📦 release: v3.5.12

Fix: plugin priority was not properly applied

.dockerignore

@@ -17,4 +17,8 @@ ENV/
 .conda/
 README*.md
 dashboard/
-data/
+data/
+changelogs/
+tests/
+.ruff_cache/
+.astrbot

.github/FUNDING.yml

@@ -0,0 +1,15 @@
+# These are supported funding model platforms
+
+github: # Replace with up to 4 GitHub Sponsors-enabled usernames e.g., [user1, user2]
+patreon: # Replace with a single Patreon username
+open_collective: astrbot
+ko_fi: # Replace with a single Ko-fi username
+tidelift: # Replace with a single Tidelift platform-name/package-name e.g., npm/babel
+community_bridge: # Replace with a single Community Bridge project-name e.g., cloud-foundry
+liberapay: # Replace with a single Liberapay username
+issuehunt: # Replace with a single IssueHunt username
+lfx_crowdfunding: # Replace with a single LFX Crowdfunding project-name e.g., cloud-foundry
+polar: # Replace with a single Polar username
+buy_me_a_coffee: # Replace with a single Buy Me a Coffee username
+thanks_dev: # Replace with a single thanks.dev username
+custom: ['https://afdian.com/a/astrbot_team']

.github/PULL_REQUEST_TEMPLATE.md

@@ -1,5 +1,5 @@
 <!-- 如果有的话，指定这个 PR 要解决的 ISSUE -->
-修复了 #XYZ
+解决了 #XYZ
 
 ### Motivation
 
@@ -8,3 +8,12 @@
 ### Modifications
 
 <!--简单解释你的改动-->
+
+### Check
+
+<!--如果分支被合并，您的代码将服务于数万名用户！在提交前，请核查一下几点内容-->
+
+- [ ] 😊 我的 Commit Message 符合良好的[规范](https://www.conventionalcommits.org/en/v1.0.0/#summary)
+- [ ] 👀 我的更改经过良好的测试
+- [ ] 🤓 我确保没有引入新依赖库，或者引入了新依赖库的同时将其添加到了 `requirements.txt` 和 `pyproject.toml` 文件相应位置。
+- [ ] 😮 我的更改没有引入恶意代码

.github/workflows/auto_release.yml

@@ -7,7 +7,7 @@ on:
 name: Auto Release
 
 jobs:
-  build:
+  build-and-publish-to-github-release:
     runs-on: ubuntu-latest
     permissions:
       contents: write
@@ -28,8 +28,35 @@ jobs:
         run: |
           echo "changelog=changelogs/${{github.ref_name}}.md" >> "$GITHUB_ENV"
 
-      - name: Create Release
+      - name: Create GitHub Release
         uses: ncipollo/release-action@v1
         with:
           bodyFile: ${{ env.changelog }}
-          artifacts: "dashboard/dist.zip"
+          artifacts: "dashboard/dist.zip"
+      
+  build-and-publish-to-pypi:
+    # 构建并发布到 PyPI
+    runs-on: ubuntu-latest
+    needs: build-and-publish-to-github-release
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.10'
+
+      - name: Install uv
+        run: |
+          python -m pip install uv
+
+      - name: Build package
+        run: |
+          uv build
+
+      - name: Publish to PyPI
+        env:
+          UV_PUBLISH_TOKEN: ${{ secrets.PYPI_TOKEN }}
+        run: |
+          uv publish

.gitignore

@@ -30,3 +30,4 @@ packages/python_interpreter/workplace
 .conda/
 .idea
 pytest.ini
+.astrbot

.python-version

@@ -0,0 +1 @@
+3.10

Dockerfile

@@ -4,6 +4,8 @@ WORKDIR /AstrBot
 COPY . /AstrBot/
 
 RUN apt-get update && apt-get install -y --no-install-recommends \
+    nodejs \
+    npm \
     gcc \
     build-essential \
     python3-dev \
@@ -28,3 +30,6 @@ EXPOSE 6185
 EXPOSE 6186
 
 CMD [ "python", "main.py" ]
+
+
+

README.md

@@ -13,9 +13,11 @@ _✨ 易上手的多平台 LLM 聊天机器人及开发框架 ✨_
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/Soulter/AstrBot?style=for-the-badge&color=76bad9)](https://github.com/Soulter/AstrBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10+-blue.svg?style=for-the-badge&color=76bad9" alt="python">
 <a href="https://hub.docker.com/r/soulter/astrbot"><img alt="Docker pull" src="https://img.shields.io/docker/pulls/soulter/astrbot.svg?style=for-the-badge&color=76bad9"/></a>
-<a  href="https://qm.qq.com/cgi-bin/qm/qr?k=wtbaNx7EioxeaqS9z7RQWVXPIxg2zYr7&jump_from=webapi&authKey=vlqnv/AV2DbJEvGIcxdlNSpfxVy+8vVqijgreRdnVKOaydpc+YSw4MctmEbr0k5"><img alt="Static Badge" src="https://img.shields.io/badge/QQ群-775869627-purple?style=for-the-badge&color=76bad9"></a>
+<a  href="https://qm.qq.com/cgi-bin/qm/qr?k=wtbaNx7EioxeaqS9z7RQWVXPIxg2zYr7&jump_from=webapi&authKey=vlqnv/AV2DbJEvGIcxdlNSpfxVy+8vVqijgreRdnVKOaydpc+YSw4MctmEbr0k5"><img alt="QQ_community" src="https://img.shields.io/badge/QQ群-775869627-purple?style=for-the-badge&color=76bad9"></a>
+<a  href="https://t.me/+hAsD2Ebl5as3NmY1"><img alt="Telegram_community" src="https://img.shields.io/badge/Telegram-AstrBot-purple?style=for-the-badge&color=76bad9"></a>
 [![wakatime](https://wakatime.com/badge/user/915e5316-99c6-4563-a483-ef186cf000c9/project/018e705a-a1a7-409a-a849-3013485e6c8e.svg?style=for-the-badge&color=76bad9)](https://wakatime.com/badge/user/915e5316-99c6-4563-a483-ef186cf000c9/project/018e705a-a1a7-409a-a849-3013485e6c8e)
-![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fstats&query=v&label=7%E6%97%A5%E6%B4%BB%E8%B7%83%E9%87%8F&cacheSeconds=10800&style=for-the-badge&color=3b618e)
+![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fstats&query=v&label=7%E6%97%A5%E6%B4%BB%E8%B7%83%E9%87%8F&cacheSeconds=3600&style=for-the-badge&color=3b618e)
+![Dynamic JSON Badge](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fapi.soulter.top%2Fastrbot%2Fplugin-num&query=%24.result&suffix=%E4%B8%AA&style=for-the-badge&label=%E6%8F%92%E4%BB%B6%E5%B8%82%E5%9C%BA&cacheSeconds=3600)
 
 <a href="https://github.com/Soulter/AstrBot/blob/master/README_en.md">English</a> ｜
 <a href="https://github.com/Soulter/AstrBot/blob/master/README_ja.md">日本語</a> ｜
@@ -25,11 +27,14 @@ _✨ 易上手的多平台 LLM 聊天机器人及开发框架 ✨_
 
 AstrBot 是一个松耦合、异步、支持多消息平台部署、具有易用的插件系统和完善的大语言模型（LLM）接入功能的聊天机器人及开发框架。
 
-[![star](https://gitcode.com/Soulter/AstrBot/star/badge.svg?style=for-the-badge)](https://gitcode.com/Soulter/AstrBot)
 
 <!-- [![codecov](https://img.shields.io/codecov/c/github/soulter/astrbot?style=for-the-badge)](https://codecov.io/gh/Soulter/AstrBot)
  -->
 
+> [!NOTE]
+> 
+> 个人微信接入所依赖的开源项目 Gewechat 近期已停止维护，`v3.5.10` 已经支持接入 WeChatPadPro 替换 gewechat 方式。详见文档 [WeChatPadPro](https://astrbot.app/deploy/platform/wechat/wechatpadpro.html)
+
 ## ✨ 近期更新
 
 1. AstrBot 现已支持接入 [MCP](https://modelcontextprotocol.io/) 服务器！
@@ -73,14 +78,29 @@ AstrBot 是一个松耦合、异步、支持多消息平台部署、具有易用
 
 #### 手动部署
 
-推荐使用 `uv`。
+> 推荐使用 `uv`。
+
+首先，安装 uv：
+
+```bash
+pip install uv
+```
+
+通过 Git Clone 安装 AstrBot：
 
 ```bash
 git clone https://github.com/AstrBotDevs/AstrBot && cd AstrBot
-pip install uv
 uv run main.py
 ```
 
+或者，直接通过 uvx 安装 AstrBot：
+
+```bash
+mkdir astrbot && cd astrbot
+uvx astrbot init
+# uvx astrbot run
+```
+
 或者请参阅官方文档 [通过源码部署 AstrBot](https://astrbot.app/deploy/astrbot/cli.html) 。
 
 #### Replit 部署
@@ -93,9 +113,10 @@ uv run main.py
 | -------- | ------- | ------- | ------ |
 | QQ(官方机器人接口) | ✔    | 私聊、群聊，QQ 频道私聊、群聊 | 文字、图片 |
 | QQ(OneBot)      | ✔    | 私聊、群聊 | 文字、图片、语音 |
-| 微信(个人号)    | ✔    | 微信个人号私聊、群聊 | 文字、图片、语音 |
-| [Telegram](https://github.com/Soulter/astrbot_plugin_telegram)   | ✔    | 私聊、群聊 | 文字、图片 |
-| [微信(企业微信)](https://github.com/Soulter/astrbot_plugin_wecom)    | ✔    | 私聊 | 文字、图片、语音 |
+| 微信个人号    | ✔    | 微信个人号私聊、群聊 | 文字、图片、语音 |
+| Telegram   | ✔    | 私聊、群聊 | 文字、图片 |
+| 企业微信    | ✔    | 私聊 | 文字、图片、语音 |
+| 微信客服    | ✔    | 私聊 | 文字、图片 |
 | 飞书   | ✔    | 私聊、群聊 | 文字、图片 |
 | 钉钉   | ✔    | 私聊、群聊 | 文字、图片 |
 | 微信对话开放平台 | 🚧    | 计划内 | - |
@@ -107,21 +128,26 @@ uv run main.py
 
 | 名称    | 支持性 | 类型 | 备注 |
 | -------- | ------- | ------- | ------- |
-| OpenAI API | ✔    | 文本生成 | 也支持 DeepSeek、Google Gemini、GLM、Kimi、硅基流动、xAI 等兼容 OpenAI API 的服务 |
+| OpenAI API | ✔    | 文本生成 | 也支持 DeepSeek、Google Gemini、GLM、Kimi、xAI 等兼容 OpenAI API 的服务 |
 | Claude API | ✔    | 文本生成 |  |
 | Google Gemini API | ✔    | 文本生成 |  |
 | Dify | ✔    | LLMOps |  |
-| DashScope(阿里云百炼应用) | ✔    | LLMOps |  |
+| 阿里云百炼应用 | ✔    | LLMOps |  |
 | Ollama | ✔    | 模型加载器 | 本地部署 DeepSeek、Llama 等开源语言模型 |
 | LM Studio | ✔    | 模型加载器 | 本地部署 DeepSeek、Llama 等开源语言模型 |
 | LLMTuner | ✔    | 模型加载器 | 本地加载 lora 等微调模型 |
+| 硅基流动 | ✔    | 模型 API 服务平台 |  |
+| PPIO 派欧云 | ✔    | 模型 API 服务平台 |  |
 | OneAPI | ✔    | LLM 分发系统 |  |
 | Whisper | ✔    | 语音转文本 | 支持 API、本地部署 |
 | SenseVoice | ✔    | 语音转文本 | 本地部署 |
 | OpenAI TTS API | ✔    | 文本转语音 |  |
 | GSVI | ✔    | 文本转语音 | GPT-Sovits-Inference |
-| Fishaudio | ✔    | 文本转语音 | GPT-Sovits 作者参与的项目 |
-| Edge-TTS | ✔    | 文本转语音 | Edge 浏览器的免费 TTS |
+| FishAudio | ✔    | 文本转语音 | GPT-Sovits 作者参与的项目 |
+| Edge TTS | ✔    | 文本转语音 | Edge 浏览器的免费 TTS |
+| 阿里云百炼 TTS | ✔    | 文本转语音 |  |
+| Azure TTS | ✔    | 文本转语音 | Microsoft Azure TTS |
+
 
 ## ❤️ 贡献
 
@@ -149,6 +175,8 @@ pre-commit install
 
 ## ✨ Demo
 
+<details><summary>👉 点击展开多张 Demo 截图 👈</summary>
+
 <div align='center'>
 
 <img src="https://github.com/user-attachments/assets/4ee688d9-467d-45c8-99d6-368f9a8a92d8" width="600">
@@ -170,6 +198,9 @@ _✨ WebUI ✨_
 
 </div>
 
+</details>
+
+
 ## ❤️ Special Thanks
 
 特别感谢所有 Contributors 和插件开发者对 AstrBot 的贡献 ❤️
@@ -178,6 +209,10 @@ _✨ WebUI ✨_
   <img src="https://contrib.rocks/image?repo=AstrBotDevs/AstrBot" />
 </a>
 
+此外，本项目的诞生离不开以下开源项目：
+
+- [NapNeko/NapCatQQ](https://github.com/NapNeko/NapCatQQ)
+- [wechatpy/wechatpy](https://github.com/wechatpy/wechatpy)
 
 ## ⭐ Star History
 

astrbot/api/provider/__init__.py

@@ -1,5 +1,5 @@
 from astrbot.core.provider import Provider, STTProvider, Personality
-from astrbot.core.provider.entites import (
+from astrbot.core.provider.entities import (
     ProviderRequest,
     ProviderType,
     ProviderMetaData,

astrbot/cli/__init__.py

@@ -0,0 +1 @@
+__version__ = "3.5.8"

astrbot/cli/__main__.py

@@ -0,0 +1,59 @@
+"""
+AstrBot CLI入口
+"""
+
+import click
+import sys
+from . import __version__
+from .commands import init, run, plug, conf
+
+logo_tmpl = r"""
+     ___           _______.___________..______      .______     ______   .___________.
+    /   \         /       |           ||   _  \     |   _  \   /  __  \  |           |
+   /  ^  \       |   (----`---|  |----`|  |_)  |    |  |_)  | |  |  |  | `---|  |----`
+  /  /_\  \       \   \       |  |     |      /     |   _  <  |  |  |  |     |  |
+ /  _____  \  .----)   |      |  |     |  |\  \----.|  |_)  | |  `--'  |     |  |
+/__/     \__\ |_______/       |__|     | _| `._____||______/   \______/      |__|
+"""
+
+
+@click.group()
+@click.version_option(__version__, prog_name="AstrBot")
+def cli() -> None:
+    """The AstrBot CLI"""
+    click.echo(logo_tmpl)
+    click.echo("Welcome to AstrBot CLI!")
+    click.echo(f"AstrBot CLI version: {__version__}")
+
+
+@click.command()
+@click.argument("command_name", required=False, type=str)
+def help(command_name: str | None) -> None:
+    """显示命令的帮助信息
+
+    如果提供了 COMMAND_NAME，则显示该命令的详细帮助信息。
+    否则，显示通用帮助信息。
+    """
+    ctx = click.get_current_context()
+    if command_name:
+        # 查找指定命令
+        command = cli.get_command(ctx, command_name)
+        if command:
+            # 显示特定命令的帮助信息
+            click.echo(command.get_help(ctx))
+        else:
+            click.echo(f"Unknown command: {command_name}")
+            sys.exit(1)
+    else:
+        # 显示通用帮助信息
+        click.echo(cli.get_help(ctx))
+
+
+cli.add_command(init)
+cli.add_command(run)
+cli.add_command(help)
+cli.add_command(plug)
+cli.add_command(conf)
+
+if __name__ == "__main__":
+    cli()

astrbot/cli/commands/__init__.py

@@ -0,0 +1,6 @@
+from .cmd_init import init
+from .cmd_run import run
+from .cmd_plug import plug
+from .cmd_conf import conf
+
+__all__ = ["init", "run", "plug", "conf"]

astrbot/cli/commands/cmd_conf.py

@@ -0,0 +1,206 @@
+import json
+import click
+import hashlib
+import zoneinfo
+from typing import Any, Callable
+from ..utils import get_astrbot_root, check_astrbot_root
+
+
+def _validate_log_level(value: str) -> str:
+    """验证日志级别"""
+    value = value.upper()
+    if value not in ["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"]:
+        raise click.ClickException(
+            "日志级别必须是 DEBUG/INFO/WARNING/ERROR/CRITICAL 之一"
+        )
+    return value
+
+
+def _validate_dashboard_port(value: str) -> int:
+    """验证 Dashboard 端口"""
+    try:
+        port = int(value)
+        if port < 1 or port > 65535:
+            raise click.ClickException("端口必须在 1-65535 范围内")
+        return port
+    except ValueError:
+        raise click.ClickException("端口必须是数字")
+
+
+def _validate_dashboard_username(value: str) -> str:
+    """验证 Dashboard 用户名"""
+    if not value:
+        raise click.ClickException("用户名不能为空")
+    return value
+
+
+def _validate_dashboard_password(value: str) -> str:
+    """验证 Dashboard 密码"""
+    if not value:
+        raise click.ClickException("密码不能为空")
+    return hashlib.md5(value.encode()).hexdigest()
+
+
+def _validate_timezone(value: str) -> str:
+    """验证时区"""
+    try:
+        zoneinfo.ZoneInfo(value)
+    except Exception:
+        raise click.ClickException(f"无效的时区: {value}，请使用有效的IANA时区名称")
+    return value
+
+
+def _validate_callback_api_base(value: str) -> str:
+    """验证回调接口基址"""
+    if not value.startswith("http://") and not value.startswith("https://"):
+        raise click.ClickException("回调接口基址必须以 http:// 或 https:// 开头")
+    return value
+
+
+# 可通过CLI设置的配置项，配置键到验证器函数的映射
+CONFIG_VALIDATORS: dict[str, Callable[[str], Any]] = {
+    "timezone": _validate_timezone,
+    "log_level": _validate_log_level,
+    "dashboard.port": _validate_dashboard_port,
+    "dashboard.username": _validate_dashboard_username,
+    "dashboard.password": _validate_dashboard_password,
+    "callback_api_base": _validate_callback_api_base,
+}
+
+
+def _load_config() -> dict[str, Any]:
+    """加载或初始化配置文件"""
+    root = get_astrbot_root()
+    if not check_astrbot_root(root):
+        raise click.ClickException(
+            f"{root}不是有效的 AstrBot 根目录，如需初始化请使用 astrbot init"
+        )
+
+    config_path = root / "data" / "cmd_config.json"
+    if not config_path.exists():
+        from astrbot.core.config.default import DEFAULT_CONFIG
+
+        config_path.write_text(
+            json.dumps(DEFAULT_CONFIG, ensure_ascii=False, indent=2),
+            encoding="utf-8-sig",
+        )
+
+    try:
+        return json.loads(config_path.read_text(encoding="utf-8-sig"))
+    except json.JSONDecodeError as e:
+        raise click.ClickException(f"配置文件解析失败: {str(e)}")
+
+
+def _save_config(config: dict[str, Any]) -> None:
+    """保存配置文件"""
+    config_path = get_astrbot_root() / "data" / "cmd_config.json"
+
+    config_path.write_text(
+        json.dumps(config, ensure_ascii=False, indent=2), encoding="utf-8-sig"
+    )
+
+
+def _set_nested_item(obj: dict[str, Any], path: str, value: Any) -> None:
+    """设置嵌套字典中的值"""
+    parts = path.split(".")
+    for part in parts[:-1]:
+        if part not in obj:
+            obj[part] = {}
+        elif not isinstance(obj[part], dict):
+            raise click.ClickException(
+                f"配置路径冲突: {'.'.join(parts[: parts.index(part) + 1])} 不是字典"
+            )
+        obj = obj[part]
+    obj[parts[-1]] = value
+
+
+def _get_nested_item(obj: dict[str, Any], path: str) -> Any:
+    """获取嵌套字典中的值"""
+    parts = path.split(".")
+    for part in parts:
+        obj = obj[part]
+    return obj
+
+
+@click.group(name="conf")
+def conf():
+    """配置管理命令
+
+    支持的配置项:
+
+    - timezone: 时区设置 (例如: Asia/Shanghai)
+
+    - log_level: 日志级别 (DEBUG/INFO/WARNING/ERROR/CRITICAL)
+
+    - dashboard.port: Dashboard 端口
+
+    - dashboard.username: Dashboard 用户名
+
+    - dashboard.password: Dashboard 密码
+
+    - callback_api_base: 回调接口基址
+    """
+    pass
+
+
+@conf.command(name="set")
+@click.argument("key")
+@click.argument("value")
+def set_config(key: str, value: str):
+    """设置配置项的值"""
+    if key not in CONFIG_VALIDATORS.keys():
+        raise click.ClickException(f"不支持的配置项: {key}")
+
+    config = _load_config()
+
+    try:
+        old_value = _get_nested_item(config, key)
+        validated_value = CONFIG_VALIDATORS[key](value)
+        _set_nested_item(config, key, validated_value)
+        _save_config(config)
+
+        click.echo(f"配置已更新: {key}")
+        if key == "dashboard.password":
+            click.echo("  原值: ********")
+            click.echo("  新值: ********")
+        else:
+            click.echo(f"  原值: {old_value}")
+            click.echo(f"  新值: {validated_value}")
+
+    except KeyError:
+        raise click.ClickException(f"未知的配置项: {key}")
+    except Exception as e:
+        raise click.UsageError(f"设置配置失败: {str(e)}")
+
+
+@conf.command(name="get")
+@click.argument("key", required=False)
+def get_config(key: str = None):
+    """获取配置项的值，不提供key则显示所有可配置项"""
+    config = _load_config()
+
+    if key:
+        if key not in CONFIG_VALIDATORS.keys():
+            raise click.ClickException(f"不支持的配置项: {key}")
+
+        try:
+            value = _get_nested_item(config, key)
+            if key == "dashboard.password":
+                value = "********"
+            click.echo(f"{key}: {value}")
+        except KeyError:
+            raise click.ClickException(f"未知的配置项: {key}")
+        except Exception as e:
+            raise click.UsageError(f"获取配置失败: {str(e)}")
+    else:
+        click.echo("当前配置:")
+        for key in CONFIG_VALIDATORS.keys():
+            try:
+                value = (
+                    "********"
+                    if key == "dashboard.password"
+                    else _get_nested_item(config, key)
+                )
+                click.echo(f"  {key}: {value}")
+            except (KeyError, TypeError):
+                pass

astrbot/cli/commands/cmd_init.py

@@ -0,0 +1,55 @@
+import asyncio
+
+import click
+from filelock import FileLock, Timeout
+
+from ..utils import check_dashboard, get_astrbot_root
+
+
+async def initialize_astrbot(astrbot_root) -> None:
+    """执行 AstrBot 初始化逻辑"""
+    dot_astrbot = astrbot_root / ".astrbot"
+
+    if not dot_astrbot.exists():
+        click.echo(f"Current Directory: {astrbot_root}")
+        click.echo(
+            "如果你确认这是 Astrbot root directory, 你需要在当前目录下创建一个 .astrbot 文件标记该目录为 AstrBot 的数据目录。"
+        )
+        if click.confirm(
+            f"请检查当前目录是否正确，确认正确请回车: {astrbot_root}",
+            default=True,
+            abort=True,
+        ):
+            dot_astrbot.touch()
+            click.echo(f"Created {dot_astrbot}")
+
+    paths = {
+        "data": astrbot_root / "data",
+        "config": astrbot_root / "data" / "config",
+        "plugins": astrbot_root / "data" / "plugins",
+        "temp": astrbot_root / "data" / "temp",
+    }
+
+    for name, path in paths.items():
+        path.mkdir(parents=True, exist_ok=True)
+        click.echo(f"{'Created' if not path.exists() else 'Directory exists'}: {path}")
+
+    await check_dashboard(astrbot_root / "data")
+
+
+@click.command()
+def init() -> None:
+    """初始化 AstrBot"""
+    click.echo("Initializing AstrBot...")
+    astrbot_root = get_astrbot_root()
+    lock_file = astrbot_root / "astrbot.lock"
+    lock = FileLock(lock_file, timeout=5)
+
+    try:
+        with lock.acquire():
+            asyncio.run(initialize_astrbot(astrbot_root))
+    except Timeout:
+        raise click.ClickException("无法获取锁文件，请检查是否有其他实例正在运行")
+
+    except Exception as e:
+        raise click.ClickException(f"初始化失败: {e!s}")

astrbot/cli/commands/cmd_plug.py

@@ -0,0 +1,247 @@
+import re
+from pathlib import Path
+
+import click
+import shutil
+
+
+from ..utils import (
+    get_git_repo,
+    build_plug_list,
+    manage_plugin,
+    PluginStatus,
+    check_astrbot_root,
+    get_astrbot_root,
+)
+
+
+@click.group()
+def plug():
+    """插件管理"""
+    pass
+
+
+def _get_data_path() -> Path:
+    base = get_astrbot_root()
+    if not check_astrbot_root(base):
+        raise click.ClickException(
+            f"{base}不是有效的 AstrBot 根目录，如需初始化请使用 astrbot init"
+        )
+    return (base / "data").resolve()
+
+
+def display_plugins(plugins, title=None, color=None):
+    if title:
+        click.echo(click.style(title, fg=color, bold=True))
+
+    click.echo(f"{'名称':<20} {'版本':<10} {'状态':<10} {'作者':<15} {'描述':<30}")
+    click.echo("-" * 85)
+
+    for p in plugins:
+        desc = p["desc"][:30] + ("..." if len(p["desc"]) > 30 else "")
+        click.echo(
+            f"{p['name']:<20} {p['version']:<10} {p['status']:<10} "
+            f"{p['author']:<15} {desc:<30}"
+        )
+
+
+@plug.command()
+@click.argument("name")
+def new(name: str):
+    """创建新插件"""
+    base_path = _get_data_path()
+    plug_path = base_path / "plugins" / name
+
+    if plug_path.exists():
+        raise click.ClickException(f"插件 {name} 已存在")
+
+    author = click.prompt("请输入插件作者", type=str)
+    desc = click.prompt("请输入插件描述", type=str)
+    version = click.prompt("请输入插件版本", type=str)
+    if not re.match(r"^\d+\.\d+(\.\d+)?$", version.lower().lstrip("v")):
+        raise click.ClickException("版本号必须为 x.y 或 x.y.z 格式")
+    repo = click.prompt("请输入插件仓库：", type=str)
+    if not repo.startswith("http"):
+        raise click.ClickException("仓库地址必须以 http 开头")
+
+    click.echo("下载插件模板...")
+    get_git_repo(
+        "https://github.com/Soulter/helloworld",
+        plug_path,
+    )
+
+    click.echo("重写插件信息...")
+    # 重写 metadata.yaml
+    with open(plug_path / "metadata.yaml", "w", encoding="utf-8") as f:
+        f.write(
+            f"name: {name}\n"
+            f"desc: {desc}\n"
+            f"version: {version}\n"
+            f"author: {author}\n"
+            f"repo: {repo}\n"
+        )
+
+    # 重写 README.md
+    with open(plug_path / "README.md", "w", encoding="utf-8") as f:
+        f.write(f"# {name}\n\n{desc}\n\n# 支持\n\n[帮助文档](https://astrbot.app)\n")
+
+    # 重写 main.py
+    with open(plug_path / "main.py", "r", encoding="utf-8") as f:
+        content = f.read()
+
+    new_content = content.replace(
+        '@register("helloworld", "YourName", "一个简单的 Hello World 插件", "1.0.0")',
+        f'@register("{name}", "{author}", "{desc}", "{version}")',
+    )
+
+    with open(plug_path / "main.py", "w", encoding="utf-8") as f:
+        f.write(new_content)
+
+    click.echo(f"插件 {name} 创建成功")
+
+
+@plug.command()
+@click.option("--all", "-a", is_flag=True, help="列出未安装的插件")
+def list(all: bool):
+    """列出插件"""
+    base_path = _get_data_path()
+    plugins = build_plug_list(base_path / "plugins")
+
+    # 未发布的插件
+    not_published_plugins = [
+        p for p in plugins if p["status"] == PluginStatus.NOT_PUBLISHED
+    ]
+    if not_published_plugins:
+        display_plugins(not_published_plugins, "未发布的插件", "red")
+
+    # 需要更新的插件
+    need_update_plugins = [
+        p for p in plugins if p["status"] == PluginStatus.NEED_UPDATE
+    ]
+    if need_update_plugins:
+        display_plugins(need_update_plugins, "需要更新的插件", "yellow")
+
+    # 已安装的插件
+    installed_plugins = [p for p in plugins if p["status"] == PluginStatus.INSTALLED]
+    if installed_plugins:
+        display_plugins(installed_plugins, "已安装的插件", "green")
+
+    # 未安装的插件
+    not_installed_plugins = [
+        p for p in plugins if p["status"] == PluginStatus.NOT_INSTALLED
+    ]
+    if not_installed_plugins and all:
+        display_plugins(not_installed_plugins, "未安装的插件", "blue")
+
+    if (
+        not any([not_published_plugins, need_update_plugins, installed_plugins])
+        and not all
+    ):
+        click.echo("未安装任何插件")
+
+
+@plug.command()
+@click.argument("name")
+@click.option("--proxy", help="代理服务器地址")
+def install(name: str, proxy: str | None):
+    """安装插件"""
+    base_path = _get_data_path()
+    plug_path = base_path / "plugins"
+    plugins = build_plug_list(base_path / "plugins")
+
+    plugin = next(
+        (
+            p
+            for p in plugins
+            if p["name"] == name and p["status"] == PluginStatus.NOT_INSTALLED
+        ),
+        None,
+    )
+
+    if not plugin:
+        raise click.ClickException(f"未找到可安装的插件 {name}，可能是不存在或已安装")
+
+    manage_plugin(plugin, plug_path, is_update=False, proxy=proxy)
+
+
+@plug.command()
+@click.argument("name")
+def remove(name: str):
+    """卸载插件"""
+    base_path = _get_data_path()
+    plugins = build_plug_list(base_path / "plugins")
+    plugin = next((p for p in plugins if p["name"] == name), None)
+
+    if not plugin or not plugin.get("local_path"):
+        raise click.ClickException(f"插件 {name} 不存在或未安装")
+
+    plugin_path = plugin["local_path"]
+
+    click.confirm(f"确定要卸载插件 {name} 吗?", default=False, abort=True)
+
+    try:
+        shutil.rmtree(plugin_path)
+        click.echo(f"插件 {name} 已卸载")
+    except Exception as e:
+        raise click.ClickException(f"卸载插件 {name} 失败: {e}")
+
+
+@plug.command()
+@click.argument("name", required=False)
+@click.option("--proxy", help="Github代理地址")
+def update(name: str, proxy: str | None):
+    """更新插件"""
+    base_path = _get_data_path()
+    plug_path = base_path / "plugins"
+    plugins = build_plug_list(base_path / "plugins")
+
+    if name:
+        plugin = next(
+            (
+                p
+                for p in plugins
+                if p["name"] == name and p["status"] == PluginStatus.NEED_UPDATE
+            ),
+            None,
+        )
+
+        if not plugin:
+            raise click.ClickException(f"插件 {name} 不需要更新或无法更新")
+
+        manage_plugin(plugin, plug_path, is_update=True, proxy=proxy)
+    else:
+        need_update_plugins = [
+            p for p in plugins if p["status"] == PluginStatus.NEED_UPDATE
+        ]
+
+        if not need_update_plugins:
+            click.echo("没有需要更新的插件")
+            return
+
+        click.echo(f"发现 {len(need_update_plugins)} 个插件需要更新")
+        for plugin in need_update_plugins:
+            plugin_name = plugin["name"]
+            click.echo(f"正在更新插件 {plugin_name}...")
+            manage_plugin(plugin, plug_path, is_update=True, proxy=proxy)
+
+
+@plug.command()
+@click.argument("query")
+def search(query: str):
+    """搜索插件"""
+    base_path = _get_data_path()
+    plugins = build_plug_list(base_path / "plugins")
+
+    matched_plugins = [
+        p
+        for p in plugins
+        if query.lower() in p["name"].lower()
+        or query.lower() in p["desc"].lower()
+        or query.lower() in p["author"].lower()
+    ]
+
+    if not matched_plugins:
+        click.echo(f"未找到匹配 '{query}' 的插件")
+        return
+
+    display_plugins(matched_plugins, f"搜索结果: '{query}'", "cyan")

astrbot/cli/commands/cmd_run.py

@@ -0,0 +1,63 @@
+import os
+import sys
+from pathlib import Path
+
+import click
+import asyncio
+import traceback
+
+from filelock import FileLock, Timeout
+
+from ..utils import check_dashboard, check_astrbot_root, get_astrbot_root
+
+
+async def run_astrbot(astrbot_root: Path):
+    """运行 AstrBot"""
+    from astrbot.core import logger, LogManager, LogBroker, db_helper
+    from astrbot.core.initial_loader import InitialLoader
+
+    await check_dashboard(astrbot_root / "data")
+
+    log_broker = LogBroker()
+    LogManager.set_queue_handler(logger, log_broker)
+    db = db_helper
+
+    core_lifecycle = InitialLoader(db, log_broker)
+
+    await core_lifecycle.start()
+
+
+@click.option("--reload", "-r", is_flag=True, help="插件自动重载")
+@click.option("--port", "-p", help="Astrbot Dashboard端口", required=False, type=str)
+@click.command()
+def run(reload: bool, port: str) -> None:
+    """运行 AstrBot"""
+    try:
+        os.environ["ASTRBOT_CLI"] = "1"
+        astrbot_root = get_astrbot_root()
+
+        if not check_astrbot_root(astrbot_root):
+            raise click.ClickException(
+                f"{astrbot_root}不是有效的 AstrBot 根目录，如需初始化请使用 astrbot init"
+            )
+
+        os.environ["ASTRBOT_ROOT"] = str(astrbot_root)
+        sys.path.insert(0, str(astrbot_root))
+
+        if port:
+            os.environ["DASHBOARD_PORT"] = port
+
+        if reload:
+            click.echo("启用插件自动重载")
+            os.environ["ASTRBOT_RELOAD"] = "1"
+
+        lock_file = astrbot_root / "astrbot.lock"
+        lock = FileLock(lock_file, timeout=5)
+        with lock.acquire():
+            asyncio.run(run_astrbot(astrbot_root))
+    except KeyboardInterrupt:
+        click.echo("AstrBot 已关闭...")
+    except Timeout:
+        raise click.ClickException("无法获取锁文件，请检查是否有其他实例正在运行")
+    except Exception as e:
+        raise click.ClickException(f"运行时出现错误: {e}\n{traceback.format_exc()}")

astrbot/cli/utils/__init__.py

@@ -0,0 +1,18 @@
+from .basic import (
+    get_astrbot_root,
+    check_astrbot_root,
+    check_dashboard,
+)
+from .plugin import get_git_repo, manage_plugin, build_plug_list, PluginStatus
+from .version_comparator import VersionComparator
+
+__all__ = [
+    "get_astrbot_root",
+    "check_astrbot_root",
+    "check_dashboard",
+    "get_git_repo",
+    "manage_plugin",
+    "build_plug_list",
+    "VersionComparator",
+    "PluginStatus",
+]

astrbot/cli/utils/basic.py

@@ -0,0 +1,67 @@
+from pathlib import Path
+
+import click
+
+
+def check_astrbot_root(path: str | Path) -> bool:
+    """检查路径是否为 AstrBot 根目录"""
+    if not isinstance(path, Path):
+        path = Path(path)
+    if not path.exists() or not path.is_dir():
+        return False
+    if not (path / ".astrbot").exists():
+        return False
+    return True
+
+
+def get_astrbot_root() -> Path:
+    """获取Astrbot根目录路径"""
+    return Path.cwd()
+
+
+async def check_dashboard(astrbot_root: Path) -> None:
+    """检查是否安装了dashboard"""
+    from astrbot.core.utils.io import get_dashboard_version, download_dashboard
+    from astrbot.core.config.default import VERSION
+    from .version_comparator import VersionComparator
+
+    try:
+        dashboard_version = await get_dashboard_version()
+        match dashboard_version:
+            case None:
+                click.echo("未安装管理面板")
+                if click.confirm(
+                    "是否安装管理面板？",
+                    default=True,
+                    abort=True,
+                ):
+                    click.echo("正在安装管理面板...")
+                    await download_dashboard(
+                        path="data/dashboard.zip", extract_path=str(astrbot_root)
+                    )
+                    click.echo("管理面板安装完成")
+
+            case str():
+                if VersionComparator.compare_version(VERSION, dashboard_version) <= 0:
+                    click.echo("管理面板已是最新版本")
+                    return
+                else:
+                    try:
+                        version = dashboard_version.split("v")[1]
+                        click.echo(f"管理面板版本: {version}")
+                        await download_dashboard(
+                            path="data/dashboard.zip", extract_path=str(astrbot_root)
+                        )
+                    except Exception as e:
+                        click.echo(f"下载管理面板失败: {e}")
+                        return
+    except FileNotFoundError:
+        click.echo("初始化管理面板目录...")
+        try:
+            await download_dashboard(
+                path=str(astrbot_root / "dashboard.zip"), extract_path=str(astrbot_root)
+            )
+            click.echo("管理面板初始化完成")
+        except Exception as e:
+            click.echo(f"下载管理面板失败: {e}")
+            return

astrbot/cli/utils/plugin.py

@@ -0,0 +1,230 @@
+import shutil
+import tempfile
+
+import httpx
+import yaml
+from enum import Enum
+from io import BytesIO
+from pathlib import Path
+from zipfile import ZipFile
+
+import click
+from .version_comparator import VersionComparator
+
+
+class PluginStatus(str, Enum):
+    INSTALLED = "已安装"
+    NEED_UPDATE = "需更新"
+    NOT_INSTALLED = "未安装"
+    NOT_PUBLISHED = "未发布"
+
+
+def get_git_repo(url: str, target_path: Path, proxy: str | None = None):
+    """从 Git 仓库下载代码并解压到指定路径"""
+    temp_dir = Path(tempfile.mkdtemp())
+    try:
+        # 解析仓库信息
+        repo_namespace = url.split("/")[-2:]
+        author = repo_namespace[0]
+        repo = repo_namespace[1]
+
+        # 尝试获取最新的 release
+        release_url = f"https://api.github.com/repos/{author}/{repo}/releases"
+        try:
+            with httpx.Client(
+                proxy=proxy if proxy else None, follow_redirects=True
+            ) as client:
+                resp = client.get(release_url)
+                resp.raise_for_status()
+                releases = resp.json()
+
+                if releases:
+                    # 使用最新的 release
+                    download_url = releases[0]["zipball_url"]
+                else:
+                    # 没有 release，使用默认分支
+                    click.echo(f"正在从默认分支下载 {author}/{repo}")
+                    download_url = f"https://github.com/{author}/{repo}/archive/refs/heads/master.zip"
+        except Exception as e:
+            click.echo(f"获取 release 信息失败: {e}，将直接使用提供的 URL")
+            download_url = url
+
+        # 应用代理
+        if proxy:
+            download_url = f"{proxy}/{download_url}"
+
+        # 下载并解压
+        with httpx.Client(
+            proxy=proxy if proxy else None, follow_redirects=True
+        ) as client:
+            resp = client.get(download_url)
+            if (
+                resp.status_code == 404
+                and "archive/refs/heads/master.zip" in download_url
+            ):
+                alt_url = download_url.replace("master.zip", "main.zip")
+                click.echo("master 分支不存在，尝试下载 main 分支")
+                resp = client.get(alt_url)
+                resp.raise_for_status()
+            else:
+                resp.raise_for_status()
+            zip_content = BytesIO(resp.content)
+        with ZipFile(zip_content) as z:
+            z.extractall(temp_dir)
+            namelist = z.namelist()
+            root_dir = Path(namelist[0]).parts[0] if namelist else ""
+            if target_path.exists():
+                shutil.rmtree(target_path)
+            shutil.move(temp_dir / root_dir, target_path)
+    finally:
+        if temp_dir.exists():
+            shutil.rmtree(temp_dir, ignore_errors=True)
+
+
+def load_yaml_metadata(plugin_dir: Path) -> dict:
+    """从 metadata.yaml 文件加载插件元数据
+
+    Args:
+        plugin_dir: 插件目录路径
+
+    Returns:
+        dict: 包含元数据的字典，如果读取失败则返回空字典
+    """
+    yaml_path = plugin_dir / "metadata.yaml"
+    if yaml_path.exists():
+        try:
+            return yaml.safe_load(yaml_path.read_text(encoding="utf-8")) or {}
+        except Exception as e:
+            click.echo(f"读取 {yaml_path} 失败: {e}", err=True)
+    return {}
+
+
+def build_plug_list(plugins_dir: Path) -> list:
+    """构建插件列表，包含本地和在线插件信息
+
+    Args:
+        plugins_dir (Path): 插件目录路径
+
+    Returns:
+        list: 包含插件信息的字典列表
+    """
+    # 获取本地插件信息
+    result = []
+    if plugins_dir.exists():
+        for plugin_name in [d.name for d in plugins_dir.glob("*") if d.is_dir()]:
+            plugin_dir = plugins_dir / plugin_name
+
+            # 从 metadata.yaml 加载元数据
+            metadata = load_yaml_metadata(plugin_dir)
+
+            # 如果成功加载元数据，添加到结果列表
+            if metadata and all(
+                k in metadata for k in ["name", "desc", "version", "author", "repo"]
+            ):
+                result.append({
+                    "name": str(metadata.get("name", "")),
+                    "desc": str(metadata.get("desc", "")),
+                    "version": str(metadata.get("version", "")),
+                    "author": str(metadata.get("author", "")),
+                    "repo": str(metadata.get("repo", "")),
+                    "status": PluginStatus.INSTALLED,
+                    "local_path": str(plugin_dir),
+                })
+
+    # 获取在线插件列表
+    online_plugins = []
+    try:
+        with httpx.Client() as client:
+            resp = client.get("https://api.soulter.top/astrbot/plugins")
+            resp.raise_for_status()
+            data = resp.json()
+            for plugin_id, plugin_info in data.items():
+                online_plugins.append({
+                    "name": str(plugin_id),
+                    "desc": str(plugin_info.get("desc", "")),
+                    "version": str(plugin_info.get("version", "")),
+                    "author": str(plugin_info.get("author", "")),
+                    "repo": str(plugin_info.get("repo", "")),
+                    "status": PluginStatus.NOT_INSTALLED,
+                    "local_path": None,
+                })
+    except Exception as e:
+        click.echo(f"获取在线插件列表失败: {e}", err=True)
+
+    # 与在线插件比对，更新状态
+    online_plugin_names = {plugin["name"] for plugin in online_plugins}
+    for local_plugin in result:
+        if local_plugin["name"] in online_plugin_names:
+            # 查找对应的在线插件
+            online_plugin = next(
+                p for p in online_plugins if p["name"] == local_plugin["name"]
+            )
+            if (
+                VersionComparator.compare_version(
+                    local_plugin["version"], online_plugin["version"]
+                )
+                < 0
+            ):
+                local_plugin["status"] = PluginStatus.NEED_UPDATE
+        else:
+            # 本地插件未在线上发布
+            local_plugin["status"] = PluginStatus.NOT_PUBLISHED
+
+    # 添加未安装的在线插件
+    for online_plugin in online_plugins:
+        if not any(plugin["name"] == online_plugin["name"] for plugin in result):
+            result.append(online_plugin)
+
+    return result
+
+
+def manage_plugin(
+    plugin: dict, plugins_dir: Path, is_update: bool = False, proxy: str | None = None
+) -> None:
+    """安装或更新插件
+
+    Args:
+        plugin (dict): 插件信息字典
+        plugins_dir (Path): 插件目录
+        is_update (bool, optional): 是否为更新操作. 默认为 False
+        proxy (str, optional): 代理服务器地址
+    """
+    plugin_name = plugin["name"]
+    repo_url = plugin["repo"]
+
+    # 如果是更新且有本地路径，直接使用本地路径
+    if is_update and plugin.get("local_path"):
+        target_path = Path(plugin["local_path"])
+    else:
+        target_path = plugins_dir / plugin_name
+
+    backup_path = Path(f"{target_path}_backup") if is_update else None
+
+    # 检查插件是否存在
+    if is_update and not target_path.exists():
+        raise click.ClickException(f"插件 {plugin_name} 未安装，无法更新")
+
+    # 备份现有插件
+    if is_update and backup_path.exists():
+        shutil.rmtree(backup_path)
+    if is_update:
+        shutil.copytree(target_path, backup_path)
+
+    try:
+        click.echo(
+            f"正在从 {repo_url} {'更新' if is_update else '下载'}插件 {plugin_name}..."
+        )
+        get_git_repo(repo_url, target_path, proxy)
+
+        # 更新成功，删除备份
+        if is_update and backup_path.exists():
+            shutil.rmtree(backup_path)
+        click.echo(f"插件 {plugin_name} {'更新' if is_update else '安装'}成功")
+    except Exception as e:
+        if target_path.exists():
+            shutil.rmtree(target_path, ignore_errors=True)
+        if is_update and backup_path.exists():
+            shutil.move(backup_path, target_path)
+        raise click.ClickException(
+            f"{'更新' if is_update else '安装'}插件 {plugin_name} 时出错: {e}"
+        )

astrbot/cli/utils/version_comparator.py

@@ -0,0 +1,92 @@
+"""
+拷贝自 astrbot.core.utils.version_comparator
+"""
+
+import re
+
+
+class VersionComparator:
+    @staticmethod
+    def compare_version(v1: str, v2: str) -> int:
+        """根据 Semver 语义版本规范来比较版本号的大小。支持不仅局限于 3 个数字的版本号，并处理预发布标签。
+
+        参考: https://semver.org/lang/zh-CN/
+
+        返回 1 表示 v1 > v2，返回 -1 表示 v1 < v2，返回 0 表示 v1 = v2。
+        """
+        v1 = v1.lower().replace("v", "")
+        v2 = v2.lower().replace("v", "")
+
+        def split_version(version):
+            match = re.match(
+                r"^([0-9]+(?:\.[0-9]+)*)(?:-([0-9A-Za-z-]+(?:\.[0-9A-Za-z-]+)*))?(?:\+(.+))?$",
+                version,
+            )
+            if not match:
+                return [], None
+            major_minor_patch = match.group(1).split(".")
+            prerelease = match.group(2)
+            # buildmetadata = match.group(3) # 构建元数据在比较时忽略
+            parts = [int(x) for x in major_minor_patch]
+            prerelease = VersionComparator._split_prerelease(prerelease)
+            return parts, prerelease
+
+        v1_parts, v1_prerelease = split_version(v1)
+        v2_parts, v2_prerelease = split_version(v2)
+
+        # 比较数字部分
+        length = max(len(v1_parts), len(v2_parts))
+        v1_parts.extend([0] * (length - len(v1_parts)))
+        v2_parts.extend([0] * (length - len(v2_parts)))
+
+        for i in range(length):
+            if v1_parts[i] > v2_parts[i]:
+                return 1
+            elif v1_parts[i] < v2_parts[i]:
+                return -1
+
+        # 比较预发布标签
+        if v1_prerelease is None and v2_prerelease is not None:
+            return 1  # 没有预发布标签的版本高于有预发布标签的版本
+        elif v1_prerelease is not None and v2_prerelease is None:
+            return -1  # 有预发布标签的版本低于没有预发布标签的版本
+        elif v1_prerelease is not None and v2_prerelease is not None:
+            len_pre = max(len(v1_prerelease), len(v2_prerelease))
+            for i in range(len_pre):
+                p1 = v1_prerelease[i] if i < len(v1_prerelease) else None
+                p2 = v2_prerelease[i] if i < len(v2_prerelease) else None
+
+                if p1 is None and p2 is not None:
+                    return -1
+                elif p1 is not None and p2 is None:
+                    return 1
+                elif isinstance(p1, int) and isinstance(p2, str):
+                    return -1
+                elif isinstance(p1, str) and isinstance(p2, int):
+                    return 1
+                elif isinstance(p1, int) and isinstance(p2, int):
+                    if p1 > p2:
+                        return 1
+                    elif p1 < p2:
+                        return -1
+                elif isinstance(p1, str) and isinstance(p2, str):
+                    if p1 > p2:
+                        return 1
+                    elif p1 < p2:
+                        return -1
+            return 0  # 预发布标签完全相同
+
+        return 0  # 数字部分和预发布标签都相同
+
+    @staticmethod
+    def _split_prerelease(prerelease):
+        if not prerelease:
+            return None
+        parts = prerelease.split(".")
+        result = []
+        for part in parts:
+            if part.isdigit():
+                result.append(int(part))
+            else:
+                result.append(part)
+        return result

astrbot/core/__init__.py

@@ -7,24 +7,28 @@ from astrbot.core.utils.pip_installer import PipInstaller
 from astrbot.core.db.sqlite import SQLiteDatabase
 from astrbot.core.config.default import DB_PATH
 from astrbot.core.config import AstrBotConfig
+from astrbot.core.file_token_service import FileTokenService
+from .utils.astrbot_path import get_astrbot_data_path
 
 # 初始化数据存储文件夹
-os.makedirs("data", exist_ok=True)
+os.makedirs(get_astrbot_data_path(), exist_ok=True)
+
+WEBUI_SK = "Advanced_System_for_Text_Response_and_Bot_Operations_Tool"
+DEMO_MODE = os.getenv("DEMO_MODE", False)
 
 astrbot_config = AstrBotConfig()
 t2i_base_url = astrbot_config.get("t2i_endpoint", "https://t2i.soulter.top/text2img")
 html_renderer = HtmlRenderer(t2i_base_url)
 logger = LogManager.GetLogger(log_name="astrbot")
-
-if os.environ.get("TESTING", ""):
-    logger.setLevel("DEBUG")
-
 db_helper = SQLiteDatabase(DB_PATH)
-sp = (
-    SharedPreferences()
-)  # 简单的偏好设置存储, 这里后续应该存储到数据库中, 一些部分可以存储到配置中
-pip_installer = PipInstaller(astrbot_config.get("pip_install_arg", ""))
+# 简单的偏好设置存储, 这里后续应该存储到数据库中, 一些部分可以存储到配置中
+sp = SharedPreferences()
+# 文件令牌服务
+file_token_service = FileTokenService()
+pip_installer = PipInstaller(
+    astrbot_config.get("pip_install_arg", ""),
+    astrbot_config.get("pypi_index_url", None),
+)
 web_chat_queue = asyncio.Queue(maxsize=32)
 web_chat_back_queue = asyncio.Queue(maxsize=32)
-WEBUI_SK = "Advanced_System_for_Text_Response_and_Bot_Operations_Tool"
-DEMO_MODE = os.getenv("DEMO_MODE", False)
+

astrbot/core/config/astrbot_config.py

@@ -4,8 +4,9 @@ import logging
 import enum
 from .default import DEFAULT_CONFIG, DEFAULT_VALUE_MAP
 from typing import Dict
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
-ASTRBOT_CONFIG_PATH = "data/cmd_config.json"
+ASTRBOT_CONFIG_PATH = os.path.join(get_astrbot_data_path(), "cmd_config.json")
 logger = logging.getLogger("astrbot")
 
 
@@ -45,8 +46,6 @@ class AstrBotConfig(dict):
 
         with open(config_path, "r", encoding="utf-8-sig") as f:
             conf_str = f.read()
-            if conf_str.startswith("/ufeff"):  # remove BOM
-                conf_str = conf_str.encode("utf8")[3:].decode("utf8")
             conf = json.loads(conf_str)
 
         # 检查配置完整性，并插入

astrbot/core/config/default.py

@@ -2,8 +2,11 @@
 如需修改配置，请在 `data/cmd_config.json` 中修改或者在管理面板中可视化修改。
 """
 
-VERSION = "3.5.2"
-DB_PATH = "data/data_v3.db"
+import os
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
+
+VERSION = "3.5.12"
+DB_PATH = os.path.join(get_astrbot_data_path(), "data_v3.db")
 
 # 默认配置
 DEFAULT_CONFIG = {
@@ -38,6 +41,7 @@ DEFAULT_CONFIG = {
         "no_permission_reply": True,
         "empty_mention_waiting": True,
         "friend_message_needs_wake_prefix": False,
+        "ignore_bot_self_message": False,
     },
     "provider": [],
     "provider_settings": {
@@ -50,6 +54,9 @@ DEFAULT_CONFIG = {
         "default_personality": "default",
         "prompt_prefix": "",
         "max_context_length": -1,
+        "dequeue_context_length": 1,
+        "streaming_response": False,
+        "streaming_segmented": False,
     },
     "provider_stt_settings": {
         "enable": False,
@@ -58,6 +65,8 @@ DEFAULT_CONFIG = {
     "provider_tts_settings": {
         "enable": False,
         "provider_id": "",
+        "dual_output": False,
+        "use_file_service": False,
     },
     "provider_ltm_settings": {
         "group_icl_enable": False,
@@ -83,6 +92,7 @@ DEFAULT_CONFIG = {
     "t2i_word_threshold": 150,
     "t2i_strategy": "remote",
     "t2i_endpoint": "",
+    "t2i_use_file_service": False,
     "http_proxy": "",
     "dashboard": {
         "enable": True,
@@ -95,10 +105,11 @@ DEFAULT_CONFIG = {
     "wake_prefix": ["/"],
     "log_level": "INFO",
     "pip_install_arg": "",
-    "plugin_repo_mirror": "",
+    "pypi_index_url": "https://mirrors.aliyun.com/pypi/simple/",
     "knowledge_db": {},
     "persona": [],
     "timezone": "",
+    "callback_api_base": "",
 }
 
