "下午好，欢迎使用 AstrBot",
+    "evening": "晚上好，欢迎使用 AstrBot",
+    "newYear": "新年快乐！"
+  },
+  "subtitle": "可以先完成基础引导，平台和对话提供商都支持稍后再配置。",
+  "onboard": {
+    "title": "快速引导",
+    "subtitle": "欢迎页可直接完成初始化。",
+    "step1Title": "配置平台机器人",
+    "step1Desc": "将 AstrBot 连接到 QQ、飞书、企业微信、Telegram 等 IM 平台。",
+    "step2Title": "配置 AI 模型",
+    "step2Desc": "为 AstrBot 配置 AI 模型。",
+    "configure": "去配置",
+    "skip": "跳过",
+    "pending": "待处理",
+    "completed": "已完成",
+    "skipped": "已跳过",
+    "platformLoadFailed": "加载平台配置失败",
+    "providerLoadFailed": "加载提供商配置失败",
+    "providerUpdateFailed": "更新 default 配置文件默认对话提供商失败",
+    "providerDefaultUpdated": "已将 default 配置文件的默认对话提供商设置为 {id}"
+  },
+  "resources": {
+    "title": "相关资源",
+    "githubDesc": "给 AstrBot 点个 Star 吧！",
+    "docsTitle": "文档",
+    "docsDesc": "查阅 AstrBot 的官方文档。"
+  }
+}
@@ -36,6 +36,7 @@ import zhCNPersona from './locales/zh-CN/features/persona.json';
 import zhCNMigration from './locales/zh-CN/features/migration.json';
 import zhCNCommand from './locales/zh-CN/features/command.json';
 import zhCNSubagent from './locales/zh-CN/features/subagent.json';
+import zhCNWelcome from './locales/zh-CN/features/welcome.json';

 import zhCNErrors from './locales/zh-CN/messages/errors.json';
 import zhCNSuccess from './locales/zh-CN/messages/success.json';
@@ -76,6 +77,7 @@ import enUSPersona from './locales/en-US/features/persona.json';
 import enUSMigration from './locales/en-US/features/migration.json';
 import enUSCommand from './locales/en-US/features/command.json';
 import enUSSubagent from './locales/en-US/features/subagent.json';
+import enUSWelcome from './locales/en-US/features/welcome.json';

 import enUSErrors from './locales/en-US/messages/errors.json';
 import enUSSuccess from './locales/en-US/messages/success.json';
@@ -123,7 +125,8 @@ export const translations = {
      persona: zhCNPersona,
      migration: zhCNMigration,
      command: zhCNCommand,
-      subagent: zhCNSubagent
+      subagent: zhCNSubagent,
+      welcome: zhCNWelcome
    },
    messages: {
      errors: zhCNErrors,
@@ -171,7 +174,8 @@ export const translations = {
      persona: enUSPersona,
      migration: enUSMigration,
      command: enUSCommand,
-      subagent: enUSSubagent
+      subagent: enUSSubagent,
+      welcome: enUSWelcome
    },
    messages: {
      errors: enUSErrors,
@@ -18,10 +18,15 @@ export interface menu {
 // 在组件中使用时需要通过t()函数进行翻译
 // 所有键名都使用 core.navigation.* 格式
 const sidebarItem: menu[] = [
+  {
+    title: 'core.navigation.welcome',
+    icon: 'mdi-hand-wave-outline',
+    to: '/welcome',
+  },
  {
    title: 'core.navigation.platforms',
    icon: 'mdi-robot',
-    to: '/',
+    to: '/platforms',
  },
  {
    title: 'core.navigation.providers',
@@ -3,13 +3,18 @@ const MainRoutes = {
  meta: {
    requiresAuth: true
  },
-  redirect: '/main/platforms',
+  redirect: '/welcome',
  component: () => import('@/layouts/full/FullLayout.vue'),
  children: [
    {
      name: 'MainPage',
      path: '/',
-      component: () => import('@/views/PlatformPage.vue')
+      component: () => import('@/views/WelcomePage.vue')
+    },
+    {
+      name: 'Welcome',
+      path: '/welcome',
+      component: () => import('@/views/WelcomePage.vue')
    },
    {
      name: 'Extensions',
@@ -132,13 +132,17 @@ export const useCommonStore = defineStore({
    getLogCache() {
      return this.log_cache
    },
+    async fetchStartTime() {
+      const res = await axios.get('/api/stat/start-time');
+      this.startTime = res.data.data.start_time;
+      return this.startTime;
+    },
    getStartTime() {
      if (this.startTime !== -1) {
        return this.startTime
      }
-      axios.get('/api/stat/start-time').then((res) => {
-        this.startTime = res.data.data.start_time
-      })
+      this.fetchStartTime().catch(() => {});
+      return this.startTime
    },
    async getPluginCollections(force = false, customSource = null) {
      // 获取插件市场数据
@@ -0,0 +1,24 @@
+export {};
+
+declare global {
+  interface Window {
+    astrbotDesktop?: {
+      isElectron: boolean;
+      isElectronRuntime: () => Promise<boolean>;
+      getBackendState: () => Promise<{
+        running: boolean;
+        spawning: boolean;
+        restarting: boolean;
+        canManage: boolean;
+      }>;
+      restartBackend: () => Promise<{
+        ok: boolean;
+        reason: string | null;
+      }>;
+      stopBackend: () => Promise<{
+        ok: boolean;
+        reason: string | null;
+      }>;
+    };
+  }
+}
@@ -14,6 +14,8 @@ export function getPlatformIcon(name) {
    return new URL('@/assets/images/platform_logos/qq.png', import.meta.url).href
  } else if (name === 'wecom' || name === 'wecom_ai_bot') {
    return new URL('@/assets/images/platform_logos/wecom.png', import.meta.url).href
+  } else if (name === 'weixin_official_account') {
+    return new URL('@/assets/images/platform_logos/wechat.png', import.meta.url).href
  } else if (name === 'lark') {
    return new URL('@/assets/images/platform_logos/lark.png', import.meta.url).href
  } else if (name === 'dingtalk') {
@@ -0,0 +1,352 @@
+<template>
+  <div class="welcome-page">
+    <v-container fluid class="pa-0">
+      <v-row class="px-4 py-3 pb-6">
+        <v-col cols="12">
+          <h1 class="text-h1 font-weight-bold mb-2 d-flex align-center">
+            {{ greetingText }} {{ greetingEmoji }}
+          </h1>
+          <p class="text-subtitle-1 text-medium-emphasis mb-0">
+            {{ tm('subtitle') }}
+          </p>
+        </v-col>
+      </v-row>
+
+      <v-row class="px-4">
+        <v-col cols="12">
+          <v-card class="welcome-card pa-6" elevation="0" border>
+            <div class="mb-4 text-h3 font-weight-bold">
+              {{ tm('onboard.title') }}
+            </div>
+
+            <v-timeline align="start" side="end" density="compact" class="welcome-timeline" truncate-line="both">
+              <v-timeline-item :dot-color="platformStepState === 'completed' ? 'success' : 'primary'"
+                :icon="platformStepState === 'completed' ? 'mdi-check' : 'mdi-numeric-1'" fill-dot size="small">
+                <div class="pl-2">
+                  <div class="text-h6 font-weight-bold mb-1">{{ tm('onboard.step1Title') }}</div>
+                  <p class="text-body-2 text-medium-emphasis mb-3">{{ tm('onboard.step1Desc') }}</p>
+                  <div class="d-flex align-center">
+                    <v-btn color="primary" variant="flat" rounded="pill" class="px-6" :loading="loadingPlatformDialog"
+                      @click="openPlatformDialog">
+                      {{ tm('onboard.configure') }}
+                    </v-btn>
+                    <div v-if="platformStepState === 'completed'"
+                      class="text-success d-flex align-center text-body-2 font-weight-medium ml-3">
+                      {{ tm('onboard.completed') }}
