feat: Add support for notification and request events, and enhance the event handling capabilities.

.pre-commit-config.yaml

@@ -9,14 +9,16 @@ repos:
       # Run the formatter of backend.
       - id: ruff-format
 
-  - repo: local
+  - repo: https://github.com/pre-commit/mirrors-prettier
+    rev: v3.1.0
     hooks:
       - id: prettier
-        name: prettier
-        entry: npx --prefix web prettier --write --ignore-unknown
-        language: system
         types_or: [javascript, jsx, ts, tsx, css, scss]
+        additional_dependencies:
+          - prettier@3.1.0
 
+  - repo: local
+    hooks:
       - id: lint-staged
         name: lint-staged
         entry: cd web && pnpm lint-staged

README.md

@@ -19,10 +19,9 @@ English / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本
 [![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 
 <a href="https://langbot.app">Website</a> ｜
-<a href="https://docs.langbot.app/en/insight/features">Features</a> ｜
-<a href="https://docs.langbot.app/en/insight/guide">Docs</a> ｜
-<a href="https://docs.langbot.app/en/tags/readme">API</a> ｜
-<a href="https://space.langbot.app/cloud">Cloud</a> ｜
+<a href="https://docs.langbot.app/en/insight/features.html">Features</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide.html">Docs</a> ｜
+<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
 <a href="https://space.langbot.app">Plugin Market</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">Roadmap</a>
 
@@ -45,16 +44,12 @@ LangBot is an **open-source, production-grade platform** for building AI-powered
 - **Web Management Panel** — Configure, manage, and monitor your bots through an intuitive browser interface. No YAML editing required.
 - **Multi-Pipeline Architecture** — Different bots for different scenarios, with comprehensive monitoring and exception handling.
 
-[→ Learn more about all features](https://docs.langbot.app/en/insight/features)
+[→ Learn more about all features](https://docs.langbot.app/en/insight/features.html)
 
 ---
 
 ## Quick Start
 
-### ☁️ LangBot Cloud (Recommended)
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — Zero deployment, ready to use.
-
 ### One-Line Launch
 
 ```bash
@@ -76,7 +71,7 @@ docker compose up -d
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**More options:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker) · [Manual](https://docs.langbot.app/en/deploy/langbot/manual) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt) · [Kubernetes](./docker/README_K8S.md)
+**More options:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Manual](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
 
 ---
 
@@ -124,7 +119,7 @@ docker compose up -d
 | [接口 AI](https://jiekou.ai/) | Gateway | ✅ |
 | [302.AI](https://share.302.ai/SuTG99) | Gateway | ✅ |
 
-[→ View all integrations](https://docs.langbot.app/en/insight/features)
+[→ View all integrations](https://docs.langbot.app/en/insight/features.html)
 
 ---
 

README_CN.md

@@ -24,7 +24,6 @@
 <a href="https://docs.langbot.app/zh/insight/features.html">特性</a> ｜
 <a href="https://docs.langbot.app/zh/insight/guide.html">文档</a> ｜
 <a href="https://docs.langbot.app/zh/tags/readme.html">API</a> ｜
-<a href="https://space.langbot.app/cloud">Cloud</a> ｜
 <a href="https://space.langbot.app">插件市场</a> ｜
 <a href="https://langbot.featurebase.app/roadmap">路线图</a>
 
@@ -34,6 +33,8 @@
 
 ---
 
+## 什么是 LangBot？
+
 LangBot 是一个**开源的生产级平台**，用于构建 AI 驱动的即时通信机器人。它将大语言模型（LLM）连接到各种聊天平台，帮助你创建能够对话、执行任务、并集成到现有工作流程中的智能 Agent。
 
 ### 核心能力
@@ -41,7 +42,7 @@ LangBot 是一个**开源的生产级平台**，用于构建 AI 驱动的即时
 - **AI 对话与 Agent** — 多轮对话、工具调用、多模态、流式输出。自带 RAG（知识库），深度集成 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) 等 LLMOps 平台。
 - **全平台支持** — 一套代码，覆盖 QQ、微信、企业微信、飞书、钉钉、Discord、Telegram、Slack、LINE、KOOK 等平台。
 - **生产就绪** — 访问控制、限速、敏感词过滤、全面监控与异常处理，已被多家企业采用。
-- **插件生态** — 数百个插件，跨进程的事件驱动架构，组件扩展，适配 [MCP 协议](https://modelcontextprotocol.io/)。
+- **插件生态** — 数百个插件，事件驱动架构，组件扩展，适配 [MCP 协议](https://modelcontextprotocol.io/)。
 - **Web 管理面板** — 通过浏览器直观地配置、管理和监控机器人，无需手动编辑配置文件。
 - **多流水线架构** — 不同机器人用于不同场景，具备全面的监控和异常处理能力。
 
@@ -51,10 +52,6 @@ LangBot 是一个**开源的生产级平台**，用于构建 AI 驱动的即时
 
 ## 快速开始
 
-### ☁️ LangBot Cloud（推荐）
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — 免部署，开箱即用。
-
 ### 一键启动
 
 ```bash

README_ES.md

@@ -50,10 +50,6 @@ LangBot es una **plataforma de código abierto y grado de producción** para con
 
 ## Inicio Rápido
 
-### ☁️ LangBot Cloud (Recomendado)
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — Sin despliegue, listo para usar.
-
 ### Lanzamiento en una línea
 
 ```bash

README_FR.md

@@ -50,10 +50,6 @@ LangBot est une **plateforme open-source de niveau production** pour créer des
 
 ## Démarrage Rapide
 
-### ☁️ LangBot Cloud (Recommandé)
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — Sans déploiement, prêt à utiliser.
-
 ### Lancement en une ligne
 
 ```bash

README_JP.md

@@ -50,10 +50,6 @@ LangBot は、AI搭載のインスタントメッセージングボットを構
 
 ## クイックスタート
 
-### ☁️ LangBot Cloud（推奨）
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — デプロイ不要、すぐに使えます。
-
 ### ワンライン起動
 
 ```bash

README_KO.md

@@ -50,10 +50,6 @@ LangBot은 AI 기반 인스턴트 메시징 봇을 구축하기 위한 **오픈
 
 ## 빠른 시작
 
-### ☁️ LangBot Cloud (추천)
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — 배포 없이 바로 사용.
-
 ### 원라인 실행
 
 ```bash

README_RU.md

@@ -50,10 +50,6 @@ LangBot — это **платформа с открытым исходным к
 
 ## Быстрый старт
 
-### ☁️ LangBot Cloud (Рекомендуется)
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — Без развёртывания, готово к использованию.
-
 ### Запуск одной командой
 
 ```bash

README_TW.md

@@ -52,10 +52,6 @@ LangBot 是一個**開源的生產級平台**，用於建構 AI 驅動的即時
 
 ## 快速開始
 
-### ☁️ LangBot Cloud（推薦）
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — 免部署，開箱即用。
-
 ### 一鍵啟動
 