 
@@ -135,6 +146,7 @@ CONFIG_METADATA_2 = {
                         "enable": False,
                         "ws_reverse_host": "0.0.0.0",
                         "ws_reverse_port": 6199,
+                        "ws_reverse_token": "",
                     },
                     "gewechat(微信)": {
                         "id": "gwchat",
@@ -145,6 +157,29 @@ CONFIG_METADATA_2 = {
                         "host": "这里填写你的局域网IP或者公网服务器IP",
                         "port": 11451,
                     },
+                    "wechatpadpro(微信)": {
+                        "id": "wechatpadpro",
+                        "type": "wechatpadpro",
+                        "enable": False,
+                        "admin_key": "stay33",
+                        "host": "这里填写你的局域网IP或者公网服务器IP",
+                        "port": 8059,
+                        "wpp_active_message_poll": False,
+                        "wpp_active_message_poll_interval": 3,
+                    },
+                    "weixin_official_account(微信公众平台)": {
+                        "id": "weixin_official_account",
+                        "type": "weixin_official_account",
+                        "enable": False,
+                        "appid": "",
+                        "secret": "",
+                        "token": "",
+                        "encoding_aes_key": "",
+                        "api_base_url": "https://api.weixin.qq.com/cgi-bin/",
+                        "callback_server_host": "0.0.0.0",
+                        "port": 6194,
+                        "active_send_mode": False,
+                    },
                     "wecom(企业微信)": {
                         "id": "wecom",
                         "type": "wecom",
@@ -153,6 +188,7 @@ CONFIG_METADATA_2 = {
                         "secret": "",
                         "token": "",
                         "encoding_aes_key": "",
+                        "kf_name": "",
                         "api_base_url": "https://qyapi.weixin.qq.com/cgi-bin/",
                         "callback_server_host": "0.0.0.0",
                         "port": 6195,
@@ -181,19 +217,57 @@ CONFIG_METADATA_2 = {
                         "start_message": "Hello, I'm AstrBot!",
                         "telegram_api_base_url": "https://api.telegram.org/bot",
                         "telegram_file_base_url": "https://api.telegram.org/file/bot",
+                        "telegram_command_register": True,
+                        "telegram_command_auto_refresh": True,
+                        "telegram_command_register_interval": 300,
                     },
                 },
                 "items": {
+                    "active_send_mode": {
+                        "description": "是否换用主动发送接口",
+                        "type": "bool",
+                        "desc": "只有企业认证的公众号才能主动发送。主动发送接口的限制会少一些。",
+                    },
+                    "wpp_active_message_poll": {
+                        "description": "是否启用主动消息轮询",
+                        "type": "bool",
+                        "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",
+                        "type": "int",
+                        "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。",
+                    },
+                    "kf_name": {
+                        "description": "微信客服账号名",
+                        "type": "string",
+                        "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",
+                    },
                     "telegram_token": {
                         "description": "Bot Token",
                         "type": "string",
                         "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。",
                     },
+                    "telegram_command_register": {
+                        "description": "Telegram 命令注册",
+                        "type": "bool",
+                        "hint": "启用后，AstrBot 将会自动注册 Telegram 命令。",
+                    },
+                    "telegram_command_auto_refresh": {
+                        "description": "Telegram 命令自动刷新",
+                        "type": "bool",
+                        "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_interval": {
+                        "description": "Telegram 命令自动刷新间隔",
+                        "type": "int",
+                        "hint": "Telegram 命令自动刷新间隔，单位为秒。",
+                    },
                     "id": {
-                        "description": "ID",
+                        "description": "机器人名称",
                         "type": "string",
                         "obvious_hint": True,
-                        "hint": "ID 不能和其它的平台适配器重复，否则将发生严重冲突。",
+                        "hint": "机器人名称(ID)不能和其它的平台适配器重复。",
                     },
                     "type": {
                         "description": "适配器类型",
@@ -213,7 +287,7 @@ CONFIG_METADATA_2 = {
                     "secret": {
                         "description": "secret",
                         "type": "string",
-                        "hint": "必填项。QQ 官方机器人平台的 secret。如何获取请参考文档。",
+                        "hint": "必填项。",
                     },
                     "enable_group_c2c": {
                         "description": "启用消息列表单聊",
@@ -235,6 +309,11 @@ CONFIG_METADATA_2 = {
                         "type": "int",
                         "hint": "aiocqhttp 适配器的反向 Websocket 端口。",
                     },
+                    "ws_reverse_token": {
+                        "description": "反向 Websocket Token",
+                        "type": "string",
+                        "hint": "aiocqhttp 适配器的反向 Websocket Token。未设置则不启用 Token 验证。",
+                    },
                     "lark_bot_name": {
                         "description": "飞书机器人的名字",
                         "type": "string",
@@ -247,6 +326,9 @@ CONFIG_METADATA_2 = {
                 "description": "平台设置",
                 "type": "object",
                 "items": {
+                    "plugin_enable": {
+                        "invisible": True,  # 隐藏插件启用配置
+                    },
                     "unique_session": {
                         "description": "会话隔离",
                         "type": "bool",
@@ -282,6 +364,11 @@ CONFIG_METADATA_2 = {
                         "type": "bool",
                         "hint": "启用后，私聊消息需要唤醒前缀才会被处理，同群聊一样。",
                     },
+                    "ignore_bot_self_message": {
+                        "description": "是否忽略机器人自身的消息",
+                        "type": "bool",
+                        "hint": "某些平台如 gewechat 会将自身账号在其他 APP 端发送的消息也当做消息事件下发导致给自己发消息时唤醒机器人",
+                    },
                     "segmented_reply": {
                         "description": "分段回复",
                         "type": "object",
@@ -438,6 +525,7 @@ CONFIG_METADATA_2 = {
                     "OpenAI": {
                         "id": "openai",
                         "type": "openai_chat_completion",
+                        "provider_type": "chat_completion",
                         "enable": True,
                         "key": [],
                         "api_base": "https://api.openai.com/v1",
@@ -446,9 +534,10 @@ CONFIG_METADATA_2 = {
                             "model": "gpt-4o-mini",
                         },
                     },
-                    "Azure_OpenAI": {
+                    "Azure OpenAI": {
                         "id": "azure",
                         "type": "openai_chat_completion",
+                        "provider_type": "chat_completion",
                         "enable": True,
                         "api_version": "2024-05-01-preview",
                         "key": [],
@@ -458,9 +547,10 @@ CONFIG_METADATA_2 = {
                             "model": "gpt-4o-mini",
                         },
                     },
-                    "xAI(grok)": {
+                    "xAI": {
                         "id": "xai",
                         "type": "openai_chat_completion",
+                        "provider_type": "chat_completion",
                         "enable": True,
                         "key": [],
                         "api_base": "https://api.x.ai/v1",
@@ -469,9 +559,10 @@ CONFIG_METADATA_2 = {
                             "model": "grok-2-latest",
                         },
                     },
-                    "Anthropic(claude)": {
+                    "Anthropic": {
                         "id": "claude",
                         "type": "anthropic_chat_completion",
+                        "provider_type": "chat_completion",
                         "enable": True,
                         "key": [],
                         "api_base": "https://api.anthropic.com/v1",
@@ -484,6 +575,7 @@ CONFIG_METADATA_2 = {
                     "Ollama": {
                         "id": "ollama_default",
                         "type": "openai_chat_completion",
+                        "provider_type": "chat_completion",
                         "enable": True,
                         "key": ["ollama"],  # ollama 的 key 默认是 ollama
                         "api_base": "http://localhost:11434/v1",
@@ -491,9 +583,10 @@ CONFIG_METADATA_2 = {
                             "model": "llama3.1-8b",
                         },
                     },
-                    "LM_Studio": {
+                    "LM Studio": {
                         "id": "lm_studio",
                         "type": "openai_chat_completion",
+                        "provider_type": "chat_completion",
                         "enable": True,
                         "key": ["lmstudio"],
                         "api_base": "http://localhost:1234/v1",
@@ -504,6 +597,7 @@ CONFIG_METADATA_2 = {
                     "Gemini(OpenAI兼容)": {
                         "id": "gemini_default",
                         "type": "openai_chat_completion",
+                        "provider_type": "chat_completion",
                         "enable": True,
                         "key": [],
                         "api_base": "https://generativelanguage.googleapis.com/v1beta/openai/",
@@ -512,9 +606,10 @@ CONFIG_METADATA_2 = {
                             "model": "gemini-1.5-flash",
                         },
                     },
-                    "Gemini(googlegenai原生)": {
+                    "Gemini": {
                         "id": "gemini_default",
                         "type": "googlegenai_chat_completion",
+                        "provider_type": "chat_completion",
                         "enable": True,
                         "key": [],
                         "api_base": "https://generativelanguage.googleapis.com/",
@@ -523,16 +618,22 @@ CONFIG_METADATA_2 = {
                             "model": "gemini-2.0-flash-exp",
                         },
                         "gm_resp_image_modal": False,
+                        "gm_native_search": False,
+                        "gm_native_coderunner": False,
                         "gm_safety_settings": {
                             "harassment": "BLOCK_MEDIUM_AND_ABOVE",
                             "hate_speech": "BLOCK_MEDIUM_AND_ABOVE",
                             "sexually_explicit": "BLOCK_MEDIUM_AND_ABOVE",
                             "dangerous_content": "BLOCK_MEDIUM_AND_ABOVE",
                         },
+                        "gm_thinking_config": {
+                            "budget": 0,
+                        },
                     },
                     "DeepSeek": {
                         "id": "deepseek_default",
                         "type": "openai_chat_completion",
+                        "provider_type": "chat_completion",
                         "enable": True,
                         "key": [],
                         "api_base": "https://api.deepseek.com/v1",
@@ -541,9 +642,10 @@ CONFIG_METADATA_2 = {
                             "model": "deepseek-chat",
                         },
                     },
-                    "Zhipu(智谱)": {
+                    "智谱 AI": {
                         "id": "zhipu_default",
                         "type": "zhipu_chat_completion",
+                        "provider_type": "chat_completion",
                         "enable": True,
                         "key": [],
                         "timeout": 120,
@@ -552,9 +654,10 @@ CONFIG_METADATA_2 = {
                             "model": "glm-4-flash",
                         },
                     },
-                    "SiliconFlow(硅基流动)": {
+                    "硅基流动": {
                         "id": "siliconflow",
                         "type": "openai_chat_completion",
+                        "provider_type": "chat_completion",
                         "enable": True,
                         "key": [],
                         "timeout": 120,
@@ -563,9 +666,10 @@ CONFIG_METADATA_2 = {
                             "model": "deepseek-ai/DeepSeek-V3",
                         },
                     },
-                    "MoonShot(Kimi)": {
+                    "Kimi": {
                         "id": "moonshot",
                         "type": "openai_chat_completion",
+                        "provider_type": "chat_completion",
                         "enable": True,
                         "key": [],
                         "timeout": 120,
@@ -574,9 +678,22 @@ CONFIG_METADATA_2 = {
                             "model": "moonshot-v1-8k",
                         },
                     },
+                    "PPIO派欧云": {
+                        "id": "ppio",
+                        "type": "openai_chat_completion",
+                        "provider_type": "chat_completion",
+                        "enable": True,
+                        "key": [],
+                        "api_base": "https://api.ppinfra.com/v3/openai",
+                        "timeout": 120,
+                        "model_config": {
+                            "model": "deepseek/deepseek-r1",
+                        },
+                    },
                     "LLMTuner": {
                         "id": "llmtuner_default",
                         "type": "llm_tuner",
+                        "provider_type": "chat_completion",
                         "enable": True,
                         "base_model_path": "",
                         "adapter_model_path": "",
@@ -587,6 +704,7 @@ CONFIG_METADATA_2 = {
                     "Dify": {
                         "id": "dify_app_default",
                         "type": "dify",
+                        "provider_type": "chat_completion",
                         "enable": True,
                         "dify_api_type": "chat",
                         "dify_api_key": "",
@@ -596,9 +714,10 @@ CONFIG_METADATA_2 = {
                         "variables": {},
                         "timeout": 60,
                     },
-                    "Dashscope(阿里云百炼应用)": {
+                    "阿里云百炼应用": {
                         "id": "dashscope",
                         "type": "dashscope",
+                        "provider_type": "chat_completion",
                         "enable": True,
                         "dashscope_app_type": "agent",
                         "dashscope_api_key": "",
@@ -614,6 +733,7 @@ CONFIG_METADATA_2 = {
                     "FastGPT": {
                         "id": "fastgpt",
                         "type": "openai_chat_completion",
+                        "provider_type": "chat_completion",
                         "enable": True,
                         "key": [],
                         "api_base": "https://api.fastgpt.in/api/v1",
@@ -622,6 +742,7 @@ CONFIG_METADATA_2 = {
                     "Whisper(API)": {
                         "id": "whisper",
                         "type": "openai_whisper_api",
+                        "provider_type": "speech_to_text",
                         "enable": False,
                         "api_key": "",
                         "api_base": "",
@@ -629,22 +750,25 @@ CONFIG_METADATA_2 = {
                     },
                     "Whisper(本地加载)": {
                         "whisper_hint": "(不用修改我)",
+                        "type": "openai_whisper_selfhost",
+                        "provider_type": "speech_to_text",
                         "enable": False,
                         "id": "whisper",
-                        "type": "openai_whisper_selfhost",
                         "model": "tiny",
                     },
-                    "sensevoice(本地加载)": {
+                    "SenseVoice(本地加载)": {
                         "sensevoice_hint": "(不用修改我)",
+                        "type": "sensevoice_stt_selfhost",
+                        "provider_type": "speech_to_text",
                         "enable": False,
                         "id": "sensevoice",
-                        "type": "sensevoice_stt_selfhost",
                         "stt_model": "iic/SenseVoiceSmall",
                         "is_emotion": False,
                     },
-                    "OpenAI_TTS(API)": {
+                    "OpenAI TTS(API)": {
                         "id": "openai_tts",
                         "type": "openai_tts_api",
+                        "provider_type": "text_to_speech",
                         "enable": False,
                         "api_key": "",
                         "api_base": "",
@@ -652,43 +776,192 @@ CONFIG_METADATA_2 = {
                         "openai-tts-voice": "alloy",
                         "timeout": "20",
                     },
-                    "Edge_TTS": {
+                    "Edge TTS": {
                         "edgetts_hint": "提示：使用这个服务前需要安装有 ffmpeg，并且可以直接在终端调用 ffmpeg 指令。",
                         "id": "edge_tts",
                         "type": "edge_tts",
+                        "provider_type": "text_to_speech",
                         "enable": False,
                         "edge-tts-voice": "zh-CN-XiaoxiaoNeural",
                         "timeout": 20,
                     },
-                    "GSVI_TTS(API)": {
+                    "GSVI TTS(API)": {
                         "id": "gsvi_tts",
                         "type": "gsvi_tts_api",
+                        "provider_type": "text_to_speech",
                         "api_base": "http://127.0.0.1:5000",
                         "character": "",
                         "emotion": "default",
                         "enable": False,
                         "timeout": 20,
                     },
-                    "FishAudio_TTS(API)": {
+                    "FishAudio TTS(API)": {
                         "id": "fishaudio_tts",
                         "type": "fishaudio_tts_api",
+                        "provider_type": "text_to_speech",
                         "enable": False,
                         "api_key": "",
                         "api_base": "https://api.fish.audio/v1",
                         "fishaudio-tts-character": "可莉",
                         "timeout": "20",
                     },
-                    "阿里云百炼_TTS(API)": {
+                    "阿里云百炼 TTS(API)": {
                         "id": "dashscope_tts",
                         "type": "dashscope_tts",
+                        "provider_type": "text_to_speech",
                         "enable": False,
                         "api_key": "",
                         "model": "cosyvoice-v1",
                         "dashscope_tts_voice": "loongstella",
                         "timeout": "20",
                     },
+                    "Azure TTS": {
+                        "id": "azure_tts",
+                        "type": "azure_tts",
+                        "provider_type": "text_to_speech",
+                        "enable": True,
+                        "azure_tts_voice": "zh-CN-YunxiaNeural",
+                        "azure_tts_style": "cheerful",
+                        "azure_tts_role": "Boy",
+                        "azure_tts_rate": "1",
+                        "azure_tts_volume": "100",
+                        "azure_tts_subscription_key": "",
+                        "azure_tts_region": "eastus",
+                    },
+                    "MiniMax TTS(API)": {
+                        "id": "minimax_tts",
+                        "type": "minimax_tts_api",
+                        "provider_type": "text_to_speech",
+                        "enable": False,
+                        "api_key": "",
+                        "api_base": "https://api.minimax.chat/v1/t2a_v2",
+                        "minimax-group-id": "",
+                        "model": "speech-02-turbo",
+                        "minimax-langboost": "auto",
+                        "minimax-voice-speed": 1.0,
+                        "minimax-voice-vol": 1.0,
+                        "minimax-voice-pitch": 0,
+                        "minimax-is-timber-weight": False,
+                        "minimax-voice-id": "female-shaonv",
+                        "minimax-timber-weight": '[\n    {\n        "voice_id": "Chinese (Mandarin)_Warm_Girl",\n        "weight": 25\n    },\n    {\n        "voice_id": "Chinese (Mandarin)_BashfulGirl",\n        "weight": 50\n    }\n]',
+                        "minimax-voice-emotion": "neutral",
+                        "minimax-voice-latex": False,
+                        "minimax-voice-english-normalization": False,
+                        "timeout": 20,
+                    },
+                    "火山引擎_TTS(API)": {
+                        "id": "volcengine_tts",
+                        "type": "volcengine_tts",
+                        "provider_type": "text_to_speech",
+                        "enable": False,
+                        "api_key": "",
+                        "appid": "",
+                        "volcengine_cluster": "volcano_tts",
+                        "volcengine_voice_type": "",
+                        "volcengine_speed_ratio": 1.0,
+                        "api_base": "https://openspeech.bytedance.com/api/v1/tts",
+                        "timeout": 20,
+                    },
                 },
                 "items": {
+                    "volcengine_cluster": {
+                        "type": "string",
+                        "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": {
+                        "type": "string",
+                        "description": "火山引擎音色",
+                        "hint": "输入声音id(Voice_type)",
+                    },
+                    "volcengine_speed_ratio": {
+                        "type": "float",
+                        "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": {
+                        "type": "float",
+                        "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": {
+                        "type": "string",
+                        "description": "音色设置",
+                        "hint": "API 音色",
+                    },
+                    "azure_tts_style": {
+                        "type": "string",
+                        "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": {
+                        "type": "string",
+                        "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。",
+                        "options": [
+                            "Boy",
+                            "Girl",
+                            "YoungAdultFemale",
+                            "YoungAdultMale",
+                            "OlderAdultFemale",
+                            "OlderAdultMale",
+                            "SeniorFemale",
+                            "SeniorMale",
+                            "禁用",
+                        ],
+                    },
+                    "azure_tts_rate": {
+                        "type": "string",
+                        "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": {
+                        "type": "string",
+                        "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": {
+                        "type": "string",
+                        "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",
+                        "options": [
+                            "southafricanorth",
+                            "eastasia",
+                            "southeastasia",
+                            "australiaeast",
+                            "centralindia",
+                            "japaneast",
+                            "japanwest",
+                            "koreacentral",
+                            "canadacentral",
+                            "northeurope",
+                            "westeurope",
+                            "francecentral",
+                            "germanywestcentral",
+                            "norwayeast",
+                            "swedencentral",
+                            "switzerlandnorth",
+                            "switzerlandwest",
+                            "uksouth",
+                            "uaenorth",
+                            "brazilsouth",
+                            "qatarcentral",
+                            "centralus",
+                            "eastus",
+                            "eastus2",
+                            "northcentralus",
+                            "southcentralus",
+                            "westcentralus",
+                            "westus",
+                            "westus2",
+                            "westus3",
+                        ],
+                    },
+                    "azure_tts_subscription_key": {
+                        "type": "string",
+                        "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": "语音合成模型",
                         "type": "string",
@@ -699,6 +972,18 @@ CONFIG_METADATA_2 = {
                         "type": "bool",
                         "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",
+                        "type": "bool",
+                        "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",
+                        "obvious_hint": True,
+                    },
+                    "gm_native_coderunner": {
+                        "description": "启用原生代码执行器",
+                        "type": "bool",
+                        "hint": "启用后所有函数工具将全部失效",
+                        "obvious_hint": True,
+                    },
                     "gm_safety_settings": {
                         "description": "安全过滤器",
                         "type": "object",
@@ -750,6 +1035,109 @@ CONFIG_METADATA_2 = {
                             },
                         },
                     },
+                    "gm_thinking_config": {
+                        "description": "Gemini思考设置",
+                        "type": "object",
+                        "items": {
+                            "budget": {
+                                "description": "思考预算",
+                                "type": "int",
+                                "hint": "模型应该生成的思考Token的数量，设为0关闭思考。除gemini-2.5-flash外的模型会静默忽略此参数。",
+                            },
+                        },
+                    },
+                    "minimax-group-id": {
+                        "type": "string",
+                        "description": "用户组",
+                        "hint": "于账户管理->基本信息中可见",
+                    },
+                    "minimax-langboost": {
+                        "type": "string",
+                        "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",
+                        "options": [
+                            "Chinese",
+                            "Chinese,Yue",
+                            "English",
+                            "Arabic",
+                            "Russian",
+                            "Spanish",
+                            "French",
+                            "Portuguese",
+                            "German",
+                            "Turkish",
+                            "Dutch",
+                            "Ukrainian",
+                            "Vietnamese",
+                            "Indonesian",
+                            "Japanese",
+                            "Italian",
+                            "Korean",
+                            "Thai",
+                            "Polish",
+                            "Romanian",
+                            "Greek",
+                            "Czech",
+                            "Finnish",
+                            "Hindi",
+                            "auto",
+                        ],
+                    },
+                    "minimax-voice-speed": {
+                        "type": "float",
+                        "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": {
+                        "type": "float",
+                        "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": {
+                        "type": "int",
+                        "description": "语调",
+                        "hint": "生成声音的语调, 取值[-12, 12], 默认为0",
+                    },
+                    "minimax-is-timber-weight": {
+                        "type": "bool",
+                        "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": {
+                        "type": "string",
+                        "description": "混合音色",
+                        "editor_mode": True,
+                        "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": {
+                        "type": "string",
+                        "description": "单一音色",
+                        "hint": "单一音色编号, 详见官网文档",
+                    },
+                    "minimax-voice-emotion": {
+                        "type": "string",
+                        "description": "情绪",
+                        "hint": "控制合成语音的情绪",
+                        "options": [
+                            "happy",
+                            "sad",
+                            "angry",
+                            "fearful",
+                            "disgusted",
+                            "surprised",
+                            "neutral",
+                        ],
+                    },
+                    "minimax-voice-latex": {
+                        "type": "bool",
+                        "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": {
+                        "type": "bool",
+                        "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",
                         "type": "object",
@@ -847,7 +1235,12 @@ CONFIG_METADATA_2 = {
                         "hint": "ID 不能和其它的服务提供商重复，否则将发生严重冲突。",
                     },
                     "type": {
-                        "description": "模型提供商类型",
+                        "description": "模型提供商种类",
+                        "type": "string",
+                        "invisible": True,
+                    },
+                    "provider_type": {
+                        "description": "模型提供商能力种类",
                         "type": "string",
                         "invisible": True,
                     },
@@ -923,8 +1316,8 @@ CONFIG_METADATA_2 = {
                     "dify_api_type": {
                         "description": "Dify 应用类型",
                         "type": "string",
-                        "hint": "Dify API 类型。根据 Dify 官网，目前支持 chat, agent, workflow 三种应用类型",
-                        "options": ["chat", "agent", "workflow"],
+                        "hint": "Dify API 类型。根据 Dify 官网，目前支持 chat, chatflow, agent, workflow 三种应用类型。",
+                        "options": ["chat", "chatflow", "agent", "workflow"],
                     },
                     "dify_workflow_output_key": {
                         "description": "Dify Workflow 输出变量名",
@@ -993,6 +1386,21 @@ CONFIG_METADATA_2 = {
                         "type": "int",
                         "hint": "超出这个数量时将丢弃最旧的部分，用户和AI的一轮聊天记为 1 条。-1 表示不限制，默认为不限制。",
                     },
+                    "dequeue_context_length": {
+                        "description": "丢弃对话数量(条)",
+                        "type": "int",
+                        "hint": "超出 最多携带对话数量(条) 时，丢弃多少条记录，用户和AI的一轮聊天记为 1 条。适宜的配置，可以提高超长上下文对话 deepseek 命中缓存效果，理想情况下计费将降低到1/3以下",
+                    },
+                    "streaming_response": {
+                        "description": "启用流式回复",
+                        "type": "bool",
+                        "hint": "启用后，将会流式输出 LLM 的响应。目前仅支持 OpenAI API提供商 以及 Telegram、QQ Official 私聊 两个平台",
+                    },
+                    "streaming_segmented": {
+                        "description": "不支持流式回复的平台分段输出",
+                        "type": "bool",
+                        "hint": "启用后，若平台不支持流式回复，会分段输出。目前仅支持 aiocqhttp 和 gewechat 两个平台，不支持或无需使用流式分段输出的平台会静默忽略此选项",
+                    },
                 },
             },
             "persona": {
@@ -1067,6 +1475,17 @@ CONFIG_METADATA_2 = {
                         "type": "string",
                         "hint": "文本转语音提供商 ID。如果不填写将使用载入的第一个提供商。",
                     },
+                    "dual_output": {
+                        "description": "启用语音和文字双输出",
+                        "type": "bool",
+                        "hint": "启用后，Bot 将同时输出语音和文字消息。",
+                        "obvious_hint": True,
+                    },
+                    "use_file_service": {
+                        "description": "使用文件服务提供 TTS 语音文件",
+                        "type": "bool",
+                        "hint": "启用后，如已配置 callback_api_base ，将会使用文件服务提供TTS语音文件",
+                    },
                 },
             },
             "provider_ltm_settings": {
@@ -1179,6 +1598,12 @@ CONFIG_METADATA_2 = {
                 "obvious_hint": True,
                 "hint": "时区设置。请填写 IANA 时区名称, 如 Asia/Shanghai, 为空时使用系统默认时区。所有时区请查看: https://data.iana.org/time-zones/tzdb-2021a/zone1970.tab",
             },
+            "callback_api_base": {
+                "description": "对外可达的回调接口地址",
+                "type": "string",
+                "obvious_hint": True,
+                "hint": "外部服务可能会通过 AstrBot 生成的回调链接（如文件下载链接）访问 AstrBot 后端。由于 AstrBot 无法自动判断部署环境中对外可达的主机地址（host），因此需要通过此配置项显式指定 “外部服务如何访问 AstrBot” 的地址。如 http://localhost:6185，https://example.com 等。",
+            },
             "log_level": {
                 "description": "控制台日志级别",
                 "type": "string",
@@ -1196,21 +1621,20 @@ CONFIG_METADATA_2 = {
                 "type": "string",
                 "hint": "当 t2i_strategy 为 remote 时生效。为空时使用 AstrBot API 服务",
             },
+            "t2i_use_file_service": {
+                "description": "本地文本转图像使用文件服务提供文件",
+                "type": "bool",
+                "hint": "当 t2i_strategy 为 local 并且配置 callback_api_base 时生效。是否使用文件服务提供文件。",
+            },
             "pip_install_arg": {
                 "description": "pip 安装参数",
                 "type": "string",
                 "hint": "安装插件依赖时，会使用 Python 的 pip 工具。这里可以填写额外的参数，如 `--break-system-package` 等。",
             },
-            "plugin_repo_mirror": {
-                "description": "插件仓库镜像",
+            "pypi_index_url": {
+                "description": "PyPI 软件仓库地址",
                 "type": "string",
-                "hint": "已废弃，请使用管理面板->设置页的代理地址选择",
-                "obvious_hint": True,
-                "options": [
-                    "default",
-                    "https://ghp.ci/",
-                    "https://github-mirror.us.kg/",
-                ],
+                "hint": "安装 Python 依赖时请求的 PyPI 软件仓库地址。默认为 https://mirrors.aliyun.com/pypi/simple/",
             },
         },
     },

astrbot/core/conversation_mgr.py

@@ -175,7 +175,15 @@ class ConversationManager:
             if record["role"] == "user":
                 temp_contexts.append(f"User: {record['content']}")
             elif record["role"] == "assistant":
-                temp_contexts.append(f"Assistant: {record['content']}")
+                if "content" in record and record["content"]:
+                    temp_contexts.append(f"Assistant: {record['content']}")
+                elif "tool_calls" in record:
+                    tool_calls_str = json.dumps(
+                        record["tool_calls"], ensure_ascii=False
+                    )
+                    temp_contexts.append(f"Assistant: [函数调用] {tool_calls_str}")
+                else:
+                    temp_contexts.append("Assistant: [未知的内容]")
                 contexts.insert(0, temp_contexts)
                 temp_contexts = []
 

astrbot/core/core_lifecycle.py

@@ -1,6 +1,6 @@
 """
 Astrbot 核心生命周期管理类, 负责管理 AstrBot 的启动、停止、重启等操作。
-该类负责初始化各个组件, 包括 ProviderManager、PlatformManager、KnowledgeDBManager、ConversationManager、PluginManager、PipelineScheduler、EventBus等。
+该类负责初始化各个组件, 包括 ProviderManager、PlatformManager、ConversationManager、PluginManager、PipelineScheduler、EventBus等。
 该类还负责加载和执行插件, 以及处理事件总线的分发。
 
 工作流程:
@@ -28,7 +28,6 @@ from astrbot.core.db import BaseDatabase
 from astrbot.core.updator import AstrBotUpdator
 from astrbot.core import logger
 from astrbot.core.config.default import VERSION
-from astrbot.core.rag.knowledge_db_mgr import KnowledgeDBManager
 from astrbot.core.conversation_mgr import ConversationManager
 from astrbot.core.star.star_handler import star_handlers_registry, EventType
 from astrbot.core.star.star_handler import star_map
@@ -37,7 +36,7 @@ from astrbot.core.star.star_handler import star_map
 class AstrBotCoreLifecycle:
     """
     AstrBot 核心生命周期管理类, 负责管理 AstrBot 的启动、停止、重启等操作。
-    该类负责初始化各个组件, 包括 ProviderManager、PlatformManager、KnowledgeDBManager、ConversationManager、PluginManager、PipelineScheduler、
+    该类负责初始化各个组件, 包括 ProviderManager、PlatformManager、ConversationManager、PluginManager、PipelineScheduler、
     EventBus 等。
     该类还负责加载和执行插件, 以及处理事件总线的分发。
     """
@@ -54,7 +53,7 @@ class AstrBotCoreLifecycle:
 
     async def initialize(self):
         """
-        初始化 AstrBot 核心生命周期管理类, 负责初始化各个组件, 包括 ProviderManager、PlatformManager、KnowledgeDBManager、ConversationManager、PluginManager、PipelineScheduler、EventBus、AstrBotUpdator等。
+        初始化 AstrBot 核心生命周期管理类, 负责初始化各个组件, 包括 ProviderManager、PlatformManager、ConversationManager、PluginManager、PipelineScheduler、EventBus、AstrBotUpdator等。
         """
 
         # 初始化日志代理
@@ -73,9 +72,6 @@ class AstrBotCoreLifecycle:
         # 初始化平台管理器
         self.platform_manager = PlatformManager(self.astrbot_config, self.event_queue)
 
-        # 初始化知识库管理器
-        self.knowledge_db_manager = KnowledgeDBManager(self.astrbot_config)
-
         # 初始化对话管理器
         self.conversation_manager = ConversationManager(self.db)
 
@@ -87,7 +83,6 @@ class AstrBotCoreLifecycle:
             self.provider_manager,
             self.platform_manager,
             self.conversation_manager,
-            self.knowledge_db_manager,
         )
 
         # 初始化插件管理器
@@ -106,7 +101,7 @@ class AstrBotCoreLifecycle:
         await self.pipeline_scheduler.initialize()
 
         # 初始化更新器
-        self.astrbot_updator = AstrBotUpdator(self.astrbot_config["plugin_repo_mirror"])
+        self.astrbot_updator = AstrBotUpdator()
 
         # 初始化事件总线
         self.event_bus = EventBus(self.event_queue, self.pipeline_scheduler)

astrbot/core/db/plugin/sqlite_impl.py

@@ -1,112 +0,0 @@
-import json
-import aiosqlite
-import os
-from typing import Any
-from .plugin_storage import PluginStorage
-
-DBPATH = "data/plugin_data/sqlite/plugin_data.db"
-
-
-class SQLitePluginStorage(PluginStorage):
-    """插件数据的 SQLite 存储实现类。
-
-    该类提供异步方式将插件数据存储到 SQLite 数据库中，支持数据的增删改查操作。
-    所有数据以 (plugin, key) 作为复合主键进行索引。
-    """
-
-    _instance = None  # Standalone instance of the class
-    _db_conn = None
-    db_path = None
-
-    def __new__(cls):
-        """
-        创建或获取 SQLitePluginStorage 的单例实例。
-        如果实例已存在，则返回现有实例；否则创建一个新实例。
-        数据在 `data/plugin_data/sqlite/plugin_data.db` 下。
-        """
-        os.makedirs(os.path.dirname(DBPATH), exist_ok=True)
-        if cls._instance is None:
-            cls._instance = super(SQLitePluginStorage, cls).__new__(cls)
-            cls._instance.db_path = DBPATH
-        return cls._instance
-
-    async def _init_db(self):
-        """初始化数据库连接（只执行一次）"""
-        if SQLitePluginStorage._db_conn is None:
-            SQLitePluginStorage._db_conn = await aiosqlite.connect(self.db_path)
-            await self._setup_db()
-
-    async def _setup_db(self):
-        """
-        异步初始化数据库。
-
-        创建插件数据表，如果表不存在则创建，表结构包含 plugin、key 和 value 字段，
-        其中 plugin 和 key 组合作为主键。
-        """
-        await self._db_conn.execute("""
-            CREATE TABLE IF NOT EXISTS plugin_data (
-                plugin TEXT,
-                key TEXT,
-                value TEXT,
-                PRIMARY KEY (plugin, key)
-            )
-        """)
-        await self._db_conn.commit()
-
-    async def set(self, plugin: str, key: str, value: Any):
-        """
-        异步存储数据。
-
-        将指定插件的键值对存入数据库，如果键已存在则更新值。
-        值会被序列化为 JSON 字符串后存储。
-
-        Args:
-            plugin: 插件标识符
-            key: 数据键名
-            value: 要存储的数据值（任意类型，将被 JSON 序列化）
-        """
-        await self._init_db()
-        await self._db_conn.execute(
-            "INSERT INTO plugin_data (plugin, key, value) VALUES (?, ?, ?) "
-            "ON CONFLICT(plugin, key) DO UPDATE SET value = excluded.value",
-            (plugin, key, json.dumps(value)),
-        )
-        await self._db_conn.commit()
-
-    async def get(self, plugin: str, key: str) -> Any:
-        """
-        异步获取数据。
-
-        从数据库中获取指定插件和键名对应的值，
-        返回的值会从 JSON 字符串反序列化为原始数据类型。
-
-        Args:
-            plugin: 插件标识符
-            key: 数据键名
-
-        Returns:
-            Any: 存储的数据值，如果未找到则返回 None
-        """
-        await self._init_db()
-        async with self._db_conn.execute(
-            "SELECT value FROM plugin_data WHERE plugin = ? AND key = ?",
-            (plugin, key),
-        ) as cursor:
-            row = await cursor.fetchone()
-            return json.loads(row[0]) if row else None
-
-    async def delete(self, plugin: str, key: str):
-        """
-        异步删除数据。
-
-        从数据库中删除指定插件和键名对应的数据项。
-
-        Args:
-            plugin: 插件标识符
-            key: 要删除的数据键名
-        """
-        await self._init_db()
-        await self._db_conn.execute(
-            "DELETE FROM plugin_data WHERE plugin = ? AND key = ?", (plugin, key)
-        )
-        await self._db_conn.commit()

astrbot/core/db/vec_db/base.py

@@ -0,0 +1,46 @@
+import abc
+from dataclasses import dataclass
+
+
+@dataclass
+class Result:
+    similarity: float
+    data: dict
+
+
+class BaseVecDB:
+    async def initialize(self):
+        """
+        初始化向量数据库
+        """
+        pass
+
+    @abc.abstractmethod
+    async def insert(self, content: str, metadata: dict = None, id: str = None) -> int:
+        """
+        插入一条文本和其对应向量，自动生成 ID 并保持一致性。
+        """
+        ...
+
+    @abc.abstractmethod
+    async def retrieve(self, query: str, top_k: int = 5) -> list[Result]:
+        """
+        搜索最相似的文档。
+        Args:
+            query (str): 查询文本
+            top_k (int): 返回的最相似文档的数量
+        Returns:
+            List[Result]: 查询结果
+        """
+        ...
+
+    @abc.abstractmethod
+    async def delete(self, doc_id: str) -> bool:
+        """
+        删除指定文档。
+        Args:
+            doc_id (str): 要删除的文档 ID
+        Returns:
+            bool: 删除是否成功
+        """
+        ...

astrbot/core/db/vec_db/faiss_impl/__init__.py

@@ -0,0 +1,3 @@
+from .vec_db import FaissVecDB
+
+__all__ = ["FaissVecDB"]

astrbot/core/db/vec_db/faiss_impl/document_storage.py

@@ -0,0 +1,121 @@
+import aiosqlite
+import os
+
+
+class DocumentStorage:
+    def __init__(self, db_path: str):
+        self.db_path = db_path
+        self.connection = None
+        self.sqlite_init_path = os.path.join(
+            os.path.dirname(__file__), "sqlite_init.sql"
+        )
+
+    async def initialize(self):
+        """Initialize the SQLite database and create the documents table if it doesn't exist."""
+        if not os.path.exists(self.db_path):
+            await self.connect()
+            async with self.connection.cursor() as cursor:
+                with open(self.sqlite_init_path, "r", encoding="utf-8") as f:
+                    sql_script = f.read()
+                await cursor.executescript(sql_script)
+            await self.connection.commit()
+        else:
+            await self.connect()
+
+    async def connect(self):
+        """Connect to the SQLite database."""
+        self.connection = await aiosqlite.connect(self.db_path)
+
+    async def get_documents(self, metadata_filters: dict, ids: list = None):
+        """Retrieve documents by metadata filters and ids.
+
+        Args:
+            metadata_filters (dict): The metadata filters to apply.
+
+        Returns:
+            list: The list of document IDs(primary key, not doc_id) that match the filters.
+        """
+        # metadata filter -> SQL WHERE clause
+        where_clauses = []
+        values = []
+        for key, val in metadata_filters.items():
+            where_clauses.append(f"json_extract(metadata, '$.{key}') = ?")
+            values.append(val)
+        if ids is not None and len(ids) > 0:
+            ids = [str(i) for i in ids if i != -1]
+            where_clauses.append("id IN ({})".format(",".join("?" * len(ids))))
+            values.extend(ids)
+        where_sql = " AND ".join(where_clauses) or "1=1"
+
+        result = []
+        async with self.connection.cursor() as cursor:
+            sql = "SELECT * FROM documents WHERE " + where_sql
+            await cursor.execute(sql, values)
+            for row in await cursor.fetchall():
+                result.append(await self.tuple_to_dict(row))
+        return result
+
+    async def get_document_by_doc_id(self, doc_id: str):
+        """Retrieve a document by its doc_id.
+
+        Args:
+            doc_id (str): The doc_id of the document to retrieve.
+
+        Returns:
+            dict: The document data.
+        """
+        async with self.connection.cursor() as cursor:
+            await cursor.execute("SELECT * FROM documents WHERE doc_id = ?", (doc_id,))
+            row = await cursor.fetchone()
+            if row:
+                return await self.tuple_to_dict(row)
+            else:
+                return None
+
+    async def update_document_by_doc_id(self, doc_id: str, new_text: str):
+        """Retrieve a document by its doc_id.
+
+        Args:
+            doc_id (str): The doc_id.
+            new_text (str): The new text to update the document with.
+        """
+        async with self.connection.cursor() as cursor:
+            await cursor.execute(
+                "UPDATE documents SET text = ? WHERE doc_id = ?", (new_text, doc_id)
+            )
+            await self.connection.commit()
+
+    async def get_user_ids(self) -> list[str]:
+        """Retrieve all user IDs from the documents table.
+
+        Returns:
+            list: A list of user IDs.
+        """
+        async with self.connection.cursor() as cursor:
+            await cursor.execute("SELECT DISTINCT user_id FROM documents")
+            rows = await cursor.fetchall()
+            return [row[0] for row in rows]
+
+    async def tuple_to_dict(self, row):
+        """Convert a tuple to a dictionary.
+
+        Args:
+            row (tuple): The row to convert.
+
+        Returns:
+            dict: The converted dictionary.
+        """
+        return {
+            "id": row[0],
+            "doc_id": row[1],
+            "text": row[2],
+            "metadata": row[3],
+            "created_at": row[4],
+            "updated_at": row[5],
+        }
+
+    async def close(self):
+        """Close the connection to the SQLite database."""
+        if self.connection:
+            await self.connection.close()
+            self.connection = None

astrbot/core/db/vec_db/faiss_impl/embedding_storage.py

@@ -0,0 +1,59 @@
+try:
+    import faiss
+except ModuleNotFoundError:
+    raise ImportError(
+        "faiss 未安装。请使用 'pip install faiss-cpu' 或 'pip install faiss-gpu' 安装。"
+    )
+import os
+import numpy as np
+
+
+class EmbeddingStorage:
+    def __init__(self, dimension: int, path: str = None):
+        self.dimension = dimension
+        self.path = path
+        self.index = None
+        if path and os.path.exists(path):
+            self.index = faiss.read_index(path)
+        else:
+            base_index = faiss.IndexFlatL2(dimension)
+            self.index = faiss.IndexIDMap(base_index)
+        self.storage = {}
+
+    async def insert(self, vector: np.ndarray, id: int):
+        """插入向量
+
+        Args:
+            vector (np.ndarray): 要插入的向量
+            id (int): 向量的ID
+        Raises:
+            ValueError: 如果向量的维度与存储的维度不匹配
+        """
+        if vector.shape[0] != self.dimention:
+            raise ValueError(
+                f"向量维度不匹配, 期望: {self.dimention}, 实际: {vector.shape[0]}"
+            )
+        self.index.add_with_ids(vector.reshape(1, -1), np.array([id]))
+        self.storage[id] = vector
+        await self.save_index()
+
+    async def search(self, vector: np.ndarray, k: int) -> tuple:
+        """搜索最相似的向量
+
+        Args:
+            vector (np.ndarray): 查询向量
+            k (int): 返回的最相似向量的数量
+        Returns:
+            tuple: (距离, 索引)
+        """
+        faiss.normalize_L2(vector)
+        distances, indices = self.index.search(vector, k)
+        return distances, indices
+
+    async def save_index(self):
+        """保存索引
+
+        Args:
+            path (str): 保存索引的路径
+        """
+        faiss.write_index(self.index, self.path)

astrbot/core/db/vec_db/faiss_impl/sqlite_init.sql

@@ -0,0 +1,17 @@
+-- 创建文档存储表，包含 faiss 中文档的 id，文档文本，create_at，updated_at
+CREATE TABLE documents (
+    id INTEGER PRIMARY KEY AUTOINCREMENT,
+    doc_id TEXT NOT NULL,
+    text TEXT NOT NULL,
+    metadata TEXT,
+    created_at DATETIME DEFAULT CURRENT_TIMESTAMP,
+    updated_at DATETIME DEFAULT CURRENT_TIMESTAMP
+);
+
+ALTER TABLE documents
+ADD COLUMN group_id TEXT GENERATED ALWAYS AS (json_extract(metadata, '$.group_id')) STORED;
+ALTER TABLE documents
+ADD COLUMN user_id TEXT GENERATED ALWAYS AS (json_extract(metadata, '$.user_id')) STORED;
+
+CREATE INDEX idx_documents_user_id ON documents(user_id);
+CREATE INDEX idx_documents_group_id ON documents(group_id);

astrbot/core/db/vec_db/faiss_impl/vec_db.py

@@ -0,0 +1,123 @@
+import uuid
+import json
+import numpy as np
+from .document_storage import DocumentStorage
+from .embedding_storage import EmbeddingStorage
+from ..base import Result, BaseVecDB
+from astrbot.core.provider.provider import EmbeddingProvider
+
+
+class FaissVecDB(BaseVecDB):
+    """
+    A class to represent a vector database.
+    """
+
+    def __init__(
+        self,
+        doc_store_path: str,
+        index_store_path: str,
+        embedding_provider: EmbeddingProvider,
+    ):
+        self.doc_store_path = doc_store_path
+        self.index_store_path = index_store_path
+        self.embedding_provider = embedding_provider
+        self.document_storage = DocumentStorage(doc_store_path)
+        self.embedding_storage = EmbeddingStorage(
+            embedding_provider.get_dim(), index_store_path
+        )
+        self.embedding_provider = embedding_provider
+
+    async def initialize(self):
+        await self.document_storage.initialize()
+
+    async def insert(
+        self,
+        content: str,
+        metadata: dict = None,
+        id: str = None,
+    ) -> int:
+        """
+        插入一条文本和其对应向量，自动生成 ID 并保持一致性。
+        """
+        metadata = metadata or {}
+        str_id = id or str(uuid.uuid4())  # 使用 UUID 作为原始 ID
+
+        # 获取向量
+        vector = await self.embedding_provider.get_embedding(content)
+        vector = np.array(vector, dtype=np.float32)
+        async with self.document_storage.connection.cursor() as cursor:
+            await cursor.execute(
+                "INSERT INTO documents (doc_id, text, metadata) VALUES (?, ?, ?)",
+                (str_id, content, json.dumps(metadata)),
+            )
+            await self.document_storage.connection.commit()
+            result = await self.document_storage.get_document_by_doc_id(str_id)
+            int_id = result["id"]
+
+        # 插入向量到 FAISS
+        await self.embedding_storage.insert(vector, int_id)
+        return int_id
+
+    async def retrieve(
+        self, query: str, k: int = 5, fetch_k: int = 20, metadata_filters: dict = None
+    ) -> list[Result]:
+        """
+        搜索最相似的文档。
+
+        Args:
+            query (str): 查询文本
+            k (int): 返回的最相似文档的数量
+            fetch_k (int): 在根据 metadata 过滤前从 FAISS 中获取的数量
+            metadata_filters (dict): 元数据过滤器
+
+        Returns:
+            List[Result]: 查询结果
+        """
+        embedding = await self.embedding_provider.get_embedding(query)
+        scores, indices = await self.embedding_storage.search(
+            vector=np.array([embedding]).astype("float32"),
+            k=fetch_k if metadata_filters else k,
+        )
+        # TODO: rerank
+        if len(indices[0]) == 0 or indices[0][0] == -1:
+            return []
+        # normalize scores
+        scores[0] = 1.0 - (scores[0] / 2.0)
+        # NOTE: maybe the size is less than k.
+        fetched_docs = await self.document_storage.get_documents(
+            metadata_filters=metadata_filters or {}, ids=indices[0]
+        )
+        if not fetched_docs:
+            return []
+        result_docs = []
+
+        idx_pos = {fetch_doc["id"]: idx for idx, fetch_doc in enumerate(fetched_docs)}
+        for i, indice_idx in enumerate(indices[0]):
+            pos = idx_pos.get(indice_idx)
+            if pos is None:
+                continue
+            fetch_doc = fetched_docs[pos]
+            score = scores[0][i]
+            result_docs.append(Result(similarity=float(score), data=fetch_doc))
+        return result_docs[:k]
+
+    async def delete(self, doc_id: int):
+        """
+        删除一条文档
+        """
+        await self.document_storage.connection.execute(
+            "DELETE FROM documents WHERE doc_id = ?", (doc_id,)
+        )
+        await self.document_storage.connection.commit()
+
+    async def close(self):
+        await self.document_storage.close()
+
+    async def count_documents(self) -> int:
+        """
+        计算文档数量
+        """
+        async with self.document_storage.connection.cursor() as cursor:
+            await cursor.execute("SELECT COUNT(*) FROM documents")
+            count = await cursor.fetchone()
+            return count[0] if count else 0

astrbot/core/file_token_service.py

@@ -0,0 +1,68 @@
+import asyncio
+import os
+import uuid
+import time
+
+
+class FileTokenService:
+    """维护一个简单的基于令牌的文件下载服务，支持超时和懒清除。"""
+
+    def __init__(self, default_timeout: float = 300):
+        self.lock = asyncio.Lock()
+        self.staged_files = {}  # token: (file_path, expire_time)
+        self.default_timeout = default_timeout
+
+    async def _cleanup_expired_tokens(self):
+        """清理过期的令牌"""
+        now = time.time()
+        expired_tokens = [token for token, (_, expire) in self.staged_files.items() if expire < now]
+        for token in expired_tokens:
+            self.staged_files.pop(token, None)
+
+    async def register_file(self, file_path: str, timeout: float = None) -> str:
+        """向令牌服务注册一个文件。
+
+        Args:
+            file_path(str): 文件路径
+            timeout(float): 超时时间，单位秒（可选）
+
+        Returns:
+            str: 一个单次令牌
+
+        Raises:
+            FileNotFoundError: 当路径不存在时抛出
+        """
+        async with self.lock:
+            await self._cleanup_expired_tokens()
+
+            if not os.path.exists(file_path):
+                raise FileNotFoundError(f"文件不存在: {file_path}")
+
+            file_token = str(uuid.uuid4())
+            expire_time = time.time() + (timeout if timeout is not None else self.default_timeout)
+            self.staged_files[file_token] = (file_path, expire_time)
+            return file_token
+
+    async def handle_file(self, file_token: str) -> str:
+        """根据令牌获取文件路径，使用后令牌失效。
+
+        Args:
+            file_token(str): 注册时返回的令牌
+
+        Returns:
+            str: 文件路径
+
+        Raises:
+            KeyError: 当令牌不存在或已过期时抛出
+            FileNotFoundError: 当文件本身已被删除时抛出
+        """
+        async with self.lock:
+            await self._cleanup_expired_tokens()
+
+            if file_token not in self.staged_files:
+                raise KeyError(f"无效或过期的文件 token: {file_token}")
+
+            file_path, _ = self.staged_files.pop(file_token)
+            if not os.path.exists(file_path):
+                raise FileNotFoundError(f"文件不存在: {file_path}")
+            return file_path

astrbot/core/initial_loader.py

@@ -26,13 +26,14 @@ class InitialLoader:
     async def start(self):
         core_lifecycle = AstrBotCoreLifecycle(self.log_broker, self.db)
 
-        core_task = []
         try:
             await core_lifecycle.initialize()
-            core_task = core_lifecycle.start()
         except Exception as e:
             logger.critical(traceback.format_exc())
             logger.critical(f"😭 初始化 AstrBot 失败：{e} !!!")
+            return
+
+        core_task = core_lifecycle.start()
 
         self.dashboard_server = AstrBotDashboard(
             core_lifecycle, self.db, core_lifecycle.dashboard_shutdown_event

astrbot/core/log.py

@@ -25,6 +25,7 @@ import logging
 import colorlog
 import asyncio
 import os
+import sys
 from collections import deque
 from asyncio import Queue
 from typing import List
@@ -141,11 +142,13 @@ class LogQueueHandler(logging.Handler):
             record (logging.LogRecord): 日志记录对象, 包含日志信息
         """
         log_entry = self.format(record)
-        self.log_broker.publish({
-            "level": record.levelname,
-            "time": record.asctime,
-            "data": log_entry,
-        })
+        self.log_broker.publish(
+            {
+                "level": record.levelname,
+                "time": record.asctime,
+                "data": log_entry,
+            }
+        )
 
 
 class LogManager:
@@ -169,7 +172,9 @@ class LogManager:
         if logger.hasHandlers():
             return logger
         # 如果logger没有处理器
-        console_handler = logging.StreamHandler()  # 创建一个StreamHandler用于控制台输出
+        console_handler = logging.StreamHandler(
+            sys.stdout
+        )  # 创建一个StreamHandler用于控制台输出
         console_handler.setLevel(
             logging.DEBUG
         )  # 将日志级别设置为DEBUG(最低级别, 显示所有日志), *如果插件没有设置级别, 默认为DEBUG

astrbot/core/message/components.py

@@ -22,14 +22,19 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 SOFTWARE.
 """
 
+import asyncio
 import base64
 import json
 import os
-import uuid
 import typing as T
+import uuid
 from enum import Enum
+
 from pydantic.v1 import BaseModel
-from astrbot.core.utils.io import download_image_by_url, file_to_base64
+
+from astrbot.core import astrbot_config, file_token_service, logger
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
+from astrbot.core.utils.io import download_file, download_image_by_url, file_to_base64
 
 
 class ComponentType(Enum):
@@ -97,6 +102,10 @@ class BaseMessageComponent(BaseModel):
             data[k] = v
         return {"type": self.type.lower(), "data": data}
 
+    async def to_dict(self) -> dict:
+        # 默认情况下，回退到旧的同步 toDict()
+        return self.toDict()
+
 
 class Plain(BaseMessageComponent):
     type: ComponentType = "Plain"
@@ -113,6 +122,9 @@ class Plain(BaseMessageComponent):
             self.text.replace("&", "&").replace("[", "[").replace("]", "]")
         )
 
+    def toDict(self):
+        return {"type": "text", "data": {"text": self.text.strip()}}
+
 
 class Face(BaseMessageComponent):
     type: ComponentType = "Face"
@@ -165,7 +177,8 @@ class Record(BaseMessageComponent):
         elif self.file and self.file.startswith("base64://"):
             bs64_data = self.file.removeprefix("base64://")
             image_bytes = base64.b64decode(bs64_data)
-            file_path = f"data/temp/{uuid.uuid4()}.jpg"
+            temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+            file_path = os.path.join(temp_dir, f"{uuid.uuid4()}.jpg")
             with open(file_path, "wb") as f:
                 f.write(image_bytes)
             return os.path.abspath(file_path)
@@ -193,8 +206,32 @@ class Record(BaseMessageComponent):
             bs64_data = file_to_base64(self.file)
         else:
             raise Exception(f"not a valid file: {self.file}")
+        bs64_data = bs64_data.removeprefix("base64://")
         return bs64_data
 
+    async def register_to_file_service(self) -> str:
+        """
+        将语音注册到文件服务。
+
+        Returns:
+            str: 注册后的URL
+
+        Raises:
+            Exception: 如果未配置 callback_api_base
+        """
+        callback_host = astrbot_config.get("callback_api_base")
+
+        if not callback_host:
+            raise Exception("未配置 callback_api_base，文件服务不可用")
+
+        file_path = await self.convert_to_file_path()
+
+        token = await file_token_service.register_file(file_path)
+
+        logger.debug(f"已注册：{callback_host}/api/file/{token}")
+
+        return f"{callback_host}/api/file/{token}"
+
 
 class Video(BaseMessageComponent):
     type: ComponentType = "Video"
@@ -205,9 +242,6 @@ class Video(BaseMessageComponent):
     path: T.Optional[str] = ""
 
     def __init__(self, file: str, **_):
-        # for k in _.keys():
-        #     if k == "c" and _[k] not in [2, 3]:
-        #         logger.warn(f"Protocol: {k}={_[k]} doesn't match values")
         super().__init__(file=file, **_)
 
     @staticmethod
@@ -220,6 +254,70 @@ class Video(BaseMessageComponent):
             return Video(file=url, **_)
         raise Exception("not a valid url")
 