+                    </div>
+                  </div>
+                </div>
+              </v-timeline-item>
+
+              <v-timeline-item :dot-color="providerStepState === 'completed' ? 'success' : 'primary'"
+                :icon="providerStepState === 'completed' ? 'mdi-check' : 'mdi-numeric-2'" fill-dot size="small">
+                <div class="pl-2">
+                  <div class="text-h6 font-weight-bold mb-1"
+                    :class="{ 'text-medium-emphasis': platformStepState !== 'completed' }">{{ tm('onboard.step2Title')
+                    }}
+                  </div>
+                  <p class="text-body-2 text-medium-emphasis mb-3">{{ tm('onboard.step2Desc') }}</p>
+                  <div class="d-flex align-center">
+                    <v-btn color="primary" variant="flat" rounded="pill" class="px-6" @click="openProviderDialog">
+                      {{ tm('onboard.configure') }}
+                    </v-btn>
+                    <div v-if="providerStepState === 'completed'"
+                      class="text-success d-flex align-center text-body-2 font-weight-medium ml-3">
+                      {{ tm('onboard.completed') }}
+                    </div>
+                  </div>
+                </div>
+              </v-timeline-item>
+            </v-timeline>
+          </v-card>
+
+        </v-col>
+      </v-row>
+
+      <v-row class="px-4 mt-4">
+        <v-col cols="12">
+          <v-card class="welcome-card pa-6" elevation="0" border>
+            <div class="mb-4 text-h3 font-weight-bold">
+              {{ tm('resources.title') }}
+            </div>
+            <v-row>
+              <v-col cols="12" sm="6">
+                <!-- GitHub Card -->
+                <v-card variant="outlined" class="h-100 pa-4 d-flex flex-column"
+                  href="https://github.com/AstrBotDevs/AstrBot/" target="_blank">
+                  <div class="d-flex align-center mb-3">
+                    <v-icon size="32" class="mr-3">mdi-github</v-icon>
+                    <span class="text-h6 font-weight-bold">GitHub</span>
+                  </div>
+                  <p class="text-body-2 text-medium-emphasis mb-0">
+                    {{ tm('resources.githubDesc') }}
+                  </p>
+                </v-card>
+              </v-col>
+
+              <v-col cols="12" sm="6">
+                <!-- Docs Card -->
+                <v-card variant="outlined" class="h-100 pa-4 d-flex flex-column" href="https://docs.astrbot.app"
+                  target="_blank">
+                  <div class="d-flex align-center mb-3">
+                    <v-icon size="32" class="mr-3">mdi-book-open-variant</v-icon>
+                    <span class="text-h6 font-weight-bold">{{ tm('resources.docsTitle') }}</span>
+                  </div>
+                  <p class="text-body-2 text-medium-emphasis mb-0">
+                    {{ tm('resources.docsDesc') }}
+                  </p>
+                </v-card>
+              </v-col>
+
+            </v-row>
+          </v-card>
+        </v-col>
+      </v-row>
+    </v-container>
+
+    <AddNewPlatform v-model:show="showAddPlatformDialog" :metadata="platformMetadata" :config_data="platformConfigData"
+      @refresh-config="loadPlatformConfigBase" />
+    <ProviderConfigDialog v-model="showProviderDialog" />
+  </div>
+</template>
+
+<script setup lang="ts">
+import { computed, ref, watch, onMounted } from 'vue';
+import axios from 'axios';
+import AddNewPlatform from '@/components/platform/AddNewPlatform.vue';
+import ProviderConfigDialog from '@/components/chat/ProviderConfigDialog.vue';
+import { useModuleI18n } from '@/i18n/composables';
+import { useToast } from '@/utils/toast';
+
+type StepState = 'pending' | 'completed' | 'skipped';
+
+const { tm } = useModuleI18n('features/welcome');
+const { success: showSuccess, error: showError } = useToast();
+
+const showAddPlatformDialog = ref(false);
+const showProviderDialog = ref(false);
+const loadingPlatformDialog = ref(false);
+
+const platformMetadata = ref<Record<string, any>>({});
+const platformConfigData = ref<Record<string, any>>({});
+const platformCountBeforeOpen = ref(0);
+const providerCountBeforeOpen = ref(0);
+
+const platformStepState = ref<StepState>('pending');
+const providerStepState = ref<StepState>('pending');
+
+const springFestivalDates: Record<number, string> = {
+  2025: '01-29',
+  2026: '02-17',
+  2027: '02-06',
+  2028: '01-26',
+  2029: '02-13',
+  2030: '02-03'
+}
+
+function isSpringFestival() {
+  const now = new Date();
+  const year = now.getFullYear();
+  const dateStr = springFestivalDates[year];
+
+  if (!dateStr) return false;
+
+  const [month, day] = dateStr.split('-').map(Number);
+  const festivalDate = new Date(year, month - 1, day);
+
+  const start = new Date(festivalDate);
+  start.setDate(festivalDate.getDate() - 5);
+
+  const end = new Date(festivalDate);
+  end.setDate(festivalDate.getDate() + 5);
+
+  // start of day for comparison
+  const nowTime = now.setHours(0, 0, 0, 0);
+  const startTime = start.setHours(0, 0, 0, 0);
+  const endTime = end.setHours(0, 0, 0, 0);
+
+  return nowTime >= startTime && nowTime <= endTime;
+}
+
+function isExactSpringFestivalDay() {
+  const now = new Date();
+  const year = now.getFullYear();
+  const dateStr = springFestivalDates[year];
+
+  if (!dateStr) return false;
+
+  const [month, day] = dateStr.split('-').map(Number);
+  const festivalDate = new Date(year, month - 1, day);
+
+  const nowTime = new Date(now).setHours(0, 0, 0, 0);
+  const festivalTime = festivalDate.setHours(0, 0, 0, 0);
+
+  return nowTime === festivalTime;
+}
+
+const greetingEmoji = computed(() => {
+  if (isExactSpringFestivalDay()) {
+    return '🧨';
+  }
+  const hour = new Date().getHours();
+  if (hour >= 0 && hour < 5) {
+    return '😴';
+  }
+  return '😊';
+});
+
+const greetingText = computed(() => {
+  if (isSpringFestival()) {
+    return tm('greeting.newYear');
+  }
+  const hour = new Date().getHours();
+  if (hour < 12) return tm('greeting.morning');
+  if (hour < 18) return tm('greeting.afternoon');
+  return tm('greeting.evening');
+});
+
+async function loadPlatformConfigBase() {
+  const res = await axios.get('/api/config/get');
+  platformMetadata.value = res.data.data.metadata || {};
+  platformConfigData.value = res.data.data.config || {};
+}
+
+function getChatProvidersFromTemplatePayload(payload: any) {
+  const providers = payload?.providers || [];
+  const sources = payload?.provider_sources || [];
+  const sourceMap = new Map();
+  sources.forEach((s: any) => sourceMap.set(s.id, s.provider_type));
+
+  return providers.filter((provider: any) => {
+    if (provider.provider_type) {
+      return provider.provider_type === 'chat_completion';
+    }
+    if (provider.provider_source_id) {
+      const type = sourceMap.get(provider.provider_source_id);
+      if (type === 'chat_completion') return true;