 ```bash

README_VI.md

@@ -50,10 +50,6 @@ LangBot là một **nền tảng mã nguồn mở, cấp sản xuất** để x
 
 ## Bắt đầu nhanh
 
-### ☁️ LangBot Cloud (Khuyên dùng)
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — Không cần triển khai, sẵn sàng sử dụng.
-
 ### Khởi chạy một dòng
 
 ```bash

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "langbot"
-version = "4.9.4"
+version = "4.8.4"
 description = "Production-grade platform for building agentic IM bots"
 readme = "README.md"
 license-files = ["LICENSE"]
@@ -61,17 +61,16 @@ dependencies = [
     "html2text>=2024.2.26",
     "langchain>=0.2.0",
     "langchain-text-splitters>=0.0.1",
-    "chromadb>=1.0.0,<2.0.0",
+    "chromadb>=0.4.24",
     "qdrant-client (>=1.15.1,<2.0.0)",
-    "pyseekdb==1.1.0.post3",
-    "langbot-plugin==0.3.5",
+    "pyseekdb==1.0.0b7",
+    "langbot-plugin==0.2.6",
     "asyncpg>=0.30.0",
     "line-bot-sdk>=3.19.0",
     "tboxsdk>=0.0.10",
     "boto3>=1.35.0",
     "pymilvus>=2.6.4",
     "pgvector>=0.4.1",
-    "botocore>=1.42.39",
 ]
 keywords = [
     "bot",

src/langbot/__init__.py

@@ -1,3 +1,3 @@
 """LangBot - Production-grade platform for building agentic IM bots"""
 
-__version__ = '4.9.4'
+__version__ = '4.8.4'

src/langbot/libs/dingtalk_api/api.py

@@ -272,30 +272,15 @@ class DingTalkClient:
 
                 message_data['Type'] = 'audio'
             elif incoming_message.message_type == 'file':
-                # 获取原始数据字典并提取嵌套的文件信息
-                raw_data = incoming_message.to_dict()
-                file_info = raw_data.get('content', {})
-
-                # 兼容处理：如果 content 仍为 JSON 字符串则进行解析
-                if isinstance(file_info, str):
-                    try:
-                        file_info = json.loads(file_info)
-                    except (json.JSONDecodeError, TypeError):
-                        file_info = {}
-
-                download_code = file_info.get('downloadCode')
-                file_name = file_info.get('fileName')
-
-                if download_code and file_name:
-                    # 转换 downloadCode 为可下载的真实 URL
-                    message_data['File'] = await self.get_file_url(download_code)
-                    message_data['Name'] = file_name
+                down_list = incoming_message.get_down_list()
+                if len(down_list) >= 2:
+                    message_data['File'] = await self.get_file_url(down_list[0])
+                    message_data['Name'] = down_list[1]
                 else:
                     if self.logger:
-                        await self.logger.error(f'Failed to extract file info from message content: {file_info}')
+                        await self.logger.error(f'get_down_list() returned fewer than 2 elements: {down_list}')
                     message_data['File'] = None
                     message_data['Name'] = None
-
                 message_data['Type'] = 'file'
 
             copy_message_data = message_data.copy()

src/langbot/libs/openclaw_weixin_api/__init__.py

@@ -1,3 +0,0 @@
-from .client import OpenClawWeixinClient as OpenClawWeixinClient
-from .types import ApiError as ApiError
-from .types import LoginResult as LoginResult

src/langbot/libs/openclaw_weixin_api/client.py

@@ -1,807 +0,0 @@
-"""Async HTTP client for the OpenClaw WeChat API.
-
-Implements the iLink Bot API protocol.
-Reference: https://github.com/epiral/weixin-bot
-
-Endpoints: getUpdates (long-poll), sendMessage, getUploadUrl, getConfig, sendTyping.
-"""
-
-from __future__ import annotations
-
-import asyncio
-import base64
-import io
-import logging
-import os
-import struct
-import typing
-import uuid
-from typing import Optional
-from urllib.parse import quote
-
-import aiohttp
-
-from .types import (
-    ApiError,
-    CDNMedia,
-    FileItem,
-    GetConfigResponse,
-    GetUpdatesResponse,
-    GetUploadUrlResponse,
-    ImageItem,
-    LoginResult,
-    MessageItem,
-    QRCodeResponse,
-    QRStatusResponse,
-    RefMessage,
-    TextItem,
-    VideoItem,
-    VoiceItem,
-    WeixinMessage,
-)
-
-logger = logging.getLogger('openclaw-weixin-sdk')
-
-DEFAULT_BASE_URL = 'https://ilinkai.weixin.qq.com'
-CDN_BASE_URL = 'https://novac2c.cdn.weixin.qq.com/c2c'
-
-CHANNEL_VERSION = '1.0.0'
-
-DEFAULT_API_TIMEOUT = 15
-DEFAULT_LONG_POLL_TIMEOUT = 40
-DEFAULT_CONFIG_TIMEOUT = 10
-DEFAULT_QR_POLL_TIMEOUT = 35
-
-SESSION_EXPIRED_ERRCODE = -14
-
-DEFAULT_BOT_TYPE = '3'
-
-# Maximum text length per message chunk (WeChat limit)
-MAX_TEXT_CHUNK_SIZE = 2000
-
-
-def _random_wechat_uin() -> str:
-    """Generate the X-WECHAT-UIN header: random uint32 -> decimal string -> base64."""
-    rand_bytes = os.urandom(4)
-    uint32_val = struct.unpack('>I', rand_bytes)[0]
-    return base64.b64encode(str(uint32_val).encode('utf-8')).decode('utf-8')
-
-
-def _build_base_info() -> dict:
-    """Build the base_info payload included in every API request."""
-    return {'channel_version': CHANNEL_VERSION}
-
-
-def _chunk_text(text: str, max_size: int = MAX_TEXT_CHUNK_SIZE) -> list[str]:
-    """Split long text into chunks that fit within WeChat's message size limit."""
-    if len(text) <= max_size:
-        return [text]
-    chunks = []
-    while text:
-        chunks.append(text[:max_size])
-        text = text[max_size:]
-    return chunks
-
-
-class OpenClawWeixinClient:
-    """Async client for the OpenClaw WeChat HTTP JSON API."""
-
-    def __init__(self, base_url: str, token: str):
-        self.base_url = base_url.rstrip('/')
-        self.token = token
-        self._session: Optional[aiohttp.ClientSession] = None
-
-    async def _get_session(self) -> aiohttp.ClientSession:
-        if self._session is None or self._session.closed:
-            self._session = aiohttp.ClientSession()
-        return self._session
-
-    async def close(self):
-        if self._session and not self._session.closed:
-            await self._session.close()
-
-    def _build_headers(self) -> dict[str, str]:
-        headers = {
-            'Content-Type': 'application/json',
-            'AuthorizationType': 'ilink_bot_token',
-            'X-WECHAT-UIN': _random_wechat_uin(),
-        }
-        if self.token:
-            headers['Authorization'] = f'Bearer {self.token}'
-        return headers
-
-    async def _post(self, endpoint: str, payload: dict, timeout: float = DEFAULT_API_TIMEOUT) -> dict:
-        """Make a POST request and return the JSON response.
-
-        Raises ApiError on HTTP errors or when the response contains a non-zero errcode.
-        """
-        payload['base_info'] = _build_base_info()
-
-        session = await self._get_session()
-        url = f'{self.base_url}/{endpoint}'
-        headers = self._build_headers()
-
-        async with session.post(
-            url, json=payload, headers=headers, timeout=aiohttp.ClientTimeout(total=timeout)
-        ) as resp:
-            if resp.status != 200:
-                text = await resp.text()
-                raise ApiError(
-                    f'OpenClaw API error {resp.status}: {text}',
-                    status=resp.status,
-                )
-            data = await resp.json(content_type=None)
-
-        # Check for application-level errors in the response body
-        errcode = data.get('errcode') or data.get('ret')
-        if errcode and errcode != 0:
-            raise ApiError(
-                data.get('errmsg') or f'API errcode {errcode}',
-                status=200,
-                code=errcode,
-                payload=data,
-            )
-
-        return data
-
-    async def get_updates(
-        self, get_updates_buf: str = '', timeout: float = DEFAULT_LONG_POLL_TIMEOUT
-    ) -> GetUpdatesResponse:
-        """Long-poll for new messages.
-
-        Note: This method does NOT raise ApiError for errcode responses —
-        it returns them in the GetUpdatesResponse so the caller can handle
-        session expiry and other errors with full context.
-        """
-        try:
-            # Bypass the errcode check in _post since get_updates needs
-            # to return error info (e.g. session expired) to the caller.
-            payload: dict = {'get_updates_buf': get_updates_buf}
-            payload['base_info'] = _build_base_info()
-
-            session = await self._get_session()
-            url = f'{self.base_url}/ilink/bot/getupdates'
-            headers = self._build_headers()
-
-            async with session.post(
-                url,
-                json=payload,
-                headers=headers,
-                timeout=aiohttp.ClientTimeout(total=timeout),
-            ) as resp:
-                if resp.status != 200:
-                    text = await resp.text()
-                    raise ApiError(
-                        f'OpenClaw API error {resp.status}: {text}',
-                        status=resp.status,
-                    )
-                data = await resp.json(content_type=None)
-
-        except (asyncio.TimeoutError, aiohttp.ServerTimeoutError):
-            return GetUpdatesResponse(ret=0, msgs=[], get_updates_buf=get_updates_buf)
-        except ApiError:
-            raise
-        except Exception as e:
-            if 'timeout' in str(e).lower():
-                return GetUpdatesResponse(ret=0, msgs=[], get_updates_buf=get_updates_buf)
-            raise
-
-        return _parse_get_updates_response(data)
-
-    async def send_message(
-        self,
-        to_user_id: str,
-        item_list: list[MessageItem],
-        context_token: str = '',
-    ) -> None:
-        """Send a message to a user."""
-        items_payload = [_message_item_to_dict(item) for item in item_list]
-
-        payload = {
-            'msg': {
-                'from_user_id': '',
-                'to_user_id': to_user_id,
-                'client_id': f'langbot-{uuid.uuid4().hex[:16]}',
-                'message_type': WeixinMessage.TYPE_BOT,
-                'message_state': WeixinMessage.STATE_FINISH,
-                'item_list': items_payload,
-                'context_token': context_token or None,
-            }
-        }
-        await self._post('ilink/bot/sendmessage', payload)
-
-    async def send_text(self, to_user_id: str, text: str, context_token: str = '') -> None:
-        """Send a plain text message, automatically chunking if too long."""
-        chunks = _chunk_text(text)
-        for chunk in chunks:
-            item = MessageItem(type=MessageItem.TEXT, text_item=TextItem(text=chunk))
-            await self.send_message(to_user_id, [item], context_token)
-
-    async def get_config(self, ilink_user_id: str, context_token: str = '') -> GetConfigResponse:
-        """Get bot config including typing_ticket."""
-        data = await self._post(
-            'ilink/bot/getconfig',
-            {'ilink_user_id': ilink_user_id, 'context_token': context_token or None},
-            timeout=DEFAULT_CONFIG_TIMEOUT,
-        )
-        return GetConfigResponse(
-            ret=data.get('ret'),
-            errmsg=data.get('errmsg'),
-            typing_ticket=data.get('typing_ticket'),
-        )
-
-    async def send_typing(self, ilink_user_id: str, typing_ticket: str, status: int = 1) -> None:
-        """Send typing indicator. status: 1=typing, 2=cancel."""
-        await self._post(
-            'ilink/bot/sendtyping',
-            {
-                'ilink_user_id': ilink_user_id,
-                'typing_ticket': typing_ticket,
-                'status': status,
-            },
-            timeout=DEFAULT_CONFIG_TIMEOUT,
-        )
-
-    async def stop_typing(self, ilink_user_id: str, typing_ticket: str) -> None:
-        """Cancel the typing indicator for a user."""
-        await self.send_typing(ilink_user_id, typing_ticket, status=2)
-
-    async def download_media(
-        self,
-        media: CDNMedia,
-    ) -> bytes:
-        """Download and decrypt a file from the WeChat CDN.
-
-        Args:
-            media: CDNMedia object with encrypt_query_param and aes_key.
-
-        Returns:
-            Decrypted file bytes.
-        """
-        from cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes
-        from cryptography.hazmat.primitives.padding import PKCS7
-
-        if not media.encrypt_query_param:
-            raise ApiError('CDN media has no encrypt_query_param', status=0)
-        if not media.aes_key:
-            raise ApiError('CDN media has no aes_key', status=0)
-
-        # Derive 16-byte AES key
-        # aes_key is base64-encoded; the decoded content may be:
-        #   - raw 16 bytes (direct AES key)
-        #   - 32-char hex string (decode hex to get 16 bytes)
-        raw = base64.b64decode(media.aes_key)
-        if len(raw) == 16:
-            aes_key = raw
-        elif len(raw) == 32:
-            # Hex-encoded 16-byte key
-            aes_key = bytes.fromhex(raw.decode('utf-8'))
-        else:
-            raise ApiError(f'Invalid AES key length: {len(raw)} (expected 16 or 32)', status=0)
-
-        # Download encrypted bytes from CDN
-        session = await self._get_session()
-        cdn_url = f'{CDN_BASE_URL}/download?encrypted_query_param={quote(media.encrypt_query_param, safe="")}'
-
-        async with session.get(cdn_url, timeout=aiohttp.ClientTimeout(total=120)) as resp:
-            if resp.status != 200:
-                text = await resp.text()
-                raise ApiError(f'CDN download failed: {resp.status} {text}', status=resp.status)
-            encrypted = await resp.read()
-
-        # Decrypt AES-128-ECB with PKCS7 padding
-        cipher = Cipher(algorithms.AES(aes_key), modes.ECB())
-        decryptor = cipher.decryptor()
-        padded = decryptor.update(encrypted) + decryptor.finalize()
-
-        unpadder = PKCS7(128).unpadder()
-        return unpadder.update(padded) + unpadder.finalize()
-
-    async def upload_media(
-        self,
-        file_bytes: bytes,
-        to_user_id: str,
-        media_type: int,
-    ) -> CDNMedia:
-        """Encrypt and upload media to WeChat CDN.
-
-        Args:
-            file_bytes: Raw file bytes to upload.
-            to_user_id: Recipient user ID.
-            media_type: 1=IMAGE, 2=VIDEO, 3=FILE, 4=VOICE.
-
-        Returns:
-            CDNMedia with encrypt_query_param and aes_key for use in sendMessage.
-        """
-        import hashlib
-
-        from cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes
-        from cryptography.hazmat.primitives.padding import PKCS7
-
-        # 1. Generate random 16-byte AES key
-        raw_key = os.urandom(16)
-        aes_key_hex = raw_key.hex()  # 32-char hex string
-
-        # 2. Encode key for CDNMedia: base64(hex_string) — same for all media types
-        # Matches official SDK: Buffer.from(aeskey_hex).toString("base64")
-        encoded_key = base64.b64encode(aes_key_hex.encode('utf-8')).decode('utf-8')
-
-        # 3. Encrypt file with AES-128-ECB + PKCS7
-        padder = PKCS7(128).padder()
-        padded = padder.update(file_bytes) + padder.finalize()
-        cipher = Cipher(algorithms.AES(raw_key), modes.ECB())
-        encryptor = cipher.encryptor()
-        encrypted = encryptor.update(padded) + encryptor.finalize()
-
-        # 4. Get upload URL
-        raw_md5 = hashlib.md5(file_bytes).hexdigest()
-        filekey = os.urandom(16).hex()  # 32-char hex, matches official SDK
-
-        upload_resp = await self.get_upload_url(
-            filekey=filekey,
-            media_type=media_type,
-            to_user_id=to_user_id,
-            rawsize=len(file_bytes),
-            rawfilemd5=raw_md5,
-            filesize=len(encrypted),
-            aeskey=aes_key_hex,  # hex string, as expected by the API
-        )
-
-        if not upload_resp.upload_param:
-            raise ApiError('Failed to get upload URL', status=0)
-
-        # 5. Upload to CDN
-        # upload_param is an opaque token from the server — pass it as-is
-        session = await self._get_session()
-        cdn_url = f'{CDN_BASE_URL}/upload?encrypted_query_param={quote(upload_resp.upload_param, safe="")}&filekey={quote(filekey, safe="")}'
-        logger.debug(
-            'CDN upload: url=%s raw_size=%d encrypted_size=%d md5=%s aeskey=%s',
-            cdn_url,
-            len(file_bytes),
-            len(encrypted),
-            raw_md5,
-            encoded_key,
-        )
-
-        async with session.post(
-            cdn_url,
-            data=encrypted,
-            headers={'Content-Type': 'application/octet-stream'},
-            timeout=aiohttp.ClientTimeout(total=120),
-        ) as resp:
-            if resp.status != 200:
-                text = await resp.text()
-                logger.error('CDN upload failed: status=%d url=%s body=%s', resp.status, cdn_url, text[:500])
-                raise ApiError(f'CDN upload failed: {resp.status} {text}', status=resp.status)
-            download_param = resp.headers.get('x-encrypted-param', '')
-
-        if not download_param:
-            raise ApiError('CDN upload succeeded but no x-encrypted-param returned', status=0)
-
-        return CDNMedia(
-            encrypt_query_param=download_param,
-            aes_key=encoded_key,
-            encrypt_type=1,
-        )
-
-    async def send_image(
-        self,
-        to_user_id: str,
-        image_bytes: bytes,
-        context_token: str = '',
-    ) -> None:
-        """Upload an image to CDN and send it."""
-        media = await self.upload_media(image_bytes, to_user_id, media_type=1)
-        item = MessageItem(
-            type=MessageItem.IMAGE,
-            image_item=ImageItem(
-                media=media,
-                aeskey=media.aes_key,
-            ),
-        )
-        await self.send_message(to_user_id, [item], context_token)
-
-    async def send_file(
-        self,
-        to_user_id: str,
-        file_bytes: bytes,
-        file_name: str,
-        context_token: str = '',
-    ) -> None:
-        """Upload a file to CDN and send it."""
-        import hashlib
-
-        media = await self.upload_media(file_bytes, to_user_id, media_type=3)
-        item = MessageItem(
-            type=MessageItem.FILE,
-            file_item=FileItem(
-                media=media,
-                file_name=file_name,
-                md5=hashlib.md5(file_bytes).hexdigest(),
-                len=str(len(file_bytes)),
-            ),
-        )
-        await self.send_message(to_user_id, [item], context_token)
-
-    async def send_voice(
-        self,
-        to_user_id: str,
-        voice_bytes: bytes,
-        playtime: int = 0,
-        context_token: str = '',
-    ) -> None:
-        """Upload a voice message to CDN and send it."""
-        media = await self.upload_media(voice_bytes, to_user_id, media_type=4)
-        item = MessageItem(
-            type=MessageItem.VOICE,
-            voice_item=VoiceItem(
-                media=media,
-                playtime=playtime,
-            ),
-        )
-        await self.send_message(to_user_id, [item], context_token)
-
-    async def get_upload_url(
-        self,
-        filekey: str,
-        media_type: int,
-        to_user_id: str,
-        rawsize: int,
-        rawfilemd5: str,
-        filesize: int,
-        thumb_rawsize: Optional[int] = None,
-        thumb_rawfilemd5: Optional[str] = None,
-        thumb_filesize: Optional[int] = None,
-        aeskey: Optional[str] = None,
-    ) -> GetUploadUrlResponse:
-        """Get a pre-signed CDN upload URL."""
-        payload: dict = {
-            'filekey': filekey,
-            'media_type': media_type,
-            'to_user_id': to_user_id,
-            'rawsize': rawsize,
-            'rawfilemd5': rawfilemd5,
-            'filesize': filesize,
-            'no_need_thumb': True,
-        }
-        if thumb_rawsize is not None:
-            payload['thumb_rawsize'] = thumb_rawsize
-        if thumb_rawfilemd5 is not None:
-            payload['thumb_rawfilemd5'] = thumb_rawfilemd5
-        if thumb_filesize is not None:
-            payload['thumb_filesize'] = thumb_filesize
-        if aeskey is not None:
-            payload['aeskey'] = aeskey
-
-        data = await self._post('ilink/bot/getuploadurl', payload)
-        logger.debug('get_upload_url response: %s', data)
-        return GetUploadUrlResponse(
-            upload_param=data.get('upload_param'),
-            thumb_upload_param=data.get('thumb_upload_param'),
-        )
-
-    # -----------------------------------------------------------------------
-    # QR Code Login
-    # -----------------------------------------------------------------------
-
-    async def fetch_qrcode(self, bot_type: str = DEFAULT_BOT_TYPE) -> QRCodeResponse:
-        """Fetch a QR code for WeChat login authorization (GET, no auth needed)."""
-        session = await self._get_session()
-        url = f'{self.base_url}/ilink/bot/get_bot_qrcode?bot_type={bot_type}'
-
-        async with session.get(url, timeout=aiohttp.ClientTimeout(total=DEFAULT_API_TIMEOUT)) as resp:
-            if resp.status != 200:
-                text = await resp.text()
-                raise ApiError(
-                    f'Failed to fetch QR code: {resp.status} {text}',
-                    status=resp.status,
-                )
-            data = await resp.json(content_type=None)
-
-        logger.debug(
-            'fetch_qrcode response: qrcode=%s, img=%s', data.get('qrcode'), bool(data.get('qrcode_img_content'))
-        )
-
-        return QRCodeResponse(
-            qrcode=data.get('qrcode'),
-            qrcode_img_content=data.get('qrcode_img_content'),
-        )
-
-    async def _fetch_qr_image_base64(self, url: str) -> str:
-        """Generate a QR code image from the URL and return a data URI string.
-
-        The qrcode_img_content URL points to an HTML page (not a raw image),
-        so we generate the QR code locally using the qrcode library.
-        """
-        import qrcode
-
-        qr = qrcode.QRCode(error_correction=qrcode.constants.ERROR_CORRECT_L)
-        qr.add_data(url)
-        qr.make(fit=True)
-        img = qr.make_image(fill_color='black', back_color='white')
-
-        buf = io.BytesIO()
-        img.save(buf, format='PNG')
-        b64 = base64.b64encode(buf.getvalue()).decode('utf-8')
-        return f'data:image/png;base64,{b64}'
-
-    async def poll_qrcode_status(self, qrcode: str) -> QRStatusResponse:
-        """Long-poll the QR code scan status (GET with iLink-App-ClientVersion header)."""
-        session = await self._get_session()
-        url = f'{self.base_url}/ilink/bot/get_qrcode_status?qrcode={quote(qrcode, safe="")}'
-        headers = {'iLink-App-ClientVersion': '1'}
-
-        try:
-            async with session.get(
-                url, headers=headers, timeout=aiohttp.ClientTimeout(total=DEFAULT_QR_POLL_TIMEOUT)
-            ) as resp:
-                if resp.status != 200:
-                    text = await resp.text()
-                    raise ApiError(
-                        f'Failed to poll QR status: {resp.status} {text}',
-                        status=resp.status,
-                    )
-                data = await resp.json(content_type=None)
-                logger.debug('QR status poll response: %s', data)
-        except (asyncio.TimeoutError, aiohttp.ServerTimeoutError):
-            return QRStatusResponse(status='wait')
-
-        return QRStatusResponse(
-            status=data.get('status'),
-            bot_token=data.get('bot_token'),
-            ilink_bot_id=data.get('ilink_bot_id'),
-            baseurl=data.get('baseurl'),
-            ilink_user_id=data.get('ilink_user_id'),
-        )
-
-    async def login(
-        self,
-        max_retries: int = 5,
-        poll_timeout_ms: int = 480_000,
-        on_qrcode: Optional[typing.Callable[[str, str], typing.Any]] = None,
-        on_status: Optional[typing.Callable[[str], typing.Any]] = None,
-    ) -> LoginResult:
-        """Complete QR code login flow with auto-retry on expiry.
-
-        Args:
-            max_retries: Max number of QR code refreshes on expiry.
-            poll_timeout_ms: Timeout per QR code in milliseconds.
-            on_qrcode: Callback(qr_image_base64, qr_url) called each time a
-                        new QR code is fetched. Use this to display the QR code.
-            on_status: Callback(status_str) called on each status poll change.
-
-        Returns:
-            LoginResult with token, base_url, and account_id.
-
-        Raises:
-            ApiError: On unrecoverable API errors.
-            Exception: If all retries are exhausted.
-        """
-        last_qr_base64: Optional[str] = None
-
-        for attempt in range(max_retries):
-            qr_resp = await self.fetch_qrcode()
-            if not qr_resp.qrcode or not qr_resp.qrcode_img_content:
-                raise ApiError('Failed to get QR code from server', status=0)
-
-            # Convert QR image to base64 and notify caller
-            last_qr_base64 = await self._fetch_qr_image_base64(qr_resp.qrcode_img_content)
-            if on_qrcode:
-                try:
-                    result = on_qrcode(last_qr_base64, qr_resp.qrcode_img_content)
-                    if asyncio.iscoroutine(result) or asyncio.isfuture(result):
-                        await result
-                except Exception as e:
-                    logger.warning('on_qrcode callback error: %s', e)
-
-            # Poll until confirmed / expired / timeout
-            loop = asyncio.get_running_loop()
-            deadline = loop.time() + poll_timeout_ms / 1000.0
-
-            while loop.time() < deadline:
-                try:
-                    status_resp = await self.poll_qrcode_status(qr_resp.qrcode)
-                except Exception as e:
-                    logger.error('Error polling QR status: %s', e)
-                    await asyncio.sleep(2)
-                    continue
-
-                if on_status:
-                    try:
-                        cb_result = on_status(status_resp.status or 'unknown')
-                        if asyncio.iscoroutine(cb_result) or asyncio.isfuture(cb_result):
-                            await cb_result
-                    except Exception as e:
-                        logger.warning('on_status callback error: %s', e)
-
-                if status_resp.status == 'confirmed' and status_resp.bot_token:
-                    new_base_url = status_resp.baseurl or self.base_url
-                    # Update this client instance as well
-                    self.token = status_resp.bot_token
-                    self.base_url = new_base_url.rstrip('/')
-                    return LoginResult(
-                        token=status_resp.bot_token,
-                        base_url=new_base_url,
-                        account_id=status_resp.ilink_bot_id or '',
-                        qr_image_base64=last_qr_base64,
-                    )
-
-                if status_resp.status == 'expired':
-                    break  # retry with a new QR code
-
-                await asyncio.sleep(1)
-            else:
-                # While-loop ended without break → poll timeout, treat as expired
-                pass
-
-            remaining = max_retries - attempt - 1
-            if remaining > 0:
-                logger.info('QR code expired, refreshing... (%d retries left)', remaining)
-            else:
-                raise ApiError('QR code login failed: max retries exceeded', status=0)
-
-        # Should not reach here, but just in case
-        raise ApiError('QR code login failed', status=0)
-
-
-# ---------------------------------------------------------------------------
-# Parsing helpers
-# ---------------------------------------------------------------------------
-
-
-def _parse_cdn_media(data: Optional[dict]) -> Optional[CDNMedia]:
-    if not data:
-        return None
-    return CDNMedia(
-        encrypt_query_param=data.get('encrypt_query_param'),
-        aes_key=data.get('aes_key'),
-        encrypt_type=data.get('encrypt_type'),
-    )
-
-
-def _parse_message_item(data: dict) -> MessageItem:
-    item = MessageItem(
-        type=data.get('type'),
-        create_time_ms=data.get('create_time_ms'),
-        update_time_ms=data.get('update_time_ms'),
-        is_completed=data.get('is_completed'),
-        msg_id=data.get('msg_id'),
-    )
-
-    if data.get('text_item'):
-        item.text_item = TextItem(text=data['text_item'].get('text'))
-
-    if data.get('image_item'):
-        img = data['image_item']
-        item.image_item = ImageItem(
-            media=_parse_cdn_media(img.get('media')),
-            thumb_media=_parse_cdn_media(img.get('thumb_media')),
-            aeskey=img.get('aeskey'),
-            url=img.get('url'),
-            mid_size=img.get('mid_size'),
-        )
-
-    if data.get('voice_item'):
-        v = data['voice_item']
-        item.voice_item = VoiceItem(
-            media=_parse_cdn_media(v.get('media')),
-            encode_type=v.get('encode_type'),
-            playtime=v.get('playtime'),
-            text=v.get('text'),
-        )
-
-    if data.get('file_item'):
-        f = data['file_item']
-        item.file_item = FileItem(
-            media=_parse_cdn_media(f.get('media')),
-            file_name=f.get('file_name'),
-            md5=f.get('md5'),
-            len=f.get('len'),
-        )
-
-    if data.get('video_item'):
-        vid = data['video_item']
-        item.video_item = VideoItem(
-            media=_parse_cdn_media(vid.get('media')),
-            video_size=vid.get('video_size'),
-            play_length=vid.get('play_length'),
-            video_md5=vid.get('video_md5'),
-            thumb_media=_parse_cdn_media(vid.get('thumb_media')),
-        )
-
-    if data.get('ref_msg'):
-        ref = data['ref_msg']
-        item.ref_msg = RefMessage(
-            title=ref.get('title'),
-            message_item=_parse_message_item(ref['message_item']) if ref.get('message_item') else None,
-        )
-
-    return item
-
-
-def _parse_weixin_message(data: dict) -> WeixinMessage:
-    msg = WeixinMessage(
-        seq=data.get('seq'),
-        message_id=data.get('message_id'),
-        from_user_id=data.get('from_user_id'),
-        to_user_id=data.get('to_user_id'),
-        client_id=data.get('client_id'),
-        create_time_ms=data.get('create_time_ms'),
-        session_id=data.get('session_id'),
-        group_id=data.get('group_id'),
-        message_type=data.get('message_type'),
-        message_state=data.get('message_state'),
-        context_token=data.get('context_token'),
-    )
-    if data.get('item_list'):
-        msg.item_list = [_parse_message_item(item) for item in data['item_list']]
-    return msg
-
-
-def _parse_get_updates_response(data: dict) -> GetUpdatesResponse:
-    resp = GetUpdatesResponse(
-        ret=data.get('ret'),
-        errcode=data.get('errcode'),
-        errmsg=data.get('errmsg'),
-        get_updates_buf=data.get('get_updates_buf'),
-        longpolling_timeout_ms=data.get('longpolling_timeout_ms'),
-    )
-    if data.get('msgs'):
-        resp.msgs = [_parse_weixin_message(m) for m in data['msgs']]
-    return resp
-
-
-def _cdn_media_to_dict(media: Optional[CDNMedia]) -> Optional[dict]:
-    if not media:
-        return None
-    d: dict = {}
-    if media.encrypt_query_param is not None:
-        d['encrypt_query_param'] = media.encrypt_query_param
-    if media.aes_key is not None:
-        d['aes_key'] = media.aes_key
-    if media.encrypt_type is not None:
-        d['encrypt_type'] = media.encrypt_type
-    return d or None
-
-
-def _message_item_to_dict(item: MessageItem) -> dict:
-    d: dict = {'type': item.type}
-
-    if item.text_item:
-        d['text_item'] = {'text': item.text_item.text}
-
-    if item.image_item:
-        img_d: dict = {}
-        if item.image_item.media:
-            img_d['media'] = _cdn_media_to_dict(item.image_item.media)
-        if item.image_item.mid_size is not None:
-            img_d['mid_size'] = item.image_item.mid_size
-        d['image_item'] = img_d
-
-    if item.voice_item:
-        voice_d: dict = {}
-        if item.voice_item.media:
-            voice_d['media'] = _cdn_media_to_dict(item.voice_item.media)
-        if item.voice_item.playtime is not None:
-            voice_d['playtime'] = item.voice_item.playtime
-        d['voice_item'] = voice_d
-
-    if item.file_item:
-        file_d: dict = {}
-        if item.file_item.media:
-            file_d['media'] = _cdn_media_to_dict(item.file_item.media)
-        if item.file_item.file_name:
-            file_d['file_name'] = item.file_item.file_name
-        if item.file_item.len:
-            file_d['len'] = item.file_item.len
-        d['file_item'] = file_d
-
-    if item.video_item:
-        vid_d: dict = {}
-        if item.video_item.media:
-            vid_d['media'] = _cdn_media_to_dict(item.video_item.media)
-        if item.video_item.video_size is not None:
-            vid_d['video_size'] = item.video_item.video_size
-        d['video_item'] = vid_d
-
-    return d

src/langbot/libs/openclaw_weixin_api/types.py

@@ -1,200 +0,0 @@
-"""Type definitions for the OpenClaw WeChat API, mirroring the upstream protocol."""
-
-from __future__ import annotations
-
-from dataclasses import dataclass, field
-from typing import Any, Optional
-
-SESSION_EXPIRED_ERRCODE = -14
-
-
-class ApiError(Exception):
-    """Structured error raised by the OpenClaw WeChat API."""
-
-    def __init__(
-        self,
-        message: str,
-        *,
-        status: int = 0,
-        code: int | None = None,
-        payload: Any = None,
-    ):
-        super().__init__(message)
-        self.status = status
-        self.code = code
-        self.payload = payload
-
-    @property
-    def is_session_expired(self) -> bool:
-        return self.code == SESSION_EXPIRED_ERRCODE
-
-
-@dataclass
-class CDNMedia:
-    encrypt_query_param: Optional[str] = None
-    aes_key: Optional[str] = None
-    encrypt_type: Optional[int] = None
-
-
-@dataclass
-class TextItem:
-    text: Optional[str] = None
-
-
-@dataclass
-class ImageItem:
-    media: Optional[CDNMedia] = None
-    thumb_media: Optional[CDNMedia] = None
-    aeskey: Optional[str] = None
-    url: Optional[str] = None
-    mid_size: Optional[int] = None
-    thumb_size: Optional[int] = None
-    thumb_height: Optional[int] = None
-    thumb_width: Optional[int] = None
-    hd_size: Optional[int] = None
-    _downloaded_bytes: Optional[bytes] = field(default=None, repr=False)
-
-
-@dataclass
-class VoiceItem:
-    media: Optional[CDNMedia] = None
-    encode_type: Optional[int] = None
-    bits_per_sample: Optional[int] = None
-    sample_rate: Optional[int] = None
-    playtime: Optional[int] = None
-    text: Optional[str] = None
-    _downloaded_bytes: Optional[bytes] = field(default=None, repr=False)
-
-
-@dataclass
-class FileItem:
-    media: Optional[CDNMedia] = None
-    file_name: Optional[str] = None
-    md5: Optional[str] = None
-    len: Optional[str] = None
-    _downloaded_bytes: Optional[bytes] = field(default=None, repr=False)
-
-
-@dataclass
-class VideoItem:
-    media: Optional[CDNMedia] = None
-    video_size: Optional[int] = None
-    play_length: Optional[int] = None
-    video_md5: Optional[str] = None
-    thumb_media: Optional[CDNMedia] = None
-    thumb_size: Optional[int] = None
-    thumb_height: Optional[int] = None
-    thumb_width: Optional[int] = None
-    _downloaded_bytes: Optional[bytes] = field(default=None, repr=False)
-
-
-@dataclass
-class RefMessage:
-    message_item: Optional[MessageItem] = None
-    title: Optional[str] = None
-
-
-@dataclass
-class MessageItem:
-    """A single content item inside a WeixinMessage."""
-
-    # Item types
-    NONE = 0
-    TEXT = 1
-    IMAGE = 2
-    VOICE = 3
-    FILE = 4
-    VIDEO = 5
-
-    type: Optional[int] = None
-    create_time_ms: Optional[int] = None
-    update_time_ms: Optional[int] = None
-    is_completed: Optional[bool] = None
-    msg_id: Optional[str] = None
-    ref_msg: Optional[RefMessage] = None
-    text_item: Optional[TextItem] = None
-    image_item: Optional[ImageItem] = None
-    voice_item: Optional[VoiceItem] = None
-    file_item: Optional[FileItem] = None
-    video_item: Optional[VideoItem] = None
-
-
-@dataclass
-class WeixinMessage:
-    """Unified message from getUpdates or for sendMessage."""
-
-    # Message types
-    TYPE_USER = 1
-    TYPE_BOT = 2
-
-    # Message states
-    STATE_NEW = 0
-    STATE_GENERATING = 1
-    STATE_FINISH = 2
-
-    seq: Optional[int] = None
-    message_id: Optional[int] = None
-    from_user_id: Optional[str] = None
-    to_user_id: Optional[str] = None
-    client_id: Optional[str] = None
-    create_time_ms: Optional[int] = None
-    update_time_ms: Optional[int] = None
-    delete_time_ms: Optional[int] = None
-    session_id: Optional[str] = None
-    group_id: Optional[str] = None
-    message_type: Optional[int] = None
-    message_state: Optional[int] = None
-    item_list: Optional[list[MessageItem]] = None
-    context_token: Optional[str] = None
-
-
-@dataclass
-class GetUpdatesResponse:
-    ret: Optional[int] = None
-    errcode: Optional[int] = None
-    errmsg: Optional[str] = None
-    msgs: list[WeixinMessage] = field(default_factory=list)
-    get_updates_buf: Optional[str] = None
-    longpolling_timeout_ms: Optional[int] = None
-
-
-@dataclass
-class GetConfigResponse:
-    ret: Optional[int] = None
-    errmsg: Optional[str] = None
-    typing_ticket: Optional[str] = None
-
-
-@dataclass
-class GetUploadUrlResponse:
-    upload_param: Optional[str] = None
-    thumb_upload_param: Optional[str] = None
-
-
-@dataclass
-class QRCodeResponse:
-    """Response from get_bot_qrcode endpoint."""
-
-    qrcode: Optional[str] = None
-    qrcode_img_content: Optional[str] = None
-
-
-@dataclass
-class QRStatusResponse:
-    """Response from get_qrcode_status endpoint."""
-
-    status: Optional[str] = None  # "wait" | "scaned" | "confirmed" | "expired"
-    bot_token: Optional[str] = None
-    ilink_bot_id: Optional[str] = None
-    baseurl: Optional[str] = None
-    ilink_user_id: Optional[str] = None
-
-
-@dataclass
-class LoginResult:
-    """Result returned by the login flow."""
-
-    token: str
-    base_url: str
-    account_id: str
-    qr_image_base64: Optional[str] = None  # data URI of the last QR code shown

src/langbot/libs/wechatpad_api/util/http_util.py

@@ -1,5 +1,5 @@
 import requests
-from langbot.pkg.utils import httpclient
+import aiohttp
 
 
 def post_json(base_url, token, data=None):
@@ -63,16 +63,16 @@ async def async_request(
     """
     headers = {'Content-Type': 'application/json'}
     url = f'{base_url}?key={token_key}'
-    session = httpclient.get_session()
-    async with session.request(
-        method=method, url=url, params=params, headers=headers, data=data, json=json
-    ) as response:
-        response.raise_for_status()  # 如果状态码不是200，抛出异常
-        result = await response.json()
-        # print(result)
-        return result
-        # if result.get('Code') == 200:
-        #
-        #     return await result
-        # else:
-        #     raise RuntimeError("请求失败",response.text)
+    async with aiohttp.ClientSession() as session:
+        async with session.request(
+            method=method, url=url, params=params, headers=headers, data=data, json=json
+        ) as response:
+            response.raise_for_status()  # 如果状态码不是200，抛出异常
+            result = await response.json()
+            # print(result)
+            return result
+            # if result.get('Code') == 200:
+            #
+            #     return await result
+            # else:
+            #     raise RuntimeError("请求失败",response.text)

src/langbot/libs/wecom_ai_bot_api/api.py

@@ -6,8 +6,7 @@ import traceback
 import uuid
 import xml.etree.ElementTree as ET
 from dataclasses import dataclass, field
-import re
-from typing import Any, Callable, Optional, Tuple
+from typing import Any, Callable, Optional
 from urllib.parse import unquote
 
 import httpx
@@ -200,366 +199,6 @@ class StreamSessionManager:
                 self._msg_index.pop(msg_id, None)
 
 
-def _decrypt_file(encrypted_data: bytes, aes_key_str: str) -> bytes:
-    """Decrypt AES-256-CBC encrypted file data.
-
-    Aligned with the official WeCom AI Bot Python SDK (crypto_utils.py).
-
-    Args:
-        encrypted_data: The raw encrypted bytes.
-        aes_key_str: Base64-encoded AES key (may lack padding).
-
-    Returns:
-        Decrypted bytes with PKCS#7 padding removed.
-    """
-    if not encrypted_data:
-        raise ValueError('encrypted_data is empty')
-    if not aes_key_str:
-        raise ValueError('aes_key is empty')
-
-    # Python's base64.b64decode requires proper padding (length % 4 == 0).
-    # Node.js Buffer.from tolerates missing '=', so we must pad manually.
-    remainder = len(aes_key_str) % 4
-    if remainder != 0:
-        aes_key_str = aes_key_str + '=' * (4 - remainder)
-    key = base64.b64decode(aes_key_str)
-
-    iv = key[:16]
-
-    cipher = AES.new(key, AES.MODE_CBC, iv)
-
-    # Ensure encrypted data is aligned to AES block size (16 bytes).
-    # Node.js setAutoPadding(false) silently handles unaligned data,
-    # but PyCryptodome will raise an error.
-    block_size = 16
-    data_remainder = len(encrypted_data) % block_size
-    if data_remainder != 0:
-        encrypted_data = encrypted_data + b'\x00' * (block_size - data_remainder)
-
-    decrypted = cipher.decrypt(encrypted_data)
-
-    # Remove PKCS#7 padding with validation
-    if len(decrypted) == 0:
-        raise ValueError('Decrypted data is empty')
-
-    pad_len = decrypted[-1]
-    if pad_len < 1 or pad_len > 32 or pad_len > len(decrypted):
-        raise ValueError(f'Invalid PKCS#7 padding value: {pad_len}')
-
-    # Verify all padding bytes are consistent
-    for i in range(len(decrypted) - pad_len, len(decrypted)):
-        if decrypted[i] != pad_len:
-            raise ValueError('Invalid PKCS#7 padding: padding bytes mismatch')
-
-    return decrypted[: len(decrypted) - pad_len]
-
-
-def _extract_filename(content_disposition: str) -> Optional[str]:
-    """Extract filename from a Content-Disposition header value."""
-    if not content_disposition:
-        return None
-    # RFC 5987: filename*=UTF-8''xxx
-    utf8_match = re.search(r"filename\*=UTF-8''([^;\s]+)", content_disposition, re.IGNORECASE)
-    if utf8_match:
-        return unquote(utf8_match.group(1))
-    # Standard: filename="xxx" or filename=xxx
-    match = re.search(r'filename="?([^";\s]+)"?', content_disposition, re.IGNORECASE)
-    if match:
-        return unquote(match.group(1))
-    return None
-
-
-def _bytes_to_data_uri(data: bytes) -> str:
-    """Convert raw bytes to a data URI with auto-detected MIME type."""
-    if data.startswith(b'\xff\xd8'):
-        mime_type = 'image/jpeg'
-    elif data.startswith(b'\x89PNG'):
-        mime_type = 'image/png'
-    elif data.startswith((b'GIF87a', b'GIF89a')):
-        mime_type = 'image/gif'
-    elif data.startswith(b'BM'):
-        mime_type = 'image/bmp'
-    elif data.startswith(b'II*\x00') or data.startswith(b'MM\x00*'):
-        mime_type = 'image/tiff'
-    elif data[:4] == b'%PDF':
-        mime_type = 'application/pdf'
-    elif data[:4] == b'PK\x03\x04':
-        mime_type = 'application/zip'
-    else:
-        mime_type = 'application/octet-stream'
-
-    base64_str = base64.b64encode(data).decode('utf-8')
-    return f'data:{mime_type};base64,{base64_str}'
-
-
-async def download_encrypted_file(
-    download_url: str, aes_key: str, logger: EventLogger
-) -> Tuple[Optional[bytes], Optional[str]]:
-    """Download an AES-encrypted file from WeChat Work and decrypt it.
-
-    Args:
-        download_url: The encrypted file download URL.
-        aes_key: The AES key for decryption (base64-encoded, per-message aeskey
-                 or platform EncodingAESKey).
-        logger: Logger instance.
-
-    Returns:
-        A tuple of (decrypted_bytes, filename) or (None, None) on failure.
-    """
-    if not download_url:
-        return None, None
-    if not aes_key:
-        await logger.error('download_encrypted_file: aes_key is empty, cannot decrypt')
-        return None, None
-
-    filename: Optional[str] = None
-    try:
-        async with httpx.AsyncClient(timeout=30.0) as client:
-            response = await client.get(download_url)
-            if response.status_code != 200:
-                await logger.error(f'Failed to download file (HTTP {response.status_code}): {response.text[:200]}')
-                return None, None
-            encrypted_bytes = response.content
-            filename = _extract_filename(response.headers.get('content-disposition', ''))
-    except Exception:
-        await logger.error(f'Failed to download file: {traceback.format_exc()}')
-        return None, None
-
-    try:
-        decrypted = _decrypt_file(encrypted_bytes, aes_key)
-        return decrypted, filename
-    except Exception:
-        await logger.error(f'Failed to decrypt file: {traceback.format_exc()}')
-        return None, None
-
-
-async def parse_wecom_bot_message(
-    msg_json: dict[str, Any], encoding_aes_key: str, logger: EventLogger
-) -> dict[str, Any]:
-    """Parse a decrypted WeChat Work AI Bot message JSON into a unified message dict.
-
-    This is the shared message parsing logic used by both webhook and WebSocket modes.
-
-    Args:
-        msg_json: The decrypted message JSON from WeChat Work.
-        encoding_aes_key: AES key for file decryption.
-        logger: Logger instance.
-
-    Returns:
-        A dict suitable for constructing a WecomBotEvent.
-    """
-    message_data: dict[str, Any] = {}
-
-    msg_type = msg_json.get('msgtype', '')
-    if msg_type:
-        message_data['msgtype'] = msg_type
-
-    if msg_json.get('chattype', '') == 'single':
-        message_data['type'] = 'single'
-    elif msg_json.get('chattype', '') == 'group':
-        message_data['type'] = 'group'
-
-    max_inline_file_size = 5 * 1024 * 1024
-
-    async def _safe_download(url: str, per_msg_aeskey: str = '') -> Tuple[Optional[bytes], Optional[str]]:
-        """Download and decrypt a file, preferring per-message aeskey over platform key."""
-        if not url:
-            return None, None
-        key = per_msg_aeskey or encoding_aes_key
-        if not key:
-            await logger.warning('No AES key available for file decryption, skipping download')
-            return None, None
-        return await download_encrypted_file(url, key, logger)
-
-    async def _safe_download_as_data_uri(url: str, per_msg_aeskey: str = '') -> Optional[str]:
-        """Download, decrypt, and convert to data URI for backward compatibility."""
-        data, _filename = await _safe_download(url, per_msg_aeskey)
-        if data:
-            return _bytes_to_data_uri(data)
-        return None
-
-    if msg_type == 'text':
-        message_data['content'] = msg_json.get('text', {}).get('content')
-    elif msg_type == 'markdown':
-        message_data['content'] = msg_json.get('markdown', {}).get('content') or msg_json.get('text', {}).get(
-            'content', ''
-        )
-    elif msg_type == 'image':
-        image_info = msg_json.get('image', {})
-        picurl = image_info.get('url', '')
-        per_msg_aeskey = image_info.get('aeskey', '')
-        base64_data = await _safe_download_as_data_uri(picurl, per_msg_aeskey)
-        if base64_data:
-            message_data['picurl'] = base64_data
-            message_data['images'] = [base64_data]
-    elif msg_type == 'voice':
-        voice_info = msg_json.get('voice', {}) or {}
-        download_url = voice_info.get('url')
-        per_msg_aeskey = voice_info.get('aeskey', '')
-        message_data['voice'] = {
-            'url': download_url,
-            'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
-            'filesize': voice_info.get('filesize') or voice_info.get('size'),
-            'sdkfileid': voice_info.get('sdkfileid') or voice_info.get('fileid'),
-        }
-        if voice_info.get('content'):
-            message_data['content'] = voice_info.get('content')
-        if (message_data['voice'].get('filesize') or 0) <= max_inline_file_size:
-            voice_base64 = await _safe_download_as_data_uri(download_url, per_msg_aeskey)
-            if voice_base64:
-                message_data['voice']['base64'] = voice_base64
-    elif msg_type == 'video':
-        video_info = msg_json.get('video', {}) or {}
-        download_url = video_info.get('url')
-        per_msg_aeskey = video_info.get('aeskey', '')
-        video_data = {
-            'url': download_url,
-            'filesize': video_info.get('filesize') or video_info.get('size'),
-            'sdkfileid': video_info.get('sdkfileid') or video_info.get('fileid'),
-            'md5sum': video_info.get('md5sum') or video_info.get('md5'),
-            'filename': video_info.get('filename') or video_info.get('name'),
-        }
-        if (video_data.get('filesize') or 0) <= max_inline_file_size:
-            video_base64 = await _safe_download_as_data_uri(download_url, per_msg_aeskey)
-            if video_base64:
-                video_data['base64'] = video_base64
-        message_data['video'] = video_data
-    elif msg_type == 'file':
-        file_info = msg_json.get('file', {}) or {}
-        download_url = file_info.get('url') or file_info.get('fileurl')
-        per_msg_aeskey = file_info.get('aeskey', '')
-        file_data = {
-            'filename': file_info.get('filename') or file_info.get('name'),
-            'filesize': file_info.get('filesize') or file_info.get('size'),
-            'md5sum': file_info.get('md5sum') or file_info.get('md5'),
-            'sdkfileid': file_info.get('sdkfileid') or file_info.get('fileid'),
-            'download_url': download_url,
-            'extra': file_info,
-        }
-        if (file_data.get('filesize') or 0) <= max_inline_file_size:
-            file_bytes, dl_filename = await _safe_download(download_url, per_msg_aeskey)
-            if file_bytes:
-                file_data['base64'] = _bytes_to_data_uri(file_bytes)
-                if dl_filename and not file_data.get('filename'):
-                    file_data['filename'] = dl_filename
-        message_data['file'] = file_data
-    elif msg_type == 'link':
-        message_data['link'] = msg_json.get('link', {})
-        if not message_data.get('content'):
-            title = message_data['link'].get('title', '')
-            desc = message_data['link'].get('description') or message_data['link'].get('digest', '')
-            message_data['content'] = '\n'.join(filter(None, [title, desc]))
-    elif msg_type == 'mixed':
-        items = msg_json.get('mixed', {}).get('msg_item', [])
-        texts = []
-        images = []
-        files = []
-        voices = []
-        videos = []
-        links = []
-        for item in items:
-            item_type = item.get('msgtype')
-            if item_type == 'text':
-                texts.append(item.get('text', {}).get('content', ''))
-            elif item_type == 'image':
-                img_info = item.get('image', {})
-                img_url = img_info.get('url')
-                img_aeskey = img_info.get('aeskey', '')
-                base64_data = await _safe_download_as_data_uri(img_url, img_aeskey)
-                if base64_data:
-                    images.append(base64_data)
-            elif item_type == 'file':
-                file_info = item.get('file', {}) or {}
-                download_url = file_info.get('url') or file_info.get('fileurl')
-                item_aeskey = file_info.get('aeskey', '')
-                file_data = {
-                    'filename': file_info.get('filename') or file_info.get('name'),
-                    'filesize': file_info.get('filesize') or file_info.get('size'),
-                    'md5sum': file_info.get('md5sum') or file_info.get('md5'),
-                    'sdkfileid': file_info.get('sdkfileid') or file_info.get('fileid'),
-                    'download_url': download_url,
-                    'extra': file_info,
-                }
-                if (file_data.get('filesize') or 0) <= max_inline_file_size:
-                    file_bytes, dl_filename = await _safe_download(download_url, item_aeskey)
-                    if file_bytes:
-                        file_data['base64'] = _bytes_to_data_uri(file_bytes)
-                        if dl_filename and not file_data.get('filename'):
-                            file_data['filename'] = dl_filename
-                files.append(file_data)
-            elif item_type == 'voice':
-                voice_info = item.get('voice', {}) or {}
-                download_url = voice_info.get('url')
-                item_aeskey = voice_info.get('aeskey', '')
-                voice_data = {
-                    'url': download_url,
-                    'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
-                    'filesize': voice_info.get('filesize') or voice_info.get('size'),
-                    'sdkfileid': voice_info.get('sdkfileid') or voice_info.get('fileid'),
-                }
-                if voice_info.get('content'):
-                    texts.append(voice_info.get('content'))
-                if (voice_data.get('filesize') or 0) <= max_inline_file_size:
-                    voice_base64 = await _safe_download_as_data_uri(download_url, item_aeskey)
-                    if voice_base64:
-                        voice_data['base64'] = voice_base64
-                voices.append(voice_data)
-            elif item_type == 'video':
-                video_info = item.get('video', {}) or {}
-                download_url = video_info.get('url')
-                item_aeskey = video_info.get('aeskey', '')
-                video_data = {
-                    'url': download_url,
-                    'filesize': video_info.get('filesize') or video_info.get('size'),
-                    'sdkfileid': video_info.get('sdkfileid') or video_info.get('fileid'),
-                    'md5sum': video_info.get('md5sum') or video_info.get('md5'),
-                    'filename': video_info.get('filename') or video_info.get('name'),
-                }
-                if (video_data.get('filesize') or 0) <= max_inline_file_size:
-                    video_base64 = await _safe_download_as_data_uri(download_url, item_aeskey)
-                    if video_base64:
-                        video_data['base64'] = video_base64
-                videos.append(video_data)
-            elif item_type == 'link':
-                links.append(item.get('link', {}))
-
-        if texts:
-            message_data['content'] = ' '.join(texts)
-        if images:
-            message_data['images'] = images
-            message_data['picurl'] = images[0]
-        if files:
-            message_data['files'] = files
-            message_data['file'] = files[0]
-        if voices:
-            message_data['voices'] = voices
-            message_data['voice'] = voices[0]
-        if videos:
-            message_data['videos'] = videos
-            message_data['video'] = videos[0]
-        if links:
-            message_data['link'] = links[0]
-        if items:
-            message_data['attachments'] = items
-    else:
-        message_data['raw_msg'] = msg_json
-
-    from_info = msg_json.get('from', {})
-    message_data['userid'] = from_info.get('userid', '')
-    message_data['username'] = from_info.get('alias', '') or from_info.get('name', '') or from_info.get('userid', '')
-
-    if msg_json.get('chattype', '') == 'group':
-        message_data['chatid'] = msg_json.get('chatid', '')
-        message_data['chatname'] = msg_json.get('chatname', '') or msg_json.get('chatid', '')
-
-    message_data['msgid'] = msg_json.get('msgid', '')
-
-    if msg_json.get('aibotid'):
-        message_data['aibotid'] = msg_json.get('aibotid', '')
-
-    return message_data
-
-
 class WecomBotClient:
     def __init__(self, Token: str, EnCodingAESKey: str, Corpid: str, logger: EventLogger, unified_mode: bool = False):
         """企业微信智能机器人客户端。
@@ -816,7 +455,196 @@ class WecomBotClient:
         return await self._handle_post_initial_response(msg_json, nonce)
 
     async def get_message(self, msg_json):
-        return await parse_wecom_bot_message(msg_json, self.EnCodingAESKey, self.logger)
+        message_data = {}
+
+        msg_type = msg_json.get('msgtype', '')
+        if msg_type:
+            message_data['msgtype'] = msg_type
+
+        if msg_json.get('chattype', '') == 'single':
+            message_data['type'] = 'single'
+        elif msg_json.get('chattype', '') == 'group':
+            message_data['type'] = 'group'
+
+        max_inline_file_size = 5 * 1024 * 1024  # avoid decoding very large payloads by default
+
+        async def _safe_download(url: str):
+            if not url:
+                return None
+            return await self.download_url_to_base64(url, self.EnCodingAESKey)
+
+        if msg_type == 'text':
+            message_data['content'] = msg_json.get('text', {}).get('content')
+        elif msg_type == 'markdown':
+            message_data['content'] = msg_json.get('markdown', {}).get('content') or msg_json.get('text', {}).get(
+                'content', ''
+            )
+        elif msg_type == 'image':
+            picurl = msg_json.get('image', {}).get('url', '')
+            base64_data = await _safe_download(picurl)
+            if base64_data:
+                message_data['picurl'] = base64_data
+                message_data['images'] = [base64_data]
+        elif msg_type == 'voice':
+            voice_info = msg_json.get('voice', {}) or {}
+            download_url = voice_info.get('url')
+            message_data['voice'] = {
+                'url': download_url,
+                'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
+                'filesize': voice_info.get('filesize') or voice_info.get('size'),
+                'sdkfileid': voice_info.get('sdkfileid') or voice_info.get('fileid'),
+            }
+            # 企业微信智能转写文本（如果已有）直接复用，避免重复转写
+            if voice_info.get('content'):
+                message_data['content'] = voice_info.get('content')
+            if (message_data['voice'].get('filesize') or 0) <= max_inline_file_size:
+                voice_base64 = await _safe_download(download_url)
+                if voice_base64:
+                    message_data['voice']['base64'] = voice_base64
+        elif msg_type == 'video':
+            video_info = msg_json.get('video', {}) or {}
+            download_url = video_info.get('url')
+            video_data = {
+                'url': download_url,
+                'filesize': video_info.get('filesize') or video_info.get('size'),
+                'sdkfileid': video_info.get('sdkfileid') or video_info.get('fileid'),
+                'md5sum': video_info.get('md5sum') or video_info.get('md5'),
+                'filename': video_info.get('filename') or video_info.get('name'),
+            }
+            if (video_data.get('filesize') or 0) <= max_inline_file_size:
+                video_base64 = await _safe_download(download_url)
+                if video_base64:
+                    video_data['base64'] = video_base64
+            message_data['video'] = video_data
+        elif msg_type == 'file':
+            file_info = msg_json.get('file', {}) or {}
+            download_url = file_info.get('url') or file_info.get('fileurl')
+            file_data = {
+                'filename': file_info.get('filename') or file_info.get('name'),
+                'filesize': file_info.get('filesize') or file_info.get('size'),
+                'md5sum': file_info.get('md5sum') or file_info.get('md5'),
+                'sdkfileid': file_info.get('sdkfileid') or file_info.get('fileid'),
+                'download_url': download_url,
+                'extra': file_info,
+            }
+            if (file_data.get('filesize') or 0) <= max_inline_file_size:
+                file_base64 = await _safe_download(download_url)
+                if file_base64:
+                    file_data['base64'] = file_base64
+            message_data['file'] = file_data
+        elif msg_type == 'link':
+            message_data['link'] = msg_json.get('link', {})
+            if not message_data.get('content'):
+                title = message_data['link'].get('title', '')
+                desc = message_data['link'].get('description') or message_data['link'].get('digest', '')
+                message_data['content'] = '\n'.join(filter(None, [title, desc]))
+        elif msg_type == 'mixed':
+            items = msg_json.get('mixed', {}).get('msg_item', [])
+            texts = []
+            images = []
+            files = []
+            voices = []
+            videos = []
+            links = []
+            for item in items:
+                item_type = item.get('msgtype')
+                if item_type == 'text':
+                    texts.append(item.get('text', {}).get('content', ''))
+                elif item_type == 'image':
+                    img_url = item.get('image', {}).get('url')
+                    base64_data = await _safe_download(img_url)
+                    if base64_data:
+                        images.append(base64_data)
+                elif item_type == 'file':
+                    file_info = item.get('file', {}) or {}
+                    download_url = file_info.get('url') or file_info.get('fileurl')
+                    file_data = {
+                        'filename': file_info.get('filename') or file_info.get('name'),
+                        'filesize': file_info.get('filesize') or file_info.get('size'),
+                        'md5sum': file_info.get('md5sum') or file_info.get('md5'),
+                        'sdkfileid': file_info.get('sdkfileid') or file_info.get('fileid'),
+                        'download_url': download_url,
+                        'extra': file_info,
+                    }
+                    if (file_data.get('filesize') or 0) <= max_inline_file_size:
+                        file_base64 = await _safe_download(download_url)
+                        if file_base64:
+                            file_data['base64'] = file_base64
+                    files.append(file_data)
+                elif item_type == 'voice':
+                    voice_info = item.get('voice', {}) or {}
+                    download_url = voice_info.get('url')
+                    voice_data = {
+                        'url': download_url,
+                        'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
+                        'filesize': voice_info.get('filesize') or voice_info.get('size'),
+                        'sdkfileid': voice_info.get('sdkfileid') or voice_info.get('fileid'),
+                    }
+                    if voice_info.get('content'):
+                        texts.append(voice_info.get('content'))
+                    if (voice_data.get('filesize') or 0) <= max_inline_file_size:
+                        voice_base64 = await _safe_download(download_url)
+                        if voice_base64:
+                            voice_data['base64'] = voice_base64
+                    voices.append(voice_data)
+                elif item_type == 'video':
+                    video_info = item.get('video', {}) or {}
+                    download_url = video_info.get('url')
+                    video_data = {
+                        'url': download_url,
+                        'filesize': video_info.get('filesize') or video_info.get('size'),
+                        'sdkfileid': video_info.get('sdkfileid') or video_info.get('fileid'),
+                        'md5sum': video_info.get('md5sum') or video_info.get('md5'),
+                        'filename': video_info.get('filename') or video_info.get('name'),
+                    }
+                    if (video_data.get('filesize') or 0) <= max_inline_file_size:
+                        video_base64 = await _safe_download(download_url)
+                        if video_base64:
+                            video_data['base64'] = video_base64
+                    videos.append(video_data)
+                elif item_type == 'link':
+                    links.append(item.get('link', {}))
+
+            if texts:
+                message_data['content'] = ' '.join(texts)  # 拼接所有 text
+            if images:
+                message_data['images'] = images
+                message_data['picurl'] = images[0]  # 只保留第一个 image
+            if files:
+                message_data['files'] = files
+                message_data['file'] = files[0]
+            if voices:
+                message_data['voices'] = voices
+                message_data['voice'] = voices[0]
+            if videos:
+                message_data['videos'] = videos
+                message_data['video'] = videos[0]