+    async def convert_to_file_path(self) -> str:
+        """将这个视频统一转换为本地文件路径。这个方法避免了手动判断视频数据类型，直接返回视频数据的本地路径（如果是网络 URL，则会自动进行下载）。
+
+        Returns:
+            str: 视频的本地路径，以绝对路径表示。
+        """
+        url = self.file
+        if url and url.startswith("file:///"):
+            return url[8:]
+        elif url and url.startswith("http"):
+            download_dir = os.path.join(get_astrbot_data_path(), "temp")
+            video_file_path = os.path.join(download_dir, f"{uuid.uuid4().hex}")
+            await download_file(url, video_file_path)
+            if os.path.exists(video_file_path):
+                return os.path.abspath(video_file_path)
+            else:
+                raise Exception(f"download failed: {url}")
+        elif os.path.exists(url):
+            return os.path.abspath(url)
+        else:
+            raise Exception(f"not a valid file: {url}")
+
+    async def register_to_file_service(self):
+        """
+        将视频注册到文件服务。
+
+        Returns:
+            str: 注册后的URL
+
+        Raises:
+            Exception: 如果未配置 callback_api_base
+        """
+        callback_host = astrbot_config.get("callback_api_base")
+
+        if not callback_host:
+            raise Exception("未配置 callback_api_base，文件服务不可用")
+
+        file_path = await self.convert_to_file_path()
+
+        token = await file_token_service.register_file(file_path)
+
+        logger.debug(f"已注册：{callback_host}/api/file/{token}")
+
+        return f"{callback_host}/api/file/{token}"
+
+    async def to_dict(self):
+        """需要和 toDict 区分开，toDict 是同步方法"""
+        url_or_path = self.file
+        if url_or_path.startswith("http"):
+            payload_file = url_or_path
+        elif callback_host := astrbot_config.get("callback_api_base"):
+            callback_host = str(callback_host).removesuffix("/")
+            token = await file_token_service.register_file(url_or_path)
+            payload_file = f"{callback_host}/api/file/{token}"
+            logger.debug(f"Generated video file callback link: {payload_file}")
+        else:
+            payload_file = url_or_path
+        return {
+            "type": "video",
+            "data": {
+                "file": payload_file,
+            },
+        }
+
 
 class At(BaseMessageComponent):
     type: ComponentType = "At"
@@ -229,6 +327,12 @@ class At(BaseMessageComponent):
     def __init__(self, **_):
         super().__init__(**_)
 
+    def toDict(self):
+        return {
+            "type": "at",
+            "data": {"qq": str(self.qq)},
+        }
+
 
 class AtAll(At):
     qq: str = "all"
@@ -368,7 +472,8 @@ class Image(BaseMessageComponent):
         elif url and url.startswith("base64://"):
             bs64_data = url.removeprefix("base64://")
             image_bytes = base64.b64decode(bs64_data)
-            image_file_path = f"data/temp/{uuid.uuid4()}.jpg"
+            temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+            image_file_path = os.path.join(temp_dir, f"{uuid.uuid4()}.jpg")
             with open(image_file_path, "wb") as f:
                 f.write(image_bytes)
             return os.path.abspath(image_file_path)
@@ -397,25 +502,47 @@ class Image(BaseMessageComponent):
             bs64_data = file_to_base64(url)
         else:
             raise Exception(f"not a valid file: {url}")
+        bs64_data = bs64_data.removeprefix("base64://")
         return bs64_data
 
+    async def register_to_file_service(self) -> str:
+        """
+        将图片注册到文件服务。
+
+        Returns:
+            str: 注册后的URL
+
+        Raises:
+            Exception: 如果未配置 callback_api_base
+        """
+        callback_host = astrbot_config.get("callback_api_base")
+
+        if not callback_host:
+            raise Exception("未配置 callback_api_base，文件服务不可用")
+
+        file_path = await self.convert_to_file_path()
+
+        token = await file_token_service.register_file(file_path)
+
+        logger.debug(f"已注册：{callback_host}/api/file/{token}")
+
+        return f"{callback_host}/api/file/{token}"
+
 
 class Reply(BaseMessageComponent):
     type: ComponentType = "Reply"
     id: T.Union[str, int]
     """所引用的消息 ID"""
     chain: T.Optional[T.List["BaseMessageComponent"]] = []
-    """引用的消息段列表"""
+    """被引用的消息段列表"""
     sender_id: T.Optional[int] | T.Optional[str] = 0
-    """引用的消息发送者 ID"""
+    """被引用的消息对应的发送者的 ID"""
     sender_nickname: T.Optional[str] = ""
-    """引用的消息发送者昵称"""
+    """被引用的消息对应的发送者的昵称"""
     time: T.Optional[int] = 0
-    """引用的消息发送时间"""
+    """被引用的消息发送时间"""
     message_str: T.Optional[str] = ""
-    """解析后的纯文本消息字符串"""
-    sender_str: T.Optional[str] = ""
-    """被引用的消息纯文本"""
+    """被引用的消息解析后的纯文本消息字符串"""
 
     text: T.Optional[str] = ""
     """deprecated"""
@@ -460,28 +587,48 @@ class Node(BaseMessageComponent):
     type: ComponentType = "Node"
     id: T.Optional[int] = 0  # 忽略
     name: T.Optional[str] = ""  # qq昵称
-    uin: T.Optional[int] = 0  # qq号
-    content: T.Optional[T.Union[str, list, dict]] = ""  # 子消息段列表
+    uin: T.Optional[str] = "0"  # qq号
+    content: T.Optional[list[BaseMessageComponent]] = []
     seq: T.Optional[T.Union[str, list]] = ""  # 忽略
-    time: T.Optional[int] = 0
+    time: T.Optional[int] = 0  # 忽略
 
-    def __init__(self, content: T.Union[str, list, dict, "Node", T.List["Node"]], **_):
-        if isinstance(content, list):
-            _content = None
-            if all(isinstance(item, Node) for item in content):
-                _content = [node.toDict() for node in content]
-            else:
-                _content = ""
-                for chain in content:
-                    _content += chain.toString()
-            content = _content
-        elif isinstance(content, Node):
-            content = content.toDict()
+    def __init__(self, content: list[BaseMessageComponent], **_):
+        if isinstance(content, Node):
+            # back
+            content = [content]
         super().__init__(content=content, **_)
 
-    def toString(self):
-        # logger.warn("Protocol: node doesn't support stringify")
-        return ""
+    async def to_dict(self):
+        data_content = []
+        for comp in self.content:
+            if isinstance(comp, (Image, Record)):
+                # For Image and Record segments, we convert them to base64
+                bs64 = await comp.convert_to_base64()
+                data_content.append(
+                    {
+                        "type": comp.type.lower(),
+                        "data": {"file": f"base64://{bs64}"},
+                    }
+                )
+            elif isinstance(comp, File):
+                # For File segments, we need to handle the file differently
+                d = await comp.to_dict()
+                data_content.append(d)
+            elif isinstance(comp, (Node, Nodes)):
+                # For Node segments, we recursively convert them to dict
+                d = await comp.to_dict()
+                data_content.append(d)
+            else:
+                d = comp.toDict()
+                data_content.append(d)
+        return {
+            "type": "node",
+            "data": {
+                "user_id": str(self.uin),
+                "nickname": self.name,
+                "content": data_content,
+            },
+        }
 
 
 class Nodes(BaseMessageComponent):
@@ -492,7 +639,22 @@ class Nodes(BaseMessageComponent):
         super().__init__(nodes=nodes, **_)
 
     def toDict(self):
-        return {"messages": [node.toDict() for node in self.nodes]}
+        """Deprecated. Use to_dict instead"""
+        ret = {
+            "messages": [],
+        }
+        for node in self.nodes:
+            d = node.toDict()
+            ret["messages"].append(d)
+        return ret
+
+    async def to_dict(self):
+        """将 Nodes 转换为字典格式，适用于 OneBot JSON 格式"""
+        ret = {"messages": []}
+        for node in self.nodes:
+            d = await node.to_dict()
+            ret["messages"].append(d)
+        return ret
 
 
 class Xml(BaseMessageComponent):
@@ -552,15 +714,136 @@ class Unknown(BaseMessageComponent):
 
 class File(BaseMessageComponent):
     """
-    目前此消息段只适配了 Napcat。
+    文件消息段
     """
 
     type: ComponentType = "File"
     name: T.Optional[str] = ""  # 名字
-    file: T.Optional[str] = ""  # url（本地路径）
+    file_: T.Optional[str] = ""  # 本地路径
+    url: T.Optional[str] = ""  # url
 
-    def __init__(self, name: str, file: str):
-        super().__init__(name=name, file=file)
+    def __init__(self, name: str, file: str = "", url: str = ""):
+        """文件消息段。"""
+        super().__init__(name=name, file_=file, url=url)
+
+    @property
+    def file(self) -> str:
+        """
+        获取文件路径，如果文件不存在但有URL，则同步下载文件
+
+        Returns:
+            str: 文件路径
+        """
+        if self.file_ and os.path.exists(self.file_):
+            return os.path.abspath(self.file_)
+
+        if self.url:
+            try:
+                loop = asyncio.get_event_loop()
+                if loop.is_running():
+                    logger.warning(
+                        (
+                            "不可以在异步上下文中同步等待下载! "
+                            "这个警告通常发生于某些逻辑试图通过 <File>.file 获取文件消息段的文件内容。"
+                            "请使用 await get_file() 代替直接获取 <File>.file 字段"
+                        )
+                    )
+                    return ""
+                else:
+                    # 等待下载完成
+                    loop.run_until_complete(self._download_file())
+
+                    if self.file_ and os.path.exists(self.file_):
+                        return os.path.abspath(self.file_)
+            except Exception as e:
+                logger.error(f"文件下载失败: {e}")
+
+        return ""
+
+    @file.setter
+    def file(self, value: str):
+        """
+        向前兼容, 设置file属性, 传入的参数可能是文件路径或URL
+
+        Args:
+            value (str): 文件路径或URL
+        """
+        if value.startswith("http://") or value.startswith("https://"):
+            self.url = value
+        else:
+            self.file_ = value
+
+    async def get_file(self, allow_return_url: bool = False) -> str:
+        """异步获取文件。请注意在使用后清理下载的文件, 以免占用过多空间
+
+        Args:
+            allow_return_url: 是否允许以文件 http 下载链接的形式返回，这允许您自行控制是否需要下载文件。
+            注意，如果为 True，也可能返回文件路径。
+        Returns:
+            str: 文件路径或者 http 下载链接
+        """
+        if allow_return_url and self.url:
+            return self.url
+
+        if self.file_ and os.path.exists(self.file_):
+            return os.path.abspath(self.file_)
+
+        if self.url:
+            await self._download_file()
+            return os.path.abspath(self.file_)
+
+        return ""
+
+    async def _download_file(self):
+        """下载文件"""
+        download_dir = os.path.join(get_astrbot_data_path(), "temp")
+        os.makedirs(download_dir, exist_ok=True)
+        file_path = os.path.join(download_dir, f"{uuid.uuid4().hex}")
+        await download_file(self.url, file_path)
+        self.file_ = os.path.abspath(file_path)
+
+    async def register_to_file_service(self):
+        """
+        将文件注册到文件服务。
+
+        Returns:
+            str: 注册后的URL
+
+        Raises:
+            Exception: 如果未配置 callback_api_base
+        """
+        callback_host = astrbot_config.get("callback_api_base")
+
+        if not callback_host:
+            raise Exception("未配置 callback_api_base，文件服务不可用")
+
+        file_path = await self.get_file()
+
+        token = await file_token_service.register_file(file_path)
+
+        logger.debug(f"已注册：{callback_host}/api/file/{token}")
+
+        return f"{callback_host}/api/file/{token}"
+
+    async def to_dict(self):
+        """需要和 toDict 区分开，toDict 是同步方法"""
+        url_or_path = await self.get_file(allow_return_url=True)
+        if url_or_path.startswith("http"):
+            payload_file = url_or_path
+        elif callback_host := astrbot_config.get("callback_api_base"):
+            callback_host = str(callback_host).removesuffix("/")
+            token = await file_token_service.register_file(url_or_path)
+            payload_file = f"{callback_host}/api/file/{token}"
+            logger.debug(f"Generated file callback link: {payload_file}")
+        else:
+            payload_file = url_or_path
+        return {
+            "type": "file",
+            "data": {
+                "name": self.name,
+                "file": payload_file,
+            },
+        }
 
 
 class WechatEmoji(BaseMessageComponent):

astrbot/core/message/message_event_result.py

@@ -1,6 +1,6 @@
 import enum
 
-from typing import List, Optional, Union
+from typing import List, Optional, Union, AsyncGenerator
 from dataclasses import dataclass, field
 from astrbot.core.message.components import (
     BaseMessageComponent,
@@ -111,6 +111,30 @@ class MessageChain:
         """获取纯文本消息。这个方法将获取 chain 中所有 Plain 组件的文本并拼接成一条消息。空格分隔。"""
         return " ".join([comp.text for comp in self.chain if isinstance(comp, Plain)])
 
+    def squash_plain(self):
+        """将消息链中的所有 Plain 消息段聚合到第一个 Plain 消息段中。"""
+        if not self.chain:
+            return
+
+        new_chain = []
+        first_plain = None
+        plain_texts = []
+
+        for comp in self.chain:
+            if isinstance(comp, Plain):
+                if first_plain is None:
+                    first_plain = comp
+                    new_chain.append(comp)
+                plain_texts.append(comp.text)
+            else:
+                new_chain.append(comp)
+
+        if first_plain is not None:
+            first_plain.text = "".join(plain_texts)
+
+        self.chain = new_chain
+        return self
+
 
 class EventResultType(enum.Enum):
     """用于描述事件处理的结果类型。
@@ -131,6 +155,10 @@ class ResultContentType(enum.Enum):
     """调用 LLM 产生的结果"""
     GENERAL_RESULT = enum.auto()
     """普通的消息结果"""
+    STREAMING_RESULT = enum.auto()
+    """调用 LLM 产生的流式结果"""
+    STREAMING_FINISH= enum.auto()
+    """流式输出完成"""
 
 
 @dataclass
@@ -152,6 +180,9 @@ class MessageEventResult(MessageChain):
         default_factory=lambda: ResultContentType.GENERAL_RESULT
     )
 
+    async_stream: Optional[AsyncGenerator] = None
+    """异步流"""
+
     def stop_event(self) -> "MessageEventResult":
         """终止事件传播。"""
         self.result_type = EventResultType.STOP
@@ -168,6 +199,11 @@ class MessageEventResult(MessageChain):
         """
         return self.result_type == EventResultType.STOP
 
+    def set_async_stream(self, stream: AsyncGenerator) -> "MessageEventResult":
+        """设置异步流。"""
+        self.async_stream = stream
+        return self
+
     def set_result_content_type(self, typ: ResultContentType) -> "MessageEventResult":
         """设置事件处理的结果类型。
 

astrbot/core/pipeline/__init__.py

@@ -7,6 +7,7 @@ from .waking_check.stage import WakingCheckStage
 from .whitelist_check.stage import WhitelistCheckStage
 from .rate_limit_check.stage import RateLimitStage
 from .content_safety_check.stage import ContentSafetyCheckStage
+from .platform_compatibility.stage import PlatformCompatibilityStage
 from .preprocess_stage.stage import PreProcessStage
 from .process_stage.stage import ProcessStage
 from .result_decorate.stage import ResultDecorateStage
@@ -18,6 +19,7 @@ STAGES_ORDER = [
     "WhitelistCheckStage",  # 检查是否在群聊/私聊白名单
     "RateLimitStage",  # 检查会话是否超过频率限制
     "ContentSafetyCheckStage",  # 检查内容安全
+    "PlatformCompatibilityStage",  # 检查所有处理器的平台兼容性
     "PreProcessStage",  # 预处理
     "ProcessStage",  # 交由 Stars 处理（a.k.a 插件），或者 LLM 调用
     "ResultDecorateStage",  # 处理结果，比如添加回复前缀、t2i、转换为语音 等
@@ -29,6 +31,7 @@ __all__ = [
     "WhitelistCheckStage",
     "RateLimitStage",
     "ContentSafetyCheckStage",
+    "PlatformCompatibilityStage",
     "PreProcessStage",
     "ProcessStage",
     "ResultDecorateStage",

astrbot/core/pipeline/platform_compatibility/stage.py

@@ -0,0 +1,56 @@
+from ..stage import Stage, register_stage
+from ..context import PipelineContext
+from typing import Union, AsyncGenerator
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
+from astrbot.core.star.star import star_map
+from astrbot.core.star.star_handler import StarHandlerMetadata
+from astrbot.core import logger
+
+
+@register_stage
+class PlatformCompatibilityStage(Stage):
+    """检查所有处理器的平台兼容性。
+
+    这个阶段会检查所有处理器是否在当前平台启用，如果未启用则设置platform_compatible属性为False。
+    """
+
+    async def initialize(self, ctx: PipelineContext) -> None:
+        """初始化平台兼容性检查阶段
+
+        Args:
+            ctx (PipelineContext): 消息管道上下文对象, 包括配置和插件管理器
+        """
+        self.ctx = ctx
+
+    async def process(
+        self, event: AstrMessageEvent
+    ) -> Union[None, AsyncGenerator[None, None]]:
+        # 获取当前平台ID
+        platform_id = event.get_platform_id()
+
+        # 获取已激活的处理器
+        activated_handlers = event.get_extra("activated_handlers")
+        if activated_handlers is None:
+            activated_handlers = []
+
+        # 标记不兼容的处理器
+        for handler in activated_handlers:
+            if not isinstance(handler, StarHandlerMetadata):
+                continue
+            # 检查处理器是否在当前平台启用
+            enabled = handler.is_enabled_for_platform(platform_id)
+            if not enabled:
+                if handler.handler_module_path in star_map:
+                    plugin_name = star_map[handler.handler_module_path].name
+                logger.debug(
+                    f"[PlatformCompatibilityStage] 插件 {plugin_name} 在平台 {platform_id} 未启用，标记处理器 {handler.handler_name} 为平台不兼容"
+                )
+                # 设置处理器为平台不兼容状态
+                # TODO: 更好的标记方式
+                handler.platform_compatible = False
+            else:
+                # 确保处理器为平台兼容状态
+                handler.platform_compatible = True
+
+        # 更新已激活的处理器列表
+        event.set_extra("activated_handlers", activated_handlers)

astrbot/core/pipeline/preprocess_stage/stage.py

@@ -46,28 +46,29 @@ class PreProcessStage(Stage):
             stt_provider = (
                 self.plugin_manager.context.provider_manager.curr_stt_provider_inst
             )
-            if stt_provider:
-                message_chain = event.get_messages()
-                for idx, component in enumerate(message_chain):
-                    if isinstance(component, Record) and component.url:
-                        path = component.url.removeprefix("file://")
-                        retry = 5
-                        for i in range(retry):
-                            try:
-                                result = await stt_provider.get_text(audio_url=path)
-                                if result:
-                                    logger.info("语音转文本结果: " + result)
-                                    message_chain[idx] = Plain(result)
-                                    event.message_str += result
-                                    event.message_obj.message_str += result
-                                break
-                            except FileNotFoundError as e:
-                                # napcat workaround
-                                logger.warning(e)
-                                logger.warning(f"重试中: {i + 1}/{retry}")
-                                await asyncio.sleep(0.5)
-                                continue
-                            except BaseException as e:
-                                logger.error(traceback.format_exc())
-                                logger.error(f"语音转文本失败: {e}")
-                                break
+            if not stt_provider:
+                return
+            message_chain = event.get_messages()
+            for idx, component in enumerate(message_chain):
+                if isinstance(component, Record) and component.url:
+                    path = component.url.removeprefix("file://")
+                    retry = 5
+                    for i in range(retry):
+                        try:
+                            result = await stt_provider.get_text(audio_url=path)
+                            if result:
+                                logger.info("语音转文本结果: " + result)
+                                message_chain[idx] = Plain(result)
+                                event.message_str += result
+                                event.message_obj.message_str += result
+                            break
+                        except FileNotFoundError as e:
+                            # napcat workaround
+                            logger.warning(e)
+                            logger.warning(f"重试中: {i + 1}/{retry}")
+                            await asyncio.sleep(0.5)
+                            continue
+                        except BaseException as e:
+                            logger.error(traceback.format_exc())
+                            logger.error(f"语音转文本失败: {e}")
+                            break

astrbot/core/pipeline/process_stage/method/llm_request.py

@@ -12,11 +12,12 @@ from astrbot.core.platform.astr_message_event import AstrMessageEvent
 from astrbot.core.message.message_event_result import (
     MessageEventResult,
     ResultContentType,
+    MessageChain,
 )
 from astrbot.core.message.components import Image
 from astrbot.core import logger
 from astrbot.core.utils.metrics import Metric
-from astrbot.core.provider.entites import (
+from astrbot.core.provider.entities import (
     ProviderRequest,
     LLMResponse,
     ToolCallMessageSegment,
@@ -25,6 +26,13 @@ from astrbot.core.provider.entites import (
 )
 from astrbot.core.star.star_handler import star_handlers_registry, EventType
 from astrbot.core.star.star import star_map
+from mcp.types import (
+    TextContent,
+    ImageContent,
+    EmbeddedResource,
+    TextResourceContents,
+    BlobResourceContents,
+)
 
 
 class LLMRequestSubStage(Stage):
@@ -37,6 +45,13 @@ class LLMRequestSubStage(Stage):
         self.max_context_length = ctx.astrbot_config["provider_settings"][
             "max_context_length"
         ]  # int
+        self.dequeue_context_length = min(
+            max(1, ctx.astrbot_config["provider_settings"]["dequeue_context_length"]),
+            self.max_context_length - 1,
+        )  # int
+        self.streaming_response = ctx.astrbot_config["provider_settings"][
+            "streaming_response"
+        ]  # bool
 
         for bwp in self.bot_wake_prefixs:
             if self.provider_wake_prefix.startswith(bwp):
@@ -52,6 +67,10 @@ class LLMRequestSubStage(Stage):
     ) -> Union[None, AsyncGenerator[None, None]]:
         req: ProviderRequest = None
 
+        if not self.ctx.astrbot_config["provider_settings"]["enable"]:
+            logger.debug("未启用 LLM 能力，跳过处理。")
+            return
+
         provider = self.ctx.plugin_manager.context.get_using_provider()
         if provider is None:
             return
@@ -63,7 +82,11 @@ class LLMRequestSubStage(Stage):
             )
 
             if req.conversation:
-                req.contexts = json.loads(req.conversation.history)
+                all_contexts = json.loads(req.conversation.history)
+                req.contexts = self._process_tool_message_pairs(
+                    all_contexts, remove_tags=True
+                )
+
         else:
             req = ProviderRequest(prompt="", image_urls=[])
             if self.provider_wake_prefix:
@@ -104,8 +127,10 @@ class LLMRequestSubStage(Stage):
 
         # 执行请求 LLM 前事件钩子。
         # 装饰 system_prompt 等功能
+        # 获取当前平台ID
+        platform_id = event.get_platform_id()
         handlers = star_handlers_registry.get_handlers_by_event_type(
-            EventType.OnLLMRequestEvent
+            EventType.OnLLMRequestEvent, platform_id=platform_id
         )
         for handler in handlers:
             try:
@@ -131,76 +156,152 @@ class LLMRequestSubStage(Stage):
             and len(req.contexts) // 2 > self.max_context_length
         ):
             logger.debug("上下文长度超过限制，将截断。")
-            req.contexts = req.contexts[-self.max_context_length * 2 :]
+            req.contexts = req.contexts[
+                -(self.max_context_length - self.dequeue_context_length + 1) * 2 :
+            ]
+            # 找到第一个role 为 user 的索引，确保上下文格式正确
+            index = next(
+                (
+                    i
+                    for i, item in enumerate(req.contexts)
+                    if item.get("role") == "user"
+                ),
+                None,
+            )
+            if index is not None and index > 0:
+                req.contexts = req.contexts[index:]
 
         # session_id
         if not req.session_id:
             req.session_id = event.unified_msg_origin
 
-        try:
-            need_loop = True
-            while need_loop:
-                need_loop = False
-                logger.debug(f"提供商请求 Payload: {req}")
-                llm_response = await provider.text_chat(**req.__dict__)  # 请求 LLM
+        async def requesting(req: ProviderRequest):
+            try:
+                need_loop = True
+                while need_loop:
+                    need_loop = False
+                    logger.debug(f"提供商请求 Payload: {req}")
 
-                # 执行 LLM 响应后的事件钩子。
-                handlers = star_handlers_registry.get_handlers_by_event_type(
-                    EventType.OnLLMResponseEvent
-                )
-                for handler in handlers:
-                    try:
-                        logger.debug(
-                            f"hook(on_llm_response) -> {star_map[handler.handler_module_path].name} - {handler.handler_name}"
-                        )
-                        await handler.handler(event, llm_response)
-                    except BaseException:
-                        logger.error(traceback.format_exc())
+                    final_llm_response = None
 
-                    if event.is_stopped():
-                        logger.info(
-                            f"{star_map[handler.handler_module_path].name} - {handler.handler_name} 终止了事件传播。"
-                        )
-                        return
-
-                async for result in self._handle_llm_response(event, req, llm_response):
-                    if isinstance(result, ProviderRequest):
-                        # 有函数工具调用并且返回了结果，我们需要再次请求 LLM
-                        req = result
-                        need_loop = True
+                    if self.streaming_response:
+                        stream = provider.text_chat_stream(**req.__dict__)
+                        async for llm_response in stream:
+                            if llm_response.is_chunk:
+                                if llm_response.result_chain:
+                                    yield llm_response.result_chain  # MessageChain
+                                else:
+                                    yield MessageChain().message(
+                                        llm_response.completion_text
+                                    )
+                            else:
+                                final_llm_response = llm_response
                     else:
-                        yield
+                        final_llm_response = await provider.text_chat(
+                            **req.__dict__
+                        )  # 请求 LLM
 
-            asyncio.create_task(
-                Metric.upload(
-                    llm_tick=1,
-                    model_name=provider.get_model(),
-                    provider_type=provider.meta().type,
+                    if not final_llm_response:
+                        raise Exception("LLM response is None.")
+
+                    # 执行 LLM 响应后的事件钩子。
+                    handlers = star_handlers_registry.get_handlers_by_event_type(
+                        EventType.OnLLMResponseEvent
+                    )
+                    for handler in handlers:
+                        try:
+                            logger.debug(
+                                f"hook(on_llm_response) -> {star_map[handler.handler_module_path].name} - {handler.handler_name}"
+                            )
+                            await handler.handler(event, final_llm_response)
+                        except BaseException:
+                            logger.error(traceback.format_exc())
+
+                        if event.is_stopped():
+                            logger.info(
+                                f"{star_map[handler.handler_module_path].name} - {handler.handler_name} 终止了事件传播。"
+                            )
+                            return
+
+                    if self.streaming_response:
+                        # 流式输出的处理
+                        async for result in self._handle_llm_stream_response(
+                            event, req, final_llm_response
+                        ):
+                            if isinstance(result, ProviderRequest):
+                                # 有函数工具调用并且返回了结果，我们需要再次请求 LLM
+                                req = result
+                                need_loop = True
+                            else:
+                                yield
+                    else:
+                        # 非流式输出的处理
+                        async for result in self._handle_llm_response(
+                            event, req, final_llm_response
+                        ):
+                            if isinstance(result, ProviderRequest):
+                                # 有函数工具调用并且返回了结果，我们需要再次请求 LLM
+                                req = result
+                                need_loop = True
+                            else:
+                                yield
+
+                asyncio.create_task(
+                    Metric.upload(
+                        llm_tick=1,
+                        model_name=provider.get_model(),
+                        provider_type=provider.meta().type,
+                    )
                 )
-            )
 
-            # 保存到历史记录
-            await self._save_to_history(event, req, llm_response)
+                # 保存到历史记录
+                await self._save_to_history(event, req, final_llm_response)
 
-        except BaseException as e:
-            logger.error(traceback.format_exc())
+            except BaseException as e:
+                logger.error(traceback.format_exc())
+                event.set_result(
+                    MessageEventResult().message(
+                        f"AstrBot 请求失败。\n错误类型: {type(e).__name__}\n错误信息: {str(e)}"
+                    )
+                )
+
+        if not self.streaming_response:
+            event.set_extra("tool_call_result", None)
+            async for _ in requesting(req):
+                yield
+        else:
             event.set_result(
-                MessageEventResult().message(
-                    f"AstrBot 请求失败。\n错误类型: {type(e).__name__}\n错误信息: {str(e)}"
-                )
+                MessageEventResult()
+                .set_result_content_type(ResultContentType.STREAMING_RESULT)
+                .set_async_stream(requesting(req))
             )
-            return
+            # 这里使用yield来暂停当前阶段，等待流式输出完成后继续处理
+            yield
+
+            if event.get_extra("tool_call_result"):
+                event.set_result(event.get_extra("tool_call_result"))
+                event.set_extra("tool_call_result", None)
+                yield
+
+        # 暂时直接发出去
+        if img_b64 := event.get_extra("tool_call_img_respond"):
+            await event.send(MessageChain(chain=[Image.fromBase64(img_b64)]))
+            event.set_extra("tool_call_img_respond", None)
+            yield
 
     async def _handle_llm_response(
-        self, event: AstrMessageEvent, req: ProviderRequest, llm_response: LLMResponse
-    ) -> AsyncGenerator[None, None]:
-        """处理 LLM 响应。
+        self,
+        event: AstrMessageEvent,
+        req: ProviderRequest,
+        llm_response: LLMResponse,
+    ) -> AsyncGenerator[Union[None, ProviderRequest], None]:
+        """处理非流式 LLM 响应。
 
         Returns:
-            bool: 是否需要继续调用 LLM
+            AsyncGenerator[Union[None, ProviderRequest], None]: 如果返回 ProviderRequest，表示需要再次调用 LLM
 
         Yields:
-            Iterator[bool]: 将 event 交付给下一个 stage
+            Iterator[Union[None, ProviderRequest]]: 将 event 交付给下一个 stage 或者返回 ProviderRequest 表示需要再次调用 LLM
         """
         if llm_response.role == "assistant":
             # text completion
@@ -223,30 +324,83 @@ class LLMRequestSubStage(Stage):
                 )
             )
         elif llm_response.role == "tool":
-            # function calling
-            tool_call_result: list[ToolCallMessageSegment] = []
-            logger.info(
-                f"触发 {len(llm_response.tools_call_name)} 个函数调用: {llm_response.tools_call_name}"
+            # 处理函数工具调用
+            async for result in self._handle_function_tools(event, req, llm_response):
+                yield result
+
+    async def _handle_llm_stream_response(
+        self,
+        event: AstrMessageEvent,
+        req: ProviderRequest,
+        llm_response: LLMResponse,
+    ) -> AsyncGenerator[Union[None, ProviderRequest], None]:
+        """处理流式 LLM 响应。
+
+        专门用于处理流式输出完成后的响应，与非流式响应处理分离。
+
+        Returns:
+            AsyncGenerator[Union[None, ProviderRequest], None]: 如果返回 ProviderRequest，表示需要再次调用 LLM
+
+        Yields:
+            Iterator[Union[None, ProviderRequest]]: 将 event 交付给下一个 stage 或者返回 ProviderRequest 表示需要再次调用 LLM
+        """
+        if llm_response.role == "assistant":
+            # text completion
+            if llm_response.result_chain:
+                event.set_result(
+                    MessageEventResult(
+                        chain=llm_response.result_chain.chain
+                    ).set_result_content_type(ResultContentType.STREAMING_FINISH)
+                )
+            else:
+                event.set_result(
+                    MessageEventResult()
+                    .message(llm_response.completion_text)
+                    .set_result_content_type(ResultContentType.STREAMING_FINISH)
+                )
+        elif llm_response.role == "err":
+            event.set_result(
+                MessageEventResult().message(
+                    f"AstrBot 请求失败。\n错误信息: {llm_response.completion_text}"
+                )
             )
-            for func_tool_name, func_tool_args, func_tool_id in zip(
-                llm_response.tools_call_name,
-                llm_response.tools_call_args,
-                llm_response.tools_call_ids,
-            ):
-                try:
-                    func_tool = req.func_tool.get_func(func_tool_name)
-                    if func_tool.origin == "mcp":
-                        logger.info(
-                            f"从 MCP 服务 {func_tool.mcp_server_name} 调用工具函数：{func_tool.name}，参数：{func_tool_args}"
-                        )
-                        client = req.func_tool.mcp_client_dict[
-                            func_tool.mcp_server_name
-                        ]
-                        res = await client.session.call_tool(
-                            func_tool.name, func_tool_args
-                        )
-                        if res:
-                            # TODO content的类型可能包括list[TextContent | ImageContent | EmbeddedResource]，这里只处理了TextContent。
+        elif llm_response.role == "tool":
+            # 处理函数工具调用
+            async for result in self._handle_function_tools(event, req, llm_response):
+                yield result
+
+    async def _handle_function_tools(
+        self,
+        event: AstrMessageEvent,
+        req: ProviderRequest,
+        llm_response: LLMResponse,
+    ) -> AsyncGenerator[Union[None, ProviderRequest], None]:
+        """处理函数工具调用。
+
+        Returns:
+            AsyncGenerator[Union[None, ProviderRequest], None]: 如果返回 ProviderRequest，表示需要再次调用 LLM
+        """
+        # function calling
+        tool_call_result: list[ToolCallMessageSegment] = []
+        logger.info(
+            f"触发 {len(llm_response.tools_call_name)} 个函数调用: {llm_response.tools_call_name}"
+        )
+        for func_tool_name, func_tool_args, func_tool_id in zip(
+            llm_response.tools_call_name,
+            llm_response.tools_call_args,
+            llm_response.tools_call_ids,
+        ):
+            try:
+                func_tool = req.func_tool.get_func(func_tool_name)
+                if func_tool.origin == "mcp":
+                    logger.info(
+                        f"从 MCP 服务 {func_tool.mcp_server_name} 调用工具函数：{func_tool.name}，参数：{func_tool_args}"
+                    )
+                    client = req.func_tool.mcp_client_dict[func_tool.mcp_server_name]
+                    res = await client.session.call_tool(func_tool.name, func_tool_args)
+                    if res:
+                        # TODO 仅对ImageContent | EmbeddedResource进行了简单的Fallback
+                        if isinstance(res.content[0], TextContent):
                             tool_call_result.append(
                                 ToolCallMessageSegment(
                                     role="tool",
@@ -254,52 +408,115 @@ class LLMRequestSubStage(Stage):
                                     content=res.content[0].text,
                                 )
                             )
-                    else:
-                        logger.info(
-                            f"调用工具函数：{func_tool_name}，参数：{func_tool_args}"
-                        )
-                        # 尝试调用工具函数
-                        wrapper = self._call_handler(
-                            self.ctx, event, func_tool.handler, **func_tool_args
-                        )
-                        async for resp in wrapper:
-                            if resp is not None:  # 有 return 返回
+                        elif isinstance(res.content[0], ImageContent):
+                            tool_call_result.append(
+                                ToolCallMessageSegment(
+                                    role="tool",
+                                    tool_call_id=func_tool_id,
+                                    content="返回了图片(已直接发送给用户)",
+                                )
+                            )
+                            event.set_extra(
+                                "tool_call_img_respond",
+                                res.content[0].data,
+                            )
+                        elif isinstance(res.content[0], EmbeddedResource):
+                            resource = res.content[0].resource
+                            if isinstance(resource, TextResourceContents):
                                 tool_call_result.append(
                                     ToolCallMessageSegment(
                                         role="tool",
                                         tool_call_id=func_tool_id,
-                                        content=resp,
+                                        content=resource.text,
                                     )
                                 )
+                            elif (
+                                isinstance(resource, BlobResourceContents)
+                                and resource.mimeType
+                                and resource.mimeType.startswith("image/")
+                            ):
+                                tool_call_result.append(
+                                    ToolCallMessageSegment(
+                                        role="tool",
+                                        tool_call_id=func_tool_id,
+                                        content="返回了图片(已直接发送给用户)",
+                                    )
+                                )
+                                event.set_extra(
+                                    "tool_call_img_respond",
+                                    res.content[0].data,
+                                )
                             else:
-                                yield  # 有生成器返回
-                    event.clear_result()  # 清除上一个 handler 的结果
-                except BaseException as e:
-                    logger.warning(traceback.format_exc())
-                    tool_call_result.append(
-                        ToolCallMessageSegment(
-                            role="tool",
-                            tool_call_id=func_tool_id,
-                            content=f"error: {str(e)}",
+                                tool_call_result.append(
+                                    ToolCallMessageSegment(
+                                        role="tool",
+                                        tool_call_id=func_tool_id,
+                                        content="返回的数据类型不受支持",
+                                    )
+                                )
+                else:
+                    # 获取处理器，过滤掉平台不兼容的处理器
+                    platform_id = event.get_platform_id()
+                    star_md = star_map.get(func_tool.handler_module_path)
+                    if (
+                        star_md
+                        and platform_id in star_md.supported_platforms
+                        and not star_md.supported_platforms[platform_id]
+                    ):
+                        logger.debug(
+                            f"处理器 {func_tool_name}({star_md.name}) 在当前平台不兼容或者被禁用，跳过执行"
                         )
+                        # 直接跳过，不添加任何消息到tool_call_result
+                        continue
+
+                    logger.info(
+                        f"调用工具函数：{func_tool_name}，参数：{func_tool_args}"
                     )
-            if tool_call_result:
-                # 函数调用结果
-                req.func_tool = None  # 暂时不支持递归工具调用
-                assistant_msg_seg = AssistantMessageSegment(
-                    role="assistant", tool_calls=llm_response.to_openai_tool_calls()
-                )
-                # 在多轮 Tool 调用的情况下，这里始终保持最新的 Tool 调用结果，减少上下文长度。
-                req.tool_calls_result = ToolCallsResult(
-                    tool_calls_info=assistant_msg_seg,
-                    tool_calls_result=tool_call_result,
-                )
-                yield req  # 再次执行 LLM 请求
-            else:
-                if llm_response.completion_text:
-                    event.set_result(
-                        MessageEventResult().message(llm_response.completion_text)
+                    # 尝试调用工具函数
+                    wrapper = self._call_handler(
+                        self.ctx, event, func_tool.handler, **func_tool_args
                     )
+                    async for resp in wrapper:
+                        if resp is not None:  # 有 return 返回
+                            tool_call_result.append(
+                                ToolCallMessageSegment(
+                                    role="tool",
+                                    tool_call_id=func_tool_id,
+                                    content=resp,
+                                )
+                            )
+                        else:
+                            res = event.get_result()
+                            if res and res.chain:
+                                event.set_extra("tool_call_result", res)
+                            yield  # 有生成器返回
+                event.clear_result()  # 清除上一个 handler 的结果
+            except BaseException as e:
+                logger.warning(traceback.format_exc())
+                tool_call_result.append(
+                    ToolCallMessageSegment(
+                        role="tool",
+                        tool_call_id=func_tool_id,
+                        content=f"error: {str(e)}",
+                    )
+                )
+        if tool_call_result:
+            # 函数调用结果
+            req.func_tool = None  # 暂时不支持递归工具调用
+            assistant_msg_seg = AssistantMessageSegment(
+                role="assistant", tool_calls=llm_response.to_openai_tool_calls()
+            )
+            # 在多轮 Tool 调用的情况下，这里始终保持最新的 Tool 调用结果，减少上下文长度。
+            req.tool_calls_result = ToolCallsResult(
+                tool_calls_info=assistant_msg_seg,
+                tool_calls_result=tool_call_result,
+            )
+            yield req  # 再次执行 LLM 请求
+        else:
+            if llm_response.completion_text:
+                event.set_result(
+                    MessageEventResult().message(llm_response.completion_text)
+                )
 
     async def _save_to_history(
         self, event: AstrMessageEvent, req: ProviderRequest, llm_response: LLMResponse
@@ -309,12 +526,22 @@ class LLMRequestSubStage(Stage):
 
         if llm_response.role == "assistant":
             # 文本回复
-            contexts = req.contexts
+            contexts = req.contexts.copy()
             contexts.append(await req.assemble_context())
 
-            # tool calls result
+            # 记录并标记函数调用结果
             if req.tool_calls_result:
-                contexts.extend(req.tool_calls_result.to_openai_messages())
+                tool_calls_messages = req.tool_calls_result.to_openai_messages()
+
+                # 添加标记
+                for message in tool_calls_messages:
+                    message["_tool_call_history"] = True
+
+                processed_tool_messages = self._process_tool_message_pairs(
+                    tool_calls_messages, remove_tags=False
+                )
+
+                contexts.extend(processed_tool_messages)
 
             contexts.append(
                 {"role": "assistant", "content": llm_response.completion_text}
@@ -325,3 +552,59 @@ class LLMRequestSubStage(Stage):
             await self.conv_manager.update_conversation(
                 event.unified_msg_origin, req.conversation.cid, history=contexts_to_save
             )
+
+    def _process_tool_message_pairs(self, messages, remove_tags=True):
+        """处理工具调用消息，确保assistant和tool消息成对出现
+
+        Args:
+            messages (list): 消息列表
+            remove_tags (bool): 是否移除_tool_call_history标记
+
+        Returns:
+            list: 处理后的消息列表，保证了assistant和对应tool消息的成对出现
+        """
+        result = []
+        i = 0
+
+        while i < len(messages):
+            current_msg = messages[i]
+
+            # 普通消息直接添加
+            if "_tool_call_history" not in current_msg:
+                result.append(current_msg.copy() if remove_tags else current_msg)
+                i += 1
+                continue
+
+            # 工具调用消息成对处理
+            if current_msg.get("role") == "assistant" and "tool_calls" in current_msg:
+                assistant_msg = current_msg.copy()
+
+                if remove_tags and "_tool_call_history" in assistant_msg:
+                    del assistant_msg["_tool_call_history"]
+
+                related_tools = []
+                j = i + 1
+                while (
+                    j < len(messages)
+                    and messages[j].get("role") == "tool"
+                    and "_tool_call_history" in messages[j]
+                ):
+                    tool_msg = messages[j].copy()
+
+                    if remove_tags:
+                        del tool_msg["_tool_call_history"]
+
+                    related_tools.append(tool_msg)
+                    j += 1
+
+                # 成对的时候添加到结果
+                if related_tools:
+                    result.append(assistant_msg)
+                    result.extend(related_tools)
+
+                i = j  # 跳过已处理
+            else:
+                # 单独的tool消息
+                i += 1
+
+        return result

astrbot/core/pipeline/process_stage/method/star_request.py

@@ -31,7 +31,18 @@ class StarRequestSubStage(Stage):
         )
         if not handlers_parsed_params:
             handlers_parsed_params = {}
+
         for handler in activated_handlers:
+            # 检查处理器是否在当前平台兼容
+            if (
+                hasattr(handler, "platform_compatible")
+                and handler.platform_compatible is False
+            ):
+                logger.debug(
+                    f"处理器 {handler.handler_name} 在当前平台不兼容，跳过执行"
+                )
+                continue
+
             params = handlers_parsed_params.get(handler.handler_full_name, {})
             try:
                 if handler.handler_module_path not in star_map:

astrbot/core/pipeline/process_stage/stage.py

@@ -5,7 +5,7 @@ from .method.llm_request import LLMRequestSubStage
 from .method.star_request import StarRequestSubStage
 from astrbot.core.platform.astr_message_event import AstrMessageEvent
 from astrbot.core.star.star_handler import StarHandlerMetadata
-from astrbot.core.provider.entites import ProviderRequest
+from astrbot.core.provider.entities import ProviderRequest
 from astrbot.core import logger
 
 

astrbot/core/pipeline/rate_limit_check/stage.py

@@ -58,33 +58,30 @@ class RateLimitStage(Stage):
         now = datetime.now()
 
         async with self.locks[session_id]:  # 确保同一会话不会并发修改队列
-            timestamps = self.event_timestamps[session_id]
+            # 检查并处理限流，可能需要多次检查直到满足条件
+            while True:
+                timestamps = self.event_timestamps[session_id]
+                self._remove_expired_timestamps(timestamps, now)
 
-            self._remove_expired_timestamps(timestamps, now)
+                if len(timestamps) < self.rate_limit_count:
+                    timestamps.append(now)
+                    break
+                else:
+                    next_window_time = timestamps[0] + self.rate_limit_time
+                    stall_duration = (next_window_time - now).total_seconds() + 0.3
 
-            if len(timestamps) >= self.rate_limit_count:
-                # 达到限流阈值，计算下一个窗口的时间
-                next_window_time = timestamps[0] + self.rate_limit_time
-                stall_duration = (next_window_time - now).total_seconds()
-
-                match self.rl_strategy:
-                    case RateLimitStrategy.STALL.value:
-                        logger.info(
-                            f"会话 {session_id} 被限流。根据限流策略，此会话处理将被暂停 {stall_duration:.2f} 秒。"
-                        )
-                        await asyncio.sleep(stall_duration)
-                    case RateLimitStrategy.DISCARD.value:
-                        # event.set_result(MessageEventResult().message(f"会话 {session_id} 被限流。根据限流策略，此请求已被丢弃，直到您的限额于 {stall_duration:.2f} 秒后重置。"))
-                        logger.info(
-                            f"会话 {session_id} 被限流。根据限流策略，此请求已被丢弃，直到限额于 {stall_duration:.2f} 秒后重置。"
-                        )
-                        return event.stop_event()
-
-                self._remove_expired_timestamps(
-                    timestamps, now + timedelta(seconds=stall_duration)
-                )
-
-            timestamps.append(now)
+                    match self.rl_strategy:
+                        case RateLimitStrategy.STALL.value:
+                            logger.info(
+                                f"会话 {session_id} 被限流。根据限流策略，此会话处理将被暂停 {stall_duration:.2f} 秒。"
+                            )
+                            await asyncio.sleep(stall_duration)
+                            now = datetime.now()
+                        case RateLimitStrategy.DISCARD.value:
+                            logger.info(
+                                f"会话 {session_id} 被限流。根据限流策略，此请求已被丢弃，直到限额于 {stall_duration:.2f} 秒后重置。"
+                            )
+                            return event.stop_event()
 
     def _remove_expired_timestamps(
         self, timestamps: Deque[datetime], now: datetime

astrbot/core/pipeline/respond/stage.py

@@ -7,49 +7,37 @@ from typing import Union, AsyncGenerator
 from ..stage import register_stage, Stage
 from ..context import PipelineContext
 from astrbot.core.platform.astr_message_event import AstrMessageEvent
-from astrbot.core.message.message_event_result import MessageChain
+from astrbot.core.message.message_event_result import MessageChain, ResultContentType
 from astrbot.core import logger
 from astrbot.core.message.message_event_result import BaseMessageComponent
 from astrbot.core.star.star_handler import star_handlers_registry, EventType
 from astrbot.core.star.star import star_map
+from astrbot.core.utils.path_util import path_Mapping
 
 
 @register_stage
 class RespondStage(Stage):
     # 组件类型到其非空判断函数的映射
     _component_validators = {
-        Comp.Plain: lambda comp: bool(comp.text and comp.text.strip()),  # 纯文本消息需要strip
+        Comp.Plain: lambda comp: bool(
+            comp.text and comp.text.strip()
+        ),  # 纯文本消息需要strip
         Comp.Face: lambda comp: comp.id is not None,  # QQ表情
         Comp.Record: lambda comp: bool(comp.file),  # 语音
         Comp.Video: lambda comp: bool(comp.file),  # 视频
         Comp.At: lambda comp: bool(comp.qq) or bool(comp.name),  # @
-        Comp.AtAll: lambda comp: True,  # @所有人
-        Comp.RPS: lambda comp: True,  # 不知道是啥(未完成)
-        Comp.Dice: lambda comp: True,  # 骰子(未完成)
-        Comp.Shake: lambda comp: True,  # 摇一摇(未完成)
-        Comp.Anonymous: lambda comp: True,  # 匿名(未完成)
-        Comp.Share: lambda comp: bool(comp.url) and bool(comp.title),  # 分享
-        Comp.Contact: lambda comp: True,  # 联系人(未完成)
-        Comp.Location: lambda comp: bool(comp.lat and comp.lon),  # 位置
-        Comp.Music: lambda comp: bool(comp._type) and bool(comp.url) and bool(comp.audio),  # 音乐
         Comp.Image: lambda comp: bool(comp.file),  # 图片
         Comp.Reply: lambda comp: bool(comp.id) and comp.sender_id is not None,  # 回复
-        Comp.RedBag: lambda comp: bool(comp.title),  # 红包
         Comp.Poke: lambda comp: comp.id != 0 and comp.qq != 0,  # 戳一戳
-        Comp.Forward: lambda comp: bool(comp.id and comp.id.strip()),  # 转发
-        Comp.Node: lambda comp: bool(comp.name) and comp.uin != 0 and bool(comp.content),  # 一个转发节点
+        Comp.Node: lambda comp: bool(comp.content),  # 转发节点
         Comp.Nodes: lambda comp: bool(comp.nodes),  # 多个转发节点
-        Comp.Xml: lambda comp: bool(comp.data and comp.data.strip()),  # XML
-        Comp.Json: lambda comp: bool(comp.data),  # JSON
-        Comp.CardImage: lambda comp: bool(comp.file),  # 卡片图片
-        Comp.TTS: lambda comp: bool(comp.text and comp.text.strip()),  # 语音合成
-        Comp.Unknown: lambda comp: bool(comp.text and comp.text.strip()),  # 未知消息
-        Comp.File: lambda comp: bool(comp.file),  # 文件
-        Comp.WechatEmoji: lambda comp: bool(comp.md5),  # 微信表情
+        Comp.File: lambda comp: bool(comp.file_ or comp.url),
     }
 
     async def initialize(self, ctx: PipelineContext):
         self.ctx = ctx
+        self.config = ctx.astrbot_config
+        self.platform_settings: dict = self.config.get("platform_settings", {})
 
         self.reply_with_mention = ctx.astrbot_config["platform_settings"][
             "reply_with_mention"
@@ -120,8 +108,6 @@ class RespondStage(Stage):
             if comp_type in self._component_validators:
                 if self._component_validators[comp_type](comp):
                     return False
-            else:
-                logger.info(f"空内容检查: 无法识别的组件类型: {comp_type.__name__}")
 
         # 如果所有组件都为空
         return True
@@ -132,8 +118,28 @@ class RespondStage(Stage):
         result = event.get_result()
         if result is None:
             return
+        if result.result_content_type == ResultContentType.STREAMING_FINISH:
+            return
+
+        if result.result_content_type == ResultContentType.STREAMING_RESULT:
+            # 流式结果直接交付平台适配器处理
+            use_fallback = self.config.get("provider_settings", {}).get(
+                "streaming_segmented", False
+            )
+            logger.info(f"应用流式输出({event.get_platform_name()})")
+            await event._pre_send()
+            await event.send_streaming(result.async_stream, use_fallback)
+            await event._post_send()
+            return
+        elif len(result.chain) > 0:
+            # 检查路径映射
+            if mappings := self.platform_settings.get("path_mapping", []):
+                for idx, component in enumerate(result.chain):
+                    if isinstance(component, Comp.File) and component.file:
+                        # 支持 File 消息段的路径映射。
+                        component.file = path_Mapping(mappings, component.file)
+                        event.get_result().chain[idx] = component
 
-        if len(result.chain) > 0:
             await event._pre_send()
 
             # 检查消息链是否为空
@@ -146,6 +152,11 @@ class RespondStage(Stage):
             except Exception as e:
                 logger.warning(f"空内容检查异常: {e}")
 
+            record_comps = [c for c in result.chain if isinstance(c, Comp.Record)]
+            non_record_comps = [
+                c for c in result.chain if not isinstance(c, Comp.Record)
+            ]
+
             if self.enable_seg and (
                 (self.only_llm_result and result.is_llm_result())
                 or not self.only_llm_result
@@ -163,8 +174,18 @@ class RespondStage(Stage):
                             decorated_comps.append(comp)
                             result.chain.remove(comp)
                             break
+
+                for rcomp in record_comps:
+                    i = await self._calc_comp_interval(rcomp)
+                    await asyncio.sleep(i)
+                    try:
+                        await event.send(MessageChain([rcomp]))
+                    except Exception as e:
+                        logger.error(f"发送消息失败: {e} chain: {result.chain}")
+                        break
+
                 # 分段回复
-                for comp in result.chain:
+                for comp in non_record_comps:
                     i = await self._calc_comp_interval(comp)
                     await asyncio.sleep(i)
                     try:
@@ -173,17 +194,25 @@ class RespondStage(Stage):
                         logger.error(f"发送消息失败: {e} chain: {result.chain}")
                         break
             else:
+                for rcomp in record_comps:
+                    try:
+                        await event.send(MessageChain([rcomp]))
+                    except Exception as e:
+                        logger.error(f"发送消息失败: {e} chain: {result.chain}")
+
                 try:
-                    await event.send(result)
+                    await event.send(MessageChain(non_record_comps))
                 except Exception as e:
+                    logger.error(traceback.format_exc())
                     logger.error(f"发送消息失败: {e} chain: {result.chain}")
+
             await event._post_send()
             logger.info(
                 f"AstrBot -> {event.get_sender_name()}/{event.get_sender_id()}: {event._outline_chain(result.chain)}"
             )
 
         handlers = star_handlers_registry.get_handlers_by_event_type(
-            EventType.OnAfterMessageSentEvent
+            EventType.OnAfterMessageSentEvent, platform_id=event.get_platform_id()
         )
         for handler in handlers:
             try:

astrbot/core/pipeline/result_decorate/stage.py

@@ -1,16 +1,18 @@
-import time
 import re
+import time
 import traceback
-from typing import Union, AsyncGenerator
-from ..stage import Stage, register_stage, registered_stages
-from ..context import PipelineContext
+from typing import AsyncGenerator, Union
+
+from astrbot.core import html_renderer, logger, file_token_service
+from astrbot.core.message.components import At, File, Image, Node, Plain, Record, Reply
+from astrbot.core.message.message_event_result import ResultContentType
 from astrbot.core.platform.astr_message_event import AstrMessageEvent
 from astrbot.core.platform.message_type import MessageType
-from astrbot.core import logger
-from astrbot.core.message.components import Plain, Image, At, Reply, Record, File, Node
-from astrbot.core import html_renderer
-from astrbot.core.star.star_handler import star_handlers_registry, EventType
 from astrbot.core.star.star import star_map
+from astrbot.core.star.star_handler import EventType, star_handlers_registry
+
+from ..context import PipelineContext
+from ..stage import Stage, register_stage, registered_stages
 
 
 @register_stage
@@ -72,11 +74,17 @@ class ResultDecorateStage(Stage):
         if result is None or not result.chain:
             return
 
+        if result.result_content_type == ResultContentType.STREAMING_RESULT:
+            return
+
+        is_stream = result.result_content_type == ResultContentType.STREAMING_FINISH
+
         # 回复时检查内容安全
         if (
             self.content_safe_check_reply
             and self.content_safe_check_stage
             and result.is_llm_result()
+            and not is_stream  # 流式输出不检查内容安全
         ):
             text = ""
             for comp in result.chain:
@@ -89,13 +97,17 @@ class ResultDecorateStage(Stage):
 