+    }
+    return String(provider.type || '').includes('chat_completion');
+  });
+}
+
+async function fetchChatProviders() {
+  const response = await axios.get('/api/config/provider/template');
+  if (response.data.status !== 'ok') {
+    throw new Error(response.data.message || tm('onboard.providerLoadFailed'));
+  }
+  return getChatProvidersFromTemplatePayload(response.data.data);
+}
+
+function pickDefaultProviderId(providers: any[]) {
+  if (!providers.length) return '';
+  const enabledProvider = providers.find((provider) => provider.enable !== false);
+  return (enabledProvider || providers[0]).id || '';
+}
+
+async function syncDefaultConfigProviderIfNeeded() {
+  const providers = await fetchChatProviders();
+  if (!providers.length) return;
+
+  const targetProviderId = pickDefaultProviderId(providers);
+  if (!targetProviderId) return;
+
+  const configRes = await axios.get('/api/config/abconf', { params: { id: 'default' } });
+  const configData = configRes.data?.data?.config || {};
+  if (!configData.provider_settings) {
+    configData.provider_settings = {};
+  }
+
+  if (configData.provider_settings.default_provider_id === targetProviderId) return;
+
+  configData.provider_settings.default_provider_id = targetProviderId;
+
+  const updateRes = await axios.post('/api/config/astrbot/update', {
+    conf_id: 'default',
+    config: configData
+  });
+  if (updateRes.data.status !== 'ok') {
+    throw new Error(updateRes.data.message || tm('onboard.providerUpdateFailed'));
+  }
+
+  showSuccess(tm('onboard.providerDefaultUpdated', { id: targetProviderId }));
+}
+
+onMounted(async () => {
+  try {
+    await loadPlatformConfigBase();
+    if ((platformConfigData.value.platform || []).length > 0) {
+      platformStepState.value = 'completed';
+    }
+  } catch (e) {
+    console.error(e);
+  }
+
+  try {
+    const providers = await fetchChatProviders();
+    if (providers.length > 0) {
+      providerStepState.value = 'completed';
+    }
+  } catch (e) {
+    console.error(e);
+  }
+});
+
+async function openPlatformDialog() {
+  loadingPlatformDialog.value = true;
+  try {
+    await loadPlatformConfigBase();
+    platformCountBeforeOpen.value = (platformConfigData.value.platform || []).length;
+    showAddPlatformDialog.value = true;
+  } catch (err: any) {
+    showError(err?.response?.data?.message || err?.message || tm('onboard.platformLoadFailed'));
+  } finally {
+    loadingPlatformDialog.value = false;
+  }
+}
+
+async function openProviderDialog() {
+  try {
+    const providers = await fetchChatProviders();
+    providerCountBeforeOpen.value = providers.length;
+    showProviderDialog.value = true;
+  } catch (err: any) {
+    showError(err?.response?.data?.message || err?.message || tm('onboard.providerLoadFailed'));
+  }
+}
+
+watch(showAddPlatformDialog, async (visible, wasVisible) => {
+  if (!wasVisible || visible) return;
+  try {
+    await loadPlatformConfigBase();
+    const newCount = (platformConfigData.value.platform || []).length;
+    if (newCount > platformCountBeforeOpen.value) {
+      platformStepState.value = 'completed';
+    }
+  } catch (err: any) {
+    showError(err?.response?.data?.message || err?.message || tm('onboard.platformLoadFailed'));
+  }
+});
+
+watch(showProviderDialog, async (visible, wasVisible) => {
+  if (!wasVisible || visible) return;
+  try {
+    const providers = await fetchChatProviders();
+    if (providers.length > providerCountBeforeOpen.value) {
+      providerStepState.value = 'completed';
+      await syncDefaultConfigProviderIfNeeded();
+    }
+  } catch (err: any) {
+    showError(err?.response?.data?.message || err?.message || tm('onboard.providerUpdateFailed'));
+  }
+});
+</script>
+
+<style scoped>
+.welcome-page {
+  height: 100%;
+}
+
+.welcome-card {
+  border-radius: 16px;
+}
+</style>
@@ -29,6 +29,7 @@ export default defineConfig({
    }
  },
  build: {
+    sourcemap: false,
    chunkSizeWarningLimit: 1024 * 1024 // Set the limit to 1 MB
  },
  optimizeDeps: {
@@ -0,0 +1,122 @@
+# AstrBot Desktop (Electron)
+
+This document describes how to build the Electron desktop app from source.
+
+## What This Package Contains
+
+- Electron desktop shell (`desktop/main.js`)
+- Bundled WebUI static files (`desktop/resources/webui`)
+- App assets (`desktop/assets`)
+
+Current behavior:
+
+- Backend executable is bundled in the installer/package.
+- App startup checks backend availability and auto-starts bundled backend when needed.
+- Runtime data is stored under `~/.astrbot` by default, not as a full AstrBot source project.
+
+## Prerequisites
+
+- Python environment ready in repository root (`uv` available)
+- Node.js available
+- `pnpm` available
+
+Desktop dependency management uses `pnpm` with a lockfile:
+
+- `desktop/pnpm-lock.yaml`
+- `pnpm --dir desktop install --frozen-lockfile`
+
+## Build From Scratch
+
+Run commands from repository root:
+
+```bash
+uv sync
+pnpm --dir dashboard install
+pnpm --dir dashboard build
+pnpm --dir desktop install --frozen-lockfile
+pnpm --dir desktop run dist:full
+```
+
+Output files are generated under:
+
+- `desktop/dist/`
+
+## Local Run (Development)
+
+Start backend first:
+
+```bash
+uv run main.py
+```
+
+Start Electron shell:
+
+```bash
+pnpm --dir desktop run dev
+```
+
+## Notes
+
+- `dist:full` runs WebUI build + backend build + Electron packaging.
+- In packaged app mode, backend data root defaults to `~/.astrbot` (can be overridden by `ASTRBOT_ROOT`).
+- Backend build uses `uv run --with pyinstaller ...`, so no manual `PyInstaller` install is required.
+
+## Runtime Directory Layout
+
+By default (`ASTRBOT_ROOT` not set), packaged desktop app uses this layout:
+
+```text
+~/.astrbot/
+  data/
+    config/         # Main configuration
+    plugins/        # Installed plugins
+    plugin_data/    # Plugin persistent data
+    site-packages/  # Plugin dependency installation target in packaged mode
+    temp/           # Runtime temp files
+    skills/         # Skill-related runtime data
+    knowledge_base/ # Knowledge base files
+    backups/        # Backup data
+```
+
+The app does not store a full AstrBot source tree in home directory.
+
+## Troubleshooting
+
+Startup behavior:
+
+- Packaged app shows a local startup page first, then switches to dashboard after backend is reachable.
+- If startup page never switches, check logs and timeout settings below.
+
+Runtime logs:
+
+- Electron shell log: `~/.astrbot/logs/electron.log`
+- Backend stdout/stderr log: `~/.astrbot/logs/backend.log`
+- On backend startup failure, the app dialog also shows the backend reason and backend log path.
+
+Timeout and loading controls:
+
+- `ASTRBOT_BACKEND_TIMEOUT_MS` controls how long Electron waits for backend reachability.
+- In packaged mode, default is `0` (auto mode with a 5-minute safety cap).
+- In development mode, default is `20000`.