+            if links:
+                message_data['link'] = links[0]
+            if items:
+                message_data['attachments'] = items
+        else:
+            message_data['raw_msg'] = msg_json
+
+        # Extract user information
+        from_info = msg_json.get('from', {})
+        message_data['userid'] = from_info.get('userid', '')
+        message_data['username'] = (
+            from_info.get('alias', '') or from_info.get('name', '') or from_info.get('userid', '')
+        )
+
+        # Extract chat/group information
+        if msg_json.get('chattype', '') == 'group':
+            message_data['chatid'] = msg_json.get('chatid', '')
+            # Try to get group name if available
+            message_data['chatname'] = msg_json.get('chatname', '') or msg_json.get('chatid', '')
+
+        message_data['msgid'] = msg_json.get('msgid', '')
+
+        if msg_json.get('aibotid'):
+            message_data['aibotid'] = msg_json.get('aibotid', '')
+
+        return message_data
 
     async def _handle_message(self, event: wecombotevent.WecomBotEvent):
         """
@@ -884,10 +712,39 @@ class WecomBotClient:
         return decorator
 
     async def download_url_to_base64(self, download_url, encoding_aes_key):
-        data, _filename = await download_encrypted_file(download_url, encoding_aes_key, self.logger)
-        if data:
-            return _bytes_to_data_uri(data)
-        return None
+        async with httpx.AsyncClient() as client:
+            response = await client.get(download_url)
+            if response.status_code != 200:
+                await self.logger.error(f'failed to get file: {response.text}')
+                return None
+
+            encrypted_bytes = response.content
+
+        aes_key = base64.b64decode(encoding_aes_key + '=')  # base64 补齐
+        iv = aes_key[:16]
+
+        cipher = AES.new(aes_key, AES.MODE_CBC, iv)
+        decrypted = cipher.decrypt(encrypted_bytes)
+
+        pad_len = decrypted[-1]
+        decrypted = decrypted[:-pad_len]
+
+        if decrypted.startswith(b'\xff\xd8'):  # JPEG
+            mime_type = 'image/jpeg'
+        elif decrypted.startswith(b'\x89PNG'):  # PNG
+            mime_type = 'image/png'
+        elif decrypted.startswith((b'GIF87a', b'GIF89a')):  # GIF
+            mime_type = 'image/gif'
+        elif decrypted.startswith(b'BM'):  # BMP
+            mime_type = 'image/bmp'
+        elif decrypted.startswith(b'II*\x00') or decrypted.startswith(b'MM\x00*'):  # TIFF
+            mime_type = 'image/tiff'
+        else:
+            mime_type = 'application/octet-stream'
+
+        # 转 base64
+        base64_str = base64.b64encode(decrypted).decode('utf-8')
+        return f'data:{mime_type};base64,{base64_str}'
 
     async def run_task(self, host: str, port: int, *args, **kwargs):
         """

src/langbot/libs/wecom_ai_bot_api/ws_client.py

@@ -1,596 +0,0 @@
-"""WeChat Work AI Bot WebSocket long connection client.
-
-Implements the WebSocket protocol for receiving messages and sending replies
-via a persistent connection to wss://openws.work.weixin.qq.com, as an
-alternative to the HTTP callback (webhook) mode.
-
-Protocol reference: https://developer.work.weixin.qq.com/document/path/101463
-Official Node.js SDK: https://github.com/WecomTeam/aibot-node-sdk
-"""
-
-from __future__ import annotations
-
-import asyncio
-import json
-import secrets
-import time
-import traceback
-from typing import Any, Callable, Optional
-
-import aiohttp
-
-from langbot.libs.wecom_ai_bot_api import wecombotevent
-from langbot.libs.wecom_ai_bot_api.api import parse_wecom_bot_message
-from langbot.pkg.platform.logger import EventLogger
-
-DEFAULT_WS_URL = 'wss://openws.work.weixin.qq.com'
-
-# WebSocket frame command constants
-CMD_SUBSCRIBE = 'aibot_subscribe'
-CMD_HEARTBEAT = 'ping'
-CMD_MSG_CALLBACK = 'aibot_msg_callback'
-CMD_EVENT_CALLBACK = 'aibot_event_callback'
-CMD_RESPOND_MSG = 'aibot_respond_msg'
-CMD_RESPOND_WELCOME = 'aibot_respond_welcome_msg'
-CMD_RESPOND_UPDATE = 'aibot_respond_update_msg'
-CMD_SEND_MSG = 'aibot_send_msg'
-
-
-def _generate_req_id(prefix: str) -> str:
-    """Generate a unique request ID in the format: {prefix}_{timestamp}_{random}."""
-    ts = int(time.time() * 1000)
-    rand = secrets.token_hex(4)
-    return f'{prefix}_{ts}_{rand}'
-
-
-class WecomBotWsClient:
-    """WeChat Work AI Bot WebSocket long connection client.
-
-    Provides message receiving, streaming reply, proactive message sending,
-    and event callback handling over a persistent WebSocket connection.
-    """
-
-    def __init__(
-        self,
-        bot_id: str,
-        secret: str,
-        logger: EventLogger,
-        encoding_aes_key: str = '',
-        ws_url: str = DEFAULT_WS_URL,
-        heartbeat_interval: float = 30.0,
-        max_reconnect_attempts: int = -1,
-        reconnect_base_delay: float = 1.0,
-        reconnect_max_delay: float = 30.0,
-    ):
-        self.bot_id = bot_id
-        self.secret = secret
-        self.logger = logger
-        self.encoding_aes_key = encoding_aes_key
-        self.ws_url = ws_url
-        self.heartbeat_interval = heartbeat_interval
-        self.max_reconnect_attempts = max_reconnect_attempts
-        self.reconnect_base_delay = reconnect_base_delay
-        self.reconnect_max_delay = reconnect_max_delay
-
-        self._ws: Optional[aiohttp.ClientWebSocketResponse] = None
-        self._session: Optional[aiohttp.ClientSession] = None
-        self._running = False
-        self._heartbeat_task: Optional[asyncio.Task] = None
-        self._missed_pong_count = 0
-        self._max_missed_pong = 2
-        self._reconnect_attempts = 0
-
-        # Message handler registry (same pattern as WecomBotClient)
-        self._message_handlers: dict[str, list[Callable]] = {}
-        # Message deduplication
-        self._msg_id_map: dict[str, int] = {}
-
-        # Pending ACK futures: req_id -> Future[dict]
-        self._pending_acks: dict[str, asyncio.Future] = {}
-        # Per-req_id serial reply queues
-        self._reply_queues: dict[str, asyncio.Queue] = {}
-        self._reply_workers: dict[str, asyncio.Task] = {}
-        self._reply_ack_timeout = 5.0
-
-        # Stream ID tracking for WebSocket mode
-        self._stream_ids: dict[str, str] = {}  # msg_id -> req_id|stream_id
-        # Dedup: skip sending when content hasn't changed
-        self._stream_last_content: dict[str, str] = {}  # msg_id -> last content sent
-
-    # ── Public API ──────────────────────────────────────────────────
-
-    async def connect(self):
-        """Connect to WebSocket server with automatic reconnection.
-
-        This method blocks until disconnect() is called or max reconnect
-        attempts are exhausted.
-        """
-        self._running = True
-        self._reconnect_attempts = 0
-
-        while self._running:
-            try:
-                await self._connect_once()
-            except Exception:
-                if not self._running:
-                    break
-                await self.logger.error(f'WebSocket connection error: {traceback.format_exc()}')
-
-            if not self._running:
-                break
-
-            # Reconnect with exponential backoff
-            if self.max_reconnect_attempts != -1 and self._reconnect_attempts >= self.max_reconnect_attempts:
-                await self.logger.error(f'Max reconnect attempts reached ({self.max_reconnect_attempts}), giving up')
-                break
-
-            self._reconnect_attempts += 1
-            delay = min(
-                self.reconnect_base_delay * (2 ** (self._reconnect_attempts - 1)),
-                self.reconnect_max_delay,
-            )
-            await self.logger.info(f'Reconnecting in {delay:.1f}s (attempt {self._reconnect_attempts})...')
-            await asyncio.sleep(delay)
-
-    async def disconnect(self):
-        """Gracefully disconnect from the WebSocket server."""
-        self._running = False
-        if self._heartbeat_task and not self._heartbeat_task.done():
-            self._heartbeat_task.cancel()
-        for task in self._reply_workers.values():
-            if not task.done():
-                task.cancel()
-        if self._ws and not self._ws.closed:
-            await self._ws.close()
-        self._ws = None
-        if self._session and not self._session.closed:
-            await self._session.close()
-        self._session = None
-
-    def on_message(self, msg_type: str) -> Callable:
-        """Decorator to register a message handler.
-
-        Same interface as WecomBotClient.on_message for compatibility.
-
-        Args:
-            msg_type: 'single', 'group', or specific message type.
-        """
-
-        def decorator(func: Callable[[wecombotevent.WecomBotEvent], Any]):
-            if msg_type not in self._message_handlers:
-                self._message_handlers[msg_type] = []
-            self._message_handlers[msg_type].append(func)
-            return func
-
-        return decorator
-
-    async def reply_stream(
-        self,
-        req_id: str,
-        stream_id: str,
-        content: str,
-        finish: bool = False,
-    ) -> Optional[dict]:
-        """Send a streaming reply frame.
-
-        Args:
-            req_id: The req_id from the original message frame (must be passed through).
-            stream_id: The stream ID for this streaming session.
-            content: The content to send (supports Markdown).
-            finish: Whether this is the final chunk.
-
-        Returns:
-            The ACK frame dict, or None on failure.
-        """
-        body = {
-            'msgtype': 'stream',
-            'stream': {
-                'id': stream_id,
-                'finish': finish,
-                'content': content,
-            },
-        }
-        return await self._send_reply(req_id, body)
-
-    async def reply_text(self, req_id: str, content: str) -> Optional[dict]:
-        """Send a non-streaming text reply.
-
-        Args:
-            req_id: The req_id from the original message frame.
-            content: The text content to reply.
-
-        Returns:
-            The ACK frame dict, or None on failure.
-        """
-        body = {
-            'msgtype': 'markdown',
-            'markdown': {
-                'content': content,
-            },
-        }
-        return await self._send_reply(req_id, body)
-
-    async def send_message(self, chat_id: str, content: str, msgtype: str = 'markdown') -> Optional[dict]:
-        """Proactively send a message to a specified chat.
-
-        Args:
-            chat_id: The chat ID (userid for single chat, chatid for group chat).
-            content: The message content.
-            msgtype: Message type, 'markdown' by default.
-
-        Returns:
-            The ACK frame dict, or None on failure.
-        """
-        req_id = _generate_req_id(CMD_SEND_MSG)
-        body: dict[str, Any] = {
-            'chatid': chat_id,
-            'msgtype': msgtype,
-        }
-        if msgtype == 'markdown':
-            body['markdown'] = {'content': content}
-        elif msgtype == 'text':
-            body['text'] = {'content': content}
-        return await self._send_reply(req_id, body, cmd=CMD_SEND_MSG)
-
-    async def push_stream_chunk(self, msg_id: str, content: str, is_final: bool = False) -> bool:
-        """Push a streaming chunk for a given message ID.
-
-        Compatible interface with WecomBotClient.push_stream_chunk.
-
-        Args:
-            msg_id: The original message ID.
-            content: The cumulative content from the pipeline.
-            is_final: Whether this is the final chunk.
-
-        Returns:
-            True if the stream session exists and chunk was sent.
-        """
-        key = self._stream_ids.get(msg_id)
-        if not key:
-            return False
-        req_id, stream_id = key.split('|', 1)
-        try:
-            # Skip sending if content hasn't changed (e.g. during tool call argument streaming)
-            if not is_final and content == self._stream_last_content.get(msg_id):
-                return True
-            await self.reply_stream(req_id, stream_id, content, finish=is_final)
-            self._stream_last_content[msg_id] = content
-            if is_final:
-                self._stream_ids.pop(msg_id, None)
-                self._stream_last_content.pop(msg_id, None)
-            return True
-        except Exception:
-            await self.logger.error(f'Failed to push stream chunk: {traceback.format_exc()}')
-            return False
-
-    async def set_message(self, msg_id: str, content: str):
-        """Fallback: send content as a final stream chunk or direct reply.
-
-        Compatible interface with WecomBotClient.set_message.
-        """
-        handled = await self.push_stream_chunk(msg_id, content, is_final=True)
-        if not handled:
-            await self.logger.warning(f'No active stream for msg_id={msg_id}, message dropped')
-
-    # ── Connection lifecycle ────────────────────────────────────────
-
-    async def _connect_once(self):
-        """Establish a single WebSocket connection, authenticate, and listen."""
-        await self.logger.info(f'Connecting to {self.ws_url}...')
-
-        self._session = aiohttp.ClientSession()
-        try:
-            self._ws = await self._session.ws_connect(self.ws_url)
-            self._missed_pong_count = 0
-            self._reconnect_attempts = 0
-            await self.logger.info('WebSocket connected, sending auth...')
-
-            await self._send_auth()
-
-            # Wait for auth response
-            auth_ok = await self._wait_for_auth()
-            if not auth_ok:
-                await self.logger.error('Authentication failed')
-                return
-
-            await self.logger.info('Authenticated successfully')
-
-            # Start heartbeat
-            self._heartbeat_task = asyncio.create_task(self._heartbeat_loop())
-
-            try:
-                await self._listen_loop()
-            finally:
-                if self._heartbeat_task and not self._heartbeat_task.done():
-                    self._heartbeat_task.cancel()
-                self._clear_pending_acks('Connection closed')
-        finally:
-            if self._ws and not self._ws.closed:
-                await self._ws.close()
-            self._ws = None
-            if self._session and not self._session.closed:
-                await self._session.close()
-            self._session = None
-
-    async def _send_auth(self):
-        """Send the authentication frame."""
-        frame = {
-            'cmd': CMD_SUBSCRIBE,
-            'headers': {'req_id': _generate_req_id(CMD_SUBSCRIBE)},
-            'body': {
-                'bot_id': self.bot_id,
-                'secret': self.secret,
-            },
-        }
-        await self._send_frame(frame)
-
-    async def _wait_for_auth(self) -> bool:
-        """Wait for and validate the authentication response."""
-        try:
-            msg = await asyncio.wait_for(self._ws.receive(), timeout=10.0)
-            if msg.type in (aiohttp.WSMsgType.TEXT,):
-                frame = json.loads(msg.data)
-                req_id = frame.get('headers', {}).get('req_id', '')
-                if req_id.startswith(CMD_SUBSCRIBE) and frame.get('errcode') == 0:
-                    return True
-                await self.logger.error(f'Auth response: errcode={frame.get("errcode")}, errmsg={frame.get("errmsg")}')
-                return False
-            elif msg.type in (aiohttp.WSMsgType.ERROR, aiohttp.WSMsgType.CLOSED, aiohttp.WSMsgType.CLOSING):
-                await self.logger.error(f'WebSocket closed during auth: {msg.type}')
-                return False
-            await self.logger.error(f'Unexpected message type during auth: {msg.type}')
-            return False
-        except asyncio.TimeoutError:
-            await self.logger.error('Auth response timeout')
-            return False
-
-    async def _heartbeat_loop(self):
-        """Periodically send heartbeat pings."""
-        try:
-            while self._running and self._ws and not self._ws.closed:
-                await asyncio.sleep(self.heartbeat_interval)
-                if not self._running or not self._ws or self._ws.closed:
-                    break
-
-                if self._missed_pong_count >= self._max_missed_pong:
-                    await self.logger.warning(
-                        f'No heartbeat ack for {self._missed_pong_count} consecutive pings, connection considered dead'
-                    )
-                    await self._ws.close()
-                    break
-
-                self._missed_pong_count += 1
-                frame = {
-                    'cmd': CMD_HEARTBEAT,
-                    'headers': {'req_id': _generate_req_id(CMD_HEARTBEAT)},
-                }
-                try:
-                    await self._send_frame(frame)
-                except Exception:
-                    break
-        except asyncio.CancelledError:
-            pass
-
-    async def _listen_loop(self):
-        """Listen for incoming WebSocket frames and dispatch them."""
-        async for msg in self._ws:
-            if not self._running:
-                break
-            if msg.type == aiohttp.WSMsgType.TEXT:
-                try:
-                    frame = json.loads(msg.data)
-                    await self._handle_frame(frame)
-                except json.JSONDecodeError:
-                    await self.logger.error(f'Failed to parse WebSocket message: {str(msg.data)[:200]}')
-                except Exception:
-                    await self.logger.error(f'Error handling frame: {traceback.format_exc()}')
-            elif msg.type == aiohttp.WSMsgType.BINARY:
-                try:
-                    frame = json.loads(msg.data)
-                    await self._handle_frame(frame)
-                except Exception:
-                    await self.logger.error(f'Error handling binary frame: {traceback.format_exc()}')
-            elif msg.type in (aiohttp.WSMsgType.ERROR, aiohttp.WSMsgType.CLOSED, aiohttp.WSMsgType.CLOSING):
-                await self.logger.warning(f'WebSocket connection closed: {msg.type}')
-                break
-
-    # ── Frame handling ──────────────────────────────────────────────
-
-    async def _handle_frame(self, frame: dict):
-        """Route an incoming frame to the appropriate handler."""
-        cmd = frame.get('cmd', '')
-
-        # Message push
-        if cmd == CMD_MSG_CALLBACK:
-            asyncio.create_task(self._handle_message_callback(frame))
-            return
-
-        # Event push
-        if cmd == CMD_EVENT_CALLBACK:
-            asyncio.create_task(self._handle_event_callback(frame))
-            return
-
-        # No cmd → response/ACK frame, dispatch by req_id prefix
-        req_id = frame.get('headers', {}).get('req_id', '')
-
-        # Check pending ACKs first
-        if req_id in self._pending_acks:
-            future = self._pending_acks.pop(req_id)
-            if not future.done():
-                future.set_result(frame)
-            return
-
-        # Heartbeat response
-        if req_id.startswith(CMD_HEARTBEAT):
-            if frame.get('errcode') == 0:
-                self._missed_pong_count = 0
-            return
-
-        # Unknown frame
-        await self.logger.warning(f'Unknown frame: {json.dumps(frame, ensure_ascii=False)[:200]}')
-
-    async def _handle_message_callback(self, frame: dict):
-        """Handle an incoming message callback frame."""
-        try:
-            body = frame.get('body', {})
-            req_id = frame.get('headers', {}).get('req_id', '')
-
-            # Parse message using shared logic
-            message_data = await parse_wecom_bot_message(body, self.encoding_aes_key, self.logger)
-            if not message_data:
-                return
-
-            # Generate stream_id for this message and store the mapping
-            stream_id = _generate_req_id('stream')
-            msg_id = message_data.get('msgid', '')
-            if msg_id:
-                self._stream_ids[msg_id] = f'{req_id}|{stream_id}'
-            message_data['stream_id'] = stream_id
-            message_data['req_id'] = req_id
-
-            event = wecombotevent.WecomBotEvent(message_data)
-            await self._dispatch_event(event)
-        except Exception:
-            await self.logger.error(f'Error in message callback: {traceback.format_exc()}')
-
-    async def _handle_event_callback(self, frame: dict):
-        """Handle an incoming event callback frame (enter_chat, template_card_event, etc.)."""
-        try:
-            body = frame.get('body', {})
-            req_id = frame.get('headers', {}).get('req_id', '')
-
-            event_info = body.get('event', {})
-            event_type = event_info.get('eventtype', '')
-
-            message_data = {
-                'msgtype': 'event',
-                'type': body.get('chattype', 'single'),
-                'event': event_info,
-                'eventtype': event_type,
-                'msgid': body.get('msgid', ''),
-                'aibotid': body.get('aibotid', ''),
-                'req_id': req_id,
-            }
-
-            from_info = body.get('from', {})
-            message_data['userid'] = from_info.get('userid', '')
-            message_data['username'] = from_info.get('alias', '') or from_info.get('userid', '')
-
-            if body.get('chatid'):
-                message_data['chatid'] = body.get('chatid', '')
-
-            event = wecombotevent.WecomBotEvent(message_data)
-
-            # Dispatch to event-specific handlers
-            if event_type in self._message_handlers:
-                for handler in self._message_handlers[event_type]:
-                    await handler(event)
-
-            # Also dispatch to generic 'event' handlers
-            if 'event' in self._message_handlers:
-                for handler in self._message_handlers['event']:
-                    await handler(event)
-
-        except Exception:
-            await self.logger.error(f'Error in event callback: {traceback.format_exc()}')
-
-    async def _dispatch_event(self, event: wecombotevent.WecomBotEvent):
-        """Dispatch a message event to registered handlers with deduplication."""
-        try:
-            message_id = event.message_id
-            if message_id in self._msg_id_map:
-                self._msg_id_map[message_id] += 1
-                return
-            self._msg_id_map[message_id] = 1
-
-            msg_type = event.type
-            if msg_type in self._message_handlers:
-                for handler in self._message_handlers[msg_type]:
-                    await handler(event)
-        except Exception:
-            await self.logger.error(f'Error dispatching event: {traceback.format_exc()}')
-
-    # ── Reply sending with serial queue ─────────────────────────────
-
-    async def _send_reply(
-        self,
-        req_id: str,
-        body: dict,
-        cmd: str = CMD_RESPOND_MSG,
-    ) -> Optional[dict]:
-        """Send a reply frame and wait for ACK.
-
-        Replies with the same req_id are serialized to maintain ordering.
-        """
-        if not self._ws or self._ws.closed:
-            return None
-
-        frame = {
-            'cmd': cmd,
-            'headers': {'req_id': req_id},
-            'body': body,
-        }
-
-        # Ensure serial delivery per req_id
-        if req_id not in self._reply_queues:
-            self._reply_queues[req_id] = asyncio.Queue()
-            self._reply_workers[req_id] = asyncio.create_task(self._reply_queue_worker(req_id))
-
-        future: asyncio.Future = asyncio.get_event_loop().create_future()
-        await self._reply_queues[req_id].put((frame, future))
-        return await future
-
-    async def _reply_queue_worker(self, req_id: str):
-        """Process reply queue items serially for a given req_id."""
-        queue = self._reply_queues[req_id]
-        try:
-            while self._running:
-                try:
-                    frame, future = await asyncio.wait_for(queue.get(), timeout=60.0)
-                except asyncio.TimeoutError:
-                    # Queue idle, clean up worker
-                    break
-
-                try:
-                    ack = await self._send_and_wait_ack(frame)
-                    if not future.done():
-                        future.set_result(ack)
-                except Exception as e:
-                    if not future.done():
-                        future.set_exception(e)
-        except asyncio.CancelledError:
-            pass
-        finally:
-            self._reply_queues.pop(req_id, None)
-            self._reply_workers.pop(req_id, None)
-
-    async def _send_and_wait_ack(self, frame: dict) -> Optional[dict]:
-        """Send a frame and wait for the corresponding ACK."""
-        req_id = frame['headers']['req_id']
-        ack_future: asyncio.Future = asyncio.get_event_loop().create_future()
-        self._pending_acks[req_id] = ack_future
-
-        try:
-            await self._send_frame(frame)
-            result = await asyncio.wait_for(ack_future, timeout=self._reply_ack_timeout)
-            if result.get('errcode', 0) != 0:
-                await self.logger.warning(
-                    f'Reply ACK error: errcode={result.get("errcode")}, errmsg={result.get("errmsg")}'
-                )
-            return result
-        except asyncio.TimeoutError:
-            self._pending_acks.pop(req_id, None)
-            await self.logger.warning(f'Reply ACK timeout ({self._reply_ack_timeout}s) for req_id={req_id}')
-            return None
-
-    async def _send_frame(self, frame: dict):
-        """Send a JSON frame over the WebSocket connection."""
-        if self._ws and not self._ws.closed:
-            await self._ws.send_str(json.dumps(frame, ensure_ascii=False))
-
-    def _clear_pending_acks(self, reason: str):
-        """Reject all pending ACK futures on disconnection."""
-        for req_id, future in self._pending_acks.items():
-            if not future.done():
-                future.set_exception(ConnectionError(reason))
-        self._pending_acks.clear()

src/langbot/libs/wecom_api/api.py

@@ -4,7 +4,6 @@ import base64
 import binascii
 import httpx
 import traceback
-from urllib.parse import quote
 from quart import Quart
 import xml.etree.ElementTree as ET
 from typing import Callable, Dict, Any
@@ -68,31 +67,6 @@ class WecomClient:
                 await self.logger.error(f'获取accesstoken失败:{response.json()}')
                 raise Exception(f'未获取access token: {data}')
 
-    async def get_user_info(self, userid: str) -> dict:
-        """
-        Get user information by user ID using the application secret.
-
-        Args:
-            userid: The user ID to look up.
-
-        Returns:
-            dict: User information including 'name' field.
-        """
-        if not await self.check_access_token():
-            self.access_token = await self.get_access_token(self.secret)
-
-        url = self.base_url + '/user/get?access_token=' + self.access_token + '&userid=' + quote(userid)
-        async with httpx.AsyncClient() as client:
-            response = await client.get(url)
-            data = response.json()
-            if data.get('errcode') == 40014 or data.get('errcode') == 42001:
-                self.access_token = await self.get_access_token(self.secret)
-                return await self.get_user_info(userid)
-            if data.get('errcode', 0) != 0:
-                await self.logger.error(f'获取用户信息失败:{data}')
-                return {}
-            return data
-
     async def get_users(self):
         if not self.check_access_token_for_contacts():
             self.access_token_for_contacts = await self.get_access_token(self.secret_for_contacts)

src/langbot/libs/wecom_customer_service_api/api.py

@@ -10,7 +10,6 @@ from typing import Callable
 from .wecomcsevent import WecomCSEvent
 import langbot_plugin.api.entities.builtin.platform.message as platform_message
 import aiofiles
-import time
 
 
 class WecomCSClient:
@@ -35,10 +34,6 @@ class WecomCSClient:
         self.unified_mode = unified_mode
         self.app = Quart(__name__)
 
-        # Customer info cache: {external_userid: (info_dict, timestamp)}
-        self._customer_cache: dict[str, tuple[dict, float]] = {}
-        self._cache_ttl = 60  # Cache TTL in seconds (1 minute)
-
         # 只有在非统一模式下才注册独立路由
         if not self.unified_mode:
             self.app.add_url_rule(
@@ -383,53 +378,3 @@ class WecomCSClient:
     async def get_media_id(self, image: platform_message.Image):
         media_id = await self.upload_to_work(image=image)
         return media_id
-
-    async def get_customer_info(self, external_userid: str) -> dict | None:
-        """
-        Get customer information by external_userid with caching.
-
-        Uses a 1-minute cache to avoid repeated API calls for the same user.
-
-        Args:
-            external_userid: The external user ID of the customer.
-
-        Returns:
-            Customer info dict with 'nickname', 'avatar', etc., or None if not found.
-        """
-        # Check cache first
-        current_time = time.time()
-        if external_userid in self._customer_cache:
-            cached_info, cached_time = self._customer_cache[external_userid]
-            if current_time - cached_time < self._cache_ttl:
-                return cached_info
-
-        # Cache miss or expired, fetch from API
-        if not await self.check_access_token():
-            self.access_token = await self.get_access_token(self.secret)
-
-        url = f'{self.base_url}/kf/customer/batchget?access_token={self.access_token}'
-
-        payload = {
-            'external_userid_list': [external_userid],
-        }
-
-        async with httpx.AsyncClient() as client:
-            response = await client.post(url, json=payload)
-            data = response.json()
-
-            if data.get('errcode') in [40014, 42001]:
-                self.access_token = await self.get_access_token(self.secret)
-                return await self.get_customer_info(external_userid)
-
-            if data.get('errcode', 0) != 0:
-                if self.logger:
-                    await self.logger.warning(f'Failed to get customer info: {data}')
-                return None
-
-            customer_list = data.get('customer_list', [])
-            if customer_list:
-                customer_info = customer_list[0]
-                # Store in cache
-                self._customer_cache[external_userid] = (customer_info, current_time)
-                return customer_info
-            return None

src/langbot/pkg/api/http/controller/groups/files.py

@@ -13,9 +13,9 @@ from .. import group
 @group.group_class('files', '/api/v1/files')
 class FilesRouterGroup(group.RouterGroup):
     async def initialize(self) -> None:
-        @self.route('/image/<path:image_key>', methods=['GET'], auth_type=group.AuthType.NONE)
+        @self.route('/image/<image_key>', methods=['GET'], auth_type=group.AuthType.NONE)
         async def _(image_key: str) -> quart.Response:
-            if '..' in image_key or '\\' in image_key:
+            if '/' in image_key or '\\' in image_key:
                 return quart.Response(status=404)
 
             if not await self.ap.storage_mgr.storage_provider.exists(image_key):

src/langbot/pkg/api/http/controller/groups/knowledge/base.py

@@ -13,10 +13,7 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
 
             elif quart.request.method == 'POST':
                 json_data = await quart.request.json
-                try:
-                    knowledge_base_uuid = await self.ap.knowledge_service.create_knowledge_base(json_data)
-                except ValueError as e:
-                    return self.http_status(400, -1, str(e))
+                knowledge_base_uuid = await self.ap.knowledge_service.create_knowledge_base(json_data)
                 return self.success(data={'uuid': knowledge_base_uuid})
 
             return self.http_status(405, -1, 'Method not allowed')
@@ -42,7 +39,7 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
             elif quart.request.method == 'PUT':
                 json_data = await quart.request.json
                 await self.ap.knowledge_service.update_knowledge_base(knowledge_base_uuid, json_data)
-                return self.success(data={'uuid': knowledge_base_uuid})
+                return self.success({})
 
             elif quart.request.method == 'DELETE':
                 await self.ap.knowledge_service.delete_knowledge_base(knowledge_base_uuid)
@@ -68,12 +65,8 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
                 if not file_id:
                     return self.http_status(400, -1, 'File ID is required')
 
-                parser_plugin_id = json_data.get('parser_plugin_id')
-
                 # 调用服务层方法将文件与知识库关联
-                task_id = await self.ap.knowledge_service.store_file(
-                    knowledge_base_uuid, file_id, parser_plugin_id=parser_plugin_id
-                )
+                task_id = await self.ap.knowledge_service.store_file(knowledge_base_uuid, file_id)
                 return self.success(
                     {
                         'task_id': task_id,
@@ -97,13 +90,5 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
         async def retrieve_knowledge_base(knowledge_base_uuid: str) -> str:
             json_data = await quart.request.json
             query = json_data.get('query')
-
-            if not query or not query.strip():
-                return self.http_status(400, -1, 'Query is required and cannot be empty')
-
-            # Extract retrieval_settings to allow dynamic control over Knowledge Engine behavior (e.g. top_k, filters)
-            retrieval_settings = json_data.get('retrieval_settings', {})
-            results = await self.ap.knowledge_service.retrieve_knowledge_base(
-                knowledge_base_uuid, query, retrieval_settings
-            )
+            results = await self.ap.knowledge_service.retrieve_knowledge_base(knowledge_base_uuid, query)
             return self.success(data={'results': results})

src/langbot/pkg/api/http/controller/groups/knowledge/engines.py

@@ -1,45 +0,0 @@
-import quart
-from urllib.parse import unquote
-from ... import group
-
-
-@group.group_class('knowledge_engines', '/api/v1/knowledge/engines')
-class KnowledgeEnginesRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
-        async def list_knowledge_engines() -> quart.Response:
-            """List all available Knowledge Engines from plugins.
-
-            Returns a list of Knowledge Engines with their capabilities and configuration schemas.
-            This is used by the frontend to render the knowledge base creation wizard.
-            """
-            engines = await self.ap.knowledge_service.list_knowledge_engines()
-            return self.success(data={'engines': engines})
-
-        @self.route(
-            '/<path:plugin_id>/creation-schema', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY
-        )
-        async def get_engine_creation_schema(plugin_id: str) -> quart.Response:
-            """Get creation settings schema for a specific Knowledge Engine.
-
-            plugin_id is in 'author/name' format, captured via <path:> converter.
-            """
-            plugin_id = unquote(plugin_id)
-            if '/' not in plugin_id:
-                return self.http_status(400, -1, 'Invalid plugin_id format. Expected author/name.')
-            schema = await self.ap.knowledge_service.get_engine_creation_schema(plugin_id)
-            return self.success(data={'schema': schema})
-
-        @self.route(
-            '/<path:plugin_id>/retrieval-schema', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY
-        )
-        async def get_engine_retrieval_schema(plugin_id: str) -> quart.Response:
-            """Get retrieval settings schema for a specific Knowledge Engine.
-
-            plugin_id is in 'author/name' format, captured via <path:> converter.
-            """
-            plugin_id = unquote(plugin_id)
-            if '/' not in plugin_id:
-                return self.http_status(400, -1, 'Invalid plugin_id format. Expected author/name.')
-            schema = await self.ap.knowledge_service.get_engine_retrieval_schema(plugin_id)
-            return self.success(data={'schema': schema})

src/langbot/pkg/api/http/controller/groups/knowledge/external.py

@@ -0,0 +1,61 @@
+import quart
+from ... import group
+
+
+@group.group_class('external_knowledge_base', '/api/v1/knowledge/external-bases')
+class ExternalKnowledgeBaseRouterGroup(group.RouterGroup):
+    async def initialize(self) -> None:
+        @self.route('/retrievers', methods=['GET'])
+        async def list_knowledge_retrievers() -> quart.Response:
+            """List all available knowledge retrievers from plugins."""
+            retrievers = await self.ap.plugin_connector.list_knowledge_retrievers()
+            return self.success(data={'retrievers': retrievers})
+
+        @self.route('', methods=['POST', 'GET'])
+        async def handle_external_knowledge_bases() -> quart.Response:
+            if quart.request.method == 'GET':
+                external_kbs = await self.ap.external_kb_service.get_external_knowledge_bases()
+                return self.success(data={'bases': external_kbs})
+
+            elif quart.request.method == 'POST':
+                json_data = await quart.request.json
+                kb_uuid = await self.ap.external_kb_service.create_external_knowledge_base(json_data)
+                return self.success(data={'uuid': kb_uuid})
+
+            return self.http_status(405, -1, 'Method not allowed')
+
+        @self.route(
+            '/<kb_uuid>',
+            methods=['GET', 'DELETE', 'PUT'],
+        )
+        async def handle_specific_external_knowledge_base(kb_uuid: str) -> quart.Response:
+            if quart.request.method == 'GET':
+                external_kb = await self.ap.external_kb_service.get_external_knowledge_base(kb_uuid)
+
+                if external_kb is None:
+                    return self.http_status(404, -1, 'external knowledge base not found')
+
+                return self.success(
+                    data={
+                        'base': external_kb,
+                    }
+                )
+
+            elif quart.request.method == 'PUT':
+                json_data = await quart.request.json
+                await self.ap.external_kb_service.update_external_knowledge_base(kb_uuid, json_data)
+                return self.success({})
+
+            elif quart.request.method == 'DELETE':
+                await self.ap.external_kb_service.delete_external_knowledge_base(kb_uuid)
+                return self.success({})
+
+        @self.route(
+            '/<kb_uuid>/retrieve',
+            methods=['POST'],
+        )
+        async def retrieve_external_knowledge_base(kb_uuid: str) -> str:
+            json_data = await quart.request.json
+            query = json_data.get('query')
+            results = await self.ap.external_kb_service.retrieve_external_knowledge_base(kb_uuid, query)
+            return self.success(data={'results': results})

src/langbot/pkg/api/http/controller/groups/knowledge/migration.py

@@ -1,372 +0,0 @@
-import asyncio
-import json
-
-import httpx
-import quart
-import sqlalchemy
-
-from ... import group
-from ......core import taskmgr
-from ......entity.persistence import metadata as persistence_metadata
-from langbot_plugin.runtime.plugin.mgr import PluginInstallSource
-
-LANGRAG_PLUGIN_AUTHOR = 'langbot-team'
-LANGRAG_PLUGIN_NAME = 'LangRAG'
-LANGRAG_PLUGIN_ID = f'{LANGRAG_PLUGIN_AUTHOR}/{LANGRAG_PLUGIN_NAME}'
-DEFAULT_SPACE_URL = 'https://space.langbot.app'
-
-# Old Retriever plugin_name -> New Connector plugin_name
-EXTERNAL_PLUGIN_NAME_MAPPING = {
-    'DifyDatasetsRetriever': 'DifyDatasetsConnector',
-    'RAGFlowRetriever': 'RAGFlowConnector',
-    'FastGPTRetriever': 'FastGPTConnector',
-}
-
-# Per-plugin: which old retriever_config fields belong to creation_settings.
-# Remaining fields go to retrieval_settings.
-# None means ALL fields go to creation_settings (no retrieval_schema).
-EXTERNAL_PLUGIN_CREATION_FIELDS: dict[str, set[str] | None] = {
-    'langbot-team/DifyDatasetsConnector': {'api_base_url', 'dify_apikey', 'dataset_id'},
-    'langbot-team/RAGFlowConnector': {'api_base_url', 'api_key', 'dataset_ids'},
-    'langbot-team/FastGPTConnector': None,  # all fields -> creation_settings
-}
-
-
-@group.group_class('knowledge/migration', '/api/v1/knowledge/migration')
-class KnowledgeMigrationRouterGroup(group.RouterGroup):
-    async def _get_migration_flag(self) -> bool:
-        """Check if rag_plugin_migration_needed flag is set."""
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_metadata.Metadata).where(
-                persistence_metadata.Metadata.key == 'rag_plugin_migration_needed'
-            )
-        )
-        row = result.first()
-        return row is not None and row.value == 'true'
-
-    async def _set_migration_flag(self, value: str):
-        """Set rag_plugin_migration_needed flag."""
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.update(persistence_metadata.Metadata)
-            .where(persistence_metadata.Metadata.key == 'rag_plugin_migration_needed')
-            .values(value=value)
-        )
-
-    async def _table_exists(self, table_name: str) -> bool:
-        """Check if a table exists."""
-        if self.ap.persistence_mgr.db.name == 'postgresql':
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text(
-                    'SELECT EXISTS (SELECT FROM information_schema.tables WHERE table_name = :table_name);'
-                ).bindparams(table_name=table_name)
-            )
-            return result.scalar()
-        else:
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text("SELECT name FROM sqlite_master WHERE type='table' AND name=:table_name;").bindparams(
-                    table_name=table_name
-                )
-            )
-            return result.first() is not None
-
-    async def _install_plugin_from_marketplace(
-        self, plugin_id: str, task_context: taskmgr.TaskContext, space_url: str
-    ) -> None:
-        """Install a single plugin from the marketplace."""
-        p_author, p_name = plugin_id.split('/', 1)
-        self.ap.logger.info(f'RAG migration: installing plugin {plugin_id} from marketplace...')
-        task_context.trace(f'Installing plugin {plugin_id} from marketplace...')
-
-        async with httpx.AsyncClient(trust_env=True, timeout=15) as client:
-            resp = await client.get(f'{space_url}/api/v1/marketplace/plugins/{p_author}/{p_name}')
-            resp.raise_for_status()
-            p_data = resp.json().get('data', {}).get('plugin', {})
-            p_version = p_data.get('latest_version')
-            if not p_version:
-                raise Exception(f'Could not determine latest version for {plugin_id}')
-
-        await self.ap.plugin_connector.install_plugin(
-            PluginInstallSource.MARKETPLACE,
-            {
-                'plugin_author': p_author,
-                'plugin_name': p_name,
-                'plugin_version': p_version,
-            },
-            task_context=task_context,
-        )
-        self.ap.logger.info(f'RAG migration: plugin {plugin_id} install request sent.')
-
-    async def _execute_rag_migration(self, task_context: taskmgr.TaskContext, install_plugin: bool = True):
-        """Execute RAG migration: install required plugins and restore backup data."""
-        warnings = []
-
-        # Collect all plugins we need: LangRAG (always) + connector plugins (from external KBs)
-        needed_plugins: dict[str, str] = {
-            LANGRAG_PLUGIN_ID: LANGRAG_PLUGIN_NAME,
-        }
-
-        has_external = await self._table_exists('external_knowledge_bases')
-        if has_external:
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('SELECT DISTINCT plugin_author, plugin_name FROM external_knowledge_bases;')
-            )
-            for row in result.fetchall():
-                plugin_author = row[0] or ''
-                plugin_name = row[1] or ''
-                mapped_name = EXTERNAL_PLUGIN_NAME_MAPPING.get(plugin_name, plugin_name)
-                plugin_id = f'{plugin_author}/{mapped_name}'
-                if plugin_id not in needed_plugins:
-                    needed_plugins[plugin_id] = mapped_name
-
-        self.ap.logger.info(f'RAG migration: plugins needed: {list(needed_plugins.keys())}')
-
-        if install_plugin:
-            # Step 1: Install all required plugins from marketplace
-            task_context.trace('Installing required plugins...', action='install-plugin')
-            space_url = self.ap.instance_config.data.get('space', {}).get('url', DEFAULT_SPACE_URL).rstrip('/')
-
-            for plugin_id in needed_plugins:
-                try:
-                    await self._install_plugin_from_marketplace(plugin_id, task_context, space_url)
-                except Exception as e:
-                    self.ap.logger.warning(f'RAG migration: plugin {plugin_id} install returned: {e}')
-                    task_context.trace(f'Plugin install note ({plugin_id}): {e}')
-
-            # Step 2: Wait for all plugins to become available as knowledge engines
-            task_context.trace(
-                f'Waiting for plugins to become available: {list(needed_plugins.keys())}...',
-                action='wait-plugin',
-            )
-            max_retries = 30
-            engine_id_set: set[str] = set()
-            for i in range(max_retries):
-                try:
-                    engines = await self.ap.plugin_connector.list_knowledge_engines()
-                    engine_id_set = {e.get('plugin_id') for e in engines}
-                except Exception:
-                    pass
-                if all(pid in engine_id_set for pid in needed_plugins):
-                    self.ap.logger.info(f'RAG migration: all plugins ready: {engine_id_set}')
-                    task_context.trace('All required plugins are ready.')
-                    break
-                if i == max_retries - 1:
-                    still_missing = [pid for pid in needed_plugins if pid not in engine_id_set]
-                    warning = f'Plugin(s) {still_missing} did not become available after {max_retries} retries'
-                    self.ap.logger.warning(f'RAG migration: {warning}')
-                    warnings.append(warning)
-                    task_context.trace(warning)
-                await asyncio.sleep(2)
-        else:
-            try:
-                engines = await self.ap.plugin_connector.list_knowledge_engines()
-                engine_id_set = {e.get('plugin_id') for e in engines}
-            except Exception:
-                engine_id_set = set()
-
-        # Step 3: Restore internal knowledge bases from backup
-        task_context.trace('Restoring internal knowledge bases...', action='restore-internal')
-        if await self._table_exists('knowledge_bases_backup'):
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('SELECT * FROM knowledge_bases_backup;')
-            )
-            rows = result.fetchall()
-            columns = result.keys()
-
-            for row in rows:
-                row_dict = dict(zip(columns, row))
-                kb_uuid = row_dict.get('uuid')
-                name = row_dict.get('name', 'Untitled')
-                description = row_dict.get('description', '')
-                emoji = row_dict.get('emoji', '\U0001f4da')
-                embedding_model_uuid = row_dict.get('embedding_model_uuid', '')
-                top_k = row_dict.get('top_k', 5)
-                created_at = row_dict.get('created_at')
-                updated_at = row_dict.get('updated_at')
-
-                creation_settings = json.dumps({'embedding_model_uuid': embedding_model_uuid})
-                retrieval_settings = json.dumps({'top_k': top_k})
-
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'INSERT INTO knowledge_bases '
-                        '(uuid, name, description, emoji, created_at, updated_at, '
-                        'knowledge_engine_plugin_id, collection_id, creation_settings, retrieval_settings) '
-                        'VALUES (:uuid, :name, :description, :emoji, :created_at, :updated_at, '
-                        ':plugin_id, :collection_id, :creation_settings, :retrieval_settings);'
-                    ).bindparams(
-                        uuid=kb_uuid,
-                        name=name,
-                        description=description,
-                        emoji=emoji,
-                        created_at=created_at,
-                        updated_at=updated_at,
-                        plugin_id=LANGRAG_PLUGIN_ID,
-                        collection_id=kb_uuid,
-                        creation_settings=creation_settings,
-                        retrieval_settings=retrieval_settings,
-                    )
-                )
-
-                try:
-                    config = {'embedding_model_uuid': embedding_model_uuid}
-                    await self.ap.plugin_connector.rag_on_kb_create(LANGRAG_PLUGIN_ID, kb_uuid, config)
-                    task_context.trace(f'Restored internal KB: {name} ({kb_uuid})')
-                except Exception as e:
-                    warning = f'Failed to notify plugin for KB {name} ({kb_uuid}): {e}'
-                    warnings.append(warning)
-                    task_context.trace(warning)
-
-            await self.ap.rag_mgr.load_knowledge_bases_from_db()
-
-        # Step 4: Restore external knowledge bases
-        task_context.trace('Restoring external knowledge bases...', action='restore-external')
-        if has_external:
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('SELECT * FROM external_knowledge_bases;')
-            )
-            rows = result.fetchall()
-            columns = result.keys()
-
-            self.ap.logger.info(
-                f'RAG migration: {len(rows)} external KB(s) to restore. Available engines: {engine_id_set}'
-            )
-            task_context.trace(f'Found {len(rows)} external KB(s). Available engines: {engine_id_set}')
-
-            for row in rows:
-                row_dict = dict(zip(columns, row))
-                kb_uuid = row_dict.get('uuid')
-                name = row_dict.get('name', 'Untitled')
-                description = row_dict.get('description', '')
-                emoji = row_dict.get('emoji', '\U0001f517')
-                plugin_author = row_dict.get('plugin_author', '')
-                plugin_name = row_dict.get('plugin_name', '')
-                retriever_config = row_dict.get('retriever_config', {})
-                created_at = row_dict.get('created_at')
-
-                mapped_plugin_name = EXTERNAL_PLUGIN_NAME_MAPPING.get(plugin_name, plugin_name)
-                external_plugin_id = f'{plugin_author}/{mapped_plugin_name}'
-
-                self.ap.logger.info(
-                    f'RAG migration: processing external KB "{name}" ({kb_uuid}), '
-                    f'plugin: {plugin_author}/{plugin_name} -> {external_plugin_id}'
-                )
-
-                if isinstance(retriever_config, str):
-                    try:
-                        retriever_config = json.loads(retriever_config)
-                    except (json.JSONDecodeError, TypeError):
-                        retriever_config = {}
-
-                creation_fields = EXTERNAL_PLUGIN_CREATION_FIELDS.get(external_plugin_id)
-                if creation_fields is None:
-                    creation_settings_dict = retriever_config
-                    retrieval_settings_dict = {}
-                else:
-                    creation_settings_dict = {k: v for k, v in retriever_config.items() if k in creation_fields}
-                    retrieval_settings_dict = {k: v for k, v in retriever_config.items() if k not in creation_fields}
-
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'INSERT INTO knowledge_bases '
-                        '(uuid, name, description, emoji, created_at, updated_at, '
-                        'knowledge_engine_plugin_id, collection_id, creation_settings, retrieval_settings) '
-                        'VALUES (:uuid, :name, :description, :emoji, :created_at, :updated_at, '
-                        ':plugin_id, :collection_id, :creation_settings, :retrieval_settings);'
-                    ).bindparams(
-                        uuid=kb_uuid,
-                        name=name,
-                        description=description,
-                        emoji=emoji,
-                        created_at=created_at,
-                        updated_at=created_at,
-                        plugin_id=external_plugin_id,
-                        collection_id=kb_uuid,
-                        creation_settings=json.dumps(creation_settings_dict),
-                        retrieval_settings=json.dumps(retrieval_settings_dict),
-                    )
-                )
-
-                if external_plugin_id not in engine_id_set:
-                    warning = (
-                        f'External KB "{name}" ({kb_uuid}) record saved, but plugin {external_plugin_id} '
-                        f'is not installed yet. Install the connector plugin to use it.'
-                    )
-                    warnings.append(warning)
-                    task_context.trace(warning)
-                else:
-                    try:
-                        await self.ap.plugin_connector.rag_on_kb_create(
-                            external_plugin_id, kb_uuid, creation_settings_dict
-                        )
-                        task_context.trace(f'Restored external KB: {name} ({kb_uuid})')
-                    except Exception as e:
-                        warning = f'Failed to notify plugin for external KB {name} ({kb_uuid}): {e}'
-                        warnings.append(warning)
-                        task_context.trace(warning)
-
-            await self.ap.rag_mgr.load_knowledge_bases_from_db()
-
-        # Step 5: Clear migration flag
-        await self._set_migration_flag('false')
-        task_context.trace('RAG migration completed.', action='done')
-
-        if warnings:
-            task_context.trace(f'Completed with {len(warnings)} warning(s).')
-
-    async def initialize(self) -> None:
-        @self.route('/status', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            needed = await self._get_migration_flag()
-
-            internal_kb_count = 0
-            external_kb_count = 0
-
-            if needed:
-                if await self._table_exists('knowledge_bases_backup'):
-                    result = await self.ap.persistence_mgr.execute_async(
-                        sqlalchemy.text('SELECT COUNT(*) FROM knowledge_bases_backup;')
-                    )
-                    internal_kb_count = result.scalar() or 0
-
-                if await self._table_exists('external_knowledge_bases'):
-                    result = await self.ap.persistence_mgr.execute_async(
-                        sqlalchemy.text('SELECT COUNT(*) FROM external_knowledge_bases;')
-                    )
-                    external_kb_count = result.scalar() or 0
-
-            return self.success(
-                data={
-                    'needed': needed,
-                    'internal_kb_count': internal_kb_count,
-                    'external_kb_count': external_kb_count,
-                }
-            )
-
-        @self.route('/execute', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            needed = await self._get_migration_flag()
-            if not needed:
-                return self.http_status(400, -1, 'RAG migration is not needed')
-
-            data = await quart.request.get_json(silent=True) or {}
-            install_plugin = data.get('install_plugin', True)
-
-            ctx = taskmgr.TaskContext.new()
-            wrapper = self.ap.task_mgr.create_user_task(
-                self._execute_rag_migration(task_context=ctx, install_plugin=install_plugin),
-                kind='rag-migration',
-                name='rag-migration-execute',
-                label='Migrating knowledge bases to plugin architecture',
-                context=ctx,
-            )
-
-            return self.success(data={'task_id': wrapper.id})
-
-        @self.route('/dismiss', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            needed = await self._get_migration_flag()
-            if not needed:
-                return self.http_status(400, -1, 'RAG migration is not needed')
-
-            await self._set_migration_flag('false')
-            return self.success()

src/langbot/pkg/api/http/controller/groups/knowledge/parsers.py

@@ -1,16 +0,0 @@
-import quart
-from ... import group
-
-
-@group.group_class('parsers', '/api/v1/knowledge/parsers')
-class ParsersRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
-        async def list_parsers() -> quart.Response:
-            """List all available parsers from plugins.
-
-            Optional query parameter `mime_type` to filter parsers by supported MIME type.
-            """
-            mime_type = quart.request.args.get('mime_type')
-            parsers = await self.ap.knowledge_service.list_parsers(mime_type)
-            return self.success(data={'parsers': parsers})

src/langbot/pkg/api/http/controller/groups/monitoring.py

@@ -52,7 +52,6 @@ class MonitoringRouterGroup(group.RouterGroup):
             # Parse query parameters
             bot_ids = quart.request.args.getlist('botId')
             pipeline_ids = quart.request.args.getlist('pipelineId')
-            session_ids = quart.request.args.getlist('sessionId')
             start_time_str = quart.request.args.get('startTime')
             end_time_str = quart.request.args.get('endTime')
             limit = int(quart.request.args.get('limit', 100))
@@ -65,7 +64,6 @@ class MonitoringRouterGroup(group.RouterGroup):
             messages, total = await self.ap.monitoring_service.get_messages(
                 bot_ids=bot_ids if bot_ids else None,
                 pipeline_ids=pipeline_ids if pipeline_ids else None,
-                session_ids=session_ids if session_ids else None,
                 start_time=start_time,
                 end_time=end_time,
                 limit=limit,

src/langbot/pkg/api/http/controller/groups/pipelines/pipelines.py

@@ -68,7 +68,7 @@ class PipelinesRouterGroup(group.RouterGroup):
                     return self.http_status(404, -1, 'pipeline not found')
 
                 # Only include plugins with pipeline-related components (Command, EventListener, Tool)
-                # Plugins that only have KnowledgeEngine components are not suitable for pipeline extensions
+                # Plugins that only have KnowledgeRetriever components are not suitable for pipeline extensions
                 pipeline_component_kinds = ['Command', 'EventListener', 'Tool']
                 plugins = await self.ap.plugin_connector.list_plugins(component_kinds=pipeline_component_kinds)
                 mcp_servers = await self.ap.mcp_service.get_mcp_servers(contain_runtime_info=True)

src/langbot/pkg/api/http/controller/groups/survey.py

@@ -1,47 +0,0 @@
-import quart
-
-from .. import group
-
-
-@group.group_class('survey', '/api/v1/survey')
-class SurveyRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('/pending', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def _get_pending() -> str:
-            """Get pending survey for the frontend to display."""
-            survey = self.ap.survey.get_pending_survey() if self.ap.survey else None
-            return self.success(data={'survey': survey})
-
-        @self.route('/respond', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _respond() -> str:
-            """Submit survey response."""
-            json_data = await quart.request.json
-            survey_id = json_data.get('survey_id')
-            answers = json_data.get('answers', {})
-            completed = json_data.get('completed', True)
-
-            if not survey_id:
-                return self.fail(1, 'survey_id required')
-
-            if self.ap.survey:
-                ok = await self.ap.survey.submit_response(survey_id, answers, completed)
-                if ok:
-                    return self.success()
-                return self.fail(2, 'Failed to submit response')
-            return self.fail(3, 'Survey not available')
-
-        @self.route('/dismiss', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _dismiss() -> str:
-            """Dismiss survey."""
-            json_data = await quart.request.json
-            survey_id = json_data.get('survey_id')
-
-            if not survey_id:
-                return self.fail(1, 'survey_id required')
-
-            if self.ap.survey:
-                ok = await self.ap.survey.dismiss_survey(survey_id)
-                if ok:
-                    return self.success()
-                return self.fail(2, 'Failed to dismiss')
-            return self.fail(3, 'Survey not available')

src/langbot/pkg/api/http/controller/main.py

@@ -105,28 +105,6 @@ class HTTPController:
             ):
                 if os.path.exists(os.path.join(frontend_path, path + '.html')):
                     path += '.html'
-                elif path.startswith('home/'):
-                    # SPA fallback for /home/* sub-routes.
-                    # Entity detail views use query params (e.g. /home/bots?id=uuid),
-                    # so the pre-rendered list page is served directly via path + '.html'.
-                    # This fallback handles any remaining unmatched sub-paths.
-                    segments = path.rstrip('/').split('/')
-
-                    # Walk up parent segments looking for matching .html files
-                    for i in range(len(segments) - 1, 0, -1):
-                        parent_path = '/'.join(segments[:i]) + '.html'
-                        if os.path.exists(os.path.join(frontend_path, parent_path)):
-                            response = await quart.send_from_directory(frontend_path, parent_path, mimetype='text/html')
-                            response.headers['Cache-Control'] = 'no-cache, no-store, must-revalidate'
-                            response.headers['Pragma'] = 'no-cache'
-                            response.headers['Expires'] = '0'
-                            return response
-                    # Final fallback to index.html for /home/* routes
-                    response = await quart.send_from_directory(frontend_path, 'index.html', mimetype='text/html')
-                    response.headers['Cache-Control'] = 'no-cache, no-store, must-revalidate'
-                    response.headers['Pragma'] = 'no-cache'
-                    response.headers['Expires'] = '0'
-                    return response
                 else:
                     return await quart.send_from_directory(frontend_path, '404.html')
 

src/langbot/pkg/api/http/service/bot.py

@@ -70,17 +70,12 @@ class BotService:
             'lark',
         ]:
             webhook_prefix = self.ap.instance_config.data['api'].get('webhook_prefix', 'http://127.0.0.1:5300')
-            extra_webhook_prefix = self.ap.instance_config.data['api'].get('extra_webhook_prefix', '')
             webhook_url = f'/bots/{bot_uuid}'
             adapter_runtime_values['webhook_url'] = webhook_url
             adapter_runtime_values['webhook_full_url'] = f'{webhook_prefix}{webhook_url}'
-            adapter_runtime_values['extra_webhook_full_url'] = (
-                f'{extra_webhook_prefix}{webhook_url}' if extra_webhook_prefix else ''
-            )
         else:
             adapter_runtime_values['webhook_url'] = None
             adapter_runtime_values['webhook_full_url'] = None
-            adapter_runtime_values['extra_webhook_full_url'] = None
 
         persistence_bot['adapter_runtime_values'] = adapter_runtime_values
 

src/langbot/pkg/api/http/service/external_kb.py

@@ -0,0 +1,80 @@
+from __future__ import annotations
+
+from ....core import app
+import sqlalchemy
+from langbot.pkg.entity.persistence import rag as persistence_rag
+import uuid
+
+
+class ExternalKBService:
+    """External KB service"""
+
+    ap: app.Application
+
+    def __init__(self, ap: app.Application) -> None:
+        self.ap = ap
+
+    # External Knowledge Base methods
+    async def get_external_knowledge_bases(self) -> list[dict]:
+        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_rag.ExternalKnowledgeBase))
+        external_kbs = result.all()
+        return [
+            self.ap.persistence_mgr.serialize_model(persistence_rag.ExternalKnowledgeBase, external_kb)