         # 发送消息前事件钩子
         handlers = star_handlers_registry.get_handlers_by_event_type(
-            EventType.OnDecoratingResultEvent
+            EventType.OnDecoratingResultEvent, platform_id=event.get_platform_id()
         )
         for handler in handlers:
             try:
                 logger.debug(
                     f"hook(on_decorating_result) -> {star_map[handler.handler_module_path].name} - {handler.handler_name}"
                 )
+                if is_stream:
+                    logger.warning(
+                        "启用流式输出时，依赖发送消息前事件钩子的插件可能无法正常工作"
+                    )
                 await handler.handler(event)
                 if event.get_result() is None or not event.get_result().chain:
                     logger.debug(
@@ -110,6 +122,11 @@ class ResultDecorateStage(Stage):
                 )
                 return
 
+        # 流式输出不执行下面的逻辑
+        if is_stream:
+            logger.info("流式输出已启用，跳过结果装饰阶段")
+            return
+
         # 需要再获取一次。插件可能直接对 chain 进行了替换。
         result = event.get_result()
         if result is None:
@@ -135,9 +152,9 @@ class ResultDecorateStage(Stage):
                                 # 不分段回复
                                 new_chain.append(comp)
                                 continue
-                            split_response = []
-                            for line in comp.text.split("\n"):
-                                split_response.extend(re.findall(self.regex, line))
+                            split_response = re.findall(
+                                self.regex, comp.text, re.DOTALL | re.MULTILINE
+                            )
                             if not split_response:
                                 new_chain.append(comp)
                                 continue
@@ -152,28 +169,55 @@ class ResultDecorateStage(Stage):
                     result.chain = new_chain
 
             # TTS
+            tts_provider = (
+                self.ctx.plugin_manager.context.provider_manager.curr_tts_provider_inst
+            )
             if (
                 self.ctx.astrbot_config["provider_tts_settings"]["enable"]
                 and result.is_llm_result()
+                and tts_provider
             ):
-                tts_provider = self.ctx.plugin_manager.context.provider_manager.curr_tts_provider_inst
                 new_chain = []
                 for comp in result.chain:
                     if isinstance(comp, Plain) and len(comp.text) > 1:
                         try:
-                            logger.info("TTS 请求: " + comp.text)
+                            logger.info(f"TTS 请求: {comp.text}")
                             audio_path = await tts_provider.get_audio(comp.text)
-                            logger.info("TTS 结果: " + audio_path)
-                            if audio_path:
-                                new_chain.append(
-                                    Record(file=audio_path, url=audio_path)
-                                )
-                            else:
+                            logger.info(f"TTS 结果: {audio_path}")
+                            if not audio_path:
                                 logger.error(
-                                    f"由于 TTS 音频文件没找到，消息段转语音失败: {comp.text}"
+                                    f"由于 TTS 音频文件未找到，消息段转语音失败: {comp.text}"
                                 )
                                 new_chain.append(comp)
-                        except BaseException:
+                                continue
+
+                            use_file_service = self.ctx.astrbot_config[
+                                "provider_tts_settings"
+                            ]["use_file_service"]
+                            callback_api_base = self.ctx.astrbot_config[
+                                "callback_api_base"
+                            ]
+                            dual_output = self.ctx.astrbot_config[
+                                "provider_tts_settings"
+                            ]["dual_output"]
+
+                            url = None
+                            if use_file_service and callback_api_base:
+                                token = await file_token_service.register_file(
+                                    audio_path
+                                )
+                                url = f"{callback_api_base}/api/file/{token}"
+                                logger.debug(f"已注册：{url}")
+
+                            new_chain.append(
+                                Record(
+                                    file=url or audio_path,
+                                    url=url or audio_path,
+                                )
+                            )
+                            if dual_output:
+                                new_chain.append(comp)
+                        except Exception:
                             logger.error(traceback.format_exc())
                             logger.error("TTS 失败，使用文本发送。")
                             new_chain.append(comp)
@@ -207,6 +251,14 @@ class ResultDecorateStage(Stage):
                     if url:
                         if url.startswith("http"):
                             result.chain = [Image.fromURL(url)]
+                        elif (
+                            self.ctx.astrbot_config["t2i_use_file_service"]
+                            and self.ctx.astrbot_config["callback_api_base"]
+                        ):
+                            token = await file_token_service.register_file(url)
+                            url = f"{self.ctx.astrbot_config['callback_api_base']}/api/file/{token}"
+                            logger.debug(f"已注册：{url}")
+                            result.chain = [Image.fromURL(url)]
                         else:
                             result.chain = [Image.fromFileSystem(url)]
 

astrbot/core/pipeline/waking_check/stage.py

@@ -1,5 +1,6 @@
 from ..stage import Stage, register_stage
 from ..context import PipelineContext
+from astrbot import logger
 from typing import Union, AsyncGenerator
 from astrbot.core.platform.astr_message_event import AstrMessageEvent
 from astrbot.core.message.message_event_result import MessageEventResult, MessageChain
@@ -34,10 +35,21 @@ class WakingCheckStage(Stage):
         self.friend_message_needs_wake_prefix = self.ctx.astrbot_config[
             "platform_settings"
         ].get("friend_message_needs_wake_prefix", False)
+        # 是否忽略机器人自己发送的消息
+        self.ignore_bot_self_message = self.ctx.astrbot_config["platform_settings"].get(
+            "ignore_bot_self_message", False
+        )
 
     async def process(
         self, event: AstrMessageEvent
     ) -> Union[None, AsyncGenerator[None, None]]:
+        if (
+            self.ignore_bot_self_message
+            and event.get_self_id() == event.get_sender_id()
+        ):
+            # 忽略机器人自己发送的消息
+            event.stop_event()
+            return
         # 设置 sender 身份
         event.message_str = event.message_str.strip()
         for admin_id in self.ctx.astrbot_config["admins_id"]:
@@ -93,6 +105,7 @@ class WakingCheckStage(Stage):
             # filter 需满足 AND 逻辑关系
             passed = True
             permission_not_pass = False
+            permission_filter_raise_error = False
             if len(handler.event_filters) == 0:
                 continue
 
@@ -101,6 +114,7 @@ class WakingCheckStage(Stage):
                     if isinstance(filter, PermissionTypeFilter):
                         if not filter.filter(event, self.ctx.astrbot_config):
                             permission_not_pass = True
+                            permission_filter_raise_error = filter.raise_error
                     else:
                         if not filter.filter(event, self.ctx.astrbot_config):
                             passed = False
@@ -117,13 +131,19 @@ class WakingCheckStage(Stage):
                     break
             if passed:
                 if permission_not_pass:
+                    if not permission_filter_raise_error:
+                        # 跳过
+                        continue
                     if self.no_permission_reply:
                         await event.send(
                             MessageChain().message(
-                                f"ID {event.get_sender_id()} 权限不足。通过 /sid 获取 ID 并请管理员添加。"
+                                f"您(ID: {event.get_sender_id()})的权限不足以使用此指令。通过 /sid 获取 ID 并请管理员添加。"
                             )
                         )
                         await event._post_send()
+                    logger.info(
+                        f"触发 {star_map[handler.handler_module_path].name} 时, 用户(ID={event.get_sender_id()}) 权限不足。"
+                    )
                     event.stop_event()
                     return
 

astrbot/core/platform/astr_message_event.py

@@ -1,7 +1,10 @@
 import abc
 import asyncio
+import re
+import hashlib
+import uuid
 from dataclasses import dataclass
-from typing import List, Union, Optional
+from typing import List, Union, Optional, AsyncGenerator
 
 from astrbot.core.db.po import Conversation
 from astrbot.core.message.components import (
@@ -16,7 +19,7 @@ from astrbot.core.message.components import (
 )
 from astrbot.core.message.message_event_result import MessageEventResult, MessageChain
 from astrbot.core.platform.message_type import MessageType
-from astrbot.core.provider.entites import ProviderRequest
+from astrbot.core.provider.entities import ProviderRequest
 from astrbot.core.utils.metrics import Metric
 from .astrbot_message import AstrBotMessage, Group
 from .platform_metadata import PlatformMetadata
@@ -81,6 +84,9 @@ class AstrMessageEvent(abc.ABC):
     def get_platform_name(self):
         return self.platform_meta.name
 
+    def get_platform_id(self):
+        return self.platform_meta.id
+
     def get_message_str(self) -> str:
         """
         获取消息字符串。
@@ -202,6 +208,32 @@ class AstrMessageEvent(abc.ABC):
         """
         return self.role == "admin"
 
+    async def process_buffer(self, buffer: str, pattern: re.Pattern) -> str:
+        """
+        将消息缓冲区中的文本按指定正则表达式分割后发送至消息平台，作为不支持流式输出平台的Fallback。
+        """
+        while True:
+            match = re.search(pattern, buffer)
+            if not match:
+                break
+            matched_text = match.group()
+            await self.send(MessageChain([Plain(matched_text)]))
+            buffer = buffer[match.end() :]
+            await asyncio.sleep(1.5)  # 限速
+        return buffer
+
+    async def send_streaming(
+        self, generator: AsyncGenerator[MessageChain, None], use_fallback: bool = False
+    ):
+        """发送流式消息到消息平台，使用异步生成器。
+        目前仅支持: telegram，qq official 私聊。
+        Fallback仅支持 aiocqhttp, gewechat。
+        """
+        asyncio.create_task(
+            Metric.upload(msg_event_tick=1, adapter_name=self.platform_meta.name)
+        )
+        self._has_send_oper = True
+
     async def _pre_send(self):
         """调度器会在执行 send() 前调用该方法"""
 
@@ -372,8 +404,13 @@ class AstrMessageEvent(abc.ABC):
         Args:
             message (MessageChain): 消息链，具体使用方式请参考文档。
         """
+        # Leverage BLAKE2 hash function to generate a non-reversible hash of the sender ID for privacy.
+        hash_obj = hashlib.blake2b(self.get_sender_id().encode("utf-8"), digest_size=16)
+        sid = str(uuid.UUID(bytes=hash_obj.digest()))
         asyncio.create_task(
-            Metric.upload(msg_event_tick=1, adapter_name=self.platform_meta.name)
+            Metric.upload(
+                msg_event_tick=1, adapter_name=self.platform_meta.name, sid=sid
+            )
         )
         self._has_send_oper = True
 

astrbot/core/platform/manager.py

@@ -62,6 +62,10 @@ class PlatformManager:
                     from .sources.gewechat.gewechat_platform_adapter import (
                         GewechatPlatformAdapter,  # noqa: F401
                     )
+                case "wechatpadpro":
+                    from .sources.wechatpadpro.wechatpadpro_adapter import (
+                        WeChatPadProAdapter,  # noqa: F401
+                    )
                 case "lark":
                     from .sources.lark.lark_adapter import LarkPlatformAdapter  # noqa: F401
                 case "dingtalk":
@@ -72,6 +76,8 @@ class PlatformManager:
                     from .sources.telegram.tg_adapter import TelegramPlatformAdapter  # noqa: F401
                 case "wecom":
                     from .sources.wecom.wecom_adapter import WecomPlatformAdapter  # noqa: F401
+                case "weixin_official_account":
+                    from .sources.weixin_official_account.weixin_offacc_adapter import WeixinOfficialAccountPlatformAdapter # noqa
         except (ImportError, ModuleNotFoundError) as e:
             logger.error(
                 f"加载平台适配器 {platform_config['type']} 失败，原因：{e}。请检查依赖库是否安装。提示：可以在 管理面板->控制台->安装Pip库 中安装依赖库。"

astrbot/core/platform/platform_metadata.py

@@ -7,6 +7,8 @@ class PlatformMetadata:
     """平台的名称"""
     description: str
     """平台的描述"""
+    id: str = None
+    """平台的唯一标识符，用于配置中识别特定平台"""
 
     default_config_tmpl: dict = None
     """平台的默认配置模板"""

astrbot/core/platform/sources/aiocqhttp/aiocqhttp_message_event.py

@@ -1,9 +1,19 @@
 import asyncio
-import typing
-from astrbot.api.event import AstrMessageEvent, MessageChain
-from astrbot.api.platform import Group, MessageMember
-from astrbot.api.message_components import Plain, Image, Record, At, Node, Nodes
+import re
+from typing import AsyncGenerator, Dict, List
 from aiocqhttp import CQHttp
+from astrbot.api.event import AstrMessageEvent, MessageChain
+from astrbot.api.message_components import (
+    Image,
+    Node,
+    Nodes,
+    Plain,
+    Record,
+    Video,
+    File,
+    BaseMessageComponent,
+)
+from astrbot.api.platform import Group, MessageMember
 
 
 class AiocqhttpMessageEvent(AstrMessageEvent):
@@ -13,44 +23,46 @@ class AiocqhttpMessageEvent(AstrMessageEvent):
         super().__init__(message_str, message_obj, platform_meta, session_id)
         self.bot = bot
 
+    @staticmethod
+    async def _from_segment_to_dict(segment: BaseMessageComponent) -> dict:
+        """修复部分字段"""
+        if isinstance(segment, (Image, Record)):
+            # For Image and Record segments, we convert them to base64
+            bs64 = await segment.convert_to_base64()
+            return {
+                "type": segment.type.lower(),
+                "data": {
+                    "file": f"base64://{bs64}",
+                },
+            }
+        elif isinstance(segment, File):
+            # For File segments, we need to handle the file differently
+            d = await segment.to_dict()
+            return d
+        elif isinstance(segment, Video):
+            d = await segment.to_dict()
+            return d
+        else:
+            # For other segments, we simply convert them to a dict by calling toDict
+            return segment.toDict()
+
     @staticmethod
     async def _parse_onebot_json(message_chain: MessageChain):
         """解析成 OneBot json 格式"""
         ret = []
         for segment in message_chain.chain:
-            d = segment.toDict()
             if isinstance(segment, Plain):
-                d["type"] = "text"
-                d["data"]["text"] = segment.text.strip()
-                # 如果是空文本或者只带换行符的文本，不发送
-                if not d["data"]["text"]:
+                if not segment.text.strip():
                     continue
-            elif isinstance(segment, (Image, Record)):
-                # convert to base64
-                bs64 = await segment.convert_to_base64()
-                d["data"] = {
-                    "file": bs64,
-                }
-            elif isinstance(segment, At):
-                d["data"] = {
-                    "qq": str(segment.qq)  # 转换为字符串
-                }
+            d = await AiocqhttpMessageEvent._from_segment_to_dict(segment)
             ret.append(d)
         return ret
 
     async def send(self, message: MessageChain):
-        ret = await AiocqhttpMessageEvent._parse_onebot_json(message)
-
-        if not ret:
-            return
-
-        send_one_by_one = False
-        for seg in message.chain:
-            if isinstance(seg, (Node, Nodes)):
-                # 转发消息不能和普通消息混在一起发送
-                send_one_by_one = True
-                break
-
+        # 转发消息、文件消息不能和普通消息混在一起发送
+        send_one_by_one = any(
+            isinstance(seg, (Node, Nodes, File)) for seg in message.chain
+        )
         if send_one_by_one:
             for seg in message.chain:
                 if isinstance(seg, (Node, Nodes)):
@@ -60,7 +72,8 @@ class AiocqhttpMessageEvent(AstrMessageEvent):
                         nodes = Nodes([seg])
                         seg = nodes
 
-                    payload = seg.toDict()
+                    payload = await seg.to_dict()
+
                     if self.get_group_id():
                         payload["group_id"] = self.get_group_id()
                         await self.bot.call_action("send_group_forward_msg", **payload)
@@ -69,6 +82,12 @@ class AiocqhttpMessageEvent(AstrMessageEvent):
                         await self.bot.call_action(
                             "send_private_forward_msg", **payload
                         )
+                elif isinstance(seg, File):
+                    d = await AiocqhttpMessageEvent._from_segment_to_dict(seg)
+                    await self.bot.send(
+                        self.message_obj.raw_message,
+                        [d],
+                    )
                 else:
                     await self.bot.send(
                         self.message_obj.raw_message,
@@ -78,10 +97,47 @@ class AiocqhttpMessageEvent(AstrMessageEvent):
                     )
                     await asyncio.sleep(0.5)
         else:
+            ret = await AiocqhttpMessageEvent._parse_onebot_json(message)
+            if not ret:
+                return
             await self.bot.send(self.message_obj.raw_message, ret)
 
         await super().send(message)
 
+    async def send_streaming(
+        self, generator: AsyncGenerator, use_fallback: bool = False
+    ):
+        if not use_fallback:
+            buffer = None
+            async for chain in generator:
+                if not buffer:
+                    buffer = chain
+                else:
+                    buffer.chain.extend(chain.chain)
+            if not buffer:
+                return
+            buffer.squash_plain()
+            await self.send(buffer)
+            return await super().send_streaming(generator, use_fallback)
+
+        buffer = ""
+        pattern = re.compile(r"[^。？！~…]+[。？！~…]+")
+
+        async for chain in generator:
+            if isinstance(chain, MessageChain):
+                for comp in chain.chain:
+                    if isinstance(comp, Plain):
+                        buffer += comp.text
+                        if any(p in buffer for p in "。？！~…"):
+                            buffer = await self.process_buffer(buffer, pattern)
+                    else:
+                        await self.send(MessageChain(chain=[comp]))
+                        await asyncio.sleep(1.5)  # 限速
+
+        if buffer.strip():
+            await self.send(MessageChain([Plain(buffer)]))
+        return await super().send_streaming(generator, use_fallback)
+
     async def get_group(self, group_id=None, **kwargs):
         if isinstance(group_id, str) and group_id.isdigit():
             group_id = int(group_id)
@@ -95,7 +151,7 @@ class AiocqhttpMessageEvent(AstrMessageEvent):
             group_id=group_id,
         )
 
-        members: typing.List[typing.Dict] = await self.bot.call_action(
+        members: List[Dict] = await self.bot.call_action(
             "get_group_member_list",
             group_id=group_id,
         )

astrbot/core/platform/sources/aiocqhttp/aiocqhttp_platform_adapter.py

@@ -1,8 +1,8 @@
-import os
 import time
 import asyncio
 import logging
 import uuid
+import itertools
 from typing import Awaitable, Any
 from aiocqhttp import CQHttp, Event
 from astrbot.api.platform import (
@@ -20,7 +20,6 @@ from .aiocqhttp_message_event import AiocqhttpMessageEvent
 from astrbot.core.platform.astr_message_event import MessageSesion
 from ...register import register_platform_adapter
 from aiocqhttp.exceptions import ActionFailed
-from astrbot.core.utils.io import download_file
 
 
 @register_platform_adapter(
@@ -39,12 +38,18 @@ class AiocqhttpAdapter(Platform):
         self.port = platform_config["ws_reverse_port"]
 
         self.metadata = PlatformMetadata(
-            "aiocqhttp",
-            "适用于 OneBot 标准的消息平台适配器，支持反向 WebSockets。",
+            name="aiocqhttp",
+            description="适用于 OneBot 标准的消息平台适配器，支持反向 WebSockets。",
+            id=self.config.get("id"),
         )
 
         self.bot = CQHttp(
-            use_ws_reverse=True, import_name="aiocqhttp", api_timeout_sec=180
+            use_ws_reverse=True,
+            import_name="aiocqhttp",
+            api_timeout_sec=180,
+            access_token=platform_config.get(
+                "ws_reverse_token"
+            ),  # 以防旧版本配置不存在
         )
 
         @self.bot.on_request()
@@ -98,6 +103,9 @@ class AiocqhttpAdapter(Platform):
 
         if event["post_type"] == "message":
             abm = await self._convert_handle_message_event(event)
+            if abm.sender.user_id == "2854196310":
+                # 屏蔽 QQ 管家的消息
+                return
         elif event["post_type"] == "notice":
             abm = await self._convert_handle_notice_event(event)
         elif event["post_type"] == "request":
@@ -109,7 +117,7 @@ class AiocqhttpAdapter(Platform):
         """OneBot V11 请求类事件"""
         abm = AstrBotMessage()
         abm.self_id = str(event.self_id)
-        abm.sender = MessageMember(user_id=event.user_id, nickname=event.user_id)
+        abm.sender = MessageMember(user_id=str(event.user_id), nickname=event.user_id)
         abm.type = MessageType.OTHER_MESSAGE
         if "group_id" in event and event["group_id"]:
             abm.type = MessageType.GROUP_MESSAGE
@@ -118,6 +126,12 @@ class AiocqhttpAdapter(Platform):
             abm.type = MessageType.FRIEND_MESSAGE
         if self.unique_session and abm.type == MessageType.GROUP_MESSAGE:
             abm.session_id = str(abm.sender.user_id) + "_" + str(event.group_id)
+        else:
+            abm.session_id = (
+                str(event.group_id)
+                if abm.type == MessageType.GROUP_MESSAGE
+                else abm.sender.user_id
+            )
         abm.message_str = ""
         abm.message = []
         abm.timestamp = int(time.time())
@@ -129,7 +143,7 @@ class AiocqhttpAdapter(Platform):
         """OneBot V11 通知类事件"""
         abm = AstrBotMessage()
         abm.self_id = str(event.self_id)
-        abm.sender = MessageMember(user_id=event.user_id, nickname=event.user_id)
+        abm.sender = MessageMember(user_id=str(event.user_id), nickname=event.user_id)
         abm.type = MessageType.OTHER_MESSAGE
         if "group_id" in event and event["group_id"]:
             abm.group_id = str(event.group_id)
@@ -154,7 +168,9 @@ class AiocqhttpAdapter(Platform):
 
         if "sub_type" in event:
             if event["sub_type"] == "poke" and "target_id" in event:
-                abm.message.append(Poke(qq=str(event["target_id"]), type="poke"))  # noqa: F405
+                abm.message.append(
+                    Poke(qq=str(event["target_id"]), type="poke")
+                )  # noqa: F405
 
         return abm
 
@@ -201,82 +217,119 @@ class AiocqhttpAdapter(Platform):
             return
 
         # 按消息段类型类型适配
-        for m in event.message:
-            t = m["type"]
+        for t, m_group in itertools.groupby(event.message, key=lambda x: x["type"]):
             a = None
             if t == "text":
-                message_str += m["data"]["text"].strip()
-                a = ComponentTypes[t](**m["data"])  # noqa: F405
+                current_text = "".join(m["data"]["text"] for m in m_group).strip()
+                message_str += current_text
+                a = ComponentTypes[t](text=current_text)  # noqa: F405
                 abm.message.append(a)
 
             elif t == "file":
-                if m["data"].get("url") and m["data"].get("url").startswith("http"):
-                    # Lagrange
-                    logger.info("guessing lagrange")
+                for m in m_group:
+                    if m["data"].get("url") and m["data"].get("url").startswith("http"):
+                        # Lagrange
+                        logger.info("guessing lagrange")
+                        file_name = m["data"].get("file_name", "file")
+                        abm.message.append(File(name=file_name, url=m["data"]["url"]))
+                    else:
+                        try:
+                            # Napcat
+                            ret = None
+                            if abm.type == MessageType.GROUP_MESSAGE:
+                                ret = await self.bot.call_action(
+                                    action="get_group_file_url",
+                                    file_id=event.message[0]["data"]["file_id"],
+                                    group_id=event.group_id,
+                                )
+                            elif abm.type == MessageType.FRIEND_MESSAGE:
+                                ret = await self.bot.call_action(
+                                    action="get_private_file_url",
+                                    file_id=event.message[0]["data"]["file_id"],
+                                )
+                            if ret and "url" in ret:
+                                file_url = ret["url"]  # https
+                                a = File(name="", url=file_url)
+                                abm.message.append(a)
+                            else:
+                                logger.error(f"获取文件失败: {ret}")
 
-                    file_name = m["data"].get("file_name", "file")
-                    path = os.path.join("data/temp", file_name)
-                    await download_file(m["data"]["url"], path)
-
-                    m["data"] = {"file": path, "name": file_name}
-                    a = ComponentTypes[t](**m["data"])  # noqa: F405
-                    abm.message.append(a)
-
-                else:
-                    try:
-                        # Napcat, LLBot
-                        ret = await self.bot.call_action(
-                            action="get_file",
-                            file_id=event.message[0]["data"]["file_id"],
-                        )
-                        if not ret.get("file", None):
-                            raise ValueError(f"无法解析文件响应: {ret}")
-                        if not os.path.exists(ret["file"]):
-                            raise FileNotFoundError(
-                                f"文件不存在或者权限问题: {ret['file']}。如果您使用 Docker 部署了 AstrBot 或者消息协议端(Napcat等),请先映射路径。如果路径在 /root 目录下，请用 sudo 打开 AstrBot"
-                            )
-
-                        m["data"] = {"file": ret["file"], "name": ret["file_name"]}
-                        a = ComponentTypes[t](**m["data"])  # noqa: F405
-                        abm.message.append(a)
-                    except ActionFailed as e:
-                        logger.error(f"获取文件失败: {e}，此消息段将被忽略。")
-                    except BaseException as e:
-                        logger.error(f"获取文件失败: {e}，此消息段将被忽略。")
+                        except ActionFailed as e:
+                            logger.error(f"获取文件失败: {e}，此消息段将被忽略。")
+                        except BaseException as e:
+                            logger.error(f"获取文件失败: {e}，此消息段将被忽略。")
 
             elif t == "reply":
-                if not get_reply:
-                    a = ComponentTypes[t](**m["data"])  # noqa: F405
-                    abm.message.append(a)
-                else:
-                    try:
-                        reply_event_data = await self.bot.call_action(
-                            action="get_msg",
-                            message_id=int(m["data"]["id"]),
-                        )
-                        abm_reply = await self._convert_handle_message_event(
-                            Event.from_payload(reply_event_data), get_reply=False
-                        )
-
-                        reply_seg = Reply(
-                            id=abm_reply.message_id,
-                            chain=abm_reply.message,
-                            sender_id=abm_reply.sender.user_id,
-                            sender_nickname=abm_reply.sender.nickname,
-                            time=abm_reply.timestamp,
-                            message_str=abm_reply.message_str,
-                            text=abm_reply.message_str,  # for compatibility
-                            qq=abm_reply.sender.user_id,  # for compatibility
-                        )
-
-                        abm.message.append(reply_seg)
-                    except BaseException as e:
-                        logger.error(f"获取引用消息失败: {e}。")
+                for m in m_group:
+                    if not get_reply:
                         a = ComponentTypes[t](**m["data"])  # noqa: F405
                         abm.message.append(a)
+                    else:
+                        try:
+                            reply_event_data = await self.bot.call_action(
+                                action="get_msg",
+                                message_id=int(m["data"]["id"]),
+                            )
+                            abm_reply = await self._convert_handle_message_event(
+                                Event.from_payload(reply_event_data), get_reply=False
+                            )
+
+                            reply_seg = Reply(
+                                id=abm_reply.message_id,
+                                chain=abm_reply.message,
+                                sender_id=abm_reply.sender.user_id,
+                                sender_nickname=abm_reply.sender.nickname,
+                                time=abm_reply.timestamp,
+                                message_str=abm_reply.message_str,
+                                text=abm_reply.message_str,  # for compatibility
+                                qq=abm_reply.sender.user_id,  # for compatibility
+                            )
+
+                            abm.message.append(reply_seg)
+                        except BaseException as e:
+                            logger.error(f"获取引用消息失败: {e}。")
+                            a = ComponentTypes[t](**m["data"])  # noqa: F405
+                            abm.message.append(a)
+            elif t == "at":
+                first_at_self_processed = False
+
+                for m in m_group:
+                    try:
+                        if m["data"]["qq"] == "all":
+                            abm.message.append(At(qq="all", name="全体成员"))
+                            continue
+
+                        at_info = await self.bot.call_action(
+                            action="get_stranger_info",
+                            user_id=int(m["data"]["qq"]),
+                        )
+                        if at_info:
+                            nickname = at_info.get("nick", "")
+                            is_at_self = str(m["data"]["qq"]) in {abm.self_id, "all"}
+
+                            abm.message.append(
+                                At(
+                                    qq=m["data"]["qq"],
+                                    name=nickname,
+                                )
+                            )
+
+                            if is_at_self and not first_at_self_processed:
+                                # 第一个@是机器人，不添加到message_str
+                                first_at_self_processed = True
+                            else:
+                                # 非第一个@机器人或@其他用户，添加到message_str
+                                message_str += f" @{nickname} "
+                        else:
+                            abm.message.append(At(qq=str(m["data"]["qq"]), name=""))
+                    except ActionFailed as e:
+                        logger.error(f"获取 @ 用户信息失败: {e}，此消息段将被忽略。")
+                    except BaseException as e:
+                        logger.error(f"获取 @ 用户信息失败: {e}，此消息段将被忽略。")
             else:
-                a = ComponentTypes[t](**m["data"])  # noqa: F405
-                abm.message.append(a)
+                for m in m_group:
+                    a = ComponentTypes[t](**m["data"])  # noqa: F405
+                    abm.message.append(a)
 
         abm.timestamp = int(time.time())
         abm.message_str = message_str

astrbot/core/platform/sources/dingtalk/dingtalk_adapter.py

@@ -1,4 +1,5 @@
 import asyncio
+import os
 import uuid
 import aiohttp
 import dingtalk_stream
@@ -19,6 +20,7 @@ from ...register import register_platform_adapter
 from astrbot import logger
 from dingtalk_stream import AckMessage
 from astrbot.core.utils.io import download_file
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 
 class MyEventHandler(dingtalk_stream.EventHandler):
@@ -73,8 +75,9 @@ class DingtalkPlatformAdapter(Platform):
 
     def meta(self) -> PlatformMetadata:
         return PlatformMetadata(
-            "dingtalk",
-            "钉钉机器人官方 API 适配器",
+            name="dingtalk",
+            description="钉钉机器人官方 API 适配器",
+            id=self.config.get("id"),
         )
 
     async def convert_msg(
@@ -151,7 +154,8 @@ class DingtalkPlatformAdapter(Platform):
             "downloadCode": download_code,
             "robotCode": robot_code,
         }
-        f_path = f"data/dingtalk_file_{uuid.uuid4()}.{ext}"
+        temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+        f_path = os.path.join(temp_dir, f"dingtalk_file_{uuid.uuid4()}.{ext}")
         async with aiohttp.ClientSession() as session:
             async with session.post(
                 "https://api.dingtalk.com/v1.0/robot/messageFiles/download",

astrbot/core/platform/sources/dingtalk/dingtalk_event.py

@@ -24,7 +24,11 @@ class DingtalkMessageEvent(AstrMessageEvent):
             if isinstance(segment, Comp.Plain):
                 segment.text = segment.text.strip()
                 await asyncio.get_event_loop().run_in_executor(
-                    None, client.reply_markdown, "AstrBot", segment.text, self.message_obj.raw_message
+                    None,
+                    client.reply_markdown,
+                    "AstrBot",
+                    segment.text,
+                    self.message_obj.raw_message,
                 )
             elif isinstance(segment, Comp.Image):
                 markdown_str = ""
@@ -56,3 +60,16 @@ class DingtalkMessageEvent(AstrMessageEvent):
     async def send(self, message: MessageChain):
         await self.send_with_client(self.client, message)
         await super().send(message)
+
+    async def send_streaming(self, generator, use_fallback: bool = False):
+        buffer = None
+        async for chain in generator:
+            if not buffer:
+                buffer = chain
+            else:
+                buffer.chain.extend(chain.chain)
+        if not buffer:
+            return
+        buffer.squash_plain()
+        await self.send(buffer)
+        return await super().send_streaming(generator, use_fallback)

astrbot/core/platform/sources/gewechat/client.py

@@ -3,6 +3,7 @@ import base64
 import datetime
 import os
 import re
+import uuid
 import threading
 
 import aiohttp
@@ -14,6 +15,7 @@ from astrbot.api.message_components import Plain, Image, At, Record, Video
 from astrbot.api.platform import AstrBotMessage, MessageMember, MessageType
 from astrbot.core.utils.io import download_image_by_url
 from .downloader import GeweDownloader
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 try:
     from .xml_data_parser import GeweDataParser
@@ -63,7 +65,7 @@ class SimpleGewechatClient:
             "/astrbot-gewechat/callback", view_func=self._callback, methods=["POST"]
         )
         self.server.add_url_rule(
-            "/astrbot-gewechat/file/<file_id>",
+            "/astrbot-gewechat/file/<file_token>",
             view_func=self._handle_file,
             methods=["GET"],
         )
@@ -81,6 +83,11 @@ class SimpleGewechatClient:
 
         self.shutdown_event = asyncio.Event()
 
+        self.staged_files = {}
+        """存储了允许外部访问的文件列表。auth_token: file_path。通过 register_file 方法注册。"""
+
+        self.lock = asyncio.Lock()
+
     async def get_token_id(self):
         """获取 Gewechat Token。"""
         async with aiohttp.ClientSession() as session:
@@ -143,18 +150,25 @@ class SimpleGewechatClient:
         content = d["Content"]["string"]  # 消息内容
 
         at_me = False
+        at_wxids = []
         if "@chatroom" in from_user_name:
             abm.type = MessageType.GROUP_MESSAGE
             _t = content.split(":\n")
             user_id = _t[0]
             content = _t[1]
+            # at
+            msg_source = d["MsgSource"]
             if "\u2005" in content:
                 # at
                 # content = content.split('\u2005')[1]
                 content = re.sub(r"@[^\u2005]*\u2005", "", content)
+                at_wxids = re.findall(
+                    r"<atuserlist><!\[CDATA\[.*?(?:,|\b)([^,]+?)(?=,|\]\]></atuserlist>)",
+                    msg_source,
+                )
+
             abm.group_id = from_user_name
-            # at
-            msg_source = d["MsgSource"]
+
             if (
                 f"<atuserlist><![CDATA[,{abm.self_id}]]>" in msg_source
                 or f"<atuserlist><![CDATA[{abm.self_id}]]>" in msg_source
@@ -167,13 +181,12 @@ class SimpleGewechatClient:
             user_id = from_user_name
 
         # 检查消息是否由自己发送，若是则忽略
-        if user_id == abm.self_id:
-            logger.info("忽略自己发送的消息")
-            return None
+        # 已经有可配置项专门配置是否需要响应自己的消息，因此这里注释掉。
+        # if user_id == abm.self_id:
+        #     logger.info("忽略自己发送的消息")
+        #     return None
 
         abm.message = []
-        if at_me:
-            abm.message.insert(0, At(qq=abm.self_id))
 
         # 解析用户真实名字
         user_real_name = "unknown"
@@ -197,7 +210,19 @@ class SimpleGewechatClient:
             else:
                 user_real_name = self.userrealnames[abm.group_id][user_id]
         else:
-            user_real_name = d.get("PushContent", "unknown : ").split(" : ")[0]
+            try:
+                info = (await self.get_user_or_group_info(user_id))["data"][0]
+                user_real_name = info["nickName"]
+            except Exception as e:
+                logger.debug(f"获取用户 {user_id} 昵称失败: {e}")
+                user_real_name = user_id
+
+        if at_me:
+            abm.message.insert(0, At(qq=abm.self_id, name=self.nickname))
+        for wxid in at_wxids:
+            # 群聊里 At 其他人的列表
+            _username = self.userrealnames.get(abm.group_id, {}).get(wxid, wxid)
+            abm.message.append(At(qq=wxid, name=_username))
 
         abm.sender = MessageMember(user_id, user_real_name)
         abm.raw_message = d
@@ -226,7 +251,10 @@ class SimpleGewechatClient:
                 # 语音消息
                 if "ImgBuf" in d and "buffer" in d["ImgBuf"]:
                     voice_data = base64.b64decode(d["ImgBuf"]["buffer"])
-                    file_path = f"data/temp/gewe_voice_{abm.message_id}.silk"
+                    temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+                    file_path = os.path.join(
+                        temp_dir, f"gewe_voice_{abm.message_id}.silk"
+                    )
 
                     async with await anyio.open_file(file_path, "wb") as f:
                         await f.write(voice_data)
@@ -248,9 +276,12 @@ class SimpleGewechatClient:
                 logger.info("消息类型(48)：地理位置")
             case 49:  # 公众号/文件/小程序/引用/转账/红包/视频号/群聊邀请
                 data_parser = GeweDataParser(content, abm.group_id == "")
-                abm_data = data_parser.parse_mutil_49()
-                if abm_data:
-                    abm.message.append(abm_data)
+                segments = data_parser.parse_mutil_49()
+                if segments:
+                    abm.message.extend(segments)
+                    for seg in segments:
+                        if isinstance(seg, Plain):
+                            abm.message_str += seg.text
             case 51:  # 帐号消息同步?
                 logger.info("消息类型(51)：帐号消息同步？")
             case 10000:  # 被踢出群聊/更换群主/修改群名称
@@ -289,9 +320,33 @@ class SimpleGewechatClient:
 
         return quart.jsonify({"r": "AstrBot ACK"})
 
-    async def _handle_file(self, file_id):
-        file_path = f"data/temp/{file_id}"
-        return await quart.send_file(file_path)
+    async def _register_file(self, file_path: str) -> str:
+        """向 AstrBot 回调服务器 注册一个允许外部访问的文件。
+
+        Args:
+            file_path (str): 文件路径。
+        Returns:
+            str: 返回一个 auth_token，文件路径为 file_path。通过 /astrbot-gewechat/file/auth_token 得到文件。
+        """
+        async with self.lock:
+            if not os.path.exists(file_path):
+                raise Exception(f"文件不存在: {file_path}")
+
+            file_token = str(uuid.uuid4())
+            self.staged_files[file_token] = file_path
+            return file_token
+
+    async def _handle_file(self, file_token):
+        async with self.lock:
+            if file_token not in self.staged_files:
+                logger.warning(f"请求的文件 {file_token} 不存在。")
+                return quart.abort(404)
+            if not os.path.exists(self.staged_files[file_token]):
+                logger.warning(f"请求的文件 {self.staged_files[file_token]} 不存在。")
+                return quart.abort(404)
+            file_path = self.staged_files[file_token]
+            self.staged_files.pop(file_token, None)
+            return await quart.send_file(file_path)
 
     async def _set_callback_url(self):
         logger.info("设置回调，请等待...")
@@ -407,8 +462,10 @@ class SimpleGewechatClient:
             retry_cnt -= 1
 
             # 需要验证码
-            if os.path.exists("data/temp/gewe_code"):
-                with open("data/temp/gewe_code", "r") as f:
+            temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+            code_file_path = os.path.join(temp_dir, "gewe_code")
+            if os.path.exists(code_file_path):
+                with open(code_file_path, "r") as f:
                     code = f.read().strip()
                     if not code:
                         logger.warning(
@@ -419,9 +476,9 @@ class SimpleGewechatClient:
                     payload["captchCode"] = code
                     logger.info(f"使用验证码: {code}")
                     try:
-                        os.remove("data/temp/gewe_code")
+                        os.remove(code_file_path)
                     except Exception:
-                        logger.warning("删除验证码文件 data/temp/gewe_code 失败。")
+                        logger.warning(f"删除验证码文件 {code_file_path} 失败。")
 
             async with aiohttp.ClientSession() as session:
                 async with session.post(
@@ -441,17 +498,18 @@ class SimpleGewechatClient:
                             "此次登录需要安全验证码，请在管理面板聊天页输入 /gewe_code 验证码 来验证，如 /gewe_code 123456"
                         )
                     else:
-                        status = json_blob["data"]["status"]
-                        nickname = json_blob["data"].get("nickName", "")
-                        if status == 1:
-                            logger.info(f"等待确认...{nickname}")
-                        elif status == 2:
-                            logger.info(f"绿泡泡平台登录成功: {nickname}")
-                            break
-                        elif status == 0:
-                            logger.info("等待扫码...")
-                        else:
-                            logger.warning(f"未知状态: {status}")
+                        if "status" in json_blob["data"]:
+                            status = json_blob["data"]["status"]
+                            nickname = json_blob["data"].get("nickName", "")
+                            if status == 1:
+                                logger.info(f"等待确认...{nickname}")
+                            elif status == 2:
+                                logger.info(f"绿泡泡平台登录成功: {nickname}")
+                                break
+                            elif status == 0:
+                                logger.info("等待扫码...")
+                            else:
+                                logger.warning(f"未知状态: {status}")
             await asyncio.sleep(5)
 
         if appid:

astrbot/core/platform/sources/gewechat/gewechat_event.py

@@ -1,9 +1,12 @@
+import asyncio
+import re
 import wave
 import uuid
 import traceback
 import os
 
-from astrbot.core.utils.io import save_temp_img, download_file
+from typing import AsyncGenerator
+from astrbot.core.utils.io import download_file
 from astrbot.core.utils.tencent_record_helper import wav_to_tencent_silk
 from astrbot.api import logger
 from astrbot.api.event import AstrMessageEvent, MessageChain
@@ -18,6 +21,7 @@ from astrbot.api.message_components import (
     WechatEmoji as Emoji,
 )
 from .client import SimpleGewechatClient
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 
 def get_wav_duration(file_path):
@@ -80,15 +84,9 @@ class GewechatPlatformEvent(AstrMessageEvent):
 
             elif isinstance(comp, Image):
                 img_path = await comp.convert_to_file_path()
-
-                # 检查 record_path 是否在 data/temp 目录中
-                temp_directory = os.path.abspath("data/temp")
-                if os.path.commonpath([temp_directory, img_path]) != temp_directory:
-                    with open(img_path, "rb") as f:
-                        img_path = save_temp_img(f.read())
-
-                file_id = os.path.basename(img_path)
-                img_url = f"{client.file_server_url}/{file_id}"
+                # 为了安全，向 AstrBot 回调服务注册可被 gewechat 访问的文件，并获得文件 token
+                token = await client._register_file(img_path)
+                img_url = f"{client.file_server_url}/{token}"
                 logger.debug(f"gewe callback img url: {img_url}")
                 await client.post_image(to_wxid, img_url)
             elif isinstance(comp, Video):
@@ -107,20 +105,33 @@ class GewechatPlatformEvent(AstrMessageEvent):
 
                     video_url = comp.file
                     # 根据 url 下载视频
-                    video_filename = f"{uuid.uuid4()}.mp4"
-                    video_path = f"data/temp/{video_filename}"
-                    await download_file(video_url, video_path)
+                    if video_url.startswith("http"):
+                        video_filename = f"{uuid.uuid4()}.mp4"
+                        temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+                        video_path = os.path.join(temp_dir, video_filename)
+                        await download_file(video_url, video_path)
+                    else:
+                        video_path = video_url
+
+                    video_token = await client._register_file(video_path)
+                    video_callback_url = f"{client.file_server_url}/{video_token}"
 
                     # 获取视频第一帧
-                    thumb_path = f"data/temp/{uuid.uuid4()}.jpg"
+                    temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+                    thumb_path = os.path.join(
+                        temp_dir, f"gewechat_video_thumb_{uuid.uuid4()}.jpg"
+                    )
+
+                    video_path = video_path.replace(" ", "\\ ")
                     try:
                         ff = FFmpeg()
-                        command = f'-i "{video_path}" -ss 0 -vframes 1 "{thumb_path}"'
+                        command = f"-i {video_path} -ss 0 -vframes 1 {thumb_path}"
                         ff.options(command)
-                        thumb_file_id = os.path.basename(thumb_path)
-                        thumb_url = f"{client.file_server_url}/{thumb_file_id}"
+                        thumb_token = await client._register_file(thumb_path)
+                        thumb_url = f"{client.file_server_url}/{thumb_token}"
                     except Exception as e:
                         logger.error(f"获取视频第一帧失败: {e}")
+
                     # 获取视频时长
                     try:
                         from pyffmpeg import FFprobe
@@ -135,15 +146,12 @@ class GewechatPlatformEvent(AstrMessageEvent):
                         logger.error(f"获取时长失败: {e}")
                         video_duration = 10
 
-                    file_id = os.path.basename(video_path)
-                    video_url = f"{client.file_server_url}/{file_id}"
+                    # 发送视频
                     await client.post_video(
-                        to_wxid, video_url, thumb_url, video_duration
+                        to_wxid, video_callback_url, thumb_url, video_duration
                     )
 
-                    # 删除临时视频和缩略图文件
-                    if os.path.exists(video_path):
-                        os.remove(video_path)
+                    # 删除临时缩略图文件
                     if os.path.exists(thumb_path):
                         os.remove(thumb_path)
             elif isinstance(comp, Record):
@@ -151,7 +159,8 @@ class GewechatPlatformEvent(AstrMessageEvent):
                 record_url = comp.file
                 record_path = await comp.convert_to_file_path()
 
-                silk_path = f"data/temp/{uuid.uuid4()}.silk"
+                temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+                silk_path = os.path.join(temp_dir, f"{uuid.uuid4()}.silk")
                 try:
                     duration = await wav_to_tencent_silk(record_path, silk_path)
                 except Exception as e:
@@ -160,8 +169,8 @@ class GewechatPlatformEvent(AstrMessageEvent):
                 logger.info("Silk 语音文件格式转换至: " + record_path)
                 if duration == 0:
                     duration = get_wav_duration(record_path)
-                file_id = os.path.basename(silk_path)
-                record_url = f"{client.file_server_url}/{file_id}"
+                token = await client._register_file(silk_path)
+                record_url = f"{client.file_server_url}/{token}"
                 logger.debug(f"gewe callback record url: {record_url}")
                 await client.post_voice(to_wxid, record_url, duration * 1000)
             elif isinstance(comp, File):
@@ -170,14 +179,17 @@ class GewechatPlatformEvent(AstrMessageEvent):
                 if file_path.startswith("file:///"):
                     file_path = file_path[8:]
                 elif file_path.startswith("http"):
-                    await download_file(file_path, f"data/temp/{file_name}")
+                    temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+                    temp_file_path = os.path.join(temp_dir, file_name)
+                    await download_file(file_path, temp_file_path)
+                    file_path = temp_file_path
                 else:
                     file_path = file_path
 
-                file_id = os.path.basename(file_path)
-                file_url = f"{client.file_server_url}/{file_id}"
+                token = await client._register_file(file_path)
+                file_url = f"{client.file_server_url}/{token}"
                 logger.debug(f"gewe callback file url: {file_url}")
-                await client.post_file(to_wxid, file_url, file_id)
+                await client.post_file(to_wxid, file_url, file_name)
             elif isinstance(comp, Emoji):
                 await client.post_emoji(to_wxid, comp.md5, comp.md5_len, comp.cdnurl)
             elif isinstance(comp, At):
@@ -216,3 +228,37 @@ class GewechatPlatformEvent(AstrMessageEvent):
             group_owner=data.get("chatRoomOwner"),
             members=members,
         )
+
+    async def send_streaming(
+        self, generator: AsyncGenerator, use_fallback: bool = False
+    ):
+        if not use_fallback:
+            buffer = None
+            async for chain in generator:
+                if not buffer:
+                    buffer = chain
+                else:
+                    buffer.chain.extend(chain.chain)
+            if not buffer:
+                return
+            buffer.squash_plain()
+            await self.send(buffer)
+            return await super().send_streaming(generator, use_fallback)
+
+        buffer = ""
+        pattern = re.compile(r"[^。？！~…]+[。？！~…]+")
+
+        async for chain in generator:
+            if isinstance(chain, MessageChain):
+                for comp in chain.chain:
+                    if isinstance(comp, Plain):
+                        buffer += comp.text
+                        if any(p in buffer for p in "。？！~…"):
+                            buffer = await self.process_buffer(buffer, pattern)
+                    else:
+                        await self.send(MessageChain(chain=[comp]))
+                        await asyncio.sleep(1.5)  # 限速
+
+        if buffer.strip():
+            await self.send(MessageChain([Plain(buffer)]))
+        return await super().send_streaming(generator, use_fallback)

astrbot/core/platform/sources/gewechat/gewechat_platform_adapter.py

@@ -60,13 +60,17 @@ class GewechatPlatformAdapter(Platform):
     @override
     def meta(self) -> PlatformMetadata:
         return PlatformMetadata(
-            "gewechat",
-            "基于 gewechat 的 Wechat 适配器",
+            name="gewechat",
+            description="基于 gewechat 的 Wechat 适配器",
+            id=self.config.get("id"),
         )
 
     async def terminate(self):
         self.client.shutdown_event.set()
-        await self.client.server.shutdown()
+        try:
+            await self.client.server.shutdown()
+        except Exception as _:
+            pass
         logger.info("Gewechat 适配器已被优雅地关闭。")
 
     async def logout(self):

astrbot/core/platform/sources/gewechat/xml_data_parser.py

@@ -1,6 +1,11 @@
 from defusedxml import ElementTree as eT
 from astrbot.api import logger
-from astrbot.api.message_components import WechatEmoji as Emoji, Reply, Plain
+from astrbot.api.message_components import (
+    WechatEmoji as Emoji,
+    Reply,
+    Plain,
+    BaseMessageComponent,
+)
 
 
 class GeweDataParser:
@@ -11,7 +16,7 @@ class GeweDataParser:
     def _format_to_xml(self):
         return eT.fromstring(self.data)
 
-    def parse_mutil_49(self):
+    def parse_mutil_49(self) -> list[BaseMessageComponent] | None:
         appmsg_type = self._format_to_xml().find(".//appmsg/type")
         if appmsg_type is None:
             return
@@ -34,13 +39,18 @@ class GeweDataParser:
         except Exception as e:
             logger.error(f"gewechat: parse_emoji failed, {e}")
 
-    def parse_reply(self) -> Reply | None:
+    def parse_reply(self) -> list[Reply, Plain] | None:
+        """解析引用消息
+
+        Returns:
+            list[Reply, Plain]: 一个包含两个元素的列表。Reply 消息对象和引用者说的文本内容。微信平台下引用消息时只能发送文本消息。
+        """
         try:
             replied_id = -1
             replied_uid = 0
             replied_nickname = ""
-            replied_content = ""
-            content = ""
+            replied_content = ""  # 被引用者说的内容
+            content = ""  # 引用者说的内容
 
             root = self._format_to_xml()
             refermsg = root.find(".//refermsg")
@@ -57,22 +67,44 @@ class GeweDataParser:
                 if displayname is not None:
                     replied_nickname = displayname.text
                 if refermsg_content is not None:
-                    replied_content = refermsg_content.text
+                    # 处理引用嵌套，包括嵌套公众号消息
+                    if refermsg_content.text.startswith(
+                        "<msg>"
+                    ) or refermsg_content.text.startswith("<?xml"):
+                        try:
+                            logger.debug("gewechat: Reference message is nested")
+                            refer_root = eT.fromstring(refermsg_content.text)
+                            img = refer_root.find("img")
+                            if img is not None:
+                                replied_content = "[图片]"
+                            else:
+                                app_msg = refer_root.find("appmsg")
+                                refermsg_content_title = app_msg.find("title")
+                                logger.debug(
+                                    f"gewechat: Reference message nesting: {refermsg_content_title.text}"
+                                )
+                                replied_content = refermsg_content_title.text
+                        except Exception as e:
+                            logger.error(f"gewechat: nested failed, {e}")
+                            # 处理异常情况
+                            replied_content = refermsg_content.text
+                    else:
+                        replied_content = refermsg_content.text
 
                 # 提取引用者说的内容
             title = root.find(".//appmsg/title")
             if title is not None:
                 content = title.text
 
-            r = Reply(
+            reply_seg = Reply(
                 id=replied_id,
-                chain=[Plain(content)],
+                chain=[Plain(replied_content)],
                 sender_id=replied_uid,
                 sender_nickname=replied_nickname,
-                sender_str=replied_content,
-                message_str=content,
+                message_str=replied_content,
             )
-            return r
+            plain_seg = Plain(content)
+            return [reply_seg, plain_seg]
 
         except Exception as e:
             logger.error(f"gewechat: parse_reply failed, {e}")

astrbot/core/platform/sources/lark/lark_adapter.py

@@ -2,6 +2,7 @@ import base64
 import asyncio
 import json
 import re
+import uuid
 import astrbot.api.message_components as Comp
 
 from astrbot.api.platform import (
@@ -66,12 +67,47 @@ class LarkPlatformAdapter(Platform):
     async def send_by_session(
         self, session: MessageSesion, message_chain: MessageChain
     ):
-        raise NotImplementedError("Lark 适配器不支持 send_by_session")
+        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]
+        else:
+            id_type = "open_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()
+        )
+
+        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:
         return PlatformMetadata(
-            "lark",
-            "飞书机器人官方 API 适配器",
+            name="lark",
+            description="飞书机器人官方 API 适配器",
+            id=self.config.get("id"),
         )
 
     async def convert_msg(self, event: lark.im.v1.P2ImMessageReceiveV1):
@@ -165,7 +201,10 @@ class LarkPlatformAdapter(Platform):
             else:
                 abm.session_id = abm.sender.user_id
         else:
-            abm.session_id = abm.sender.user_id
+            if abm.type == MessageType.GROUP_MESSAGE:
+                abm.session_id = f"{abm.sender.user_id}%{abm.group_id}"  # 也保留群组id
+            else:
+                abm.session_id = abm.sender.user_id
 
         logger.debug(abm)
         await self.handle_msg(abm)

astrbot/core/platform/sources/lark/lark_event.py

@@ -1,12 +1,16 @@
 import json
+import os
 import uuid
+import base64
 import lark_oapi as lark
+from io import BytesIO
 from typing import List
 from astrbot.api.event import AstrMessageEvent, MessageChain
 from astrbot.api.message_components import Plain, Image as AstrBotImage, At
 from astrbot.core.utils.io import download_image_by_url
 from lark_oapi.api.im.v1 import *
 from astrbot import logger
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 
 class LarkMessageEvent(AstrMessageEvent):
@@ -27,22 +31,33 @@ class LarkMessageEvent(AstrMessageEvent):
                 _stage.append({"tag": "at", "user_id": comp.qq, "style": []})
             elif isinstance(comp, AstrBotImage):
                 file_path = ""
+                image_file = None
+
                 if comp.file and comp.file.startswith("file:///"):
                     file_path = comp.file.replace("file:///", "")
                 elif comp.file and comp.file.startswith("http"):
                     image_file_path = await download_image_by_url(comp.file)
                     file_path = image_file_path
                 elif comp.file and comp.file.startswith("base64://"):
-                    pass
+                    base64_str = comp.file.removeprefix("base64://")
+                    image_data = base64.b64decode(base64_str)
+                    # save as temp file
+                    temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+                    file_path = os.path.join(temp_dir, f"{uuid.uuid4()}_test.jpg")
+                    with open(file_path, "wb") as f:
+                        f.write(BytesIO(image_data).getvalue())
                 else:
                     file_path = comp.file
 