+- If backend startup times out, app shows startup failure dialog and exits.
+- `ASTRBOT_DASHBOARD_TIMEOUT_MS` controls dashboard page load wait time after backend is ready (default `20000`).
+- If you see `Unable to load the AstrBot dashboard.`, increase `ASTRBOT_DASHBOARD_TIMEOUT_MS`.
+
+Startup page locale:
+
+- Startup page language follows cached dashboard locale in `~/.astrbot/data/desktop_state.json`.
+- Supported startup locales are `zh-CN` and `en-US`.
+- Remove that file to reset locale fallback behavior.
+
+Backend auto-start:
+
+- `ASTRBOT_BACKEND_AUTO_START=0` disables Electron-managed backend startup.
+- When disabled, backend must already be running at `ASTRBOT_BACKEND_URL` before launching app.
+
+If Electron download times out on restricted networks, configure mirrors before install:
+
+```bash
+export ELECTRON_MIRROR="https://npmmirror.com/mirrors/electron/"
+export ELECTRON_BUILDER_BINARIES_MIRROR="https://npmmirror.com/mirrors/electron-builder-binaries/"
+pnpm --dir desktop install --frozen-lockfile
+```
@@ -0,0 +1,504 @@
+'use strict';
+
+const fs = require('fs');
+const os = require('os');
+const path = require('path');
+const { spawn, spawnSync } = require('child_process');
+const { delay, ensureDir, normalizeUrl, waitForProcessExit } = require('./common');
+
+const PACKAGED_BACKEND_TIMEOUT_FALLBACK_MS = 5 * 60 * 1000;
+
+function parseBackendTimeoutMs(app) {
+  const defaultTimeoutMs = app.isPackaged ? 0 : 20000;
+  const parsed = Number.parseInt(
+    process.env.ASTRBOT_BACKEND_TIMEOUT_MS || `${defaultTimeoutMs}`,
+    10,
+  );
+  if (Number.isFinite(parsed) && parsed >= 0) {
+    return parsed;
+  }
+  return defaultTimeoutMs;
+}
+
+class BackendManager {
+  constructor({ app, baseDir, log, shouldSkipStart }) {
+    this.app = app;
+    this.baseDir = baseDir;
+    this.log = typeof log === 'function' ? log : () => {};
+    this.shouldSkipStart =
+      typeof shouldSkipStart === 'function' ? shouldSkipStart : () => false;
+
+    this.backendUrl = normalizeUrl(
+      process.env.ASTRBOT_BACKEND_URL || 'http://127.0.0.1:6185/',
+    );
+    this.backendAutoStart = process.env.ASTRBOT_BACKEND_AUTO_START !== '0';
+    this.backendTimeoutMs = parseBackendTimeoutMs(app);
+
+    this.backendProcess = null;
+    this.backendConfig = null;
+    this.backendLogFd = null;
+    this.backendLastExitReason = null;
+    this.backendStartupFailureReason = null;
+    this.backendSpawning = false;
+    this.backendRestarting = false;
+  }
+
+  getBackendUrl() {
+    return this.backendUrl;
+  }
+
+  getBackendTimeoutMs() {
+    return this.backendTimeoutMs;
+  }
+
+  getRootDir() {
+    return (
+      process.env.ASTRBOT_ROOT ||
+      this.backendConfig?.rootDir ||
+      this.resolveBackendRoot()
+    );
+  }
+
+  getBackendLogPath() {
+    const rootDir = this.getRootDir();
+    if (!rootDir) {
+      return null;
+    }
+    return path.join(rootDir, 'logs', 'backend.log');
+  }
+
+  getStartupFailureReason() {
+    return this.backendStartupFailureReason;
+  }
+
+  isSpawning() {
+    return this.backendSpawning;
+  }
+
+  isRestarting() {
+    return this.backendRestarting;
+  }
+
+  resolveBackendRoot() {
+    if (!this.app.isPackaged) {
+      return null;
+    }
+    return path.join(os.homedir(), '.astrbot');
+  }
+
+  resolveBackendCwd() {
+    if (!this.app.isPackaged) {
+      return path.resolve(this.baseDir, '..');
+    }
+    return this.resolveBackendRoot();
+  }
+
+  resolveWebuiDir() {
+    if (process.env.ASTRBOT_WEBUI_DIR) {
+      return process.env.ASTRBOT_WEBUI_DIR;
+    }
+    if (!this.app.isPackaged) {
+      return null;
+    }
+    const candidate = path.join(process.resourcesPath, 'webui');
+    const indexPath = path.join(candidate, 'index.html');
+    return fs.existsSync(indexPath) ? candidate : null;
+  }
+
+  getPackagedBackendPath() {
+    if (!this.app.isPackaged) {
+      return null;
+    }
+    const filename =
+      process.platform === 'win32' ? 'astrbot-backend.exe' : 'astrbot-backend';
+    const candidate = path.join(process.resourcesPath, 'backend', filename);
+    return fs.existsSync(candidate) ? candidate : null;
+  }
+
+  buildDefaultBackendLaunch(webuiDir) {
+    if (this.app.isPackaged) {
+      const packagedBackend = this.getPackagedBackendPath();
+      if (!packagedBackend) {
+        return null;
+      }
+      const args = [];
+      if (webuiDir) {
+        args.push('--webui-dir', webuiDir);
+      }
+      return {
+        cmd: packagedBackend,
+        args,
+        shell: false,
+      };
+    }
+
+    const args = ['run', 'main.py'];
+    if (webuiDir) {
+      args.push('--webui-dir', webuiDir);
+    }
+    return {
+      cmd: 'uv',
+      args,
+      shell: process.platform === 'win32',
+    };
+  }
+
+  resolveBackendConfig() {
+    const webuiDir = this.resolveWebuiDir();
+    const customCmd = process.env.ASTRBOT_BACKEND_CMD;
+    const launch = customCmd
+      ? {
+          cmd: customCmd,
+          args: [],
+          shell: true,
+        }
+      : this.buildDefaultBackendLaunch(webuiDir);
+    const cwd = process.env.ASTRBOT_BACKEND_CWD || this.resolveBackendCwd();
+    const rootDir = process.env.ASTRBOT_ROOT || this.resolveBackendRoot();
+    ensureDir(cwd);
+    if (rootDir) {
+      ensureDir(rootDir);
+    }
+    this.backendConfig = {
+      cmd: launch ? launch.cmd : null,
+      args: launch ? launch.args : [],
+      shell: launch ? launch.shell : true,
+      cwd,
+      webuiDir,
+      rootDir,
+    };
+    return this.backendConfig;
+  }
+
+  getBackendConfig() {
+    if (!this.backendConfig) {
+      return this.resolveBackendConfig();
+    }
+    return this.backendConfig;
+  }
+
+  canManageBackend() {
+    return Boolean(this.getBackendConfig().cmd);
+  }
+
+  closeBackendLogFd() {
+    if (this.backendLogFd === null) {
+      return;
+    }
+    try {
+      fs.closeSync(this.backendLogFd);
+    } catch {}
+    this.backendLogFd = null;
+  }
+
+  async pingBackend(timeoutMs = 800) {
+    const controller = new AbortController();
+    const timeout = setTimeout(() => controller.abort(), timeoutMs);
+    try {
+      await fetch(this.backendUrl, {
+        signal: controller.signal,
+        redirect: 'manual',
+      });
+      return true;
+    } catch {
+      return false;
+    } finally {
+      clearTimeout(timeout);
+    }
+  }
+
+  async waitForBackend(maxWaitMs = 0, failOnProcessExit = false) {