+            for external_kb in external_kbs
+        ]
+
+    async def get_external_knowledge_base(self, kb_uuid: str) -> dict | None:
+        result = await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.select(persistence_rag.ExternalKnowledgeBase).where(
+                persistence_rag.ExternalKnowledgeBase.uuid == kb_uuid
+            )
+        )
+        external_kb = result.first()
+        if external_kb is None:
+            return None
+        return self.ap.persistence_mgr.serialize_model(persistence_rag.ExternalKnowledgeBase, external_kb)
+
+    async def create_external_knowledge_base(self, kb_data: dict) -> str:
+        kb_data['uuid'] = str(uuid.uuid4())
+        await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.insert(persistence_rag.ExternalKnowledgeBase).values(kb_data)
+        )
+
+        kb = await self.get_external_knowledge_base(kb_data['uuid'])
+
+        await self.ap.rag_mgr.load_external_knowledge_base(kb)
+
+        return kb_data['uuid']
+
+    async def retrieve_external_knowledge_base(self, kb_uuid: str, query: str) -> list[dict]:
+        """Retrieve external knowledge base"""
+        runtime_kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
+        if runtime_kb is None:
+            raise Exception('Knowledge base not found')
+        return [
+            result.model_dump() for result in await runtime_kb.retrieve(query, 5)
+        ]  # top_k is just a placeholder for external knowledge base
+
+    async def update_external_knowledge_base(self, kb_uuid: str, kb_data: dict) -> None:
+        if 'uuid' in kb_data:
+            del kb_data['uuid']
+
+        await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.update(persistence_rag.ExternalKnowledgeBase)
+            .values(kb_data)
+            .where(persistence_rag.ExternalKnowledgeBase.uuid == kb_uuid)
+        )
+        await self.ap.rag_mgr.remove_knowledge_base_from_runtime(kb_uuid)
+
+        kb = await self.get_external_knowledge_base(kb_uuid)
+
+        await self.ap.rag_mgr.load_external_knowledge_base(kb)
+
+    async def delete_external_knowledge_base(self, kb_uuid: str) -> None:
+        await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.delete(persistence_rag.ExternalKnowledgeBase).where(
+                persistence_rag.ExternalKnowledgeBase.uuid == kb_uuid
+            )
+        )
+
+        await self.ap.rag_mgr.delete_knowledge_base(kb_uuid)

src/langbot/pkg/api/http/service/knowledge.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import uuid
 import sqlalchemy
 
 from ....core import app
@@ -16,77 +17,64 @@ class KnowledgeService:
 
     async def get_knowledge_bases(self) -> list[dict]:
         """获取所有知识库"""
-        return await self.ap.rag_mgr.get_all_knowledge_base_details()
+        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_rag.KnowledgeBase))
+        knowledge_bases = result.all()
+        return [
+            self.ap.persistence_mgr.serialize_model(persistence_rag.KnowledgeBase, knowledge_base)
+            for knowledge_base in knowledge_bases
+        ]
 
     async def get_knowledge_base(self, kb_uuid: str) -> dict | None:
         """获取知识库"""
-        return await self.ap.rag_mgr.get_knowledge_base_details(kb_uuid)
+        result = await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.select(persistence_rag.KnowledgeBase).where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
+        )
+        knowledge_base = result.first()
+        if knowledge_base is None:
+            return None
+        return self.ap.persistence_mgr.serialize_model(persistence_rag.KnowledgeBase, knowledge_base)
 
     async def create_knowledge_base(self, kb_data: dict) -> str:
         """创建知识库"""
-        # In new architecture, we delegate entirely to RAGManager which uses plugins.
-        # Legacy internal KB creation is removed.
+        kb_data['uuid'] = str(uuid.uuid4())
+        await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_rag.KnowledgeBase).values(kb_data))
 
-        knowledge_engine_plugin_id = kb_data.get('knowledge_engine_plugin_id')
-        if not knowledge_engine_plugin_id:
-            raise ValueError('knowledge_engine_plugin_id is required')
+        kb = await self.get_knowledge_base(kb_data['uuid'])
 
-        kb = await self.ap.rag_mgr.create_knowledge_base(
-            name=kb_data.get('name', 'Untitled'),
-            knowledge_engine_plugin_id=knowledge_engine_plugin_id,
-            creation_settings=kb_data.get('creation_settings', {}),
-            retrieval_settings=kb_data.get('retrieval_settings', {}),
-            description=kb_data.get('description', ''),
-        )
-        return kb.uuid
+        await self.ap.rag_mgr.load_knowledge_base(kb)
+
+        return kb_data['uuid']
 
     async def update_knowledge_base(self, kb_uuid: str, kb_data: dict) -> None:
         """更新知识库"""
-        # Filter to only mutable fields
-        filtered_data = {k: v for k, v in kb_data.items() if k in persistence_rag.KnowledgeBase.MUTABLE_FIELDS}
+        if 'uuid' in kb_data:
+            del kb_data['uuid']
 
-        if not filtered_data:
-            return
+        if 'embedding_model_uuid' in kb_data:
+            del kb_data['embedding_model_uuid']
 
         await self.ap.persistence_mgr.execute_async(
             sqlalchemy.update(persistence_rag.KnowledgeBase)
-            .values(filtered_data)
+            .values(kb_data)
             .where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
         )
         await self.ap.rag_mgr.remove_knowledge_base_from_runtime(kb_uuid)
 
         kb = await self.get_knowledge_base(kb_uuid)
-        if kb is None:
-            raise Exception('Knowledge base not found after update')
 
         await self.ap.rag_mgr.load_knowledge_base(kb)
 
-    async def _check_doc_capability(self, kb_uuid: str, operation: str) -> None:
-        """Check if the KB's Knowledge Engine supports document operations.
-
-        Args:
-            kb_uuid: Knowledge base UUID.
-            operation: Human-readable operation name for error messages.
-
-        Raises:
-            Exception: If the KB does not support doc_ingestion.
-        """
-        kb_info = await self.ap.rag_mgr.get_knowledge_base_details(kb_uuid)
-        if not kb_info:
-            raise Exception('Knowledge base not found')
-        capabilities = kb_info.get('knowledge_engine', {}).get('capabilities', [])
-        if 'doc_ingestion' not in capabilities:
-            raise Exception(f'This knowledge base does not support {operation}')
-
-    async def store_file(self, kb_uuid: str, file_id: str, parser_plugin_id: str | None = None) -> str:
+    async def store_file(self, kb_uuid: str, file_id: str) -> int:
         """存储文件"""
+        # await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_rag.File).values(kb_id=kb_uuid, file_id=file_id))
+        # await self.ap.rag_mgr.store_file(file_id)
         runtime_kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
         if runtime_kb is None:
             raise Exception('Knowledge base not found')
-
-        await self._check_doc_capability(kb_uuid, 'document upload')
-
-        result = await runtime_kb.store_file(file_id, parser_plugin_id=parser_plugin_id)
+        # Only internal KBs support file storage
+        if runtime_kb.get_type() != 'internal':
+            raise Exception('Only internal knowledge bases support file storage')
+        result = await runtime_kb.store_file(file_id)
 
         # Update the KB's updated_at timestamp
         await self.ap.persistence_mgr.execute_async(
@@ -97,18 +85,14 @@ class KnowledgeService:
 
         return result
 
-    async def retrieve_knowledge_base(
-        self, kb_uuid: str, query: str, retrieval_settings: dict | None = None
-    ) -> list[dict]:
+    async def retrieve_knowledge_base(self, kb_uuid: str, query: str) -> list[dict]:
         """检索知识库"""
         runtime_kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
         if runtime_kb is None:
             raise Exception('Knowledge base not found')
-
-        # Pass retrieval_settings
-        results = await runtime_kb.retrieve(query, settings=retrieval_settings)
-
-        return [result.model_dump() for result in results]
+        return [
+            result.model_dump() for result in await runtime_kb.retrieve(query, runtime_kb.knowledge_base_entity.top_k)
+        ]
 
     async def get_files_by_knowledge_base(self, kb_uuid: str) -> list[dict]:
         """获取知识库文件"""
@@ -123,9 +107,9 @@ class KnowledgeService:
         runtime_kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
         if runtime_kb is None:
             raise Exception('Knowledge base not found')
-
-        await self._check_doc_capability(kb_uuid, 'document deletion')
-
+        # Only internal KBs support file deletion
+        if runtime_kb.get_type() != 'internal':
+            raise Exception('Only internal knowledge bases support file deletion')
         await runtime_kb.delete_file(file_id)
 
         # Update the KB's updated_at timestamp
@@ -137,14 +121,13 @@ class KnowledgeService:
 
     async def delete_knowledge_base(self, kb_uuid: str) -> None:
         """删除知识库"""
-        # Delete from DB first to commit the deletion, then clean up runtime/plugin (best-effort)
+        await self.ap.rag_mgr.delete_knowledge_base(kb_uuid)
+
         await self.ap.persistence_mgr.execute_async(
             sqlalchemy.delete(persistence_rag.KnowledgeBase).where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
         )
 
         # delete files
-        # NOTE: Chunk cleanup is for legacy (pre-plugin) KBs that stored chunks locally.
-        # For plugin-based Knowledge Engines, the Chunk table is not populated, so this is a no-op.
         files = await self.ap.persistence_mgr.execute_async(
             sqlalchemy.select(persistence_rag.File).where(persistence_rag.File.kb_id == kb_uuid)
         )
@@ -157,53 +140,3 @@ class KnowledgeService:
             await self.ap.persistence_mgr.execute_async(
                 sqlalchemy.delete(persistence_rag.File).where(persistence_rag.File.uuid == file.uuid)
             )
-
-        # Remove from runtime and notify plugin (best-effort, DB is already cleaned up)
-        await self.ap.rag_mgr.delete_knowledge_base(kb_uuid)
-
-    # ================= Knowledge Engine Discovery =================
-
-    async def list_knowledge_engines(self) -> list[dict]:
-        """List all available Knowledge Engines from plugins."""
-        engines = []
-
-        if not self.ap.plugin_connector.is_enable_plugin:
-            return engines
-
-        # Get KnowledgeEngine plugins
-        try:
-            knowledge_engines = await self.ap.plugin_connector.list_knowledge_engines()
-            engines.extend(knowledge_engines)
-        except Exception as e:
-            self.ap.logger.warning(f'Failed to list Knowledge Engines from plugins: {e}')
-
-        return engines
-
-    async def list_parsers(self, mime_type: str | None = None) -> list[dict]:
-        """List available parsers, optionally filtered by MIME type."""
-        if not self.ap.plugin_connector.is_enable_plugin:
-            return []
-        try:
-            parsers = await self.ap.plugin_connector.list_parsers()
-            if mime_type:
-                parsers = [p for p in parsers if mime_type in p.get('supported_mime_types', [])]
-            return parsers
-        except Exception as e:
-            self.ap.logger.warning(f'Failed to list parsers: {e}')
-            return []
-
-    async def get_engine_creation_schema(self, plugin_id: str) -> dict:
-        """Get creation settings schema for a specific Knowledge Engine."""
-        try:
-            return await self.ap.plugin_connector.get_rag_creation_schema(plugin_id)
-        except Exception as e:
-            self.ap.logger.warning(f'Failed to get creation schema for {plugin_id}: {e}')
-            return {}
-
-    async def get_engine_retrieval_schema(self, plugin_id: str) -> dict:
-        """Get retrieval settings schema for a specific Knowledge Engine."""
-        try:
-            return await self.ap.plugin_connector.get_rag_retrieval_schema(plugin_id)
-        except Exception as e:
-            self.ap.logger.warning(f'Failed to get retrieval schema for {plugin_id}: {e}')
-            return {}

src/langbot/pkg/api/http/service/model.py

@@ -105,16 +105,11 @@ class LLMModelsService:
                 )
             )
             pipeline = result.first()
-            if pipeline is not None:
-                model_config = pipeline.config.get('ai', {}).get('local-agent', {}).get('model', {})
-                if not model_config.get('primary', ''):
-                    pipeline_config = pipeline.config
-                    pipeline_config['ai']['local-agent']['model'] = {
-                        'primary': model_data['uuid'],
-                        'fallbacks': [],
-                    }
-                    pipeline_data = {'config': pipeline_config}
-                    await self.ap.pipeline_service.update_pipeline(pipeline.uuid, pipeline_data)
+            if pipeline is not None and pipeline.config['ai']['local-agent']['model'] == '':
+                pipeline_config = pipeline.config
+                pipeline_config['ai']['local-agent']['model'] = model_data['uuid']
+                pipeline_data = {'config': pipeline_config}
+                await self.ap.pipeline_service.update_pipeline(pipeline.uuid, pipeline_data)
 
         return model_data['uuid']
 

src/langbot/pkg/api/http/service/monitoring.py

@@ -16,57 +16,6 @@ class MonitoringService:
     def __init__(self, ap: app.Application) -> None:
         self.ap = ap
 
-    # ========== Cleanup Methods ==========
-
-    async def cleanup_expired_records(self, retention_days: int) -> dict[str, int]:
-        """Delete monitoring records older than the specified retention period.
-
-        Args:
-            retention_days: Number of days to retain records.
-
-        Returns:
-            A dict mapping table name to the number of deleted rows.
-        """
-        cutoff = datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None) - datetime.timedelta(
-            days=retention_days
-        )
-
-        tables_and_columns: list[tuple[str, type, sqlalchemy.Column]] = [
-            (
-                'monitoring_messages',
-                persistence_monitoring.MonitoringMessage,
-                persistence_monitoring.MonitoringMessage.timestamp,
-            ),
-            (
-                'monitoring_llm_calls',
-                persistence_monitoring.MonitoringLLMCall,
-                persistence_monitoring.MonitoringLLMCall.timestamp,
-            ),
-            (
-                'monitoring_embedding_calls',
-                persistence_monitoring.MonitoringEmbeddingCall,
-                persistence_monitoring.MonitoringEmbeddingCall.timestamp,
-            ),
-            (
-                'monitoring_errors',
-                persistence_monitoring.MonitoringError,
-                persistence_monitoring.MonitoringError.timestamp,
-            ),
-            (
-                'monitoring_sessions',
-                persistence_monitoring.MonitoringSession,
-                persistence_monitoring.MonitoringSession.last_activity,
-            ),
-        ]
-
-        deleted_counts: dict[str, int] = {}
-
-        for table_name, model_cls, ts_column in tables_and_columns:
-            result = await self.ap.persistence_mgr.execute_async(sqlalchemy.delete(model_cls).where(ts_column < cutoff))
-            deleted_counts[table_name] = result.rowcount
-
-        return deleted_counts
-
     # ========== Recording Methods ==========
 
     async def record_message(
@@ -81,10 +30,8 @@ class MonitoringService:
         level: str = 'info',
         platform: str | None = None,
         user_id: str | None = None,
-        user_name: str | None = None,
         runner_name: str | None = None,
         variables: str | None = None,
-        role: str = 'user',
     ) -> str:
         """Record a message"""
         message_id = str(uuid.uuid4())
@@ -101,10 +48,8 @@ class MonitoringService:
             'level': level,
             'platform': platform,
             'user_id': user_id,
-            'user_name': user_name,
             'runner_name': runner_name,
             'variables': variables,
-            'role': role,
         }
 
         await self.ap.persistence_mgr.execute_async(
@@ -205,7 +150,6 @@ class MonitoringService:
         pipeline_name: str,
         platform: str | None = None,
         user_id: str | None = None,
-        user_name: str | None = None,
     ) -> None:
         """Record a new session"""
         session_data = {
@@ -220,7 +164,6 @@ class MonitoringService:
             'is_active': True,
             'platform': platform,
             'user_id': user_id,
-            'user_name': user_name,
         }
 
         await self.ap.persistence_mgr.execute_async(
@@ -412,7 +355,6 @@ class MonitoringService:
         self,
         bot_ids: list[str] | None = None,
         pipeline_ids: list[str] | None = None,
-        session_ids: list[str] | None = None,
         start_time: datetime.datetime | None = None,
         end_time: datetime.datetime | None = None,
         limit: int = 100,
@@ -425,8 +367,6 @@ class MonitoringService:
             conditions.append(persistence_monitoring.MonitoringMessage.bot_id.in_(bot_ids))
         if pipeline_ids:
             conditions.append(persistence_monitoring.MonitoringMessage.pipeline_id.in_(pipeline_ids))
-        if session_ids:
-            conditions.append(persistence_monitoring.MonitoringMessage.session_id.in_(session_ids))
         if start_time:
             conditions.append(persistence_monitoring.MonitoringMessage.timestamp >= start_time)
         if end_time:

src/langbot/pkg/api/http/service/space.py

@@ -1,6 +1,6 @@
 from __future__ import annotations
 
-from langbot.pkg.utils import httpclient
+import aiohttp
 import typing
 import datetime
 import time
@@ -99,49 +99,49 @@ class SpaceService:
         space_config = self._get_space_config()
         space_url = space_config['url']
 
-        session = httpclient.get_session()
-        async with session.post(
-            f'{space_url}/api/v1/accounts/oauth/token',
-            json={'code': code, 'instance_id': constants.instance_id},
-        ) as response:
-            if response.status != 200:
-                raise ValueError(f'Failed to exchange OAuth code: {await response.text()}')
-            data = await response.json()
-            if data.get('code') != 0:
-                raise ValueError(f'Failed to exchange OAuth code: {data.get("msg")}')
-            return data.get('data', {})
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                f'{space_url}/api/v1/accounts/oauth/token',
+                json={'code': code, 'instance_id': constants.instance_id},
+            ) as response:
+                if response.status != 200:
+                    raise ValueError(f'Failed to exchange OAuth code: {await response.text()}')
+                data = await response.json()
+                if data.get('code') != 0:
+                    raise ValueError(f'Failed to exchange OAuth code: {data.get("msg")}')
+                return data.get('data', {})
 
     async def refresh_token(self, refresh_token: str) -> typing.Dict:
         """Refresh Space access token"""
         space_config = self._get_space_config()
         space_url = space_config['url']
 
-        session = httpclient.get_session()
-        async with session.post(
-            f'{space_url}/api/v1/accounts/token/refresh', json={'refresh_token': refresh_token}
-        ) as response:
-            if response.status != 200:
-                raise ValueError(f'Failed to refresh token: {await response.text()}')
-            data = await response.json()
-            if data.get('code') != 0:
-                raise ValueError(f'Failed to refresh token: {data.get("msg")}')
-            return data.get('data', {})
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                f'{space_url}/api/v1/accounts/token/refresh', json={'refresh_token': refresh_token}
+            ) as response:
+                if response.status != 200:
+                    raise ValueError(f'Failed to refresh token: {await response.text()}')
+                data = await response.json()
+                if data.get('code') != 0:
+                    raise ValueError(f'Failed to refresh token: {data.get("msg")}')
+                return data.get('data', {})
 
     async def get_user_info_raw(self, access_token: str) -> typing.Dict:
         """Get user info from Space using access token (no validation)"""
         space_config = self._get_space_config()
         space_url = space_config['url']
 
-        session = httpclient.get_session()
-        async with session.get(
-            f'{space_url}/api/v1/accounts/me', headers={'Authorization': f'Bearer {access_token}'}
-        ) as response:
-            if response.status != 200:
-                raise ValueError(f'Failed to get user info: {await response.text()}')
-            data = await response.json()
-            if data.get('code') != 0:
-                raise ValueError(f'Failed to get user info: {data.get("msg")}')
-            return data.get('data', {})
+        async with aiohttp.ClientSession() as session:
+            async with session.get(
+                f'{space_url}/api/v1/accounts/me', headers={'Authorization': f'Bearer {access_token}'}
+            ) as response:
+                if response.status != 200:
+                    raise ValueError(f'Failed to get user info: {await response.text()}')
+                data = await response.json()
+                if data.get('code') != 0:
+                    raise ValueError(f'Failed to get user info: {data.get("msg")}')
+                return data.get('data', {})
 
     # === API calls with token validation ===
 
@@ -178,12 +178,12 @@ class SpaceService:
         space_config = self._get_space_config()
         space_url = space_config['url']
 
-        session = httpclient.get_session()
-        async with session.get(f'{space_url}/api/v1/models') as response:
-            if response.status != 200:
-                raise ValueError(f'Failed to get models: {await response.text()}')
-            data = await response.json()
-            if data.get('code') != 0:
-                raise ValueError(f'Failed to get models: {data.get("msg")}')
-            models_data = data.get('data', {}).get('models', [])
-            return [SpaceModel.model_validate(model_dict) for model_dict in models_data]
+        async with aiohttp.ClientSession() as session:
+            async with session.get(f'{space_url}/api/v1/models') as response:
+                if response.status != 200:
+                    raise ValueError(f'Failed to get models: {await response.text()}')
+                data = await response.json()
+                if data.get('code') != 0:
+                    raise ValueError(f'Failed to get models: {data.get("msg")}')
+                models_data = data.get('data', {}).get('models', [])
+                return [SpaceModel.model_validate(model_dict) for model_dict in models_data]

src/langbot/pkg/core/app.py

@@ -9,14 +9,12 @@ from ..platform import botmgr as im_mgr
 from ..platform.webhook_pusher import WebhookPusher
 from ..provider.session import sessionmgr as llm_session_mgr
 from ..provider.modelmgr import modelmgr as llm_model_mgr
-
 from langbot.pkg.provider.tools import toolmgr as llm_tool_mgr
 from ..config import manager as config_mgr
 from ..command import cmdmgr
 from ..plugin import connector as plugin_connector
 from ..pipeline import pool
 from ..pipeline import controller, pipelinemgr
-from ..pipeline import aggregator as message_aggregator
 from ..utils import version as version_mgr, proxy as proxy_mgr
 from ..persistence import mgr as persistencemgr
 from ..api.http.controller import main as http_controller
@@ -30,18 +28,16 @@ from ..api.http.service import knowledge as knowledge_service
 from ..api.http.service import mcp as mcp_service
 from ..api.http.service import apikey as apikey_service
 from ..api.http.service import webhook as webhook_service
+from ..api.http.service import external_kb as external_kb_service
 from ..api.http.service import monitoring as monitoring_service
-
 from ..discover import engine as discover_engine
 from ..storage import mgr as storagemgr
 from ..utils import logcache
 from . import taskmgr
 from . import entities as core_entities
 from ..rag.knowledge import kbmgr as rag_mgr
-from ..rag.service import RAGRuntimeService
 from ..vector import mgr as vectordb_mgr
 from ..telemetry import telemetry as telemetry_module
-from ..survey import manager as survey_module
 
 
 class Application:
@@ -65,7 +61,6 @@ class Application:
     model_mgr: llm_model_mgr.ModelManager = None
 
     rag_mgr: rag_mgr.RAGManager = None
-    rag_runtime_service: RAGRuntimeService = None
 
     # TODO move to pipeline
     tool_mgr: llm_tool_mgr.ToolManager = None
@@ -101,8 +96,6 @@ class Application:
 
     query_pool: pool.QueryPool = None
 
-    msg_aggregator: message_aggregator.MessageAggregator = None
-
     ctrl: controller.Controller = None
 
     pipeline_mgr: pipelinemgr.PipelineManager = None
@@ -141,6 +134,8 @@ class Application:
 
     knowledge_service: knowledge_service.KnowledgeService = None
 
+    external_kb_service: external_kb_service.ExternalKBService = None
+
     mcp_service: mcp_service.MCPService = None
 
     apikey_service: apikey_service.ApiKeyService = None
@@ -149,8 +144,6 @@ class Application:
 
     telemetry: telemetry_module.TelemetryManager = None
 
-    survey: survey_module.SurveyManager = None
-
     monitoring_service: monitoring_service.MonitoringService = None
 
     def __init__(self):
@@ -188,34 +181,6 @@ class Application:
                 scopes=[core_entities.LifecycleControlScope.APPLICATION],
             )
 
-            # Start monitoring data cleanup task if enabled
-            monitoring_cfg = self.instance_config.data.get('monitoring', {})
-            auto_cleanup_cfg = monitoring_cfg.get('auto_cleanup', {})
-            if auto_cleanup_cfg.get('enabled', True):
-                retention_days = auto_cleanup_cfg.get('retention_days', 30)
-                check_interval_hours = auto_cleanup_cfg.get('check_interval_hours', 1)
-
-                async def monitoring_cleanup_loop():
-                    check_interval_seconds = check_interval_hours * 3600
-                    while True:
-                        try:
-                            deleted = await self.monitoring_service.cleanup_expired_records(retention_days)
-                            total_deleted = sum(deleted.values())
-                            if total_deleted > 0:
-                                self.logger.info(
-                                    f'Monitoring auto-cleanup: deleted {total_deleted} expired records '
-                                    f'(retention={retention_days}d): {deleted}'
-                                )
-                        except Exception as e:
-                            self.logger.warning(f'Monitoring auto-cleanup error: {e}')
-                        await asyncio.sleep(check_interval_seconds)
-
-                self.task_mgr.create_task(
-                    monitoring_cleanup_loop(),
-                    name='monitoring-cleanup',
-                    scopes=[core_entities.LifecycleControlScope.APPLICATION],
-                )
-
             self.task_mgr.create_task(
                 never_ending(),
                 name='never-ending-task',

src/langbot/pkg/core/bootutils/deps.py

@@ -1,4 +1,3 @@
-import importlib.util
 import pip
 import os
 from ...utils import pkgmgr
@@ -50,10 +49,9 @@ async def check_deps() -> list[str]:
 
     missing_deps = []
     for dep in required_deps:
-        # Use find_spec instead of __import__ to avoid actually loading
-        # all modules into memory. find_spec only checks if the module
-        # can be found, without executing module-level code.
-        if importlib.util.find_spec(dep) is None:
+        try:
+            __import__(dep)
+        except ImportError:
             missing_deps.append(dep)
     return missing_deps
 

src/langbot/pkg/core/stages/build_app.py

@@ -5,14 +5,12 @@ import asyncio
 from .. import stage, app
 from ...utils import version, proxy
 from ...pipeline import pool, controller, pipelinemgr
-from ...pipeline import aggregator as message_aggregator
 from ...plugin import connector as plugin_connector
 from ...command import cmdmgr
 from ...provider.session import sessionmgr as llm_session_mgr
 from ...provider.modelmgr import modelmgr as llm_model_mgr
 from ...provider.tools import toolmgr as llm_tool_mgr
 from ...rag.knowledge import kbmgr as rag_mgr
-from ...rag.service import RAGRuntimeService
 from ...platform import botmgr as im_mgr
 from ...platform.webhook_pusher import WebhookPusher
 from ...persistence import mgr as persistencemgr
@@ -27,6 +25,7 @@ from ...api.http.service import knowledge as knowledge_service
 from ...api.http.service import mcp as mcp_service
 from ...api.http.service import apikey as apikey_service
 from ...api.http.service import webhook as webhook_service
+from ...api.http.service import external_kb as external_kb_service
 from ...api.http.service import monitoring as monitoring_service
 from ...discover import engine as discover_engine
 from ...storage import mgr as storagemgr
@@ -34,7 +33,6 @@ from ...utils import logcache
 from ...vector import mgr as vectordb_mgr
 from .. import taskmgr
 from ...telemetry import telemetry as telemetry_module
-from ...survey import manager as survey_module
 
 
 @stage.stage_class('BuildAppStage')
@@ -73,6 +71,9 @@ class BuildAppStage(stage.BootingStage):
         knowledge_service_inst = knowledge_service.KnowledgeService(ap)
         ap.knowledge_service = knowledge_service_inst
 
+        external_kb_service_inst = external_kb_service.ExternalKBService(ap)
+        ap.external_kb_service = external_kb_service_inst
+
         mcp_service_inst = mcp_service.MCPService(ap)
         ap.mcp_service = mcp_service_inst
 
@@ -108,11 +109,6 @@ class BuildAppStage(stage.BootingStage):
         await telemetry_inst.initialize()
         ap.telemetry = telemetry_inst
 
-        # Survey manager
-        survey_inst = survey_module.SurveyManager(ap)
-        await survey_inst.initialize()
-        ap.survey = survey_inst
-
         cmd_mgr_inst = cmdmgr.CommandManager(ap)
         await cmd_mgr_inst.initialize()
         ap.cmd_mgr = cmd_mgr_inst
@@ -141,17 +137,10 @@ class BuildAppStage(stage.BootingStage):
         await pipeline_mgr.initialize()
         ap.pipeline_mgr = pipeline_mgr
 
-        # Initialize message aggregator (after pipeline_mgr, as it needs pipeline config)
-        msg_aggregator_inst = message_aggregator.MessageAggregator(ap)
-        ap.msg_aggregator = msg_aggregator_inst
-
         rag_mgr_inst = rag_mgr.RAGManager(ap)
         await rag_mgr_inst.initialize()
         ap.rag_mgr = rag_mgr_inst
 
-        # Initialize RAG Runtime Service for plugins
-        ap.rag_runtime_service = RAGRuntimeService(ap)
-
         # 初始化向量数据库管理器
         vectordb_mgr_inst = vectordb_mgr.VectorDBManager(ap)
         await vectordb_mgr_inst.initialize()

src/langbot/pkg/core/stages/load_config.py

@@ -74,26 +74,20 @@ def _apply_env_overrides_to_config(cfg: dict) -> dict:
         current = cfg
 
         for i, key in enumerate(keys):
-            if not isinstance(current, dict):
+            if not isinstance(current, dict) or key not in current:
                 break
 
             if i == len(keys) - 1:
-                # At the final key
-                if key in current:
-                    if isinstance(current[key], (dict, list)):
-                        # Skip dict and list types
-                        pass
-                    else:
-                        # Valid scalar value - convert and set it
-                        converted_value = convert_value(env_value, current[key])
-                        current[key] = converted_value
+                # At the final key - check if it's a scalar value
+                if isinstance(current[key], (dict, list)):
+                    # Skip dict and list types
+                    pass
                 else:
-                    # Key doesn't exist yet - create it as string
-                    current[key] = env_value
+                    # Valid scalar value - convert and set it
+                    converted_value = convert_value(env_value, current[key])
+                    current[key] = converted_value
             else:
-                # Navigate deeper - create intermediate dict if needed
-                if key not in current:
-                    current[key] = {}
+                # Navigate deeper
                 current = current[key]
 
     return cfg
@@ -152,50 +146,16 @@ class LoadConfigStage(stage.BootingStage):
         await ap.instance_config.dump_config()
 
         # load or generate instance id
-        # Priority:
-        # 1. system.instance_id from config.yaml (can be set via SYSTEM__INSTANCE_ID env var)
-        # 2. data/labels/instance_id.json (if file exists)
-        # 3. Generate new and save to file
-        config_instance_id = ap.instance_config.data.get('system', {}).get('instance_id', '')
+        ap.instance_id = await config.load_json_config(
+            'data/labels/instance_id.json',
+            template_data={
+                'instance_id': f'instance_{str(uuid.uuid4())}',
+                'instance_create_ts': int(time.time()),
+            },
+            completion=False,
+        )
 
-        if config_instance_id:
-            # Use the instance_id from config.yaml
-            constants.instance_id = config_instance_id
-            # Still load/create the file for backward compat, but don't use its value
-            ap.instance_id = await config.load_json_config(
-                'data/labels/instance_id.json',
-                template_data={
-                    'instance_id': f'instance_{str(uuid.uuid4())}',
-                    'instance_create_ts': int(time.time()),
-                },
-                completion=False,
-            )
-        else:
-            # Try loading file-based instance id
-            instance_id_path = os.path.join('data', 'labels', 'instance_id.json')
-            if os.path.exists(instance_id_path):
-                # File exists, read it
-                ap.instance_id = await config.load_json_config(
-                    'data/labels/instance_id.json',
-                    template_data={
-                        'instance_id': '',
-                        'instance_create_ts': 0,
-                    },
-                    completion=False,
-                )
-                constants.instance_id = ap.instance_id.data['instance_id']
-            else:
-                # Neither config nor file, generate new and save to file
-                new_id = f'instance_{str(uuid.uuid4())}'
-                ap.instance_id = await config.load_json_config(
-                    'data/labels/instance_id.json',
-                    template_data={
-                        'instance_id': new_id,
-                        'instance_create_ts': int(time.time()),
-                    },
-                    completion=False,
-                )
-                constants.instance_id = new_id
+        constants.instance_id = ap.instance_id.data['instance_id']
         constants.edition = ap.instance_config.data.get('system', {}).get('edition', 'community')
 
         print(f'LangBot instance id: {constants.instance_id}')

src/langbot/pkg/entity/persistence/monitoring.py

@@ -20,10 +20,8 @@ class MonitoringMessage(Base):
     level = sqlalchemy.Column(sqlalchemy.String(50), nullable=False)  # info, warning, error, debug
     platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
     user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
-    user_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)  # User display name
     runner_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)  # Runner name for this query
     variables = sqlalchemy.Column(sqlalchemy.Text, nullable=True)  # Query variables as JSON string
-    role = sqlalchemy.Column(sqlalchemy.String(50), nullable=True, default='user')  # user, assistant
 
 
 class MonitoringLLMCall(Base):
@@ -65,7 +63,6 @@ class MonitoringSession(Base):
     is_active = sqlalchemy.Column(sqlalchemy.Boolean, nullable=False, default=True, index=True)
     platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
     user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
-    user_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)  # User display name
 
 
 class MonitoringError(Base):

src/langbot/pkg/entity/persistence/rag.py

@@ -10,21 +10,8 @@ class KnowledgeBase(Base):
     emoji = sqlalchemy.Column(sqlalchemy.String(10), nullable=True, default='📚')
     created_at = sqlalchemy.Column(sqlalchemy.DateTime, default=sqlalchemy.func.now())
     updated_at = sqlalchemy.Column(sqlalchemy.DateTime, default=sqlalchemy.func.now(), onupdate=sqlalchemy.func.now())
-    # New fields for plugin-based RAG
-    knowledge_engine_plugin_id = sqlalchemy.Column(sqlalchemy.String, nullable=True)
-    collection_id = sqlalchemy.Column(sqlalchemy.String, nullable=True)
-    creation_settings = sqlalchemy.Column(sqlalchemy.JSON, nullable=True, default=None)
-    retrieval_settings = sqlalchemy.Column(sqlalchemy.JSON, nullable=True, default=None)
-
-    # Field sets for different operations
-    MUTABLE_FIELDS = {'name', 'description', 'retrieval_settings'}
-    """Fields that can be updated after creation."""
-
-    CREATE_FIELDS = MUTABLE_FIELDS | {'uuid', 'knowledge_engine_plugin_id', 'collection_id', 'creation_settings'}
-    """Fields used when creating a new knowledge base."""
-
-    ALL_DB_FIELDS = CREATE_FIELDS | {'emoji', 'created_at', 'updated_at'}
-    """All fields stored in database (for loading from DB row)."""
+    embedding_model_uuid = sqlalchemy.Column(sqlalchemy.String, default='')
+    top_k = sqlalchemy.Column(sqlalchemy.Integer, default=5)
 
 
 class File(Base):
@@ -42,3 +29,16 @@ class Chunk(Base):
     uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
     file_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
     text = sqlalchemy.Column(sqlalchemy.Text)
+
+
+class ExternalKnowledgeBase(Base):
+    __tablename__ = 'external_knowledge_bases'
+    uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
+    name = sqlalchemy.Column(sqlalchemy.String, index=True)
+    description = sqlalchemy.Column(sqlalchemy.Text)
+    emoji = sqlalchemy.Column(sqlalchemy.String(10), nullable=True, default='🔗')
+    plugin_author = sqlalchemy.Column(sqlalchemy.String, nullable=False)
+    plugin_name = sqlalchemy.Column(sqlalchemy.String, nullable=False)
+    retriever_name = sqlalchemy.Column(sqlalchemy.String, nullable=False)
+    retriever_config = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
+    created_at = sqlalchemy.Column(sqlalchemy.DateTime, default=sqlalchemy.func.now())

src/langbot/pkg/persistence/mgr.py

@@ -2,16 +2,18 @@ from __future__ import annotations
 
 import datetime
 import typing
-
+import json
+import uuid
 
 import sqlalchemy.ext.asyncio as sqlalchemy_asyncio
 import sqlalchemy
 
 from . import database, migration
-from ..entity.persistence import base, metadata, model as persistence_model
+from ..entity.persistence import base, pipeline, metadata, model as persistence_model
 from ..entity import persistence
 from ..core import app
 from ..utils import constants, importutil
+from ..api.http.service import pipeline as pipeline_service
 from . import databases, migrations
 
 importutil.import_modules_in_pkg(databases)
@@ -76,6 +78,7 @@ class PersistenceManager:
 
             self.ap.logger.info(f'Successfully upgraded database to version {last_migration_number}.')
 
+        await self.write_default_pipeline()
         await self.write_space_model_providers()
 
     async def create_tables(self):
@@ -98,6 +101,29 @@ class PersistenceManager:
             if row is None:
                 await self.execute_async(sqlalchemy.insert(metadata.Metadata).values(item))
 
+    async def write_default_pipeline(self):
+        # write default pipeline
+        result = await self.execute_async(sqlalchemy.select(pipeline.LegacyPipeline))
+        default_pipeline_uuid = None
+        if result.first() is None:
+            self.ap.logger.info('Creating default pipeline...')
+
+            pipeline_config = json.loads(importutil.read_resource_file('templates/default-pipeline-config.json'))
+
+            default_pipeline_uuid = str(uuid.uuid4())
+            pipeline_data = {
+                'uuid': default_pipeline_uuid,
+                'for_version': self.ap.ver_mgr.get_current_version(),
+                'stages': pipeline_service.default_stage_order,
+                'is_default': True,
+                'name': 'ChatPipeline',
+                'description': 'Default pipeline, new bots will be bound to this pipeline | 默认提供的流水线，您配置的机器人将自动绑定到此流水线',
+                'config': pipeline_config,
+                'extensions_preferences': {},
+            }
+
+            await self.execute_async(sqlalchemy.insert(pipeline.LegacyPipeline).values(pipeline_data))
+
     async def write_space_model_providers(self):
         space_models_gateway_api_url = self.ap.instance_config.data.get('space', {}).get(
             'models_gateway_api_url', 'https://api.langbot.cloud/v1'

src/langbot/pkg/persistence/migrations/dbm019_monitoring_message_role.py

@@ -1,24 +0,0 @@
-import sqlalchemy
-from .. import migration
-
-
-@migration.migration_class(19)
-class DBMigrateMonitoringMessageRole(migration.DBMigration):
-    """Add role column to monitoring_messages table"""
-
-    async def upgrade(self):
-        """Upgrade"""
-        try:
-            sql_text = sqlalchemy.text("ALTER TABLE monitoring_messages ADD COLUMN role VARCHAR(50) DEFAULT 'user'")
-            await self.ap.persistence_mgr.execute_async(sql_text)
-        except Exception:
-            # Column may already exist
-            pass
-
-    async def downgrade(self):
-        """Downgrade"""
-        try:
-            sql_text = sqlalchemy.text('ALTER TABLE monitoring_messages DROP COLUMN role')
-            await self.ap.persistence_mgr.execute_async(sql_text)
-        except Exception:
-            pass

src/langbot/pkg/persistence/migrations/dbm020_knowledge_engine_plugin_architecture.py

@@ -1,161 +0,0 @@
-import sqlalchemy
-from .. import migration
-
-
-@migration.migration_class(20)
-class DBMigrateKnowledgeEnginePluginArchitecture(migration.DBMigration):
-    """Migrate to unified Knowledge Engine plugin architecture.
-
-    Changes:
-    - Backup existing knowledge_bases data to knowledge_bases_backup
-    - Clear knowledge_bases table and add new plugin architecture columns
-    - Drop old columns (PostgreSQL only; SQLite leaves them unmapped)
-    - Preserve external_knowledge_bases table as-is for future migration
-    - Set rag_plugin_migration_needed flag in metadata if old data exists
-    """
-
-    async def upgrade(self):
-        """Upgrade"""
-        has_internal_data = await self._backup_knowledge_bases()
-        has_external_data = await self._check_external_knowledge_bases()
-        await self._clear_knowledge_bases()
-        await self._add_columns_to_knowledge_bases()
-        await self._drop_old_columns()
-        if has_internal_data or has_external_data:
-            await self._set_migration_flag()
-
-    async def _get_table_columns(self, table_name: str) -> list[str]:
-        """Get column names from a table (works for both SQLite and PostgreSQL)."""
-        if self.ap.persistence_mgr.db.name == 'postgresql':
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text(
-                    'SELECT column_name FROM information_schema.columns WHERE table_name = :table_name;'
-                ).bindparams(table_name=table_name)
-            )
-            return [row[0] for row in result.fetchall()]
-        else:
-            # SQLite PRAGMA does not support bind parameters; validate identifier.
-            if not table_name.isidentifier():
-                raise ValueError(f'Invalid table name: {table_name}')
-            result = await self.ap.persistence_mgr.execute_async(sqlalchemy.text(f'PRAGMA table_info({table_name});'))
-            return [row[1] for row in result.fetchall()]
-
-    async def _table_exists(self, table_name: str) -> bool:
-        """Check if a table exists."""
-        if self.ap.persistence_mgr.db.name == 'postgresql':
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text(
-                    'SELECT EXISTS (SELECT FROM information_schema.tables WHERE table_name = :table_name);'
-                ).bindparams(table_name=table_name)
-            )
-            return result.scalar()
-        else:
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text("SELECT name FROM sqlite_master WHERE type='table' AND name=:table_name;").bindparams(
-                    table_name=table_name
-                )
-            )
-            return result.first() is not None
-
-    async def _backup_knowledge_bases(self) -> bool:
-        """Backup knowledge_bases data. Returns True if data was backed up."""
-        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.text('SELECT COUNT(*) FROM knowledge_bases;'))
-        count = result.scalar()
-        if count == 0:
-            return False
-
-        # Drop backup table if it already exists (from a previous failed migration)
-        if await self._table_exists('knowledge_bases_backup'):
-            await self.ap.persistence_mgr.execute_async(sqlalchemy.text('DROP TABLE knowledge_bases_backup;'))
-
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('CREATE TABLE knowledge_bases_backup AS SELECT * FROM knowledge_bases;')
-        )
-        self.ap.logger.info(
-            'Backed up %d knowledge base(s) to knowledge_bases_backup table.',
-            count,
-        )
-        return True
-
-    async def _check_external_knowledge_bases(self) -> bool:
-        """Check if external_knowledge_bases table exists and has data.
-
-        The table is preserved as-is (not dropped) for future migration.
-        """
-        if not await self._table_exists('external_knowledge_bases'):
-            return False
-
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT COUNT(*) FROM external_knowledge_bases;')
-        )
-        count = result.scalar()
-        if count > 0:
-            self.ap.logger.info(
-                'Found %d external knowledge base(s) in external_knowledge_bases table. '
-                'Table preserved for future migration.',
-                count,
-            )
-        return count > 0
-
-    async def _clear_knowledge_bases(self):
-        """Clear all rows from knowledge_bases table (preserve table structure)."""
-        await self.ap.persistence_mgr.execute_async(sqlalchemy.text('DELETE FROM knowledge_bases;'))
-
-    async def _add_columns_to_knowledge_bases(self):
-        """Add new RAG plugin architecture columns to knowledge_bases table."""
-        columns = await self._get_table_columns('knowledge_bases')
-
-        new_columns = {
-            'knowledge_engine_plugin_id': 'VARCHAR',
-            'collection_id': 'VARCHAR',
-            'creation_settings': 'TEXT',  # JSON stored as TEXT for SQLite compatibility
-            'retrieval_settings': 'TEXT',
-        }
-
-        for col_name, col_type in new_columns.items():
-            if col_name not in columns:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(f'ALTER TABLE knowledge_bases ADD COLUMN {col_name} {col_type};')
-                )
-
-    async def _drop_old_columns(self):
-        """Drop embedding_model_uuid and top_k columns (PostgreSQL only).
-
-        SQLite does not support DROP COLUMN in older versions, so we leave the
-        columns in place — the SQLAlchemy entity simply won't map them.
-        """
-        if self.ap.persistence_mgr.db.name != 'postgresql':
-            return
-
-        columns = await self._get_table_columns('knowledge_bases')
-
-        if 'embedding_model_uuid' in columns:
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('ALTER TABLE knowledge_bases DROP COLUMN embedding_model_uuid;')
-            )
-
-        if 'top_k' in columns:
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('ALTER TABLE knowledge_bases DROP COLUMN top_k;')
-            )
-
-    async def _set_migration_flag(self):
-        """Set rag_plugin_migration_needed flag in metadata table."""
-        # Check if the key already exists
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text("SELECT value FROM metadata WHERE key = 'rag_plugin_migration_needed';")
-        )
-        row = result.first()
-        if row is not None:
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text("UPDATE metadata SET value = 'true' WHERE key = 'rag_plugin_migration_needed';")
-            )
-        else:
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text("INSERT INTO metadata (key, value) VALUES ('rag_plugin_migration_needed', 'true');")
-            )
-        self.ap.logger.info('Set rag_plugin_migration_needed=true in metadata.')
-
-    async def downgrade(self):
-        """Downgrade"""
-        pass

src/langbot/pkg/persistence/migrations/dbm021_merge_exception_handling.py

@@ -1,74 +0,0 @@
-from .. import migration
-
-import sqlalchemy
-import json
-
-
-@migration.migration_class(21)
-class DBMigrateMergeExceptionHandling(migration.DBMigration):
-    """Merge hide-exception and block-failed-request-output into a single exception-handling select option,
-    and add failure-hint field.
-
-    Conversion logic:
-    - block-failed-request-output=true  ->  exception-handling: hide
-    - hide-exception=true               ->  exception-handling: show-hint
-    - hide-exception=false              ->  exception-handling: show-error
-    """
-
-    async def upgrade(self):
-        """Upgrade"""
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
-        )
-        pipelines = result.fetchall()
-
-        current_version = self.ap.ver_mgr.get_current_version()
-
-        for pipeline_row in pipelines:
-            uuid = pipeline_row[0]
-            config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
-
-            if 'output' not in config:
-                config['output'] = {}
-            if 'misc' not in config['output']:
-                config['output']['misc'] = {}
-
-            misc = config['output']['misc']
-
-            # Determine new exception-handling value from legacy fields
-            hide_exception = misc.get('hide-exception', True)
-            block_failed = misc.get('block-failed-request-output', False)
-
-            if block_failed:
-                exception_handling = 'hide'
-            elif hide_exception:
-                exception_handling = 'show-hint'
-            else:
-                exception_handling = 'show-error'
-
-            misc['exception-handling'] = exception_handling
-
-            # Add failure-hint with default value
-            misc['failure-hint'] = 'Request failed.'
-
-            # Remove legacy fields
-            misc.pop('hide-exception', None)
-
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )
-
-    async def downgrade(self):
-        """Downgrade"""
-        pass

src/langbot/pkg/persistence/migrations/dbm022_monitoring_user_name.py

@@ -1,73 +0,0 @@
-import sqlalchemy
-from .. import migration
-
-
-@migration.migration_class(22)
-class DBMigrateMonitoringUserId(migration.DBMigration):
-    """Add user_id and user_name columns to monitoring_sessions table
-
-    This migration adds the missing user_id column and also ensures user_name
-    column exists (in case migration 21 failed or was skipped).
-    """
-
-    async def _table_exists(self, table_name: str) -> bool:
-        """Check if a table exists (works for both SQLite and PostgreSQL)."""
-        if self.ap.persistence_mgr.db.name == 'postgresql':
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text(
-                    'SELECT EXISTS (SELECT FROM information_schema.tables WHERE table_name = :table_name);'
-                ).bindparams(table_name=table_name)
-            )
-            return bool(result.scalar())
-        else:
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text("SELECT name FROM sqlite_master WHERE type='table' AND name=:table_name;").bindparams(
-                    table_name=table_name
-                )
-            )
-            return result.first() is not None
-
-    async def _get_table_columns(self, table_name: str) -> list[str]:
-        """Get column names from a table (works for both SQLite and PostgreSQL)."""
-        if self.ap.persistence_mgr.db.name == 'postgresql':
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text(
-                    'SELECT column_name FROM information_schema.columns WHERE table_name = :table_name;'
-                ).bindparams(table_name=table_name)
-            )
-            return [row[0] for row in result.fetchall()]
-        else:
-            if not table_name.isidentifier():
-                raise ValueError(f'Invalid table name: {table_name}')
-            result = await self.ap.persistence_mgr.execute_async(sqlalchemy.text(f'PRAGMA table_info({table_name});'))
-            return [row[1] for row in result.fetchall()]
-
-    async def _add_column_if_not_exists(self, table_name: str, column_name: str, column_type: str):
-        """Add a column to a table if it does not already exist."""
-        columns = await self._get_table_columns(table_name)
-        if column_name in columns:
-            self.ap.logger.debug('%s column already exists in %s.', column_name, table_name)
-            return
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text(f'ALTER TABLE {table_name} ADD COLUMN {column_name} {column_type};')
-        )
-        self.ap.logger.info('Added %s column to %s table.', column_name, table_name)
-
-    async def upgrade(self):
-        # Check if monitoring_sessions table exists
-        if not await self._table_exists('monitoring_sessions'):
-            self.ap.logger.warning('monitoring_sessions table does not exist, skipping migration.')
-            return
-
-        # Add user_id column to monitoring_sessions table
-        await self._add_column_if_not_exists('monitoring_sessions', 'user_id', 'VARCHAR(255)')
-
-        # Add user_name column to monitoring_sessions table (in case migration 21 failed)
-        await self._add_column_if_not_exists('monitoring_sessions', 'user_name', 'VARCHAR(255)')
-
-        # Add user_name column to monitoring_messages table (in case migration 21 failed)
-        if await self._table_exists('monitoring_messages'):
-            await self._add_column_if_not_exists('monitoring_messages', 'user_name', 'VARCHAR(255)')
-
-    async def downgrade(self):
-        pass

src/langbot/pkg/persistence/migrations/dbm023_model_fallback_config.py

@@ -1,102 +0,0 @@
-from .. import migration
-
-import sqlalchemy
-import json
-
-
-@migration.migration_class(23)
-class DBMigrateModelFallbackConfig(migration.DBMigration):
-    """Convert model field from plain UUID string to object with primary/fallbacks"""
-
-    async def upgrade(self):
-        """Upgrade"""
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
-        )
-        pipelines = result.fetchall()
-
-        current_version = self.ap.ver_mgr.get_current_version()
-
-        for pipeline_row in pipelines:
-            uuid = pipeline_row[0]
-            config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
-
-            if 'ai' not in config or 'local-agent' not in config['ai']:
-                continue
-
-            local_agent = config['ai']['local-agent']
-            changed = False
-
-            # Convert model from string to object
-            model_value = local_agent.get('model', '')
-            if isinstance(model_value, str):
-                local_agent['model'] = {
-                    'primary': model_value,
-                    'fallbacks': [],
-                }
-                changed = True
-
-            # Remove leftover fallback-models field if present
-            if 'fallback-models' in local_agent:
-                del local_agent['fallback-models']
-                changed = True
-
-            if not changed:
-                continue
-
-            # Update using raw SQL with compatibility for both SQLite and PostgreSQL
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )
-
-    async def downgrade(self):
-        """Downgrade"""
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
-        )
-        pipelines = result.fetchall()
-
-        current_version = self.ap.ver_mgr.get_current_version()
-
-        for pipeline_row in pipelines:
-            uuid = pipeline_row[0]
-            config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
-
-            if 'ai' not in config or 'local-agent' not in config['ai']:
-                continue
-
-            local_agent = config['ai']['local-agent']
-
-            # Convert model from object back to string
-            model_value = local_agent.get('model', '')
-            if isinstance(model_value, dict):
-                local_agent['model'] = model_value.get('primary', '')
-            else:
-                continue
-
-            # Update using raw SQL with compatibility for both SQLite and PostgreSQL
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )

src/langbot/pkg/persistence/migrations/dbm024_wecombot_websocket_mode.py

@@ -1,49 +0,0 @@
-from .. import migration
-
-import sqlalchemy
-import json
-
-
-@migration.migration_class(24)
-class DBMigrateWecomBotWebSocketMode(migration.DBMigration):
-    """Add enable-webhook field to existing wecombot adapter configs.
-
-    Existing wecombot bots were all using webhook mode, so we set
-    enable-webhook=true to preserve their behavior after the new
-    WebSocket long connection mode is introduced as default.
-    """
-
-    async def upgrade(self):
-        """Upgrade"""
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text("SELECT uuid, adapter_config FROM bots WHERE adapter = 'wecombot'")
-        )
-        bots = result.fetchall()
-
-        for bot_row in bots:
-            bot_uuid = bot_row[0]
-            adapter_config = json.loads(bot_row[1]) if isinstance(bot_row[1], str) else bot_row[1]
-
-            if 'enable-webhook' in adapter_config:
-                continue
-
-            # Determine mode based on existing config: if webhook fields are present, keep webhook mode
-            has_webhook_config = bool(
-                adapter_config.get('Token') and adapter_config.get('EncodingAESKey') and adapter_config.get('Corpid')
-            )
-            adapter_config['enable-webhook'] = has_webhook_config
-
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text('UPDATE bots SET adapter_config = :config::jsonb WHERE uuid = :uuid'),
-                    {'config': json.dumps(adapter_config), 'uuid': bot_uuid},
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text('UPDATE bots SET adapter_config = :config WHERE uuid = :uuid'),
-                    {'config': json.dumps(adapter_config), 'uuid': bot_uuid},
-                )
-
-    async def downgrade(self):
-        """Downgrade"""
-        pass

src/langbot/pkg/pipeline/aggregator.py

@@ -1,289 +0,0 @@
-"""Message Aggregator Module
-
-This module provides message aggregation/debounce functionality.
-When users send multiple messages consecutively, the aggregator will wait
-for a configurable delay period and merge them into a single message
-before processing.
-"""
-
-from __future__ import annotations
-
-import asyncio
-import time
-import typing
-from dataclasses import dataclass, field
-
-import langbot_plugin.api.entities.builtin.platform.message as platform_message
-import langbot_plugin.api.entities.builtin.platform.events as platform_events
-import langbot_plugin.api.entities.builtin.provider.session as provider_session
-import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
-
-if typing.TYPE_CHECKING:
-    from ..core import app
-
-# Maximum number of messages to buffer before forcing a flush
-MAX_BUFFER_MESSAGES = 10
-
-
-@dataclass
-class PendingMessage:
-    """A pending message waiting to be aggregated"""
-
-    bot_uuid: str
-    launcher_type: provider_session.LauncherTypes
-    launcher_id: typing.Union[int, str]
-    sender_id: typing.Union[int, str]
-    message_event: platform_events.MessageEvent
-    message_chain: platform_message.MessageChain
-    adapter: abstract_platform_adapter.AbstractMessagePlatformAdapter
-    pipeline_uuid: typing.Optional[str]
-    timestamp: float = field(default_factory=time.time)
-
-
-@dataclass
-class SessionBuffer:
-    """Buffer for a single session's pending messages"""
-
-    session_id: str
-    messages: list[PendingMessage] = field(default_factory=list)
-    timer_task: typing.Optional[asyncio.Task] = None
-    last_message_time: float = field(default_factory=time.time)
-
-
-class MessageAggregator:
-    """Message aggregator that buffers and merges consecutive messages
-
-    This class implements a debounce mechanism for incoming messages.
-    When a message arrives, it starts a timer. If more messages arrive
-    before the timer expires, they are buffered. When the timer expires,
-    all buffered messages are merged and sent to the query pool.
-    """
-
-    ap: app.Application
-
-    buffers: dict[str, SessionBuffer]
-    """Session ID -> SessionBuffer mapping"""
-
-    lock: asyncio.Lock
-    """Lock for thread-safe buffer operations"""
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-        self.buffers = {}
-        self.lock = asyncio.Lock()
-
-    def _get_session_id(
-        self,
-        bot_uuid: str,
-        launcher_type: provider_session.LauncherTypes,
-        launcher_id: typing.Union[int, str],
-    ) -> str:
-        """Generate a unique session ID"""
-        return f'{bot_uuid}:{launcher_type.value}:{launcher_id}'
-
-    async def _get_aggregation_config(self, pipeline_uuid: typing.Optional[str]) -> tuple[bool, float]:
-        """Get aggregation configuration for a pipeline
-
-        Returns:
-            tuple: (enabled, delay_seconds)
-        """
-        default_enabled = False
-        default_delay = 1.5
-
-        if pipeline_uuid is None:
-            return default_enabled, default_delay
-
-        # Get pipeline from pipeline manager
-        pipeline = await self.ap.pipeline_mgr.get_pipeline_by_uuid(pipeline_uuid)
-        if pipeline is None:
-            return default_enabled, default_delay
-
-        config = pipeline.pipeline_entity.config or {}
-        trigger_config = config.get('trigger', {})
-        aggregation_config = trigger_config.get('message-aggregation', {})
-
-        enabled = aggregation_config.get('enabled', default_enabled)
-
-        delay_raw = aggregation_config.get('delay', default_delay)
-        try:
-            delay = float(delay_raw)
-        except (TypeError, ValueError):
-            delay = default_delay
-
-        # Clamp delay to valid range
-        delay = max(1.0, min(10.0, delay))
-
-        return enabled, delay
-
-    async def add_message(
-        self,
-        bot_uuid: str,
-        launcher_type: provider_session.LauncherTypes,
-        launcher_id: typing.Union[int, str],
-        sender_id: typing.Union[int, str],
-        message_event: platform_events.MessageEvent,
-        message_chain: platform_message.MessageChain,
-        adapter: abstract_platform_adapter.AbstractMessagePlatformAdapter,
-        pipeline_uuid: typing.Optional[str] = None,
-    ) -> None:
-        """Add a message to the aggregation buffer
-
-        If aggregation is disabled for the pipeline, the message is sent
-        directly to the query pool. Otherwise, it's buffered and will be
-        merged with other messages from the same session.
-        """
-        enabled, delay = await self._get_aggregation_config(pipeline_uuid)
-
-        if not enabled:
-            # Aggregation disabled, send directly to query pool
-            await self.ap.query_pool.add_query(
-                bot_uuid=bot_uuid,
-                launcher_type=launcher_type,
-                launcher_id=launcher_id,
-                sender_id=sender_id,
-                message_event=message_event,
-                message_chain=message_chain,
-                adapter=adapter,
-                pipeline_uuid=pipeline_uuid,
-            )
-            return
-
-        session_id = self._get_session_id(bot_uuid, launcher_type, launcher_id)
-