+                if image_file is None:
+                    image_file = open(file_path, "rb")
+
                 request = (
                     CreateImageRequest.builder()
                     .request_body(
                         CreateImageRequestBody.builder()
                         .image_type("message")
-                        .image(open(file_path, "rb"))
+                        .image(image_file)
                         .build()
                     )
                     .build()
@@ -51,7 +66,7 @@ class LarkMessageEvent(AstrMessageEvent):
                 if not response.success():
                     logger.error(f"无法上传飞书图片({response.code}): {response.msg}")
                 image_key = response.data.image_key
-                print(image_key)
+                logger.debug(image_key)
                 ret.append(_stage)
                 ret.append([{"tag": "img", "image_key": image_key}])
                 _stage.clear()
@@ -91,3 +106,16 @@ class LarkMessageEvent(AstrMessageEvent):
             logger.error(f"回复飞书消息失败({response.code}): {response.msg}")
 
         await super().send(message)
+
+    async def send_streaming(self, generator, use_fallback: bool = False):
+        buffer = None
+        async for chain in generator:
+            if not buffer:
+                buffer = chain
+            else:
+                buffer.chain.extend(chain.chain)
+        if not buffer:
+            return
+        buffer.squash_plain()
+        await self.send(buffer)
+        return await super().send_streaming(generator, use_fallback)

astrbot/core/platform/sources/qqofficial/qqofficial_message_event.py

@@ -2,6 +2,7 @@ import botpy
 import botpy.message
 import botpy.types
 import botpy.types.message
+import asyncio
 from astrbot.core.utils.io import file_to_base64, download_image_by_url
 from astrbot.api.event import AstrMessageEvent, MessageChain
 from astrbot.api.platform import AstrBotMessage, PlatformMetadata
@@ -9,6 +10,8 @@ from astrbot.api.message_components import Plain, Image
 from botpy import Client
 from botpy.http import Route
 from astrbot.api import logger
+from botpy.types import message
+import random
 
 
 class QQOfficialMessageEvent(AstrMessageEvent):
@@ -30,8 +33,45 @@ class QQOfficialMessageEvent(AstrMessageEvent):
         else:
             self.send_buffer.chain.extend(message.chain)
 
-    async def _post_send(self):
-        """QQ 官方 API 仅支持回复一次"""
+    async def send_streaming(self, generator, use_fallback: bool = False):
+        """流式输出仅支持消息列表私聊"""
+        stream_payload = {"state": 1, "id": None, "index": 0, "reset": False}
+        last_edit_time = 0  # 上次编辑消息的时间
+        throttle_interval = 1  # 编辑消息的间隔时间 (秒)
+        try:
+            async for chain in generator:
+                source = self.message_obj.raw_message
+                if not self.send_buffer:
+                    self.send_buffer = chain
+                else:
+                    self.send_buffer.chain.extend(chain.chain)
+
+                if isinstance(source, botpy.message.C2CMessage):
+                    # 真流式传输
+                    current_time = asyncio.get_event_loop().time()
+                    time_since_last_edit = current_time - last_edit_time
+
+                    if time_since_last_edit >= throttle_interval:
+                        ret = await self._post_send(stream=stream_payload)
+                        stream_payload["index"] += 1
+                        stream_payload["id"] = ret["id"]
+                        last_edit_time = asyncio.get_event_loop().time()
+
+            if isinstance(source, botpy.message.C2CMessage):
+                # 结束流式对话，并且传输 buffer 中剩余的消息
+                stream_payload["state"] = 10
+                ret = await self._post_send(stream=stream_payload)
+
+        except Exception as e:
+            logger.error(f"发送流式消息时出错: {e}", exc_info=True)
+            self.send_buffer = None
+
+        return await super().send_streaming(generator, use_fallback)
+
+    async def _post_send(self, stream: dict = None):
+        if not self.send_buffer:
+            return
+
         source = self.message_obj.raw_message
         assert isinstance(
             source,
@@ -57,6 +97,9 @@ class QQOfficialMessageEvent(AstrMessageEvent):
             "msg_id": self.message_obj.message_id,
         }
 
+        if not isinstance(source, (botpy.message.Message, botpy.message.DirectMessage)):
+            payload["msg_seq"] = random.randint(1, 10000)
+
         match type(source):
             case botpy.message.GroupMessage:
                 if image_base64:
@@ -65,7 +108,7 @@ class QQOfficialMessageEvent(AstrMessageEvent):
                     )
                     payload["media"] = media
                     payload["msg_type"] = 7
-                await self.bot.api.post_group_message(
+                ret = await self.bot.api.post_group_message(
                     group_openid=source.group_openid, **payload
                 )
             case botpy.message.C2CMessage:
@@ -75,22 +118,34 @@ class QQOfficialMessageEvent(AstrMessageEvent):
                     )
                     payload["media"] = media
                     payload["msg_type"] = 7
-                await self.bot.api.post_c2c_message(
-                    openid=source.author.user_openid, **payload
-                )
+                if stream:
+                    ret = await self.post_c2c_message(
+                        openid=source.author.user_openid,
+                        **payload,
+                        stream=stream,
+                    )
+                else:
+                    ret = await self.post_c2c_message(
+                        openid=source.author.user_openid, **payload
+                    )
+                logger.debug(f"Message sent to C2C: {ret}")
             case botpy.message.Message:
                 if image_path:
                     payload["file_image"] = image_path
-                await self.bot.api.post_message(channel_id=source.channel_id, **payload)
+                ret = await self.bot.api.post_message(
+                    channel_id=source.channel_id, **payload
+                )
             case botpy.message.DirectMessage:
                 if image_path:
                     payload["file_image"] = image_path
-                await self.bot.api.post_dms(guild_id=source.guild_id, **payload)
+                ret = await self.bot.api.post_dms(guild_id=source.guild_id, **payload)
 
         await super().send(self.send_buffer)
 
         self.send_buffer = None
 
+        return ret
+
     async def upload_group_and_c2c_image(
         self, image_base64: str, file_type: int, **kwargs
     ) -> botpy.types.message.Media:
@@ -112,6 +167,27 @@ class QQOfficialMessageEvent(AstrMessageEvent):
             )
             return await self.bot.api._http.request(route, json=payload)
 
+    async def post_c2c_message(
+        self,
+        openid: str,
+        msg_type: int = 0,
+        content: str = None,
+        embed: message.Embed = None,
+        ark: message.Ark = None,
+        message_reference: message.Reference = None,
+        media: message.Media = None,
+        msg_id: str = None,
+        msg_seq: str = 1,
+        event_id: str = None,
+        markdown: message.MarkdownPayload = None,
+        keyboard: message.Keyboard = None,
+        stream: dict = None,
+    ) -> message.Message:
+        payload = locals()
+        payload.pop("self", None)
+        route = Route("POST", "/v2/users/{openid}/messages", openid=openid)
+        return await self.bot.api._http.request(route, json=payload)
+
     @staticmethod
     async def _parse_to_qqofficial(message: MessageChain):
         plain_text = ""

astrbot/core/platform/sources/qqofficial/qqofficial_platform_adapter.py

@@ -126,8 +126,9 @@ class QQOfficialPlatformAdapter(Platform):
 
     def meta(self) -> PlatformMetadata:
         return PlatformMetadata(
-            "qq_official",
-            "QQ 机器人官方 API 适配器",
+            name="qq_official",
+            description="QQ 机器人官方 API 适配器",
+            id=self.config.get("id"),
         )
 
     @staticmethod

astrbot/core/platform/sources/qqofficial_webhook/qo_webhook_adapter.py

@@ -99,8 +99,9 @@ class QQOfficialWebhookPlatformAdapter(Platform):
 
     def meta(self) -> PlatformMetadata:
         return PlatformMetadata(
-            "qq_official_webhook",
-            "QQ 机器人官方 API 适配器",
+            name="qq_official_webhook",
+            description="QQ 机器人官方 API 适配器",
+            id=self.config.get("id"),
         )
 
     async def run(self):
@@ -116,5 +117,8 @@ class QQOfficialWebhookPlatformAdapter(Platform):
     async def terminate(self):
         self.webhook_helper.shutdown_event.set()
         await self.client.close()
-        await self.webhook_helper.server.shutdown()
+        try:
+            await self.webhook_helper.server.shutdown()
+        except Exception as _:
+            pass
         logger.info("QQ 机器人官方 API 适配器已经被优雅地关闭")

astrbot/core/platform/sources/telegram/tg_adapter.py

@@ -1,26 +1,32 @@
+import asyncio
+import re
 import sys
 import uuid
-import asyncio
-import astrbot.api.message_components as Comp
 
+from apscheduler.schedulers.asyncio import AsyncIOScheduler
+from telegram import BotCommand, Update
+from telegram.constants import ChatType
+from telegram.ext import ApplicationBuilder, ContextTypes, ExtBot, filters
+from telegram.ext import MessageHandler as TelegramMessageHandler
+
+import astrbot.api.message_components as Comp
+from astrbot.api import logger
+from astrbot.api.event import MessageChain
 from astrbot.api.platform import (
-    Platform,
     AstrBotMessage,
     MessageMember,
-    PlatformMetadata,
     MessageType,
+    Platform,
+    PlatformMetadata,
+    register_platform_adapter,
 )
-from astrbot.api.event import MessageChain
 from astrbot.core.platform.astr_message_event import MessageSesion
-from astrbot.api.platform import register_platform_adapter
+from astrbot.core.star.filter.command import CommandFilter
+from astrbot.core.star.filter.command_group import CommandGroupFilter
+from astrbot.core.star.star import star_map
+from astrbot.core.star.star_handler import star_handlers_registry
 
-from telegram import Update
-from telegram.ext import ApplicationBuilder, ContextTypes, filters
-from telegram.constants import ChatType
-from telegram.ext import MessageHandler as TelegramMessageHandler
 from .tg_event import TelegramPlatformEvent
-from astrbot.api import logger
-from telegram.ext import ExtBot
 
 if sys.version_info >= (3, 12):
     from typing import override
@@ -52,6 +58,14 @@ class TelegramPlatformAdapter(Platform):
 
         self.base_url = base_url
 
+        self.enable_command_register = self.config.get(
+            "telegram_command_register", True
+        )
+        self.enable_command_refresh = self.config.get(
+            "telegram_command_auto_refresh", True
+        )
+        self.last_command_hash = None
+
         self.application = (
             ApplicationBuilder()
             .token(self.config["telegram_token"])
@@ -67,6 +81,8 @@ class TelegramPlatformAdapter(Platform):
         self.client = self.application.bot
         logger.debug(f"Telegram base url: {self.client.base_url}")
 
+        self.scheduler = AsyncIOScheduler()
+
     @override
     async def send_by_session(
         self, session: MessageSesion, message_chain: MessageChain
@@ -80,18 +96,104 @@ class TelegramPlatformAdapter(Platform):
     @override
     def meta(self) -> PlatformMetadata:
         return PlatformMetadata(
-            "telegram",
-            "telegram 适配器",
+            name="telegram", description="telegram 适配器", id=self.config.get("id")
         )
 
     @override
     async def run(self):
         await self.application.initialize()
         await self.application.start()
+
+        if self.enable_command_register:
+            await self.register_commands()
+
+        if self.enable_command_refresh and self.enable_command_register:
+            self.scheduler.add_job(
+                self.register_commands,
+                "interval",
+                seconds=self.config.get("telegram_command_register_interval", 300),
+                id="telegram_command_register",
+                misfire_grace_time=60,
+            )
+            self.scheduler.start()
+
         queue = self.application.updater.start_polling()
         logger.info("Telegram Platform Adapter is running.")
         await queue
 
+    async def register_commands(self):
+        """收集所有注册的指令并注册到 Telegram"""
+        try:
+            commands = self.collect_commands()
+
+            if commands:
+                current_hash = hash(
+                    tuple((cmd.command, cmd.description) for cmd in commands)
+                )
+                if current_hash == self.last_command_hash:
+                    return
+                self.last_command_hash = current_hash
+                await self.client.delete_my_commands()
+                await self.client.set_my_commands(commands)
+
+        except Exception as e:
+            logger.error(f"向 Telegram 注册指令时发生错误: {e!s}")
+
+    def collect_commands(self) -> list[BotCommand]:
+        """从注册的处理器中收集所有指令"""
+        command_dict = {}
+        skip_commands = {"start"}
+
+        for handler_md in star_handlers_registry:
+            handler_metadata = handler_md
+            if not star_map[handler_metadata.handler_module_path].activated:
+                continue
+            for event_filter in handler_metadata.event_filters:
+                cmd_info = self._extract_command_info(
+                    event_filter, handler_metadata, skip_commands
+                )
+                if cmd_info:
+                    cmd_name, description = cmd_info
+                    command_dict.setdefault(cmd_name, description)
+
+        commands_a = sorted(command_dict.keys())
+        return [BotCommand(cmd, command_dict[cmd]) for cmd in commands_a]
+
+    @staticmethod
+    def _extract_command_info(
+        event_filter, handler_metadata, skip_commands: set
+    ) -> tuple[str, str] | None:
+        """从事件过滤器中提取指令信息"""
+        cmd_name = None
+        is_group = False
+        if isinstance(event_filter, CommandFilter) and event_filter.command_name:
+            if (
+                event_filter.parent_command_names
+                and event_filter.parent_command_names != [""]
+            ):
+                return None
+            cmd_name = event_filter.command_name
+        elif isinstance(event_filter, CommandGroupFilter):
+            if event_filter.parent_group:
+                return None
+            cmd_name = event_filter.group_name
+            is_group = True
+
+        if not cmd_name or cmd_name in skip_commands:
+            return None
+
+        if not re.match(r"^[a-z0-9_]+$", cmd_name) or len(cmd_name) > 32:
+            logger.debug(f"跳过无法注册的命令: {cmd_name}")
+            return None
+
+        # Build description.
+        description = handler_metadata.desc or (
+            f"指令组: {cmd_name} (包含多个子指令)" if is_group else f"指令: {cmd_name}"
+        )
+        if len(description) > 30:
+            description = description[:30] + "..."
+        return cmd_name, description
+
     async def start(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
         await context.bot.send_message(
             chat_id=update.effective_chat.id, text=self.config["start_message"]
@@ -163,6 +265,16 @@ class TelegramPlatformAdapter(Platform):
             # 处理文本消息
             plain_text = update.message.text
 
+            # 群聊场景命令特殊处理
+            if plain_text.startswith("/"):
+                command_parts = plain_text.split(" ", 1)
+                if "@" in command_parts[0]:
+                    command, bot_name = command_parts[0].split("@")
+                    if bot_name == self.client.username:
+                        plain_text = command + (
+                            f" {command_parts[1]}" if len(command_parts) > 1 else ""
+                        )
+
             if update.message.entities:
                 for entity in update.message.entities:
                     if entity.type == "mention":
@@ -170,10 +282,12 @@ class TelegramPlatformAdapter(Platform):
                             entity.offset + 1 : entity.offset + entity.length
                         ]
                         message.message.append(Comp.At(qq=name, name=name))
-                        plain_text = (
-                            plain_text[: entity.offset]
-                            + plain_text[entity.offset + entity.length :]
-                        )
+                        # 如果mention是当前bot则移除；否则保留
+                        if name.lower() == context.bot.username.lower():
+                            plain_text = (
+                                plain_text[: entity.offset]
+                                + plain_text[entity.offset + entity.length :]
+                            )
 
             if plain_text:
                 message.message.append(Comp.Plain(plain_text))
@@ -242,8 +356,14 @@ class TelegramPlatformAdapter(Platform):
 
     async def terminate(self):
         try:
+            if self.scheduler.running:
+                self.scheduler.shutdown()
+
             await self.application.stop()
 
+            if self.enable_command_register:
+                await self.client.delete_my_commands()
+
             # 保险起见先判断是否存在updater对象
             if self.application.updater is not None:
                 await self.application.updater.stop()

astrbot/core/platform/sources/telegram/tg_event.py

@@ -1,13 +1,34 @@
+import os
+import re
+import asyncio
 import telegramify_markdown
 from astrbot.api.event import AstrMessageEvent, MessageChain
 from astrbot.api.platform import AstrBotMessage, PlatformMetadata, MessageType
-from astrbot.api.message_components import Plain, Image, Reply, At, File, Record
+from astrbot.api.message_components import (
+    Plain,
+    Image,
+    Reply,
+    At,
+    File,
+    Record,
+)
 from telegram.ext import ExtBot
 from astrbot.core.utils.io import download_file
 from astrbot import logger
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 
 class TelegramPlatformEvent(AstrMessageEvent):
+    # Telegram 的最大消息长度限制
+    MAX_MESSAGE_LENGTH = 4096
+
+    SPLIT_PATTERNS = {
+        "paragraph": re.compile(r"\n\n"),
+        "line": re.compile(r"\n"),
+        "sentence": re.compile(r"[.!?。！？]"),
+        "word": re.compile(r"\s"),
+    }
+
     def __init__(
         self,
         message_str: str,
@@ -19,8 +40,33 @@ class TelegramPlatformEvent(AstrMessageEvent):
         super().__init__(message_str, message_obj, platform_meta, session_id)
         self.client = client
 
-    @staticmethod
-    async def send_with_client(client: ExtBot, message: MessageChain, user_name: str):
+    def _split_message(self, text: str) -> list[str]:
+        if len(text) <= self.MAX_MESSAGE_LENGTH:
+            return [text]
+
+        chunks = []
+        while text:
+            if len(text) <= self.MAX_MESSAGE_LENGTH:
+                chunks.append(text)
+                break
+
+            split_point = self.MAX_MESSAGE_LENGTH
+            segment = text[: self.MAX_MESSAGE_LENGTH]
+
+            for _, pattern in self.SPLIT_PATTERNS.items():
+                if matches := list(pattern.finditer(segment)):
+                    last_match = matches[-1]
+                    split_point = last_match.end()
+                    break
+
+            chunks.append(text[:split_point])
+            text = text[split_point:].lstrip()
+
+        return chunks
+
+    async def send_with_client(
+        self, client: ExtBot, message: MessageChain, user_name: str
+    ):
         image_path = None
 
         has_reply = False
@@ -49,25 +95,29 @@ class TelegramPlatformEvent(AstrMessageEvent):
 
             if isinstance(i, Plain):
                 if at_user_id and not at_flag:
-                    i.text = f"@{at_user_id} " + i.text
+                    i.text = f"@{at_user_id} {i.text}"
                     at_flag = True
-                text = i.text
-                try:
-                    text = telegramify_markdown.markdownify(
-                        i.text, max_line_length=None, normalize_whitespace=False
-                    )
-                except Exception as e:
-                    logger.warning(
-                        f"MarkdownV2 conversion failed: {e}. Using plain text instead."
-                    )
-                    return
-                await client.send_message(text=text, parse_mode="MarkdownV2", **payload)
+                chunks = self._split_message(i.text)
+                for chunk in chunks:
+                    try:
+                        md_text = telegramify_markdown.markdownify(
+                            chunk, max_line_length=None, normalize_whitespace=False
+                        )
+                        await client.send_message(
+                            text=md_text, parse_mode="MarkdownV2", **payload
+                        )
+                    except Exception as e:
+                        logger.warning(
+                            f"MarkdownV2 send failed: {e}. Using plain text instead."
+                        )
+                        await client.send_message(text=chunk, **payload)
             elif isinstance(i, Image):
                 image_path = await i.convert_to_file_path()
                 await client.send_photo(photo=image_path, **payload)
             elif isinstance(i, File):
                 if i.file.startswith("https://"):
-                    path = "data/temp/" + i.name
+                    temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+                    path = os.path.join(temp_dir, i.name)
                     await download_file(i.file, path)
                     i.file = path
 
@@ -82,3 +132,110 @@ class TelegramPlatformEvent(AstrMessageEvent):
         else:
             await self.send_with_client(self.client, message, self.get_sender_id())
         await super().send(message)
+
+    async def send_streaming(self, generator, use_fallback: bool = False):
+        message_thread_id = None
+
+        if self.get_message_type() == MessageType.GROUP_MESSAGE:
+            user_name = self.message_obj.group_id
+        else:
+            user_name = self.get_sender_id()
+
+        if "#" in user_name:
+            # it's a supergroup chat with message_thread_id
+            user_name, message_thread_id = user_name.split("#")
+        payload = {
+            "chat_id": user_name,
+        }
+        if message_thread_id:
+            payload["reply_to_message_id"] = message_thread_id
+
+        delta = ""
+        current_content = ""
+        message_id = None
+        last_edit_time = 0  # 上次编辑消息的时间
+        throttle_interval = 0.6  # 编辑消息的间隔时间 (秒)
+
+        async for chain in generator:
+            if isinstance(chain, MessageChain):
+                # 处理消息链中的每个组件
+                for i in chain.chain:
+                    if isinstance(i, Plain):
+                        delta += i.text
+                    elif isinstance(i, Image):
+                        image_path = await i.convert_to_file_path()
+                        await self.client.send_photo(photo=image_path, **payload)
+                        continue
+                    elif isinstance(i, File):
+                        if i.file.startswith("https://"):
+                            temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+                            path = os.path.join(temp_dir, i.name)
+                            await download_file(i.file, path)
+                            i.file = path
+
+                        await self.client.send_document(
+                            document=i.file, filename=i.name, **payload
+                        )
+                        continue
+                    elif isinstance(i, Record):
+                        path = await i.convert_to_file_path()
+                        await self.client.send_voice(voice=path, **payload)
+                        continue
+                    else:
+                        logger.warning(f"不支持的消息类型: {type(i)}")
+                        continue
+
+                # Plain
+                if message_id and len(delta) <= self.MAX_MESSAGE_LENGTH:
+                    current_time = asyncio.get_event_loop().time()
+                    time_since_last_edit = current_time - last_edit_time
+
+                    # 如果距离上次编辑的时间 >= 设定的间隔，等待一段时间
+                    if time_since_last_edit >= throttle_interval:
+                        # 编辑消息
+                        try:
+                            await self.client.edit_message_text(
+                                text=delta,
+                                chat_id=payload["chat_id"],
+                                message_id=message_id,
+                            )
+                            current_content = delta
+                        except Exception as e:
+                            logger.warning(f"编辑消息失败(streaming): {e!s}")
+                        last_edit_time = (
+                            asyncio.get_event_loop().time()
+                        )  # 更新上次编辑的时间
+                else:
+                    # delta 长度一般不会大于 4096，因此这里直接发送
+                    try:
+                        msg = await self.client.send_message(text=delta, **payload)
+                        current_content = delta
+                        delta = ""
+                    except Exception as e:
+                        logger.warning(f"发送消息失败(streaming): {e!s}")
+                    message_id = msg.message_id
+                    last_edit_time = (
+                        asyncio.get_event_loop().time()
+                    )  # 记录初始消息发送时间
+
+        try:
+            if delta and current_content != delta:
+                try:
+                    markdown_text = telegramify_markdown.markdownify(
+                        delta, max_line_length=None, normalize_whitespace=False
+                    )
+                    await self.client.edit_message_text(
+                        text=markdown_text,
+                        chat_id=payload["chat_id"],
+                        message_id=message_id,
+                        parse_mode="MarkdownV2",
+                    )
+                except Exception as e:
+                    logger.warning(f"Markdown转换失败，使用普通文本: {e!s}")
+                    await self.client.edit_message_text(
+                        text=delta, chat_id=payload["chat_id"], message_id=message_id
+                    )
+        except Exception as e:
+            logger.warning(f"编辑消息失败(streaming): {e!s}")
+
+        return await super().send_streaming(generator, use_fallback)

astrbot/core/platform/sources/webchat/webchat_adapter.py

@@ -17,6 +17,7 @@ from astrbot.core import web_chat_queue
 from .webchat_event import WebChatMessageEvent
 from astrbot.core.platform.astr_message_event import MessageSesion
 from ...register import register_platform_adapter
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 
 class QueueListener:
@@ -40,11 +41,11 @@ class WebChatAdapter(Platform):
         self.config = platform_config
         self.settings = platform_settings
         self.unique_session = platform_settings["unique_session"]
-        self.imgs_dir = "data/webchat/imgs"
+        self.imgs_dir = os.path.join(get_astrbot_data_path(), "webchat", "imgs")
+        os.makedirs(self.imgs_dir, exist_ok=True)
 
         self.metadata = PlatformMetadata(
-            "webchat",
-            "webchat",
+            name="webchat", description="webchat", id=self.config.get("id")
         )
 
     async def send_by_session(

astrbot/core/platform/sources/webchat/webchat_event.py

@@ -6,8 +6,9 @@ from astrbot.api.event import AstrMessageEvent, MessageChain
 from astrbot.api.message_components import Plain, Image, Record
 from astrbot.core.utils.io import download_image_by_url
 from astrbot.core import web_chat_back_queue
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
-imgs_dir = "data/webchat/imgs"
+imgs_dir = os.path.join(get_astrbot_data_path(), "webchat", "imgs")
 
 
 class WebChatMessageEvent(AstrMessageEvent):
@@ -16,16 +17,26 @@ class WebChatMessageEvent(AstrMessageEvent):
         os.makedirs(imgs_dir, exist_ok=True)
 
     @staticmethod
-    async def _send(message: MessageChain, session_id: str):
+    async def _send(message: MessageChain, session_id: str, streaming: bool = False):
         if not message:
-            web_chat_back_queue.put_nowait(None)
-            return
+            await web_chat_back_queue.put(
+                {"type": "end", "data": "", "streaming": False}
+            )
+            return ""
 
         cid = session_id.split("!")[-1]
-
+        data = ""
         for comp in message.chain:
             if isinstance(comp, Plain):
-                web_chat_back_queue.put_nowait((comp.text, cid))
+                data = comp.text
+                await web_chat_back_queue.put(
+                    {
+                        "type": "plain",
+                        "cid": cid,
+                        "data": data,
+                        "streaming": streaming,
+                    }
+                )
             elif isinstance(comp, Image):
                 # save image to local
                 filename = str(uuid.uuid4()) + ".jpg"
@@ -46,7 +57,15 @@ class WebChatMessageEvent(AstrMessageEvent):
                     with open(path, "wb") as f:
                         with open(comp.file, "rb") as f2:
                             f.write(f2.read())
-                web_chat_back_queue.put_nowait((f"[IMAGE]{filename}", cid))
+                data = f"[IMAGE]{filename}"
+                await web_chat_back_queue.put(
+                    {
+                        "type": "image",
+                        "cid": cid,
+                        "data": data,
+                        "streaming": streaming,
+                    }
+                )
             elif isinstance(comp, Record):
                 # save record to local
                 filename = str(uuid.uuid4()) + ".wav"
@@ -62,11 +81,45 @@ class WebChatMessageEvent(AstrMessageEvent):
                     with open(path, "wb") as f:
                         with open(comp.file, "rb") as f2:
                             f.write(f2.read())
-                web_chat_back_queue.put_nowait((f"[RECORD]{filename}", cid))
+                data = f"[RECORD]{filename}"
+                await web_chat_back_queue.put(
+                    {
+                        "type": "record",
+                        "cid": cid,
+                        "data": data,
+                        "streaming": streaming,
+                    }
+                )
             else:
                 logger.debug(f"webchat 忽略: {comp.type}")
-        web_chat_back_queue.put_nowait(None)
+
+        return data
 
     async def send(self, message: MessageChain):
         await WebChatMessageEvent._send(message, session_id=self.session_id)
+        await web_chat_back_queue.put(
+            {
+                "type": "end",
+                "data": "",
+                "streaming": False,
+                "cid": self.session_id.split("!")[-1],
+            }
+        )
         await super().send(message)
+
+    async def send_streaming(self, generator, use_fallback: bool = False):
+        final_data = ""
+        async for chain in generator:
+            final_data += await WebChatMessageEvent._send(
+                chain, session_id=self.session_id, streaming=True
+            )
+
+        await web_chat_back_queue.put(
+            {
+                "type": "end",
+                "data": final_data,
+                "streaming": True,
+                "cid": self.session_id.split("!")[-1],
+            }
+        )
+        await super().send_streaming(generator, use_fallback)

astrbot/core/platform/sources/wechatpadpro/wechatpadpro_adapter.py

@@ -0,0 +1,707 @@
+import asyncio
+import json
+import os
+import time
+from typing import Optional
+
+import aiohttp
+import websockets
+
+from astrbot import logger
+from astrbot.api.message_components import Plain, Image
+from astrbot.api.platform import Platform, PlatformMetadata
+from astrbot.core.message.message_event_result import MessageChain
+from astrbot.core.platform.astrbot_message import (
+    AstrBotMessage,
+    MessageMember,
+    MessageType,
+)
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
+from astrbot.core.platform.astr_message_event import MessageSesion
+
+from ...register import register_platform_adapter
+from .wechatpadpro_message_event import WeChatPadProMessageEvent
+
+
+@register_platform_adapter("wechatpadpro", "WeChatPadPro 消息平台适配器")
+class WeChatPadProAdapter(Platform):
+    def __init__(
+        self, platform_config: dict, platform_settings: dict, event_queue: asyncio.Queue
+    ) -> None:
+        super().__init__(event_queue)
+        self._shutdown_event = None
+        self.wxnewpass = None
+        self.config = platform_config
+        self.settings = platform_settings
+        self.unique_session = platform_settings.get("unique_session", False)
+
+        self.metadata = PlatformMetadata(
+            name="wechatpadpro",
+            description="WeChatPadPro 消息平台适配器",
+            id=self.config.get("id", "wechatpadpro"),
+        )
+
+        # 保存配置信息
+        self.admin_key = self.config.get("admin_key")
+        self.host = self.config.get("host")
+        self.port = self.config.get("port")
+        self.active_mesasge_poll: bool = self.config.get(
+            "wpp_active_message_poll", False
+        )
+        self.active_message_poll_interval: int = self.config.get(
+            "wpp_active_message_poll_interval", 5
+        )
+        self.base_url = f"http://{self.host}:{self.port}"
+        self.auth_key = None  # 用于保存生成的授权码
+        self.wxid = None  # 用于保存登录成功后的 wxid
+        self.credentials_file = os.path.join(
+            get_astrbot_data_path(), "wechatpadpro_credentials.json"
+        )  # 持久化文件路径
+        self.ws_handle_task = None
+
+    async def run(self) -> None:
+        """
+        启动平台适配器的运行实例。
+        """
+        logger.info("WeChatPadPro 适配器正在启动...")
+
+        if loaded_credentials := self.load_credentials():
+            self.auth_key = loaded_credentials.get("auth_key")
+            self.wxid = loaded_credentials.get("wxid")
+
+        isLoginIn = await self.check_online_status()
+
+        # 检查在线状态
+        if self.auth_key and isLoginIn:
+            logger.info("WeChatPadPro 设备已在线，凭据存在，跳过扫码登录。")
+            # 如果在线，连接 WebSocket 接收消息
+            self.ws_handle_task = asyncio.create_task(self.connect_websocket())
+        else:
+            # 1. 生成授权码
+            if not self.auth_key:
+                logger.info("WeChatPadPro 无可用凭据，将生成新的授权码。")
+                await self.generate_auth_key()
+
+            # 2. 获取登录二维码
+            if not isLoginIn:
+                logger.info("WeChatPadPro 设备已离线，开始扫码登录。")
+                qr_code_url = await self.get_login_qr_code()
+
+                if qr_code_url:
+                    logger.info(f"请扫描以下二维码登录: {qr_code_url}")
+                else:
+                    logger.error("无法获取登录二维码。")
+                    return
+
+                # 3. 检测扫码状态
+                login_successful = await self.check_login_status()
+
+                if login_successful:
+                    logger.info("登录成功，WeChatPadPro适配器已连接。")
+                else:
+                    logger.warning("登录失败或超时，WeChatPadPro 适配器将关闭。")
+                    await self.terminate()
+                    return
+            
+            # 登录成功后，连接 WebSocket 接收消息
+            self.ws_handle_task = asyncio.create_task(self.connect_websocket())
+
+        self._shutdown_event = asyncio.Event()
+        await self._shutdown_event.wait()
+        logger.info("WeChatPadPro 适配器已停止。")
+
+    def load_credentials(self):
+        """
+        从文件中加载 auth_key 和 wxid。
+        """
+        if os.path.exists(self.credentials_file):
+            try:
+                with open(self.credentials_file, "r") as f:
+                    credentials = json.load(f)
+                    logger.info("成功加载 WeChatPadPro 凭据。")
+                    return credentials
+            except Exception as e:
+                logger.error(f"加载 WeChatPadPro 凭据失败: {e}")
+        return None
+
+    def save_credentials(self):
+        """
+        将 auth_key 和 wxid 保存到文件。
+        """
+        credentials = {
+            "auth_key": self.auth_key,
+            "wxid": self.wxid,
+        }
+        try:
+            # 确保数据目录存在
+            data_dir = os.path.dirname(self.credentials_file)
+            os.makedirs(data_dir, exist_ok=True)
+            with open(self.credentials_file, "w") as f:
+                json.dump(credentials, f)
+            logger.info("成功保存 WeChatPadPro 凭据。")
+        except Exception as e:
+            logger.error(f"保存 WeChatPadPro 凭据失败: {e}")
+
+    async def check_online_status(self):
+        """
+        检查 WeChatPadPro 设备是否在线。
+        """
+        url = f"{self.base_url}/login/GetLoginStatus"
+        params = {"key": self.auth_key}
+
+        async with aiohttp.ClientSession() as session:
+            try:
+                async with session.get(url, params=params) as response:
+                    response_data = await response.json()
+                    # 根据提供的在线接口返回示例，成功状态码是 200，loginState 为 1 表示在线
+                    if response.status == 200 and response_data.get("Code") == 200:
+                        login_state = response_data.get("Data", {}).get("loginState")
+                        if login_state == 1:
+                            logger.info("WeChatPadPro 设备当前在线。")
+                            return True
+                        # login_state == 3 为离线状态
+                        elif login_state == 3:
+                            logger.info(
+                                "WeChatPadPro 设备不在线。"
+                            )
+                            return False
+                        else:
+                            logger.error(
+                                f"未知的在线状态: {login_state:}"
+                            )
+                            return False
+                    # Code == 300 为微信退出状态。
+                    elif response.status == 200 and response_data.get("Code") == 300:
+                        logger.info(
+                            "WeChatPadPro 设备已退出。"
+                        )
+                        return False
+                    else:
+                        logger.error(
+                            f"检查在线状态失败: {response.status}, {response_data}"
+                        )
+                        return False
+                    
+            except aiohttp.ClientConnectorError as e:
+                logger.error(f"连接到 WeChatPadPro 服务失败: {e}")
+                return False
+            except Exception as e:
+                logger.error(f"检查在线状态时发生错误: {e}")
+                return False
+
+    async def generate_auth_key(self):
+        """
+        生成授权码。
+        """
+        url = f"{self.base_url}/admin/GenAuthKey1"
+        params = {"key": self.admin_key}
+        payload = {"Count": 1, "Days": 365}  # 生成一个有效期365天的授权码
+
+        async with aiohttp.ClientSession() as session:
+            try:
+                async with session.post(url, params=params, json=payload) as response:
+                    response_data = await response.json()
+                    # 修正成功判断条件和授权码提取路径
+                    if response.status == 200 and response_data.get("Code") == 200:
+                        # 授权码在 Data 字段的列表中
+                        if (
+                            response_data.get("Data")
+                            and isinstance(response_data["Data"], list)
+                            and len(response_data["Data"]) > 0
+                        ):
+                            self.auth_key = response_data["Data"][0]
+                            logger.info("成功获取授权码")
+                        else:
+                            logger.error(
+                                f"生成授权码成功但未找到授权码: {response_data}"
+                            )
+                    else:
+                        logger.error(
+                            f"生成授权码失败: {response.status}, {response_data}"
+                        )
+            except aiohttp.ClientConnectorError as e:
+                logger.error(f"连接到 WeChatPadPro 服务失败: {e}")
+            except Exception as e:
+                logger.error(f"生成授权码时发生错误: {e}")
+
+    async def get_login_qr_code(self):
+        """
+        获取登录二维码地址。
+        """
+        url = f"{self.base_url}/login/GetLoginQrCodeNew"
+        params = {"key": self.auth_key}
+        payload = {}  # 根据文档，这个接口的 body 可以为空
+
+        async with aiohttp.ClientSession() as session:
+            try:
+                async with session.post(url, params=params, json=payload) as response:
+                    response_data = await response.json()
+                    # 修正成功判断条件和数据提取路径
+                    if response.status == 200 and response_data.get("Code") == 200:
+                        # 二维码地址在 Data.QrCodeUrl 字段中
+                        if response_data.get("Data") and response_data["Data"].get(
+                            "QrCodeUrl"
+                        ):
+                            return response_data["Data"]["QrCodeUrl"]
+                        else:
+                            logger.error(
+                                f"获取登录二维码成功但未找到二维码地址: {response_data}"
+                            )
+                            return None
+                    else:
+                        logger.error(
+                            f"获取登录二维码失败: {response.status}, {response_data}"
+                        )
+                        return None
+            except aiohttp.ClientConnectorError as e:
+                logger.error(f"连接到 WeChatPadPro 服务失败: {e}")
+                return None
+            except Exception as e:
+                logger.error(f"获取登录二维码时发生错误: {e}")
+                return None
+
+    async def check_login_status(self):
+        """
+        循环检测扫码状态。
+        尝试 6 次后跳出循环，添加倒计时。
+        返回 True 如果登录成功，否则返回 False。
+        """
+        url = f"{self.base_url}/login/CheckLoginStatus"
+        params = {"key": self.auth_key}
+
+        attempts = 0  # 初始化尝试次数
+        max_attempts = 36  # 最大尝试次数
+        countdown = 180  # 倒计时时长
+        logger.info(f"请在 {countdown} 秒内扫码登录。")
+        while attempts < max_attempts:
+            async with aiohttp.ClientSession() as session:
+                try:
+                    async with session.get(url, params=params) as response:
+                        response_data = await response.json()
+                        # 成功判断条件和数据提取路径
+                        if response.status == 200 and response_data.get("Code") == 200:
+                            if (
+                                response_data.get("Data")
+                                and response_data["Data"].get("state") is not None
+                            ):
+                                status = response_data["Data"]["state"]
+                                logger.info(
+                                    f"第 {attempts + 1} 次尝试，当前登录状态: {status}，还剩{countdown - attempts * 5}秒"
+                                )
+                                if status == 2:  # 状态 2 表示登录成功
+                                    self.wxid = response_data["Data"].get("wxid")
+                                    self.wxnewpass = response_data["Data"].get(
+                                        "wxnewpass"
+                                    )
+                                    logger.info(
+                                        f"登录成功，wxid: {self.wxid}, wxnewpass: {self.wxnewpass}"
+                                    )
+                                    self.save_credentials()  # 登录成功后保存凭据
+                                    return True
+                                elif status == -2:  # 二维码过期
+                                    logger.error("二维码已过期，请重新获取。")
+                                    return False
+                            else:
+                                logger.error(
+                                    f"检测登录状态成功但未找到登录状态: {response_data}"
+                                )
+                        elif response_data.get("Code") == 300:
+                            # "不存在状态"
+                            pass
+                        else:
+                            logger.info(
+                                f"检测登录状态失败: {response.status}, {response_data}"
+                            )
+
+                except aiohttp.ClientConnectorError as e:
+                    logger.error(f"连接到 WeChatPadPro 服务失败: {e}")
+                    await asyncio.sleep(5)
+                    attempts += 1
+                    continue
+                except Exception as e:
+                    logger.error(f"检测登录状态时发生错误: {e}")
+                    attempts += 1
+                    continue
+
+            attempts += 1
+            await asyncio.sleep(5)  # 每隔5秒检测一次
+        logger.warning("登录检测超过最大尝试次数，退出检测。")
+        return False
+
+    async def connect_websocket(self):
+        """
+        建立 WebSocket 连接并处理接收到的消息。
+        """
+        os.environ["no_proxy"] = f"localhost,127.0.0.1,{self.host}"
+        ws_url = f"ws://{self.host}:{self.port}/ws/GetSyncMsg?key={self.auth_key}"
+        logger.info(
+            f"正在连接 WebSocket: ws://{self.host}:{self.port}/ws/GetSyncMsg?key=***"
+        )
+        while True:
+            try:
+                async with websockets.connect(ws_url) as websocket:
+                    logger.info("WebSocket 连接成功。")
+                    # 设置空闲超时重连
+                    wait_time = (
+                        self.active_message_poll_interval
+                        if self.active_mesasge_poll
+                        else 120
+                    )
+                    while True:
+                        try:
+                            message = await asyncio.wait_for(
+                                websocket.recv(), timeout=wait_time
+                            )
+                            # logger.debug(message) # 不显示原始消息内容
+                            asyncio.create_task(self.handle_websocket_message(message))
+                        except asyncio.TimeoutError:
+                            logger.warning(f"WebSocket 连接空闲超过 {wait_time} s")
+                            break
+                        except websockets.exceptions.ConnectionClosedOK:
+                            logger.info("WebSocket 连接正常关闭。")
+                            break
+                        except Exception as e:
+                            logger.error(f"处理 WebSocket 消息时发生错误: {e}")
+                            break
+            except Exception as e:
+                logger.error(f"WebSocket 连接失败: {e}, 请检查WeChatPadPro服务状态，或尝试重启WeChatPadPro适配器。")
+                await asyncio.sleep(5)
+
+    async def handle_websocket_message(self, message: str):
+        """
+        处理从 WebSocket 接收到的消息。
+        """
+        logger.debug(f"收到 WebSocket 消息: {message}")
+        try:
+            message_data = json.loads(message)
+            if (
+                message_data.get("msg_id") is not None
+                and message_data.get("from_user_name") is not None
+            ):
+                abm = await self.convert_message(message_data)
+                if abm:
+                    # 创建 WeChatPadProMessageEvent 实例
+                    message_event = WeChatPadProMessageEvent(
+                        message_str=abm.message_str,
+                        message_obj=abm,
+                        platform_meta=self.meta(),
+                        session_id=abm.session_id,
+                        # 传递适配器实例，以便在事件中调用 send 方法
+                        adapter=self,
+                    )
+                    # 提交事件到事件队列
+                    self.commit_event(message_event)
+            else:
+                logger.warning(f"收到未知结构的 WebSocket 消息: {message_data}")
+
+        except json.JSONDecodeError:
+            logger.error(f"无法解析 WebSocket 消息为 JSON: {message}")
+        except Exception as e:
+            logger.error(f"处理 WebSocket 消息时发生错误: {e}")
+
+    async def convert_message(self, raw_message: dict) -> AstrBotMessage | None:
+        """
+        将 WeChatPadPro 原始消息转换为 AstrBotMessage。
+        """
+        abm = AstrBotMessage()
+        abm.raw_message = raw_message
+        abm.message_id = str(raw_message.get("msg_id"))
+        abm.timestamp = raw_message.get("create_time")
+        abm.self_id = self.wxid
+
+        if int(time.time()) - abm.timestamp > 180:
+            logger.warning(
+                f"忽略 3 分钟前的旧消息：消息时间戳 {abm.timestamp} 超过当前时间 {int(time.time())}。"
+            )
+            return None
+
+        from_user_name = raw_message.get("from_user_name", {}).get("str", "")
+        to_user_name = raw_message.get("to_user_name", {}).get("str", "")
+        content = raw_message.get("content", {}).get("str", "")
+        push_content = raw_message.get("push_content", "")
+        msg_type = raw_message.get("msg_type")
+
+        abm.message_str = ""
+        abm.message = []
+
+        # 如果是机器人自己发送的消息、回显消息或系统消息，忽略
+        if from_user_name == self.wxid:
+            logger.info("忽略来自自己的消息。")
+            return None
+
+        if from_user_name in ["weixin", "newsapp", "newsapp_wechat"]:
+            logger.info("忽略来自微信团队的消息。")
+            return None
+
+        # 先判断群聊/私聊并设置基本属性
+        if await self._process_chat_type(
+            abm, raw_message, from_user_name, to_user_name, content, push_content
+        ):
+            # 再根据消息类型处理消息内容
+            await self._process_message_content(abm, raw_message, msg_type, content)
+            
+            return abm
+        return None
+
+    async def _process_chat_type(
+        self,
+        abm: AstrBotMessage,
+        raw_message: dict,
+        from_user_name: str,
+        to_user_name: str,
+        content: str,
+        push_content: str,
+    ):
+        """
+        判断消息是群聊还是私聊，并设置 AstrBotMessage 的基本属性。
+        """
+        if from_user_name == "weixin":
+            return False
+        if "@chatroom" in from_user_name:
+            abm.type = MessageType.GROUP_MESSAGE
+            abm.group_id = from_user_name
+
+            parts = content.split(":\n", 1)
+            sender_wxid = parts[0] if len(parts) == 2 else ""
+            abm.sender = MessageMember(user_id=sender_wxid, nickname="")
+
+            # 获取群聊发送者的nickname
+            if sender_wxid:
+                accurate_nickname = await self._get_group_member_nickname(
+                    abm.group_id, sender_wxid
+                )
+                if accurate_nickname:
+                    abm.sender.nickname = accurate_nickname
+
+            # 对于群聊，session_id 可以是群聊 ID 或发送者 ID + 群聊 ID (如果 unique_session 为 True)
+            if self.unique_session:
+                abm.session_id = f"{from_user_name}_{to_user_name}"
+            else:
+                abm.session_id = from_user_name
+        else:
+            abm.type = MessageType.FRIEND_MESSAGE
+            abm.group_id = ""
+            nick_name = ""
+            if push_content and " : " in push_content:
+                nick_name = push_content.split(" : ")[0]
+            abm.sender = MessageMember(user_id=from_user_name, nickname=nick_name)
+            abm.session_id = from_user_name
+        return True
+
+    async def _get_group_member_nickname(
+        self, group_id: str, member_wxid: str
+    ) -> Optional[str]:
+        """
+        通过接口获取群成员的昵称。
+        """
+        url = f"{self.base_url}/group/GetChatroomMemberDetail"
+        params = {"key": self.auth_key}
+        payload = {
+            "ChatRoomName": group_id,
+        }
+
+        async with aiohttp.ClientSession() as session:
+            try:
+                async with session.post(url, params=params, json=payload) as response:
+                    response_data = await response.json()
+                    if response.status == 200 and response_data.get("Code") == 200:
+                        # 从返回数据中查找对应成员的昵称
+                        member_list = (
+                            response_data.get("Data", {})
+                            .get("member_data", {})
+                            .get("chatroom_member_list", [])
+                        )
+                        for member in member_list:
+                            if member.get("user_name") == member_wxid:
+                                return member.get("nick_name")
+                        logger.warning(
+                            f"在群 {group_id} 中未找到成员 {member_wxid} 的昵称"
+                        )
+                    else:
+                        logger.error(
+                            f"获取群成员详情失败: {response.status}, {response_data}"
+                        )
+                    return None
+            except aiohttp.ClientConnectorError as e:
+                logger.error(f"连接到 WeChatPadPro 服务失败: {e}")
+                return None
+            except Exception as e:
+                logger.error(f"获取群成员详情时发生错误: {e}")
+                return None
+
+    async def _download_raw_image(
+        self, from_user_name: str, to_user_name: str, msg_id: int
+    ):
+        """下载原始图片。"""
+        url = f"{self.base_url}/message/GetMsgBigImg"
+        params = {"key": self.auth_key}
+        payload = {
+            "CompressType": 0,
+            "FromUserName": from_user_name,
+            "MsgId": msg_id,
+            "Section": {"DataLen": 61440, "StartPos": 0},
+            "ToUserName": to_user_name,
+            "TotalLen": 0,
+        }
+        async with aiohttp.ClientSession() as session:
+            try:
+                async with session.post(url, params=params, json=payload) as response:
+                    if response.status == 200:
+                        return await response.json()
+                    else:
+                        logger.error(f"下载图片失败: {response.status}")
+                        return None
+            except aiohttp.ClientConnectorError as e:
+                logger.error(f"连接到 WeChatPadPro 服务失败: {e}")
+                return None
+            except Exception as e:
+                logger.error(f"下载图片时发生错误: {e}")
+                return None
+
+    async def _process_message_content(
+        self, abm: AstrBotMessage, raw_message: dict, msg_type: int, content: str
+    ):
+        """
+        根据消息类型处理消息内容，填充 AstrBotMessage 的 message 列表。
+        """
+        if msg_type == 1:  # 文本消息
+            abm.message_str = content
+            if abm.type == MessageType.GROUP_MESSAGE:
+                parts = content.split(":\n", 1)
+                if len(parts) == 2:
+                    abm.message_str = parts[1]
+                    abm.message.append(Plain(abm.message_str))
+                else:
+                    abm.message.append(Plain(abm.message_str))
+            else:  # 私聊消息
+                abm.message.append(Plain(abm.message_str))
+        elif msg_type == 3:
+            # 图片消息
+            from_user_name = raw_message.get("from_user_name", {}).get("str", "")
+            to_user_name = raw_message.get("to_user_name", {}).get("str", "")
+            msg_id = raw_message.get("msg_id")
+            image_resp = await self._download_raw_image(
+                from_user_name, to_user_name, msg_id
+            )
+            image_bs64_data = (
+                image_resp.get("Data", {}).get("Data", {}).get("Buffer", None)
+            )
+            if image_bs64_data:
+                abm.message.append(Image.fromBase64(image_bs64_data))
+        elif msg_type == 47:
+            # 视频消息 (注意：表情消息也是 47，需要区分)
+            logger.warning("收到视频消息，待实现。")
+        elif msg_type == 50:
+            # 语音/视频
+            logger.warning("收到语音/视频消息，待实现。")
+        elif msg_type == 49:
+            # 引用消息
+            logger.warning("收到引用消息，待实现。")
+        else:
+            logger.warning(f"收到未处理的消息类型: {msg_type}。")
+
+    async def terminate(self):
+        """
+        终止一个平台的运行实例。
+        """
+        logger.info("终止 WeChatPadPro 适配器。")
+        try:
+            if self.ws_handle_task:
+                self.ws_handle_task.cancel()
+            self._shutdown_event.set()
+        except Exception:
+            pass
+
+    def meta(self) -> PlatformMetadata:
+        """
+        得到一个平台的元数据。
+        """
+        return self.metadata
+
+    async def send_by_session(
+        self, session: MessageSesion, message_chain: MessageChain
+    ):
+        dummy_message_obj = AstrBotMessage()
+        dummy_message_obj.session_id = session.session_id
+        # 根据 session_id 判断消息类型
+        if "@chatroom" in session.session_id:
+            dummy_message_obj.type = MessageType.GROUP_MESSAGE
+            dummy_message_obj.group_id = session.session_id
+            dummy_message_obj.sender = MessageMember(user_id="", nickname="")
+        else:
+            dummy_message_obj.type = MessageType.FRIEND_MESSAGE
+            dummy_message_obj.group_id = ""
+            dummy_message_obj.sender = MessageMember(user_id="", nickname="")
+        sending_event = WeChatPadProMessageEvent(
+            message_str="",
+            message_obj=dummy_message_obj,
+            platform_meta=self.meta(),
+            session_id=session.session_id,
+            adapter=self,
+        )
+        # 调用实例方法 send
+        await sending_event.send(message_chain)
+
+    async def get_contact_list(self):
+        """
+        获取联系人列表。
+        """
+        url = f"{self.base_url}/friend/GetContactList"
+        params = {"key": self.auth_key}
+        payload = {"CurrentChatRoomContactSeq": 0, "CurrentWxcontactSeq": 0}
+        async with aiohttp.ClientSession() as session:
+            try:
+                async with session.post(url, params=params, json=payload) as response:
+                    if response.status != 200:
+                        logger.error(f"获取联系人列表失败: {response.status}")
+                        return None
+                    result = await response.json()
+                    if result.get("Code") == 200 and result.get("Data"):
+                        contact_list = (
+                            result.get("Data", {})
+                            .get("ContactList", {})
+                            .get("contactUsernameList", [])
+                        )
+                        return contact_list
+                    else:
+                        logger.error(f"获取联系人列表失败: {result}")
+                        return None
+            except aiohttp.ClientConnectorError as e:
+                logger.error(f"连接到 WeChatPadPro 服务失败: {e}")
+                return None
+            except Exception as e:
+                logger.error(f"获取联系人列表时发生错误: {e}")
+                return None
+
+    async def get_contact_details_list(
+        self, room_wx_id_list: list[str] = None, user_names: list[str] = None
+    ) -> Optional[dict]:
+        """
+        获取联系人详情列表。
+        """
+        if room_wx_id_list is None:
+            room_wx_id_list = []
+        if user_names is None:
+            user_names = []
+        url = f"{self.base_url}/friend/GetContactDetailsList"
+        params = {"key": self.auth_key}
+        payload = {"RoomWxIDList": room_wx_id_list, "UserNames": user_names}
+        async with aiohttp.ClientSession() as session:
+            try:
+                async with session.post(url, params=params, json=payload) as response:
+                    if response.status != 200:
+                        logger.error(f"获取联系人详情列表失败: {response.status}")
+                        return None
+                    result = await response.json()
+                    if result.get("Code") == 200 and result.get("Data"):
+                        contact_list = result.get("Data", {}).get("contactList", {})
+                        return contact_list
+                    else:
+                        logger.error(f"获取联系人详情列表失败: {result}")
+                        return None
+            except aiohttp.ClientConnectorError as e:
+                logger.error(f"连接到 WeChatPadPro 服务失败: {e}")
+                return None
+            except Exception as e:
+                logger.error(f"获取联系人详情列表时发生错误: {e}")
+                return None

astrbot/core/platform/sources/wechatpadpro/wechatpadpro_message_event.py

@@ -0,0 +1,117 @@
+import asyncio
+import base64
+import io
+from typing import TYPE_CHECKING
+
+import aiohttp
+from PIL import Image as PILImage  # 使用别名避免冲突
+
+from astrbot import logger
+from astrbot.core.message.components import Image, Plain  # Import Image
+from astrbot.core.message.message_event_result import MessageChain
+from astrbot.core.platform.astr_message_event import AstrMessageEvent
+from astrbot.core.platform.astrbot_message import AstrBotMessage, MessageType
+from astrbot.core.platform.platform_metadata import PlatformMetadata
+
+if TYPE_CHECKING:
+    from .wechatpadpro_adapter import WeChatPadProAdapter
+
+
+class WeChatPadProMessageEvent(AstrMessageEvent):
+    def __init__(
+        self,
+        message_str: str,
+        message_obj: AstrBotMessage,
+        platform_meta: PlatformMetadata,
+        session_id: str,
+        adapter: "WeChatPadProAdapter",  # 传递适配器实例
+    ):
+        super().__init__(message_str, message_obj, platform_meta, session_id)
+        self.message_obj = message_obj  # Save the full message object
+        self.adapter = adapter  # Save the adapter instance
+
+    async def send(self, message: MessageChain):
+        async with aiohttp.ClientSession() as session:
+            for comp in message.chain:
+                await asyncio.sleep(1)
+                if isinstance(comp, Plain):
+                    await self._send_text(session, comp.text)
+                elif isinstance(comp, Image):
+                    await self._send_image(session, comp)
+        await super().send(message)
+
+    async def _send_image(self, session: aiohttp.ClientSession, comp: Image):
+        b64 = await comp.convert_to_base64()
+        raw = self._validate_base64(b64)
+        b64c = self._compress_image(raw)
+        payload = {
+            "MsgItem": [
+                {"ImageContent": b64c, "MsgType": 3, "ToUserName": self.session_id}
+            ]
+        }
+        url = f"{self.adapter.base_url}/message/SendImageNewMessage"
+        await self._post(session, url, payload)
+
+    async def _send_text(self, session: aiohttp.ClientSession, text: str):
+        if (
+            self.message_obj.type == MessageType.GROUP_MESSAGE  # 确保是群聊消息
+            and self.adapter.settings.get(
+                "reply_with_mention", False
+            )  # 检查适配器设置是否启用 reply_with_mention
+            and self.message_obj.sender  # 确保有发送者信息
+            and (
+                self.message_obj.sender.user_id or self.message_obj.sender.nickname
+            )  # 确保发送者有 ID 或昵称
+        ):
+            # 优先使用 nickname，如果没有则使用 user_id
+            mention_text = (
+                self.message_obj.sender.nickname or self.message_obj.sender.user_id
+            )
+            message_text = f"@{mention_text} {text}"
+            # logger.info(f"已添加 @ 信息: {message_text}")
+        else:
+            message_text = text
+        payload = {
+            "MsgItem": [
+                {"MsgType": 1, "TextContent": message_text, "ToUserName": self.session_id}
+            ]
+        }
+        url = f"{self.adapter.base_url}/message/SendTextMessage"
+        await self._post(session, url, payload)
+
+    @staticmethod
+    def _validate_base64(b64: str) -> bytes:
+        return base64.b64decode(b64, validate=True)
+
+    @staticmethod
+    def _compress_image(data: bytes) -> str:
+        img = PILImage.open(io.BytesIO(data))
+        buf = io.BytesIO()
+        if img.format == "JPEG":
+            img.save(buf, "JPEG", quality=80)
+        else:
+            if img.mode in ("RGBA", "P"):
+                img = img.convert("RGB")
+            img.save(buf, "JPEG", quality=80)
+        # logger.info("图片处理完成！！！")
+        return base64.b64encode(buf.getvalue()).decode()
+
+    async def _post(self, session, url, payload):
+        params = {"key": self.adapter.auth_key}
+        try:
+            async with session.post(url, params=params, json=payload) as resp:
+                data = await resp.json()
+                if resp.status != 200 or data.get("Code") != 200:
+                    logger.error(f"{url} failed: {resp.status} {data}")
+        except Exception as e:
+            logger.error(f"{url} error: {e}")
+
+
+# TODO: 添加对其他消息组件类型的处理 (Record, Video, At等)
+# elif isinstance(component, Record):
+#     pass
+# elif isinstance(component, Video):
+#     pass
+# elif isinstance(component, At):
+#     pass
+# ...