+    const effectiveMaxWaitMs =
+      maxWaitMs > 0
+        ? maxWaitMs
+        : this.app.isPackaged
+          ? PACKAGED_BACKEND_TIMEOUT_FALLBACK_MS
+          : 0;
+    const start = Date.now();
+    while (true) {
+      if (await this.pingBackend()) {
+        return { ok: true, reason: null };
+      }
+      if (failOnProcessExit && !this.backendProcess) {
+        return {
+          ok: false,
+          reason:
+            this.backendLastExitReason ||
+            'Backend process exited before becoming reachable.',
+        };
+      }
+      if (effectiveMaxWaitMs > 0 && Date.now() - start >= effectiveMaxWaitMs) {
+        return {
+          ok: false,
+          reason: `Timed out after ${effectiveMaxWaitMs}ms waiting for backend startup.`,
+        };
+      }
+      await delay(600);
+    }
+  }
+
+  startBackend() {
+    if (this.shouldSkipStart()) {
+      this.log('Skip backend start because app is quitting.');
+      return;
+    }
+    if (this.backendProcess) {
+      return;
+    }
+    const backendConfig = this.getBackendConfig();
+    if (!backendConfig.cmd) {
+      return;
+    }
+
+    this.backendLastExitReason = null;
+    const env = {
+      ...process.env,
+      PYTHONUNBUFFERED: '1',
+    };
+    if (backendConfig.rootDir) {
+      env.ASTRBOT_ROOT = backendConfig.rootDir;
+      const logsDir = path.join(backendConfig.rootDir, 'logs');
+      ensureDir(logsDir);
+      const logPath = path.join(logsDir, 'backend.log');
+      try {
+        this.backendLogFd = fs.openSync(logPath, 'a');
+      } catch {
+        this.backendLogFd = null;
+      }
+    }
+
+    this.backendProcess = spawn(backendConfig.cmd, backendConfig.args || [], {
+      cwd: backendConfig.cwd,
+      env,
+      shell: backendConfig.shell,
+      stdio:
+        this.backendLogFd === null
+          ? 'ignore'
+          : ['ignore', this.backendLogFd, this.backendLogFd],
+      windowsHide: true,
+    });
+
+    if (this.backendLogFd !== null) {
+      const launchLine = [backendConfig.cmd, ...(backendConfig.args || [])]
+        .map((item) => JSON.stringify(item))
+        .join(' ');
+      try {
+        fs.writeSync(
+          this.backendLogFd,
+          `[${new Date().toISOString()}] [Electron] Start backend ${launchLine}\n`,
+        );
+      } catch {}
+    }
+
+    this.backendProcess.on('error', (error) => {
+      this.backendLastExitReason =
+        error instanceof Error ? error.message : String(error);
+      if (this.backendLogFd !== null) {
+        try {
+          fs.writeSync(
+            this.backendLogFd,
+            `[${new Date().toISOString()}] [Electron] Backend spawn error: ${
+              error instanceof Error ? error.message : String(error)
+            }\n`,
+          );
+        } catch {}
+      }
+      this.closeBackendLogFd();
+      this.backendProcess = null;
+    });
+
+    this.backendProcess.on('exit', (code, signal) => {
+      this.backendLastExitReason = `Backend process exited (code=${code ?? 'null'}, signal=${signal ?? 'null'}).`;
+      this.closeBackendLogFd();
+      this.backendProcess = null;
+    });
+  }
+
+  async startBackendAndWait(maxWaitMs = this.backendTimeoutMs) {
+    if (!this.canManageBackend()) {
+      return {
+        ok: false,
+        reason: 'Backend command is not configured.',
+      };
+    }
+    this.backendSpawning = true;
+    try {
+      this.startBackend();
+      return await this.waitForBackend(maxWaitMs, true);
+    } finally {
+      this.backendSpawning = false;
+    }
+  }
+
+  async stopManagedBackend() {
+    if (!this.backendProcess) {
+      return;
+    }
+    const processToStop = this.backendProcess;
+    const pid = processToStop.pid;
+    this.backendProcess = null;
+    this.log(`Stop backend requested pid=${pid ?? 'unknown'}`);
+
+    if (process.platform === 'win32' && pid) {
+      try {
+        const result = spawnSync('taskkill', ['/pid', `${pid}`, '/t', '/f'], {
+          stdio: 'ignore',
+          windowsHide: true,
+        });
+        if (result.status !== 0) {
+          this.log(
+            `taskkill failed pid=${pid} status=${result.status} signal=${result.signal ?? 'null'}`,
+          );
+        } else {
+          this.log(`taskkill completed pid=${pid}`);
+        }
+      } catch (error) {
+        this.log(
+          `taskkill threw for pid=${pid}: ${
+            error instanceof Error ? error.message : String(error)
+          }`,
+        );
+      }
+      await waitForProcessExit(processToStop, 5000);
+    } else {
+      if (!processToStop.killed) {
+        try {
+          processToStop.kill('SIGTERM');
+        } catch (error) {
+          this.log(
+            `SIGTERM failed for pid=${pid ?? 'unknown'}: ${
+              error instanceof Error ? error.message : String(error)
+            }`,
+          );
+        }
+      }
+      const exitResult = await waitForProcessExit(processToStop, 5000);
+      if (exitResult === 'timeout' && !processToStop.killed) {
+        try {
+          processToStop.kill('SIGKILL');
+        } catch {}
+        await waitForProcessExit(processToStop, 1500);
+      }
+    }
+    this.closeBackendLogFd();
+  }
+
+  async ensureBackend() {
+    this.backendStartupFailureReason = null;
+
+    const running = await this.pingBackend();
+    if (running) {
+      return true;
+    }
+    if (!this.backendAutoStart || !this.canManageBackend()) {
+      this.backendStartupFailureReason =
+        'Backend auto-start is disabled or backend command is not configured.';
+      return false;
+    }
+    const waitResult = await this.startBackendAndWait(this.backendTimeoutMs);
+    if (!waitResult.ok) {
+      this.backendStartupFailureReason = waitResult.reason;
+      return false;
+    }
+    return true;
+  }
+
+  async getState() {
+    return {
+      running: await this.pingBackend(),
+      spawning: this.backendSpawning,
+      restarting: this.backendRestarting,
+      canManage: this.canManageBackend(),
+    };
+  }
+
+  async restartBackend() {
+    if (!this.canManageBackend()) {
+      return {
+        ok: false,
+        reason: 'Backend command is not configured.',
+      };
+    }
+    if (this.backendSpawning || this.backendRestarting) {
+      return {
+        ok: false,
+        reason: 'Backend action already in progress.',
+      };
+    }
+
+    this.backendRestarting = true;
+    try {
+      await this.stopManagedBackend();