-        pending_msg = PendingMessage(
-            bot_uuid=bot_uuid,
-            launcher_type=launcher_type,
-            launcher_id=launcher_id,
-            sender_id=sender_id,
-            message_event=message_event,
-            message_chain=message_chain,
-            adapter=adapter,
-            pipeline_uuid=pipeline_uuid,
-        )
-
-        force_flush = False
-        async with self.lock:
-            if session_id in self.buffers:
-                buffer = self.buffers[session_id]
-                # Cancel existing timer (just cancel, don't await inside lock)
-                if buffer.timer_task and not buffer.timer_task.done():
-                    buffer.timer_task.cancel()
-                buffer.messages.append(pending_msg)
-            else:
-                buffer = SessionBuffer(
-                    session_id=session_id,
-                    messages=[pending_msg],
-                )
-                self.buffers[session_id] = buffer
-
-            buffer.last_message_time = time.time()
-
-            # Check if buffer reached max capacity
-            if len(buffer.messages) >= MAX_BUFFER_MESSAGES:
-                force_flush = True
-            else:
-                # Start new timer
-                buffer.timer_task = asyncio.create_task(self._delayed_flush(session_id, delay))
-
-        if force_flush:
-            await self._flush_buffer(session_id)
-
-    async def _delayed_flush(self, session_id: str, delay: float) -> None:
-        """Wait for delay then flush the buffer"""
-        try:
-            await asyncio.sleep(delay)
-            await self._flush_buffer(session_id)
-        except asyncio.CancelledError:
-            # Timer was cancelled, new message arrived
-            pass
-
-    async def _flush_buffer(self, session_id: str) -> None:
-        """Flush the buffer for a session, merging all messages"""
-        async with self.lock:
-            buffer = self.buffers.pop(session_id, None)
-
-        if buffer is None or not buffer.messages:
-            return
-
-        if len(buffer.messages) == 1:
-            # Only one message, no need to merge
-            msg = buffer.messages[0]
-            await self.ap.query_pool.add_query(
-                bot_uuid=msg.bot_uuid,
-                launcher_type=msg.launcher_type,
-                launcher_id=msg.launcher_id,
-                sender_id=msg.sender_id,
-                message_event=msg.message_event,
-                message_chain=msg.message_chain,
-                adapter=msg.adapter,
-                pipeline_uuid=msg.pipeline_uuid,
-            )
-            return
-
-        # Merge multiple messages
-        merged_msg = self._merge_messages(buffer.messages)
-        await self.ap.query_pool.add_query(
-            bot_uuid=merged_msg.bot_uuid,
-            launcher_type=merged_msg.launcher_type,
-            launcher_id=merged_msg.launcher_id,
-            sender_id=merged_msg.sender_id,
-            message_event=merged_msg.message_event,
-            message_chain=merged_msg.message_chain,
-            adapter=merged_msg.adapter,
-            pipeline_uuid=merged_msg.pipeline_uuid,
-        )
-
-    def _merge_messages(self, messages: list[PendingMessage]) -> PendingMessage:
-        """Merge multiple messages into one
-
-        The merged message uses the first message as base and combines
-        all message chains with newline separators.
-        The original message_event is kept unmodified to preserve
-        message metadata (message_id, etc.) for reply/quote.
-        """
-        if len(messages) == 1:
-            return messages[0]
-
-        base_msg = messages[0]
-
-        # Build merged message chain
-        merged_chain = platform_message.MessageChain([])
-
-        for i, msg in enumerate(messages):
-            if i > 0:
-                # Add newline separator between messages
-                merged_chain.append(platform_message.Plain(text='\n'))
-
-            # Copy all components from this message
-            for component in msg.message_chain:
-                merged_chain.append(component)
-
-        # Keep message_event unmodified (preserves original message_id and
-        # metadata for reply/quote), only pass merged chain separately
-        return PendingMessage(
-            bot_uuid=base_msg.bot_uuid,
-            launcher_type=base_msg.launcher_type,
-            launcher_id=base_msg.launcher_id,
-            sender_id=base_msg.sender_id,
-            message_event=base_msg.message_event,
-            message_chain=merged_chain,
-            adapter=base_msg.adapter,
-            pipeline_uuid=base_msg.pipeline_uuid,
-        )
-
-    async def flush_all(self) -> None:
-        """Flush all pending buffers immediately
-
-        This is useful during shutdown to ensure no messages are lost.
-        """
-        # Snapshot session IDs and cancel all timers under lock
-        async with self.lock:
-            session_ids = list(self.buffers.keys())
-            for sid in session_ids:
-                buffer = self.buffers.get(sid)
-                if buffer and buffer.timer_task and not buffer.timer_task.done():
-                    buffer.timer_task.cancel()
-
-        # Flush each buffer outside the lock
-        for session_id in session_ids:
-            await self._flush_buffer(session_id)

src/langbot/pkg/pipeline/cntfilter/filters/baiduexamine.py

@@ -1,9 +1,10 @@
 from __future__ import annotations
 
+import aiohttp
+
 from .. import entities
 from .. import filter as filter_model
 import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
-from langbot.pkg.utils import httpclient
 
 BAIDU_EXAMINE_URL = 'https://aip.baidubce.com/rest/2.0/solution/v1/text_censor/v2/user_defined?access_token={}'
 BAIDU_EXAMINE_TOKEN_URL = 'https://aip.baidubce.com/oauth/2.0/token'
@@ -14,50 +15,50 @@ class BaiduCloudExamine(filter_model.ContentFilter):
     """百度云内容审核"""
 
     async def _get_token(self) -> str:
-        session = httpclient.get_session()
-        async with session.post(
-            BAIDU_EXAMINE_TOKEN_URL,
-            params={
-                'grant_type': 'client_credentials',
-                'client_id': self.ap.pipeline_cfg.data['baidu-cloud-examine']['api-key'],
-                'client_secret': self.ap.pipeline_cfg.data['baidu-cloud-examine']['api-secret'],
-            },
-        ) as resp:
-            return (await resp.json())['access_token']
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                BAIDU_EXAMINE_TOKEN_URL,
+                params={
+                    'grant_type': 'client_credentials',
+                    'client_id': self.ap.pipeline_cfg.data['baidu-cloud-examine']['api-key'],
+                    'client_secret': self.ap.pipeline_cfg.data['baidu-cloud-examine']['api-secret'],
+                },
+            ) as resp:
+                return (await resp.json())['access_token']
 
     async def process(self, query: pipeline_query.Query, message: str) -> entities.FilterResult:
-        session = httpclient.get_session()
-        async with session.post(
-            BAIDU_EXAMINE_URL.format(await self._get_token()),
-            headers={
-                'Content-Type': 'application/x-www-form-urlencoded',
-                'Accept': 'application/json',
-            },
-            data=f'text={message}'.encode('utf-8'),
-        ) as resp:
-            result = await resp.json()
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                BAIDU_EXAMINE_URL.format(await self._get_token()),
+                headers={
+                    'Content-Type': 'application/x-www-form-urlencoded',
+                    'Accept': 'application/json',
+                },
+                data=f'text={message}'.encode('utf-8'),
+            ) as resp:
+                result = await resp.json()
 
-            if 'error_code' in result:
-                return entities.FilterResult(
-                    level=entities.ResultLevel.BLOCK,
-                    replacement=message,
-                    user_notice='',
-                    console_notice=f'百度云判定出错，错误信息：{result["error_msg"]}',
-                )
-            else:
-                conclusion = result['conclusion']
-
-                if conclusion in ('合规'):
-                    return entities.FilterResult(
-                        level=entities.ResultLevel.PASS,
-                        replacement=message,
-                        user_notice='',
-                        console_notice=f'百度云判定结果：{conclusion}',
-                    )
-                else:
+                if 'error_code' in result:
                     return entities.FilterResult(
                         level=entities.ResultLevel.BLOCK,
                         replacement=message,
-                        user_notice='消息中存在不合适的内容, 请修改',
-                        console_notice=f'百度云判定结果：{conclusion}',
+                        user_notice='',
+                        console_notice=f'百度云判定出错，错误信息：{result["error_msg"]}',
                     )
+                else:
+                    conclusion = result['conclusion']
+
+                    if conclusion in ('合规'):
+                        return entities.FilterResult(
+                            level=entities.ResultLevel.PASS,
+                            replacement=message,
+                            user_notice='',
+                            console_notice=f'百度云判定结果：{conclusion}',
+                        )
+                    else:
+                        return entities.FilterResult(
+                            level=entities.ResultLevel.BLOCK,
+                            replacement=message,
+                            user_notice='消息中存在不合适的内容, 请修改',
+                            console_notice=f'百度云判定结果：{conclusion}',
+                        )

src/langbot/pkg/pipeline/config_coercion.py

@@ -1,105 +0,0 @@
-from __future__ import annotations
-
-import logging
-
-logger = logging.getLogger(__name__)
-
-# metadata type -> coercion function
-_COERCE_MAP = {
-    'integer': lambda v: int(v),
-    'number': lambda v: float(v),
-    'float': lambda v: float(v),
-}
-
-
-def _coerce_bool(v):
-    if isinstance(v, bool):
-        return v
-    if isinstance(v, str):
-        if v.lower() == 'true':
-            return True
-        if v.lower() == 'false':
-            return False
-        raise ValueError(f'Cannot convert string {v!r} to bool')
-    return bool(v)
-
-
-def _coerce_value(value, expected_type: str):
-    """Convert a single value to the expected type.
-
-    Returns the converted value, or the original value if no conversion needed.
-    """
-    if value is None:
-        return value
-
-    if expected_type == 'boolean':
-        if isinstance(value, bool):
-            return value
-        return _coerce_bool(value)
-
-    coerce_fn = _COERCE_MAP.get(expected_type)
-    if coerce_fn is None:
-        return value
-
-    # Already the correct type
-    if expected_type == 'integer' and isinstance(value, int) and not isinstance(value, bool):
-        return value
-    if expected_type in ('number', 'float') and isinstance(value, (int, float)) and not isinstance(value, bool):
-        return float(value)
-
-    return coerce_fn(value)
-
-
-def coerce_pipeline_config(
-    config: dict,
-    *metadata_list: dict,
-) -> None:
-    """Coerce pipeline config values according to metadata type definitions.
-
-    Walks each metadata dict (trigger, safety, ai, output) and converts
-    config values in-place so that strings coming from the JSON column are
-    cast to their declared types (integer, number/float, boolean).
-
-    Args:
-        config: The pipeline config dict to modify in-place.
-        *metadata_list: Metadata dicts loaded from the YAML templates.
-    """
-    for meta in metadata_list:
-        section_name = meta.get('name')
-        if not section_name or section_name not in config:
-            continue
-
-        section = config[section_name]
-        if not isinstance(section, dict):
-            continue
-
-        for stage_def in meta.get('stages', []):
-            stage_name = stage_def.get('name')
-            if not stage_name or stage_name not in section:
-                continue
-
-            stage_config = section[stage_name]
-            if not isinstance(stage_config, dict):
-                continue
-
-            for field_def in stage_def.get('config', []):
-                field_name = field_def.get('name')
-                field_type = field_def.get('type')
-                if not field_name or not field_type or field_name not in stage_config:
-                    continue
-
-                old_value = stage_config[field_name]
-                try:
-                    new_value = _coerce_value(old_value, field_type)
-                    if new_value is not old_value:
-                        stage_config[field_name] = new_value
-                except (ValueError, TypeError) as e:
-                    logger.warning(
-                        'Failed to coerce config %s.%s.%s (%r) to %s: %s',
-                        section_name,
-                        stage_name,
-                        field_name,
-                        old_value,
-                        field_type,
-                        e,
-                    )

src/langbot/pkg/pipeline/monitoring_helper.py

@@ -34,15 +34,6 @@ class MonitoringHelper:
             # Check if session exists, if not, record session start
             session_id = f'{query.launcher_type}_{query.launcher_id}'
 
-            # Get sender name from message event
-            sender_name = None
-            if hasattr(query, 'message_event'):
-                if hasattr(query.message_event, 'sender'):
-                    if hasattr(query.message_event.sender, 'nickname'):
-                        sender_name = query.message_event.sender.nickname
-                    elif hasattr(query.message_event.sender, 'member_name'):
-                        sender_name = query.message_event.sender.member_name
-
             # Try to record message
             # Use JSON serialization to preserve message chain structure (including image URLs, etc.)
             if hasattr(query, 'message_chain') and hasattr(query.message_chain, 'model_dump'):
@@ -66,7 +57,6 @@ class MonitoringHelper:
                 if hasattr(query.launcher_type, 'value')
                 else str(query.launcher_type),
                 user_id=query.sender_id,
-                user_name=sender_name,
                 runner_name=runner_name,
                 variables=None,  # Will be updated in record_query_success
             )
@@ -90,7 +80,6 @@ class MonitoringHelper:
                     if hasattr(query.launcher_type, 'value')
                     else str(query.launcher_type),
                     user_id=query.sender_id,
-                    user_name=sender_name,
                 )
 
             return message_id
@@ -125,70 +114,6 @@ class MonitoringHelper:
         except Exception as e:
             ap.logger.error(f'Failed to record query success: {e}')
 
-    @staticmethod
-    async def record_query_response(
-        ap: app.Application,
-        query: pipeline_query.Query,
-        bot_id: str,
-        bot_name: str,
-        pipeline_id: str,
-        pipeline_name: str,
-        runner_name: str | None = None,
-    ):
-        """Record bot response message to monitoring"""
-        try:
-            session_id = f'{query.launcher_type}_{query.launcher_id}'
-
-            # Get sender name from message event
-            sender_name = None
-            if hasattr(query, 'message_event'):
-                if hasattr(query.message_event, 'sender'):
-                    if hasattr(query.message_event.sender, 'nickname'):
-                        sender_name = query.message_event.sender.nickname
-                    elif hasattr(query.message_event.sender, 'member_name'):
-                        sender_name = query.message_event.sender.member_name
-
-            # Extract response content from resp_message_chain
-            if hasattr(query, 'resp_message_chain') and query.resp_message_chain:
-                # Serialize the last response message chain
-                last_resp = query.resp_message_chain[-1]
-                if hasattr(last_resp, 'model_dump'):
-                    message_content = json.dumps(last_resp.model_dump(), ensure_ascii=False)
-                else:
-                    message_content = str(last_resp)
-            elif hasattr(query, 'resp_messages') and query.resp_messages:
-                last_resp = query.resp_messages[-1]
-                if hasattr(last_resp, 'get_content_platform_message_chain'):
-                    chain = last_resp.get_content_platform_message_chain()
-                    if hasattr(chain, 'model_dump'):
-                        message_content = json.dumps(chain.model_dump(), ensure_ascii=False)
-                    else:
-                        message_content = str(chain)
-                else:
-                    message_content = str(last_resp)
-            else:
-                return  # No response to record
-
-            await ap.monitoring_service.record_message(
-                bot_id=bot_id,
-                bot_name=bot_name,
-                pipeline_id=pipeline_id,
-                pipeline_name=pipeline_name,
-                message_content=message_content,
-                session_id=session_id,
-                status='success',
-                level='info',
-                platform=query.launcher_type.value
-                if hasattr(query.launcher_type, 'value')
-                else str(query.launcher_type),
-                user_id=query.sender_id,
-                user_name=sender_name,
-                runner_name=runner_name,
-                role='assistant',
-            )
-        except Exception as e:
-            ap.logger.error(f'Failed to record query response: {e}')
-
     @staticmethod
     async def record_query_error(
         ap: app.Application,
@@ -204,15 +129,6 @@ class MonitoringHelper:
         try:
             session_id = f'{query.launcher_type}_{query.launcher_id}'
 
-            # Get sender name from message event
-            sender_name = None
-            if hasattr(query, 'message_event'):
-                if hasattr(query.message_event, 'sender'):
-                    if hasattr(query.message_event.sender, 'nickname'):
-                        sender_name = query.message_event.sender.nickname
-                    elif hasattr(query.message_event.sender, 'member_name'):
-                        sender_name = query.message_event.sender.member_name
-
             # Record error message
             message_id = await ap.monitoring_service.record_message(
                 bot_id=bot_id,
@@ -227,7 +143,6 @@ class MonitoringHelper:
                 if hasattr(query.launcher_type, 'value')
                 else str(query.launcher_type),
                 user_id=query.sender_id,
-                user_name=sender_name,
                 runner_name=runner_name,
             )
 

src/langbot/pkg/pipeline/pipelinemgr.py

@@ -13,7 +13,6 @@ import langbot_plugin.api.entities.builtin.platform.message as platform_message
 import langbot_plugin.api.entities.builtin.platform.events as platform_events
 import langbot_plugin.api.entities.events as events
 from ..utils import importutil
-from .config_coercion import coerce_pipeline_config
 
 import langbot_plugin.api.entities.builtin.provider.session as provider_session
 import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
@@ -340,20 +339,6 @@ class RuntimePipeline:
                 except Exception as e:
                     self.ap.logger.error(f'Failed to record query success: {e}')
 
-                # Record bot response message
-                try:
-                    await monitoring_helper.MonitoringHelper.record_query_response(
-                        ap=self.ap,
-                        query=query,
-                        bot_id=query.bot_uuid or 'unknown',
-                        bot_name=bot_name,
-                        pipeline_id=self.pipeline_entity.uuid,
-                        pipeline_name=pipeline_name,
-                        runner_name=runner_name,
-                    )
-                except Exception as e:
-                    self.ap.logger.error(f'Failed to record query response: {e}')
-
         except Exception as e:
             inst_name = query.current_stage_name if query.current_stage_name else 'unknown'
             self.ap.logger.error(f'Error processing query {query.query_id} stage={inst_name} : {e}')
@@ -384,6 +369,8 @@ class RuntimePipeline:
 class PipelineManager:
     """流水线管理器"""
 
+    # ====== 4.0 ======
+
     ap: app.Application
 
     pipelines: list[RuntimePipeline]
@@ -421,14 +408,6 @@ class PipelineManager:
         elif isinstance(pipeline_entity, dict):
             pipeline_entity = persistence_pipeline.LegacyPipeline(**pipeline_entity)
 
-        coerce_pipeline_config(
-            pipeline_entity.config,
-            getattr(self.ap, 'pipeline_config_meta_trigger', {'name': 'trigger', 'stages': []}),
-            getattr(self.ap, 'pipeline_config_meta_safety', {'name': 'safety', 'stages': []}),
-            getattr(self.ap, 'pipeline_config_meta_ai', {'name': 'ai', 'stages': []}),
-            getattr(self.ap, 'pipeline_config_meta_output', {'name': 'output', 'stages': []}),
-        )
-
         # initialize stage containers according to pipeline_entity.stages
         stage_containers: list[StageInstContainer] = []
         for stage_name in pipeline_entity.stages:

src/langbot/pkg/pipeline/preproc/preproc.py

@@ -36,36 +36,17 @@ class PreProcessor(stage.PipelineStage):
         session = await self.ap.sess_mgr.get_session(query)
 
         # When not local-agent, llm_model is None
-        llm_model = None
-        if selected_runner == 'local-agent':
-            # Read model config — new format is { primary: str, fallbacks: [str] },
-            # but handle legacy plain string for backward compatibility
-            model_config = query.pipeline_config['ai']['local-agent'].get('model', {})
-            if isinstance(model_config, str):
-                # Legacy format: plain UUID string
-                primary_uuid = model_config
-                fallback_uuids = []
-            else:
-                primary_uuid = model_config.get('primary', '')
-                fallback_uuids = model_config.get('fallbacks', [])
-
-            if primary_uuid:
-                try:
-                    llm_model = await self.ap.model_mgr.get_model_by_uuid(primary_uuid)
-                except ValueError:
-                    self.ap.logger.warning(f'LLM model {primary_uuid} not found or not configured')
-
-            # Resolve fallback model UUIDs
-            if fallback_uuids:
-                valid_fallbacks = []
-                for fb_uuid in fallback_uuids:
-                    try:
-                        await self.ap.model_mgr.get_model_by_uuid(fb_uuid)
-                        valid_fallbacks.append(fb_uuid)
-                    except ValueError:
-                        self.ap.logger.warning(f'Fallback model {fb_uuid} not found, skipping')
-                if valid_fallbacks:
-                    query.variables['_fallback_model_uuids'] = valid_fallbacks
+        try:
+            llm_model = (
+                await self.ap.model_mgr.get_model_by_uuid(query.pipeline_config['ai']['local-agent']['model'])
+                if selected_runner == 'local-agent'
+                else None
+            )
+        except ValueError:
+            self.ap.logger.warning(
+                f'LLM model {query.pipeline_config["ai"]["local-agent"]["model"] + " "}not found or not configured'
+            )
+            llm_model = None
 
         conversation = await self.ap.sess_mgr.get_conversation(
             query,
@@ -80,28 +61,20 @@ class PreProcessor(stage.PipelineStage):
         query.prompt = conversation.prompt.copy()
         query.messages = conversation.messages.copy()
 
-        if selected_runner == 'local-agent':
+        if selected_runner == 'local-agent' and llm_model:
             query.use_funcs = []
-            if llm_model:
-                query.use_llm_model_uuid = llm_model.model_entity.uuid
+            query.use_llm_model_uuid = llm_model.model_entity.uuid
 
-                if llm_model.model_entity.abilities.__contains__('func_call'):
-                    # Get bound plugins and MCP servers for filtering tools
-                    bound_plugins = query.variables.get('_pipeline_bound_plugins', None)
-                    bound_mcp_servers = query.variables.get('_pipeline_bound_mcp_servers', None)
-                    query.use_funcs = await self.ap.tool_mgr.get_all_tools(bound_plugins, bound_mcp_servers)
-
-                    self.ap.logger.debug(f'Bound plugins: {bound_plugins}')
-                    self.ap.logger.debug(f'Bound MCP servers: {bound_mcp_servers}')
-                    self.ap.logger.debug(f'Use funcs: {query.use_funcs}')
-
-            # If primary model doesn't support func_call but fallback models exist,
-            # load tools anyway since fallback models may support them
-            if not query.use_funcs and query.variables.get('_fallback_model_uuids'):
+            if llm_model.model_entity.abilities.__contains__('func_call'):
+                # Get bound plugins and MCP servers for filtering tools
                 bound_plugins = query.variables.get('_pipeline_bound_plugins', None)
                 bound_mcp_servers = query.variables.get('_pipeline_bound_mcp_servers', None)
                 query.use_funcs = await self.ap.tool_mgr.get_all_tools(bound_plugins, bound_mcp_servers)
 
+                self.ap.logger.debug(f'Bound plugins: {bound_plugins}')
+                self.ap.logger.debug(f'Bound MCP servers: {bound_mcp_servers}')
+                self.ap.logger.debug(f'Use funcs: {query.use_funcs}')
+
         sender_name = ''
 
         if isinstance(query.message_event, platform_events.GroupMessage):
@@ -176,16 +149,6 @@ class PreProcessor(stage.PipelineStage):
         query.variables['user_message_text'] = plain_text
 
         query.user_message = provider_message.Message(role='user', content=content_list)
-
-        # Extract knowledge base UUIDs into query variables so plugins can modify them
-        # during PromptPreProcessing before the runner performs retrieval.
-        kb_uuids = query.pipeline_config['ai']['local-agent'].get('knowledge-bases', [])
-        if not kb_uuids:
-            old_kb_uuid = query.pipeline_config['ai']['local-agent'].get('knowledge-base', '')
-            if old_kb_uuid and old_kb_uuid != '__none__':
-                kb_uuids = [old_kb_uuid]
-        query.variables['_knowledge_base_uuids'] = list(kb_uuids)
-
         # =========== 触发事件 PromptPreProcessing
 
         event = events.PromptPreProcessing(

src/langbot/pkg/pipeline/process/handlers/chat.py

@@ -12,7 +12,7 @@ from ... import entities
 from ....provider import runner as runner_module
 
 import langbot_plugin.api.entities.events as events
-from ....utils import importutil, constants, runner as runner_utils
+from ....utils import importutil, constants
 from ....provider import runners
 import langbot_plugin.api.entities.builtin.provider.session as provider_session
 import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
@@ -149,19 +149,12 @@ class ChatMessageHandler(handler.MessageHandler):
                 self.ap.logger.error(f'Conversation({query.query_id}) Request Failed: {error_info}')
                 traceback.print_exc()
 
-                exception_handling = query.pipeline_config['output']['misc'].get('exception-handling', 'show-hint')
-
-                if exception_handling == 'show-error':
-                    user_notice = f'{e}'
-                elif exception_handling == 'show-hint':
-                    user_notice = query.pipeline_config['output']['misc'].get('failure-hint', 'Request failed.')
-                else:  # hide
-                    user_notice = None
+                hide_exception_info = query.pipeline_config['output']['misc']['hide-exception']
 
                 yield entities.StageProcessResult(
                     result_type=entities.ResultType.INTERRUPT,
                     new_query=query,
-                    user_notice=user_notice,
+                    user_notice='请求失败' if hide_exception_info else f'{e}',
                     error_notice=f'{e}',
                     debug_notice=traceback.format_exc(),
                 )
@@ -192,15 +185,10 @@ class ChatMessageHandler(handler.MessageHandler):
 
                     pipeline_plugins = query.variables.get('_pipeline_bound_plugins', None)
 
-                    runner_category = runner_utils.get_runner_category_from_runner(
-                        runner_name, runner, query.pipeline_config
-                    )
-
                     payload = {
                         'query_id': query.query_id,
                         'adapter': adapter_name,
                         'runner': runner_name,
-                        'runner_category': runner_category,
                         'duration_ms': duration_ms,
                         'model_name': model_name,
                         'version': constants.semantic_version,
@@ -212,11 +200,6 @@ class ChatMessageHandler(handler.MessageHandler):
 
                     # Send telemetry asynchronously and do not block pipeline via app's telemetry manager
                     await self.ap.telemetry.start_send_task(payload)
-
-                    # Trigger survey event on first successful non-WebSocket response
-                    if not locals().get('error_info') and adapter_name and 'WebSocket' not in adapter_name:
-                        if self.ap.survey:
-                            await self.ap.survey.trigger_event('first_bot_response_success')
                 except Exception as ex:
                     # Ensure telemetry issues do not affect normal flow
                     self.ap.logger.warning(f'Failed to send telemetry: {ex}')

src/langbot/pkg/platform/botmgr.py

@@ -18,6 +18,7 @@ import langbot_plugin.api.entities.builtin.provider.session as provider_session
 import langbot_plugin.api.entities.builtin.platform.events as platform_events
 import langbot_plugin.api.entities.builtin.platform.message as platform_message
 import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
+import langbot_plugin.api.entities.events as events
 
 
 class RuntimeBot:
@@ -82,7 +83,7 @@ class RuntimeBot:
                     if custom_launcher_id:
                         launcher_id = custom_launcher_id
 
-                await self.ap.msg_aggregator.add_message(
+                await self.ap.query_pool.add_query(
                     bot_uuid=self.bot_entity.uuid,
                     launcher_type=provider_session.LauncherTypes.PERSON,
                     launcher_id=launcher_id,
@@ -125,7 +126,7 @@ class RuntimeBot:
                     if custom_launcher_id:
                         launcher_id = custom_launcher_id
 
-                await self.ap.msg_aggregator.add_message(
+                await self.ap.query_pool.add_query(
                     bot_uuid=self.bot_entity.uuid,
                     launcher_type=provider_session.LauncherTypes.GROUP,
                     launcher_id=launcher_id,
@@ -141,6 +142,56 @@ class RuntimeBot:
         self.adapter.register_listener(platform_events.FriendMessage, on_friend_message)
         self.adapter.register_listener(platform_events.GroupMessage, on_group_message)
 
+        async def on_notice(
+            event: platform_events.NoticeEvent,
+            adapter: abstract_platform_adapter.AbstractMessagePlatformAdapter,
+        ):
+            await self.logger.info(f'Notice event: {event.notice_type} {event.sub_type}')
+
+            try:
+                event_obj = events.NoticeReceived(
+                    notice_type=event.notice_type,
+                    sub_type=event.sub_type,
+                    group_id=event.group_id,
+                    user_id=event.user_id,
+                    operator_id=event.operator_id,
+                    target_id=event.target_id,
+                    message_id=event.message_id,
+                    duration=event.duration,
+                    file=event.file,
+                    honor_type=event.honor_type,
+                )
+
+                if hasattr(self.ap, 'plugin_connector') and self.ap.plugin_connector:
+                    await self.ap.plugin_connector.emit_event(event_obj)
+            except Exception:
+                await self.logger.error(f'Error emitting notice event: {traceback.format_exc()}')
+
+        self.adapter.register_listener(platform_events.NoticeEvent, on_notice)
+
+        async def on_request(
+            event: platform_events.RequestEvent,
+            adapter: abstract_platform_adapter.AbstractMessagePlatformAdapter,
+        ):
+            await self.logger.info(f'Request event: {event.request_type} {event.sub_type}')
+
+            try:
+                event_obj = events.RequestReceived(
+                    request_type=event.request_type,
+                    sub_type=event.sub_type,
+                    user_id=event.user_id,
+                    group_id=event.group_id,
+                    comment=event.comment,
+                    flag=event.flag,
+                )
+
+                if hasattr(self.ap, 'plugin_connector') and self.ap.plugin_connector:
+                    await self.ap.plugin_connector.emit_event(event_obj)
+            except Exception:
+                await self.logger.error(f'Error emitting request event: {traceback.format_exc()}')
+
+        self.adapter.register_listener(platform_events.RequestEvent, on_request)
+
     async def run(self):
         async def exception_wrapper():
             try:
@@ -282,8 +333,6 @@ class PlatformManager:
         return runtime_bot
 
     async def get_bot_by_uuid(self, bot_uuid: str) -> RuntimeBot | None:
-        if self.websocket_proxy_bot and self.websocket_proxy_bot.bot_entity.uuid == bot_uuid:
-            return self.websocket_proxy_bot
         for bot in self.bots:
             if bot.bot_entity.uuid == bot_uuid:
                 return bot

src/langbot/pkg/platform/sources/aiocqhttp.py

@@ -306,9 +306,8 @@ class AiocqhttpEventConverter(abstract_platform_adapter.AbstractEventConverter):
 
     @staticmethod
     async def target2yiri(event: aiocqhttp.Event, bot=None):
-        yiri_chain = await AiocqhttpMessageConverter.target2yiri(event.message, event.message_id, bot)
-
         if event.message_type == 'group':
+            yiri_chain = await AiocqhttpMessageConverter.target2yiri(event.message, event.message_id, bot)
             permission = 'MEMBER'
 
             if 'role' in event.sender:
@@ -334,6 +333,7 @@ class AiocqhttpEventConverter(abstract_platform_adapter.AbstractEventConverter):
             )
             return converted_event
         elif event.message_type == 'private':
+            yiri_chain = await AiocqhttpMessageConverter.target2yiri(event.message, event.message_id, bot)
             return platform_events.FriendMessage(
                 sender=platform_entities.Friend(
                     id=event.sender['user_id'],
@@ -344,6 +344,57 @@ class AiocqhttpEventConverter(abstract_platform_adapter.AbstractEventConverter):
                 time=event.time,
                 source_platform_object=event,
             )
+        elif event.post_type == 'notice':
+            yiri_chain = platform_message.MessageChain(
+                [
+                    platform_message.Source(id=-1, time=datetime.datetime.now()),
+                    platform_message.Notice(
+                        notice_type=event.get('notice_type', ''),
+                        sub_type=event.get('sub_type', ''),
+                        user_id=event.get('user_id', None),
+                        target_id=event.get('target_id', None),
+                        group_id=event.get('group_id', None),
+                        operator_id=event.get('operator_id', None),
+                        message_id=event.get('message_id', None),
+                        duration=event.get('duration', None),
+                        file=event.get('file', None),
+                        honor_type=event.get('honor_type', None),
+                    ),
+                ]
+            )
+            return platform_events.NoticeEvent(
+                notice_type=event.get('notice_type', ''),
+                sub_type=event.get('sub_type', ''),
+                user_id=event.get('user_id', None),
+                target_id=event.get('target_id', None),
+                group_id=event.get('group_id', None),
+                time=event.time,
+                source_platform_object=event,
+            )
+        elif event.post_type == 'request':
+            yiri_chain = platform_message.MessageChain(
+                [
+                    platform_message.Source(id=-1, time=datetime.datetime.now()),
+                    platform_message.Request(
+                        request_type=event.get('request_type', ''),
+                        sub_type=event.get('sub_type', ''),
+                        user_id=event.get('user_id', None),
+                        group_id=event.get('group_id', None),
+                        comment=event.get('comment', ''),
+                        flag=event.get('flag', ''),
+                    ),
+                ]
+            )
+            return platform_events.RequestEvent(
+                request_type=event.get('request_type', ''),
+                sub_type=event.get('sub_type', ''),
+                user_id=event.get('user_id', None),
+                group_id=event.get('group_id', None),
+                comment=event.get('comment', ''),
+                flag=event.get('flag', ''),
+                time=event.time,
+                source_platform_object=event,
+            )
 
 
 class AiocqhttpAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
@@ -375,18 +426,6 @@ class AiocqhttpAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
             self.bot = aiocqhttp.CQHttp()
 
     async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain):
-        # Check if message contains a Forward component
-        forward_msg = message.get_first(platform_message.Forward)
-        if forward_msg:
-            if target_type == 'group':
-                # Send as merged forward message via OneBot API
-                await self._send_forward_message(int(target_id), forward_msg)
-                return
-            else:
-                await self.logger.warning(
-                    f'Forward message is only supported for group targets, got target_type={target_type}. Falling through to normal send.'
-                )
-
         aiocq_msg = (await AiocqhttpMessageConverter.yiri2target(message))[0]
 
         if target_type == 'group':
@@ -394,90 +433,6 @@ class AiocqhttpAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
         elif target_type == 'person':
             await self.bot.send_private_msg(user_id=int(target_id), message=aiocq_msg)
 
-    async def _send_forward_message(self, group_id: int, forward: platform_message.Forward):
-        """Send a merged forward message to a group using NapCat extended API."""
-        messages = []
-
-        for node in forward.node_list:
-            # Build content for each node
-            content = []
-            if node.message_chain:
-                for component in node.message_chain:
-                    if isinstance(component, platform_message.Plain):
-                        if component.text:
-                            content.append({'type': 'text', 'data': {'text': component.text}})
-                    elif isinstance(component, platform_message.Image):
-                        img_data = {}
-                        if component.base64:
-                            b64 = component.base64
-                            if b64.startswith('data:'):
-                                b64 = b64.split(',', 1)[-1] if ',' in b64 else b64
-                            img_data['file'] = f'base64://{b64}'
-                        elif component.url:
-                            img_data['file'] = component.url
-                        elif component.path:
-                            img_data['file'] = str(component.path)
-
-                        if img_data:
-                            content.append({'type': 'image', 'data': img_data})
-
-            if not content:
-                continue
-
-            # Build node data - use user_id and nickname format for NapCat
-            user_id = str(node.sender_id) if node.sender_id else str(self.bot_account_id or '10000')
-            node_data = {
-                'type': 'node',
-                'data': {
-                    'user_id': user_id,
-                    'nickname': node.sender_name or '未知',
-                    'content': content,
-                },
-            }
-
-            messages.append(node_data)
-
-        if not messages:
-            return
-
-        # Build the full message payload for NapCat's send_forward_msg API
-        # This matches the format used by GiveMeSetuPlugin
-        bot_id = str(self.bot_account_id) if self.bot_account_id else '10000'
-        payload = {
-            'group_id': group_id,
-            'user_id': bot_id,  # Required by NapCat for display
-            'messages': messages,
-        }
-
-        # Add display settings if available
-        if forward.display:
-            if forward.display.title:
-                payload['news'] = [{'text': forward.display.title}]
-            if forward.display.brief:
-                payload['prompt'] = forward.display.brief
-            if forward.display.summary:
-                payload['summary'] = forward.display.summary
-            if forward.display.source:
-                payload['source'] = forward.display.source
-
-        try:
-            # Use send_forward_msg (NapCat extended API) instead of send_group_forward_msg
-            await self.logger.info(
-                f'Sending forward message to group {group_id} with {len(messages)} nodes, payload keys: {list(payload.keys())}'
-            )
-            result = await self.bot.call_action('send_forward_msg', **payload)
-            await self.logger.info(f'Forward message sent to group {group_id}, result: {result}')
-        except Exception as e:
-            await self.logger.error(f'Failed to send forward message to group {group_id}: {e}')
-            # Fallback: try standard OneBot API with integer group_id
-            try:
-                await self.logger.info('Trying fallback API send_group_forward_msg')
-                await self.bot.call_action('send_group_forward_msg', group_id=group_id, messages=messages)
-                await self.logger.info(f'Forward message sent via fallback API to group {group_id}')
-            except Exception as e2:
-                await self.logger.error(f'Fallback also failed: {e2}')
-                raise
-
     async def reply_message(
         self,
         message_source: platform_events.MessageEvent,
@@ -509,12 +464,31 @@ class AiocqhttpAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
                 await self.logger.error(f'Error in on_message: {traceback.format_exc()}')
                 traceback.print_exc()
 
+        async def on_notice(event: aiocqhttp.Event):
+            self.bot_account_id = event.self_id
+            try:
+                return await callback(await self.event_converter.target2yiri(event, self.bot), self)
+            except Exception:
+                await self.logger.error(f'Error in on_notice: {traceback.format_exc()}')
+                traceback.print_exc()
+
+        async def on_request(event: aiocqhttp.Event):
+            self.bot_account_id = event.self_id
+            try:
+                return await callback(await self.event_converter.target2yiri(event, self.bot), self)
+            except Exception:
+                await self.logger.error(f'Error in on_request: {traceback.format_exc()}')
+                traceback.print_exc()
+
         if event_type == platform_events.GroupMessage:
             self.bot.on_message('group')(on_message)
             # self.bot.on_notice()(on_message)
         elif event_type == platform_events.FriendMessage:
             self.bot.on_message('private')(on_message)
-            # self.bot.on_notice()(on_message)
+        elif event_type == platform_events.NoticeEvent:
+            self.bot.on_notice()(on_notice)
+        elif event_type == platform_events.RequestEvent:
+            self.bot.on_request()(on_request)
         # print(event_type)
 
         async def on_websocket_connection(event: aiocqhttp.Event):

src/langbot/pkg/platform/sources/discord.py

@@ -14,7 +14,7 @@ import io
 import asyncio
 from enum import Enum
 
-from langbot.pkg.utils import httpclient
+import aiohttp
 import pydantic
 
 import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
@@ -622,23 +622,23 @@ class DiscordMessageConverter(abstract_platform_adapter.AbstractMessageConverter
                     image_bytes = base64.b64decode(base64_data)
                 elif ele.url:
                     # 从URL下载图片
-                    session = httpclient.get_session()
-                    async with session.get(ele.url) as response:
-                        image_bytes = await response.read()
-                        # 从URL或Content-Type推断文件类型
-                        content_type = response.headers.get('Content-Type', '')
-                        if 'jpeg' in content_type or 'jpg' in content_type:
-                            filename = f'{uuid.uuid4()}.jpg'
-                        elif 'gif' in content_type:
-                            filename = f'{uuid.uuid4()}.gif'
-                        elif 'webp' in content_type:
-                            filename = f'{uuid.uuid4()}.webp'
-                        elif ele.url.lower().endswith(('.jpg', '.jpeg')):
-                            filename = f'{uuid.uuid4()}.jpg'
-                        elif ele.url.lower().endswith('.gif'):
-                            filename = f'{uuid.uuid4()}.gif'
-                        elif ele.url.lower().endswith('.webp'):
-                            filename = f'{uuid.uuid4()}.webp'
+                    async with aiohttp.ClientSession() as session:
+                        async with session.get(ele.url) as response:
+                            image_bytes = await response.read()
+                            # 从URL或Content-Type推断文件类型
+                            content_type = response.headers.get('Content-Type', '')
+                            if 'jpeg' in content_type or 'jpg' in content_type:
+                                filename = f'{uuid.uuid4()}.jpg'
+                            elif 'gif' in content_type:
+                                filename = f'{uuid.uuid4()}.gif'
+                            elif 'webp' in content_type:
+                                filename = f'{uuid.uuid4()}.webp'
+                            elif ele.url.lower().endswith(('.jpg', '.jpeg')):
+                                filename = f'{uuid.uuid4()}.jpg'
+                            elif ele.url.lower().endswith('.gif'):
+                                filename = f'{uuid.uuid4()}.gif'
+                            elif ele.url.lower().endswith('.webp'):
+                                filename = f'{uuid.uuid4()}.webp'
                 elif ele.path:
                     # 从文件路径读取图片
                     # 确保路径没有空字节
@@ -702,9 +702,9 @@ class DiscordMessageConverter(abstract_platform_adapter.AbstractMessageConverter
                     file_base64 = ele.base64.split(',')[-1]
                     file_bytes = base64.b64decode(file_base64)
                 elif ele.url:
-                    session = httpclient.get_session()
-                    async with session.get(ele.url) as response:
-                        file_bytes = await response.read()
+                    async with aiohttp.ClientSession() as session:
+                        async with session.get(ele.url) as response:
+                            file_bytes = await response.read()
                 if file_bytes:
                     files.append(discord.File(fp=io.BytesIO(file_bytes), filename=filename))
             elif isinstance(ele, platform_message.File):
@@ -717,9 +717,9 @@ class DiscordMessageConverter(abstract_platform_adapter.AbstractMessageConverter
                     else:
                         file_bytes = base64.b64decode(ele.base64)
                 elif ele.url:
-                    session = httpclient.get_session()
-                    async with session.get(ele.url) as response:
-                        file_bytes = await response.read()
+                    async with aiohttp.ClientSession() as session:
+                        async with session.get(ele.url) as response:
+                            file_bytes = await response.read()
                 if file_bytes:
                     files.append(discord.File(fp=io.BytesIO(file_bytes), filename=filename))
             elif isinstance(ele, platform_message.Forward):
@@ -775,12 +775,12 @@ class DiscordMessageConverter(abstract_platform_adapter.AbstractMessageConverter
 
         # attachments
         for attachment in message.attachments:
-            session = httpclient.get_session(trust_env=True)
-            async with session.get(attachment.url) as response:
-                image_data = await response.read()
-                image_base64 = base64.b64encode(image_data).decode('utf-8')
-                image_format = response.headers['Content-Type']
-                element_list.append(platform_message.Image(base64=f'data:{image_format};base64,{image_base64}'))
+            async with aiohttp.ClientSession(trust_env=True) as session:
+                async with session.get(attachment.url) as response:
+                    image_data = await response.read()
+                    image_base64 = base64.b64encode(image_data).decode('utf-8')
+                    image_format = response.headers['Content-Type']
+                    element_list.append(platform_message.Image(base64=f'data:{image_format};base64,{image_base64}'))
 
         return platform_message.MessageChain(element_list)
 

src/langbot/pkg/platform/sources/kook.py

@@ -9,8 +9,6 @@ import traceback
 import time
 
 import aiohttp
-
-from langbot.pkg.utils import httpclient
 import websockets
 import pydantic
 
@@ -122,16 +120,16 @@ class KookMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
             if content:
                 # Download image and convert to base64
                 try:
-                    session = httpclient.get_session()
-                    async with session.get(content) as response:
-                        if response.status == 200:
-                            image_bytes = await response.read()
-                            image_base64 = base64.b64encode(image_bytes).decode('utf-8')
-                            # Detect image format
-                            content_type = response.headers.get('Content-Type', 'image/png')
-                            components.append(
-                                platform_message.Image(base64=f'data:{content_type};base64,{image_base64}')
-                            )
+                    async with aiohttp.ClientSession() as session:
+                        async with session.get(content) as response:
+                            if response.status == 200:
+                                image_bytes = await response.read()
+                                image_base64 = base64.b64encode(image_bytes).decode('utf-8')
+                                # Detect image format
+                                content_type = response.headers.get('Content-Type', 'image/png')
+                                components.append(
+                                    platform_message.Image(base64=f'data:{content_type};base64,{image_base64}')
+                                )
                 except Exception:
                     # If download fails, just add as plain text
                     components.append(platform_message.Plain(text=f'[Image: {content}]'))
@@ -297,17 +295,17 @@ class KookAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             'Authorization': f'Bot {self.config["token"]}',
         }
 
-        session = httpclient.get_session()
-        async with session.get(base_url, params=params, headers=headers) as response:
-            if response.status == 200:
-                data = await response.json()
-                if data.get('code') == 0:
-                    gateway_url = data['data']['url']
-                    return gateway_url
+        async with aiohttp.ClientSession() as session:
+            async with session.get(base_url, params=params, headers=headers) as response:
+                if response.status == 200:
+                    data = await response.json()
+                    if data.get('code') == 0:
+                        gateway_url = data['data']['url']
+                        return gateway_url
+                    else:
+                        raise Exception(f'Failed to get gateway URL: {data.get("message")}')
                 else:
-                    raise Exception(f'Failed to get gateway URL: {data.get("message")}')
-            else:
-                raise Exception(f'Failed to get gateway URL: HTTP {response.status}')
+                    raise Exception(f'Failed to get gateway URL: HTTP {response.status}')
 
     async def _get_bot_user_info(self) -> dict:
         """Get bot's own user information from KOOK API"""
@@ -317,17 +315,17 @@ class KookAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             'Authorization': f'Bot {self.config["token"]}',
         }
 
-        session = httpclient.get_session()
-        async with session.get(base_url, headers=headers) as response:
-            if response.status == 200:
-                data = await response.json()
-                if data.get('code') == 0:
-                    user_info = data['data']
-                    return user_info
+        async with aiohttp.ClientSession() as session:
+            async with session.get(base_url, headers=headers) as response:
+                if response.status == 200:
+                    data = await response.json()
+                    if data.get('code') == 0:
+                        user_info = data['data']
+                        return user_info
+                    else:
+                        raise Exception(f'Failed to get bot user info: {data.get("message")}')
                 else:
-                    raise Exception(f'Failed to get bot user info: {data.get("message")}')
-            else:
-                raise Exception(f'Failed to get bot user info: HTTP {response.status}')
+                    raise Exception(f'Failed to get bot user info: HTTP {response.status}')
 
     async def _handle_hello(self, data: dict):
         """Handle HELLO signal (signal 1)"""
@@ -512,7 +510,7 @@ class KookAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
 
         try:
             if not self.http_session:
-                self.http_session = httpclient.get_session()
+                self.http_session = aiohttp.ClientSession()
 
             async with self.http_session.post(url, json=payload, headers=headers) as response:
                 if response.status == 200:
@@ -578,7 +576,7 @@ class KookAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
 
         try:
             if not self.http_session:
-                self.http_session = httpclient.get_session()
+                self.http_session = aiohttp.ClientSession()
 
             async with self.http_session.post(url, json=payload, headers=headers) as response:
                 if response.status == 200:
@@ -626,7 +624,7 @@ class KookAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
 
         try:
             # Create HTTP session
-            self.http_session = httpclient.get_session()
+            self.http_session = aiohttp.ClientSession()
 
             await self.logger.info('Starting KOOK adapter')
 

src/langbot/pkg/platform/sources/lark.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 import lark_oapi
-from lark_oapi.api.im.v1 import CreateImageRequest, CreateImageRequestBody, CreateFileRequest, CreateFileRequestBody
+from lark_oapi.api.im.v1 import CreateImageRequest, CreateImageRequestBody
 import traceback
 import typing
 import asyncio
@@ -17,7 +17,7 @@ import tempfile
 import os
 import mimetypes
 
-from langbot.pkg.utils import httpclient
+import aiohttp
 import lark_oapi.ws.exception
 import quart
 from lark_oapi.api.im.v1 import *
@@ -78,13 +78,13 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
                 return None
         elif msg.url:
             try:
-                session = httpclient.get_session()
-                async with session.get(msg.url) as response:
-                    if response.status == 200:
-                        image_bytes = await response.read()
-                    else:
-                        print(f'Failed to download image from {msg.url}: HTTP {response.status}')
-                        return None
+                async with aiohttp.ClientSession() as session:
+                    async with session.get(msg.url) as response:
+                        if response.status == 200:
+                            image_bytes = await response.read()
+                        else:
+                            print(f'Failed to download image from {msg.url}: HTTP {response.status}')
+                            return None
             except Exception as e:
                 print(f'Failed to download image from {msg.url}: {e}')
                 traceback.print_exc()
@@ -141,88 +141,6 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
             traceback.print_exc()
             return None
 
-    @staticmethod
-    async def upload_file_to_lark(
-        file_bytes: bytes,
-        api_client: lark_oapi.Client,
-        file_type: str,
-        file_name: str = 'file',
-        duration: typing.Optional[int] = None,
-    ) -> typing.Optional[str]:
-        """Upload a file to Lark and return the file_key, or None if upload fails.
-
-        Args:
-            file_bytes: Raw file bytes.
-            api_client: Lark API client.
-            file_type: Lark file type, e.g. 'opus', 'mp4', 'pdf', 'doc', etc.
-            file_name: Display name for the file.
-            duration: Duration in milliseconds (for audio files).
-        """
-        try:
-            with tempfile.NamedTemporaryFile(delete=False) as temp_file:
-                temp_file.write(file_bytes)
-                temp_file_path = temp_file.name
-
-            try:
-                body_builder = (
-                    CreateFileRequestBody.builder()
-                    .file_type(file_type)
-                    .file_name(file_name)
-                    .file(open(temp_file_path, 'rb'))
-                )
-                if duration is not None:
-                    body_builder = body_builder.duration(duration)
-
-                request = CreateFileRequest.builder().request_body(body_builder.build()).build()
-
-                response = await api_client.im.v1.file.acreate(request)
-
-                if not response.success():
-                    print(
-                        f'client.im.v1.file.create failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}'
-                    )
-                    return None
-
-                return response.data.file_key
-            finally:
-                os.unlink(temp_file_path)
-        except Exception as e:
-            print(f'Failed to upload file to Lark: {e}')
-            traceback.print_exc()
-            return None
-
-    @staticmethod
-    async def _get_media_bytes(
-        msg: typing.Union[platform_message.Voice, platform_message.File],
-    ) -> typing.Optional[bytes]:
-        """Get bytes from a Voice or File message (base64, url, or path)."""
-        data = None
-
-        if msg.base64:
-            try:
-                base64_str = msg.base64
-                if ',' in base64_str:
-                    base64_str = base64_str.split(',', 1)[1]
-                data = base64.b64decode(base64_str)
-            except Exception:
-                pass
-        elif msg.url:
-            try:
-                session = httpclient.get_session()
-                async with session.get(msg.url) as resp:
-                    if resp.status == 200:
-                        data = await resp.read()
-            except Exception:
-                pass
-        elif msg.path:
-            try:
-                with open(msg.path, 'rb') as f:
-                    data = f.read()
-            except Exception:
-                pass
-
-        return data
-
     @staticmethod
     async def yiri2target(
         message_chain: platform_message.MessageChain, api_client: lark_oapi.Client
@@ -232,10 +150,10 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
         Returns:
             Tuple of (text_elements, image_keys):
             - text_elements: List of paragraphs for post message format
-            - media_items: List of dicts with 'msg_type' and 'content' for separate media messages
+            - image_keys: List of image_key strings for separate image messages
         """
         message_elements = []
-        media_items = []
+        image_keys = []
         pending_paragraph = []
 
         # Regex pattern to match Markdown image syntax: ![alt](url)
@@ -278,77 +196,40 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
                 # Check for and extract Markdown images from text
                 cleaned_text, extracted_urls = await process_text_with_images(text)
 
-                # Split by blank lines to create separate paragraphs for Lark post format.
-                # Lark truncates md elements at the first \n\n, so we must use the
-                # post format's native paragraph structure instead.
+                # Add cleaned text if not empty
                 if cleaned_text:
-                    segments = re.split(r'\n\s*\n', cleaned_text)
-                    for i, segment in enumerate(segments):
-                        segment = segment.strip()
-                        if not segment:
-                            continue
-                        if i > 0 and pending_paragraph:
-                            message_elements.append(pending_paragraph)
-                            pending_paragraph = []
-                        pending_paragraph.append({'tag': 'md', 'text': segment})
+                    pending_paragraph.append({'tag': 'md', 'text': cleaned_text})
 
                 # Process extracted image URLs
                 for url in extracted_urls:
+                    # Create a temporary Image message to upload
                     temp_image = platform_message.Image(url=url)
                     image_key = await LarkMessageConverter.upload_image_to_lark(temp_image, api_client)
                     if image_key:
-                        media_items.append({'msg_type': 'image', 'content': {'image_key': image_key}})
+                        image_keys.append(image_key)
 
             elif isinstance(msg, platform_message.At):
                 pending_paragraph.append({'tag': 'at', 'user_id': msg.target, 'style': []})
             elif isinstance(msg, platform_message.AtAll):
                 pending_paragraph.append({'tag': 'at', 'user_id': 'all', 'style': []})
             elif isinstance(msg, platform_message.Image):
+                # Upload image and get image_key
                 image_key = await LarkMessageConverter.upload_image_to_lark(msg, api_client)
                 if image_key:
-                    media_items.append({'msg_type': 'image', 'content': {'image_key': image_key}})
-            elif isinstance(msg, platform_message.Voice):
-                data = await LarkMessageConverter._get_media_bytes(msg)
-                if data:
-                    duration = int(msg.length * 1000) if msg.length else None
-                    file_key = await LarkMessageConverter.upload_file_to_lark(
-                        data, api_client, file_type='opus', file_name='voice.opus', duration=duration
-                    )
-                    if file_key:
-                        media_items.append({'msg_type': 'audio', 'content': {'file_key': file_key}})
-            elif isinstance(msg, platform_message.File):
-                data = await LarkMessageConverter._get_media_bytes(msg)
-                if data:
-                    file_name = msg.name or 'file'
-                    # Guess file_type from extension