astrbot/core/platform/sources/wecom/wecom_adapter.py

@@ -1,28 +1,33 @@
+import asyncio
+import os
 import sys
 import uuid
-import asyncio
-import quart
 
+import quart
+from requests import Response
+from wechatpy.enterprise import WeChatClient, parse_message
+from wechatpy.enterprise.crypto import WeChatCrypto
+from wechatpy.enterprise.messages import ImageMessage, TextMessage, VoiceMessage
+from wechatpy.exceptions import InvalidSignatureException
+from wechatpy.messages import BaseMessage
+
+from astrbot.api.event import MessageChain
+from astrbot.api.message_components import Image, Plain, Record
 from astrbot.api.platform import (
-    Platform,
     AstrBotMessage,
     MessageMember,
-    PlatformMetadata,
     MessageType,
+    Platform,
+    PlatformMetadata,
+    register_platform_adapter,
 )
-from astrbot.api.event import MessageChain
-from astrbot.api.message_components import Plain, Image, Record
-from astrbot.core.platform.astr_message_event import MessageSesion
-from astrbot.api.platform import register_platform_adapter
 from astrbot.core import logger
-from requests import Response
+from astrbot.core.platform.astr_message_event import MessageSesion
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
-from wechatpy.enterprise.crypto import WeChatCrypto
-from wechatpy.enterprise import WeChatClient
-from wechatpy.enterprise.messages import TextMessage, ImageMessage, VoiceMessage
-from wechatpy.exceptions import InvalidSignatureException
-from wechatpy.enterprise import parse_message
 from .wecom_event import WecomPlatformEvent
+from .wecom_kf import WeChatKF
+from .wecom_kf_message import WeChatKFMessage
 
 if sys.version_info >= (3, 12):
     from typing import override
@@ -131,9 +136,40 @@ class WecomPlatformAdapter(Platform):
             self.config["corpid"].strip(),
             self.config["secret"].strip(),
         )
+
+        # 微信客服
+        self.kf_name = self.config.get("kf_name", None)
+        if self.kf_name:
+            # inject
+            self.wechat_kf_api = WeChatKF(client=self.client)
+            self.wechat_kf_message_api = WeChatKFMessage(self.client)
+            self.client.kf = self.wechat_kf_api
+            self.client.kf_message = self.wechat_kf_message_api
+
         self.client.API_BASE_URL = self.api_base_url
 
-        async def callback(msg):
+        async def callback(msg: BaseMessage):
+            if msg.type == "unknown" and msg._data["Event"] == "kf_msg_or_event":
+
+                def get_latest_msg_item() -> dict | None:
+                    token = msg._data["Token"]
+                    kfid = msg._data["OpenKfId"]
+                    has_more = 1
+                    ret = {}
+                    while has_more:
+                        ret = self.wechat_kf_api.sync_msg(token, kfid)
+                        has_more = ret["has_more"]
+                    msg_list = ret.get("msg_list", [])
+                    if msg_list:
+                        return msg_list[-1]
+                    return None
+
+                msg_new = await asyncio.get_event_loop().run_in_executor(
+                    None, get_latest_msg_item
+                )
+                if msg_new:
+                    await self.convert_wechat_kf_message(msg_new)
+                return
             await self.convert_message(msg)
 
         self.server.callback = callback
@@ -153,9 +189,39 @@ class WecomPlatformAdapter(Platform):
 
     @override
     async def run(self):
+        loop = asyncio.get_event_loop()
+        if self.kf_name:
+            try:
+                acc_list = (
+                    await loop.run_in_executor(
+                        None, self.wechat_kf_api.get_account_list
+                    )
+                ).get("account_list", [])
+                logger.debug(f"获取到微信客服列表: {str(acc_list)}")
+                for acc in acc_list:
+                    name = acc.get("name", None)
+                    if name != self.kf_name:
+                        continue
+                    open_kfid = acc.get("open_kfid", None)
+                    if not open_kfid:
+                        logger.error("获取微信客服失败，open_kfid 为空。")
+                    logger.debug(f"Found open_kfid: {str(open_kfid)}")
+                    kf_url = (
+                        await loop.run_in_executor(
+                            None,
+                            self.wechat_kf_api.add_contact_way,
+                            open_kfid,
+                            "astrbot_placeholder",
+                        )
+                    ).get("url", "")
+                    logger.info(
+                        f"请打开以下链接，在微信扫码以获取客服微信: https://api.cl2wm.cn/api/qrcode/code?text={kf_url}"
+                    )
+            except Exception as e:
+                logger.error(e)
         await self.server.start_polling()
 
-    async def convert_message(self, msg):
+    async def convert_message(self, msg: BaseMessage) -> AstrBotMessage | None:
         abm = AstrBotMessage()
         if msg.type == "text":
             assert isinstance(msg, TextMessage)
@@ -191,14 +257,15 @@ class WecomPlatformAdapter(Platform):
             resp: Response = await asyncio.get_event_loop().run_in_executor(
                 None, self.client.media.download, msg.media_id
             )
-            path = f"data/temp/wecom_{msg.media_id}.amr"
+            temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+            path = os.path.join(temp_dir, f"wecom_{msg.media_id}.amr")
             with open(path, "wb") as f:
                 f.write(resp.content)
 
             try:
                 from pydub import AudioSegment
 
-                path_wav = f"data/temp/wecom_{msg.media_id}.wav"
+                path_wav = os.path.join(temp_dir, f"wecom_{msg.media_id}.wav")
                 audio = AudioSegment.from_file(path)
                 audio.export(path_wav, format="wav")
             except Exception as e:
@@ -218,10 +285,43 @@ class WecomPlatformAdapter(Platform):
             abm.timestamp = msg.time
             abm.session_id = abm.sender.user_id
             abm.raw_message = msg
+        else:
+            logger.warning(f"暂未实现的事件: {msg.type}")
+            return
 
         logger.info(f"abm: {abm}")
         await self.handle_msg(abm)
 
+    async def convert_wechat_kf_message(self, msg: dict) -> AstrBotMessage | None:
+        msgtype = msg.get("msgtype", None)
+        external_userid = msg.get("external_userid", None)
+        abm = AstrBotMessage()
+        abm.raw_message = msg
+        abm.raw_message["_wechat_kf_flag"] = None  # 方便处理
+        abm.self_id = msg["open_kfid"]
+        abm.sender = MessageMember(external_userid, external_userid)
+        abm.session_id = external_userid
+        abm.type = MessageType.FRIEND_MESSAGE
+        abm.message_id = msg.get("msgid", uuid.uuid4().hex[:8])
+        if msgtype == "text":
+            text = msg.get("text", {}).get("content", "").strip()
+            abm.message = [Plain(text=text)]
+            abm.message_str = text
+        elif msgtype == "image":
+            media_id = msg.get("image", {}).get("media_id", "")
+            resp: Response = await asyncio.get_event_loop().run_in_executor(
+                None, self.client.media.download, media_id
+            )
+            path = f"data/temp/wechat_kf_{media_id}.jpg"
+            with open(path, "wb") as f:
+                f.write(resp.content)
+            abm.message = [Image(file=path, url=path)]
+            abm.message_str = "[图片]"
+        else:
+            logger.warning(f"未实现的微信客服消息事件: {msg}")
+            return
+        await self.handle_msg(abm)
+
     async def handle_msg(self, message: AstrBotMessage):
         message_event = WecomPlatformEvent(
             message_str=message.message_str,
@@ -237,5 +337,8 @@ class WecomPlatformAdapter(Platform):
 
     async def terminate(self):
         self.server.shutdown_event.set()
-        await self.server.server.shutdown()
+        try:
+            await self.server.server.shutdown()
+        except Exception as _:
+            pass
         logger.info("企业微信 适配器已被优雅地关闭")

astrbot/core/platform/sources/wecom/wecom_event.py

@@ -1,10 +1,14 @@
+import os
 import uuid
+import asyncio
 from astrbot.api.event import AstrMessageEvent, MessageChain
 from astrbot.api.platform import AstrBotMessage, PlatformMetadata
 from astrbot.api.message_components import Plain, Image, Record
 from wechatpy.enterprise import WeChatClient
+from .wecom_kf_message import WeChatKFMessage
 
 from astrbot.api import logger
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 try:
     import pydub
@@ -33,54 +37,158 @@ class WecomPlatformEvent(AstrMessageEvent):
     ):
         pass
 
+    async def split_plain(self, plain: str) -> list[str]:
+        """将长文本分割成多个小文本, 每个小文本长度不超过 2048 字符
+
+        Args:
+            plain (str): 要分割的长文本
+        Returns:
+            list[str]: 分割后的文本列表
+        """
+        if len(plain) <= 2048:
+            return [plain]
+        else:
+            result = []
+            start = 0
+            while start < len(plain):
+                # 剩下的字符串长度<2048时结束
+                if start + 2048 >= len(plain):
+                    result.append(plain[start:])
+                    break
+
+                # 向前搜索分割标点符号
+                end = min(start + 2048, len(plain))
+                cut_position = end
+                for i in range(end, start, -1):
+                    if i < len(plain) and plain[i - 1] in [
+                        "。",
+                        "！",
+                        "？",
+                        ".",
+                        "!",
+                        "?",
+                        "\n",
+                        ";",
+                        "；",
+                    ]:
+                        cut_position = i
+                        break
+
+                # 没找到合适的位置分割, 直接切分
+                if cut_position == end and end < len(plain):
+                    cut_position = end
+
+                result.append(plain[start:cut_position])
+                start = cut_position
+
+            return result
+
     async def send(self, message: MessageChain):
         message_obj = self.message_obj
 
-        for comp in message.chain:
-            if isinstance(comp, Plain):
-                self.client.message.send_text(
-                    message_obj.self_id, message_obj.session_id, comp.text
-                )
-            elif isinstance(comp, Image):
-                img_path = await comp.convert_to_file_path()
+        is_wechat_kf = hasattr(self.client, "kf_message")
+        if is_wechat_kf:
+            # 微信客服
+            kf_message_api = getattr(self.client, "kf_message", None)
+            if not kf_message_api:
+                logger.warning("未找到微信客服发送消息方法。")
+                return
+            assert isinstance(kf_message_api, WeChatKFMessage)
+            user_id = self.get_sender_id()
+            for comp in message.chain:
+                if isinstance(comp, Plain):
+                    # Split long text messages if needed
+                    plain_chunks = await self.split_plain(comp.text)
+                    for chunk in plain_chunks:
+                        kf_message_api.send_text(user_id, self.get_self_id(), chunk)
+                        await asyncio.sleep(0.5)  # Avoid sending too fast
+                elif isinstance(comp, Image):
+                    img_path = await comp.convert_to_file_path()
 
-                with open(img_path, "rb") as f:
-                    try:
-                        response = self.client.media.upload("image", f)
-                    except Exception as e:
-                        logger.error(f"企业微信上传图片失败: {e}")
-                        await self.send(
-                            MessageChain().message(f"企业微信上传图片失败: {e}")
+                    with open(img_path, "rb") as f:
+                        try:
+                            response = self.client.media.upload("image", f)
+                        except Exception as e:
+                            logger.error(f"微信客服上传图片失败: {e}")
+                            await self.send(
+                                MessageChain().message(f"微信客服上传图片失败: {e}")
+                            )
+                            return
+                        logger.debug(f"微信客服上传图片返回: {response}")
+                        kf_message_api.send_image(
+                            user_id,
+                            self.get_self_id(),
+                            response["media_id"],
                         )
-                        return
-                    logger.info(f"企业微信上传图片返回: {response}")
-                    self.client.message.send_image(
-                        message_obj.self_id,
-                        message_obj.session_id,
-                        response["media_id"],
-                    )
-            elif isinstance(comp, Record):
-                record_path = await comp.convert_to_file_path()
-                # 转成amr
-                record_path_amr = f"data/temp/{uuid.uuid4()}.amr"
-                pydub.AudioSegment.from_wav(record_path).export(
-                    record_path_amr, format="amr"
-                )
+                else:
+                    logger.warning(f"还没实现这个消息类型的发送逻辑: {comp.type}。")
+        else:
+            # 企业微信应用
+            for comp in message.chain:
+                if isinstance(comp, Plain):
+                    # Split long text messages if needed
+                    plain_chunks = await self.split_plain(comp.text)
+                    for chunk in plain_chunks:
+                        self.client.message.send_text(
+                            message_obj.self_id, message_obj.session_id, chunk
+                        )
+                        await asyncio.sleep(0.5)  # Avoid sending too fast
+                elif isinstance(comp, Image):
+                    img_path = await comp.convert_to_file_path()
 
-                with open(record_path_amr, "rb") as f:
-                    try:
-                        response = self.client.media.upload("voice", f)
-                    except Exception as e:
-                        logger.error(f"企业微信上传语音失败: {e}")
-                        await self.send(
-                            MessageChain().message(f"企业微信上传语音失败: {e}")
+                    with open(img_path, "rb") as f:
+                        try:
+                            response = self.client.media.upload("image", f)
+                        except Exception as e:
+                            logger.error(f"企业微信上传图片失败: {e}")
+                            await self.send(
+                                MessageChain().message(f"企业微信上传图片失败: {e}")
+                            )
+                            return
+                        logger.debug(f"企业微信上传图片返回: {response}")
+                        self.client.message.send_image(
+                            message_obj.self_id,
+                            message_obj.session_id,
+                            response["media_id"],
                         )
-                        return
-                    logger.info(f"企业微信上传语音返回: {response}")
-                    self.client.message.send_voice(
-                        message_obj.self_id,
-                        message_obj.session_id,
-                        response["media_id"],
+                elif isinstance(comp, Record):
+                    record_path = await comp.convert_to_file_path()
+                    # 转成amr
+                    temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+                    record_path_amr = os.path.join(temp_dir, f"{uuid.uuid4()}.amr")
+                    pydub.AudioSegment.from_wav(record_path).export(
+                        record_path_amr, format="amr"
                     )
 
+                    with open(record_path_amr, "rb") as f:
+                        try:
+                            response = self.client.media.upload("voice", f)
+                        except Exception as e:
+                            logger.error(f"企业微信上传语音失败: {e}")
+                            await self.send(
+                                MessageChain().message(f"企业微信上传语音失败: {e}")
+                            )
+                            return
+                        logger.info(f"企业微信上传语音返回: {response}")
+                        self.client.message.send_voice(
+                            message_obj.self_id,
+                            message_obj.session_id,
+                            response["media_id"],
+                        )
+                else:
+                    logger.warning(f"还没实现这个消息类型的发送逻辑: {comp.type}。")
+
         await super().send(message)
+
+    async def send_streaming(self, generator, use_fallback: bool = False):
+        buffer = None
+        async for chain in generator:
+            if not buffer:
+                buffer = chain
+            else:
+                buffer.chain.extend(chain.chain)
+        if not buffer:
+            return
+        buffer.squash_plain()
+        await self.send(buffer)
+        return await super().send_streaming(generator, use_fallback)

astrbot/core/platform/sources/wecom/wecom_kf.py

@@ -0,0 +1,278 @@
+# -*- coding: utf-8 -*-
+
+"""
+The MIT License (MIT)
+
+Copyright (c) 2014-2020 messense
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+"""
+
+from wechatpy.client.api.base import BaseWeChatAPI
+
+
+class WeChatKF(BaseWeChatAPI):
+    """
+    微信客服接口
+
+    https://work.weixin.qq.com/api/doc/90000/90135/94670
+    """
+
+    def sync_msg(self, token, open_kfid, cursor="", limit=1000):
+        """
+        微信客户发送的消息、接待人员在企业微信回复的消息、发送消息接口发送失败事件（如被用户拒收）
+        、客户点击菜单消息的回复消息，可以通过该接口获取具体的消息内容和事件。不支持读取通过发送消息接口发送的消息。
+        支持的消息类型：文本、图片、语音、视频、文件、位置、链接、名片、小程序、事件。
+
+
+        :param token: 回调事件返回的token字段，10分钟内有效；可不填，如果不填接口有严格的频率限制。不多于128字节
+        :param open_kfid: 客服帐号ID
+        :param cursor: 上一次调用时返回的next_cursor，第一次拉取可以不填。不多于64字节
+        :param limit: 期望请求的数据量，默认值和最大值都为1000。
+        注意：可能会出现返回条数少于limit的情况，需结合返回的has_more字段判断是否继续请求。
+        :return: 接口调用结果
+        """
+        data = {"token": token, "cursor": cursor, "limit": limit, "open_kfid": open_kfid}
+        return self._post("kf/sync_msg", data=data)
+
+    def get_service_state(self, open_kfid, external_userid):
+        """
+        获取会话状态
+
+        ID	状态	说明
+        0	未处理	新会话接入。可选择：1.直接用API自动回复消息。2.放进待接入池等待接待人员接待。3.指定接待人员进行接待
+        1	由智能助手接待	可使用API回复消息。可选择转入待接入池或者指定接待人员处理。
+        2	待接入池排队中	在待接入池中排队等待接待人员接入。可选择转为指定人员接待
+        3	由人工接待	人工接待中。可选择结束会话
+        4	已结束	会话已经结束。不允许变更会话状态，等待用户重新发起咨询
+
+        :param open_kfid: 客服帐号ID
+        :param external_userid: 微信客户的external_userid
+        :return: 接口调用结果
+        """
+        data = {
+            "open_kfid": open_kfid,
+            "external_userid": external_userid,
+        }
+        return self._post("kf/service_state/get", data=data)
+
+    def trans_service_state(self, open_kfid, external_userid, service_state, servicer_userid=""):
+        """
+        变更会话状态
+
+        :param open_kfid: 客服帐号ID
+        :param external_userid: 微信客户的external_userid
+        :param service_state: 当前的会话状态，状态定义参考概述中的表格
+        :return: 接口调用结果
+        """
+        data = {
+            "open_kfid": open_kfid,
+            "external_userid": external_userid,
+            "service_state": service_state,
+        }
+        if servicer_userid:
+            data["servicer_userid"] = servicer_userid
+        return self._post("kf/service_state/trans", data=data)
+
+    def get_servicer_list(self, open_kfid):
+        """
+        获取接待人员列表
+
+        :param open_kfid: 客服帐号ID
+        :return: 接口调用结果
+        """
+        data = {
+            "open_kfid": open_kfid,
+        }
+        return self._get("kf/servicer/list", params=data)
+
+    def add_servicer(self, open_kfid, userid_list):
+        """
+        添加接待人员
+        添加指定客服帐号的接待人员。
+
+        :param open_kfid: 客服帐号ID
+        :param userid_list: 接待人员userid列表
+        :return: 接口调用结果
+        """
+        if not isinstance(userid_list, list):
+            userid_list = [userid_list]
+
+        data = {
+            "open_kfid": open_kfid,
+            "userid_list": userid_list,
+        }
+        return self._post("kf/servicer/add", data=data)
+
+    def del_servicer(self, open_kfid, userid_list):
+        """
+        删除接待人员
+        从客服帐号删除接待人员
+
+        :param open_kfid: 客服帐号ID
+        :param userid_list: 接待人员userid列表
+        :return: 接口调用结果
+        """
+        if not isinstance(userid_list, list):
+            userid_list = [userid_list]
+
+        data = {
+            "open_kfid": open_kfid,
+            "userid_list": userid_list,
+        }
+        return self._post("kf/servicer/del", data=data)
+
+    def batchget_customer(self, external_userid_list):
+        """
+        客户基本信息获取
+
+        :param external_userid_list: external_userid列表
+        :return: 接口调用结果
+        """
+        if not isinstance(external_userid_list, list):
+            external_userid_list = [external_userid_list]
+
+        data = {
+            "external_userid_list": external_userid_list,
+        }
+        return self._post("kf/customer/batchget", data=data)
+
+    def get_account_list(self):
+        """
+        获取客服帐号列表
+
+        :return: 接口调用结果
+        """
+        return self._get("kf/account/list")
+
+    def add_contact_way(self, open_kfid, scene):
+        """
+        获取客服帐号链接
+
+        :param open_kfid: 	客服帐号ID
+        :param scene: 场景值，字符串类型，由开发者自定义。不多于32字节;字符串取值范围(正则表达式)：[0-9a-zA-Z_-]*
+        :return: 接口调用结果
+        """
+        data = {"open_kfid": open_kfid, "scene": scene}
+        return self._post("kf/add_contact_way", data=data)
+
+    def get_upgrade_service_config(self):
+        """
+        获取配置的专员与客户群
+
+        :return: 接口调用结果
+        """
+        return self._get("kf/customer/get_upgrade_service_config")
+
+    def upgrade_service(self, open_kfid, external_userid, service_type, member=None, groupchat=None):
+        """
+        为客户升级为专员或客户群服务
+
+        :param open_kfid: 	客服帐号ID
+        :param external_userid: 微信客户的external_userid
+        :param service_type: 表示是升级到专员服务还是客户群服务。1:专员服务。2:客户群服务
+        :param member: 推荐的服务专员，type等于1时有效
+        :param groupchat: 推荐的客户群，type等于2时有效
+        :return: 接口调用结果
+        """
+
+        data = {
+            "open_kfid": open_kfid,
+            "external_userid": external_userid,
+            "type": service_type,
+        }
+        if service_type == 1:
+            data["member"] = member
+        else:
+            data["groupchat"] = groupchat
+        return self._post("kf/customer/upgrade_service", data=data)
+
+    def cancel_upgrade_service(self, open_kfid, external_userid):
+        """
+        为客户取消推荐
+
+        :param open_kfid: 	客服帐号ID
+        :param external_userid: 微信客户的external_userid
+        :return: 接口调用结果
+        """
+
+        data = {"open_kfid": open_kfid, "external_userid": external_userid}
+        return self._post("kf/customer/cancel_upgrade_service", data=data)
+
+    def send_msg_on_event(self, code, msgtype, msg_content, msgid=None):
+        """
+        当特定的事件回调消息包含code字段，可以此code为凭证，调用该接口给用户发送相应事件场景下的消息，如客服欢迎语。
+        支持发送消息类型：文本、菜单消息。
+
+        :param code: 事件响应消息对应的code。通过事件回调下发，仅可使用一次。
+        :param msgtype: 消息类型。对不同的msgtype，有相应的结构描述，详见消息类型
+        :param msg_content: 目前支持文本与菜单消息，具体查看文档
+        :param msgid: 消息ID。如果请求参数指定了msgid，则原样返回，否则系统自动生成并返回。不多于32字节；
+                      字符串取值范围(正则表达式)：[0-9a-zA-Z_-]*
+        :return: 接口调用结果
+        """
+
+        data = {"code": code, "msgtype": msgtype}
+        if msgid:
+            data["msgid"] = msgid
+        data.update(msg_content)
+        return self._post("kf/send_msg_on_event", data=data)
+
+    def get_corp_statistic(self, start_time, end_time, open_kfid=None):
+        """
+        获取「客户数据统计」企业汇总数据
+
+        :param start_time: 开始时间
+        :param end_time: 结束时间
+        :param open_kfid: 	客服帐号ID
+        :return: 接口调用结果
+        """
+        data = {"open_kfid": open_kfid, "start_time": start_time, "end_time": end_time}
+        return self._post("kf/get_corp_statistic", data=data)
+
+    def get_servicer_statistic(self, start_time, end_time, open_kfid=None, servicer_userid=None):
+        """
+        获取「客户数据统计」接待人员明细数据
+
+        :param start_time: 开始时间
+        :param end_time: 结束时间
+        :param open_kfid: 	客服帐号ID
+        :param servicer_userid: 接待人员
+        :return: 接口调用结果
+        """
+        data = {
+            "open_kfid": open_kfid,
+            "servicer_userid": servicer_userid,
+            "start_time": start_time,
+            "end_time": end_time,
+        }
+        return self._post("kf/get_servicer_statistic", data=data)
+
+    def account_update(self, open_kfid, name, media_id):
+        """
+        修改客服账号
+
+        :param open_kfid: 客服帐号ID
+        :param name: 客服名称
+        :param media_id: 客服头像临时素材
+
+        :return: 接口调用结果
+        """
+        data = {"open_kfid": open_kfid, "name": name, "media_id": media_id}
+        return self._post("kf/account/update", data=data)

astrbot/core/platform/sources/wecom/wecom_kf_message.py

@@ -0,0 +1,159 @@
+"""
+The MIT License (MIT)
+
+Copyright (c) 2014-2020 messense
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+"""
+
+from optionaldict import optionaldict
+
+from wechatpy.client.api.base import BaseWeChatAPI
+
+class WeChatKFMessage(BaseWeChatAPI):
+    """
+    发送微信客服消息
+
+    https://work.weixin.qq.com/api/doc/90000/90135/94677
+
+    支持：
+    * 文本消息
+    * 图片消息
+    * 语音消息
+    * 视频消息
+    * 文件消息
+    * 图文链接
+    * 小程序
+    * 菜单消息
+    * 地理位置
+    """
+
+    def send(self, user_id, open_kfid, msgid="", msg=None):
+        """
+        当微信客户处于“新接入待处理”或“由智能助手接待”状态下，可调用该接口给用户发送消息。
+        注意仅当微信客户在主动发送消息给客服后的48小时内，企业可发送消息给客户，最多可发送5条消息；若用户继续发送消息，企业可再次下发消息。
+        支持发送消息类型：文本、图片、语音、视频、文件、图文、小程序、菜单消息、地理位置。
+
+        :param user_id: 指定接收消息的客户UserID
+        :param open_kfid: 指定发送消息的客服帐号ID
+        :param msgid: 指定消息ID
+        :param tag_ids: 标签ID列表。
+        :param msg: 发送消息的 dict 对象
+        :type msg: dict | None
+        :return: 接口调用结果
+        """
+        msg = msg or {}
+        data = {
+            "touser": user_id,
+            "open_kfid": open_kfid,
+        }
+        if msgid:
+            data["msgid"] = msgid
+        data.update(msg)
+        return self._post("kf/send_msg", data=data)
+
+    def send_text(self, user_id, open_kfid, content, msgid=""):
+        return self.send(
+            user_id,
+            open_kfid,
+            msgid,
+            msg={"msgtype": "text", "text": {"content": content}},
+        )
+
+    def send_image(self, user_id, open_kfid, media_id, msgid=""):
+        return self.send(
+            user_id,
+            open_kfid,
+            msgid,
+            msg={"msgtype": "image", "image": {"media_id": media_id}},
+        )
+
+    def send_voice(self, user_id, open_kfid, media_id, msgid=""):
+        return self.send(
+            user_id,
+            open_kfid,
+            msgid,
+            msg={"msgtype": "voice", "voice": {"media_id": media_id}},
+        )
+
+    def send_video(self, user_id, open_kfid, media_id, msgid=""):
+        video_data = optionaldict()
+        video_data["media_id"] = media_id
+
+        return self.send(
+            user_id,
+            open_kfid,
+            msgid,
+            msg={"msgtype": "video", "video": dict(video_data)},
+        )
+
+    def send_file(self, user_id, open_kfid, media_id, msgid=""):
+        return self.send(
+            user_id,
+            open_kfid,
+            msgid,
+            msg={"msgtype": "file", "file": {"media_id": media_id}},
+        )
+
+    def send_articles_link(self, user_id, open_kfid, article, msgid=""):
+        articles_data = {
+            "title": article["title"],
+            "desc": article["desc"],
+            "url": article["url"],
+            "thumb_media_id": article["thumb_media_id"],
+        }
+        return self.send(
+            user_id,
+            open_kfid,
+            msgid,
+            msg={"msgtype": "news", "link": {"link": articles_data}},
+        )
+
+    def send_msgmenu(self, user_id, open_kfid, head_content, menu_list, tail_content, msgid=""):
+        return self.send(
+            user_id,
+            open_kfid,
+            msgid,
+            msg={
+                "msgtype": "msgmenu",
+                "msgmenu": {"head_content": head_content, "list": menu_list, "tail_content": tail_content},
+            },
+        )
+
+    def send_location(self, user_id, open_kfid, name, address, latitude, longitude, msgid=""):
+        return self.send(
+            user_id,
+            open_kfid,
+            msgid,
+            msg={
+                "msgtype": "location",
+                "msgmenu": {"name": name, "address": address, "latitude": latitude, "longitude": longitude},
+            },
+        )
+
+    def send_miniprogram(self, user_id, open_kfid, appid, title, thumb_media_id, pagepath, msgid=""):
+        return self.send(
+            user_id,
+            open_kfid,
+            msgid,
+            msg={
+                "msgtype": "miniprogram",
+                "msgmenu": {"appid": appid, "title": title, "thumb_media_id": thumb_media_id, "pagepath": pagepath},
+            },
+        )

astrbot/core/platform/sources/weixin_official_account/weixin_offacc_adapter.py

@@ -0,0 +1,286 @@
+import sys
+import uuid
+import asyncio
+import quart
+
+from astrbot.api.platform import (
+    Platform,
+    AstrBotMessage,
+    MessageMember,
+    PlatformMetadata,
+    MessageType,
+)
+from astrbot.api.event import MessageChain
+from astrbot.api.message_components import Plain, Image, Record
+from astrbot.core.platform.astr_message_event import MessageSesion
+from astrbot.api.platform import register_platform_adapter
+from astrbot.core import logger
+from requests import Response
+
+from wechatpy.utils import check_signature
+from wechatpy.crypto import WeChatCrypto
+from wechatpy import WeChatClient
+from wechatpy.messages import TextMessage, ImageMessage, VoiceMessage, BaseMessage
+from wechatpy.exceptions import InvalidSignatureException
+from wechatpy import parse_message
+from .weixin_offacc_event import WeixinOfficialAccountPlatformEvent
+
+if sys.version_info >= (3, 12):
+    from typing import override
+else:
+    from typing_extensions import override
+
+
+class WecomServer:
+    def __init__(self, event_queue: asyncio.Queue, config: dict):
+        self.server = quart.Quart(__name__)
+        self.port = int(config.get("port"))
+        self.callback_server_host = config.get("callback_server_host", "0.0.0.0")
+        self.token = config.get("token")
+        self.encoding_aes_key = config.get("encoding_aes_key")
+        self.appid = config.get("appid")
+        self.server.add_url_rule(
+            "/callback/command", view_func=self.verify, methods=["GET"]
+        )
+        self.server.add_url_rule(
+            "/callback/command", view_func=self.callback_command, methods=["POST"]
+        )
+        self.crypto = WeChatCrypto(self.token, self.encoding_aes_key, self.appid)
+
+        self.event_queue = event_queue
+
+        self.callback = None
+        self.shutdown_event = asyncio.Event()
+
+    async def verify(self):
+        logger.info(f"验证请求有效性: {quart.request.args}")
+
+        args = quart.request.args
+        if not args.get("signature", None):
+            logger.error("未知的响应，请检查回调地址是否填写正确。")
+            return "err"
+        try:
+            check_signature(
+                self.token,
+                args.get("signature"),
+                args.get("timestamp"),
+                args.get("nonce"),
+            )
+            logger.info("验证请求有效性成功。")
+            return args.get("echostr", "empty")
+        except InvalidSignatureException:
+            logger.error("验证请求有效性失败，签名异常，请检查配置。")
+            return "err"
+
+    async def callback_command(self):
+        data = await quart.request.get_data()
+        msg_signature = quart.request.args.get("msg_signature")
+        timestamp = quart.request.args.get("timestamp")
+        nonce = quart.request.args.get("nonce")
+        try:
+            xml = self.crypto.decrypt_message(data, msg_signature, timestamp, nonce)
+        except InvalidSignatureException:
+            logger.error("解密失败，签名异常，请检查配置。")
+            raise
+        else:
+            msg = parse_message(xml)
+            logger.info(f"解析成功: {msg}")
+
+            if self.callback:
+                result_xml = await self.callback(msg)
+                if not result_xml:
+                    return "success"
+                if isinstance(result_xml, str):
+                    return result_xml
+
+        return "success"
+
+    async def start_polling(self):
+        logger.info(
+            f"将在 {self.callback_server_host}:{self.port} 端口启动 微信公众平台 适配器。"
+        )
+        await self.server.run_task(
+            host=self.callback_server_host,
+            port=self.port,
+            shutdown_trigger=self.shutdown_trigger,
+        )
+
+    async def shutdown_trigger(self):
+        await self.shutdown_event.wait()
+
+
+@register_platform_adapter("weixin_official_account", "微信公众平台 适配器")
+class WeixinOfficialAccountPlatformAdapter(Platform):
+    def __init__(
+        self, platform_config: dict, platform_settings: dict, event_queue: asyncio.Queue
+    ) -> None:
+        super().__init__(event_queue)
+        self.config = platform_config
+        self.settingss = platform_settings
+        self.client_self_id = uuid.uuid4().hex[:8]
+        self.api_base_url = platform_config.get(
+            "api_base_url", "https://api.weixin.qq.com/cgi-bin/"
+        )
+        self.active_send_mode = self.config.get("active_send_mode", False)
+
+        if not self.api_base_url:
+            self.api_base_url = "https://api.weixin.qq.com/cgi-bin/"
+
+        if self.api_base_url.endswith("/"):
+            self.api_base_url = self.api_base_url[:-1]
+        if not self.api_base_url.endswith("/cgi-bin"):
+            self.api_base_url += "/cgi-bin"
+
+        if not self.api_base_url.endswith("/"):
+            self.api_base_url += "/"
+
+        self.server = WecomServer(self._event_queue, self.config)
+
+        self.client = WeChatClient(
+            self.config["appid"].strip(),
+            self.config["secret"].strip(),
+        )
+
+        self.client.API_BASE_URL = self.api_base_url
+
+        # 微信公众号必须 5 秒内进行回复，否则会重试 3 次，我们需要对其进行消息排重
+        # msgid -> Future
+        self.wexin_event_workers: dict[str, asyncio.Future] = {}
+
+        async def callback(msg: BaseMessage):
+            try:
+                if self.active_send_mode:
+                    await self.convert_message(msg, None)
+                else:
+                    if msg.id in self.wexin_event_workers:
+                        future = self.wexin_event_workers[msg.id]
+                        logger.debug(f"duplicate message id checked: {msg.id}")
+                    else:
+                        future = asyncio.get_event_loop().create_future()
+                        self.wexin_event_workers[msg.id] = future
+                        await self.convert_message(msg, future)
+                    # I love shield so much!
+                    result = await asyncio.wait_for(asyncio.shield(future), 60)  # wait for 60s
+                    logger.debug(f"Got future result: {result}")
+                    self.wexin_event_workers.pop(msg.id, None)
+                    return result  # xml. see weixin_offacc_event.py
+            except asyncio.TimeoutError:
+                pass
+            except Exception as e:
+                logger.error(f"转换消息时出现异常: {e}")
+
+        self.server.callback = callback
+
+    @override
+    async def send_by_session(
+        self, session: MessageSesion, message_chain: MessageChain
+    ):
+        await super().send_by_session(session, message_chain)
+
+    @override
+    def meta(self) -> PlatformMetadata:
+        return PlatformMetadata(
+            "weixin_official_account",
+            "微信公众平台 适配器",
+        )
+
+    @override
+    async def run(self):
+        await self.server.start_polling()
+
+    async def convert_message(
+        self, msg, future: asyncio.Future = None
+    ) -> AstrBotMessage | None:
+        abm = AstrBotMessage()
+        if isinstance(msg, TextMessage):
+            abm.message_str = msg.content
+            abm.self_id = str(msg.target)
+            abm.message = [Plain(msg.content)]
+            abm.type = MessageType.FRIEND_MESSAGE
+            abm.sender = MessageMember(
+                msg.source,
+                msg.source,
+            )
+            abm.message_id = msg.id
+            abm.timestamp = msg.time
+            abm.session_id = abm.sender.user_id
+        elif msg.type == "image":
+            assert isinstance(msg, ImageMessage)
+            abm.message_str = "[图片]"
+            abm.self_id = str(msg.target)
+            abm.message = [Image(file=msg.image, url=msg.image)]
+            abm.type = MessageType.FRIEND_MESSAGE
+            abm.sender = MessageMember(
+                msg.source,
+                msg.source,
+            )
+            abm.message_id = msg.id
+            abm.timestamp = msg.time
+            abm.session_id = abm.sender.user_id
+        elif msg.type == "voice":
+            assert isinstance(msg, VoiceMessage)
+
+            resp: Response = await asyncio.get_event_loop().run_in_executor(
+                None, self.client.media.download, msg.media_id
+            )
+            path = f"data/temp/wecom_{msg.media_id}.amr"
+            with open(path, "wb") as f:
+                f.write(resp.content)
+
+            try:
+                from pydub import AudioSegment
+
+                path_wav = f"data/temp/wecom_{msg.media_id}.wav"
+                audio = AudioSegment.from_file(path)
+                audio.export(path_wav, format="wav")
+            except Exception as e:
+                logger.error(
+                    f"转换音频失败: {e}。如果没有安装 pydub 和 ffmpeg 请先安装。"
+                )
+                path_wav = path
+                return
+
+            abm.message_str = ""
+            abm.self_id = str(msg.target)
+            abm.message = [Record(file=path_wav, url=path_wav)]
+            abm.type = MessageType.FRIEND_MESSAGE
+            abm.sender = MessageMember(
+                msg.source,
+                msg.source,
+            )
+            abm.message_id = msg.id
+            abm.timestamp = msg.time
+            abm.session_id = abm.sender.user_id
+        else:
+            logger.warning(f"暂未实现的事件: {msg.type}")
+            future.set_result(None)
+            return
+        # 很不优雅 :(
+        abm.raw_message = {
+            "message": msg,
+            "future": future,
+            "active_send_mode": self.active_send_mode,
+        }
+        logger.info(f"abm: {abm}")
+        await self.handle_msg(abm)
+
+    async def handle_msg(self, message: AstrBotMessage):
+        message_event = WeixinOfficialAccountPlatformEvent(
+            message_str=message.message_str,
+            message_obj=message,
+            platform_meta=self.meta(),
+            session_id=message.session_id,
+            client=self.client,
+        )
+        self.commit_event(message_event)
+
+    def get_client(self) -> WeChatClient:
+        return self.client
+
+    async def terminate(self):
+        self.server.shutdown_event.set()
+        try:
+            await self.server.server.shutdown()
+        except Exception as _:
+            pass
+        logger.info("微信公众平台 适配器已被优雅地关闭")

astrbot/core/platform/sources/weixin_official_account/weixin_offacc_event.py

@@ -0,0 +1,185 @@
+import uuid
+import asyncio
+from astrbot.api.event import AstrMessageEvent, MessageChain
+from astrbot.api.platform import AstrBotMessage, PlatformMetadata
+from astrbot.api.message_components import Plain, Image, Record
+from wechatpy import WeChatClient
+from wechatpy.replies import TextReply, ImageReply, VoiceReply
+
+
+from astrbot.api import logger
+
+try:
+    import pydub
+except Exception:
+    logger.warning(
+        "检测到 pydub 库未安装，微信公众平台将无法语音收发。如需使用语音，请前往管理面板 -> 控制台 -> 安装 Pip 库安装 pydub。"
+    )
+    pass
+
+
+class WeixinOfficialAccountPlatformEvent(AstrMessageEvent):
+    def __init__(
+        self,
+        message_str: str,
+        message_obj: AstrBotMessage,
+        platform_meta: PlatformMetadata,
+        session_id: str,
+        client: WeChatClient,
+    ):
+        super().__init__(message_str, message_obj, platform_meta, session_id)
+        self.client = client
+
+    @staticmethod
+    async def send_with_client(
+        client: WeChatClient, message: MessageChain, user_name: str
+    ):
+        pass
+
+    async def split_plain(self, plain: str) -> list[str]:
+        """将长文本分割成多个小文本, 每个小文本长度不超过 2048 字符
+
+        Args:
+            plain (str): 要分割的长文本
+        Returns:
+            list[str]: 分割后的文本列表
+        """
+        if len(plain) <= 2048:
+            return [plain]
+        else:
+            result = []
+            start = 0
+            while start < len(plain):
+                # 剩下的字符串长度<2048时结束
+                if start + 2048 >= len(plain):
+                    result.append(plain[start:])
+                    break
+
+                # 向前搜索分割标点符号
+                end = min(start + 2048, len(plain))
+                cut_position = end
+                for i in range(end, start, -1):
+                    if i < len(plain) and plain[i - 1] in [
+                        "。",
+                        "！",
+                        "？",
+                        ".",
+                        "!",
+                        "?",
+                        "\n",
+                        ";",
+                        "；",
+                    ]:
+                        cut_position = i
+                        break
+
+                # 没找到合适的位置分割, 直接切分
+                if cut_position == end and end < len(plain):
+                    cut_position = end
+
+                result.append(plain[start:cut_position])
+                start = cut_position
+
+            return result
+
+    async def send(self, message: MessageChain):
+        message_obj = self.message_obj
+        active_send_mode = message_obj.raw_message.get("active_send_mode", False)
+        for comp in message.chain:
+            if isinstance(comp, Plain):
+                # Split long text messages if needed
+                plain_chunks = await self.split_plain(comp.text)
+                for chunk in plain_chunks:
+                    if active_send_mode:
+                        self.client.message.send_text(message_obj.sender.user_id, chunk)
+                    else:
+                        reply = TextReply(
+                            content=chunk,
+                            message=self.message_obj.raw_message["message"],
+                        )
+                        xml = reply.render()
+                        future = self.message_obj.raw_message["future"]
+                        assert isinstance(future, asyncio.Future)
+                        future.set_result(xml)
+                    await asyncio.sleep(0.5)  # Avoid sending too fast
+            elif isinstance(comp, Image):
+                img_path = await comp.convert_to_file_path()
+
+                with open(img_path, "rb") as f:
+                    try:
+                        response = self.client.media.upload("image", f)
+                    except Exception as e:
+                        logger.error(f"微信公众平台上传图片失败: {e}")
+                        await self.send(
+                            MessageChain().message(f"微信公众平台上传图片失败: {e}")
+                        )
+                        return
+                    logger.debug(f"微信公众平台上传图片返回: {response}")
+
+                    if active_send_mode:
+                        self.client.message.send_image(
+                            message_obj.sender.user_id,
+                            response["media_id"],
+                        )
+                    else:
+                        reply = ImageReply(
+                            media_id=response["media_id"],
+                            message=self.message_obj.raw_message["message"],
+                        )
+                        xml = reply.render()
+                        future = self.message_obj.raw_message["future"]
+                        assert isinstance(future, asyncio.Future)
+                        future.set_result(xml)
+
+            elif isinstance(comp, Record):
+                record_path = await comp.convert_to_file_path()
+                # 转成amr
+                record_path_amr = f"data/temp/{uuid.uuid4()}.amr"
+                pydub.AudioSegment.from_wav(record_path).export(
+                    record_path_amr, format="amr"
+                )
+
+                with open(record_path_amr, "rb") as f:
+                    try:
+                        response = self.client.media.upload("voice", f)
+                    except Exception as e:
+                        logger.error(f"微信公众平台上传语音失败: {e}")
+                        await self.send(
+                            MessageChain().message(f"微信公众平台上传语音失败: {e}")
+                        )
+                        return
+                    logger.info(f"微信公众平台上传语音返回: {response}")
+
+
+                    if active_send_mode:
+                        self.client.message.send_voice(
+                            message_obj.sender.user_id,
+                            response["media_id"],
+                        )
+                    else:
+                        reply = VoiceReply(
+                            media_id=response["media_id"],
+                            message=self.message_obj.raw_message["message"],
+                        )
+                        xml = reply.render()
+                        future = self.message_obj.raw_message["future"]
+                        assert isinstance(future, asyncio.Future)
+                        future.set_result(xml)
+
+            else:
+                logger.warning(f"还没实现这个消息类型的发送逻辑: {comp.type}。")
+
+        await super().send(message)
+
+    async def send_streaming(self, generator, use_fallback: bool = False):
+        buffer = None
+        async for chain in generator:
+            if not buffer:
+                buffer = chain
+            else:
+                buffer.chain.extend(chain.chain)
+        if not buffer:
+            return
+        buffer.squash_plain()
+        await self.send(buffer)
+        return await super().send_streaming(generator, use_fallback)

astrbot/core/provider/__init__.py

@@ -1,5 +1,5 @@
 from .provider import Provider, Personality, STTProvider
 
-from .entites import ProviderMetaData
+from .entities import ProviderMetaData
 
 __all__ = ["Provider", "Personality", "ProviderMetaData", "STTProvider"]

astrbot/core/provider/entites.py

@@ -1,269 +1,19 @@
-import enum
-import base64
-import json
-from astrbot.core.utils.io import download_image_by_url
-from astrbot import logger
-from dataclasses import dataclass, field
-from typing import List, Dict, Type
-from .func_tool_manager import FuncCall
-from openai.types.chat.chat_completion import ChatCompletion
-from openai.types.chat.chat_completion_message_tool_call import (
-    ChatCompletionMessageToolCall,
+from astrbot.core.provider.entities import (
+    ProviderRequest,
+    ProviderType,
+    ProviderMetaData,
+    ToolCallsResult,
+    AssistantMessageSegment,
+    ToolCallMessageSegment,
+    LLMResponse,
 )
-from astrbot.core.db.po import Conversation
-from astrbot.core.message.message_event_result import MessageChain
-import astrbot.core.message.components as Comp
 