+      const startResult = await this.startBackendAndWait(this.backendTimeoutMs);
+      if (!startResult.ok) {
+        return {
+          ok: false,
+          reason: startResult.reason || 'Failed to restart backend.',
+        };
+      }
+      return {
+        ok: true,
+        reason: null,
+      };
+    } catch (error) {
+      return {
+        ok: false,
+        reason: error instanceof Error ? error.message : String(error),
+      };
+    } finally {
+      this.backendRestarting = false;
+    }
+  }
+
+  async stopBackendForIpc() {
+    if (!this.canManageBackend()) {
+      return {
+        ok: false,
+        reason: 'Backend command is not configured.',
+      };
+    }
+    if (this.backendSpawning || this.backendRestarting) {
+      return {
+        ok: false,
+        reason: 'Backend action already in progress.',
+      };
+    }
+
+    try {
+      if (!this.backendProcess) {
+        const running = await this.pingBackend();
+        if (running) {
+          return {
+            ok: false,
+            reason: 'Backend is running but not managed by Electron.',
+          };
+        }
+        return {
+          ok: true,
+          reason: null,
+        };
+      }
+      await this.stopManagedBackend();
+      const running = await this.pingBackend();
+      if (running) {
+        return {
+          ok: false,
+          reason: 'Backend is still reachable after stop request.',
+        };
+      }
+      return {
+        ok: true,
+        reason: null,
+      };
+    } catch (error) {
+      return {
+        ok: false,
+        reason: error instanceof Error ? error.message : String(error),
+      };
+    }
+  }
+}
+
+module.exports = {
+  BackendManager,
+};
@@ -0,0 +1,59 @@
+'use strict';
+
+const fs = require('fs');
+
+function normalizeUrl(value) {
+  try {
+    const url = new URL(value);
+    if (!url.pathname.endsWith('/')) {
+      url.pathname += '/';
+    }
+    return url.toString();
+  } catch {
+    return 'http://127.0.0.1:6185/';
+  }
+}
+
+function ensureDir(value) {
+  if (!value) {
+    return;
+  }
+  if (fs.existsSync(value)) {
+    return;
+  }
+  fs.mkdirSync(value, { recursive: true });
+}
+
+function delay(ms) {
+  return new Promise((resolve) => setTimeout(resolve, ms));
+}
+
+function waitForProcessExit(child, timeoutMs = 5000) {
+  if (!child) {
+    return Promise.resolve('missing');
+  }
+  if (child.exitCode !== null || child.signalCode !== null) {
+    return Promise.resolve('exited');
+  }
+  return new Promise((resolve) => {
+    let settled = false;
+    const finish = (reason) => {
+      if (settled) {
+        return;
+      }
+      settled = true;
+      clearTimeout(timeout);
+      resolve(reason);
+    };
+    const timeout = setTimeout(() => finish('timeout'), timeoutMs);
+    child.once('exit', () => finish('exit'));
+    child.once('error', () => finish('error'));
+  });
+}
+
+module.exports = {
+  delay,
+  ensureDir,
+  normalizeUrl,
+  waitForProcessExit,
+};
@@ -0,0 +1,30 @@
+'use strict';
+
+const { delay } = require('./common');
+
+async function loadDashboard(mainWindow, backendUrl, maxWaitMs = 20000) {
+  if (!mainWindow) {
+    return false;
+  }
+  const loadUrl = new URL(backendUrl);
+  loadUrl.searchParams.set('_electron_ts', `${Date.now()}`);
+  const start = Date.now();
+  let lastError = null;
+  while (maxWaitMs <= 0 || Date.now() - start < maxWaitMs) {
+    try {
+      await mainWindow.loadURL(loadUrl.toString());
+      return true;
+    } catch (error) {
+      lastError = error;
+      await delay(600);
+    }
+  }
+  if (lastError) {
+    throw lastError;
+  }
+  throw new Error(`Timed out loading ${backendUrl}`);
+}
+
+module.exports = {
+  loadDashboard,
+};
@@ -0,0 +1,33 @@
+'use strict';
+
+const fs = require('fs');
+const path = require('path');
+const { ensureDir } = require('./common');
+
+function createElectronLogger({ app, getRootDir }) {
+  function getElectronLogPath() {
+    const rootDir =
+      process.env.ASTRBOT_ROOT ||
+      (typeof getRootDir === 'function' ? getRootDir() : null) ||
+      app.getPath('userData');
+    return path.join(rootDir, 'logs', 'electron.log');
+  }
+
+  function logElectron(message) {
+    const logPath = getElectronLogPath();
+    ensureDir(path.dirname(logPath));
+    const line = `[${new Date().toISOString()}] ${message}\n`;
+    try {
+      fs.appendFileSync(logPath, line, 'utf8');
+    } catch {}
+  }
+
+  return {
+    getElectronLogPath,
+    logElectron,
+  };
+}
+
+module.exports = {
+  createElectronLogger,
+};
@@ -0,0 +1,172 @@
+'use strict';
+
+const fs = require('fs');
+const path = require('path');
+const { delay, ensureDir } = require('./common');
+
+const LOCALE_STORAGE_KEY = 'astrbot-locale';
+const SUPPORTED_STARTUP_LOCALES = new Set(['zh-CN', 'en-US']);
+
+function normalizeLocale(value) {
+  if (!value) {
+    return null;
+  }
+  const raw = String(value).trim();
+  if (!raw) {
+    return null;
+  }
+  if (SUPPORTED_STARTUP_LOCALES.has(raw)) {
+    return raw;
+  }
+  const lower = raw.toLowerCase();
+  if (lower.startsWith('zh')) {
+    return 'zh-CN';
+  }
+  if (lower.startsWith('en')) {
+    return 'en-US';
+  }
+  return null;
+}
+
+function getStartupTexts(locale) {
+  if (locale === 'zh-CN') {
+    return {
+      title: 'AstrBot 正在启动',
+      message: '界面很快就会加载完成。',
+    };
+  }
+  return {
+    title: 'AstrBot is starting',
+    message: 'The dashboard will be ready in a moment.',
+  };
+}
+
+function getShellTexts(locale) {
+  if (locale === 'zh-CN') {
+    return {
+      trayHide: '隐藏 AstrBot',
+      trayShow: '显示 AstrBot',
+      trayReload: '重新加载',
+      trayQuit: '退出',
+      startupFailTitle: 'AstrBot 启动失败',
+      startupFailMessage: 'AstrBot 后端不可达。',
+      startupFailReasonPrefix: '原因',
+      startupFailAction:
+        '请先启动 http://127.0.0.1:6185 的后端服务，然后重新打开 AstrBot。',
+      startupFailLogPrefix: '后端日志',
+      dashboardFailTitle: 'AstrBot 加载失败',
+      dashboardFailMessage: '无法加载 AstrBot 控制台页面。',
+    };
+  }
+  return {
+    trayHide: 'Hide AstrBot',
+    trayShow: 'Show AstrBot',
+    trayReload: 'Reload',
+    trayQuit: 'Quit',
+    startupFailTitle: 'AstrBot startup failed',
+    startupFailMessage: 'AstrBot backend is not reachable.',
+    startupFailReasonPrefix: 'Reason',
+    startupFailAction:
+      'Please start the backend at http://127.0.0.1:6185 and relaunch AstrBot.',
+    startupFailLogPrefix: 'Backend log',