-                    ext = os.path.splitext(file_name)[1].lstrip('.').lower() if file_name else ''
-                    file_type_map = {
-                        'opus': 'opus',
-                        'mp4': 'mp4',
-                        'pdf': 'pdf',
-                        'doc': 'doc',
-                        'docx': 'doc',
-                        'xls': 'xls',
-                        'xlsx': 'xls',
-                        'ppt': 'ppt',
-                        'pptx': 'ppt',
-                    }
-                    file_type = file_type_map.get(ext, 'stream')
-                    file_key = await LarkMessageConverter.upload_file_to_lark(
-                        data, api_client, file_type=file_type, file_name=file_name
-                    )
-                    if file_key:
-                        media_items.append({'msg_type': 'file', 'content': {'file_key': file_key}})
+                    # Store image_key for separate image message
+                    image_keys.append(image_key)
             elif isinstance(msg, platform_message.Forward):
                 for node in msg.node_list:
-                    sub_elements, sub_media = await LarkMessageConverter.yiri2target(node.message_chain, api_client)
+                    sub_elements, sub_image_keys = await LarkMessageConverter.yiri2target(
+                        node.message_chain, api_client
+                    )
                     message_elements.extend(sub_elements)
-                    media_items.extend(sub_media)
+                    image_keys.extend(sub_image_keys)
 
         if pending_paragraph:
             message_elements.append(pending_paragraph)
 
-        return message_elements, media_items
+        return message_elements, image_keys
 
     @staticmethod
     async def target2yiri(
@@ -575,127 +456,6 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
 
 
 class LarkEventConverter(abstract_platform_adapter.AbstractEventConverter):
-    _processed_thread_quote_cache: typing.ClassVar[dict[str, float]] = {}
-    _processed_thread_quote_cache_max_size: typing.ClassVar[int] = 4096
-    _processed_thread_quote_cache_ttl_seconds: typing.ClassVar[int] = 86400
-
-    @classmethod
-    def _prune_processed_thread_quote_cache(cls, now: typing.Optional[float] = None) -> None:
-        if now is None:
-            now = time.time()
-
-        expire_before = now - cls._processed_thread_quote_cache_ttl_seconds
-        while cls._processed_thread_quote_cache:
-            oldest_key, oldest_ts = next(iter(cls._processed_thread_quote_cache.items()))
-            if oldest_ts >= expire_before:
-                break
-            cls._processed_thread_quote_cache.pop(oldest_key, None)
-
-        while len(cls._processed_thread_quote_cache) > cls._processed_thread_quote_cache_max_size:
-            oldest_key = next(iter(cls._processed_thread_quote_cache))
-            cls._processed_thread_quote_cache.pop(oldest_key, None)
-
-    @classmethod
-    def _mark_thread_quote_processed(cls, thread_id: str) -> None:
-        now = time.time()
-        cls._prune_processed_thread_quote_cache(now)
-        cls._processed_thread_quote_cache[thread_id] = now
-
-    @classmethod
-    def _extract_quote_message_id(cls, message: EventMessage) -> typing.Optional[str]:
-        """
-        Extract the message ID to quote from the given message.
-
-        Rules:
-        - First thread reply in a topic: return parent_id and mark topic as processed
-        - Follow-up thread replies in the same topic: return None
-        - Non-thread message: return parent_id if valid (non-empty, different from message_id)
-
-        Thread reply state is kept in a bounded TTL cache to avoid unbounded memory growth.
-        """
-        parent_id = getattr(message, 'parent_id', None)
-        if not parent_id:
-            return None
-
-        message_id = getattr(message, 'message_id', None)
-        if parent_id == message_id:
-            return None
-
-        thread_id = getattr(message, 'thread_id', None)
-        if thread_id:
-            cls._prune_processed_thread_quote_cache()
-            if thread_id in cls._processed_thread_quote_cache:
-                return None
-            cls._mark_thread_quote_processed(thread_id)
-
-        return parent_id
-
-    @staticmethod
-    def _build_event_message_from_message_item(message_item: Message) -> typing.Optional[EventMessage]:
-        """
-        Build EventMessage from SDK typed Message item.
-
-        Returns None if body or content is missing.
-        """
-        body = getattr(message_item, 'body', None)
-        if not body:
-            return None
-
-        content = getattr(body, 'content', None)
-        if not content:
-            return None
-
-        event_data = {
-            'message_id': message_item.message_id,
-            'message_type': message_item.msg_type,
-            'content': content,
-            'create_time': message_item.create_time,
-            'mentions': getattr(message_item, 'mentions', []) or [],
-        }
-
-        # Preserve thread-related fields
-        if hasattr(message_item, 'parent_id') and message_item.parent_id:
-            event_data['parent_id'] = message_item.parent_id
-        if hasattr(message_item, 'root_id') and message_item.root_id:
-            event_data['root_id'] = message_item.root_id
-        if hasattr(message_item, 'thread_id') and message_item.thread_id:
-            event_data['thread_id'] = message_item.thread_id
-        if hasattr(message_item, 'chat_id') and message_item.chat_id:
-            event_data['chat_id'] = message_item.chat_id
-
-        return EventMessage(event_data)
-
-    @staticmethod
-    async def _fetch_quoted_message(
-        quote_message_id: str,
-        api_client: lark_oapi.Client,
-    ) -> typing.Optional[platform_message.MessageChain]:
-        """
-        Fetch the quoted message and convert to MessageChain.
-
-        Returns None if:
-        - API call fails
-        - Response items is empty
-        - Message item normalization fails
-        """
-        request = GetMessageRequest.builder().message_id(quote_message_id).build()
-        response = await api_client.im.v1.message.aget(request)
-
-        if not response.success():
-            return None
-
-        items = getattr(response.data, 'items', None)
-        if not items:
-            return None
-
-        message_item = items[0]
-        event_message = LarkEventConverter._build_event_message_from_message_item(message_item)
-        if event_message is None:
-            return None
-
-        quote_chain = await LarkMessageConverter.target2yiri(event_message, api_client)
-        return quote_chain
-
     @staticmethod
     async def yiri2target(
         event: platform_events.MessageEvent,
@@ -708,23 +468,6 @@ class LarkEventConverter(abstract_platform_adapter.AbstractEventConverter):
     ) -> platform_events.Event:
         message_chain = await LarkMessageConverter.target2yiri(event.event.message, api_client)
 
-        # Check for quote/reply message
-        quote_message_id = LarkEventConverter._extract_quote_message_id(event.event.message)
-        if quote_message_id:
-            quote_chain = await LarkEventConverter._fetch_quoted_message(quote_message_id, api_client)
-            if quote_chain:
-                # Filter out Source component from quoted chain, keep only content
-                quote_origin = platform_message.MessageChain(
-                    [comp for comp in quote_chain if not isinstance(comp, platform_message.Source)]
-                )
-                if quote_origin:
-                    message_chain.append(
-                        platform_message.Quote(
-                            message_id=quote_message_id,
-                            origin=quote_origin,
-                        )
-                    )
-
         if event.event.message.chat_type == 'p2p':
             return platform_events.FriendMessage(
                 sender=platform_entities.Friend(
@@ -908,32 +651,6 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             self.request_tenant_access_token(tenant_key)
         return self.tenant_access_tokens.get(tenant_key)['token'] if self.tenant_access_tokens.get(tenant_key) else None
 
-    def get_launcher_id(self, event: platform_events.MessageEvent) -> str | None:
-        """
-        Get topic-scoped launcher_id for thread-aware session isolation.
-
-        For group thread messages, returns "{group_id}_{thread_id}"
-        to ensure conversation context stays stable per topic.
-
-        Returns None for non-thread messages or P2P messages.
-        """
-        source_event = getattr(event.source_platform_object, 'event', None)
-        if not source_event:
-            return None
-
-        message = getattr(source_event, 'message', None)
-        if not message:
-            return None
-
-        thread_id = getattr(message, 'thread_id', None)
-        if not thread_id:
-            return None
-
-        if isinstance(event, platform_events.GroupMessage):
-            return f'{event.group.id}_{thread_id}'
-
-        return None
-
     def build_api_client(self, config):
         app_id = config['app_id']
         app_secret = config['app_secret']
@@ -1200,40 +917,23 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
     ):
         # 不再需要了，因为message_id已经被包含到message_chain中
         # lark_event = await self.event_converter.yiri2target(message_source)
-        text_elements, media_items = await self.message_converter.yiri2target(message, self.api_client)
+        text_elements, image_keys = await self.message_converter.yiri2target(message, self.api_client)
 
         # Send text message if there are text elements
         if text_elements:
-            # Determine msg_type based on content: use 'post' if at mentions
-            # are present (requires post paragraph structure), otherwise 'text'
-            needs_post = any(ele['tag'] == 'at' for paragraph in text_elements for ele in paragraph)
-
-            if needs_post:
-                msg_type = 'post'
-                final_content = json.dumps(
-                    {
-                        'zh_Hans': {
-                            'title': '',
-                            'content': text_elements,
-                        },
-                    }
-                )
-            else:
-                msg_type = 'text'
-                parts = []
-                for paragraph in text_elements:
-                    para_text = ''.join(ele.get('text', '') for ele in paragraph)
-                    if para_text:
-                        parts.append(para_text)
-                final_content = json.dumps({'text': '\n\n'.join(parts)})
-
+            final_content = {
+                'zh_Hans': {
+                    'title': '',
+                    'content': text_elements,
+                },
+            }
             request: ReplyMessageRequest = (
                 ReplyMessageRequest.builder()
                 .message_id(message_source.message_chain.message_id)
                 .request_body(
                     ReplyMessageRequestBody.builder()
-                    .content(final_content)
-                    .msg_type(msg_type)
+                    .content(json.dumps(final_content))
+                    .msg_type('post')
                     .reply_in_thread(False)
                     .uuid(str(uuid.uuid4()))
                     .build()
@@ -1263,15 +963,17 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                     f'client.im.v1.message.reply failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}'
                 )
 
-        # Send media messages separately (image, audio, file, etc.)
-        for media in media_items:
+        # Send image messages separately using msg_type='image'
+        for image_key in image_keys:
+            image_content = json.dumps({'image_key': image_key})
+
             request: ReplyMessageRequest = (
                 ReplyMessageRequest.builder()
                 .message_id(message_source.message_chain.message_id)
                 .request_body(
                     ReplyMessageRequestBody.builder()
-                    .content(json.dumps(media['content']))
-                    .msg_type(media['msg_type'])
+                    .content(image_content)
+                    .msg_type('image')
                     .reply_in_thread(False)
                     .uuid(str(uuid.uuid4()))
                     .build()
@@ -1298,7 +1000,7 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
 
             if not response.success():
                 raise Exception(
-                    f'client.im.v1.message.reply ({media["msg_type"]}) failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}'
+                    f'client.im.v1.message.reply (image) failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}'
                 )
 
     async def reply_message_chunk(
@@ -1316,16 +1018,15 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         message_id = bot_message.resp_message_id
         msg_seq = bot_message.msg_sequence
         if msg_seq % 8 == 0 or is_final:
-            text_elements, media_items = await self.message_converter.yiri2target(message, self.api_client)
+            text_elements, image_keys = await self.message_converter.yiri2target(message, self.api_client)
 
             text_message = ''
             if text_elements:
-                parts = []
-                for paragraph in text_elements:
-                    para_text = ''.join(ele['text'] for ele in paragraph if ele['tag'] in ('text', 'md'))
-                    if para_text:
-                        parts.append(para_text)
-                text_message = '\n\n'.join(parts)
+                for ele in text_elements[0]:
+                    if ele['tag'] == 'text':
+                        text_message += ele['text']
+                    elif ele['tag'] == 'md':
+                        text_message += ele['text']
 
             # content = {
             #     'type': 'card_json',
@@ -1375,30 +1076,6 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
                 )
                 return
 
-            # Send media messages when streaming is done
-            if is_final and media_items:
-                for media in media_items:
-                    media_request: ReplyMessageRequest = (
-                        ReplyMessageRequest.builder()
-                        .message_id(message_source.message_chain.message_id)
-                        .request_body(
-                            ReplyMessageRequestBody.builder()
-                            .content(json.dumps(media['content']))
-                            .msg_type(media['msg_type'])
-                            .reply_in_thread(False)
-                            .uuid(str(uuid.uuid4()))
-                            .build()
-                        )
-                        .build()
-                    )
-                    media_response: ReplyMessageResponse = await self.api_client.im.v1.message.areply(
-                        media_request, req_opt
-                    )
-                    if not media_response.success():
-                        raise Exception(
-                            f'client.im.v1.message.reply ({media["msg_type"]}) failed, code: {media_response.code}, msg: {media_response.msg}, log_id: {media_response.get_log_id()}'
-                        )
-
     async def is_muted(self, group_id: int) -> bool:
         return False
 

src/langbot/pkg/platform/sources/legacy/gewechat.py

@@ -9,7 +9,7 @@ import copy
 import threading
 
 import quart
-from langbot.pkg.utils import httpclient
+import aiohttp
 
 import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
 from ....core import app
@@ -639,14 +639,14 @@ class GeWeChatAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
 
     async def run_async(self):
         if not self.config['token']:
-            session = httpclient.get_session()
-            async with session.post(
-                f'{self.config["gewechat_url"]}/v2/api/tools/getTokenId',
-                json={'app_id': self.config['app_id']},
-            ) as response:
-                if response.status != 200:
-                    raise Exception(f'获取gewechat token失败: {await response.text()}')
-                self.config['token'] = (await response.json())['data']
+            async with aiohttp.ClientSession() as session:
+                async with session.post(
+                    f'{self.config["gewechat_url"]}/v2/api/tools/getTokenId',
+                    json={'app_id': self.config['app_id']},
+                ) as response:
+                    if response.status != 200:
+                        raise Exception(f'获取gewechat token失败: {await response.text()}')
+                    self.config['token'] = (await response.json())['data']
 
         self.bot = gewechat_client.GewechatClient(f'{self.config["gewechat_url"]}/v2/api', self.config['token'])
 

src/langbot/pkg/platform/sources/openclaw_weixin.py

@@ -1,577 +0,0 @@
-"""OpenClaw WeChat adapter for LangBot.
-
-Uses the OpenClaw WeChat HTTP JSON API (long-poll getUpdates + sendMessage)
-to integrate personal WeChat accounts with LangBot.
-
-Reference: https://github.com/epiral/weixin-bot
-"""
-
-from __future__ import annotations
-
-import asyncio
-import base64
-import traceback
-import typing
-
-import pydantic
-import sqlalchemy
-
-from langbot.libs.openclaw_weixin_api.client import (
-    DEFAULT_BASE_URL,
-    SESSION_EXPIRED_ERRCODE,
-    OpenClawWeixinClient,
-)
-from langbot.libs.openclaw_weixin_api.types import (
-    MessageItem,
-    WeixinMessage,
-)
-from langbot.pkg.entity.persistence import bot as persistence_bot
-
-import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
-import langbot_plugin.api.definition.abstract.platform.event_logger as abstract_platform_logger
-import langbot_plugin.api.entities.builtin.platform.entities as platform_entities
-import langbot_plugin.api.entities.builtin.platform.events as platform_events
-import langbot_plugin.api.entities.builtin.platform.message as platform_message
-
-
-class OpenClawWeixinMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
-    """Converts between LangBot MessageChain and OpenClaw WeChat message items."""
-
-    @staticmethod
-    async def yiri2target(message_chain: platform_message.MessageChain) -> list[dict]:
-        """Convert LangBot MessageChain to a list of OpenClaw message item dicts."""
-        items = []
-        for component in message_chain:
-            if isinstance(component, platform_message.Plain):
-                items.append({'type': MessageItem.TEXT, 'text_item': {'text': component.text}})
-            elif isinstance(component, platform_message.Image):
-                # OpenClaw WeChat only supports text messages without CDN upload.
-                # For images, we send a placeholder text with the URL if available.
-                if component.url:
-                    items.append(
-                        {
-                            'type': MessageItem.TEXT,
-                            'text_item': {'text': f'[Image: {component.url}]'},
-                        }
-                    )
-                elif component.base64:
-                    items.append(
-                        {
-                            'type': MessageItem.TEXT,
-                            'text_item': {'text': '[Image]'},
-                        }
-                    )
-            elif isinstance(component, platform_message.File):
-                if component.name:
-                    items.append(
-                        {
-                            'type': MessageItem.TEXT,
-                            'text_item': {'text': f'[File: {component.name}]'},
-                        }
-                    )
-            elif isinstance(component, platform_message.Forward):
-                for node in component.node_list:
-                    if node.message_chain:
-                        items.extend(await OpenClawWeixinMessageConverter.yiri2target(node.message_chain))
-        return items
-
-    @staticmethod
-    async def target2yiri(
-        msg: WeixinMessage,
-    ) -> platform_message.MessageChain:
-        """Convert an OpenClaw WeixinMessage to LangBot MessageChain."""
-        components: list[platform_message.MessageComponent] = []
-
-        if not msg.item_list:
-            return platform_message.MessageChain(components)
-
-        for item in msg.item_list:
-            if item.type == MessageItem.TEXT and item.text_item and item.text_item.text:
-                text = item.text_item.text
-
-                # Handle quoted messages
-                if item.ref_msg:
-                    ref_parts = []
-                    if item.ref_msg.title:
-                        ref_parts.append(item.ref_msg.title)
-                    if item.ref_msg.message_item:
-                        ref_item = item.ref_msg.message_item
-                        if ref_item.text_item and ref_item.text_item.text:
-                            ref_parts.append(ref_item.text_item.text)
-                    if ref_parts:
-                        components.append(
-                            platform_message.Quote(
-                                sender_id='',
-                                origin=platform_message.MessageChain(
-                                    [platform_message.Plain(text=' | '.join(ref_parts))]
-                                ),
-                            )
-                        )
-
-                components.append(platform_message.Plain(text=text))
-
-            elif item.type == MessageItem.IMAGE and item.image_item:
-                if hasattr(item.image_item, '_downloaded_bytes') and item.image_item._downloaded_bytes:
-                    b64 = base64.b64encode(item.image_item._downloaded_bytes).decode('utf-8')
-                    components.append(platform_message.Image(base64=f'data:image/jpeg;base64,{b64}'))
-                else:
-                    components.append(platform_message.Unknown(text='[Image]'))
-
-            elif item.type == MessageItem.VOICE and item.voice_item:
-                # Voice with speech-to-text: use the transcribed text
-                if item.voice_item.text:
-                    components.append(platform_message.Plain(text=item.voice_item.text))
-                else:
-                    components.append(platform_message.Unknown(text='[Voice]'))
-
-            # TODO: enable after full testing
-            # elif item.type == MessageItem.VOICE and item.voice_item:
-            #     if item.voice_item.text:
-            #         components.append(platform_message.Plain(text=item.voice_item.text))
-            #     elif hasattr(item.voice_item, '_downloaded_bytes') and item.voice_item._downloaded_bytes:
-            #         b64 = base64.b64encode(item.voice_item._downloaded_bytes).decode('utf-8')
-            #         components.append(
-            #             platform_message.Voice(
-            #                 base64=b64,
-            #                 length=item.voice_item.playtime or 0,
-            #             )
-            #         )
-            #     else:
-            #         components.append(
-            #             platform_message.Voice(
-            #                 length=item.voice_item.playtime or 0,
-            #             )
-            #         )
-
-            elif item.type == MessageItem.FILE and item.file_item:
-                components.append(platform_message.Unknown(text=f'[File: {item.file_item.file_name or ""}]'))
-
-            # TODO: enable after full testing
-            # elif item.type == MessageItem.FILE and item.file_item:
-            #     file_name = item.file_item.file_name or ''
-            #     file_size = int(item.file_item.len) if item.file_item.len else 0
-            #     if hasattr(item.file_item, '_downloaded_bytes') and item.file_item._downloaded_bytes:
-            #         b64 = base64.b64encode(item.file_item._downloaded_bytes).decode('utf-8')
-            #         components.append(
-            #             platform_message.File(
-            #                 name=file_name,
-            #                 size=file_size,
-            #                 base64=b64,
-            #             )
-            #         )
-            #     else:
-            #         components.append(
-            #             platform_message.File(
-            #                 name=file_name,
-            #                 size=file_size,
-            #             )
-            #         )
-
-            elif item.type == MessageItem.VIDEO and item.video_item:
-                components.append(platform_message.Unknown(text='[Video]'))
-
-            # TODO: enable after full testing
-            # elif item.type == MessageItem.VIDEO and item.video_item:
-            #     if hasattr(item.video_item, '_downloaded_bytes') and item.video_item._downloaded_bytes:
-            #         b64 = base64.b64encode(item.video_item._downloaded_bytes).decode('utf-8')
-            #         components.append(
-            #             platform_message.File(
-            #                 name='video.mp4',
-            #                 size=item.video_item.video_size or 0,
-            #                 base64=b64,
-            #             )
-            #         )
-            #     else:
-            #         components.append(
-            #             platform_message.File(
-            #                 name='video.mp4',
-            #                 size=item.video_item.video_size or 0,
-            #             )
-            #         )
-
-            else:
-                components.append(platform_message.Unknown(text='[Unknown message type]'))
-
-        return platform_message.MessageChain(components)
-
-
-class OpenClawWeixinEventConverter(abstract_platform_adapter.AbstractEventConverter):
-    """Converts OpenClaw WeChat messages to LangBot events."""
-
-    @staticmethod
-    async def yiri2target(event: platform_events.MessageEvent) -> dict:
-        return event.source_platform_object
-
-    @staticmethod
-    async def target2yiri(msg: WeixinMessage) -> typing.Optional[platform_events.MessageEvent]:
-        """Convert an inbound WeixinMessage to a LangBot event."""
-        if msg.message_type != WeixinMessage.TYPE_USER:
-            return None
-
-        from_user_id = msg.from_user_id or ''
-        if not from_user_id:
-            return None
-
-        message_chain = await OpenClawWeixinMessageConverter.target2yiri(msg)
-        if not message_chain:
-            return None
-
-        timestamp = (msg.create_time_ms or 0) / 1000.0
-
-        return platform_events.FriendMessage(
-            sender=platform_entities.Friend(
-                id=from_user_id,
-                nickname=from_user_id,
-                remark='',
-            ),
-            message_chain=message_chain,
-            time=timestamp,
-            source_platform_object=msg,
-        )
-
-
-class OpenClawWeixinAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
-    """LangBot adapter for OpenClaw WeChat (long-poll based)."""
-
-    name: str = 'openclaw-weixin'
-
-    client: OpenClawWeixinClient = pydantic.Field(exclude=True)
-
-    config: dict
-
-    message_converter: OpenClawWeixinMessageConverter = OpenClawWeixinMessageConverter()
-    event_converter: OpenClawWeixinEventConverter = OpenClawWeixinEventConverter()
-
-    # context_token cache: from_user_id -> context_token
-    _context_tokens: dict[str, str] = pydantic.PrivateAttr(default_factory=dict)
-
-    _polling: bool = pydantic.PrivateAttr(default=False)
-    _poll_task: typing.Optional[asyncio.Task] = pydantic.PrivateAttr(default=None)
-    _bot_uuid: typing.Optional[str] = pydantic.PrivateAttr(default=None)
-
-    listeners: typing.Dict[
-        typing.Type[platform_events.Event],
-        typing.Callable[[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None],
-    ] = {}
-
-    def __init__(self, config: dict, logger: abstract_platform_logger.AbstractEventLogger):
-        client = OpenClawWeixinClient(
-            base_url=config.get('base_url', DEFAULT_BASE_URL),
-            token=config.get('token', ''),
-        )
-        super().__init__(
-            config=config,
-            logger=logger,
-            client=client,
-            bot_account_id='',
-            listeners={},
-            name='openclaw-weixin',
-        )
-
-    def set_bot_uuid(self, bot_uuid: str):
-        """Called by BotManager to provide the bot's UUID for config persistence."""
-        self._bot_uuid = bot_uuid
-
-    async def _persist_config(self) -> None:
-        """Persist current self.config to the database so token survives restart."""
-        if not self._bot_uuid:
-            return
-        try:
-            ap = self.logger.ap
-            await ap.persistence_mgr.execute_async(
-                sqlalchemy.update(persistence_bot.Bot)
-                .where(persistence_bot.Bot.uuid == self._bot_uuid)
-                .values(adapter_config=self.config)
-            )
-        except Exception as e:
-            await self.logger.warning(f'Failed to persist adapter config: {e}')
-
-    async def _do_login(self) -> None:
-        """Run the QR code login flow via client.login() and update config."""
-        adapter_logger = self.logger
-
-        async def _on_qrcode(qr_base64: str, _qr_url: str):
-            await adapter_logger.info(
-                f'Please scan the QR code to login WeChat: {_qr_url}',
-                images=[platform_message.Image(base64=qr_base64)],
-            )
-
-        login_result = await self.client.login(
-            on_qrcode=_on_qrcode,
-        )
-
-        # client.login() already updates client.token and client.base_url
-        self.config['token'] = login_result.token
-        self.config['base_url'] = login_result.base_url
-        if login_result.account_id:
-            self.config['account_id'] = login_result.account_id
-
-        await self.logger.info(f'WeChat login successful! account_id={login_result.account_id}')
-
-        # Persist token to database so it survives restart
-        await self._persist_config()
-
-    async def send_message(
-        self,
-        target_type: str,
-        target_id: str,
-        message: platform_message.MessageChain,
-    ):
-        """Send a message to a user."""
-        context_token = self._context_tokens.get(target_id, '')
-
-        for component in message:
-            try:
-                if isinstance(component, platform_message.Plain):
-                    if component.text:
-                        await self.client.send_text(target_id, component.text, context_token)
-
-                elif isinstance(component, platform_message.Image):
-                    img_bytes, _ = await component.get_bytes()
-                    await self.client.send_image(target_id, img_bytes, context_token)
-
-                elif isinstance(component, platform_message.File):
-                    file_bytes = await self._get_component_bytes(component)
-                    if file_bytes:
-                        await self.client.send_file(target_id, file_bytes, component.name or 'file', context_token)
-
-                elif isinstance(component, platform_message.Voice):
-                    voice_bytes = await self._get_component_bytes(component)
-                    if voice_bytes:
-                        await self.client.send_voice(target_id, voice_bytes, component.length or 0, context_token)
-
-                elif isinstance(component, platform_message.Forward):
-                    for node in component.node_list:
-                        if node.message_chain:
-                            await self.send_message(target_type, target_id, node.message_chain)
-
-            except Exception:
-                await self.logger.error(
-                    f'Failed to send component {type(component).__name__}: {traceback.format_exc()}'
-                )
-
-    async def reply_message(
-        self,
-        message_source: platform_events.MessageEvent,
-        message: platform_message.MessageChain,
-        quote_origin: bool = False,
-    ):
-        """Reply to a received message."""
-        source_msg = message_source.source_platform_object
-        if isinstance(source_msg, WeixinMessage):
-            target_id = source_msg.from_user_id or ''
-            if target_id:
-                await self.send_message('friend', target_id, message)
-
-    async def is_muted(self, group_id: int) -> bool:
-        return False
-
-    @staticmethod
-    async def _get_component_bytes(component: platform_message.MessageComponent) -> typing.Optional[bytes]:
-        """Extract raw bytes from a File or Voice component."""
-        b64_val = getattr(component, 'base64', None)
-        url_val = getattr(component, 'url', None)
-        path_val = getattr(component, 'path', None)
-
-        if b64_val:
-            return base64.b64decode(b64_val)
-        elif url_val and url_val.startswith(('http://', 'https://')):
-            import aiohttp
-
-            async with aiohttp.ClientSession() as session:
-                async with session.get(url_val) as resp:
-                    if resp.status == 200:
-                        return await resp.read()
-        elif path_val:
-            import asyncio
-
-            with open(path_val, 'rb') as f:
-                return await asyncio.to_thread(f.read)
-        return None
-
-    def register_listener(
-        self,
-        event_type: typing.Type[platform_events.Event],
-        callback: typing.Callable[
-            [platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter],
-            None,
-        ],
-    ):
-        self.listeners[event_type] = callback
-
-    def unregister_listener(
-        self,
-        event_type: typing.Type[platform_events.Event],
-        callback: typing.Callable[
-            [platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter],
-            None,
-        ],
-    ):
-        self.listeners.pop(event_type, None)
-
-    async def run_async(self):
-        """Start the adapter. If no token is configured, trigger QR code login first."""
-        base_url = self.config.get('base_url', DEFAULT_BASE_URL)
-        token = self.config.get('token', '')
-
-        await self.logger.info('OpenClaw WeChat adapter starting...')
-
-        # QR code login flow when no token is provided
-        if not token:
-            await self.logger.info('No token configured, starting QR code login...')
-            try:
-                await self._do_login()
-            except Exception as e:
-                await self.logger.error(f'QR code login failed: {e}')
-                raise
-
-        # Rebuild client with the (possibly updated) config
-        self.client = OpenClawWeixinClient(
-            base_url=self.config.get('base_url', base_url),
-            token=self.config.get('token', token),
-        )
-        self.bot_account_id = self.config.get('account_id', 'openclaw-weixin')
-        self._polling = True
-
-        # Start the long-poll loop
-        self._poll_task = asyncio.create_task(self._poll_loop())
-        await self.logger.info('OpenClaw WeChat adapter running')
-
-        try:
-            await self._poll_task
-        except asyncio.CancelledError:
-            pass
-
-    async def _poll_loop(self):
-        """Long-poll loop: call getUpdates continuously.
-
-        Error handling follows the weixin-bot SDK pattern:
-        - Exponential backoff (1s -> 10s max) on failures
-        - Session expired (errcode -14) triggers automatic re-login
-        """
-        get_updates_buf = ''
-        poll_timeout = float(self.config.get('poll_timeout', 35))
-
-        backoff_delay = 1.0
-        max_backoff = 10.0
-
-        while self._polling:
-            try:
-                resp = await self.client.get_updates(
-                    get_updates_buf=get_updates_buf,
-                    timeout=poll_timeout + 5,
-                )
-
-                if resp.longpolling_timeout_ms and resp.longpolling_timeout_ms > 0:
-                    poll_timeout = resp.longpolling_timeout_ms / 1000.0
-
-                is_api_error = (resp.ret is not None and resp.ret != 0) or (
-                    resp.errcode is not None and resp.errcode != 0
-                )
-                if is_api_error:
-                    is_session_expired = resp.errcode == SESSION_EXPIRED_ERRCODE or resp.ret == SESSION_EXPIRED_ERRCODE
-
-                    if is_session_expired:
-                        await self.logger.error('OpenClaw WeChat session expired, attempting re-login...')
-                        try:
-                            await self._do_login()
-                            # Rebuild client with new credentials
-                            self.client = OpenClawWeixinClient(
-                                base_url=self.config.get('base_url', DEFAULT_BASE_URL),
-                                token=self.config.get('token', ''),
-                            )
-                            self._context_tokens.clear()
-                            get_updates_buf = ''
-                            backoff_delay = 1.0
-                            continue
-                        except Exception:
-                            await self.logger.error(f'Re-login failed: {traceback.format_exc()}')
-                            break
-
-                    await self.logger.error(
-                        f'OpenClaw getUpdates failed: ret={resp.ret} errcode={resp.errcode} errmsg={resp.errmsg}'
-                    )
-                    await asyncio.sleep(backoff_delay)
-                    backoff_delay = min(backoff_delay * 2, max_backoff)
-                    continue
-
-                backoff_delay = 1.0
-
-                if resp.get_updates_buf:
-                    get_updates_buf = resp.get_updates_buf
-
-                for msg in resp.msgs:
-                    try:
-                        await self._handle_inbound_message(msg)
-                    except Exception:
-                        await self.logger.error(f'Error handling message: {traceback.format_exc()}')
-
-            except asyncio.CancelledError:
-                break
-            except Exception:
-                await self.logger.error(f'OpenClaw poll error: {traceback.format_exc()}')
-                await asyncio.sleep(backoff_delay)
-                backoff_delay = min(backoff_delay * 2, max_backoff)
-
-    async def _handle_inbound_message(self, msg: WeixinMessage):
-        """Process a single inbound message from getUpdates."""
-        if msg.context_token and msg.from_user_id:
-            self._context_tokens[msg.from_user_id] = msg.context_token
-
-        # Download CDN media (files, images) before converting to LangBot events
-        await self._download_media_items(msg)
-
-        event = await OpenClawWeixinEventConverter.target2yiri(msg)
-        if event is None:
-            return
-
-        if type(event) in self.listeners:
-            await self.listeners[type(event)](event, self)
-
-    async def _download_media_items(self, msg: WeixinMessage):
-        """Download CDN media for image items in the message."""
-        if not msg.item_list:
-            return
-
-        for item in msg.item_list:
-            try:
-                if item.type == MessageItem.IMAGE and item.image_item:
-                    if (
-                        item.image_item.media
-                        and item.image_item.media.encrypt_query_param
-                        and item.image_item.media.aes_key
-                    ):
-                        img_bytes = await self.client.download_media(item.image_item.media)
-                        item.image_item._downloaded_bytes = img_bytes
-
-                # TODO: enable after full testing
-                # elif item.type == MessageItem.FILE and item.file_item and item.file_item.media:
-                #     if item.file_item.media.encrypt_query_param and item.file_item.media.aes_key:
-                #         file_bytes = await self.client.download_media(item.file_item.media)
-                #         item.file_item._downloaded_bytes = file_bytes
-                #
-                # elif item.type == MessageItem.VOICE and item.voice_item and item.voice_item.media:
-                #     if item.voice_item.media.encrypt_query_param and item.voice_item.media.aes_key:
-                #         voice_bytes = await self.client.download_media(item.voice_item.media)
-                #         item.voice_item._downloaded_bytes = voice_bytes
-                #
-                # elif item.type == MessageItem.VIDEO and item.video_item and item.video_item.media:
-                #     if item.video_item.media.encrypt_query_param and item.video_item.media.aes_key:
-                #         video_bytes = await self.client.download_media(item.video_item.media)
-                #         item.video_item._downloaded_bytes = video_bytes
-
-            except Exception:
-                await self.logger.warning(f'Failed to download CDN media: {traceback.format_exc()}')
-
-    async def kill(self) -> bool:
-        """Stop the adapter."""
-        self._polling = False
-        if self._poll_task and not self._poll_task.done():
-            self._poll_task.cancel()
-            try:
-                await self._poll_task
-            except asyncio.CancelledError:
-                pass
-        await self.client.close()
-        await self.logger.info('OpenClaw WeChat adapter stopped')
-        return True

src/langbot/pkg/platform/sources/openclaw_weixin.yaml

@@ -1,57 +0,0 @@
-apiVersion: v1
-kind: MessagePlatformAdapter
-metadata:
-  name: openclaw-weixin
-  label:
-    en_US: OpenClaw WeChat
-    zh_Hans: OpenClaw 微信
-  description:
-    en_US: OpenClaw WeChat adapter, supports personal WeChat via QR code login
-    zh_Hans: OpenClaw 微信适配器，通过扫码登录支持个人微信
-  icon: wechat.png
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: API Base URL
-        zh_Hans: API 基础地址
-      description:
-        en_US: The base URL of the OpenClaw WeChat backend API
-        zh_Hans: OpenClaw 微信后端 API 的基础地址
-      type: string
-      required: true
-      default: "https://ilinkai.weixin.qq.com"
-    - name: token
-      label:
-        en_US: Token
-        zh_Hans: 令牌
-      description:
-        en_US: Bearer token obtained after QR code login authorization. Leave empty to trigger QR code login on startup.
-        zh_Hans: 扫码登录授权后获取的 Bearer 令牌。留空则启动时自动触发扫码登录。
-      type: string
-      required: false
-      default: ""
-    - name: account_id
-      label:
-        en_US: Account ID
-        zh_Hans: 账号标识
-      description:
-        en_US: A label for this WeChat account (used for display purposes)
-        zh_Hans: 此微信账号的标识（用于显示）
-      type: string
-      required: false
-      default: "openclaw-weixin"
-    - name: poll_timeout
-      label:
-        en_US: Poll Timeout (seconds)
-        zh_Hans: 轮询超时（秒）
-      description:
-        en_US: Long-poll timeout for getUpdates, the server may hold the request up to this duration
-        zh_Hans: getUpdates 长轮询超时时间，服务端最多持有请求的时长
-      type: integer
-      required: false
-      default: 35
-execution:
-  python:
-    path: ./openclaw_weixin.py
-    attr: OpenClawWeixinAdapter

src/langbot/pkg/platform/sources/telegram.py

@@ -1,5 +1,4 @@
 from __future__ import annotations
-import time
 
 
 import telegram
@@ -10,9 +9,9 @@ import telegramify_markdown
 import typing
 import traceback
 import base64
+import aiohttp
 import pydantic
 
-from langbot.pkg.utils import httpclient
 import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
 import langbot_plugin.api.entities.builtin.platform.message as platform_message
 import langbot_plugin.api.entities.builtin.platform.events as platform_events
@@ -34,33 +33,14 @@ class TelegramMessageConverter(abstract_platform_adapter.AbstractMessageConverte
                 if component.base64:
                     photo_bytes = base64.b64decode(component.base64)
                 elif component.url:
-                    session = httpclient.get_session()
-                    async with session.get(component.url) as response:
-                        photo_bytes = await response.read()
+                    async with aiohttp.ClientSession() as session:
+                        async with session.get(component.url) as response:
+                            photo_bytes = await response.read()
                 elif component.path:
                     with open(component.path, 'rb') as f:
                         photo_bytes = f.read()
 
                 components.append({'type': 'photo', 'photo': photo_bytes})
-            elif isinstance(component, platform_message.File):
-                file_bytes = None
-
-                if component.base64:
-                    # Strip data URI prefix if present (e.g. "data:application/pdf;base64,...")
-                    b64_data = component.base64
-                    if ';base64,' in b64_data:
-                        b64_data = b64_data.split(';base64,', 1)[1]
-                    file_bytes = base64.b64decode(b64_data)
-                elif component.url:
-                    session = httpclient.get_session()
-                    async with session.get(component.url) as response:
-                        file_bytes = await response.read()
-                elif component.path:
-                    with open(component.path, 'rb') as f:
-                        file_bytes = f.read()
-
-                file_name = getattr(component, 'name', None) or 'file'
-                components.append({'type': 'document', 'document': file_bytes, 'filename': file_name})
             elif isinstance(component, platform_message.Forward):
                 for node in component.node_list:
                     components.extend(await TelegramMessageConverter.yiri2target(node.message_chain, bot))
@@ -94,9 +74,10 @@ class TelegramMessageConverter(abstract_platform_adapter.AbstractMessageConverte
             file_bytes = None
             file_format = ''
 
-            async with httpclient.get_session(trust_env=True).get(file.file_path) as response:
-                file_bytes = await response.read()
-                file_format = 'image/jpeg'
+            async with aiohttp.ClientSession(trust_env=True) as session:
+                async with session.get(file.file_path) as response:
+                    file_bytes = await response.read()
+                    file_format = 'image/jpeg'
 
             message_components.append(
                 platform_message.Image(
@@ -113,8 +94,9 @@ class TelegramMessageConverter(abstract_platform_adapter.AbstractMessageConverte
             file_bytes = None
             file_format = message.voice.mime_type or 'audio/ogg'
 
-            async with httpclient.get_session(trust_env=True).get(file.file_path) as response:
-                file_bytes = await response.read()
+            async with aiohttp.ClientSession(trust_env=True) as session:
+                async with session.get(file.file_path) as response:
+                    file_bytes = await response.read()
 
             message_components.append(
                 platform_message.Voice(
@@ -123,27 +105,6 @@ class TelegramMessageConverter(abstract_platform_adapter.AbstractMessageConverte
                 )
             )
 
-        if message.document:
-            if message.caption:
-                message_components.extend(parse_message_text(message.caption))
-
-            file = await message.document.get_file()
-            file_name = message.document.file_name or 'document'
-            file_size = message.document.file_size or 0
-            file_format = message.document.mime_type or 'application/octet-stream'
-
-            file_bytes = None
-            async with httpclient.get_session(trust_env=True).get(file.file_path) as response:
-                file_bytes = await response.read()
-
-            message_components.append(
-                platform_message.File(
-                    name=file_name,
-                    size=file_size,
-                    base64=f'data:{file_format};base64,{base64.b64encode(file_bytes).decode("utf-8")}',
-                )
-            )
-
         return platform_message.MessageChain(message_components)
 
 
@@ -219,10 +180,7 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         application = ApplicationBuilder().token(config['token']).build()
         bot = application.bot
         application.add_handler(
-            MessageHandler(
-                filters.TEXT | (filters.COMMAND) | filters.PHOTO | filters.VOICE | filters.Document.ALL,
-                telegram_callback,
-            )
+            MessageHandler(filters.TEXT | (filters.COMMAND) | filters.PHOTO | filters.VOICE, telegram_callback)
         )
         super().__init__(
             config=config,
@@ -236,38 +194,7 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         )
 
     async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain):
-        components = await TelegramMessageConverter.yiri2target(message, self.bot)
-
-        chat_id_str, _, thread_id_str = str(target_id).partition('#')
-        chat_id: int | str = int(chat_id_str) if chat_id_str.lstrip('-').isdigit() else chat_id_str
-        message_thread_id = int(thread_id_str) if thread_id_str and thread_id_str.isdigit() else None
-
-        for component in components:
-            component_type = component.get('type')
-            args = {'chat_id': chat_id}
-            if message_thread_id is not None:
-                args['message_thread_id'] = message_thread_id
-
-            if component_type == 'text':
-                text = component.get('text', '')
-                if self.config['markdown_card'] is True:
-                    text = telegramify_markdown.markdownify(content=text)
-                    args['parse_mode'] = 'MarkdownV2'
-                args['text'] = text
-                await self.bot.send_message(**args)
-            elif component_type == 'photo':
-                photo = component.get('photo')
-                if photo is None:
-                    continue
-                args['photo'] = telegram.InputFile(photo)
-                await self.bot.send_photo(**args)
-            elif component_type == 'document':
-                doc = component.get('document')
-                if doc is None:
-                    continue
-                filename = component.get('filename', 'file')
-                args['document'] = telegram.InputFile(doc, filename=filename)
-                await self.bot.send_document(**args)
+        pass
 
     async def reply_message(
         self,
@@ -301,39 +228,6 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
 
         await self.bot.send_message(**args)
 
-    def _process_markdown(self, text: str) -> str:
-        if self.config.get('markdown_card', False):
-            return telegramify_markdown.markdownify(content=text)
-        return text
-
-    def _build_message_args(self, chat_id: int, text: str, message_thread_id: int = None, **extra_args) -> dict:
-        args = {'chat_id': chat_id, 'text': self._process_markdown(text), **extra_args}
-        if message_thread_id:
-            args['message_thread_id'] = message_thread_id
-        if self.config.get('markdown_card', False):
-            args['parse_mode'] = 'MarkdownV2'
-        return args
-
-    async def create_message_card(self, message_id, event):
-        assert isinstance(event.source_platform_object, Update)
-        update = event.source_platform_object
-        chat_id = update.effective_chat.id
-        chat_type = update.effective_chat.type
-        message_thread_id = update.message.message_thread_id
-
-        if chat_type == 'private':
-            draft_id = int(time.time() * 1000)
-            self.msg_stream_id[message_id] = ('private', draft_id)
-
-            args = self._build_message_args(chat_id, 'Thinking...', message_thread_id, draft_id=draft_id)
-            await self.bot.send_message_draft(**args)
-        else:
-            args = self._build_message_args(chat_id, 'Thinking...', message_thread_id)
-            send_msg = await self.bot.send_message(**args)
-            self.msg_stream_id[message_id] = ('group', send_msg.message_id)
-
-        return True
-
     async def reply_message_chunk(
         self,
         message_source: platform_events.MessageEvent,
@@ -342,47 +236,59 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         quote_origin: bool = False,
         is_final: bool = False,
     ):
-        message_id = bot_message.resp_message_id
         msg_seq = bot_message.msg_sequence
-        assert isinstance(message_source.source_platform_object, Update)
-        update = message_source.source_platform_object
-        chat_id = update.effective_chat.id
-        message_thread_id = update.message.message_thread_id
+        if (msg_seq - 1) % 8 == 0 or is_final:
+            assert isinstance(message_source.source_platform_object, Update)
+            components = await TelegramMessageConverter.yiri2target(message, self.bot)
+            args = {}
+            message_id = message_source.source_platform_object.message.id
 
-        if message_id not in self.msg_stream_id:
-            return
+            component = components[0]
+            if message_id not in self.msg_stream_id:  # 当消息回复第一次时，发送新消息
+                # time.sleep(0.6)
+                if component['type'] == 'text':
+                    if self.config['markdown_card'] is True:
+                        content = telegramify_markdown.markdownify(
+                            content=component['text'],
+                        )
+                    else:
+                        content = component['text']
+                    args = {
+                        'chat_id': message_source.source_platform_object.effective_chat.id,
+                        'text': content,
+                    }
+                    if message_source.source_platform_object.message.message_thread_id:
+                        args['message_thread_id'] = message_source.source_platform_object.message.message_thread_id
 
-        chat_mode, draft_id = self.msg_stream_id[message_id]
-        components = await TelegramMessageConverter.yiri2target(message, self.bot)
+                    if quote_origin:
+                        args['reply_to_message_id'] = message_source.source_platform_object.message.id
 
-        if not components or components[0]['type'] != 'text':
-            if is_final and bot_message.tool_calls is None:
-                self.msg_stream_id.pop(message_id)
-            return
+                    if self.config['markdown_card'] is True:
+                        args['parse_mode'] = 'MarkdownV2'
 
-        content = components[0]['text']
+                send_msg = await self.bot.send_message(**args)
+                send_msg_id = send_msg.message_id
+                self.msg_stream_id[message_id] = send_msg_id
+            else:  # 存在消息的时候直接编辑消息1
+                if component['type'] == 'text':
+                    if self.config['markdown_card'] is True:
+                        content = telegramify_markdown.markdownify(
+                            content=component['text'],
+                        )
+                    else:
+                        content = component['text']
+                    args = {
+                        'message_id': self.msg_stream_id[message_id],
+                        'chat_id': message_source.source_platform_object.effective_chat.id,
+                        'text': content,
+                    }
+                    if self.config['markdown_card'] is True:
+                        args['parse_mode'] = 'MarkdownV2'
 
-        if chat_mode == 'private':
-            args = self._build_message_args(chat_id, content, message_thread_id, draft_id=draft_id)
-            await self.bot.send_message_draft(**args)
-            if is_final and bot_message.tool_calls is None:
-                del args['draft_id']
-                await self.bot.send_message(**args)
-                self.msg_stream_id.pop(message_id)
-        else:
-            stream_id = draft_id
-            if (msg_seq - 1) % 8 == 0 or is_final:
-                args = {
-                    'message_id': stream_id,
-                    'chat_id': chat_id,
-                    'text': self._process_markdown(content),
-                }
-                if self.config.get('markdown_card', False):
-                    args['parse_mode'] = 'MarkdownV2'
                 await self.bot.edit_message_text(**args)
-
             if is_final and bot_message.tool_calls is None:
-                self.msg_stream_id.pop(message_id)
+                # self.seq = 1  # 消息回复结束之后重置seq
+                self.msg_stream_id.pop(message_id)  # 消息回复结束之后删除流式消息id
 
     def get_launcher_id(self, event: platform_events.MessageEvent) -> str | None:
         if not isinstance(event.source_platform_object, Update):

src/langbot/pkg/platform/sources/websocket_adapter.py

@@ -37,24 +37,16 @@ class WebSocketSession:
     id: str
     message_lists: dict[str, list[WebSocketMessage]] = {}
     """消息列表 {pipeline_uuid: [messages]}"""
-    stream_message_indexes: dict[str, dict[str, int]] = {}
-    """流式消息索引 {pipeline_uuid: {resp_message_id: message_index}}"""
 
     def __init__(self, id: str):
         self.id = id
         self.message_lists = {}
-        self.stream_message_indexes = {}
 
     def get_message_list(self, pipeline_uuid: str) -> list[WebSocketMessage]:
         if pipeline_uuid not in self.message_lists:
             self.message_lists[pipeline_uuid] = []
         return self.message_lists[pipeline_uuid]
 
-    def get_stream_message_indexes(self, pipeline_uuid: str) -> dict[str, int]:
-        if pipeline_uuid not in self.stream_message_indexes:
-            self.stream_message_indexes[pipeline_uuid] = {}
-        return self.stream_message_indexes[pipeline_uuid]
-
 
 class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
     """WebSocket适配器 - 支持双向实时通信"""
@@ -97,46 +89,20 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
         target_id: str,
         message: platform_message.MessageChain,
     ) -> dict:
-        """发送消息 - 这里用于主动推送消息到前端
+        """发送消息 - 这里用于主动推送消息到前端"""
+        message_data = {
+            'type': 'bot_message',
+            'target_type': target_type,
+            'target_id': target_id,
+            'content': str(message),
+            'message_chain': [component.__dict__ for component in message],
+            'timestamp': datetime.now().isoformat(),
+        }
 
-        对于 WebSocket 适配器，我们需要将消息广播到正确的 pipeline 连接。
-        target_id 可能是 launcher_id（如 websocket_xxx）或 pipeline_uuid。
-        我们需要尝试两种方式来确保消息能够送达。
-        """
-        # 获取当前的 pipeline_uuid
-        pipeline_uuid = self.ap.platform_mgr.websocket_proxy_bot.bot_entity.use_pipeline_uuid
-        session_type = 'group' if target_type == 'group' else 'person'
+        # 推送到所有相关连接
+        await self.outbound_message_queue.put(message_data)
 
-        # 选择会话
-        session = self.websocket_group_session if session_type == 'group' else self.websocket_person_session
-
-        # 生成唯一消息ID
-        msg_id = len(session.get_message_list(pipeline_uuid)) + 1
-
-        message_data = WebSocketMessage(
-            id=msg_id,
-            role='assistant',
-            content=str(message),
-            message_chain=[component.__dict__ for component in message],
-            timestamp=datetime.now().isoformat(),
-            is_final=True,
-        )
-
-        # 保存到历史记录
-        session.get_message_list(pipeline_uuid).append(message_data)
-
-        # 直接广播到当前pipeline的连接
-        await ws_connection_manager.broadcast_to_pipeline(
-            pipeline_uuid,
-            {
-                'type': 'response',
-                'session_type': session_type,
-                'data': message_data.model_dump(),
-            },
-            session_type=session_type,
-        )
-
-        return message_data.model_dump()
+        return message_data
 
     async def reply_message(
         self,
@@ -203,16 +169,10 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
         pipeline_uuid = self.ap.platform_mgr.websocket_proxy_bot.bot_entity.use_pipeline_uuid
         session_type = 'group' if isinstance(message_source, platform_events.GroupMessage) else 'person'
         message_list = session.get_message_list(pipeline_uuid)
-        stream_message_indexes = session.get_stream_message_indexes(pipeline_uuid)
 
-        # Streaming messages in LangBot have a stable resp_message_id during the same assistant reply.
-        # Use it as the primary key to avoid overwriting an old card from a previous reply.
-        resp_message_id = str(getattr(bot_message, 'resp_message_id', '') or '')
-        existing_index = stream_message_indexes.get(resp_message_id) if resp_message_id else None
-
-        message_is_final = is_final and bot_message.tool_calls is None
-
-        if existing_index is None or existing_index >= len(message_list):
+        # 检查是否是新的流式消息（通过bot_message对象判断）
+        # 如果列表为空，或者最后一条消息已经is_final=True，则创建新消息
+        if not message_list or message_list[-1].is_final:
             # 创建新消息
             msg_id = len(message_list) + 1
             message_data = WebSocketMessage(
@@ -221,31 +181,27 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
                 content=str(message),
                 message_chain=[component.__dict__ for component in message],
                 timestamp=datetime.now().isoformat(),
-                is_final=message_is_final,
+                is_final=is_final and bot_message.tool_calls is None,
             )
 
-            # 立即添加到历史记录（即使is_final=False），以便后续块可以更新它
-            message_list.append(message_data)
-            if resp_message_id:
-                stream_message_indexes[resp_message_id] = len(message_list) - 1
+            # 只有在is_final时才保存到历史记录
+            if is_final and bot_message.tool_calls is None:
+                message_list.append(message_data)
         else:
-            # 更新同一条流式消息
-            old_message = message_list[existing_index]
-            msg_id = old_message.id
+            # 更新最后一条消息
+            msg_id = message_list[-1].id
             message_data = WebSocketMessage(
                 id=msg_id,
                 role='assistant',
                 content=str(message),
                 message_chain=[component.__dict__ for component in message],
-                timestamp=old_message.timestamp,  # 保持原始时间戳
-                is_final=message_is_final,
+                timestamp=message_list[-1].timestamp,  # 保持原始时间戳
+                is_final=is_final and bot_message.tool_calls is None,
             )
 
-            # 更新历史记录中的对应消息
-            message_list[existing_index] = message_data
-
-        if message_is_final and resp_message_id:
-            stream_message_indexes.pop(resp_message_id, None)
+            # 如果是final，更新历史记录中的最后一条
+            if is_final and bot_message.tool_calls is None:
+                message_list[-1] = message_data
 
         # 直接广播到所有该pipeline的连接，包含session_type信息
         await ws_connection_manager.broadcast_to_pipeline(
@@ -454,10 +410,6 @@ class WebSocketAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
         if session_type == 'person':
             if pipeline_uuid in self.websocket_person_session.message_lists:
                 self.websocket_person_session.message_lists[pipeline_uuid] = []
-            if pipeline_uuid in self.websocket_person_session.stream_message_indexes:
-                self.websocket_person_session.stream_message_indexes[pipeline_uuid] = {}
         else:
             if pipeline_uuid in self.websocket_group_session.message_lists:
                 self.websocket_group_session.message_lists[pipeline_uuid] = []
-            if pipeline_uuid in self.websocket_group_session.stream_message_indexes:
-                self.websocket_group_session.stream_message_indexes[pipeline_uuid] = {}

src/langbot/pkg/platform/sources/wecom.py

@@ -148,54 +148,51 @@ class WecomEventConverter(abstract_platform_adapter.AbstractEventConverter):
             pass
 
         if type(event) is platform_events.FriendMessage:
-            return event.source_platform_object
+            payload = {
+                'MsgType': 'text',
+                'Content': '',
+                'FromUserName': event.sender.id,
+                'ToUserName': bot_account_id,
+                'CreateTime': int(datetime.datetime.now().timestamp()),
+                'AgentID': event.sender.nickname,
+            }
+            wecom_event = WecomEvent.from_payload(payload=payload)
+            if not wecom_event:
+                raise ValueError('无法从 message_data 构造 WecomEvent 对象')