-
-class ProviderType(enum.Enum):
-    CHAT_COMPLETION = "chat_completion"
-    SPEECH_TO_TEXT = "speech_to_text"
-    TEXT_TO_SPEECH = "text_to_speech"
-
-
-@dataclass
-class ProviderMetaData:
-    type: str
-    """提供商适配器名称，如 openai, ollama"""
-    desc: str = ""
-    """提供商适配器描述."""
-    provider_type: ProviderType = ProviderType.CHAT_COMPLETION
-    cls_type: Type = None
-
-    default_config_tmpl: dict = None
-    """平台的默认配置模板"""
-    provider_display_name: str = None
-    """显示在 WebUI 配置页中的提供商名称，如空则是 type"""
-
-
-@dataclass
-class ToolCallMessageSegment:
-    """OpenAI 格式的上下文中 role 为 tool 的消息段。参考: https://platform.openai.com/docs/guides/function-calling"""
-
-    tool_call_id: str
-    content: str
-    role: str = "tool"
-
-    def to_dict(self):
-        return {
-            "tool_call_id": self.tool_call_id,
-            "content": self.content,
-            "role": self.role,
-        }
-
-
-@dataclass
-class AssistantMessageSegment:
-    """OpenAI 格式的上下文中 role 为 assistant 的消息段。参考: https://platform.openai.com/docs/guides/function-calling"""
-
-    content: str = None
-    tool_calls: List[ChatCompletionMessageToolCall | Dict] = None
-    role: str = "assistant"
-
-    def to_dict(self):
-        ret = {
-            "role": self.role,
-        }
-        if self.content:
-            ret["content"] = self.content
-        elif self.tool_calls:
-            ret["tool_calls"] = self.tool_calls
-        return ret
-
-
-@dataclass
-class ToolCallsResult:
-    """工具调用结果"""
-
-    tool_calls_info: AssistantMessageSegment
-    """函数调用的信息"""
-    tool_calls_result: List[ToolCallMessageSegment]
-    """函数调用的结果"""
-
-    def to_openai_messages(self) -> List[Dict]:
-        ret = [
-            self.tool_calls_info.to_dict(),
-            *[item.to_dict() for item in self.tool_calls_result],
-        ]
-        return ret
-
-
-@dataclass
-class ProviderRequest:
-    prompt: str
-    """提示词"""
-    session_id: str = ""
-    """会话 ID"""
-    image_urls: List[str] = None
-    """图片 URL 列表"""
-    func_tool: FuncCall = None
-    """可用的函数工具"""
-    contexts: List = None
-    """上下文。格式与 openai 的上下文格式一致：
-    参考 https://platform.openai.com/docs/api-reference/chat/create#chat-create-messages
-    """
-    system_prompt: str = ""
-    """系统提示词"""
-    conversation: Conversation = None
-
-    tool_calls_result: ToolCallsResult = None
-    """附加的上次请求后工具调用的结果。参考: https://platform.openai.com/docs/guides/function-calling#handling-function-calls"""
-
-    def __repr__(self):
-        return f"ProviderRequest(prompt={self.prompt}, session_id={self.session_id}, image_urls={self.image_urls}, func_tool={self.func_tool}, contexts={self._print_friendly_context()}, system_prompt={self.system_prompt.strip()}, tool_calls_result={self.tool_calls_result})"
-
-    def __str__(self):
-        return self.__repr__()
-
-    def _print_friendly_context(self):
-        """打印友好的消息上下文。将 image_url 的值替换为 <Image>"""
-        if not self.contexts:
-            return f"prompt: {self.prompt}, image_count: {len(self.image_urls or [])}"
-
-        result_parts = []
-
-        for ctx in self.contexts:
-            role = ctx.get("role", "unknown")
-            content = ctx.get("content", "")
-
-            if isinstance(content, str):
-                result_parts.append(f"{role}: {content}")
-            elif isinstance(content, list):
-                msg_parts = []
-                image_count = 0
-
-                for item in content:
-                    item_type = item.get("type", "")
-
-                    if item_type == "text":
-                        msg_parts.append(item.get("text", ""))
-                    elif item_type == "image_url":
-                        image_count += 1
-
-                if image_count > 0:
-                    if msg_parts:
-                        msg_parts.append(f"[+{image_count} images]")
-                    else:
-                        msg_parts.append(f"[{image_count} images]")
-
-                result_parts.append(f"{role}: {''.join(msg_parts)}")
-
-        return result_parts
-
-    async def assemble_context(self) -> Dict:
-        """将请求(prompt 和 image_urls)包装成 OpenAI 的消息格式。"""
-        if self.image_urls:
-            user_content = {
-                "role": "user",
-                "content": [{"type": "text", "text": self.prompt}],
-            }
-            for image_url in self.image_urls:
-                if image_url.startswith("http"):
-                    image_path = await download_image_by_url(image_url)
-                    image_data = await self._encode_image_bs64(image_path)
-                elif image_url.startswith("file:///"):
-                    image_path = image_url.replace("file:///", "")
-                    image_data = await self._encode_image_bs64(image_path)
-                else:
-                    image_data = await self._encode_image_bs64(image_url)
-                if not image_data:
-                    logger.warning(f"图片 {image_url} 得到的结果为空，将忽略。")
-                    continue
-                user_content["content"].append(
-                    {"type": "image_url", "image_url": {"url": image_data}}
-                )
-            return user_content
-        else:
-            return {"role": "user", "content": self.prompt}
-
-    async def _encode_image_bs64(self, image_url: str) -> str:
-        """将图片转换为 base64"""
-        if image_url.startswith("base64://"):
-            return image_url.replace("base64://", "data:image/jpeg;base64,")
-        with open(image_url, "rb") as f:
-            image_bs64 = base64.b64encode(f.read()).decode("utf-8")
-            return "data:image/jpeg;base64," + image_bs64
-        return ""
-
-
-@dataclass
-class LLMResponse:
-    role: str
-    """角色, assistant, tool, err"""
-    result_chain: MessageChain = None
-    """返回的消息链"""
-    tools_call_args: List[Dict[str, any]] = field(default_factory=list)
-    """工具调用参数"""
-    tools_call_name: List[str] = field(default_factory=list)
-    """工具调用名称"""
-    tools_call_ids: List[str] = field(default_factory=list)
-    """工具调用 ID"""
-
-    raw_completion: ChatCompletion = None
-    _new_record: Dict[str, any] = None
-
-    _completion_text: str = ""
-
-    def __init__(
-        self,
-        role: str,
-        completion_text: str = "",
-        result_chain: MessageChain = None,
-        tools_call_args: List[Dict[str, any]] = [],
-        tools_call_name: List[str] = [],
-        tools_call_ids: List[str] = [],
-        raw_completion: ChatCompletion = None,
-        _new_record: Dict[str, any] = None,
-    ):
-        """初始化 LLMResponse
-
-        Args:
-            role (str): 角色, assistant, tool, err
-            completion_text (str, optional): 返回的结果文本，已经过时，推荐使用 result_chain. Defaults to "".
-            result_chain (MessageChain, optional): 返回的消息链. Defaults to None.
-            tools_call_args (List[Dict[str, any]], optional): 工具调用参数. Defaults to None.
-            tools_call_name (List[str], optional): 工具调用名称. Defaults to None.
-            raw_completion (ChatCompletion, optional): 原始响应, OpenAI 格式. Defaults to None.
-        """
-        self.role = role
-        self.completion_text = completion_text
-        self.result_chain = result_chain
-        self.tools_call_args = tools_call_args
-        self.tools_call_name = tools_call_name
-        self.tools_call_ids = tools_call_ids
-        self.raw_completion = raw_completion
-        self._new_record = _new_record
-
-    @property
-    def completion_text(self):
-        if self.result_chain:
-            return self.result_chain.get_plain_text()
-        return self._completion_text
-
-    @completion_text.setter
-    def completion_text(self, value):
-        if self.result_chain:
-            self.result_chain.chain = [
-                comp
-                for comp in self.result_chain.chain
-                if not isinstance(comp, Comp.Plain)
-            ]  # 清空 Plain 组件
-            self.result_chain.chain.insert(0, Comp.Plain(value))
-        else:
-            self._completion_text = value
-
-    def to_openai_tool_calls(self) -> List[Dict]:
-        """将工具调用信息转换为 OpenAI 格式"""
-        ret = []
-        for idx, tool_call_arg in enumerate(self.tools_call_args):
-            ret.append(
-                {
-                    "id": self.tools_call_ids[idx],
-                    "function": {
-                        "name": self.tools_call_name[idx],
-                        "arguments": json.dumps(tool_call_arg),
-                    },
-                    "type": "function",
-                }
-            )
-        return ret
+__all__ = [
+    "ProviderRequest",
+    "ProviderType",
+    "ProviderMetaData",
+    "ToolCallsResult",
+    "AssistantMessageSegment",
+    "ToolCallMessageSegment",
+    "LLMResponse",
+]

astrbot/core/provider/entities.py

@@ -0,0 +1,281 @@
+import enum
+import base64
+import json
+from astrbot.core.utils.io import download_image_by_url
+from astrbot import logger
+from dataclasses import dataclass, field
+from typing import List, Dict, Type
+from .func_tool_manager import FuncCall
+from openai.types.chat.chat_completion import ChatCompletion
+from openai.types.chat.chat_completion_message_tool_call import (
+    ChatCompletionMessageToolCall,
+)
+from astrbot.core.db.po import Conversation
+from astrbot.core.message.message_event_result import MessageChain
+import astrbot.core.message.components as Comp
+
+
+class ProviderType(enum.Enum):
+    CHAT_COMPLETION = "chat_completion"
+    SPEECH_TO_TEXT = "speech_to_text"
+    TEXT_TO_SPEECH = "text_to_speech"
+
+
+@dataclass
+class ProviderMetaData:
+    type: str
+    """提供商适配器名称，如 openai, ollama"""
+    desc: str = ""
+    """提供商适配器描述."""
+    provider_type: ProviderType = ProviderType.CHAT_COMPLETION
+    cls_type: Type = None
+
+    default_config_tmpl: dict = None
+    """平台的默认配置模板"""
+    provider_display_name: str = None
+    """显示在 WebUI 配置页中的提供商名称，如空则是 type"""
+
+
+@dataclass
+class ToolCallMessageSegment:
+    """OpenAI 格式的上下文中 role 为 tool 的消息段。参考: https://platform.openai.com/docs/guides/function-calling"""
+
+    tool_call_id: str
+    content: str
+    role: str = "tool"
+
+    def to_dict(self):
+        return {
+            "tool_call_id": self.tool_call_id,
+            "content": self.content,
+            "role": self.role,
+        }
+
+
+@dataclass
+class AssistantMessageSegment:
+    """OpenAI 格式的上下文中 role 为 assistant 的消息段。参考: https://platform.openai.com/docs/guides/function-calling"""
+
+    content: str = None
+    tool_calls: List[ChatCompletionMessageToolCall | Dict] = None
+    role: str = "assistant"
+
+    def to_dict(self):
+        ret = {
+            "role": self.role,
+        }
+        if self.content:
+            ret["content"] = self.content
+        elif self.tool_calls:
+            ret["tool_calls"] = self.tool_calls
+        return ret
+
+
+@dataclass
+class ToolCallsResult:
+    """工具调用结果"""
+
+    tool_calls_info: AssistantMessageSegment
+    """函数调用的信息"""
+    tool_calls_result: List[ToolCallMessageSegment]
+    """函数调用的结果"""
+
+    def to_openai_messages(self) -> List[Dict]:
+        ret = [
+            self.tool_calls_info.to_dict(),
+            *[item.to_dict() for item in self.tool_calls_result],
+        ]
+        return ret
+
+
+@dataclass
+class ProviderRequest:
+    prompt: str
+    """提示词"""
+    session_id: str = ""
+    """会话 ID"""
+    image_urls: List[str] = None
+    """图片 URL 列表"""
+    func_tool: FuncCall = None
+    """可用的函数工具"""
+    contexts: List = None
+    """上下文。格式与 openai 的上下文格式一致：
+    参考 https://platform.openai.com/docs/api-reference/chat/create#chat-create-messages
+    """
+    system_prompt: str = ""
+    """系统提示词"""
+    conversation: Conversation = None
+
+    tool_calls_result: ToolCallsResult = None
+    """附加的上次请求后工具调用的结果。参考: https://platform.openai.com/docs/guides/function-calling#handling-function-calls"""
+
+    def __repr__(self):
+        return f"ProviderRequest(prompt={self.prompt}, session_id={self.session_id}, image_urls={self.image_urls}, func_tool={self.func_tool}, contexts={self._print_friendly_context()}, system_prompt={self.system_prompt.strip()}, tool_calls_result={self.tool_calls_result})"
+
+    def __str__(self):
+        return self.__repr__()
+
+    def _print_friendly_context(self):
+        """打印友好的消息上下文。将 image_url 的值替换为 <Image>"""
+        if not self.contexts:
+            return f"prompt: {self.prompt}, image_count: {len(self.image_urls or [])}"
+
+        result_parts = []
+
+        for ctx in self.contexts:
+            role = ctx.get("role", "unknown")
+            content = ctx.get("content", "")
+
+            if isinstance(content, str):
+                result_parts.append(f"{role}: {content}")
+            elif isinstance(content, list):
+                msg_parts = []
+                image_count = 0
+
+                for item in content:
+                    item_type = item.get("type", "")
+
+                    if item_type == "text":
+                        msg_parts.append(item.get("text", ""))
+                    elif item_type == "image_url":
+                        image_count += 1
+
+                if image_count > 0:
+                    if msg_parts:
+                        msg_parts.append(f"[+{image_count} images]")
+                    else:
+                        msg_parts.append(f"[{image_count} images]")
+
+                result_parts.append(f"{role}: {''.join(msg_parts)}")
+
+        return result_parts
+
+    async def assemble_context(self) -> Dict:
+        """将请求(prompt 和 image_urls)包装成 OpenAI 的消息格式。"""
+        if self.image_urls:
+            user_content = {
+                "role": "user",
+                "content": [{"type": "text", "text": self.prompt if self.prompt else "[图片]"}],
+            }
+            for image_url in self.image_urls:
+                if image_url.startswith("http"):
+                    image_path = await download_image_by_url(image_url)
+                    image_data = await self._encode_image_bs64(image_path)
+                elif image_url.startswith("file:///"):
+                    image_path = image_url.replace("file:///", "")
+                    image_data = await self._encode_image_bs64(image_path)
+                else:
+                    image_data = await self._encode_image_bs64(image_url)
+                if not image_data:
+                    logger.warning(f"图片 {image_url} 得到的结果为空，将忽略。")
+                    continue
+                user_content["content"].append(
+                    {"type": "image_url", "image_url": {"url": image_data}}
+                )
+            return user_content
+        else:
+            return {"role": "user", "content": self.prompt}
+
+    async def _encode_image_bs64(self, image_url: str) -> str:
+        """将图片转换为 base64"""
+        if image_url.startswith("base64://"):
+            return image_url.replace("base64://", "data:image/jpeg;base64,")
+        with open(image_url, "rb") as f:
+            image_bs64 = base64.b64encode(f.read()).decode("utf-8")
+            return "data:image/jpeg;base64," + image_bs64
+        return ""
+
+
+@dataclass
+class LLMResponse:
+    role: str
+    """角色, assistant, tool, err"""
+    result_chain: MessageChain = None
+    """返回的消息链"""
+    tools_call_args: List[Dict[str, any]] = field(default_factory=list)
+    """工具调用参数"""
+    tools_call_name: List[str] = field(default_factory=list)
+    """工具调用名称"""
+    tools_call_ids: List[str] = field(default_factory=list)
+    """工具调用 ID"""
+
+    raw_completion: ChatCompletion = None
+    _new_record: Dict[str, any] = None
+
+    _completion_text: str = ""
+
+    is_chunk: bool = False
+    """是否是流式输出的单个 Chunk"""
+
+    def __init__(
+        self,
+        role: str,
+        completion_text: str = "",
+        result_chain: MessageChain = None,
+        tools_call_args: List[Dict[str, any]] = None,
+        tools_call_name: List[str] = None,
+        tools_call_ids: List[str] = None,
+        raw_completion: ChatCompletion = None,
+        _new_record: Dict[str, any] = None,
+        is_chunk: bool = False,
+    ):
+        """初始化 LLMResponse
+
+        Args:
+            role (str): 角色, assistant, tool, err
+            completion_text (str, optional): 返回的结果文本，已经过时，推荐使用 result_chain. Defaults to "".
+            result_chain (MessageChain, optional): 返回的消息链. Defaults to None.
+            tools_call_args (List[Dict[str, any]], optional): 工具调用参数. Defaults to None.
+            tools_call_name (List[str], optional): 工具调用名称. Defaults to None.
+            raw_completion (ChatCompletion, optional): 原始响应, OpenAI 格式. Defaults to None.
+        """
+        if tools_call_args is None:
+            tools_call_args = []
+        if tools_call_name is None:
+            tools_call_name = []
+        if tools_call_ids is None:
+            tools_call_ids = []
+
+        self.role = role
+        self.completion_text = completion_text
+        self.result_chain = result_chain
+        self.tools_call_args = tools_call_args
+        self.tools_call_name = tools_call_name
+        self.tools_call_ids = tools_call_ids
+        self.raw_completion = raw_completion
+        self._new_record = _new_record
+        self.is_chunk = is_chunk
+
+    @property
+    def completion_text(self):
+        if self.result_chain:
+            return self.result_chain.get_plain_text()
+        return self._completion_text
+
+    @completion_text.setter
+    def completion_text(self, value):
+        if self.result_chain:
+            self.result_chain.chain = [
+                comp
+                for comp in self.result_chain.chain
+                if not isinstance(comp, Comp.Plain)
+            ]  # 清空 Plain 组件
+            self.result_chain.chain.insert(0, Comp.Plain(value))
+        else:
+            self._completion_text = value
+
+    def to_openai_tool_calls(self) -> List[Dict]:
+        """将工具调用信息转换为 OpenAI 格式"""
+        ret = []
+        for idx, tool_call_arg in enumerate(self.tools_call_args):
+            ret.append(
+                {
+                    "id": self.tools_call_ids[idx],
+                    "function": {
+                        "name": self.tools_call_name[idx],
+                        "arguments": json.dumps(tool_call_arg),
+                    },
+                    "type": "function",
+                }
+            )
+        return ret

astrbot/core/provider/func_tool_manager.py

@@ -3,19 +3,31 @@ import json
 import textwrap
 import os
 import asyncio
-import copy
+import logging
+from datetime import timedelta
 
 from typing import Dict, List, Awaitable, Literal, Any
 from dataclasses import dataclass
 from typing import Optional
 from contextlib import AsyncExitStack
 from astrbot import logger
+from astrbot.core.utils.log_pipe import LogPipe
+
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 try:
     import mcp
+    from mcp.client.sse import sse_client
 except (ModuleNotFoundError, ImportError):
     logger.warning("警告: 缺少依赖库 'mcp'，将无法使用 MCP 服务。")
 
+try:
+    from mcp.client.streamable_http import streamablehttp_client
+except (ModuleNotFoundError, ImportError):
+    logger.warning(
+        "警告: 缺少依赖库 'mcp' 或者 mcp 库版本过低，无法使用 Streamable HTTP 连接方式。"
+    )
+
 DEFAULT_MCP_CONFIG = {"mcpServers": {}}
 
 SUPPORTED_TYPES = [
@@ -87,26 +99,87 @@ class MCPClient:
         self.name = None
         self.active: bool = True
         self.tools: List[mcp.Tool] = []
+        self.server_errlogs: List[str] = []
 
-    async def connect_to_server(self, mcp_server_config: dict):
-        """Connect to an MCP server
+    async def connect_to_server(self, mcp_server_config: dict, name: str):
+        """连接到 MCP 服务器
+
+        如果 `url` 参数存在：
+            1. 当 transport 指定为 `streamable_http` 时，使用 Streamable HTTP 连接方式。
+            1. 当 transport 指定为 `sse` 时，使用 SSE 连接方式。
+            2. 如果没有指定，默认使用 SSE 的方式连接到 MCP 服务。
 
         Args:
             mcp_server_config (dict): Configuration for the MCP server. See https://modelcontextprotocol.io/quickstart/server
         """
         cfg = mcp_server_config.copy()
-        cfg.pop("active", None)
-        server_params = mcp.StdioServerParameters(
-            **cfg,
-        )
+        if "mcpServers" in cfg and len(cfg["mcpServers"]) > 0:
+            key_0 = list(cfg["mcpServers"].keys())[0]
+            cfg = cfg["mcpServers"][key_0]
+        cfg.pop("active", None)  # Remove active flag from config
 
-        stdio_transport = await self.exit_stack.enter_async_context(
-            mcp.stdio_client(server_params)
-        )
-        self.stdio, self.write = stdio_transport
-        self.session = await self.exit_stack.enter_async_context(
-            mcp.ClientSession(self.stdio, self.write)
-        )
+        if "url" in cfg:
+            is_sse = True
+            if cfg.get("transport") == "streamable_http":
+                is_sse = False
+            if is_sse:
+                # SSE transport method
+                self._streams_context = sse_client(
+                    url=cfg["url"],
+                    headers=cfg.get("headers", {}),
+                    timeout=cfg.get("timeout", 5),
+                    sse_read_timeout=cfg.get("sse_read_timeout", 60 * 5),
+                )
+                streams = await self._streams_context.__aenter__()
+
+                # Create a new client session
+                self.session = await self.exit_stack.enter_async_context(
+                    mcp.ClientSession(*streams)
+                )
+            else:
+                timeout = timedelta(seconds=cfg.get("timeout", 30))
+                sse_read_timeout = timedelta(
+                    seconds=cfg.get("sse_read_timeout", 60 * 5)
+                )
+                self._streams_context = streamablehttp_client(
+                    url=cfg["url"],
+                    headers=cfg.get("headers", {}),
+                    timeout=timeout,
+                    sse_read_timeout=sse_read_timeout,
+                    terminate_on_close=cfg.get("terminate_on_close", True),
+                )
+                read_s, write_s, _ = await self._streams_context.__aenter__()
+
+                # Create a new client session
+                self.session = await self.exit_stack.enter_async_context(
+                    mcp.ClientSession(read_stream=read_s, write_stream=write_s)
+                )
+
+        else:
+            server_params = mcp.StdioServerParameters(
+                **cfg,
+            )
+
+            def callback(msg: str):
+                # 处理 MCP 服务的错误日志
+                self.server_errlogs.append(msg)
+
+            stdio_transport = await self.exit_stack.enter_async_context(
+                mcp.stdio_client(
+                    server_params,
+                    errlog=LogPipe(
+                        level=logging.ERROR,
+                        logger=logger,
+                        identifier=f"MCPServer-{name}",
+                        callback=callback,
+                    ),
+                ),
+            )
+
+            # Create a new client session
+            self.session = await self.exit_stack.enter_async_context(
+                mcp.ClientSession(*stdio_transport)
+            )
 
         await self.session.initialize()
 
@@ -204,8 +277,7 @@ class FuncCall:
         }
         ```
         """
-        current_dir = os.path.dirname(os.path.abspath(__file__))
-        data_dir = os.path.abspath(os.path.join(current_dir, "../../../data"))
+        data_dir = get_astrbot_data_path()
 
         mcp_json_file = os.path.join(data_dir, "mcp_server.json")
         if not os.path.exists(mcp_json_file):
@@ -260,6 +332,13 @@ class FuncCall:
                     if data["name"] in self.mcp_client_event:
                         self.mcp_client_event[data["name"]].set()
                         self.mcp_client_event.pop(data["name"], None)
+                        self.func_list = [
+                            f
+                            for f in self.func_list
+                            if not (
+                                f.origin == "mcp" and f.mcp_server_name == data["name"]
+                            )
+                        ]
                 else:
                     for name in self.mcp_client_dict.keys():
                         # await self._terminate_mcp_client(name)
@@ -267,6 +346,7 @@ class FuncCall:
                         if name in self.mcp_client_event:
                             self.mcp_client_event[name].set()
                             self.mcp_client_event.pop(name, None)
+                    self.func_list = [f for f in self.func_list if f.origin != "mcp"]
 
     async def _init_mcp_client_task_wrapper(
         self, name: str, cfg: dict, event: asyncio.Event
@@ -278,6 +358,9 @@ class FuncCall:
             logger.info(f"收到 MCP 客户端 {name} 终止信号")
             await self._terminate_mcp_client(name)
         except Exception as e:
+            import traceback
+
+            traceback.print_exc()
             logger.error(f"初始化 MCP 客户端 {name} 失败: {e}")
 
     async def _init_mcp_client(self, name: str, config: dict) -> None:
@@ -289,10 +372,10 @@ class FuncCall:
 
             mcp_client = MCPClient()
             mcp_client.name = name
-            await mcp_client.connect_to_server(config)
+            self.mcp_client_dict[name] = mcp_client
+            await mcp_client.connect_to_server(config, name)
             tools_res = await mcp_client.list_tools_and_save()
             tool_names = [tool.name for tool in tools_res.tools]
-            self.mcp_client_dict[name] = mcp_client
 
             # 移除该MCP服务之前的工具（如有）
             self.func_list = [
@@ -314,13 +397,16 @@ class FuncCall:
                 self.func_list.append(func_tool)
 
             logger.info(f"已连接 MCP 服务 {name}, Tools: {tool_names}")
-            return True
+            return
         except Exception as e:
+            import traceback
+
+            logger.error(traceback.format_exc())
             logger.error(f"初始化 MCP 客户端 {name} 失败: {e}")
             # 发生错误时确保客户端被清理
             if name in self.mcp_client_dict:
                 await self._terminate_mcp_client(name)
-            return False
+            return
 
     async def _terminate_mcp_client(self, name: str) -> None:
         """关闭并清理MCP客户端"""
@@ -339,7 +425,7 @@ class FuncCall:
             ]
             logger.info(f"已关闭 MCP 服务 {name}")
 
-    def get_func_desc_openai_style(self) -> list:
+    def get_func_desc_openai_style(self, omit_empty_parameter_field=False) -> list:
         """
         获得 OpenAI API 风格的**已经激活**的工具描述
         """
@@ -348,16 +434,19 @@ class FuncCall:
         for f in self.func_list:
             if not f.active:
                 continue
-            _l.append(
-                {
-                    "type": "function",
-                    "function": {
-                        "name": f.name,
-                        "parameters": f.parameters,
-                        "description": f.description,
-                    },
-                }
-            )
+            func_ = {
+                "type": "function",
+                "function": {
+                    "name": f.name,
+                    # "parameters": f.parameters,
+                    "description": f.description,
+                },
+            }
+            func_["function"]["parameters"] = f.parameters
+            if not f.parameters.get("properties") and omit_empty_parameter_field:
+                # 如果 properties 为空，并且 omit_empty_parameter_field 为 True，则删除 parameters 字段
+                del func_["function"]["parameters"]
+            _l.append(func_)
         return _l
 
     def get_func_desc_anthropic_style(self) -> list:
@@ -383,28 +472,86 @@ class FuncCall:
             tools.append(tool)
         return tools
 
-    def get_func_desc_google_genai_style(self) -> Dict:
+    def get_func_desc_google_genai_style(self) -> dict:
+        """
+        获得 Google GenAI API 风格的**已经激活**的工具描述
+        """
+
+        # Gemini API 支持的数据类型和格式
+        supported_types = {
+            "string",
+            "number",
+            "integer",
+            "boolean",
+            "array",
+            "object",
+            "null",
+        }
+        supported_formats = {
+            "string": {"enum", "date-time"},
+            "integer": {"int32", "int64"},
+            "number": {"float", "double"},
+        }
+
+        def convert_schema(schema: dict) -> dict:
+            """转换 schema 为 Gemini API 格式"""
+
+            # 如果 schema 包含 anyOf，则只返回 anyOf 字段
+            if "anyOf" in schema:
+                return {"anyOf": [convert_schema(s) for s in schema["anyOf"]]}
+
+            result = {}
+
+            if "type" in schema and schema["type"] in supported_types:
+                result["type"] = schema["type"]
+                if "format" in schema and schema["format"] in supported_formats.get(
+                    result["type"], set()
+                ):
+                    result["format"] = schema["format"]
+            else:
+                # 暂时指定默认为null
+                result["type"] = "null"
+
+            support_fields = {
+                "title",
+                "description",
+                "enum",
+                "minimum",
+                "maximum",
+                "maxItems",
+                "minItems",
+                "nullable",
+                "required",
+            }
+            result.update({k: schema[k] for k in support_fields if k in schema})
+
+            if "properties" in schema:
+                properties = {}
+                for key, value in schema["properties"].items():
+                    prop_value = convert_schema(value)
+                    if "default" in prop_value:
+                        del prop_value["default"]
+                    properties[key] = prop_value
+
+                if properties:  # 只在有非空属性时添加
+                    result["properties"] = properties
+
+            if "items" in schema:
+                result["items"] = convert_schema(schema["items"])
+
+            return result
+
+        tools = [
+            {
+                "name": f.name,
+                "description": f.description,
+                **({"parameters": convert_schema(f.parameters)}),
+            }
+            for f in self.func_list
+            if f.active
+        ]
+
         declarations = {}
-        tools = []
-        for f in self.func_list:
-            if not f.active:
-                continue
-
-            func_declaration = {"name": f.name, "description": f.description}
-
-            # 检查并添加非空的properties参数
-            params = f.parameters if isinstance(f.parameters, dict) else {}
-            params = copy.deepcopy(params)
-            if params.get("properties", {}):
-                properties = params["properties"]
-                for key, value in properties.items():
-                    if "default" in value:
-                        del value["default"]
-                params["properties"] = properties
-                func_declaration["parameters"] = params
-
-            tools.append(func_declaration)
-
         if tools:
             declarations["function_declarations"] = tools
         return declarations

astrbot/core/provider/manager.py

@@ -2,7 +2,7 @@ import traceback
 import asyncio
 from astrbot.core.config.astrbot_config import AstrBotConfig
 from .provider import Provider, STTProvider, TTSProvider, Personality
-from .entites import ProviderType
+from .entities import ProviderType
 from typing import List
 from astrbot.core.db import BaseDatabase
 from .register import provider_cls_map, llm_tools
@@ -21,9 +21,9 @@ class ProviderManager:
         self.selected_provider_id = sp.get("curr_provider")
         self.selected_stt_provider_id = self.provider_stt_settings.get("provider_id")
         self.selected_tts_provider_id = self.provider_settings.get("provider_id")
-        self.provider_enabled = self.provider_settings.get("enable", False)
-        self.stt_enabled = self.provider_stt_settings.get("enable", False)
-        self.tts_enabled = self.provider_tts_settings.get("enable", False)
+        # self.provider_enabled = self.provider_settings.get("enable", False)
+        # self.stt_enabled = self.provider_stt_settings.get("enable", False)
+        # self.tts_enabled = self.provider_tts_settings.get("enable", False)
 
         # 人格情景管理
         # 目前没有拆成独立的模块
@@ -101,6 +101,8 @@ class ProviderManager:
         self.inst_map = {}
         """Provider 实例映射. key: provider_id, value: Provider 实例"""
         self.llm_tools = llm_tools
+        self.default_provider_inst: Provider = None
+        """默认的 Provider 实例。第 0 个或者用户以前指定的 Provider 实例"""
         self.curr_provider_inst: Provider = None
         """当前使用的 Provider 实例"""
         self.curr_stt_provider_inst: STTProvider = None
@@ -119,14 +121,9 @@ class ProviderManager:
         for provider_config in self.providers_config:
             await self.load_provider(provider_config)
 
-        if not self.curr_provider_inst:
-            logger.warning("未启用任何用于 文本生成 的提供商适配器。")
-
-        if self.stt_enabled and not self.curr_stt_provider_inst:
-            logger.warning("未启用任何用于 语音转文本 的提供商适配器。")
-
-        if self.tts_enabled and not self.curr_tts_provider_inst:
-            logger.warning("未启用任何用于 文本转语音 的提供商适配器。")
+        self.default_provider_inst = self.inst_map.get(self.selected_provider_id)
+        if not self.default_provider_inst and self.provider_insts:
+            self.default_provider_inst = self.provider_insts[0]
 
         # 初始化 MCP Client 连接
         asyncio.create_task(
@@ -202,6 +199,18 @@ class ProviderManager:
                     from .sources.dashscope_tts import (
                         ProviderDashscopeTTSAPI as ProviderDashscopeTTSAPI,
                     )
+                case "azure_tts":
+                    from .sources.azure_tts_source import (
+                        AzureTTSProvider as AzureTTSProvider,
+                    )
+                case "minimax_tts_api":
+                    from .sources.minimax_tts_api_source import (
+                        ProviderMiniMaxTTSAPI as ProviderMiniMaxTTSAPI,
+                    )
+                case "volcengine_tts":
+                    from .sources.volcengine_tts import (
+                        ProviderVolcengineTTS as ProviderVolcengineTTS,
+                    )
         except (ImportError, ModuleNotFoundError) as e:
             logger.critical(
                 f"加载 {provider_config['type']}({provider_config['id']}) 提供商适配器失败：{e}。可能是因为有未安装的依赖。"
@@ -233,15 +242,12 @@ class ProviderManager:
                     await inst.initialize()
 
                 self.stt_provider_insts.append(inst)
-                if (
-                    self.selected_stt_provider_id == provider_config["id"]
-                    and self.stt_enabled
-                ):
+                if self.selected_stt_provider_id == provider_config["id"]:
                     self.curr_stt_provider_inst = inst
                     logger.info(
                         f"已选择 {provider_config['type']}({provider_config['id']}) 作为当前语音转文本提供商适配器。"
                     )
-                if not self.curr_stt_provider_inst and self.stt_enabled:
+                if not self.curr_stt_provider_inst:
                     self.curr_stt_provider_inst = inst
 
             elif provider_metadata.provider_type == ProviderType.TEXT_TO_SPEECH:
@@ -254,15 +260,12 @@ class ProviderManager:
                     await inst.initialize()
 
                 self.tts_provider_insts.append(inst)
-                if (
-                    self.selected_tts_provider_id == provider_config["id"]
-                    and self.tts_enabled
-                ):
+                if self.selected_tts_provider_id == provider_config["id"]:
                     self.curr_tts_provider_inst = inst
                     logger.info(
                         f"已选择 {provider_config['type']}({provider_config['id']}) 作为当前文本转语音提供商适配器。"
                     )
-                if not self.curr_tts_provider_inst and self.tts_enabled:
+                if not self.curr_tts_provider_inst:
                     self.curr_tts_provider_inst = inst
 
             elif provider_metadata.provider_type == ProviderType.CHAT_COMPLETION:
@@ -279,15 +282,12 @@ class ProviderManager:
                     await inst.initialize()
 
                 self.provider_insts.append(inst)
-                if (
-                    self.selected_provider_id == provider_config["id"]
-                    and self.provider_enabled
-                ):
+                if self.selected_provider_id == provider_config["id"]:
                     self.curr_provider_inst = inst
                     logger.info(
                         f"已选择 {provider_config['type']}({provider_config['id']}) 作为当前提供商适配器。"
                     )
-                if not self.curr_provider_inst and self.provider_enabled:
+                if not self.curr_provider_inst:
                     self.curr_provider_inst = inst
 
             self.inst_map[provider_config["id"]] = inst
@@ -310,11 +310,7 @@ class ProviderManager:
 
         if len(self.provider_insts) == 0:
             self.curr_provider_inst = None
-        elif (
-            self.curr_provider_inst is None
-            and len(self.provider_insts) > 0
-            and self.provider_enabled
-        ):
+        elif self.curr_provider_inst is None and len(self.provider_insts) > 0:
             self.curr_provider_inst = self.provider_insts[0]
             self.selected_provider_id = self.curr_provider_inst.meta().id
             logger.info(
@@ -323,11 +319,7 @@ class ProviderManager:
 
         if len(self.stt_provider_insts) == 0:
             self.curr_stt_provider_inst = None
-        elif (
-            self.curr_stt_provider_inst is None
-            and len(self.stt_provider_insts) > 0
-            and self.stt_enabled
-        ):
+        elif self.curr_stt_provider_inst is None and len(self.stt_provider_insts) > 0:
             self.curr_stt_provider_inst = self.stt_provider_insts[0]
             self.selected_stt_provider_id = self.curr_stt_provider_inst.meta().id
             logger.info(
@@ -336,11 +328,7 @@ class ProviderManager:
 
         if len(self.tts_provider_insts) == 0:
             self.curr_tts_provider_inst = None
-        elif (
-            self.curr_tts_provider_inst is None
-            and len(self.tts_provider_insts) > 0
-            and self.tts_enabled
-        ):
+        elif self.curr_tts_provider_inst is None and len(self.tts_provider_insts) > 0:
             self.curr_tts_provider_inst = self.tts_provider_insts[0]
             self.selected_tts_provider_id = self.curr_tts_provider_inst.meta().id
             logger.info(

astrbot/core/provider/provider.py

@@ -1,9 +1,9 @@
 import abc
 from typing import List
 from astrbot.core.db import BaseDatabase
-from typing import TypedDict
+from typing import TypedDict, AsyncGenerator
 from astrbot.core.provider.func_tool_manager import FuncCall
-from astrbot.core.provider.entites import LLMResponse, ToolCallsResult
+from astrbot.core.provider.entities import LLMResponse, ToolCallsResult
 from dataclasses import dataclass
 
 
@@ -108,7 +108,35 @@ class Provider(AbstractProvider):
             - 如果传入了 image_urls，将会在对话时附上图片。如果模型不支持图片输入，将会抛出错误。
             - 如果传入了 tools，将会使用 tools 进行 Function-calling。如果模型不支持 Function-calling，将会抛出错误。
         """
-        raise NotImplementedError()
+        ...
+
+    async def text_chat_stream(
+        self,
+        prompt: str,
+        session_id: str = None,
+        image_urls: List[str] = None,
+        func_tool: FuncCall = None,
+        contexts: List = None,
+        system_prompt: str = None,
+        tool_calls_result: ToolCallsResult = None,
+        **kwargs,
+    ) -> AsyncGenerator[LLMResponse, None]:
+        """获得 LLM 的流式文本对话结果。会使用当前的模型进行对话。在生成的最后会返回一次完整的结果。
+
+        Args:
+            prompt: 提示词
+            session_id: 会话 ID(此属性已经被废弃)
+            image_urls: 图片 URL 列表
+            tools: Function-calling 工具
+            contexts: 上下文
+            tool_calls_result: 回传给 LLM 的工具调用结果。参考: https://platform.openai.com/docs/guides/function-calling
+            kwargs: 其他参数
+
+        Notes:
+            - 如果传入了 image_urls，将会在对话时附上图片。如果模型不支持图片输入，将会抛出错误。
+            - 如果传入了 tools，将会使用 tools 进行 Function-calling。如果模型不支持 Function-calling，将会抛出错误。
+        """
+        ...
 
     async def pop_record(self, context: List):
         """
@@ -151,3 +179,20 @@ class TTSProvider(AbstractProvider):
     async def get_audio(self, text: str) -> str:
         """获取文本的音频，返回音频文件路径"""
         raise NotImplementedError()
+
+
+class EmbeddingProvider(AbstractProvider):
+    def __init__(self, provider_config: dict, provider_settings: dict) -> None:
+        super().__init__(provider_config)
+        self.provider_config = provider_config
+        self.provider_settings = provider_settings
+
+    @abc.abstractmethod
+    async def get_embedding(self, text: str) -> list[float]:
+        """获取文本的向量"""
+        ...
+
+    @abc.abstractmethod
+    def get_dim(self) -> int:
+        """获取向量的维度"""
+        ...

astrbot/core/provider/register.py

@@ -1,5 +1,5 @@
 from typing import List, Dict
-from .entites import ProviderMetaData, ProviderType
+from .entities import ProviderMetaData, ProviderType
 from astrbot.core import logger
 from .func_tool_manager import FuncCall
 

astrbot/core/provider/sources/anthropic_source.py

@@ -10,7 +10,8 @@ from astrbot.api.provider import Provider, Personality
 from astrbot import logger
 from astrbot.core.provider.func_tool_manager import FuncCall
 from ..register import register_provider_adapter
-from astrbot.core.provider.entites import LLMResponse, ToolCallsResult
+from astrbot.core.message.message_event_result import MessageChain
+from astrbot.core.provider.entities import LLMResponse, ToolCallsResult
 from .openai_source import ProviderOpenAIOfficial
 
 
@@ -72,7 +73,8 @@ class ProviderAnthropic(ProviderOpenAIOfficial):
         if content.type == "text":
             # text completion
             completion_text = str(content.text).strip()
-            llm_response.completion_text = completion_text
+            # llm_response.completion_text = completion_text
+            llm_response.result_chain = MessageChain().message(completion_text)
 
         # Anthropic每次只返回一个函数调用
         if completion.stop_reason == "tool_use":
@@ -145,7 +147,7 @@ class ProviderAnthropic(ProviderOpenAIOfficial):
                             messages=context_query, **model_config
                         )
                         llm_response = LLMResponse("assistant")
-                        llm_response.completion_text = response.content[0].text
+                        llm_response.result_chain = MessageChain().message(response.content[0].text)
                         llm_response.raw_completion = response
                         return llm_response
                     except Exception as e:
@@ -160,6 +162,33 @@ class ProviderAnthropic(ProviderOpenAIOfficial):
 
         return llm_response
 
+    async def text_chat_stream(
+        self,
+        prompt,
+        session_id=None,
+        image_urls=...,
+        func_tool=None,
+        contexts=...,
+        system_prompt=None,
+        tool_calls_result=None,
+        **kwargs,
+    ):
+        # raise NotImplementedError("This method is not implemented yet.")
+        # 调用 text_chat 模拟流式
+        llm_response = await self.text_chat(
+            prompt=prompt,
+            session_id=session_id,
+            image_urls=image_urls,
+            func_tool=func_tool,
+            contexts=contexts,
+            system_prompt=system_prompt,
+            tool_calls_result=tool_calls_result,
+        )
+        llm_response.is_chunk = True
+        yield llm_response
+        llm_response.is_chunk = False
+        yield llm_response
+
     async def assemble_context(self, text: str, image_urls: List[str] = None):
         """组装上下文，支持文本和图片"""
         if not image_urls:

astrbot/core/provider/sources/azure_tts_source.py

@@ -0,0 +1,210 @@
+import uuid
+import time
+import json
+import re
+import hashlib
+import random
+import asyncio
+from pathlib import Path
+from typing import Dict
+from xml.sax.saxutils import escape
+
+from httpx import AsyncClient, Timeout
+from astrbot.core.config.default import VERSION
+
+from ..entities import ProviderType
+from ..provider import TTSProvider
+from ..register import register_provider_adapter
+
+TEMP_DIR = Path("data/temp/azure_tts")
+TEMP_DIR.mkdir(parents=True, exist_ok=True)
+
+class OTTSProvider:
+    def __init__(self, config: Dict):
+        self.skey = config["OTTS_SKEY"]
+        self.api_url = config["OTTS_URL"]
+        self.auth_time_url = config["OTTS_AUTH_TIME"]
+        self.time_offset = 0
+        self.last_sync_time = 0
+        self.timeout = Timeout(10.0)
+        self.retry_count = 3
+        self.client = None
+
+    async def __aenter__(self):
+        self.client = AsyncClient(timeout=self.timeout)
+        return self
+
+    async def __aexit__(self, exc_type, exc_val, exc_tb):
+        if self.client:
+            await self.client.aclose()
+
+    async def _sync_time(self):
+        try:
+            response = await self.client.get(self.auth_time_url)
+            response.raise_for_status()
+            server_time = int(response.json()["timestamp"])
+            local_time = int(time.time())
+            self.time_offset = server_time - local_time
+            self.last_sync_time = local_time
+        except Exception as e:
+            if time.time() - self.last_sync_time > 3600:
+                raise RuntimeError("时间同步失败") from e
+
+    async def _generate_signature(self) -> str:
+        await self._sync_time()
+        timestamp = int(time.time()) + self.time_offset
+        nonce = "".join(random.choices("abcdefghijklmnopqrstuvwxyz0123456789", k=10))
+        path = re.sub(r"^https?://[^/]+", "", self.api_url) or "/"
+        return f"{timestamp}-{nonce}-0-{hashlib.md5(f'{path}-{timestamp}-{nonce}-0-{self.skey}'.encode()).hexdigest()}"
+
+    async def get_audio(self, text: str, voice_params: Dict) -> str:
+        file_path = TEMP_DIR / f"otts-{uuid.uuid4()}.wav"
+        signature = await self._generate_signature()
+        for attempt in range(self.retry_count):
+            try:
+                response = await self.client.post(
+                    f"{self.api_url}?sign={signature}",
+                    data={
+                        "text": text,
+                        "voice": voice_params["voice"],
+                        "style": voice_params["style"],
+                        "role": voice_params["role"],
+                        "rate": voice_params["rate"],
+                        "volume": voice_params["volume"]
+                    },
+                    headers={
+                        "User-Agent": f"AstrBot/{VERSION}",
+                        "UAK": "AstrBot/AzureTTS"
+                    }
+                )
+                response.raise_for_status()
+                file_path.parent.mkdir(parents=True, exist_ok=True)
+                with file_path.open("wb") as f:
+                    async for chunk in response.aiter_bytes(4096):
+                        f.write(chunk)
+                return str(file_path.resolve())
+            except Exception as e:
+                if attempt == self.retry_count - 1:
+                    raise RuntimeError(f"OTTS请求失败: {str(e)}") from e
+                await asyncio.sleep(0.5 * (attempt + 1))
+
+class AzureNativeProvider(TTSProvider):
+    def __init__(self, provider_config: dict, provider_settings: dict):
+        super().__init__(provider_config, provider_settings)
+        self.subscription_key = provider_config.get("azure_tts_subscription_key", "").strip()
+        if not re.fullmatch(r"^[a-zA-Z0-9]{32}$", self.subscription_key):
+            raise ValueError("无效的Azure订阅密钥")
+        self.region = provider_config.get("azure_tts_region", "eastus").strip()
+        self.endpoint = f"https://{self.region}.tts.speech.microsoft.com/cognitiveservices/v1"
+        self.client = None
+        self.token = None
+        self.token_expire = 0
+        self.voice_params = {
+            "voice": provider_config.get("azure_tts_voice", "zh-CN-YunxiaNeural"),
+            "style": provider_config.get("azure_tts_style", "cheerful"),
+            "role": provider_config.get("azure_tts_role", "Boy"),
+            "rate": provider_config.get("azure_tts_rate", "1"),
+            "volume": provider_config.get("azure_tts_volume", "100")
+        }
+
+    async def __aenter__(self):
+        self.client = AsyncClient(headers={
+            "User-Agent": f"AstrBot/{VERSION}",
+            "Content-Type": "application/ssml+xml",
+            "X-Microsoft-OutputFormat": "riff-48khz-16bit-mono-pcm"
+        })
+        return self
+
+    async def __aexit__(self, exc_type, exc_val, exc_tb):
+        if self.client:
+            await self.client.aclose()
+
+    async def _refresh_token(self):
+        token_url = f"https://{self.region}.api.cognitive.microsoft.com/sts/v1.0/issuetoken"
+        response = await self.client.post(
+            token_url,
+            headers={"Ocp-Apim-Subscription-Key": self.subscription_key}
+        )
+        response.raise_for_status()
+        self.token = response.text
+        self.token_expire = time.time() + 540
+
+    async def get_audio(self, text: str) -> str:
+        if not self.token or time.time() > self.token_expire:
+            await self._refresh_token()
+        file_path = TEMP_DIR / f"azure-{uuid.uuid4()}.wav"
+        ssml = f"""<speak version='1.0' xmlns='http://www.w3.org/2001/10/synthesis'
+            xmlns:mstts='http://www.w3.org/2001/mstts' xml:lang='zh-CN'>
+            <voice name='{escape(self.voice_params["voice"])}'>
+                <mstts:express-as style='{escape(self.voice_params["style"])}'
+                    role='{escape(self.voice_params["role"])}'>
+                    <prosody rate='{escape(self.voice_params["rate"])}'
+                        volume='{escape(self.voice_params["volume"])}'>
+                        {escape(text)}
+                    </prosody>
+                </mstts:express-as>
+            </voice>
+        </speak>"""
+        response = await self.client.post(
+            self.endpoint,
+            content=ssml,
+            headers={
+                "Authorization": f"Bearer {self.token}",
+                "User-Agent": f"AstrBot/{VERSION}"
+            }
+        )
+        response.raise_for_status()
+        file_path.parent.mkdir(parents=True, exist_ok=True)
+        with file_path.open("wb") as f:
+            for chunk in response.iter_bytes(4096):
+                f.write(chunk)
+        return str(file_path.resolve())
+
+@register_provider_adapter("azure_tts", "Azure TTS", ProviderType.TEXT_TO_SPEECH)
+class AzureTTSProvider(TTSProvider):
+    def __init__(self, provider_config: dict, provider_settings: dict):
+        super().__init__(provider_config, provider_settings)
+        key_value = provider_config.get("azure_tts_subscription_key", "")
+        self.provider = self._parse_provider(key_value, provider_config)
+
+    def _parse_provider(self, key_value: str, config: dict) -> TTSProvider:
+        if key_value.lower().startswith("other["):
+            try:
+                match = re.match(r"other\[(.*)\]", key_value, re.DOTALL)
+                if not match:
+                    raise ValueError("无效的other[...]格式，应形如 other[{...}]")
+                json_str = match.group(1).strip()
+                otts_config = json.loads(json_str)
+                required = {"OTTS_SKEY", "OTTS_URL", "OTTS_AUTH_TIME"}
+                if missing := required - otts_config.keys():
+                    raise ValueError(f"缺少OTTS参数: {', '.join(missing)}")
+                return OTTSProvider(otts_config)
+            except json.JSONDecodeError as e:
+                error_msg = (
+                    f"JSON解析失败，请检查格式（错误位置：行 {e.lineno} 列 {e.colno}）\n"
+                    f"错误详情: {e.msg}\n"
+                    f"错误上下文: {json_str[max(0, e.pos-30):e.pos+30]}"
+                )
+                raise ValueError(error_msg) from e
+            except KeyError as e:
+                raise ValueError(f"配置错误: 缺少必要参数 {e}") from e
+        if re.fullmatch(r"^[a-zA-Z0-9]{32}$", key_value):
+            return AzureNativeProvider(config, self.provider_settings)
+        raise ValueError("订阅密钥格式无效，应为32位字母数字或other[...]格式")
+
+    async def get_audio(self, text: str) -> str:
+        if isinstance(self.provider, OTTSProvider):
+            async with self.provider as provider:
+                return await provider.get_audio(
+                    text,
+                    {
+                        "voice": self.provider_config.get("azure_tts_voice"),
+                        "style": self.provider_config.get("azure_tts_style"),
+                        "role": self.provider_config.get("azure_tts_role"),
+                        "rate": self.provider_config.get("azure_tts_rate"),
+                        "volume": self.provider_config.get("azure_tts_volume")
+                    }
+                )
+        else:
+            async with self.provider as provider:
+                return await provider.get_audio(text)

astrbot/core/provider/sources/dashscope_source.py

@@ -3,10 +3,11 @@ import asyncio
 import functools
 from typing import List
 from .. import Provider, Personality
-from ..entites import LLMResponse
+from ..entities import LLMResponse
 from ..func_tool_manager import FuncCall
 from astrbot.core.db import BaseDatabase
 from ..register import register_provider_adapter
+from astrbot.core.message.message_event_result import MessageChain
 from .openai_source import ProviderOpenAIOfficial
 from astrbot.core import logger, sp
 from dashscope import Application
@@ -132,7 +133,9 @@ class ProviderDashscope(ProviderOpenAIOfficial):
             )
             return LLMResponse(
                 role="err",
-                completion_text=f"阿里云百炼请求失败: message={response.message} code={response.status_code}",
+                result_chain=MessageChain().message(
+                    f"阿里云百炼请求失败: message={response.message} code={response.status_code}"
+                ),
             )
 
         output_text = response.output.get("text", "")
@@ -141,11 +144,45 @@ class ProviderDashscope(ProviderOpenAIOfficial):
         if self.output_reference and response.output.get("doc_references", None):
             ref_str = ""
             for ref in response.output.get("doc_references", []):
-                ref_title = ref.get("title", "") if ref.get("title") else ref.get("doc_name", "")
+                ref_title = (
+                    ref.get("title", "")
+                    if ref.get("title")
+                    else ref.get("doc_name", "")
+                )
                 ref_str += f"{ref['index_id']}. {ref_title}\n"
             output_text += f"\n\n回答来源:\n{ref_str}"
 
-        return LLMResponse(role="assistant", completion_text=output_text)
+        llm_response = LLMResponse("assistant")
+        llm_response.result_chain = MessageChain().message(output_text)
+
+        return llm_response
+
+    async def text_chat_stream(
+        self,
+        prompt,
+        session_id=None,
+        image_urls=...,
+        func_tool=None,
+        contexts=...,
+        system_prompt=None,
+        tool_calls_result=None,
+        **kwargs,
+    ):
+        # raise NotImplementedError("This method is not implemented yet.")
+        # 调用 text_chat 模拟流式
+        llm_response = await self.text_chat(
+            prompt=prompt,
+            session_id=session_id,
+            image_urls=image_urls,
+            func_tool=func_tool,
+            contexts=contexts,
+            system_prompt=system_prompt,
+            tool_calls_result=tool_calls_result,
+        )
+        llm_response.is_chunk = True
+        yield llm_response
+        llm_response.is_chunk = False
+        yield llm_response
 
     async def forget(self, session_id):
         return True

astrbot/core/provider/sources/dashscope_tts.py

@@ -1,10 +1,12 @@
+import os
 import dashscope
 import uuid
 import asyncio
 from dashscope.audio.tts_v2 import *
 from ..provider import TTSProvider
-from ..entites import ProviderType
+from ..entities import ProviderType
 from ..register import register_provider_adapter
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 
 @register_provider_adapter(
@@ -20,17 +22,17 @@ class ProviderDashscopeTTSAPI(TTSProvider):
         self.chosen_api_key: str = provider_config.get("api_key", "")
         self.voice: str = provider_config.get("dashscope_tts_voice", "loongstella")
         self.set_model(provider_config.get("model", None))
-        self.timeout_ms = float(provider_config.get("timeout", 20))*1000
-
+        self.timeout_ms = float(provider_config.get("timeout", 20)) * 1000
         dashscope.api_key = self.chosen_api_key
+
+    async def get_audio(self, text: str) -> str:
+        temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+        path = os.path.join(temp_dir, f"dashscope_tts_{uuid.uuid4()}.wav")
         self.synthesizer = SpeechSynthesizer(
             model=self.get_model(),
             voice=self.voice,
             format=AudioFormat.WAV_24000HZ_MONO_16BIT,
         )
-
-    async def get_audio(self, text: str) -> str:
-        path = f"data/temp/dashscope_tts_{uuid.uuid4()}.wav"
         audio = await asyncio.get_event_loop().run_in_executor(
             None, self.synthesizer.call, text, self.timeout_ms
         )

astrbot/core/provider/sources/dify_source.py

@@ -1,8 +1,8 @@
 import astrbot.core.message.components as Comp
-
+import os
 from typing import List
 from .. import Provider, Personality
-from ..entites import LLMResponse
+from ..entities import LLMResponse
 from ..func_tool_manager import FuncCall
 from astrbot.core.db import BaseDatabase
 from ..register import register_provider_adapter
@@ -10,6 +10,7 @@ from astrbot.core.utils.dify_api_client import DifyAPIClient
 from astrbot.core.utils.io import download_image_by_url, download_file
 from astrbot.core import logger, sp
 from astrbot.core.message.message_event_result import MessageChain
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 
 @register_provider_adapter("dify", "Dify APP 适配器。")
@@ -102,7 +103,7 @@ class ProviderDify(Provider):
 
         try:
             match self.api_type:
-                case "chat" | "agent":
+                case "chat" | "agent" | "chatflow":
                     if not prompt:
                         prompt = "请描述这张图片。"
 
@@ -189,6 +190,33 @@ class ProviderDify(Provider):
 
         return LLMResponse(role="assistant", result_chain=chain)
 
+    async def text_chat_stream(
+        self,
+        prompt,
+        session_id=None,
+        image_urls=...,
+        func_tool=None,
+        contexts=...,
+        system_prompt=None,
+        tool_calls_result=None,
+        **kwargs,
+    ):
+        # raise NotImplementedError("This method is not implemented yet.")
+        # 调用 text_chat 模拟流式
+        llm_response = await self.text_chat(
+            prompt=prompt,
+            session_id=session_id,
+            image_urls=image_urls,
+            func_tool=func_tool,
+            contexts=contexts,
+            system_prompt=system_prompt,
+            tool_calls_result=tool_calls_result,
+        )
+        llm_response.is_chunk = True
+        yield llm_response
+        llm_response.is_chunk = False
+        yield llm_response
+
     async def parse_dify_result(self, chunk: dict | str) -> MessageChain:
         if isinstance(chunk, str):
             # Chat
@@ -200,7 +228,8 @@ class ProviderDify(Provider):
                     return Comp.Image(file=item["url"], url=item["url"])
                 case "audio":
                     # 仅支持 wav
-                    path = f"data/temp/{item['filename']}.wav"
+                    temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+                    path = os.path.join(temp_dir, f"{item['filename']}.wav")
                     await download_file(item["url"], path)
                     return Comp.Image(file=item["url"], url=item["url"])
                 case "video":

astrbot/core/provider/sources/edge_tts_source.py

@@ -4,9 +4,10 @@ import edge_tts
 import subprocess
 import asyncio
 from ..provider import TTSProvider
-from ..entites import ProviderType
+from ..entities import ProviderType
 from ..register import register_provider_adapter
 from astrbot.core import logger
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 """
 edge_tts 方式，能够免费、快速生成语音，使用需要先安装edge-tts库
@@ -40,9 +41,9 @@ class ProviderEdgeTTS(TTSProvider):
         self.set_model("edge_tts")
 
     async def get_audio(self, text: str) -> str:
-        os.makedirs("data/temp", exist_ok=True)
-        mp3_path = f"data/temp/edge_tts_temp_{uuid.uuid4()}.mp3"
-        wav_path = f"data/temp/edge_tts_{uuid.uuid4()}.wav"
+        temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+        mp3_path = os.path.join(temp_dir, f"edge_tts_temp_{uuid.uuid4()}.mp3")
+        wav_path = os.path.join(temp_dir, f"edge_tts_{uuid.uuid4()}.wav")
 
         # 构建 Edge TTS 参数
         kwargs = {"text": text, "voice": self.voice}

astrbot/core/provider/sources/fishaudio_tts_api_source.py

@@ -1,11 +1,13 @@
+import os
 import uuid
 import ormsgpack
 from pydantic import BaseModel, conint
 from httpx import AsyncClient
 from typing import Annotated, Literal
 from ..provider import TTSProvider
-from ..entites import ProviderType
+from ..entities import ProviderType
 from ..register import register_provider_adapter
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 
 class ServeReferenceAudio(BaseModel):
@@ -87,7 +89,8 @@ class ProviderFishAudioTTSAPI(TTSProvider):
         )
 
     async def get_audio(self, text: str) -> str:
-        path = f"data/temp/fishaudio_tts_api_{uuid.uuid4()}.wav"
+        temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+        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).stream(

astrbot/core/provider/sources/gemini_source.py

@@ -1,88 +1,55 @@
-import base64
-import aiohttp
-import json
-import random
 import asyncio
+import base64
+import json
+import logging
+import random
+from typing import Optional
+from collections.abc import AsyncGenerator
+
+from google import genai
+from google.genai import types
+from google.genai.errors import APIError
+
 import astrbot.core.message.components as Comp
-from astrbot.core.message.message_event_result import MessageChain
-from astrbot.core.utils.io import download_image_by_url
-from astrbot.core.db import BaseDatabase
-from astrbot.api.provider import Provider, Personality
 from astrbot import logger
+from astrbot.api.provider import Personality, Provider
+from astrbot.core.db import BaseDatabase
+from astrbot.core.message.message_event_result import MessageChain
+from astrbot.core.provider.entities import LLMResponse, ToolCallsResult
 from astrbot.core.provider.func_tool_manager import FuncCall
-from typing import List
+from astrbot.core.utils.io import download_image_by_url
+
 from ..register import register_provider_adapter
-from astrbot.core.provider.entites import LLMResponse
 
 
-class SimpleGoogleGenAIClient:
-    def __init__(self, api_key: str, api_base: str, timeout: int = 120) -> None:
-        self.api_key = api_key
-        if api_base.endswith("/"):
-            self.api_base = api_base[:-1]
-        else:
-            self.api_base = api_base
-        self.client = aiohttp.ClientSession(trust_env=True)
-        self.timeout = timeout
+class SuppressNonTextPartsWarning(logging.Filter):
+    """过滤 Gemini SDK 中的非文本部分警告"""
 
-    async def models_list(self) -> List[str]:
-        request_url = f"{self.api_base}/v1beta/models?key={self.api_key}"
-        async with self.client.get(request_url, timeout=self.timeout) as resp:
-            response = await resp.json()
+    def filter(self, record):
+        return "there are non-text parts in the response" not in record.getMessage()
 
-            models = []
-            for model in response["models"]:
-                if "generateContent" in model["supportedGenerationMethods"]:
-                    models.append(model["name"].replace("models/", ""))
-            return models
 
-    async def generate_content(
-        self,
-        contents: List[dict],
-        model: str = "gemini-1.5-flash",
-        system_instruction: str = "",
-        tools: dict = None,
-        modalities: List[str] = ["Text"],
-        safety_settings: List[dict] = [],
-    ):
-        payload = {}
-        if system_instruction:
-            payload["system_instruction"] = {"parts": {"text": system_instruction}}
-        if tools:
-            payload["tools"] = [tools]
-        payload["contents"] = contents
-        payload["generationConfig"] = {
-            "responseModalities": modalities,
-        }
-        payload["safetySettings"] = [
-            {"category": s["category"], "threshold": s["threshold"]}
-            for s in safety_settings
-        ]
-        logger.debug(f"payload: {payload}")
-        request_url = (
-            f"{self.api_base}/v1beta/models/{model}:generateContent?key={self.api_key}"
-        )
-        async with self.client.post(
-            request_url, json=payload, timeout=self.timeout
-        ) as resp:
-            if "application/json" in resp.headers.get("Content-Type"):
-                try:
-                    response = await resp.json()
-                except Exception as e:
-                    text = await resp.text()
-                    logger.error(f"Gemini 返回了非 json 数据: {text}")
-                    raise e
-                return response
-            else:
-                text = await resp.text()
-                logger.error(f"Gemini 返回了非 json 数据: {text}")
-                raise Exception("Gemini 返回了非 json 数据： ")
+logging.getLogger("google_genai.types").addFilter(SuppressNonTextPartsWarning())
 