+    dashboardFailTitle: 'Failed to load AstrBot',
+    dashboardFailMessage: 'Unable to load the AstrBot dashboard.',
+  };
+}
+
+function createLocaleService({ app, getRootDir }) {
+  function resolveStateRoot() {
+    const callbackRoot = (() => {
+      try {
+        return getRootDir ? getRootDir() : null;
+      } catch {
+        return null;
+      }
+    })();
+    return process.env.ASTRBOT_ROOT || callbackRoot || app.getPath('userData');
+  }
+
+  function getDesktopStatePath() {
+    return path.join(resolveStateRoot(), 'data', 'desktop_state.json');
+  }
+
+  function readCachedLocale() {
+    const statePath = getDesktopStatePath();
+    try {
+      const raw = fs.readFileSync(statePath, 'utf8');
+      const parsed = JSON.parse(raw);
+      return normalizeLocale(parsed?.locale);
+    } catch {
+      return null;
+    }
+  }
+
+  function writeCachedLocale(locale) {
+    const normalized = normalizeLocale(locale);
+    if (!normalized) {
+      return;
+    }
+    const statePath = getDesktopStatePath();
+    ensureDir(path.dirname(statePath));
+    try {
+      fs.writeFileSync(
+        statePath,
+        `${JSON.stringify({ locale: normalized }, null, 2)}\n`,
+        'utf8',
+      );
+    } catch {}
+  }
+
+  function resolveStartupLocale() {
+    const cached = readCachedLocale();
+    if (cached) {
+      return cached;
+    }
+    return normalizeLocale(app.getLocale()) || 'zh-CN';
+  }
+
+  async function persistLocaleFromDashboard(
+    mainWindow,
+    backendUrl,
+    timeoutMs = 1200,
+  ) {
+    if (!mainWindow || mainWindow.isDestroyed()) {
+      return;
+    }
+    const currentUrl = mainWindow.webContents.getURL();
+    if (!currentUrl || !currentUrl.startsWith(backendUrl)) {
+      return;
+    }
+    try {
+      const localeRaw = await Promise.race([
+        mainWindow.webContents.executeJavaScript(
+          `(() => {
+            try {
+              return window.localStorage.getItem('${LOCALE_STORAGE_KEY}') || '';
+            } catch {
+              return '';
+            }
+          })();`,
+          true,
+        ),
+        delay(timeoutMs).then(() => null),
+      ]);
+      const locale = normalizeLocale(localeRaw);
+      if (locale) {
+        writeCachedLocale(locale);
+      }
+    } catch {}
+  }
+
+  return {
+    getShellTexts,
+    getStartupTexts,
+    persistLocaleFromDashboard,
+    resolveStartupLocale,
+  };
+}
+
+module.exports = {
+  createLocaleService,
+  normalizeLocale,
+};
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
Soulter	0553f84d6c	chore: bump version to 4.14.7	2026-02-08 23:20:34 +08:00
Soulter	3fd89808ee	chore: update Python version requirements to 3.12 (#4963 )	2026-02-08 23:13:51 +08:00
Soulter	96753821b7	feat: enhance package.json with resource filters and compression settings	2026-02-08 22:58:58 +08:00
鸦羽	eca3ede7b0	fix: dedupe preset messages (#4961 )	2026-02-08 22:18:13 +08:00
エイカク	a7e580407c	feat: supports electron app (#4952 ) * feat: add desktop wrapper with frontend-only packaging * docs: add desktop build docs and track dashboard lockfile * fix: track desktop lockfile for npm ci * fix: allow custom install directory for windows installer * chore: migrate desktop workflow to pnpm * fix(desktop): build AppImage only on Linux * fix(desktop): harden packaged startup and backend bundling * fix(desktop): adapt packaged restart and plugin dependency flow * fix(desktop): prevent backend respawn race on quit * fix(desktop): prefer pyproject version for desktop packaging * fix(desktop): improve startup loading UX and reduce flicker * ci: add desktop multi-platform release workflow * ci: fix desktop release build and mac runner labels * ci: disable electron-builder auto publish in desktop build * ci: avoid electron-builder publish path in build matrix * ci: normalize desktop release artifact names * ci: exclude blockmap files from desktop release assets * ci: prefix desktop release assets with AstrBot and purge blockmaps * feat: add electron bridge types and expose backend control methods in preload script * Update startup screen assets and styles - Changed the icon from PNG to SVG format for better scalability. - Updated the border color from #d0d0d0 to #eeeeee for a softer appearance. - Adjusted the width of the startup screen from 460px to 360px for improved responsiveness. * Update .gitignore to include package.json * chore: remove desktop gitkeep ignore exceptions * docs: update desktop troubleshooting for current runtime behavior * refactor(desktop): modularize runtime and harden startup flow --------- Co-authored-by: Soulter <905617992@qq.com> Co-authored-by: Soulter <37870767+Soulter@users.noreply.github.com>	2026-02-08 21:49:54 +08:00
Soulter	8bd1565696	fix: correct height attribute to max-height for dialog component	2026-02-08 21:13:38 +08:00
Soulter	03e0949067	feat: add welcome feature with localized content and onboarding steps	2026-02-08 21:11:34 +08:00
DD斩首	dbe8e33c4b	feat(telegram): 添加媒体组（相册）支持 / add media group (album) support (#4893 ) * feat(telegram): 添加媒体组（相册）支持 / add media group (album) support ## 功能说明支持 Telegram 的媒体组消息（相册），将多张图片/视频合并为一条消息处理，而不是分散成多条消息。 ## 主要改动 ### 1. 初始化媒体组缓存 (__init__) - 添加 `media_group_cache` 字典存储待处理的媒体组消息 - 使用 2.5 秒超时收集媒体组消息（基于社区最佳实践） - 最大等待时间 10 秒（防止永久等待） ### 2. 消息处理流程 (message_handler) - 检测 `media_group_id` 判断是否为媒体组消息 - 媒体组消息走特殊处理流程，避免分散处理 ### 3. 媒体组消息缓存 (handle_media_group_message) - 缓存收到的媒体组消息 - 使用 APScheduler 实现防抖（debounce）机制 - 每收到新消息时重置超时计时器 - 超时后触发统一处理 ### 4. 媒体组合并处理 (process_media_group) - 从缓存中取出所有媒体项 - 使用第一条消息作为基础（保留文本、回复等信息） - 依次添加所有图片、视频、文档到消息链 - 将合并后的消息发送到处理流程 ## 技术方案论证 Telegram Bot API 在处理媒体组时的设计限制： 1. 将媒体组的每个消息作为独立的 update 发送 2. 每个 update 带有相同的 `media_group_id` 3. 不提供组的总数、结束标志或一次性完整组的机制因此，bot 必须自行收集消息，并通过硬编码超时（timeout/delay）等待可能延迟到达的消息。这是目前唯一可靠的方案，被官方实现、主流框架和开发者社区广泛采用。 ### 官方和社区证据： - Telegram Bot API 服务器实现（tdlib）：明确指出缺少结束标志或总数信息 https://github.com/tdlib/telegram-bot-api/issues/643 - Telegram Bot API 服务器 issue：讨论媒体组处理的不便性，推荐使用超时机制 https://github.com/tdlib/telegram-bot-api/issues/339 - Telegraf（Node.js 框架）：专用媒体组中间件使用 timeout 控制等待时间 https://github.com/DieTime/telegraf-media-group - StackOverflow 讨论：无法一次性获取媒体组所有文件，必须手动收集 https://stackoverflow.com/questions/50180048/telegram-api-get-all-uploaded-photos-by-media-group-id - python-telegram-bot 社区：确认媒体组消息单独到达，需手动处理 https://github.com/python-telegram-bot/python-telegram-bot/discussions/3143 - Telegram Bot API 官方文档：仅定义 `media_group_id` 为可选字段，不提供获取完整组的接口 https://core.telegram.org/bots/api#message ## 实现细节 - 使用 2.5 秒超时收集媒体组消息（基于社区最佳实践） - 最大等待时间 10 秒（防止永久等待） - 采用防抖（debounce）机制：每收到新消息重置计时器 - 利用 APScheduler 实现延迟处理和任务调度 ## 测试验证 - ✅ 发送 5 张图片相册，成功合并为一条消息 - ✅ 保留原始文本说明和回复信息 - ✅ 支持图片、视频、文档混合的媒体组 - ✅ 日志显示 Processing media group <media_group_id> with 5 items ## 代码变更 - 文件：astrbot/core/platform/sources/telegram/tg_adapter.py - 新增代码：124 行 - 新增方法：handle_media_group_message(), process_media_group() Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com> * refactor(telegram): 优化媒体组处理性能和可靠性根据代码审查反馈改进： 1. 