+
+            return wecom_event
 
     @staticmethod
-    async def target2yiri(event: WecomEvent, bot: WecomClient = None):
+    async def target2yiri(event: WecomEvent):
         """
         将 WecomEvent 转换为平台的 FriendMessage 对象。
 
         Args:
             event (WecomEvent): 企业微信事件。
-            bot (WecomClient): 企业微信客户端，用于获取用户信息。
 
         Returns:
             platform_events.FriendMessage: 转换后的 FriendMessage 对象。
         """
-        # Try to get the user's real name from the WeCom API
-        nickname = str(event.user_id)
-        if bot and event.user_id:
-            try:
-                user_info = await bot.get_user_info(event.user_id)
-                if user_info and user_info.get('name'):
-                    nickname = user_info.get('name')
-            except Exception:
-                pass  # Fall back to user_id as nickname
-
         # 转换消息链
         if event.type == 'text':
             yiri_chain = await WecomMessageConverter.target2yiri(event.message, event.message_id)
             friend = platform_entities.Friend(
                 id=f'u{event.user_id}',
-                nickname=nickname,
+                nickname=str(event.agent_id),
                 remark='',
             )
 
-            return platform_events.FriendMessage(
-                sender=friend, message_chain=yiri_chain, time=event.timestamp, source_platform_object=event
-            )
+            return platform_events.FriendMessage(sender=friend, message_chain=yiri_chain, time=event.timestamp)
         elif event.type == 'image':
             friend = platform_entities.Friend(
                 id=f'u{event.user_id}',
-                nickname=nickname,
+                nickname=str(event.agent_id),
                 remark='',
             )
 
             yiri_chain = await WecomMessageConverter.target2yiri_image(picurl=event.picurl, message_id=event.message_id)
 
-            return platform_events.FriendMessage(
-                sender=friend, message_chain=yiri_chain, time=event.timestamp, source_platform_object=event
-            )
+            return platform_events.FriendMessage(sender=friend, message_chain=yiri_chain, time=event.timestamp)
 
 
 class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
@@ -213,6 +210,7 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             'secret',
             'token',
             'EncodingAESKey',
+            'contacts_secret',
         ]
 
         missing_keys = [key for key in required_keys if key not in config]
@@ -225,7 +223,7 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             secret=config['secret'],
             token=config['token'],
             EncodingAESKey=config['EncodingAESKey'],
-            contacts_secret=config.get('contacts_secret', ''),  # Optional, kept for backward compatibility
+            contacts_secret=config['contacts_secret'],
             logger=logger,
             unified_mode=True,
             api_base_url=config.get('api_base_url', 'https://qyapi.weixin.qq.com/cgi-bin'),
@@ -250,17 +248,18 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
     ):
         Wecom_event = await WecomEventConverter.yiri2target(message_source, self.bot_account_id, self.bot)
         content_list = await WecomMessageConverter.yiri2target(message, self.bot)
-        # user_id is the original FromUserName from WecomEvent
-        user_id = Wecom_event.user_id
+        fixed_user_id = Wecom_event.user_id
+        # 删掉开头的u
+        fixed_user_id = fixed_user_id[1:]
         for content in content_list:
             if content['type'] == 'text':
-                await self.bot.send_private_msg(user_id, Wecom_event.agent_id, content['content'])
+                await self.bot.send_private_msg(fixed_user_id, Wecom_event.agent_id, content['content'])
             elif content['type'] == 'image':
-                await self.bot.send_image(user_id, Wecom_event.agent_id, content['media_id'])
+                await self.bot.send_image(fixed_user_id, Wecom_event.agent_id, content['media_id'])
             elif content['type'] == 'voice':
-                await self.bot.send_voice(user_id, Wecom_event.agent_id, content['media_id'])
+                await self.bot.send_voice(fixed_user_id, Wecom_event.agent_id, content['media_id'])
             elif content['type'] == 'file':
-                await self.bot.send_file(user_id, Wecom_event.agent_id, content['media_id'])
+                await self.bot.send_file(fixed_user_id, Wecom_event.agent_id, content['media_id'])
 
     async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain):
         content_list = await WecomMessageConverter.yiri2target(message, self.bot)
@@ -288,7 +287,7 @@ class WecomAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         async def on_message(event: WecomEvent):
             self.bot_account_id = event.receiver_id
             try:
-                return await callback(await self.event_converter.target2yiri(event, self.bot), self)
+                return await callback(await self.event_converter.target2yiri(event), self)
             except Exception:
                 await self.logger.error(f'Error in wecom callback: {traceback.format_exc()}')
 

src/langbot/pkg/platform/sources/wecom.yaml

@@ -39,6 +39,13 @@ spec:
       type: string
       required: true
       default: ""
+    - name: contacts_secret
+      label:
+        en_US: Contacts Secret
+        zh_Hans: 通讯录密钥
+      type: string
+      required: true
+      default: ""
     - name: api_base_url
       label:
         en_US: API Base URL

src/langbot/pkg/platform/sources/wecombot.py

@@ -11,7 +11,6 @@ import langbot_plugin.api.entities.builtin.platform.entities as platform_entitie
 from ..logger import EventLogger
 from langbot.libs.wecom_ai_bot_api.wecombotevent import WecomBotEvent
 from langbot.libs.wecom_ai_bot_api.api import WecomBotClient
-from langbot.libs.wecom_ai_bot_api.ws_client import WecomBotWsClient
 
 
 class WecomBotMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
@@ -24,18 +23,14 @@ class WecomBotMessageConverter(abstract_platform_adapter.AbstractMessageConverte
         return content
 
     @staticmethod
-    async def target2yiri(event: WecomBotEvent, bot_name: str = ''):
+    async def target2yiri(event: WecomBotEvent):
         yiri_msg_list = []
         if event.type == 'group':
             yiri_msg_list.append(platform_message.At(target=event.ai_bot_id))
-
         yiri_msg_list.append(platform_message.Source(id=event.message_id, time=datetime.datetime.now()))
 
         if event.content:
-            content = event.content
-            if bot_name:
-                content = content.replace(f'@{bot_name}', '').strip()
-            yiri_msg_list.append(platform_message.Plain(text=content))
+            yiri_msg_list.append(platform_message.Plain(text=event.content))
 
         images = []
         if event.images:
@@ -138,15 +133,13 @@ class WecomBotMessageConverter(abstract_platform_adapter.AbstractMessageConverte
 
 
 class WecomBotEventConverter(abstract_platform_adapter.AbstractEventConverter):
-    def __init__(self, bot_name: str = ''):
-        self.bot_name = bot_name
-
     @staticmethod
     async def yiri2target(event: platform_events.MessageEvent):
         return event.source_platform_object
 
-    async def target2yiri(self, event: WecomBotEvent):
-        message_chain = await WecomBotMessageConverter.target2yiri(event, bot_name=self.bot_name)
+    @staticmethod
+    async def target2yiri(event: WecomBotEvent):
+        message_chain = await WecomBotMessageConverter.target2yiri(event)
         if event.type == 'single':
             return platform_events.FriendMessage(
                 sender=platform_entities.Friend(
@@ -183,53 +176,34 @@ class WecomBotEventConverter(abstract_platform_adapter.AbstractEventConverter):
 
 
 class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
-    bot: typing.Union[WecomBotClient, WecomBotWsClient]
+    bot: WecomBotClient
     bot_account_id: str
     message_converter: WecomBotMessageConverter = WecomBotMessageConverter()
-    event_converter: WecomBotEventConverter
+    event_converter: WecomBotEventConverter = WecomBotEventConverter()
     config: dict
     bot_uuid: str = None
-    _ws_mode: bool = False
-    bot_name: str = ''
-    listeners: dict = {}
 
     def __init__(self, config: dict, logger: EventLogger):
-        enable_webhook = config.get('enable-webhook', False)
-        bot_name = config.get('robot_name', '')
+        required_keys = ['Token', 'EncodingAESKey', 'Corpid', 'BotId']
+        missing_keys = [key for key in required_keys if key not in config]
+        if missing_keys:
+            raise Exception(f'WecomBot 缺少配置项: {missing_keys}')
 
-        if not enable_webhook:
-            bot = WecomBotWsClient(
-                bot_id=config['BotId'],
-                secret=config['Secret'],
-                logger=logger,
-                encoding_aes_key=config.get('EncodingAESKey', ''),
-            )
-        else:
-            # Webhook callback mode
-            required_keys = ['Token', 'EncodingAESKey', 'Corpid']
-            missing_keys = [key for key in required_keys if key not in config or not config[key]]
-            if missing_keys:
-                raise Exception(f'WecomBot webhook mode missing config: {missing_keys}')
+        bot = WecomBotClient(
+            Token=config['Token'],
+            EnCodingAESKey=config['EncodingAESKey'],
+            Corpid=config['Corpid'],
+            logger=logger,
+            unified_mode=True,
+        )
+        bot_account_id = config['BotId']
 
-            bot = WecomBotClient(
-                Token=config['Token'],
-                EnCodingAESKey=config['EncodingAESKey'],
-                Corpid=config['Corpid'],
-                logger=logger,
-                unified_mode=True,
-            )
-
-        bot_account_id = config.get('BotId', '')
-        event_converter = WecomBotEventConverter(bot_name=bot_name)
         super().__init__(
             config=config,
             logger=logger,
             bot=bot,
             bot_account_id=bot_account_id,
-            bot_name=bot_name,
-            event_converter=event_converter,
         )
-        self.listeners = {}
 
     async def reply_message(
         self,
@@ -238,17 +212,7 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         quote_origin: bool = False,
     ):
         content = await self.message_converter.yiri2target(message)
-        _ws_mode = not self.config.get('enable-webhook', False)
-
-        if _ws_mode:
-            event = message_source.source_platform_object
-            req_id = event.get('req_id', '')
-            if req_id:
-                await self.bot.reply_text(req_id, content)
-            else:
-                await self.bot.set_message(event.message_id, content)
-        else:
-            await self.bot.set_message(message_source.source_platform_object.message_id, content)
+        await self.bot.set_message(message_source.source_platform_object.message_id, content)
 
     async def reply_message_chunk(
         self,
@@ -258,44 +222,44 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         quote_origin: bool = False,
         is_final: bool = False,
     ):
+        """将流水线增量输出写入企业微信 stream 会话。
+
+        Args:
+            message_source: 流水线提供的原始消息事件。
+            bot_message: 当前片段对应的模型元信息（未使用）。
+            message: 需要回复的消息链。
+            quote_origin: 是否引用原消息（企业微信暂不支持）。
+            is_final: 标记当前片段是否为最终回复。
+
+        Returns:
+            dict: 包含 `stream` 键，标识写入是否成功。
+
+        Example:
+            在流水线 `reply_message_chunk` 调用中自动触发，无需手动调用。
+        """
+        # 转换为纯文本（智能机器人当前协议仅支持文本流）
         content = await self.message_converter.yiri2target(message)
         msg_id = message_source.source_platform_object.message_id
-        _ws_mode = not self.config.get('enable-webhook', False)
 
-        if _ws_mode:
-            success = await self.bot.push_stream_chunk(msg_id, content, is_final=is_final)
-            if not success and is_final:
-                event = message_source.source_platform_object
-                req_id = event.get('req_id', '')
-                if req_id:
-                    await self.bot.reply_text(req_id, content)
-            return {'stream': success}
-        else:
-            success = await self.bot.push_stream_chunk(msg_id, content, is_final=is_final)
-            if not success and is_final:
-                await self.bot.set_message(msg_id, content)
-            return {'stream': success}
+        # 将片段推送到 WecomBotClient 中的队列，返回值用于判断是否走降级逻辑
+        success = await self.bot.push_stream_chunk(msg_id, content, is_final=is_final)
+        if not success and is_final:
+            # 未命中流式队列时使用旧有 set_message 兜底
+            await self.bot.set_message(msg_id, content)
+        return {'stream': success}
 
     async def is_stream_output_supported(self) -> bool:
-        """Whether streaming output is enabled for this bot instance."""
-        return self.config.get('enable-stream-reply', True)
+        """智能机器人侧默认开启流式能力。
+
+        Returns:
+            bool: 恒定返回 True。
+
+        Example:
+            流水线执行阶段会调用此方法以确认是否启用流式。"""
+        return True
 
     async def send_message(self, target_type, target_id, message):
-        _ws_mode = not self.config.get('enable-webhook', False)
-        if _ws_mode:
-            content = await self.message_converter.yiri2target(message)
-            await self.bot.send_message(target_id, content)
-        else:
-            pass
-
-    async def on_message(self, event: WecomBotEvent):
-        try:
-            lb_event = await self.event_converter.target2yiri(event)
-            if lb_event:
-                await self.listeners[type(lb_event)](lb_event, self)
-        except Exception:
-            await self.logger.error(f'Error in wecombot callback: {traceback.format_exc()}')
-            print(traceback.format_exc())
+        pass
 
     def register_listener(
         self,
@@ -304,13 +268,18 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
             [platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None
         ],
     ):
-        self.listeners[event_type] = callback
+        async def on_message(event: WecomBotEvent):
+            try:
+                return await callback(await self.event_converter.target2yiri(event), self)
+            except Exception:
+                await self.logger.error(f'Error in wecombot callback: {traceback.format_exc()}')
+                print(traceback.format_exc())
 
         try:
             if event_type == platform_events.FriendMessage:
-                self.bot.on_message('single')(self.on_message)
+                self.bot.on_message('single')(on_message)
             elif event_type == platform_events.GroupMessage:
-                self.bot.on_message('group')(self.on_message)
+                self.bot.on_message('group')(on_message)
         except Exception:
             print(traceback.format_exc())
 
@@ -319,28 +288,29 @@ class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         self.bot_uuid = bot_uuid
 
     async def handle_unified_webhook(self, bot_uuid: str, path: str, request):
-        _ws_mode = not self.config.get('enable-webhook', False)
-        if _ws_mode:
-            return None
+        """处理统一 webhook 请求。
+
+        Args:
+            bot_uuid: Bot 的 UUID
+            path: 子路径（如果有的话）
+            request: Quart Request 对象
+
+        Returns:
+            响应数据
+        """
         return await self.bot.handle_unified_webhook(request)
 
     async def run_async(self):
-        _ws_mode = not self.config.get('enable-webhook', False)
-        if _ws_mode:
-            await self.bot.connect()
-        else:
+        # 统一 webhook 模式下，不启动独立的 Quart 应用
+        # 保持运行但不启动独立端口
 
-            async def keep_alive():
-                while True:
-                    await asyncio.sleep(1)
+        async def keep_alive():
+            while True:
+                await asyncio.sleep(1)
 
-            await keep_alive()
+        await keep_alive()
 
     async def kill(self) -> bool:
-        _ws_mode = not self.config.get('enable-webhook', False)
-        if _ws_mode:
-            await self.bot.disconnect()
-            return True
         return False
 
     async def unregister_listener(

src/langbot/pkg/platform/sources/wecombot.yaml

@@ -11,93 +11,35 @@ metadata:
   icon: wecombot.png
 spec:
   config:
-    - name: BotId
-      label:
-        en_US: BotId
-        zh_Hans: 机器人ID (BotId)
-      type: string
-      required: true
-      default: ""
-    - name: robot_name
-      label:
-        en_US: Robot Name
-        zh_Hans: 机器人名称
-      type: string
-      required: true
-      default: ""
-    - name: enable-webhook
-      label:
-        en_US: Enable Webhook Mode
-        zh_Hans: 启用Webhook模式
-      description:
-        en_US: If enabled, the bot will use webhook mode to receive messages. Otherwise, it will use WS long connection mode
-        zh_Hans: 如果启用，机器人将使用 Webhook 模式接收消息。否则，将使用 WS 长连接模式
-      type: boolean
-      required: true
-      default: false
-    - name: Secret
-      label:
-        en_US: Secret
-        zh_Hans: 机器人密钥 (Secret)
-      description:
-        en_US: Required for WebSocket long connection mode
-        zh_Hans: 使用 WS 长连接模式时必填
-      type: string
-      required: false
-      default: ""
     - name: Corpid
       label:
         en_US: Corpid
         zh_Hans: 企业ID
-      description:
-        en_US: Required for Webhook mode
-        zh_Hans: 使用 Webhook 模式时必填
       type: string
-      required: false
+      required: true
       default: ""
-      show_if:
-        field: enable-webhook
-        operator: eq
-        value: true
     - name: Token
       label:
         en_US: Token
         zh_Hans: 令牌 (Token)
-      description:
-        en_US: Required for Webhook mode
-        zh_Hans: 使用 Webhook 模式时必填
       type: string
-      required: false
+      required: true
       default: ""
-      show_if:
-        field: enable-webhook
-        operator: eq
-        value: true
     - name: EncodingAESKey
       label:
         en_US: EncodingAESKey
         zh_Hans: 消息加解密密钥 (EncodingAESKey)
-      description:
-        en_US: Required for Webhook mode. Optional for WebSocket mode (used for file decryption)
-        zh_Hans: 使用 Webhook 模式时必填。WebSocket 模式下可选（用于文件解密）
+      type: string
+      required: true
+      default: ""
+    - name: BotId
+      label:
+        en_US: BotId
+        zh_Hans: 机器人ID
       type: string
       required: false
       default: ""
-      show_if:
-        field: enable-webhook
-        operator: eq
-        value: true
-    - name: enable-stream-reply
-      label:
-        en_US: Enable Stream Reply
-        zh_Hans: 启用流式回复
-      description:
-        en_US: If enabled, the bot will use streaming mode to reply messages
-        zh_Hans: 如果启用，机器人将使用流式模式回复消息
-      type: boolean
-      required: false
-      default: true
 execution:
   python:
     path: ./wecombot.py
-    attr: WecomBotAdapter
+    attr: WecomBotAdapter

src/langbot/pkg/platform/sources/wecomcs.py

@@ -81,33 +81,22 @@ class WecomEventConverter(abstract_platform_adapter.AbstractEventConverter):
             return event.source_platform_object
 
     @staticmethod
-    async def target2yiri(event: WecomCSEvent, bot: WecomCSClient = None):
+    async def target2yiri(event: WecomCSEvent):
         """
         将 WecomEvent 转换为平台的 FriendMessage 对象。
 
         Args:
             event (WecomEvent): 企业微信客服事件。
-            bot (WecomCSClient): 企业微信客服客户端，用于获取用户信息。
 
         Returns:
             platform_events.FriendMessage: 转换后的 FriendMessage 对象。
         """
-        # Try to get customer nickname from WeChat API
-        nickname = str(event.user_id)
-        if bot and event.user_id:
-            try:
-                customer_info = await bot.get_customer_info(event.user_id)
-                if customer_info and customer_info.get('nickname'):
-                    nickname = customer_info.get('nickname')
-            except Exception:
-                pass  # Fall back to user_id as nickname
-
         # 转换消息链
         if event.type == 'text':
             yiri_chain = await WecomMessageConverter.target2yiri(event.message, event.message_id)
             friend = platform_entities.Friend(
                 id=f'u{event.user_id}',
-                nickname=nickname,
+                nickname=str(event.user_id),
                 remark='',
             )
 
@@ -117,7 +106,7 @@ class WecomEventConverter(abstract_platform_adapter.AbstractEventConverter):
         elif event.type == 'image':
             friend = platform_entities.Friend(
                 id=f'u{event.user_id}',
-                nickname=nickname,
+                nickname=str(event.user_id),
                 remark='',
             )
 
@@ -198,7 +187,7 @@ class WecomCSAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
         async def on_message(event: WecomCSEvent):
             self.bot_account_id = event.receiver_id
             try:
-                return await callback(await self.event_converter.target2yiri(event, self.bot), self)
+                return await callback(await self.event_converter.target2yiri(event), self)
             except Exception:
                 await self.logger.error(f'Error in wecomcs callback: {traceback.format_exc()}')
 

src/langbot/pkg/platform/webhook_pusher.py

@@ -3,8 +3,6 @@ from __future__ import annotations
 import asyncio
 import logging
 import aiohttp
-
-from langbot.pkg.utils import httpclient
 import uuid
 from typing import TYPE_CHECKING
 
@@ -121,23 +119,23 @@ class WebhookPusher:
             dict | None: The response JSON if successful, None otherwise
         """
         try:
-            session = httpclient.get_session()
-            async with session.post(
-                url,
-                json=payload,
-                headers={'Content-Type': 'application/json'},
-                timeout=aiohttp.ClientTimeout(total=15),
-            ) as response:
-                if response.status >= 400:
-                    self.logger.warning(f'Webhook {url} returned status {response.status}')
-                    return None
-                else:
-                    self.logger.debug(f'Successfully pushed to webhook {url}')
-                    try:
-                        return await response.json()
-                    except Exception as json_error:
-                        self.logger.debug(f'Failed to parse JSON response from webhook {url}: {json_error}')
+            async with aiohttp.ClientSession() as session:
+                async with session.post(
+                    url,
+                    json=payload,
+                    headers={'Content-Type': 'application/json'},
+                    timeout=aiohttp.ClientTimeout(total=15),
+                ) as response:
+                    if response.status >= 400:
+                        self.logger.warning(f'Webhook {url} returned status {response.status}')
                         return None
+                    else:
+                        self.logger.debug(f'Successfully pushed to webhook {url}')
+                        try:
+                            return await response.json()
+                        except Exception as json_error:
+                            self.logger.debug(f'Failed to parse JSON response from webhook {url}: {json_error}')
+                            return None
         except asyncio.TimeoutError:
             self.logger.warning(f'Timeout pushing to webhook {url}')
             return None

src/langbot/pkg/plugin/connector.py

@@ -7,6 +7,7 @@ import typing
 import os
 import sys
 import httpx
+import traceback
 import sqlalchemy
 from async_lru import alru_cache
 from langbot_plugin.api.entities.builtin.pipeline.query import provider_session
@@ -101,6 +102,12 @@ class PluginRuntimeConnector:
             self.handler_task = asyncio.create_task(self.handler.run())
             _ = await self.handler.ping()
             self.ap.logger.info('Connected to plugin runtime.')
+            # Sync polymorphic component instances after connection
+            try:
+                await self.sync_polymorphic_component_instances()
+            except Exception as e:
+                traceback.print_exc()
+                self.ap.logger.error(f'Failed to sync polymorphic component instances: {e}')
             await self.handler_task
 
         task: asyncio.Task | None = None
@@ -456,18 +463,30 @@ class PluginRuntimeConnector:
 
             yield cmd_ret
 
+    # KnowledgeRetriever methods
+    async def list_knowledge_retrievers(self, bound_plugins: list[str] | None = None) -> list[dict[str, Any]]:
+        """List all available KnowledgeRetriever components."""
+        if not self.is_enable_plugin:
+            return []
+
+        retrievers_data = await self.handler.list_knowledge_retrievers(include_plugins=bound_plugins)
+        return retrievers_data
+
     async def retrieve_knowledge(
         self,
         plugin_author: str,
         plugin_name: str,
         retriever_name: str,
+        instance_id: str,
         retrieval_context: dict[str, Any],
-    ) -> dict[str, Any]:
-        """Retrieve knowledge using a KnowledgeEngine instance."""
+    ) -> list[dict[str, Any]]:
+        """Retrieve knowledge using a KnowledgeRetriever instance."""
         if not self.is_enable_plugin:
-            return {'results': []}
+            return []
 
-        return await self.handler.retrieve_knowledge(plugin_author, plugin_name, retriever_name, retrieval_context)
+        return await self.handler.retrieve_knowledge(
+            plugin_author, plugin_name, retriever_name, instance_id, retrieval_context
+        )
 
     def dispose(self):
         # No need to consider the shutdown on Windows
@@ -481,84 +500,41 @@ class PluginRuntimeConnector:
             self.heartbeat_task.cancel()
             self.heartbeat_task = None
 
-    @staticmethod
-    def _parse_plugin_id(plugin_id: str) -> tuple[str, str]:
-        """Parse a plugin ID string into (author, name).
+    async def sync_polymorphic_component_instances(self) -> dict[str, Any]:
+        """Sync polymorphic component instances with runtime.
 
-        Args:
-            plugin_id: Plugin ID in 'author/name' format.
-
-        Returns:
-            Tuple of (plugin_author, plugin_name).
-
-        Raises:
-            ValueError: If plugin_id is not in the expected 'author/name' format.
+        This collects all external knowledge bases from database and sends to runtime
+        to ensure instance integrity across restarts.
         """
-        if '/' not in plugin_id:
-            raise ValueError(
-                f"Invalid plugin_id format: '{plugin_id}'. Expected 'author/name' format (e.g. 'langbot/rag-engine')."
+        if not self.is_enable_plugin:
+            return {}
+
+        # ===== external knowledge bases =====
+
+        external_kbs = await self.ap.external_kb_service.get_external_knowledge_bases()
+
+        # Build required_instances list
+        required_instances = []
+        for kb in external_kbs:
+            required_instances.append(
+                {
+                    'instance_id': kb['uuid'],
+                    'plugin_author': kb['plugin_author'],
+                    'plugin_name': kb['plugin_name'],
+                    'component_kind': 'KnowledgeRetriever',
+                    'component_name': kb['retriever_name'],
+                    'config': kb['retriever_config'],
+                }
             )
-        return plugin_id.split('/', 1)
 
-    async def call_rag_ingest(self, plugin_id: str, context_data: dict[str, Any]) -> dict[str, Any]:
-        """Call plugin to ingest document.
+        self.ap.logger.info(f'Syncing {len(required_instances)} polymorphic component instances to runtime')
 
-        Args:
-            plugin_id: Target plugin ID (author/name).
-            context_data: IngestionContext data.
-        """
-        plugin_author, plugin_name = self._parse_plugin_id(plugin_id)
-        return await self.handler.rag_ingest_document(plugin_author, plugin_name, context_data)
+        # Send to runtime
+        sync_result = await self.handler.sync_polymorphic_component_instances(required_instances)
 
-    async def call_rag_delete_document(self, plugin_id: str, document_id: str, kb_id: str) -> bool:
-        plugin_author, plugin_name = self._parse_plugin_id(plugin_id)
-        return await self.handler.rag_delete_document(plugin_author, plugin_name, document_id, kb_id)
+        self.ap.logger.info(
+            f'Sync complete: {len(sync_result.get("success_instances", []))} succeeded, '
+            f'{len(sync_result.get("failed_instances", []))} failed'
+        )
 
-    async def get_rag_creation_schema(self, plugin_id: str) -> dict[str, Any]:
-        plugin_author, plugin_name = self._parse_plugin_id(plugin_id)
-        return await self.handler.get_rag_creation_schema(plugin_author, plugin_name)
-
-    async def get_rag_retrieval_schema(self, plugin_id: str) -> dict[str, Any]:
-        plugin_author, plugin_name = self._parse_plugin_id(plugin_id)
-        return await self.handler.get_rag_retrieval_schema(plugin_author, plugin_name)
-
-    async def rag_on_kb_create(self, plugin_id: str, kb_id: str, config: dict[str, Any]) -> dict[str, Any]:
-        """Notify plugin about KB creation."""
-        plugin_author, plugin_name = self._parse_plugin_id(plugin_id)
-        return await self.handler.rag_on_kb_create(plugin_author, plugin_name, kb_id, config)
-
-    async def rag_on_kb_delete(self, plugin_id: str, kb_id: str) -> dict[str, Any]:
-        """Notify plugin about KB deletion."""
-        plugin_author, plugin_name = self._parse_plugin_id(plugin_id)
-        return await self.handler.rag_on_kb_delete(plugin_author, plugin_name, kb_id)
-
-    async def call_rag_retrieve(self, plugin_id: str, retrieval_context: dict[str, Any]) -> dict[str, Any]:
-        """Call plugin to retrieve knowledge.
-
-        Args:
-            plugin_id: Target plugin ID (author/name).
-            retrieval_context: RetrievalContext data.
-        """
-        plugin_author, plugin_name = self._parse_plugin_id(plugin_id)
-        return await self.handler.retrieve_knowledge(plugin_author, plugin_name, '', retrieval_context)
-
-    async def list_knowledge_engines(self) -> list[dict[str, Any]]:
-        """List all available Knowledge Engines from plugins.
-
-        Returns a list of Knowledge Engines with their capabilities and configuration schemas.
-        """
-        if not self.is_enable_plugin:
-            return []
-
-        return await self.handler.list_knowledge_engines()
-
-    async def list_parsers(self) -> list[dict[str, Any]]:
-        """List all available parsers from plugins."""
-        if not self.is_enable_plugin:
-            return []
-        return await self.handler.list_parsers()
-
-    async def call_parser(self, plugin_id: str, context_data: dict[str, Any], file_bytes: bytes) -> dict[str, Any]:
-        """Call plugin to parse a document."""
-        plugin_author, plugin_name = self._parse_plugin_id(plugin_id)
-        return await self.handler.parse_document(plugin_author, plugin_name, context_data, file_bytes)
+        return sync_result

src/langbot/pkg/plugin/handler.py

@@ -26,20 +26,6 @@ from ..core import app
 from ..utils import constants
 
 
-def _make_rag_error_response(error: Exception, error_type: str, **extra_context) -> handler.ActionResponse:
-    """Create a clean error response for RAG operations.
-
-    Args:
-        error: The caught exception.
-        error_type: A category string like 'EmbeddingError', 'VectorStoreError'.
-        **extra_context: Additional context fields for the error message.
-    """
-    context_parts = [f'{k}={v}' for k, v in extra_context.items()]
-    context_str = f' [{", ".join(context_parts)}]' if context_parts else ''
-    message = f'[{error_type}/{type(error).__name__}]{context_str} {str(error)}'
-    return handler.ActionResponse.error(message=message)
-
-
 class RuntimeConnectionHandler(handler.Handler):
     """Runtime connection handler"""
 
@@ -293,7 +279,6 @@ class RuntimeConnectionHandler(handler.Handler):
             target_id = data['target_id']
             message_chain = data['message_chain']
 
-            # Use custom deserializer that properly handles Forward messages
             message_chain_obj = platform_message.MessageChain.model_validate(message_chain)
 
             bot = await self.ap.platform_mgr.get_bot_by_uuid(bot_uuid)
@@ -314,11 +299,11 @@ class RuntimeConnectionHandler(handler.Handler):
 
         @self.action(PluginToRuntimeAction.GET_LLM_MODELS)
         async def get_llm_models(data: dict[str, Any]) -> handler.ActionResponse:
-            """Get llm models, returns list of UUID strings"""
+            """Get llm models"""
             llm_models = await self.ap.llm_model_service.get_llm_models(include_secret=False)
             return handler.ActionResponse.success(
                 data={
-                    'llm_models': [m['uuid'] for m in llm_models],
+                    'llm_models': llm_models,
                 },
             )
 
@@ -337,14 +322,7 @@ class RuntimeConnectionHandler(handler.Handler):
                 )
 
             messages_obj = [provider_message.Message.model_validate(message) for message in messages]
-
-            # The func field is excluded during model_dump() in plugin side (marked as exclude=True),
-            # but it's a required field for LLMTool validation. We need to provide a placeholder
-            # function when reconstructing the LLMTool objects from serialized data.
-            async def _placeholder_func(**kwargs):
-                pass
-
-            funcs_obj = [resource_tool.LLMTool.model_validate({**func, 'func': _placeholder_func}) for func in funcs]
+            funcs_obj = [resource_tool.LLMTool.model_validate(func) for func in funcs]
 
             result = await llm_model.provider.invoke_llm(
                 query=None,
@@ -460,7 +438,7 @@ class RuntimeConnectionHandler(handler.Handler):
                 },
             )
 
-        @self.action(PluginToRuntimeAction.GET_CONFIG_FILE)
+        @self.action(RuntimeToLangBotAction.GET_CONFIG_FILE)
         async def get_config_file(data: dict[str, Any]) -> handler.ActionResponse:
             """Get a config file by file key"""
             file_key = data['file_key']
@@ -479,282 +457,6 @@ class RuntimeConnectionHandler(handler.Handler):
                     message=f'Failed to load config file {file_key}: {e}',
                 )
 
-        # ================= RAG Capability Handlers =================
-
-        @self.action(PluginToRuntimeAction.INVOKE_EMBEDDING)
-        async def invoke_embedding(data: dict[str, Any]) -> handler.ActionResponse:
-            embedding_model_uuid = data['embedding_model_uuid']
-            texts = data['texts']
-
-            embedding_model = await self.ap.model_mgr.get_embedding_model_by_uuid(embedding_model_uuid)
-            if embedding_model is None:
-                return handler.ActionResponse.error(
-                    message=f'Embedding model with embedding_model_uuid {embedding_model_uuid} not found',
-                )
-
-            try:
-                vectors = await embedding_model.provider.invoke_embedding(embedding_model, texts)
-                return handler.ActionResponse.success(data={'vectors': vectors})
-            except Exception as e:
-                return _make_rag_error_response(e, 'EmbeddingError', embedding_model_uuid=embedding_model_uuid)
-
-        @self.action(PluginToRuntimeAction.VECTOR_UPSERT)
-        async def vector_upsert(data: dict[str, Any]) -> handler.ActionResponse:
-            collection_id = data['collection_id']
-            vectors = data['vectors']
-            ids = data['ids']
-            metadata = data.get('metadata')
-            documents = data.get('documents')
-            if len(vectors) != len(ids):
-                return handler.ActionResponse.error(message='vectors and ids must have same length')
-            if metadata and len(metadata) != len(vectors):
-                return handler.ActionResponse.error(message='metadata must match vectors length')
-            if documents and len(documents) != len(vectors):
-                return handler.ActionResponse.error(message='documents must match vectors length')
-            try:
-                await self.ap.rag_runtime_service.vector_upsert(
-                    collection_id,
-                    vectors,
-                    ids,
-                    metadata,
-                    documents,
-                )
-                return handler.ActionResponse.success(data={})
-            except Exception as e:
-                return _make_rag_error_response(e, 'VectorStoreError', collection_id=collection_id)
-
-        @self.action(PluginToRuntimeAction.VECTOR_SEARCH)
-        async def vector_search(data: dict[str, Any]) -> handler.ActionResponse:
-            collection_id = data['collection_id']
-            query_vector = data['query_vector']
-            top_k = data['top_k']
-            filters = data.get('filters')
-            search_type = data.get('search_type', 'vector')
-            query_text = data.get('query_text', '')
-            vector_weight = data.get('vector_weight')
-            try:
-                results = await self.ap.rag_runtime_service.vector_search(
-                    collection_id,
-                    query_vector,
-                    top_k,
-                    filters,
-                    search_type,
-                    query_text,
-                    vector_weight=vector_weight,
-                )
-                return handler.ActionResponse.success(data={'results': results})
-            except Exception as e:
-                return _make_rag_error_response(e, 'VectorStoreError', collection_id=collection_id)
-
-        @self.action(PluginToRuntimeAction.VECTOR_DELETE)
-        async def vector_delete(data: dict[str, Any]) -> handler.ActionResponse:
-            collection_id = data['collection_id']
-            file_ids = data.get('file_ids')
-            filters = data.get('filters')
-            try:
-                count = await self.ap.rag_runtime_service.vector_delete(collection_id, file_ids, filters)
-                return handler.ActionResponse.success(data={'count': count})
-            except Exception as e:
-                return _make_rag_error_response(e, 'VectorStoreError', collection_id=collection_id)
-
-        @self.action(PluginToRuntimeAction.VECTOR_LIST)
-        async def vector_list(data: dict[str, Any]) -> handler.ActionResponse:
-            collection_id = data['collection_id']
-            filters = data.get('filters')
-            limit = data.get('limit', 20)
-            offset = data.get('offset', 0)
-            try:
-                items, total = await self.ap.rag_runtime_service.vector_list(collection_id, filters, limit, offset)
-                return handler.ActionResponse.success(data={'items': items, 'total': total})
-            except Exception as e:
-                return _make_rag_error_response(e, 'VectorStoreError', collection_id=collection_id)
-
-        @self.action(PluginToRuntimeAction.GET_KNOWLEDEGE_FILE_STREAM)
-        async def get_knowledge_file_stream(data: dict[str, Any]) -> handler.ActionResponse:
-            storage_path = data['storage_path']
-            try:
-                content_bytes = await self.ap.rag_runtime_service.get_file_stream(storage_path)
-                file_key = await self.send_file(content_bytes, '')
-                return handler.ActionResponse.success(data={'file_key': file_key})
-            except Exception as e:
-                return _make_rag_error_response(e, 'FileServiceError', storage_path=storage_path)
-
-        @self.action(PluginToRuntimeAction.LIST_PARSERS)
-        async def list_parsers(data: dict[str, Any]) -> handler.ActionResponse:
-            """Plugin requests host to list available parser plugins."""
-            mime_type = data.get('mime_type')
-            try:
-                parsers = await self.ap.knowledge_service.list_parsers(mime_type)
-                return handler.ActionResponse.success(data={'parsers': parsers})
-            except Exception as e:
-                return _make_rag_error_response(e, 'ParserDiscoveryError', mime_type=mime_type)
-
-        @self.action(PluginToRuntimeAction.INVOKE_PARSER)
-        async def invoke_parser(data: dict[str, Any]) -> handler.ActionResponse:
-            """Plugin requests host to invoke a parser plugin."""
-            plugin_author = data['plugin_author']
-            plugin_name = data['plugin_name']
-            storage_path = data['storage_path']
-            mime_type = data.get('mime_type', 'application/octet-stream')
-            filename = data.get('filename', '')
-            metadata = data.get('metadata', {})
-            try:
-                # Read file from storage
-                file_bytes = await self.ap.rag_runtime_service.get_file_stream(storage_path)
-                context_data = {
-                    'mime_type': mime_type,
-                    'filename': filename,
-                    'metadata': metadata,
-                }
-                result = await self.ap.plugin_connector.call_parser(
-                    f'{plugin_author}/{plugin_name}', context_data, file_bytes
-                )
-                return handler.ActionResponse.success(data=result)
-            except Exception as e:
-                return _make_rag_error_response(e, 'ParserError')
-
-        # ================= Knowledge Base Query APIs =================
-
-        @self.action(PluginToRuntimeAction.LIST_KNOWLEDGE_BASES)
-        async def list_knowledge_bases(data: dict[str, Any]) -> handler.ActionResponse:
-            """List all knowledge bases available in the LangBot instance (unrestricted)."""
-            knowledge_bases = []
-            for kb_uuid, kb in self.ap.rag_mgr.knowledge_bases.items():
-                knowledge_bases.append(
-                    {
-                        'uuid': kb.get_uuid(),
-                        'name': kb.get_name(),
-                        'description': kb.knowledge_base_entity.description or '',
-                    }
-                )
-            return handler.ActionResponse.success(data={'knowledge_bases': knowledge_bases})
-
-        @self.action(PluginToRuntimeAction.RETRIEVE_KNOWLEDGE)
-        async def retrieve_knowledge(data: dict[str, Any]) -> handler.ActionResponse:
-            """Retrieve documents from any knowledge base (unrestricted)."""
-            kb_id = data['kb_id']
-            query_text = data['query_text']
-            top_k = data.get('top_k', 5)
-            filters = data.get('filters', {})
-
-            kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_id)
-            if not kb:
-                return handler.ActionResponse.error(
-                    message=f'Knowledge base {kb_id} not found',
-                )
-
-            try:
-                entries = await kb.retrieve(
-                    query_text,
-                    settings={
-                        'top_k': top_k,
-                        'filters': filters,
-                    },
-                )
-                results = [entry.model_dump(mode='json') for entry in entries]
-                return handler.ActionResponse.success(data={'results': results})
-            except Exception as e:
-                return _make_rag_error_response(e, 'RetrievalError', kb_id=kb_id)
-
-        @self.action(PluginToRuntimeAction.LIST_PIPELINE_KNOWLEDGE_BASES)
-        async def list_pipeline_knowledge_bases(data: dict[str, Any]) -> handler.ActionResponse:
-            """List knowledge bases configured for the current query's pipeline."""
-            query_id = data['query_id']
-
-            if query_id not in self.ap.query_pool.cached_queries:
-                return handler.ActionResponse.error(
-                    message=f'Query with query_id {query_id} not found',
-                )
-
-            query = self.ap.query_pool.cached_queries[query_id]
-
-            kb_uuids = []
-            if query.pipeline_config:
-                local_agent_config = query.pipeline_config.get('ai', {}).get('local-agent', {})
-                kb_uuids = local_agent_config.get('knowledge-bases', [])
-                # Backward compatibility
-                if not kb_uuids:
-                    old_kb_uuid = local_agent_config.get('knowledge-base', '')
-                    if old_kb_uuid and old_kb_uuid != '__none__':
-                        kb_uuids = [old_kb_uuid]
-
-            knowledge_bases = []
-            for kb_uuid in kb_uuids:
-                kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
-                if kb:
-                    knowledge_bases.append(
-                        {
-                            'uuid': kb.get_uuid(),
-                            'name': kb.get_name(),
-                            'description': kb.knowledge_base_entity.description or '',
-                        }
-                    )
-
-            return handler.ActionResponse.success(data={'knowledge_bases': knowledge_bases})
-
-        @self.action(PluginToRuntimeAction.RETRIEVE_KNOWLEDGE_BASE)
-        async def retrieve_knowledge_base(data: dict[str, Any]) -> handler.ActionResponse:
-            """Retrieve documents from a knowledge base within the pipeline's scope."""
-            query_id = data['query_id']
-            kb_id = data['kb_id']
-            query_text = data['query_text']
-            top_k = data.get('top_k', 5)
-            filters = data.get('filters', {})
-
-            if query_id not in self.ap.query_pool.cached_queries:
-                return handler.ActionResponse.error(
-                    message=f'Query with query_id {query_id} not found',
-                )
-
-            query = self.ap.query_pool.cached_queries[query_id]
-
-            # Validate kb_id is in pipeline's allowed list
-            allowed_kb_uuids = []
-            if query.pipeline_config:
-                local_agent_config = query.pipeline_config.get('ai', {}).get('local-agent', {})
-                allowed_kb_uuids = local_agent_config.get('knowledge-bases', [])
-                if not allowed_kb_uuids:
-                    old_kb_uuid = local_agent_config.get('knowledge-base', '')
-                    if old_kb_uuid and old_kb_uuid != '__none__':
-                        allowed_kb_uuids = [old_kb_uuid]
-
-            if kb_id not in allowed_kb_uuids:
-                return handler.ActionResponse.error(
-                    message=f'Knowledge base {kb_id} is not configured for this pipeline',
-                )
-
-            kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_id)
-            if not kb:
-                return handler.ActionResponse.error(
-                    message=f'Knowledge base {kb_id} not found',
-                )
-
-            try:
-                session_name = f'{query.session.launcher_type.value}_{query.session.launcher_id}'
-                entries = await kb.retrieve(
-                    query_text,
-                    settings={
-                        'top_k': top_k,
-                        'filters': filters,
-                        'session_name': session_name,
-                        'bot_uuid': query.bot_uuid or '',
-                        'sender_id': str(query.sender_id),
-                    },
-                )
-                results = [entry.model_dump(mode='json') for entry in entries]
-                return handler.ActionResponse.success(data={'results': results})
-            except Exception as e:
-                return _make_rag_error_response(e, 'RetrievalError', kb_id=kb_id)
-
-        @self.action(CommonAction.PING)
-        async def ping(data: dict[str, Any]) -> handler.ActionResponse:
-            """Ping"""
-            return handler.ActionResponse.success(
-                data={
-                    'pong': 'pong',
-                },
-            )
-
     async def ping(self) -> dict[str, Any]:
         """Ping the runtime"""
         return await self.call_action(
@@ -1014,13 +716,26 @@ class RuntimeConnectionHandler(handler.Handler):
         async for ret in gen:
             yield ret
 
+    # KnowledgeRetriever methods
+    async def list_knowledge_retrievers(self, include_plugins: list[str] | None = None) -> list[dict[str, Any]]:
+        """List knowledge retrievers"""
+        result = await self.call_action(
+            LangBotToRuntimeAction.LIST_KNOWLEDGE_RETRIEVERS,
+            {
+                'include_plugins': include_plugins,
+            },
+            timeout=10,
+        )
+        return result['retrievers']
+
     async def retrieve_knowledge(
         self,
         plugin_author: str,
         plugin_name: str,
         retriever_name: str,
+        instance_id: str,
         retrieval_context: dict[str, Any],
-    ) -> dict[str, Any]:
+    ) -> list[dict[str, Any]]:
         """Retrieve knowledge"""
         result = await self.call_action(
             LangBotToRuntimeAction.RETRIEVE_KNOWLEDGE,
@@ -1028,10 +743,22 @@ class RuntimeConnectionHandler(handler.Handler):
                 'plugin_author': plugin_author,
                 'plugin_name': plugin_name,
                 'retriever_name': retriever_name,
+                'instance_id': instance_id,
                 'retrieval_context': retrieval_context,
             },
             timeout=30,
         )
+        return result['retrieval_results']
+
+    async def sync_polymorphic_component_instances(self, required_instances: list[dict[str, Any]]) -> dict[str, Any]:
+        """Sync polymorphic component instances with runtime"""
+        result = await self.call_action(
+            LangBotToRuntimeAction.SYNC_POLYMORPHIC_COMPONENT_INSTANCES,
+            {
+                'required_instances': required_instances,
+            },
+            timeout=30,
+        )
         return result
 
     async def get_debug_info(self) -> dict[str, Any]:
@@ -1042,91 +769,3 @@ class RuntimeConnectionHandler(handler.Handler):
             timeout=10,
         )
         return result
-
-    # ================= RAG Capability Callers (LangBot -> Runtime) =================
-
-    async def rag_ingest_document(
-        self, plugin_author: str, plugin_name: str, context_data: dict[str, Any]
-    ) -> dict[str, Any]:
-        """Send INGEST_DOCUMENT action to runtime."""
-        result = await self.call_action(
-            LangBotToRuntimeAction.RAG_INGEST_DOCUMENT,
-            {'plugin_author': plugin_author, 'plugin_name': plugin_name, 'context': context_data},
-            timeout=1200,  # Ingestion can be slow for large documents
-        )
-        return result
-
-    async def rag_delete_document(self, plugin_author: str, plugin_name: str, document_id: str, kb_id: str) -> bool:
-        result = await self.call_action(
-            LangBotToRuntimeAction.RAG_DELETE_DOCUMENT,
-            {'plugin_author': plugin_author, 'plugin_name': plugin_name, 'document_id': document_id, 'kb_id': kb_id},
-            timeout=30,
-        )
-        return result.get('success', False)
-
-    async def rag_on_kb_create(
-        self, plugin_author: str, plugin_name: str, kb_id: str, config: dict[str, Any]
-    ) -> dict[str, Any]:
-        """Notify plugin about KB creation."""
-        result = await self.call_action(
-            LangBotToRuntimeAction.RAG_ON_KB_CREATE,
-            {'plugin_author': plugin_author, 'plugin_name': plugin_name, 'kb_id': kb_id, 'config': config},
-            timeout=30,
-        )
-        return result
-
-    async def rag_on_kb_delete(self, plugin_author: str, plugin_name: str, kb_id: str) -> dict[str, Any]:
-        """Notify plugin about KB deletion."""
-        result = await self.call_action(
-            LangBotToRuntimeAction.RAG_ON_KB_DELETE,
-            {'plugin_author': plugin_author, 'plugin_name': plugin_name, 'kb_id': kb_id},
-            timeout=30,
-        )
-        return result
-
-    async def get_rag_creation_schema(self, plugin_author: str, plugin_name: str) -> dict[str, Any]:
-        return await self.call_action(
-            LangBotToRuntimeAction.GET_RAG_CREATION_SETTINGS_SCHEMA,
-            {'plugin_author': plugin_author, 'plugin_name': plugin_name},
-            timeout=10,
-        )
-
-    async def get_rag_retrieval_schema(self, plugin_author: str, plugin_name: str) -> dict[str, Any]:
-        return await self.call_action(
-            LangBotToRuntimeAction.GET_RAG_RETRIEVAL_SETTINGS_SCHEMA,
-            {'plugin_author': plugin_author, 'plugin_name': plugin_name},
-            timeout=10,
-        )
-
-    async def list_knowledge_engines(self) -> list[dict[str, Any]]:
-        """List all available Knowledge Engines from plugins."""
-        result = await self.call_action(LangBotToRuntimeAction.LIST_KNOWLEDGE_ENGINES, {}, timeout=60)
-        return result.get('engines', [])
-
-    # ================= Parser Capability Callers (LangBot -> Runtime) =================
-
-    async def list_parsers(self) -> list[dict[str, Any]]:
-        """List all available parsers from plugins."""
-        result = await self.call_action(LangBotToRuntimeAction.LIST_PARSERS, {}, timeout=60)
-        return result.get('parsers', [])
-
-    async def parse_document(
-        self, plugin_author: str, plugin_name: str, context_data: dict[str, Any], file_bytes: bytes
-    ) -> dict[str, Any]:
-        """Send PARSE_DOCUMENT action to runtime.
-
-        Sends file content via chunked FILE_CHUNK transfer, then invokes
-        the PARSE_DOCUMENT action with a file_key reference.
-        """
-        # Send file to runtime via chunked transfer
-        file_key = await self.send_file(file_bytes, '')
-
-        # Include file_key in context_data for the runtime to read
-        context_data['file_key'] = file_key
-
-        result = await self.call_action(
-            LangBotToRuntimeAction.PARSE_DOCUMENT,
-            {'plugin_author': plugin_author, 'plugin_name': plugin_name, 'context': context_data},
-            timeout=300,
-        )
-        return result

src/langbot/pkg/provider/modelmgr/requesters/anthropicmsgs.py

@@ -288,10 +288,10 @@ class AnthropicMessages(requester.ProviderAPIRequester):
             think_started = False
             think_ended = False
             finish_reason = False
+            content = ''
             tool_name = ''
             tool_id = ''
             async for chunk in await self.client.messages.create(**args):
-                content = ''
                 tool_call = {'id': None, 'function': {'name': None, 'arguments': None}, 'type': 'function'}
                 if isinstance(
                     chunk, anthropic.types.raw_content_block_start_event.RawContentBlockStartEvent

src/langbot/pkg/provider/runners/difysvapi.py

@@ -72,28 +72,6 @@ class DifyServiceAPIRunner(runner.RequestRunner):
                 content = f'<think>\n{thinking_content}\n</think>\n{content}'.strip()
             return content, thinking_content
 
-    def _extract_dify_text_output(self, value: typing.Any) -> str:
-        """Extract text content from Dify output payload."""
-        if value is None:
-            return ''
-        if isinstance(value, dict):
-            content = value.get('content')
-            if isinstance(content, str):
-                return content
-            return json.dumps(value, ensure_ascii=False)
-        if isinstance(value, str):
-            text = value.strip()
-            if not text:
-                return ''
-            try:
-                parsed = json.loads(text)
-            except json.JSONDecodeError:
-                return value
-            if isinstance(parsed, dict) and isinstance(parsed.get('content'), str):
-                return parsed['content']
-            return value
-        return str(value)
-
     async def _preprocess_user_message(self, query: pipeline_query.Query) -> tuple[str, list[dict]]:
         """预处理用户消息，提取纯文本，并将图片/文件上传到 Dify 服务
 
@@ -214,8 +192,7 @@ class DifyServiceAPIRunner(runner.RequestRunner):
             if mode == 'workflow':
                 if chunk['event'] == 'node_finished':
                     if chunk['data']['node_type'] == 'answer':
-                        answer = self._extract_dify_text_output(chunk['data']['outputs'].get('answer'))
-                        content, _ = self._process_thinking_content(answer)
+                        content, _ = self._process_thinking_content(chunk['data']['outputs']['answer'])
 
                         yield provider_message.Message(
                             role='assistant',
@@ -428,7 +405,6 @@ class DifyServiceAPIRunner(runner.RequestRunner):
             for f in upload_files
         ]
 
-        mode = 'basic'
         basic_mode_pending_chunk = ''
 
         inputs = {}
@@ -441,7 +417,6 @@ class DifyServiceAPIRunner(runner.RequestRunner):
         is_final = False
         think_start = False
         think_end = False
-        yielded_final = False
 
         remove_think = self.pipeline_config['output'].get('misc', '').get('remove-think')
 
@@ -455,12 +430,11 @@ class DifyServiceAPIRunner(runner.RequestRunner):
         ):
             self.ap.logger.debug('dify-chat-chunk: ' + str(chunk))
 
-            if chunk['event'] == 'workflow_started':
-                mode = 'workflow'
-            elif chunk['event'] in ('node_started', 'node_finished', 'workflow_finished'):
-                # Some Dify deployments may omit workflow_started in streamed chunks.
-                mode = 'workflow'
-
+            # if chunk['event'] == 'workflow_started':
+            #     mode = 'workflow'
+            # if mode == 'workflow':
+            # elif mode == 'basic':
+            # 因为都只是返回的 message也没有工具调用什么的，暂时不分类
             if chunk['event'] == 'message':
                 message_idx += 1
                 if remove_think:
@@ -483,30 +457,14 @@ class DifyServiceAPIRunner(runner.RequestRunner):
 
             if chunk['event'] == 'message_end':
                 is_final = True
-            elif chunk['event'] == 'workflow_finished':
-                is_final = True
-                if chunk['data'].get('error'):
-                    raise errors.DifyAPIError(chunk['data']['error'])
 
-            if mode == 'workflow' and chunk['event'] == 'node_finished':
-                if chunk['data'].get('node_type') == 'answer':
-                    answer = self._extract_dify_text_output(chunk['data'].get('outputs', {}).get('answer'))
-                    if answer:
-                        basic_mode_pending_chunk = answer
-
-            if (
-                not yielded_final
-                and (is_final or message_idx % 8 == 0)
-                and (basic_mode_pending_chunk != '' or is_final)
-            ):
+            if is_final or message_idx % 8 == 0:
                 # content, _ = self._process_thinking_content(basic_mode_pending_chunk)
                 yield provider_message.MessageChunk(
                     role='assistant',
                     content=basic_mode_pending_chunk,
                     is_final=is_final,
                 )
-                if is_final:
-                    yielded_final = True
 
         if chunk is None:
             raise errors.DifyAPIError('Dify API 没有返回任何响应，请检查网络连接和API配置')

src/langbot/pkg/provider/runners/localagent.py

@@ -4,7 +4,6 @@ import json
 import copy
 import typing
 from .. import runner
-from ..modelmgr import requester as modelmgr_requester
 import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
 import langbot_plugin.api.entities.builtin.provider.message as provider_message
 import langbot_plugin.api.entities.builtin.rag.context as rag_context
@@ -27,114 +26,29 @@ Respond in the same language as the user's input.
 
 @runner.runner_class('local-agent')
 class LocalAgentRunner(runner.RequestRunner):
-    """Local agent request runner"""
+    """本地Agent请求运行器"""
 
-    async def _get_model_candidates(
-        self,
-        query: pipeline_query.Query,
-    ) -> list[modelmgr_requester.RuntimeLLMModel]:
-        """Build ordered list of models to try: primary model + fallback models."""
-        candidates = []
+    class ToolCallTracker:
+        """工具调用追踪器"""
 
-        # Primary model
-        if query.use_llm_model_uuid:
-            try:
-                primary = await self.ap.model_mgr.get_model_by_uuid(query.use_llm_model_uuid)
-                candidates.append(primary)
-            except ValueError:
-                self.ap.logger.warning(f'Primary model {query.use_llm_model_uuid} not found')
-
-        # Fallback models
-        fallback_uuids = (query.variables or {}).get('_fallback_model_uuids', [])
-        for fb_uuid in fallback_uuids:
-            try:
-                fb_model = await self.ap.model_mgr.get_model_by_uuid(fb_uuid)
-                candidates.append(fb_model)
-            except ValueError:
-                self.ap.logger.warning(f'Fallback model {fb_uuid} not found, skipping')
-
-        return candidates
-
-    async def _invoke_with_fallback(
-        self,
-        query: pipeline_query.Query,
-        candidates: list[modelmgr_requester.RuntimeLLMModel],
-        messages: list,
-        funcs: list,
-        remove_think: bool,
-    ) -> tuple[provider_message.Message, modelmgr_requester.RuntimeLLMModel]:
-        """Try non-streaming invocation with sequential fallback. Returns (message, model_used)."""
-        last_error = None
-        for model in candidates:
-            try:
-                msg = await model.provider.invoke_llm(
-                    query,
-                    model,
-                    messages,
-                    funcs if model.model_entity.abilities.__contains__('func_call') else [],
-                    extra_args=model.model_entity.extra_args,
-                    remove_think=remove_think,
-                )
-                return msg, model
-            except Exception as e:
-                last_error = e
-                self.ap.logger.warning(f'Model {model.model_entity.name} failed: {e}, trying next fallback...')
-        raise last_error or RuntimeError('No model candidates available')
-
-    async def _invoke_stream_with_fallback(
-        self,
-        query: pipeline_query.Query,
-        candidates: list[modelmgr_requester.RuntimeLLMModel],
-        messages: list,
-        funcs: list,
-        remove_think: bool,
-    ) -> tuple[typing.AsyncGenerator, modelmgr_requester.RuntimeLLMModel]:
-        """Try streaming invocation with sequential fallback. Returns (stream_generator, model_used).
-
-        Fallback is only possible before any chunks have been yielded to the client.
-        Once streaming starts, the model is committed.
-        """
-        last_error = None
-        for model in candidates:
-            try:
-                stream = model.provider.invoke_llm_stream(
-                    query,
-                    model,
-                    messages,
-                    funcs if model.model_entity.abilities.__contains__('func_call') else [],
-                    extra_args=model.model_entity.extra_args,
-                    remove_think=remove_think,
-                )
-                # Attempt to get the first chunk to verify the stream works
-                first_chunk = await stream.__anext__()
-
-                async def _chain_stream(first, rest):
-                    yield first
-                    async for chunk in rest:
-                        yield chunk
-
-                return _chain_stream(first_chunk, stream), model
-            except StopAsyncIteration:
-                # Empty stream — treat as success (model returned nothing)
-                async def _empty_stream():
-                    return
-                    yield  # make it a generator
-
-                return _empty_stream(), model
-            except Exception as e:
-                last_error = e
-                self.ap.logger.warning(f'Model {model.model_entity.name} stream failed: {e}, trying next fallback...')
-        raise last_error or RuntimeError('No model candidates available')
+        def __init__(self):
+            self.active_calls: dict[str, dict] = {}
+            self.completed_calls: list[provider_message.ToolCall] = []
 
     async def run(
         self, query: pipeline_query.Query
     ) -> typing.AsyncGenerator[provider_message.Message | provider_message.MessageChunk, None]:
-        """Run request"""
+        """运行请求"""
         pending_tool_calls = []
 
-        # Get knowledge bases list from query variables (set by PreProcessor,
-        # may have been modified by plugins during PromptPreProcessing)