 
 @register_provider_adapter(
     "googlegenai_chat_completion", "Google Gemini Chat Completion 提供商适配器"
 )
 class ProviderGoogleGenAI(Provider):
+    CATEGORY_MAPPING = {
+        "harassment": types.HarmCategory.HARM_CATEGORY_HARASSMENT,
+        "hate_speech": types.HarmCategory.HARM_CATEGORY_HATE_SPEECH,
+        "sexually_explicit": types.HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT,
+        "dangerous_content": types.HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT,
+    }
+
+    THRESHOLD_MAPPING = {
+        "BLOCK_NONE": types.HarmBlockThreshold.BLOCK_NONE,
+        "BLOCK_ONLY_HIGH": types.HarmBlockThreshold.BLOCK_ONLY_HIGH,
+        "BLOCK_MEDIUM_AND_ABOVE": types.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE,
+        "BLOCK_LOW_AND_ABOVE": types.HarmBlockThreshold.BLOCK_LOW_AND_ABOVE,
+    }
+
     def __init__(
         self,
         provider_config: dict,
@@ -98,196 +65,416 @@ class ProviderGoogleGenAI(Provider):
             db_helper,
             default_persona,
         )
-        self.chosen_api_key = None
-        self.api_keys: List = provider_config.get("key", [])
-        self.chosen_api_key = self.api_keys[0] if len(self.api_keys) > 0 else None
-        self.timeout = provider_config.get("timeout", 180)
-        if isinstance(self.timeout, str):
-            self.timeout = int(self.timeout)
-        self.client = SimpleGoogleGenAIClient(
-            api_key=self.chosen_api_key,
-            api_base=provider_config.get("api_base", None),
-            timeout=self.timeout,
-        )
+        self.api_keys: list = provider_config.get("key", [])
+        self.chosen_api_key: str = self.api_keys[0] if len(self.api_keys) > 0 else None
+        self.timeout: int = int(provider_config.get("timeout", 180))
+
+        self.api_base: Optional[str] = provider_config.get("api_base", None)
+        if self.api_base and self.api_base.endswith("/"):
+            self.api_base = self.api_base[:-1]
+
+        self._init_client()
         self.set_model(provider_config["model_config"]["model"])
+        self._init_safety_settings()
 
-        safety_mapping = {
-            "harassment": "HARM_CATEGORY_HARASSMENT",
-            "hate_speech": "HARM_CATEGORY_HATE_SPEECH",
-            "sexually_explicit": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
-            "dangerous_content": "HARM_CATEGORY_DANGEROUS_CONTENT",
-        }
+    def _init_client(self) -> None:
+        """初始化Gemini客户端"""
+        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
+            ),
+        ).aio
 
-        self.safety_settings = []
+    def _init_safety_settings(self) -> None:
+        """初始化安全设置"""
         user_safety_config = self.provider_config.get("gm_safety_settings", {})
-        for config_key, harm_category in safety_mapping.items():
-            if threshold := user_safety_config.get(config_key):
-                self.safety_settings.append(
-                    {"category": harm_category, "threshold": threshold}
-                )
+        self.safety_settings = [
+            types.SafetySetting(
+                category=harm_category, threshold=self.THRESHOLD_MAPPING[threshold_str]
+            )
+            for config_key, harm_category in self.CATEGORY_MAPPING.items()
+            if (threshold_str := user_safety_config.get(config_key))
+            and threshold_str in self.THRESHOLD_MAPPING
+        ]
 
-    async def get_models(self):
-        return await self.client.models_list()
+    async def _handle_api_error(self, e: APIError, keys: list[str]) -> bool:
+        """处理API错误，返回是否需要重试"""
+        if e.code == 429 or "API key not valid" in e.message:
+            keys.remove(self.chosen_api_key)
+            if len(keys) > 0:
+                self.set_key(random.choice(keys))
+                logger.info(
+                    f"检测到 Key 异常({e.message})，正在尝试更换 API Key 重试... 当前 Key: {self.chosen_api_key[:12]}..."
+                )
+                await asyncio.sleep(1)
+                return True
+            else:
+                logger.error(
+                    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...")
+        else:
+            logger.error(
+                f"发生了错误(gemini_source)。Provider 配置如下: {self.provider_config}"
+            )
+            raise e
+
+    async def _prepare_query_config(
+        self,
+        payloads: dict,
+        tools: Optional[FuncCall] = None,
+        system_instruction: Optional[str] = None,
+        modalities: Optional[list[str]] = None,
+        temperature: float = 0.7,
+    ) -> types.GenerateContentConfig:
+        """准备查询配置"""
+        if not modalities:
+            modalities = ["Text"]
+
+        # 流式输出不支持图片模态
+        if (
+            self.provider_settings.get("streaming_response", False)
+            and "Image" in modalities
+        ):
+            logger.warning("流式输出不支持图片模态，已自动降级为文本模态")
+            modalities = ["Text"]
+
+        tool_list = None
+        native_coderunner = self.provider_config.get("gm_native_coderunner", False)
+        native_search = self.provider_config.get("gm_native_search", False)
+
+        if native_coderunner:
+            tool_list = [types.Tool(code_execution=types.ToolCodeExecution())]
+            if native_search:
+                logger.warning("已启用代码执行工具，搜索工具将被忽略")
+            if tools:
+                logger.warning("已启用代码执行工具，函数工具将被忽略")
+        elif native_search:
+            tool_list = [types.Tool(google_search=types.GoogleSearch())]
+            if tools:
+                logger.warning("已启用搜索工具，函数工具将被忽略")
+        elif tools and (func_desc := tools.get_func_desc_google_genai_style()):
+            tool_list = [
+                types.Tool(function_declarations=func_desc["function_declarations"])
+            ]
+        return types.GenerateContentConfig(
+            system_instruction=system_instruction,
+            temperature=temperature,
+            max_output_tokens=payloads.get("max_tokens")
+            or payloads.get("maxOutputTokens"),
+            top_p=payloads.get("top_p") or payloads.get("topP"),
+            top_k=payloads.get("top_k") or payloads.get("topK"),
+            frequency_penalty=payloads.get("frequency_penalty")
+            or payloads.get("frequencyPenalty"),
+            presence_penalty=payloads.get("presence_penalty")
+            or payloads.get("presencePenalty"),
+            stop_sequences=payloads.get("stop") or payloads.get("stopSequences"),
+            response_logprobs=payloads.get("response_logprobs")
+            or payloads.get("responseLogprobs"),
+            logprobs=payloads.get("logprobs"),
+            seed=payloads.get("seed"),
+            response_modalities=modalities,
+            tools=tool_list,
+            safety_settings=self.safety_settings if self.safety_settings else None,
+            thinking_config=types.ThinkingConfig(
+                thinking_budget=min(
+                    int(
+                        self.provider_config.get("gm_thinking_config", {}).get(
+                            "budget", 0
+                        )
+                    ),
+                    24576,
+                ),
+            )
+            if "gemini-2.5-flash" in self.get_model()
+            and hasattr(types.ThinkingConfig, "thinking_budget")
+            else None,
+            automatic_function_calling=types.AutomaticFunctionCallingConfig(
+                disable=True
+            ),
+        )
+
+    def _prepare_conversation(self, payloads: dict) -> list[types.Content]:
+        """准备 Gemini SDK 的 Content 列表"""
+
+        def create_text_part(text: str) -> types.Part:
+            content_a = text if text else " "
+            if not text:
+                logger.warning("文本内容为空，已添加空格占位")
+            return types.Part.from_text(text=content_a)
+
+        def process_image_url(image_url_dict: dict) -> types.Part:
+            url = image_url_dict["url"]
+            mime_type = url.split(":")[1].split(";")[0]
+            image_bytes = base64.b64decode(url.split(",", 1)[1])
+            return types.Part.from_bytes(data=image_bytes, mime_type=mime_type)
+
+        def append_or_extend(
+            contents: list[types.Content],
+            part: list[types.Part],
+            content_cls: type[types.Content],
+        ) -> None:
+            if contents and isinstance(contents[-1], content_cls):
+                contents[-1].parts.extend(part)
+            else:
+                contents.append(content_cls(parts=part))
+
+        gemini_contents: list[types.Content] = []
+        native_tool_enabled = any(
+            [
+                self.provider_config.get("gm_native_coderunner", False),
+                self.provider_config.get("gm_native_search", False),
+            ]
+        )
+        for message in payloads["messages"]:
+            role, content = message["role"], message.get("content")
+
+            if role == "user":
+                if isinstance(content, list):
+                    parts = [
+                        types.Part.from_text(text=item["text"] or " ")
+                        if item["type"] == "text"
+                        else process_image_url(item["image_url"])
+                        for item in content
+                    ]
+                else:
+                    parts = [create_text_part(content)]
+                append_or_extend(gemini_contents, parts, types.UserContent)
+
+            elif role == "assistant":
+                if content:
+                    parts = [types.Part.from_text(text=content)]
+                    append_or_extend(gemini_contents, parts, types.ModelContent)
+                elif not native_tool_enabled and "tool_calls" in message:
+                    parts = [
+                        types.Part.from_function_call(
+                            name=tool["function"]["name"],
+                            args=json.loads(tool["function"]["arguments"]),
+                        )
+                        for tool in message["tool_calls"]
+                    ]
+                    append_or_extend(gemini_contents, parts, types.ModelContent)
+                else:
+                    logger.warning("assistant 角色的消息内容为空，已添加空格占位")
+                    if native_tool_enabled and "tool_calls" in message:
+                        logger.warning(
+                            "检测到启用Gemini原生工具，且上下文中存在函数调用，建议使用 /reset 重置上下文"
+                        )
+                    parts = [types.Part.from_text(text=" ")]
+                    append_or_extend(gemini_contents, parts, types.ModelContent)
+
+            elif role == "tool" and not native_tool_enabled:
+                parts = [
+                    types.Part.from_function_response(
+                        name=message["tool_call_id"],
+                        response={
+                            "name": message["tool_call_id"],
+                            "content": message["content"],
+                        },
+                    )
+                ]
+                append_or_extend(gemini_contents, parts, types.UserContent)
+
+        if gemini_contents and isinstance(gemini_contents[0], types.ModelContent):
+            gemini_contents.pop()
+
+        return gemini_contents
+
+    @staticmethod
+    def _process_content_parts(
+        result: types.GenerateContentResponse, llm_response: LLMResponse
+    ) -> MessageChain:
+        """处理内容部分并构建消息链"""
+        finish_reason = result.candidates[0].finish_reason
+        result_parts: Optional[types.Part] = result.candidates[0].content.parts
+
+        if finish_reason == types.FinishReason.SAFETY:
+            raise Exception("模型生成内容未通过 Gemini 平台的安全检查")
+
+        if finish_reason in {
+            types.FinishReason.PROHIBITED_CONTENT,
+            types.FinishReason.SPII,
+            types.FinishReason.BLOCKLIST,
+        }:
+            raise Exception("模型生成内容违反 Gemini 平台政策")
+
+        # 防止旧版本SDK不存在IMAGE_SAFETY
+        if hasattr(types.FinishReason, "IMAGE_SAFETY"):
+            if finish_reason == types.FinishReason.IMAGE_SAFETY:
+                raise Exception("模型生成内容违反 Gemini 平台政策")
+
+        if not result_parts:
+            logger.debug(result.candidates)
+            raise Exception("API 返回的内容为空。")
+
+        chain = []
+        part: types.Part
+
+        # 暂时这样Fallback
+        if all(
+            part.inline_data and part.inline_data.mime_type.startswith("image/")
+            for part in result_parts
+        ):
+            chain.append(Comp.Plain("这是图片"))
+        for part in result_parts:
+            if part.text:
+                chain.append(Comp.Plain(part.text))
+            elif part.function_call:
+                llm_response.role = "tool"
+                llm_response.tools_call_name.append(part.function_call.name)
+                llm_response.tools_call_args.append(part.function_call.args)
+                # gemini 返回的 function_call.id 可能为 None
+                llm_response.tools_call_ids.append(
+                    part.function_call.id or part.function_call.name
+                )
+            elif part.inline_data and part.inline_data.mime_type.startswith("image/"):
+                chain.append(Comp.Image.fromBytes(part.inline_data.data))
+        return MessageChain(chain=chain)
 
     async def _query(self, payloads: dict, tools: FuncCall) -> LLMResponse:
-        tool = None
-        if tools:
-            tool = tools.get_func_desc_google_genai_style()
-            if not tool:
-                tool = None
+        """非流式请求 Gemini API"""
+        system_instruction = next(
+            (msg["content"] for msg in payloads["messages"] if msg["role"] == "system"),
+            None,
+        )
+
+        modalities = ["Text"]
+        if self.provider_config.get("gm_resp_image_modal", False):
+            modalities.append("Image")
+
+        conversation = self._prepare_conversation(payloads)
+        temperature = payloads.get("temperature", 0.7)
+
+        result: Optional[types.GenerateContentResponse] = None
+        while True:
+            try:
+                config = await self._prepare_query_config(
+                    payloads, tools, system_instruction, modalities, temperature
+                )
+                result = await self.client.models.generate_content(
+                    model=self.get_model(),
+                    contents=conversation,
+                    config=config,
+                )
+
+                if result.candidates[0].finish_reason == types.FinishReason.RECITATION:
+                    if temperature > 2:
+                        raise Exception("温度参数已超过最大值2，仍然发生recitation")
+                    temperature += 0.2
+                    logger.warning(
+                        f"发生了recitation，正在提高温度至{temperature:.1f}重试..."
+                    )
+                    continue
 
-        system_instruction = ""
-        for message in payloads["messages"]:
-            if message["role"] == "system":
-                system_instruction = message["content"]
                 break
 
-        google_genai_conversation = []
-        for message in payloads["messages"]:
-            if message["role"] == "user":
-                if isinstance(message["content"], str):
-                    if not message["content"]:
-                        message["content"] = ""
-
-                    google_genai_conversation.append(
-                        {"role": "user", "parts": [{"text": message["content"]}]}
+            except APIError as e:
+                if "Developer instruction is not enabled" in e.message:
+                    logger.warning(
+                        f"{self.get_model()} 不支持 system prompt，已自动去除(影响人格设置)"
                     )
-                elif isinstance(message["content"], list):
-                    # images
-                    parts = []
-                    for part in message["content"]:
-                        if part["type"] == "text":
-                            if not part["text"]:
-                                part["text"] = ""
-                            parts.append({"text": part["text"]})
-                        elif part["type"] == "image_url":
-                            parts.append(
-                                {
-                                    "inline_data": {
-                                        "mime_type": "image/jpeg",
-                                        "data": part["image_url"]["url"].replace(
-                                            "data:image/jpeg;base64,", ""
-                                        ),  # base64
-                                    }
-                                }
-                            )
-                    google_genai_conversation.append({"role": "user", "parts": parts})
-
-            elif message["role"] == "assistant":
-                if "content" in message:
-                    if not message["content"]:
-                        message["content"] = ""
-                    google_genai_conversation.append(
-                        {"role": "model", "parts": [{"text": message["content"]}]}
+                    system_instruction = None
+                elif "Function calling is not enabled" in e.message:
+                    logger.warning(f"{self.get_model()} 不支持函数调用，已自动去除")
+                    tools = None
+                elif (
+                    "Multi-modal output is not supported" in e.message
+                    or "Model does not support the requested response modalities"
+                    in e.message
+                    or "only supports text output" in e.message
+                ):
+                    logger.warning(
+                        f"{self.get_model()} 不支持多模态输出，降级为文本模态"
                     )
-                elif "tool_calls" in message:
-                    # tool calls in the last turn
-                    parts = []
-                    for tool_call in message["tool_calls"]:
-                        parts.append(
-                            {
-                                "functionCall": {
-                                    "name": tool_call["function"]["name"],
-                                    "args": json.loads(
-                                        tool_call["function"]["arguments"]
-                                    ),
-                                }
-                            }
-                        )
-                    google_genai_conversation.append({"role": "model", "parts": parts})
-            elif message["role"] == "tool":
-                parts = []
-                parts.append(
-                    {
-                        "functionResponse": {
-                            "name": message["tool_call_id"],
-                            "response": {
-                                "name": message["tool_call_id"],
-                                "content": message["content"],
-                            },
-                        }
-                    }
-                )
-                google_genai_conversation.append({"role": "user", "parts": parts})
+                    modalities = ["Text"]
+                else:
+                    raise
+                continue
 
-        logger.debug(f"google_genai_conversation: {google_genai_conversation}")
-
-        modalites = ["Text"]
-        if self.provider_config.get("gm_resp_image_modal", False):
-            modalites.append("Image")
-
-        loop = True
-        while loop:
-            loop = False
-            result = await self.client.generate_content(
-                contents=google_genai_conversation,
-                model=self.get_model(),
-                system_instruction=system_instruction,
-                tools=tool,
-                modalities=modalites,
-                safety_settings=self.safety_settings,
-            )
-            logger.debug(f"result: {result}")
-
-            # Developer instruction is not enabled for models/gemini-2.0-flash-exp
-            if "Developer instruction is not enabled" in str(result):
-                logger.warning(
-                    f"{self.get_model()} 不支持 system prompt, 已自动去除, 将会影响人格设置。"
-                )
-                system_instruction = ""
-                loop = True
-
-            elif "Function calling is not enabled" in str(result):
-                logger.warning(
-                    f"{self.get_model()} 不支持函数调用，已自动去除，不影响使用。"
-                )
-                tool = None
-                loop = True
-
-            elif "Multi-modal output is not supported" in str(result):
-                logger.warning(
-                    f"{self.get_model()} 不支持多模态输出，降级为文本模态重新请求。"
-                )
-                modalites = ["Text"]
-                loop = True
-
-            elif "candidates" not in result:
-                raise Exception("Gemini 返回异常结果: " + str(result))
-
-        candidates = result["candidates"][0]["content"]["parts"]
         llm_response = LLMResponse("assistant")
-        chain = []
-        for candidate in candidates:
-            if "text" in candidate:
-                chain.append(Comp.Plain(candidate["text"]))
-            elif "functionCall" in candidate:
-                llm_response.role = "tool"
-                llm_response.tools_call_args.append(candidate["functionCall"]["args"])
-                llm_response.tools_call_name.append(candidate["functionCall"]["name"])
-                llm_response.tools_call_ids.append(
-                    candidate["functionCall"]["name"]
-                )  # 没有 tool id
-            elif "inlineData" in candidate:
-                mime_type: str = candidate["inlineData"]["mimeType"]
-                if mime_type.startswith("image/"):
-                    chain.append(Comp.Image.fromBase64(candidate["inlineData"]["data"]))
-
-        llm_response.result_chain = MessageChain(chain=chain)
+        llm_response.result_chain = self._process_content_parts(result, llm_response)
         return llm_response
 
+    async def _query_stream(
+        self, payloads: dict, tools: FuncCall
+    ) -> AsyncGenerator[LLMResponse, None]:
+        """流式请求 Gemini API"""
+        system_instruction = next(
+            (msg["content"] for msg in payloads["messages"] if msg["role"] == "system"),
+            None,
+        )
+
+        conversation = self._prepare_conversation(payloads)
+
+        result = None
+        while True:
+            try:
+                config = await self._prepare_query_config(
+                    payloads, tools, system_instruction
+                )
+                result = await self.client.models.generate_content_stream(
+                    model=self.get_model(),
+                    contents=conversation,
+                    config=config,
+                )
+                break
+            except APIError as e:
+                if "Developer instruction is not enabled" in e.message:
+                    logger.warning(
+                        f"{self.get_model()} 不支持 system prompt，已自动去除(影响人格设置)"
+                    )
+                    system_instruction = None
+                elif "Function calling is not enabled" in e.message:
+                    logger.warning(f"{self.get_model()} 不支持函数调用，已自动去除")
+                    tools = None
+                else:
+                    raise
+                continue
+
+        async for chunk in result:
+            llm_response = LLMResponse("assistant", is_chunk=True)
+
+            if chunk.candidates[0].content.parts and any(
+                part.function_call for part in chunk.candidates[0].content.parts
+            ):
+                llm_response = LLMResponse("assistant", is_chunk=False)
+                llm_response.result_chain = self._process_content_parts(
+                    chunk, llm_response
+                )
+                yield llm_response
+                break
+
+            if chunk.text:
+                llm_response.result_chain = MessageChain(chain=[Comp.Plain(chunk.text)])
+                yield llm_response
+
+            if chunk.candidates[0].finish_reason:
+                llm_response = LLMResponse("assistant", is_chunk=False)
+                if not chunk.candidates[0].content.parts:
+                    llm_response.result_chain = MessageChain(chain=[Comp.Plain(" ")])
+                else:
+                    llm_response.result_chain = self._process_content_parts(
+                        chunk, llm_response
+                    )
+                yield llm_response
+                break
+
     async def text_chat(
         self,
         prompt: str,
         session_id: str = None,
-        image_urls: List[str] = None,
+        image_urls: list[str] = None,
         func_tool: FuncCall = None,
-        contexts=[],
-        system_prompt=None,
-        tool_calls_result=None,
+        contexts: list = None,
+        system_prompt: str = None,
+        tool_calls_result: ToolCallsResult = None,
         **kwargs,
     ) -> LLMResponse:
+        if contexts is None:
+            contexts = []
         new_record = await self.assemble_context(prompt, image_urls)
-        context_query = []
         context_query = [*contexts, new_record]
         if system_prompt:
             context_query.insert(0, {"role": "system", "content": system_prompt})
@@ -304,55 +491,92 @@ class ProviderGoogleGenAI(Provider):
         model_config["model"] = self.get_model()
 
         payloads = {"messages": context_query, **model_config}
-        llm_response = None
 
         retry = 10
         keys = self.api_keys.copy()
-        chosen_key = random.choice(keys)
 
-        for i in range(retry):
+        for _ in range(retry):
             try:
-                self.client.api_key = chosen_key
-                llm_response = await self._query(payloads, func_tool)
+                return await self._query(payloads, func_tool)
+            except APIError as e:
+                if await self._handle_api_error(e, keys):
+                    continue
                 break
-            except Exception as e:
-                if "429" in str(e) or "API key not valid" in str(e):
-                    keys.remove(chosen_key)
-                    if len(keys) > 0:
-                        chosen_key = random.choice(keys)
-                        logger.info(
-                            f"检测到 Key 异常({str(e)})，正在尝试更换 API Key 重试... 当前 Key: {chosen_key[:12]}..."
-                        )
-                        await asyncio.sleep(1)
-                        continue
-                    else:
-                        logger.error(
-                            f"检测到 Key 异常({str(e)})，且已没有可用的 Key。 当前 Key: {chosen_key[:12]}..."
-                        )
-                        raise Exception("达到了 Gemini 速率限制, 请稍后再试...")
-                else:
-                    logger.error(
-                        f"发生了错误(gemini_source)。Provider 配置如下: {self.provider_config}"
-                    )
-                    raise e
 
-        return llm_response
+    async def text_chat_stream(
+        self,
+        prompt: str,
+        session_id: str = None,
+        image_urls: list[str] = None,
+        func_tool: FuncCall = None,
+        contexts: str = None,
+        system_prompt: str = None,
+        tool_calls_result: ToolCallsResult = None,
+        **kwargs,
+    ) -> AsyncGenerator[LLMResponse, None]:
+        if contexts is None:
+            contexts = []
+        new_record = await self.assemble_context(prompt, image_urls)
+        context_query = [*contexts, new_record]
+        if system_prompt:
+            context_query.insert(0, {"role": "system", "content": system_prompt})
+
+        for part in context_query:
+            if "_no_save" in part:
+                del part["_no_save"]
+
+        # tool calls result
+        if tool_calls_result:
+            context_query.extend(tool_calls_result.to_openai_messages())
+
+        model_config = self.provider_config.get("model_config", {})
+        model_config["model"] = self.get_model()
+
+        payloads = {"messages": context_query, **model_config}
+
+        retry = 10
+        keys = self.api_keys.copy()
+
+        for _ in range(retry):
+            try:
+                async for response in self._query_stream(payloads, func_tool):
+                    yield response
+                break
+            except APIError as e:
+                if await self._handle_api_error(e, keys):
+                    continue
+                break
+
+    async def get_models(self):
+        try:
+            models = await self.client.models.list()
+            return [
+                m.name.replace("models/", "")
+                for m in models
+                if "generateContent" in m.supported_actions
+            ]
+        except APIError as e:
+            raise Exception(f"获取模型列表失败: {e.message}")
 
     def get_current_key(self) -> str:
-        return self.client.api_key
+        return self.chosen_api_key
 
-    def get_keys(self) -> List[str]:
+    def get_keys(self) -> list[str]:
         return self.api_keys
 
     def set_key(self, key):
-        self.client.api_key = key
+        self.chosen_api_key = key
+        self._init_client()
 
-    async def assemble_context(self, text: str, image_urls: List[str] = None):
+    async def assemble_context(self, text: str, image_urls: list[str] = None):
         """
         组装上下文。
         """
         if image_urls:
-            user_content = {"role": "user", "content": [{"type": "text", "text": text}]}
+            user_content = {
+                "role": "user",
+                "content": [{"type": "text", "text": text if text else "[图片]"}],
+            }
             for image_url in image_urls:
                 if image_url.startswith("http"):
                     image_path = await download_image_by_url(image_url)
@@ -384,5 +608,4 @@ class ProviderGoogleGenAI(Provider):
         return ""
 
     async def terminate(self):
-        await self.client.client.close()
         logger.info("Google GenAI 适配器已终止。")

astrbot/core/provider/sources/gsvi_tts_source.py

@@ -1,9 +1,11 @@
+import os
 import uuid
 import aiohttp
 import urllib.parse
 from ..provider import TTSProvider
-from ..entites import ProviderType
+from ..entities import ProviderType
 from ..register import register_provider_adapter
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 
 @register_provider_adapter(
@@ -23,7 +25,8 @@ class ProviderGSVITTS(TTSProvider):
         self.emotion = provider_config.get("emotion")
 
     async def get_audio(self, text: str) -> str:
-        path = f"data/temp/gsvi_tts_{uuid.uuid4()}.wav"
+        temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+        path = os.path.join(temp_dir, f"gsvi_tts_{uuid.uuid4()}.wav")
         params = {"text": text}
 
         if self.character:

astrbot/core/provider/sources/llmtuner_source.py

@@ -2,7 +2,7 @@ import os
 from llmtuner.chat import ChatModel
 from typing import List
 from .. import Provider
-from ..entites import LLMResponse
+from ..entities import LLMResponse
 from ..func_tool_manager import FuncCall
 from astrbot.core.db import BaseDatabase
 from ..register import register_provider_adapter
@@ -95,6 +95,33 @@ class LLMTunerModelLoader(Provider):
 
         return llm_response
 
+    async def text_chat_stream(
+        self,
+        prompt,
+        session_id=None,
+        image_urls=...,
+        func_tool=None,
+        contexts=...,
+        system_prompt=None,
+        tool_calls_result=None,
+        **kwargs,
+    ):
+        # raise NotImplementedError("This method is not implemented yet.")
+        # 调用 text_chat 模拟流式
+        llm_response = await self.text_chat(
+            prompt=prompt,
+            session_id=session_id,
+            image_urls=image_urls,
+            func_tool=func_tool,
+            contexts=contexts,
+            system_prompt=system_prompt,
+            tool_calls_result=tool_calls_result,
+        )
+        llm_response.is_chunk = True
+        yield llm_response
+        llm_response.is_chunk = False
+        yield llm_response
+
     async def get_current_key(self):
         return "none"
 

astrbot/core/provider/sources/minimax_tts_api_source.py

@@ -0,0 +1,149 @@
+import json
+import os
+import uuid
+import aiohttp
+from typing import Dict, List, Union, AsyncIterator
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
+from astrbot.api import logger
+from ..entities import ProviderType
+from ..provider import TTSProvider
+from ..register import register_provider_adapter
+
+
+@register_provider_adapter(
+    "minimax_tts_api", "MiniMax TTS API", provider_type=ProviderType.TEXT_TO_SPEECH
+)
+class ProviderMiniMaxTTSAPI(TTSProvider):
+    def __init__(
+        self,
+        provider_config: dict,
+        provider_settings: dict,
+    ) -> None:
+        super().__init__(provider_config, provider_settings)
+        self.chosen_api_key: str = provider_config.get("api_key", "")
+        self.api_base: str = provider_config.get(
+            "api_base", "https://api.minimax.chat/v1/t2a_v2"
+        )
+        self.group_id: str = provider_config.get("minimax-group-id", "")
+        self.set_model(provider_config.get("model", ""))
+        self.lang_boost: str = provider_config.get("minimax-langboost", "auto")
+        self.is_timber_weight: bool = provider_config.get(
+            "minimax-is-timber-weight", False
+        )
+        self.timber_weight: List[Dict[str, Union[str, int]]] = json.loads(
+            provider_config.get(
+                "minimax-timber-weight",
+                '[{"voice_id": "Chinese (Mandarin)_Warm_Girl", "weight": 1}]',
+            )
+        )
+
+        self.voice_setting: dict = {
+            "speed": provider_config.get("minimax-voice-speed", 1.0),
+            "vol": provider_config.get("minimax-voice-vol", 1.0),
+            "pitch": provider_config.get("minimax-voice-pitch", 0),
+            "voice_id": ""
+            if self.is_timber_weight
+            else provider_config.get("minimax-voice-id", ""),
+            "emotion": provider_config.get("minimax-voice-emotion", "neutral"),
+            "latex_read": provider_config.get("minimax-voice-latex", False),
+            "english_normalization": provider_config.get(
+                "minimax-voice-english-normalization", False
+            ),
+        }
+
+        self.audio_setting: dict = {
+            "sample_rate": 32000,
+            "bitrate": 128000,
+            "format": "mp3",
+        }
+
+        self.concat_base_url: str = f"{self.api_base}?GroupId={self.group_id}"
+        self.headers = {
+            "Authorization": f"Bearer {self.chosen_api_key}",
+            "accept": "application/json, text/plain, */*",
+            "content-type": "application/json",
+        }
+
+    def _build_tts_stream_body(self, text: str):
+        """构建流式请求体"""
+        dict_body: Dict[str, object] = {
+            "model": self.model_name,
+            "text": text,
+            "stream": True,
+            "language_boost": self.lang_boost,
+            "voice_setting": self.voice_setting,
+            "audio_setting": self.audio_setting,
+        }
+        if self.is_timber_weight:
+            dict_body["timber_weights"] = self.timber_weight
+
+        return json.dumps(dict_body)
+
+    async def _call_tts_stream(self, text: str) -> AsyncIterator[bytes]:
+        """进行流式请求"""
+        try:
+            async with aiohttp.ClientSession() as session:
+                async with session.post(
+                    self.concat_base_url,
+                    headers=self.headers,
+                    data=self._build_tts_stream_body(text),
+                    timeout=aiohttp.ClientTimeout(total=60),
+                ) as response:
+                    response.raise_for_status()
+
+                    buffer = b""
+                    while True:
+                        chunk = await response.content.read(8192)
+                        if not chunk:
+                            break
+
+                        buffer += chunk
+
+                        while b"\n\n" in buffer:
+                            try:
+                                message, buffer = buffer.split(b"\n\n", 1)
+                                if message.startswith(b"data: "):
+                                    try:
+                                        data = json.loads(message[6:])
+                                        if "extra_info" in data:
+                                            continue
+                                        audio = data.get("data", {}).get("audio")
+                                        if audio is not None:
+                                            yield audio
+                                    except json.JSONDecodeError:
+                                        logger.warning(
+                                            "Failed to parse JSON data from SSE message"
+                                        )
+                                        continue
+                            except ValueError:
+                                buffer = buffer[-1024:]
+
+        except aiohttp.ClientError as e:
+            raise Exception(f"MiniMax TTS API请求失败: {str(e)}")
+
+    async def _audio_play(self, audio_stream: AsyncIterator[str]) -> bytes:
+        """解码数据流到 audio 比特流"""
+        chunks = []
+        async for chunk in audio_stream:
+            if chunk.strip():
+                chunks.append(bytes.fromhex(chunk.strip()))
+        return b"".join(chunks)
+
+    async def get_audio(self, text: str) -> str:
+        temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+        os.makedirs(temp_dir, exist_ok=True)
+        path = os.path.join(temp_dir, f"minimax_tts_api_{uuid.uuid4()}.mp3")
+
+        try:
+            # 直接将异步生成器传递给 _audio_play 方法
+            audio_stream = self._call_tts_stream(text)
+            audio = await self._audio_play(audio_stream)
+
+            # 结果保存至文件
+            with open(path, "wb") as file:
+                file.write(audio)
+
+            return path
+
+        except aiohttp.ClientError as e:
+            raise e

astrbot/core/provider/sources/openai_source.py

@@ -4,19 +4,24 @@ import os
 import inspect
 import random
 import asyncio
+import astrbot.core.message.components as Comp
 
 from openai import AsyncOpenAI, AsyncAzureOpenAI
 from openai.types.chat.chat_completion import ChatCompletion
+
+# from openai.types.chat.chat_completion_chunk import ChatCompletionChunk
 from openai._exceptions import NotFoundError, UnprocessableEntityError
+from openai.lib.streaming.chat._completions import ChatCompletionStreamState
 from astrbot.core.utils.io import download_image_by_url
+from astrbot.core.message.message_event_result import MessageChain
 
 from astrbot.core.db import BaseDatabase
 from astrbot.api.provider import Provider, Personality
 from astrbot import logger
 from astrbot.core.provider.func_tool_manager import FuncCall
-from typing import List
+from typing import List, AsyncGenerator
 from ..register import register_provider_adapter
-from astrbot.core.provider.entites import LLMResponse
+from astrbot.core.provider.entities import LLMResponse, ToolCallsResult
 
 
 @register_provider_adapter(
@@ -82,7 +87,11 @@ class ProviderOpenAIOfficial(Provider):
 
     async def _query(self, payloads: dict, tools: FuncCall) -> LLMResponse:
         if tools:
-            tool_list = tools.get_func_desc_openai_style()
+            model = payloads.get("model", "").lower()
+            omit_empty_param_field = "gemini" in model
+            tool_list = tools.get_func_desc_openai_style(
+                omit_empty_parameter_field=omit_empty_param_field
+            )
             if tool_list:
                 payloads["tools"] = tool_list
 
@@ -107,16 +116,76 @@ class ProviderOpenAIOfficial(Provider):
 
         logger.debug(f"completion: {completion}")
 
+        llm_response = await self.parse_openai_completion(completion, tools)
+
+        return llm_response
+
+    async def _query_stream(
+        self, payloads: dict, tools: FuncCall
+    ) -> AsyncGenerator[LLMResponse, None]:
+        """流式查询API，逐步返回结果"""
+        if tools:
+            model = payloads.get("model", "").lower()
+            omit_empty_param_field = "gemini" in model
+            tool_list = tools.get_func_desc_openai_style(
+                omit_empty_parameter_field=omit_empty_param_field
+            )
+            if tool_list:
+                payloads["tools"] = tool_list
+
+        # 不在默认参数中的参数放在 extra_body 中
+        extra_body = {}
+        to_del = []
+        for key in payloads.keys():
+            if key not in self.default_params:
+                extra_body[key] = payloads[key]
+                to_del.append(key)
+        for key in to_del:
+            del payloads[key]
+
+        stream = await self.client.chat.completions.create(
+            **payloads, stream=True, extra_body=extra_body
+        )
+
+        llm_response = LLMResponse("assistant", is_chunk=True)
+
+        state = ChatCompletionStreamState()
+
+        async for chunk in stream:
+            try:
+                state.handle_chunk(chunk)
+            except Exception as e:
+                logger.warning("Saving chunk state error: " + str(e))
+            if len(chunk.choices) == 0:
+                continue
+            delta = chunk.choices[0].delta
+            # 处理文本内容
+            if delta.content:
+                completion_text = delta.content
+                llm_response.result_chain = MessageChain(
+                    chain=[Comp.Plain(completion_text)]
+                )
+                yield llm_response
+
+        final_completion = state.get_final_completion()
+        llm_response = await self.parse_openai_completion(final_completion, tools)
+
+        yield llm_response
+
+    async def parse_openai_completion(
+        self, completion: ChatCompletion, tools: FuncCall
+    ):
+        """解析 OpenAI 的 ChatCompletion 响应"""
+        llm_response = LLMResponse("assistant")
+
         if len(completion.choices) == 0:
             raise Exception("API 返回的 completion 为空。")
         choice = completion.choices[0]
 
-        llm_response = LLMResponse("assistant")
-
         if choice.message.content:
             # text completion
             completion_text = str(choice.message.content).strip()
-            llm_response.completion_text = completion_text
+            llm_response.result_chain = MessageChain().message(completion_text)
 
         if choice.message.tool_calls:
             # tools call (function calling)
@@ -126,7 +195,11 @@ class ProviderOpenAIOfficial(Provider):
             for tool_call in choice.message.tool_calls:
                 for tool in tools.func_list:
                     if tool.name == tool_call.function.name:
-                        args = json.loads(tool_call.function.arguments)
+                        # workaround for #1454
+                        if isinstance(tool_call.function.arguments, str):
+                            args = json.loads(tool_call.function.arguments)
+                        else:
+                            args = tool_call.function.arguments
                         args_ls.append(args)
                         func_name_ls.append(tool_call.function.name)
                         tool_call_ids.append(tool_call.id)
@@ -148,17 +221,20 @@ class ProviderOpenAIOfficial(Provider):
 
         return llm_response
 
-    async def text_chat(
+    async def _prepare_chat_payload(
         self,
         prompt: str,
         session_id: str = None,
-        image_urls: List[str] = [],
+        image_urls: list[str] = None,
         func_tool: FuncCall = None,
-        contexts=[],
-        system_prompt=None,
-        tool_calls_result=None,
+        contexts: list = None,
+        system_prompt: str = None,
+        tool_calls_result: ToolCallsResult = None,
         **kwargs,
-    ) -> LLMResponse:
+    ) -> tuple:
+        """准备聊天所需的有效载荷和上下文"""
+        if contexts is None:
+            contexts = []
         new_record = await self.assemble_context(prompt, image_urls)
         context_query = [*contexts, new_record]
         if system_prompt:
@@ -177,13 +253,122 @@ class ProviderOpenAIOfficial(Provider):
 
         payloads = {"messages": context_query, **model_config}
 
-        llm_response = None
+        return payloads, context_query, func_tool
 
+    async def _handle_api_error(
+        self,
+        e: Exception,
+        payloads: dict,
+        context_query: list,
+        func_tool: FuncCall,
+        chosen_key: str,
+        available_api_keys: List[str],
+        retry_cnt: int,
+        max_retries: int,
+    ) -> tuple:
+        """处理API错误并尝试恢复"""
+        if "429" in str(e):
+            logger.warning(
+                f"API 调用过于频繁，尝试使用其他 Key 重试。当前 Key: {chosen_key[:12]}"
+            )
+            # 最后一次不等待
+            if retry_cnt < max_retries - 1:
+                await asyncio.sleep(1)
+            available_api_keys.remove(chosen_key)
+            if len(available_api_keys) > 0:
+                chosen_key = random.choice(available_api_keys)
+                return (
+                    False,
+                    chosen_key,
+                    available_api_keys,
+                    payloads,
+                    context_query,
+                    func_tool,
+                )
+            else:
+                raise e
+        elif "maximum context length" in str(e):
+            logger.warning(
+                f"上下文长度超过限制。尝试弹出最早的记录然后重试。当前记录条数: {len(context_query)}"
+            )
+            await self.pop_record(context_query)
+            payloads["messages"] = context_query
+            return (
+                False,
+                chosen_key,
+                available_api_keys,
+                payloads,
+                context_query,
+                func_tool,
+            )
+        elif "The model is not a VLM" in str(e):  # siliconcloud
+            # 尝试删除所有 image
+            new_contexts = await self._remove_image_from_context(context_query)
+            payloads["messages"] = new_contexts
+            context_query = new_contexts
+            return (
+                False,
+                chosen_key,
+                available_api_keys,
+                payloads,
+                context_query,
+                func_tool,
+            )
+        elif (
+            "Function calling is not enabled" in str(e)
+            or ("tool" in str(e).lower() and "support" in str(e).lower())
+            or ("function" in str(e).lower() and "support" in str(e).lower())
+        ):
+            # openai, ollama, gemini openai, siliconcloud 的错误提示与 code 不统一，只能通过字符串匹配
+            logger.info(
+                f"{self.get_model()} 不支持函数工具调用，已自动去除，不影响使用。"
+            )
+            if "tools" in payloads:
+                del payloads["tools"]
+            return False, chosen_key, available_api_keys, payloads, context_query, None
+        else:
+            logger.error(f"发生了错误。Provider 配置如下: {self.provider_config}")
+
+            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}"
+                    )
+
+            raise e
+
+    async def text_chat(
+        self,
+        prompt,
+        session_id=None,
+        image_urls=None,
+        func_tool=None,
+        contexts=None,
+        system_prompt=None,
+        tool_calls_result=None,
+        **kwargs,
+    ) -> LLMResponse:
+        payloads, context_query, func_tool = await self._prepare_chat_payload(
+            prompt,
+            session_id,
+            image_urls,
+            func_tool,
+            contexts,
+            system_prompt,
+            tool_calls_result,
+            **kwargs,
+        )
+
+        llm_response = None
         max_retries = 10
         available_api_keys = self.api_keys.copy()
         chosen_key = random.choice(available_api_keys)
 
-        e = None
+        last_exception = None
         retry_cnt = 0
         for retry_cnt in range(max_retries):
             try:
@@ -197,64 +382,103 @@ class ProviderOpenAIOfficial(Provider):
                 payloads["messages"] = new_contexts
                 context_query = new_contexts
             except Exception as e:
-                if "429" in str(e):
-                    logger.warning(
-                        f"API 调用过于频繁，尝试使用其他 Key 重试。当前 Key: {chosen_key[:12]}"
-                    )
-                    # 最后一次不等待
-                    if retry_cnt < max_retries - 1:
-                        await asyncio.sleep(1)
-                    available_api_keys.remove(chosen_key)
-                    if len(available_api_keys) > 0:
-                        chosen_key = random.choice(available_api_keys)
-                        continue
-                    else:
-                        raise e
-                elif "maximum context length" in str(e):
-                    logger.warning(
-                        f"上下文长度超过限制。尝试弹出最早的记录然后重试。当前记录条数: {len(context_query)}"
-                    )
-                    await self.pop_record(context_query)
-                elif "The model is not a VLM" in str(e):  # siliconcloud
-                    # 尝试删除所有 image
-                    new_contexts = await self._remove_image_from_context(context_query)
-                    payloads["messages"] = new_contexts
-                elif (
-                    "Function calling is not enabled" in str(e)
-                    or ("tool" in str(e).lower() and "support" in str(e).lower())
-                    or ("function" in str(e).lower() and "support" in str(e).lower())
-                ):
-                    # openai, ollama, gemini openai, siliconcloud 的错误提示与 code 不统一，只能通过字符串匹配
-                    logger.info(
-                        f"{self.get_model()} 不支持函数工具调用，已自动去除，不影响使用。"
-                    )
-                    if "tools" in payloads:
-                        del payloads["tools"]
-                    func_tool = None
-                else:
-                    logger.error(
-                        f"发生了错误。Provider 配置如下: {self.provider_config}"
-                    )
-
-                    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}"
-                            )
-
-                    raise e
+                last_exception = e
+                (
+                    success,
+                    chosen_key,
+                    available_api_keys,
+                    payloads,
+                    context_query,
+                    func_tool,
+                ) = await self._handle_api_error(
+                    e,
+                    payloads,
+                    context_query,
+                    func_tool,
+                    chosen_key,
+                    available_api_keys,
+                    retry_cnt,
+                    max_retries,
+                )
+                if success:
+                    break
 
         if retry_cnt == max_retries - 1:
             logger.error(f"API 调用失败，重试 {max_retries} 次仍然失败。")
-            raise e
+            if last_exception is None:
+                raise Exception("未知错误")
+            raise last_exception
         return llm_response
 
+    async def text_chat_stream(
+        self,
+        prompt: str,
+        session_id: str = None,
+        image_urls: List[str] = [],
+        func_tool: FuncCall = None,
+        contexts=[],
+        system_prompt=None,
+        tool_calls_result=None,
+        **kwargs,
+    ) -> AsyncGenerator[LLMResponse, None]:
+        """流式对话，与服务商交互并逐步返回结果"""
+        payloads, context_query, func_tool = await self._prepare_chat_payload(
+            prompt,
+            session_id,
+            image_urls,
+            func_tool,
+            contexts,
+            system_prompt,
+            tool_calls_result,
+            **kwargs,
+        )
+
+        max_retries = 10
+        available_api_keys = self.api_keys.copy()
+        chosen_key = random.choice(available_api_keys)
+
+        last_exception = None
+        retry_cnt = 0
+        for retry_cnt in range(max_retries):
+            try:
+                self.client.api_key = chosen_key
+                async for response in self._query_stream(payloads, func_tool):
+                    yield response
+                break
+            except UnprocessableEntityError as e:
+                logger.warning(f"不可处理的实体错误：{e}，尝试删除图片。")
+                # 尝试删除所有 image
+                new_contexts = await self._remove_image_from_context(context_query)
+                payloads["messages"] = new_contexts
+                context_query = new_contexts
+            except Exception as e:
+                last_exception = e
+                (
+                    success,
+                    chosen_key,
+                    available_api_keys,
+                    payloads,
+                    context_query,
+                    func_tool,
+                ) = await self._handle_api_error(
+                    e,
+                    payloads,
+                    context_query,
+                    func_tool,
+                    chosen_key,
+                    available_api_keys,
+                    retry_cnt,
+                    max_retries,
+                )
+                if success:
+                    break
+
+        if retry_cnt == max_retries - 1:
+            logger.error(f"API 调用失败，重试 {max_retries} 次仍然失败。")
+            if last_exception is None:
+                raise Exception("未知错误")
+            raise last_exception
+
     async def _remove_image_from_context(self, contexts: List):
         """
         从上下文中删除所有带有 image 的记录
@@ -293,7 +517,10 @@ class ProviderOpenAIOfficial(Provider):
     async def assemble_context(self, text: str, image_urls: List[str] = None) -> dict:
         """组装成符合 OpenAI 格式的 role 为 user 的消息段"""
         if image_urls:
-            user_content = {"role": "user", "content": [{"type": "text", "text": text}]}
+            user_content = {
+                "role": "user",
+                "content": [{"type": "text", "text": text if text else "[图片]"}],
+            }
             for image_url in image_urls:
                 if image_url.startswith("http"):
                     image_path = await download_image_by_url(image_url)

astrbot/core/provider/sources/openai_tts_api_source.py

@@ -1,8 +1,10 @@
+import os
 import uuid
 from openai import AsyncOpenAI, NOT_GIVEN
 from ..provider import TTSProvider
-from ..entites import ProviderType
+from ..entities import ProviderType
 from ..register import register_provider_adapter
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 
 @register_provider_adapter(
@@ -31,7 +33,8 @@ class ProviderOpenAITTSAPI(TTSProvider):
         self.set_model(provider_config.get("model", None))
 
     async def get_audio(self, text: str) -> str:
-        path = f"data/temp/openai_tts_api_{uuid.uuid4()}.wav"
+        temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+        path = os.path.join(temp_dir, f"openai_tts_api_{uuid.uuid4()}.wav")
         async with self.client.audio.speech.with_streaming_response.create(
             model=self.model_name, voice=self.voice, response_format="wav", input=text
         ) as response:

astrbot/core/provider/sources/sensevoice_selfhosted_source.py

@@ -11,7 +11,7 @@ import re
 from funasr_onnx import SenseVoiceSmall
 from funasr_onnx.utils.postprocess_utils import rich_transcription_postprocess
 from ..provider import STTProvider
-from ..entites import ProviderType
+from ..entities import ProviderType
 from astrbot.core.utils.io import download_file
 from ..register import register_provider_adapter
 from astrbot.core import logger

astrbot/core/provider/sources/volcengine_tts.py

@@ -0,0 +1,107 @@
+import uuid
+import base64
+import json
+import os
+import traceback
+import asyncio
+import aiohttp
+import requests
+from ..provider import TTSProvider
+from ..entities import ProviderType
+from ..register import register_provider_adapter
+from astrbot import logger
+
+@register_provider_adapter(
+    "volcengine_tts", "火山引擎 TTS", provider_type=ProviderType.TEXT_TO_SPEECH
+)
+class ProviderVolcengineTTS(TTSProvider):
+    def __init__(self, provider_config: dict, provider_settings: dict) -> None:
+        super().__init__(provider_config, provider_settings)
+        self.api_key = provider_config.get("api_key", "")
+        self.appid = provider_config.get("appid", "")
+        self.cluster = provider_config.get("volcengine_cluster", "")
+        self.voice_type = provider_config.get("volcengine_voice_type", "")
+        self.speed_ratio = provider_config.get("volcengine_speed_ratio", 1.0)
+        self.api_base = provider_config.get("api_base", f"https://openspeech.bytedance.com/api/v1/tts")
+        self.timeout = provider_config.get("timeout", 20)
+
+    def _build_request_payload(self, text: str) -> dict:
+        return {
+            "app": {
+                "appid": self.appid,
+                "token": self.api_key,
+                "cluster": self.cluster
+            },
+            "user": {
+                "uid": str(uuid.uuid4())  
+            },
+            "audio": {
+                "voice_type": self.voice_type,
+                "encoding": "mp3",
+                "speed_ratio": self.speed_ratio,
+                "volume_ratio": 1.0,
+                "pitch_ratio": 1.0,
+            },
+            "request": {
+                "reqid": str(uuid.uuid4()),
+                "text": text,
+                "text_type": "plain",
+                "operation": "query",
+                "with_frontend": 1,
+                "frontend_type": "unitTson"
+            }
+        }
+
+    async def get_audio(self, text: str) -> str:
+        """异步方法获取语音文件路径"""
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer; {self.api_key}"
+        }
+        
+        payload = self._build_request_payload(text)
+        
+        logger.debug(f"请求头: {headers}")
+        logger.debug(f"请求 URL: {self.api_base}")
+        logger.debug(f"请求体: {json.dumps(payload, ensure_ascii=False)[:100]}...")
+        
+        try:
+            async with aiohttp.ClientSession() as session:
+                async with session.post(
+                    self.api_base,
+                    data=json.dumps(payload), 
+                    headers=headers,
+                    timeout=self.timeout
+                ) as response:
+                    logger.debug(f"响应状态码: {response.status}")
+                    
+                    response_text = await response.text()
+                    logger.debug(f"响应内容: {response_text[:200]}...")
+                    
+                    if response.status == 200:
+                        resp_data = json.loads(response_text)
+                        
+                        if "data" in resp_data:
+                            audio_data = base64.b64decode(resp_data["data"])
+                            
+                            os.makedirs("data/temp", exist_ok=True)
+                            
+                            file_path = f"data/temp/volcengine_tts_{uuid.uuid4()}.mp3"
+                            
+                            loop = asyncio.get_running_loop()
+                            await loop.run_in_executor(
+                                None, 
+                                lambda: open(file_path, "wb").write(audio_data)
+                            )
+                            
+                            return file_path
+                        else:
+                            error_msg = resp_data.get("message", "未知错误")
+                            raise Exception(f"火山引擎 TTS API 返回错误: {error_msg}")
+                    else:
+                        raise Exception(f"火山引擎 TTS API 请求失败: {response.status}, {response_text}")
+        
+        except Exception as e:
+            error_details = traceback.format_exc()
+            logger.debug(f"火山引擎 TTS 异常详情: {error_details}")
+            raise Exception(f"火山引擎 TTS 异常: {str(e)}")

astrbot/core/provider/sources/whisper_api_source.py

@@ -2,11 +2,12 @@ import uuid
 import os
 from openai import AsyncOpenAI, NOT_GIVEN
 from ..provider import STTProvider
-from ..entites import ProviderType
+from ..entities import ProviderType
 from astrbot.core.utils.io import download_file
 from ..register import register_provider_adapter
 from astrbot.core import logger
 from astrbot.core.utils.tencent_record_helper import tencent_silk_to_wav
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 
 @register_provider_adapter(
@@ -50,7 +51,8 @@ class ProviderOpenAIWhisperAPI(STTProvider):
                 is_tencent = True
 
             name = str(uuid.uuid4())
-            path = os.path.join("data/temp", name)
+            temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+            path = os.path.join(temp_dir, name)
             await download_file(audio_url, path)
             audio_url = path
 
@@ -61,7 +63,8 @@ class ProviderOpenAIWhisperAPI(STTProvider):
             is_silk = await self._is_silk_file(audio_url)
             if is_silk:
                 logger.info("Converting silk file to wav ...")
-                output_path = os.path.join("data/temp", str(uuid.uuid4()) + ".wav")
+                temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+                output_path = os.path.join(temp_dir, str(uuid.uuid4()) + ".wav")
                 await tencent_silk_to_wav(audio_url, output_path)
                 audio_url = output_path
 

astrbot/core/provider/sources/whisper_selfhosted_source.py

@@ -3,11 +3,12 @@ import os
 import asyncio
 import whisper
 from ..provider import STTProvider
-from ..entites import ProviderType
+from ..entities import ProviderType
 from astrbot.core.utils.io import download_file
 from ..register import register_provider_adapter
 from astrbot.core import logger
 from astrbot.core.utils.tencent_record_helper import tencent_silk_to_wav
+from astrbot.core.utils.astrbot_path import get_astrbot_data_path
 
 
 @register_provider_adapter(
@@ -53,7 +54,8 @@ class ProviderOpenAIWhisperSelfHost(STTProvider):
                 is_tencent = True
 
             name = str(uuid.uuid4())
-            path = os.path.join("data/temp", name)
+            temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+            path = os.path.join(temp_dir, name)
             await download_file(audio_url, path)
             audio_url = path
 
@@ -64,7 +66,8 @@ class ProviderOpenAIWhisperSelfHost(STTProvider):
             is_silk = await self._is_silk_file(audio_url)
             if is_silk:
                 logger.info("Converting silk file to wav ...")
-                output_path = os.path.join("data/temp", str(uuid.uuid4()) + ".wav")
+                temp_dir = os.path.join(get_astrbot_data_path(), "temp")
+                output_path = os.path.join(temp_dir, str(uuid.uuid4()) + ".wav")
                 await tencent_silk_to_wav(audio_url, output_path)
                 audio_url = output_path
 

astrbot/core/provider/sources/zhipu_source.py

@@ -3,7 +3,7 @@ from astrbot import logger
 from astrbot.core.provider.func_tool_manager import FuncCall
 from typing import List
 from ..register import register_provider_adapter
-from astrbot.core.provider.entites import LLMResponse
+from astrbot.core.provider.entities import LLMResponse
 from .openai_source import ProviderOpenAIOfficial