实现 media_group_max_wait 防止无限延迟 - 跟踪媒体组创建时间，超过最大等待时间立即处理 - 最坏情况下 10 秒内必定处理，防止消息持续到达导致无限延迟 2. 移除手动 job 查找优化性能 - 删除 O(N) 的 get_jobs() 循环扫描 - 依赖 replace_existing=True 自动替换任务 3. 重用 convert_message 减少代码重复 - 统一所有媒体类型转换逻辑 - 未来添加新媒体类型只需修改一处 Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com> * fix(telegram): handle missing message in media group processing and improve logging messages --------- Co-authored-by: Ubuntu <ubuntu@localhost.localdomain> Co-authored-by: Claude Sonnet 4.5 <noreply@anthropic.com> Co-authored-by: Soulter <905617992@qq.com>	2026-02-08 13:22:45 +08:00
Gao Jinzhe	952023db30	feat: 允许 LLM 预览工具返回的图片并自主决定是否发送 (#4895 ) * feat: 允许 LLM 预览工具返回的图片并自主决定是否发送 * 复用 send_message_to_user 替代独立的图片发送工具 * feat: implement _HandleFunctionToolsResult class for improved tool response handling * docs: add path handling guidelines to AGENTS.md --------- Co-authored-by: Soulter <905617992@qq.com>	2026-02-08 13:16:16 +08:00
Helian Nuits	4e0b5063c6	feat(ComponentPanel): implement permission management for dashboard (#4887 ) * feat(backend): add permission update api * feat(useCommandActions): add updatePermission action and translations * feat(dashboard): implement permission editing ui * style: fix import sorting in command.py * refactor(backend): extract permission update logic to service * feat(i18n): add success and failure messages for command updates --------- Co-authored-by: Soulter <905617992@qq.com>	2026-02-08 12:27:32 +08:00
搁浅	30d1d55e3c	feat: add provider-souce-level proxy (#4949 ) * feat: 添加 Provider 级别代理支持及请求失败日志 * refactor: simplify provider source configuration structure * refactor: move env proxy fallback logic to log_connection_failure * refactor: update client proxy handling and add terminate method for cleanup * refactor: update no_proxy configuration to remove redundant subnet --------- Co-authored-by: Soulter <905617992@qq.com>	2026-02-08 12:22:01 +08:00
Soulter	1e9026d44c	chore: bump version to 4.14.6	2026-02-08 10:43:25 +08:00
letr	e48950d260	fix: localize provider source config UI (#4933 ) * fix: localize provider source ui * feat: localize provider metadata keys * chore: add provider metadata translations * chore: format provider i18n changes * fix: preserve metadata fields in i18n conversion * fix: internationalize platform config and dialog * fix: add Weixin official account platform icon --------- Co-authored-by: Soulter <905617992@qq.com>	2026-02-08 10:40:26 +08:00
Soulter	5e5207da95	perf: optimize webchat and wecom ai queue lifecycle (#4941 ) * perf: optimize webchat and wecom ai queue lifecycle * perf: enhance webchat back queue management with conversation ID support	2026-02-07 14:03:33 +08:00
Soulter	def8b730b7	fix: correct spelling of 'temporary' in SharedPreferences class	2026-02-07 14:01:08 +08:00
Soulter	22a109c2ae	feat: implement feishu / lark media file handling utilities for file, audio and video processing (#4938 ) * feat: implement media file handling utilities for audio and video processing * feat: refactor file upload handling for audio and video in LarkMessageEvent * feat: add cleanup for failed audio and video conversion outputs in media_utils * feat: add utility methods for sending messages and uploading files in LarkMessageEvent	2026-02-07 12:40:05 +08:00
Soulter	6416707e35	chore: bump version to 4.14.5 (#4930 )	2026-02-07 00:55:16 +08:00
Soulter	4658998b85	fix: messages[x] assistant content must contain at least one part (#4928 ) * fix: messages[x] assistant content must contain at least one part fixes: #4876 * ruff format	2026-02-07 00:33:07 +08:00
can	d233fb8b1e	feat: add bocha web search tool (#4902 ) * add bocha web search tool * Revert "add bocha web search tool" This reverts commit `1b36d75a17`. * add bocha web search tool * fix: correct temporary_cache spelling and update supported tools for web search * ruff --------- Co-authored-by: Soulter <905617992@qq.com>	2026-02-06 21:43:42 +08:00
Soulter	fc2a67188f	docs: update watashiwakoseinodesukara Removed duplicate text and added a new image.	2026-02-05 23:08:14 +08:00
boushi1111	d69592aaa8	fix: TypeError when MCP schema type is a list (#4867 ) * Fix TypeError when MCP schema type is a list Fixes crash in Gemini native tools with VRChat MCP. * Refactor: avoid modifying schema in place per feedback * Fix formatting and cleanup comments	2026-02-05 22:51:29 +08:00
Dt8333	f3397f6f08	fix: pyright lint (#4874 ) * feat: 将 MessageSession 的 platform_id 改为 init=False，实例化时无需传入 Co-authored-by: aider (openai/gpt-5.2) <aider@aider.chat> * refactor: 将 isinstance 检查改为元组、将默认模型值设为空字符串、将类型注解改为 Any 并导入 * refactor: 为 _serialize_job 增加返回类型注解 dict * fix: 使用 cast 获取百度 AIP 的 msg 并对 psutil_addr 引入 type: ignore Co-authored-by: aider (openai/gpt-5.2) <aider@aider.chat> * refactor: 引入 _AddrWithPort 协议并替换 conn.laddr 的 cast Co-authored-by: aider (openai/gpt-5.2) <aider@aider.chat> * fix: 在构建 AstrBotMessage 时对 ctx.channel 可能为 None 进行兜底处理 Co-authored-by: aider (openai/gpt-5.2) <aider@aider.chat> --------- Co-authored-by: aider (openai/gpt-5.2) <aider@aider.chat>	2026-02-05 21:54:12 +08:00
LIghtJUNction	be92e4f395	feat: systemd support (#4880 )	2026-02-05 21:52:21 +08:00
Soulter	912e40e7f0	chore: delete unused file	2026-02-05 10:40:53 +08:00
Xican	2876c43387	fix: 修复特定提供商导致的定时任务执行失败的问题 (#4872 ) * fix: 修复特定提供商导致的定时任务执行失败的问题 * ruff format --------- Co-authored-by: Soulter <37870767+Soulter@users.noreply.github.com>	2026-02-05 10:14:31 +08:00
Soulter	464882f206	chore: bump version to 4.14.4	2026-02-04 23:21:08 +08:00
Soulter	6736fb85c2	fix: conversation token usage calculate wrongly and fix tool call infinitely (#4869 )	2026-02-04 23:18:32 +08:00
Soulter	1f75255950	chore: bump version to 4.14.3	2026-02-04 20:31:19 +08:00
Soulter	a954e75547	fix: add apply_reset parameter to build_main_agent and handle coroutine reset in InternalAgentSubStage	2026-02-04 20:25:31 +08:00
@@ -1 +1 @@
 .10
 .12