-        kb_uuids = query.variables.get('_knowledge_base_uuids', [])
+        # Get knowledge bases list (new field)
+        kb_uuids = query.pipeline_config['ai']['local-agent'].get('knowledge-bases', [])
+
+        # Fallback to old field for backward compatibility
+        if not kb_uuids:
+            old_kb_uuid = query.pipeline_config['ai']['local-agent'].get('knowledge-base', '')
+            if old_kb_uuid and old_kb_uuid != '__none__':
+                kb_uuids = [old_kb_uuid]
 
         user_message = copy.deepcopy(query.user_message)
 
@@ -160,14 +74,15 @@ class LocalAgentRunner(runner.RequestRunner):
                     self.ap.logger.warning(f'Knowledge base {kb_uuid} not found, skipping')
                     continue
 
-                result = await kb.retrieve(
-                    user_message_text,
-                    settings={
-                        'bot_uuid': query.bot_uuid or '',
-                        'sender_id': str(query.sender_id),
-                        'session_name': f'{query.session.launcher_type.value}_{query.session.launcher_id}',
-                    },
-                )
+                # Get top_k based on KB type
+                if kb.get_type() == 'internal':
+                    top_k = kb.knowledge_base_entity.top_k
+                elif kb.get_type() == 'external':
+                    top_k = 5  # external kb's top_k is managed by plugin config
+                else:
+                    top_k = 5  # default fallback
+
+                result = await kb.retrieve(user_message_text, top_k)
 
                 if result:
                     all_results.extend(result)
@@ -182,9 +97,9 @@ class LocalAgentRunner(runner.RequestRunner):
                         if content.type == 'text' and content.text is not None:
                             texts.append(f'[{idx}] {content.text}')
                             idx += 1
-                rag_context_text = '\n\n'.join(texts)
+                rag_context = '\n\n'.join(texts)
                 final_user_message_text = rag_combined_prompt_template.format(
-                    rag_context=rag_context_text, user_message=user_message_text
+                    rag_context=rag_context, user_message=user_message_text
                 )
 
             else:
@@ -206,51 +121,51 @@ class LocalAgentRunner(runner.RequestRunner):
 
         remove_think = query.pipeline_config['output'].get('misc', '').get('remove-think')
 
-        # Build ordered candidate list (primary + fallbacks)
-        candidates = await self._get_model_candidates(query)
-        if not candidates:
-            raise RuntimeError('No LLM model configured for local-agent runner')
+        use_llm_model = await self.ap.model_mgr.get_model_by_uuid(query.use_llm_model_uuid)
 
         self.ap.logger.debug(
-            f'localagent req: query={query.query_id} req_messages={req_messages} '
-            f'candidates={[m.model_entity.name for m in candidates]}'
+            f'localagent req: query={query.query_id} req_messages={req_messages} use_llm_model={query.use_llm_model_uuid}'
         )
 
         if not is_stream:
-            # Non-streaming: invoke with fallback
-            msg, use_llm_model = await self._invoke_with_fallback(
+            # 非流式输出，直接请求
+
+            msg = await use_llm_model.provider.invoke_llm(
                 query,
-                candidates,
+                use_llm_model,
                 req_messages,
                 query.use_funcs,
-                remove_think,
+                extra_args=use_llm_model.model_entity.extra_args,
+                remove_think=remove_think,
             )
             yield msg
             final_msg = msg
         else:
-            # Streaming: invoke with fallback
+            # 流式输出，需要处理工具调用
             tool_calls_map: dict[str, provider_message.ToolCall] = {}
             msg_idx = 0
-            accumulated_content = ''
+            accumulated_content = ''  # 从开始累积的所有内容
             last_role = 'assistant'
             msg_sequence = 1
-
-            stream_src, use_llm_model = await self._invoke_stream_with_fallback(
+            async for msg in use_llm_model.provider.invoke_llm_stream(
                 query,
-                candidates,
+                use_llm_model,
                 req_messages,
                 query.use_funcs,
-                remove_think,
-            )
-            async for msg in stream_src:
+                extra_args=use_llm_model.model_entity.extra_args,
+                remove_think=remove_think,
+            ):
                 msg_idx = msg_idx + 1
 
+                # 记录角色
                 if msg.role:
                     last_role = msg.role
 
+                # 累积内容
                 if msg.content:
                     accumulated_content += msg.content
 
+                # 处理工具调用
                 if msg.tool_calls:
                     for tool_call in msg.tool_calls:
                         if tool_call.id not in tool_calls_map:
@@ -262,18 +177,21 @@ class LocalAgentRunner(runner.RequestRunner):
                                 ),
                             )
                         if tool_call.function and tool_call.function.arguments:
+                            # 流式处理中，工具调用参数可能分多个chunk返回，需要追加而不是覆盖
                             tool_calls_map[tool_call.id].function.arguments += tool_call.function.arguments
-
+                # continue
+                # 每8个chunk或最后一个chunk时，输出所有累积的内容
                 if msg_idx % 8 == 0 or msg.is_final:
                     msg_sequence += 1
                     yield provider_message.MessageChunk(
                         role=last_role,
-                        content=accumulated_content,
+                        content=accumulated_content,  # 输出所有累积内容
                         tool_calls=list(tool_calls_map.values()) if (tool_calls_map and msg.is_final) else None,
                         is_final=msg.is_final,
                         msg_sequence=msg_sequence,
                     )
 
+            # 创建最终消息用于后续处理
             final_msg = provider_message.MessageChunk(
                 role=last_role,
                 content=accumulated_content,
@@ -288,8 +206,7 @@ class LocalAgentRunner(runner.RequestRunner):
 
         req_messages.append(final_msg)
 
-        # Once a model succeeds, commit to it for the tool call loop
-        # (no fallback mid-conversation — different models may interpret tool results differently)
+        # 持续请求，只要还有待处理的工具调用就继续处理调用
         while pending_tool_calls:
             for tool_call in pending_tool_calls:
                 try:
@@ -330,6 +247,7 @@ class LocalAgentRunner(runner.RequestRunner):
 
                     req_messages.append(msg)
                 except Exception as e:
+                    # 工具调用出错，添加一个报错信息到 req_messages
                     err_msg = provider_message.Message(role='tool', content=f'err: {e}', tool_call_id=tool_call.id)
 
                     yield err_msg
@@ -337,38 +255,39 @@ class LocalAgentRunner(runner.RequestRunner):
                     req_messages.append(err_msg)
 
             self.ap.logger.debug(
-                f'localagent req: query={query.query_id} req_messages={req_messages} '
-                f'use_llm_model={use_llm_model.model_entity.name}'
+                f'localagent req: query={query.query_id} req_messages={req_messages} use_llm_model={query.use_llm_model_uuid}'
             )
 
             if is_stream:
                 tool_calls_map = {}
                 msg_idx = 0
-                accumulated_content = ''
+                accumulated_content = ''  # 从开始累积的所有内容
                 last_role = 'assistant'
                 msg_sequence = first_end_sequence
 
-                tool_stream_src = use_llm_model.provider.invoke_llm_stream(
+                async for msg in use_llm_model.provider.invoke_llm_stream(
                     query,
                     use_llm_model,
                     req_messages,
-                    query.use_funcs if use_llm_model.model_entity.abilities.__contains__('func_call') else [],
+                    query.use_funcs,
                     extra_args=use_llm_model.model_entity.extra_args,
                     remove_think=remove_think,
-                )
-                async for msg in tool_stream_src:
+                ):
                     msg_idx += 1
 
+                    # 记录角色
                     if msg.role:
                         last_role = msg.role
 
-                    # Prepend first-round content on first chunk of tool-call round
+                    # 第一次请求工具调用时的内容
                     if msg_idx == 1:
                         accumulated_content = first_content if first_content is not None else accumulated_content
 
+                    # 累积内容
                     if msg.content:
                         accumulated_content += msg.content
 
+                    # 处理工具调用
                     if msg.tool_calls:
                         for tool_call in msg.tool_calls:
                             if tool_call.id not in tool_calls_map:
@@ -380,13 +299,15 @@ class LocalAgentRunner(runner.RequestRunner):
                                     ),
                                 )
                             if tool_call.function and tool_call.function.arguments:
+                                # 流式处理中，工具调用参数可能分多个chunk返回，需要追加而不是覆盖
                                 tool_calls_map[tool_call.id].function.arguments += tool_call.function.arguments
 
+                    # 每8个chunk或最后一个chunk时，输出所有累积的内容
                     if msg_idx % 8 == 0 or msg.is_final:
                         msg_sequence += 1
                         yield provider_message.MessageChunk(
                             role=last_role,
-                            content=accumulated_content,
+                            content=accumulated_content,  # 输出所有累积内容
                             tool_calls=list(tool_calls_map.values()) if (tool_calls_map and msg.is_final) else None,
                             is_final=msg.is_final,
                             msg_sequence=msg_sequence,
@@ -399,12 +320,12 @@ class LocalAgentRunner(runner.RequestRunner):
                     msg_sequence=msg_sequence,
                 )
             else:
-                # Non-streaming: use committed model directly (no fallback in tool loop)
+                # 处理完所有调用，再次请求
                 msg = await use_llm_model.provider.invoke_llm(
                     query,
                     use_llm_model,
                     req_messages,
-                    query.use_funcs if use_llm_model.model_entity.abilities.__contains__('func_call') else [],
+                    query.use_funcs,
                     extra_args=use_llm_model.model_entity.extra_args,
                     remove_think=remove_think,
                 )

src/langbot/pkg/provider/runners/n8nsvapi.py

@@ -5,8 +5,6 @@ import json
 import uuid
 import aiohttp
 
-from langbot.pkg.utils import httpclient
-
 from .. import runner
 from ...core import app
 import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
@@ -219,50 +217,50 @@ class N8nServiceAPIRunner(runner.RequestRunner):
                 self.ap.logger.debug('no auth')
 
             # 调用webhook
-            session = httpclient.get_session()
-            if is_stream:
-                # 流式请求
-                async with session.post(
-                    self.webhook_url, json=payload, headers=headers, auth=auth, timeout=self.timeout
-                ) as response:
-                    if response.status != 200:
-                        error_text = await response.text()
-                        self.ap.logger.error(f'n8n webhook call failed: {response.status}, {error_text}')
-                        raise Exception(f'n8n webhook call failed: {response.status}, {error_text}')
-
-                    # 处理流式响应
-                    async for chunk in self._process_stream_response(response):
-                        yield chunk
-            else:
-                async with session.post(
-                    self.webhook_url, json=payload, headers=headers, auth=auth, timeout=self.timeout
-                ) as response:
-                    try:
-                        async for chunk in self._process_stream_response(response):
-                            output_content = chunk.content if chunk.is_final else ''
-                    except:
-                        # 非流式请求（保持原有逻辑）
+            async with aiohttp.ClientSession() as session:
+                if is_stream:
+                    # 流式请求
+                    async with session.post(
+                        self.webhook_url, json=payload, headers=headers, auth=auth, timeout=self.timeout
+                    ) as response:
                         if response.status != 200:
                             error_text = await response.text()
                             self.ap.logger.error(f'n8n webhook call failed: {response.status}, {error_text}')
                             raise Exception(f'n8n webhook call failed: {response.status}, {error_text}')
 
-                        # 解析响应
-                        response_data = await response.json()
-                        self.ap.logger.debug(f'n8n webhook response: {response_data}')
+                        # 处理流式响应
+                        async for chunk in self._process_stream_response(response):
+                            yield chunk
+                else:
+                    async with session.post(
+                        self.webhook_url, json=payload, headers=headers, auth=auth, timeout=self.timeout
+                    ) as response:
+                        try:
+                            async for chunk in self._process_stream_response(response):
+                                output_content = chunk.content if chunk.is_final else ''
+                        except:
+                            # 非流式请求（保持原有逻辑）
+                            if response.status != 200:
+                                error_text = await response.text()
+                                self.ap.logger.error(f'n8n webhook call failed: {response.status}, {error_text}')
+                                raise Exception(f'n8n webhook call failed: {response.status}, {error_text}')
 
-                        # 从响应中提取输出
-                        if self.output_key in response_data:
-                            output_content = response_data[self.output_key]
-                        else:
-                            # 如果没有指定的输出键，则使用整个响应
-                            output_content = json.dumps(response_data, ensure_ascii=False)
+                            # 解析响应
+                            response_data = await response.json()
+                            self.ap.logger.debug(f'n8n webhook response: {response_data}')
 
-                    # 返回消息
-                    yield provider_message.Message(
-                        role='assistant',
-                        content=output_content,
-                    )
+                            # 从响应中提取输出
+                            if self.output_key in response_data:
+                                output_content = response_data[self.output_key]
+                            else:
+                                # 如果没有指定的输出键，则使用整个响应
+                                output_content = json.dumps(response_data, ensure_ascii=False)
+
+                        # 返回消息
+                        yield provider_message.Message(
+                            role='assistant',
+                            content=output_content,
+                        )
         except Exception as e:
             self.ap.logger.error(f'n8n webhook call exception: {str(e)}')
             raise N8nAPIError(f'n8n webhook call exception: {str(e)}')

src/langbot/pkg/rag/knowledge/base.py

@@ -22,12 +22,12 @@ class KnowledgeBaseInterface(metaclass=abc.ABCMeta):
         pass
 
     @abc.abstractmethod
-    async def retrieve(self, query: str, settings: dict | None = None) -> list[rag_context.RetrievalResultEntry]:
+    async def retrieve(self, query: str, top_k: int) -> list[rag_context.RetrievalResultEntry]:
         """Retrieve relevant documents from the knowledge base
 
         Args:
             query: The query string
-            settings: Optional per-request retrieval settings overrides
+            top_k: Number of top results to return
 
         Returns:
             List of retrieve result entries
@@ -45,8 +45,8 @@ class KnowledgeBaseInterface(metaclass=abc.ABCMeta):
         pass
 
     @abc.abstractmethod
-    def get_knowledge_engine_plugin_id(self) -> str:
-        """Get the Knowledge Engine plugin ID"""
+    def get_type(self) -> str:
+        """Get the type of knowledge base (internal/external)"""
         pass
 
     @abc.abstractmethod

src/langbot/pkg/rag/knowledge/external.py

@@ -0,0 +1,85 @@
+"""External knowledge base implementation"""
+
+from __future__ import annotations
+
+from langbot.pkg.core import app
+from langbot.pkg.entity.persistence import rag as persistence_rag
+from langbot_plugin.api.entities.builtin.rag import context as rag_context
+from .base import KnowledgeBaseInterface
+
+
+class ExternalKnowledgeBase(KnowledgeBaseInterface):
+    """External knowledge base that queries via HTTP API or plugin retriever"""
+
+    external_kb_entity: persistence_rag.ExternalKnowledgeBase
+
+    # Plugin retriever instance ID
+    retriever_instance_id: str | None
+
+    def __init__(self, ap: app.Application, external_kb_entity: persistence_rag.ExternalKnowledgeBase):
+        super().__init__(ap)
+        self.external_kb_entity = external_kb_entity
+        self.retriever_instance_id = None
+
+    async def initialize(self):
+        """Initialize the external knowledge base"""
+        # Use KB UUID as instance ID
+        # Instance creation is now handled by the unified sync mechanism
+        # when LangBot connects to runtime
+        self.retriever_instance_id = self.external_kb_entity.uuid
+
+        self.ap.logger.info(
+            f'Initialized external KB {self.external_kb_entity.uuid}, instance will be created by sync mechanism'
+        )
+
+    async def retrieve(self, query: str, top_k: int = 5) -> list[rag_context.RetrievalResultEntry]:
+        """Retrieve documents from external knowledge base via plugin retriever"""
+        if not self.retriever_instance_id:
+            self.ap.logger.error(f'No retriever instance for KB {self.external_kb_entity.uuid}')
+            return []
+
+        try:
+            results = await self.ap.plugin_connector.retrieve_knowledge(
+                self.external_kb_entity.plugin_author,
+                self.external_kb_entity.plugin_name,
+                self.external_kb_entity.retriever_name,
+                self.retriever_instance_id,
+                {'query': query},
+            )
+
+            # Convert plugin results to RetrievalResultEntry
+            retrieval_entries = []
+            for result in results:
+                retrieval_entries.append(rag_context.RetrievalResultEntry(**result))
+
+            return retrieval_entries
+        except Exception as e:
+            self.ap.logger.error(f'Plugin retriever error: {e}')
+            import traceback
+
+            traceback.print_exc()
+            return []
+
+    def get_uuid(self) -> str:
+        """Get the UUID of the external knowledge base"""
+        return self.external_kb_entity.uuid
+
+    def get_name(self) -> str:
+        """Get the name of the external knowledge base"""
+        return self.external_kb_entity.name
+
+    def get_type(self) -> str:
+        """Get the type of knowledge base"""
+        return 'external'
+
+    async def dispose(self):
+        """Clean up resources"""
+        # Trigger sync to immediately delete the instance from plugin process
+        # This ensures instance is cleaned up without waiting for next LangBot restart
+        try:
+            await self.ap.plugin_connector.sync_polymorphic_component_instances()
+            self.ap.logger.info(
+                f'Disposed external KB {self.external_kb_entity.uuid}, triggered sync to delete instance'
+            )
+        except Exception as e:
+            self.ap.logger.error(f'Failed to sync after disposing KB: {e}')

src/langbot/pkg/rag/knowledge/kbmgr.py

@@ -1,19 +1,18 @@
 from __future__ import annotations
-import mimetypes
-import os.path
 import traceback
 import uuid
 import zipfile
 import io
-from typing import Any
+from .services import parser, chunker
 from langbot.pkg.core import app
+from langbot.pkg.rag.knowledge.services.embedder import Embedder
+from langbot.pkg.rag.knowledge.services.retriever import Retriever
 import sqlalchemy
-
-
 from langbot.pkg.entity.persistence import rag as persistence_rag
 from langbot.pkg.core import taskmgr
 from langbot_plugin.api.entities.builtin.rag import context as rag_context
 from .base import KnowledgeBaseInterface
+from .external import ExternalKnowledgeBase
 
 
 class RuntimeKnowledgeBase(KnowledgeBaseInterface):
@@ -21,16 +20,28 @@ class RuntimeKnowledgeBase(KnowledgeBaseInterface):
 
     knowledge_base_entity: persistence_rag.KnowledgeBase
 
+    parser: parser.FileParser
+
+    chunker: chunker.Chunker
+
+    embedder: Embedder
+
+    retriever: Retriever
+
     def __init__(self, ap: app.Application, knowledge_base_entity: persistence_rag.KnowledgeBase):
         super().__init__(ap)
         self.knowledge_base_entity = knowledge_base_entity
+        self.parser = parser.FileParser(ap=self.ap)
+        self.chunker = chunker.Chunker(ap=self.ap)
+        self.embedder = Embedder(ap=self.ap)
+        self.retriever = Retriever(ap=self.ap)
+        # 传递kb_id给retriever
+        self.retriever.kb_id = knowledge_base_entity.uuid
 
     async def initialize(self):
         pass
 
-    async def _store_file_task(
-        self, file: persistence_rag.File, task_context: taskmgr.TaskContext, parser_plugin_id: str | None = None
-    ):
+    async def _store_file_task(self, file: persistence_rag.File, task_context: taskmgr.TaskContext):
         try:
             # set file status to processing
             await self.ap.persistence_mgr.execute_async(
@@ -39,45 +50,30 @@ class RuntimeKnowledgeBase(KnowledgeBaseInterface):
                 .values(status='processing')
             )
 
-            task_context.set_current_action('Processing file')
+            task_context.set_current_action('Parsing file')
+            # parse file
+            text = await self.parser.parse(file.file_name, file.extension)
+            if not text:
+                raise Exception(f'No text extracted from file {file.file_name}')
 
-            # Get file size from storage
-            file_size = await self.ap.storage_mgr.storage_provider.size(file.file_name)
+            task_context.set_current_action('Chunking file')
+            # chunk file
+            chunks_texts = await self.chunker.chunk(text)
+            if not chunks_texts:
+                raise Exception(f'No chunks extracted from file {file.file_name}')
 
-            # Detect MIME type from extension
-            mime_type, _ = mimetypes.guess_type(file.file_name)
-            if mime_type is None:
-                mime_type = 'application/octet-stream'
+            task_context.set_current_action('Embedding chunks')
 
-            # If a parser plugin is specified, call it before ingestion
-            parsed_content = None
-            if parser_plugin_id:
-                task_context.set_current_action('Parsing file')
-                file_bytes = await self.ap.storage_mgr.storage_provider.load(file.file_name)
-                parse_context = {
-                    'mime_type': mime_type,
-                    'filename': file.file_name,
-                    'metadata': {},
-                }
-                parsed_content = await self.ap.plugin_connector.call_parser(parser_plugin_id, parse_context, file_bytes)
-
-            # Call plugin to ingest document
-            result = await self._ingest_document(
-                {
-                    'document_id': file.uuid,
-                    'filename': file.file_name,
-                    'extension': file.extension,
-                    'file_size': file_size,
-                    'mime_type': mime_type,
-                },
-                file.file_name,  # storage path
-                parsed_content=parsed_content,
+            embedding_model = await self.ap.model_mgr.get_embedding_model_by_uuid(
+                self.knowledge_base_entity.embedding_model_uuid
+            )
+            # embed chunks
+            await self.embedder.embed_and_store(
+                kb_id=self.knowledge_base_entity.uuid,
+                file_id=file.uuid,
+                chunks=chunks_texts,
+                embedding_model=embedding_model,
             )
-
-            # Check plugin result status
-            if result.get('status') == 'failed':
-                error_msg = result.get('error_message', 'Plugin ingestion returned failed status')
-                raise Exception(error_msg)
 
             # set file status to completed
             await self.ap.persistence_mgr.execute_async(
@@ -101,17 +97,16 @@ class RuntimeKnowledgeBase(KnowledgeBaseInterface):
             # delete file from storage
             await self.ap.storage_mgr.storage_provider.delete(file.file_name)
 
-    async def store_file(self, file_id: str, parser_plugin_id: str | None = None) -> str:
+    async def store_file(self, file_id: str) -> str:
         # pre checking
         if not await self.ap.storage_mgr.storage_provider.exists(file_id):
             raise Exception(f'File {file_id} not found')
 
         file_name = file_id
-        _, ext = os.path.splitext(file_name)
-        extension = ext.lstrip('.').lower() if ext else ''
+        extension = file_name.split('.')[-1].lower()
 
         if extension == 'zip':
-            return await self._store_zip_file(file_id, parser_plugin_id=parser_plugin_id)
+            return await self._store_zip_file(file_id)
 
         file_uuid = str(uuid.uuid4())
         kb_id = self.knowledge_base_entity.uuid
@@ -131,7 +126,7 @@ class RuntimeKnowledgeBase(KnowledgeBaseInterface):
         # run background task asynchronously
         ctx = taskmgr.TaskContext.new()
         wrapper = self.ap.task_mgr.create_user_task(
-            self._store_file_task(file_obj, task_context=ctx, parser_plugin_id=parser_plugin_id),
+            self._store_file_task(file_obj, task_context=ctx),
             kind='knowledge-operation',
             name=f'knowledge-store-file-{file_id}',
             label=f'Store file {file_id}',
@@ -139,7 +134,7 @@ class RuntimeKnowledgeBase(KnowledgeBaseInterface):
         )
         return wrapper.id
 
-    async def _store_zip_file(self, zip_file_id: str, parser_plugin_id: str | None = None) -> str:
+    async def _store_zip_file(self, zip_file_id: str) -> str:
         """Handle ZIP file by extracting each document and storing them separately."""
         self.ap.logger.info(f'Processing ZIP file: {zip_file_id}')
 
@@ -155,8 +150,7 @@ class RuntimeKnowledgeBase(KnowledgeBaseInterface):
                 if file_info.is_dir() or file_info.filename.startswith('.'):
                     continue
 
-                _, file_ext = os.path.splitext(file_info.filename)
-                file_extension = file_ext.lstrip('.').lower()
+                file_extension = file_info.filename.split('.')[-1].lower()
                 if file_extension not in supported_extensions:
                     self.ap.logger.debug(f'Skipping unsupported file in ZIP: {file_info.filename}')
                     continue
@@ -165,18 +159,18 @@ class RuntimeKnowledgeBase(KnowledgeBaseInterface):
                     file_content = zip_ref.read(file_info.filename)
 
                     base_name = file_info.filename.replace('/', '_').replace('\\', '_')
-                    file_stem, file_ext = os.path.splitext(base_name)
-                    extension = file_ext.lstrip('.')
+                    extension = base_name.split('.')[-1]
+                    file_name = base_name.split('.')[0]
 
-                    if file_stem.startswith('__MACOSX'):
+                    if file_name.startswith('__MACOSX'):
                         continue
 
-                    extracted_file_id = file_stem + '_' + str(uuid.uuid4())[:8] + '.' + extension
+                    extracted_file_id = file_name + '_' + str(uuid.uuid4())[:8] + '.' + extension
                     # save file to storage
 
                     await self.ap.storage_mgr.storage_provider.save(extracted_file_id, file_content)
 
-                    task_id = await self.store_file(extracted_file_id, parser_plugin_id=parser_plugin_id)
+                    task_id = await self.store_file(extracted_file_id)
                     stored_file_tasks.append(task_id)
 
                     self.ap.logger.info(
@@ -195,28 +189,21 @@ class RuntimeKnowledgeBase(KnowledgeBaseInterface):
 
         return stored_file_tasks[0] if stored_file_tasks else ''
 
-    async def retrieve(self, query: str, settings: dict | None = None) -> list[rag_context.RetrievalResultEntry]:
-        # Merge stored retrieval_settings with per-request overrides
-        stored = self.knowledge_base_entity.retrieval_settings or {}
-        merged = {**stored, **(settings or {})}
-        if 'top_k' not in merged:
-            merged['top_k'] = 5  # fallback default
-
-        response = await self._retrieve(query, merged)
-
-        results_data = response.get('results', [])
-        entries = []
-        for r in results_data:
-            if isinstance(r, dict):
-                entries.append(rag_context.RetrievalResultEntry(**r))
-            elif isinstance(r, rag_context.RetrievalResultEntry):
-                entries.append(r)
-        return entries
+    async def retrieve(self, query: str, top_k: int) -> list[rag_context.RetrievalResultEntry]:
+        embedding_model = await self.ap.model_mgr.get_embedding_model_by_uuid(
+            self.knowledge_base_entity.embedding_model_uuid
+        )
+        return await self.retriever.retrieve(self.knowledge_base_entity.uuid, query, embedding_model, top_k)
 
     async def delete_file(self, file_id: str):
-        await self._delete_document(file_id)
+        # delete vector
+        await self.ap.vector_db_mgr.vector_db.delete_by_file_id(self.knowledge_base_entity.uuid, file_id)
+
+        # delete chunk
+        await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.delete(persistence_rag.Chunk).where(persistence_rag.Chunk.file_id == file_id)
+        )
 
-        # Also cleanup DB record
         await self.ap.persistence_mgr.execute_async(
             sqlalchemy.delete(persistence_rag.File).where(persistence_rag.File.uuid == file_id)
         )
@@ -229,295 +216,32 @@ class RuntimeKnowledgeBase(KnowledgeBaseInterface):
         """Get the name of the knowledge base"""
         return self.knowledge_base_entity.name
 
-    def get_knowledge_engine_plugin_id(self) -> str:
-        """Get the Knowledge Engine plugin ID"""
-        return self.knowledge_base_entity.knowledge_engine_plugin_id or ''
+    def get_type(self) -> str:
+        """Get the type of knowledge base"""
+        return 'internal'
 
     async def dispose(self):
-        """Dispose the knowledge base, notifying the plugin to cleanup."""
-        await self._on_kb_delete()
-
-    # ========== Plugin Communication Methods ==========
-
-    async def _on_kb_create(self) -> None:
-        """Notify plugin about KB creation."""
-        plugin_id = self.knowledge_base_entity.knowledge_engine_plugin_id
-        if not plugin_id:
-            return
-
-        try:
-            config = self.knowledge_base_entity.creation_settings or {}
-            self.ap.logger.info(
-                f'Calling RAG plugin {plugin_id}: on_knowledge_base_create(kb_id={self.knowledge_base_entity.uuid})'
-            )
-            await self.ap.plugin_connector.rag_on_kb_create(plugin_id, self.knowledge_base_entity.uuid, config)
-        except Exception as e:
-            self.ap.logger.error(f'Failed to notify plugin {plugin_id} on KB create: {e}')
-            raise
-
-    async def _on_kb_delete(self) -> None:
-        """Notify plugin about KB deletion."""
-        plugin_id = self.knowledge_base_entity.knowledge_engine_plugin_id
-        if not plugin_id:
-            return
-
-        try:
-            self.ap.logger.info(
-                f'Calling RAG plugin {plugin_id}: on_knowledge_base_delete(kb_id={self.knowledge_base_entity.uuid})'
-            )
-            await self.ap.plugin_connector.rag_on_kb_delete(plugin_id, self.knowledge_base_entity.uuid)
-        except Exception as e:
-            self.ap.logger.error(f'Failed to notify plugin {plugin_id} on KB delete: {e}')
-
-    async def _ingest_document(
-        self,
-        file_metadata: dict[str, Any],
-        storage_path: str,
-        parsed_content: dict[str, Any] | None = None,
-    ) -> dict[str, Any]:
-        """Call plugin to ingest document."""
-        kb = self.knowledge_base_entity
-        plugin_id = kb.knowledge_engine_plugin_id
-        if not plugin_id:
-            self.ap.logger.error(f'No RAG plugin ID configured for KB {kb.uuid}. Ingestion failed.')
-            raise ValueError('RAG Plugin ID required')
-
-        self.ap.logger.info(f'Calling RAG plugin {plugin_id}: ingest(doc={file_metadata.get("filename")})')
-
-        # Inject knowledge_base_id into file metadata as required by SDK schema
-        file_metadata['knowledge_base_id'] = kb.uuid
-
-        context_data = {
-            'file_object': {
-                'metadata': file_metadata,
-                'storage_path': storage_path,
-            },
-            'knowledge_base_id': kb.uuid,
-            'collection_id': kb.collection_id or kb.uuid,
-            'creation_settings': kb.creation_settings or {},
-            'parsed_content': parsed_content,
-        }
-
-        try:
-            result = await self.ap.plugin_connector.call_rag_ingest(plugin_id, context_data)
-            return result
-        except Exception as e:
-            self.ap.logger.error(f'Plugin ingestion failed: {e}')
-            raise
-
-    async def _retrieve(
-        self,
-        query: str,
-        settings: dict[str, Any],
-    ) -> dict[str, Any]:
-        """Call plugin to retrieve documents.
-
-        Raises:
-            ValueError: If no RAG plugin is configured for this KB.
-            Exception: If the plugin retrieval call fails.
-        """
-        kb = self.knowledge_base_entity
-        plugin_id = kb.knowledge_engine_plugin_id
-        if not plugin_id:
-            raise ValueError(f'No RAG plugin ID configured for KB {kb.uuid}. Retrieval failed.')
-
-        # Session context (e.g. session_name) stays in retrieval_settings
-        # for plugins that need it. Do NOT move them into filters, as filters
-        # are passed directly to vector_search by some plugins (e.g. LangRAG)
-        # and would cause empty results when the metadata field doesn't exist.
-        filters = settings.pop('filters', {})
-
-        retrieval_context = {
-            'query': query,
-            'knowledge_base_id': kb.uuid,
-            'collection_id': kb.collection_id or kb.uuid,
-            'retrieval_settings': settings,
-            'creation_settings': kb.creation_settings or {},
-            'filters': filters,
-        }
-
-        result = await self.ap.plugin_connector.call_rag_retrieve(
-            plugin_id,
-            retrieval_context,
-        )
-        return result
-
-    async def _delete_document(self, document_id: str) -> bool:
-        """Call plugin to delete document."""
-        kb = self.knowledge_base_entity
-        plugin_id = kb.knowledge_engine_plugin_id
-        if not plugin_id:
-            return False
-
-        self.ap.logger.info(f'Calling RAG plugin {plugin_id}: delete_document(doc_id={document_id})')
-
-        try:
-            return await self.ap.plugin_connector.call_rag_delete_document(plugin_id, document_id, kb.uuid)
-        except Exception as e:
-            self.ap.logger.error(f'Plugin document deletion failed: {e}')
-            return False
+        await self.ap.vector_db_mgr.vector_db.delete_collection(self.knowledge_base_entity.uuid)
 
 
 class RAGManager:
     ap: app.Application
 
-    knowledge_bases: dict[str, KnowledgeBaseInterface]
+    knowledge_bases: list[KnowledgeBaseInterface]
 
     def __init__(self, ap: app.Application):
         self.ap = ap
-        self.knowledge_bases = {}
+        self.knowledge_bases = []
 
     async def initialize(self):
         await self.load_knowledge_bases_from_db()
 
-    async def get_all_knowledge_base_details(self) -> list[dict]:
-        """Get all knowledge bases with enriched Knowledge Engine details."""
-        # 1. Get raw KBs from DB
-        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_rag.KnowledgeBase))
-        knowledge_bases = result.all()
-
-        # 2. Get all available Knowledge Engines for enrichment
-        engine_map = {}
-        if self.ap.plugin_connector.is_enable_plugin:
-            try:
-                engines = await self.ap.plugin_connector.list_knowledge_engines()
-                engine_map = {e['plugin_id']: e for e in engines}
-            except Exception as e:
-                self.ap.logger.warning(f'Failed to list Knowledge Engines: {e}')
-
-        # 3. Serialize and enrich
-        kb_list = []
-        for kb in knowledge_bases:
-            kb_dict = self.ap.persistence_mgr.serialize_model(persistence_rag.KnowledgeBase, kb)
-            self._enrich_kb_dict(kb_dict, engine_map)
-            kb_list.append(kb_dict)
-
-        return kb_list
-
-    async def get_knowledge_base_details(self, kb_uuid: str) -> dict | None:
-        """Get specific knowledge base with enriched Knowledge Engine details."""
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_rag.KnowledgeBase).where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
-        )
-        kb = result.first()
-        if not kb:
-            return None
-
-        kb_dict = self.ap.persistence_mgr.serialize_model(persistence_rag.KnowledgeBase, kb)
-
-        # Fetch engines
-        engine_map = {}
-        if self.ap.plugin_connector.is_enable_plugin:
-            try:
-                engines = await self.ap.plugin_connector.list_knowledge_engines()
-                engine_map = {e['plugin_id']: e for e in engines}
-            except Exception as e:
-                self.ap.logger.warning(f'Failed to list Knowledge Engines: {e}')
-
-        self._enrich_kb_dict(kb_dict, engine_map)
-        return kb_dict
-
-    @staticmethod
-    def _to_i18n_name(name) -> dict:
-        """Ensure name is always an I18nObject-compatible dict.
-
-        If *name* is already a dict (with ``en_US`` / ``zh_Hans`` keys) it is
-        returned as-is.  A plain string is wrapped into an I18nObject so the
-        frontend ``extractI18nObject`` helper never receives an unexpected type.
-        """
-        if isinstance(name, dict):
-            return name
-        return {'en_US': str(name), 'zh_Hans': str(name)}
-
-    def _enrich_kb_dict(self, kb_dict: dict, engine_map: dict) -> None:
-        """Helper to inject engine info into KB dict."""
-        plugin_id = kb_dict.get('knowledge_engine_plugin_id')
-
-        # Default fallback structure — name must be I18nObject for frontend compatibility
-        fallback_name = self._to_i18n_name(plugin_id or 'Internal (Legacy)')
-        fallback_info = {
-            'plugin_id': plugin_id,
-            'name': fallback_name,
-            'capabilities': [],
-        }
-
-        if not plugin_id:
-            kb_dict['knowledge_engine'] = fallback_info
-            return
-
-        engine_info = engine_map.get(plugin_id)
-        if engine_info:
-            kb_dict['knowledge_engine'] = {
-                'plugin_id': plugin_id,
-                'name': self._to_i18n_name(engine_info.get('name', plugin_id)),
-                'capabilities': engine_info.get('capabilities', []),
-            }
-        else:
-            kb_dict['knowledge_engine'] = fallback_info
-
-    async def create_knowledge_base(
-        self,
-        name: str,
-        knowledge_engine_plugin_id: str,
-        creation_settings: dict,
-        retrieval_settings: dict | None = None,
-        description: str = '',
-    ) -> persistence_rag.KnowledgeBase:
-        """Create a new knowledge base using a RAG plugin."""
-        # Validate that the Knowledge Engine plugin exists
-        if self.ap.plugin_connector.is_enable_plugin:
-            try:
-                engines = await self.ap.plugin_connector.list_knowledge_engines()
-                engine_ids = [e.get('plugin_id') for e in engines]
-                if knowledge_engine_plugin_id not in engine_ids:
-                    raise ValueError(f'Knowledge Engine plugin {knowledge_engine_plugin_id} not found')
-            except ValueError:
-                raise
-            except Exception as e:
-                self.ap.logger.warning(f'Failed to validate Knowledge Engine plugin existence: {e}')
-
-        kb_uuid = str(uuid.uuid4())
-        # Use UUID as collection ID by default for isolation
-        collection_id = kb_uuid
-
-        kb_data = {
-            'uuid': kb_uuid,
-            'name': name,
-            'description': description,
-            'knowledge_engine_plugin_id': knowledge_engine_plugin_id,
-            'collection_id': collection_id,
-            'creation_settings': creation_settings,
-            'retrieval_settings': retrieval_settings or {},
-        }
-
-        # Create Entity
-        kb = persistence_rag.KnowledgeBase(**kb_data)
-
-        # Persist
-        await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_rag.KnowledgeBase).values(kb_data))
-
-        # Load into Runtime
-        runtime_kb = await self.load_knowledge_base(kb)
-
-        # Notify Plugin — rollback DB record and runtime entry on failure
-        try:
-            await runtime_kb._on_kb_create()
-        except Exception:
-            self.knowledge_bases.pop(kb_uuid, None)
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.delete(persistence_rag.KnowledgeBase).where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
-            )
-            raise
-
-        self.ap.logger.info(f'Created new Knowledge Base {name} ({kb_uuid}) using plugin {knowledge_engine_plugin_id}')
-        return kb
-
     async def load_knowledge_bases_from_db(self):
         self.ap.logger.info('Loading knowledge bases from db...')
 
-        self.knowledge_bases = {}
+        self.knowledge_bases = []
 
-        # Load knowledge bases
+        # Load internal knowledge bases
         result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_rag.KnowledgeBase))
         knowledge_bases = result.all()
 
@@ -529,37 +253,86 @@ class RAGManager:
                     f'Error loading knowledge base {knowledge_base.uuid}: {e}\n{traceback.format_exc()}'
                 )
 
+        # Load external knowledge bases
+        external_result = await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.select(persistence_rag.ExternalKnowledgeBase)
+        )
+        external_kbs = external_result.all()
+
+        for external_kb in external_kbs:
+            try:
+                # Don't trigger sync during batch loading - will sync once after LangBot connects to runtime
+                await self.load_external_knowledge_base(external_kb, trigger_sync=False)
+            except Exception as e:
+                self.ap.logger.error(
+                    f'Error loading external knowledge base {external_kb.uuid}: {e}\n{traceback.format_exc()}'
+                )
+
     async def load_knowledge_base(
         self,
         knowledge_base_entity: persistence_rag.KnowledgeBase | sqlalchemy.Row | dict,
     ) -> RuntimeKnowledgeBase:
         if isinstance(knowledge_base_entity, sqlalchemy.Row):
-            # Safe access to _mapping for SQLAlchemy 1.4+
             knowledge_base_entity = persistence_rag.KnowledgeBase(**knowledge_base_entity._mapping)
         elif isinstance(knowledge_base_entity, dict):
-            # Filter out non-database fields (like knowledge_engine which is computed)
-            filtered_dict = {
-                k: v for k, v in knowledge_base_entity.items() if k in persistence_rag.KnowledgeBase.ALL_DB_FIELDS
-            }
-            knowledge_base_entity = persistence_rag.KnowledgeBase(**filtered_dict)
+            knowledge_base_entity = persistence_rag.KnowledgeBase(**knowledge_base_entity)
 
         runtime_knowledge_base = RuntimeKnowledgeBase(ap=self.ap, knowledge_base_entity=knowledge_base_entity)
 
         await runtime_knowledge_base.initialize()
 
-        self.knowledge_bases[runtime_knowledge_base.get_uuid()] = runtime_knowledge_base
+        self.knowledge_bases.append(runtime_knowledge_base)
 
         return runtime_knowledge_base
 
+    async def load_external_knowledge_base(
+        self,
+        external_kb_entity: persistence_rag.ExternalKnowledgeBase | sqlalchemy.Row | dict,
+        trigger_sync: bool = True,
+    ) -> ExternalKnowledgeBase:
+        """Load external knowledge base into runtime
+
+        Args:
+            external_kb_entity: External KB entity to load
+            trigger_sync: Whether to trigger sync after loading (default True for manual creation, False for batch loading)
+        """
+        if isinstance(external_kb_entity, sqlalchemy.Row):
+            external_kb_entity = persistence_rag.ExternalKnowledgeBase(**external_kb_entity._mapping)
+        elif isinstance(external_kb_entity, dict):
+            external_kb_entity = persistence_rag.ExternalKnowledgeBase(**external_kb_entity)
+
+        external_kb = ExternalKnowledgeBase(ap=self.ap, external_kb_entity=external_kb_entity)
+
+        await external_kb.initialize()
+
+        self.knowledge_bases.append(external_kb)
+
+        # Trigger sync to create the instance immediately (for manual creation)
+        # Skip sync during batch loading from DB to avoid multiple sync calls
+        if trigger_sync:
+            try:
+                await self.ap.plugin_connector.sync_polymorphic_component_instances()
+                self.ap.logger.info(f'Triggered sync after loading external KB {external_kb_entity.uuid}')
+            except Exception as e:
+                self.ap.logger.error(f'Failed to sync after loading external KB: {e}')
+
+        return external_kb
+
     async def get_knowledge_base_by_uuid(self, kb_uuid: str) -> KnowledgeBaseInterface | None:
-        return self.knowledge_bases.get(kb_uuid)
+        for kb in self.knowledge_bases:
+            if kb.get_uuid() == kb_uuid:
+                return kb
+        return None
 
     async def remove_knowledge_base_from_runtime(self, kb_uuid: str):
-        self.knowledge_bases.pop(kb_uuid, None)
+        for kb in self.knowledge_bases:
+            if kb.get_uuid() == kb_uuid:
+                self.knowledge_bases.remove(kb)
+                return
 
     async def delete_knowledge_base(self, kb_uuid: str):
-        kb = self.knowledge_bases.pop(kb_uuid, None)
-        if kb is not None:
-            await kb.dispose()
-        else:
-            self.ap.logger.warning(f'Knowledge base {kb_uuid} not found in runtime, skipping plugin notification')
+        for kb in self.knowledge_bases:
+            if kb.get_uuid() == kb_uuid:
+                await kb.dispose()
+                self.knowledge_bases.remove(kb)
+                return

src/langbot/pkg/rag/knowledge/services/base_service.py

@@ -0,0 +1,15 @@
+# 封装异步操作
+import asyncio
+
+
+class BaseService:
+    def __init__(self):
+        pass
+
+    async def _run_sync(self, func, *args, **kwargs):
+        """
+        在单独的线程中运行同步函数。
+        如果第一个参数是 session，则在 to_thread 中获取新的 session。
+        """
+
+        return await asyncio.to_thread(func, *args, **kwargs)

src/langbot/pkg/rag/knowledge/services/chunker.py

@@ -0,0 +1,49 @@
+from __future__ import annotations
+
+import json
+from typing import List
+from langbot.pkg.rag.knowledge.services import base_service
+from langbot.pkg.core import app
+from langchain_text_splitters import RecursiveCharacterTextSplitter
+
+
+class Chunker(base_service.BaseService):
+    """
+    A class for splitting long texts into smaller, overlapping chunks.
+    """
+
+    def __init__(self, ap: app.Application, chunk_size: int = 500, chunk_overlap: int = 50):
+        self.ap = ap
+        self.chunk_size = chunk_size
+        self.chunk_overlap = chunk_overlap
+        if self.chunk_overlap >= self.chunk_size:
+            self.ap.logger.warning(
+                'Chunk overlap is greater than or equal to chunk size. This may lead to empty or malformed chunks.'
+            )
+
+    def _split_text_sync(self, text: str) -> List[str]:
+        """
+        Synchronously splits a long text into chunks with specified overlap.
+        This is a CPU-bound operation, intended to be run in a separate thread.
+        """
+        if not text:
+            return []
+
+        text_splitter = RecursiveCharacterTextSplitter(
+            chunk_size=self.chunk_size,
+            chunk_overlap=self.chunk_overlap,
+            length_function=len,
+            is_separator_regex=False,
+        )
+        return text_splitter.split_text(text)
+
+    async def chunk(self, text: str) -> List[str]:
+        """
+        Asynchronously chunks a given text into smaller pieces.
+        """
+        self.ap.logger.info(f'Chunking text (length: {len(text)})...')
+        # Run the synchronous splitting logic in a separate thread
+        chunks = await self._run_sync(self._split_text_sync, text)
+        self.ap.logger.info(f'Text chunked into {len(chunks)} pieces.')
+        self.ap.logger.debug(f'Chunks: {json.dumps(chunks, indent=4, ensure_ascii=False)}')
+        return chunks

src/langbot/pkg/rag/knowledge/services/embedder.py

@@ -0,0 +1,55 @@
+from __future__ import annotations
+import uuid
+from typing import List
+from langbot.pkg.rag.knowledge.services.base_service import BaseService
+from langbot.pkg.entity.persistence import rag as persistence_rag
+from langbot.pkg.core import app
+from langbot.pkg.provider.modelmgr.requester import RuntimeEmbeddingModel
+import sqlalchemy
+
+
+class Embedder(BaseService):
+    def __init__(self, ap: app.Application) -> None:
+        super().__init__()
+        self.ap = ap
+
+    async def embed_and_store(
+        self, kb_id: str, file_id: str, chunks: List[str], embedding_model: RuntimeEmbeddingModel
+    ) -> list[persistence_rag.Chunk]:
+        # save chunk to db
+        chunk_entities: list[persistence_rag.Chunk] = []
+        chunk_ids: list[str] = []
+
+        for chunk_text in chunks:
+            chunk_uuid = str(uuid.uuid4())
+            chunk_ids.append(chunk_uuid)
+            chunk_entity = persistence_rag.Chunk(uuid=chunk_uuid, file_id=file_id, text=chunk_text)
+            chunk_entities.append(chunk_entity)
+
+        chunk_dicts = [
+            self.ap.persistence_mgr.serialize_model(persistence_rag.Chunk, chunk) for chunk in chunk_entities
+        ]
+
+        await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_rag.Chunk).values(chunk_dicts))
+
+        # get embeddings (batch size limit: 64 for OpenAI)
+        MAX_BATCH_SIZE = 64
+        embeddings_list: list[list[float]] = []
+
+        for i in range(0, len(chunks), MAX_BATCH_SIZE):
+            batch = chunks[i : i + MAX_BATCH_SIZE]
+            batch_embeddings = await embedding_model.provider.invoke_embedding(
+                model=embedding_model,
+                input_text=batch,
+                extra_args={},  # TODO: add extra args
+                knowledge_base_id=kb_id,
+                call_type='embedding',
+            )
+            embeddings_list.extend(batch_embeddings)
+
+        # save embeddings to vdb
+        await self.ap.vector_db_mgr.vector_db.add_embeddings(kb_id, chunk_ids, embeddings_list, chunk_dicts)
+
+        self.ap.logger.info(f'Successfully saved {len(chunk_entities)} embeddings to Knowledge Base.')
+
+        return chunk_entities

src/langbot/pkg/rag/knowledge/services/parser.py

@@ -0,0 +1,291 @@
+from __future__ import annotations
+
+import PyPDF2
+import io
+from docx import Document
+import chardet
+from typing import Union, Callable, Any
+import markdown
+from bs4 import BeautifulSoup
+import re
+import asyncio  # Import asyncio for async operations
+from langbot.pkg.core import app
+
+
+class FileParser:
+    """
+    A robust file parser class to extract text content from various document formats.
+    It supports TXT, PDF, DOCX, XLSX, CSV, Markdown, HTML, and EPUB files.
+    All core file reading operations are designed to be run synchronously in a thread pool
+    to avoid blocking the asyncio event loop.
+    """
+
+    def __init__(self, ap: app.Application):
+        self.ap = ap
+
+    async def _run_sync(self, sync_func: Callable, *args: Any, **kwargs: Any) -> Any:
+        """
+        Runs a synchronous function in a separate thread to prevent blocking the event loop.
+        This is a general utility method for wrapping blocking I/O operations.
+        """
+        try:
+            return await asyncio.to_thread(sync_func, *args, **kwargs)
+        except Exception as e:
+            self.ap.logger.error(f'Error running synchronous function {sync_func.__name__}: {e}')
+            raise
+
+    async def parse(self, file_name: str, extension: str) -> Union[str, None]:
+        """
+        Parses the file based on its extension and returns the extracted text content.
+        This is the main asynchronous entry point for parsing.
+
+        Args:
+            file_name (str): The name of the file to be parsed, get from ap.storage_mgr
+
+        Returns:
+            Union[str, None]: The extracted text content as a single string, or None if parsing fails.
+        """
+
+        file_extension = extension.lower()
+        parser_method = getattr(self, f'_parse_{file_extension}', None)
+
+        if parser_method is None:
+            self.ap.logger.error(f'Unsupported file format: {file_extension} for file {file_name}')
+            return None
+
+        try:
+            # Pass file_path to the specific parser methods
+            return await parser_method(file_name)
+        except Exception as e:
+            self.ap.logger.error(f'Failed to parse {file_extension} file {file_name}: {e}')
+            return None
+
+    # --- Helper for reading files with encoding detection ---
+    async def _read_file_content(self, file_name: str) -> Union[str, bytes]:
+        """
+        Reads a file with automatic encoding detection, ensuring the synchronous
+        file read operation runs in a separate thread.
+        """
+
+        # def _read_sync():
+        #     with open(file_path, 'rb') as file:
+        #         raw_data = file.read()
+        #         detected = chardet.detect(raw_data)
+        #         encoding = detected['encoding'] or 'utf-8'
+
+        #     if mode == 'r':
+        #         return raw_data.decode(encoding, errors='ignore')
+        #     return raw_data  # For binary mode
+
+        # return await self._run_sync(_read_sync)
+        file_bytes = await self.ap.storage_mgr.storage_provider.load(file_name)
+
+        detected = chardet.detect(file_bytes)
+        encoding = detected['encoding'] or 'utf-8'
+
+        return file_bytes.decode(encoding, errors='ignore')
+
+    # --- Specific Parser Methods ---
+
+    async def _parse_txt(self, file_name: str) -> str:
+        """Parses a TXT file and returns its content."""
+        self.ap.logger.info(f'Parsing TXT file: {file_name}')
+        return await self._read_file_content(file_name)
+
+    async def _parse_pdf(self, file_name: str) -> str:
+        """Parses a PDF file and returns its text content."""
+        self.ap.logger.info(f'Parsing PDF file: {file_name}')
+
+        # def _parse_pdf_sync():
+        #     text_content = []
+        #     with open(file_name, 'rb') as file:
+        #         pdf_reader = PyPDF2.PdfReader(file)
+        #         for page in pdf_reader.pages:
+        #             text = page.extract_text()
+        #             if text:
+        #                 text_content.append(text)
+        #     return '\n'.join(text_content)
+
+        # return await self._run_sync(_parse_pdf_sync)
+
+        pdf_bytes = await self.ap.storage_mgr.storage_provider.load(file_name)
+
+        def _parse_pdf_sync():
+            pdf_reader = PyPDF2.PdfReader(io.BytesIO(pdf_bytes))
+            text_content = []
+            for page in pdf_reader.pages:
+                text = page.extract_text()
+                if text:
+                    text_content.append(text)
+            return '\n'.join(text_content)
+
+        return await self._run_sync(_parse_pdf_sync)
+
+    async def _parse_docx(self, file_name: str) -> str:
+        """Parses a DOCX file and returns its text content."""
+        self.ap.logger.info(f'Parsing DOCX file: {file_name}')
+
+        docx_bytes = await self.ap.storage_mgr.storage_provider.load(file_name)
+
+        def _parse_docx_sync():
+            doc = Document(io.BytesIO(docx_bytes))
+            text_content = [paragraph.text for paragraph in doc.paragraphs if paragraph.text.strip()]
+            return '\n'.join(text_content)
+
+        return await self._run_sync(_parse_docx_sync)
+
+    async def _parse_doc(self, file_name: str) -> str:
+        """Handles .doc files, explicitly stating lack of direct support."""
+        self.ap.logger.warning(f'Direct .doc parsing is not supported for {file_name}. Please convert to .docx first.')
+        raise NotImplementedError('Direct .doc parsing not supported. Please convert to .docx first.')
+
+    # async def _parse_xlsx(self, file_name: str) -> str:
+    #     """Parses an XLSX file, returning text from all sheets."""
+    #     self.ap.logger.info(f'Parsing XLSX file: {file_name}')
+
+    #     xlsx_bytes = await self.ap.storage_mgr.storage_provider.load(file_name)
+
+    #     def _parse_xlsx_sync():
+    #         excel_file = pd.ExcelFile(io.BytesIO(xlsx_bytes))
+    #         all_sheet_content = []
+    #         for sheet_name in excel_file.sheet_names:
+    #             df = pd.read_excel(io.BytesIO(xlsx_bytes), sheet_name=sheet_name)
+    #             sheet_text = f'--- Sheet: {sheet_name} ---\n{df.to_string(index=False)}\n'
+    #             all_sheet_content.append(sheet_text)
+    #         return '\n'.join(all_sheet_content)
+
+    #     return await self._run_sync(_parse_xlsx_sync)
+
+    # async def _parse_csv(self, file_name: str) -> str:
+    #     """Parses a CSV file and returns its content as a string."""
+    #     self.ap.logger.info(f'Parsing CSV file: {file_name}')
+
+    #     csv_bytes = await self.ap.storage_mgr.storage_provider.load(file_name)
+
+    #     def _parse_csv_sync():
+    #         # pd.read_csv can often detect encoding, but explicit detection is safer
+    #         # raw_data = self._read_file_content(
+    #         #     file_name, mode='rb'
+    #         # )  # Note: this will need to be await outside this sync function
+    #         # _ = raw_data
+    #         # For simplicity, we'll let pandas handle encoding internally after a raw read.
+    #         # A more robust solution might pass encoding directly to pd.read_csv after detection.
+    #         detected = chardet.detect(io.BytesIO(csv_bytes))
+    #         encoding = detected['encoding'] or 'utf-8'
+    #         df = pd.read_csv(io.BytesIO(csv_bytes), encoding=encoding)
+    #         return df.to_string(index=False)
+
+    #     return await self._run_sync(_parse_csv_sync)
+
+    async def _parse_md(self, file_name: str) -> str:
+        """Parses a Markdown file, converting it to structured plain text."""
+        self.ap.logger.info(f'Parsing Markdown file: {file_name}')
+
+        md_bytes = await self.ap.storage_mgr.storage_provider.load(file_name)
+
+        def _parse_markdown_sync():
+            md_content = io.BytesIO(md_bytes).read().decode('utf-8', errors='ignore')
+            html_content = markdown.markdown(
+                md_content, extensions=['extra', 'codehilite', 'tables', 'toc', 'fenced_code']
+            )
+            soup = BeautifulSoup(html_content, 'html.parser')
+            text_parts = []
+            for element in soup.children:
+                if element.name in ['h1', 'h2', 'h3', 'h4', 'h5', 'h6']:
+                    level = int(element.name[1])
+                    text_parts.append('#' * level + ' ' + element.get_text().strip())
+                elif element.name == 'p':
+                    text = element.get_text().strip()
+                    if text:
+                        text_parts.append(text)
+                elif element.name in ['ul', 'ol']:
+                    for li in element.find_all('li'):
+                        text_parts.append(f'* {li.get_text().strip()}')
+                elif element.name == 'pre':
+                    code_block = element.get_text().strip()
+                    if code_block:
+                        text_parts.append(f'```\n{code_block}\n```')
+                elif element.name == 'table':
+                    table_str = self._extract_table_to_markdown_sync(element)  # Call sync helper
+                    if table_str:
+                        text_parts.append(table_str)
+                elif element.name:
+                    text = element.get_text(separator=' ', strip=True)
+                    if text:
+                        text_parts.append(text)
+            cleaned_text = re.sub(r'\n\s*\n', '\n\n', '\n'.join(text_parts))
+            return cleaned_text.strip()
+
+        return await self._run_sync(_parse_markdown_sync)
+
+    async def _parse_html(self, file_name: str) -> str:
+        """Parses an HTML file, extracting structured plain text."""
+        self.ap.logger.info(f'Parsing HTML file: {file_name}')
+
+        html_bytes = await self.ap.storage_mgr.storage_provider.load(file_name)
+
+        def _parse_html_sync():
+            html_content = io.BytesIO(html_bytes).read().decode('utf-8', errors='ignore')
+            soup = BeautifulSoup(html_content, 'html.parser')
+            for script_or_style in soup(['script', 'style']):
+                script_or_style.decompose()
+            text_parts = []
+            for element in soup.body.children if soup.body else soup.children:
+                if element.name in ['h1', 'h2', 'h3', 'h4', 'h5', 'h6']:
+                    level = int(element.name[1])
+                    text_parts.append('#' * level + ' ' + element.get_text().strip())
+                elif element.name == 'p':
+                    text = element.get_text().strip()
+                    if text:
+                        text_parts.append(text)
+                elif element.name in ['ul', 'ol']:
+                    for li in element.find_all('li'):
+                        text = li.get_text().strip()
+                        if text:
+                            text_parts.append(f'* {text}')
+                elif element.name == 'table':
+                    table_str = self._extract_table_to_markdown_sync(element)  # Call sync helper
+                    if table_str:
+                        text_parts.append(table_str)
+                elif element.name:
+                    text = element.get_text(separator=' ', strip=True)
+                    if text:
+                        text_parts.append(text)
+            cleaned_text = re.sub(r'\n\s*\n', '\n\n', '\n'.join(text_parts))
+            return cleaned_text.strip()
+
+        return await self._run_sync(_parse_html_sync)
+
+    def _add_toc_items_sync(self, toc_list: list, text_content: list, level: int):
+        """Recursively adds TOC items to text_content (synchronous helper)."""
+        indent = '  ' * level
+        for item in toc_list:
+            if isinstance(item, tuple):
+                chapter, subchapters = item
+                text_content.append(f'{indent}- {chapter.title}')
+                self._add_toc_items_sync(subchapters, text_content, level + 1)
+            else:
+                text_content.append(f'{indent}- {item.title}')
+
+    def _extract_table_to_markdown_sync(self, table_element: BeautifulSoup) -> str:
+        """Helper to convert a BeautifulSoup table element into a Markdown table string (synchronous)."""
+        headers = [th.get_text().strip() for th in table_element.find_all('th')]
+        rows = []
+        for tr in table_element.find_all('tr'):
+            cells = [td.get_text().strip() for td in tr.find_all('td')]
+            if cells:
+                rows.append(cells)
+
+        if not headers and not rows:
+            return ''
+
+        table_lines = []
+        if headers:
+            table_lines.append(' | '.join(headers))
+            table_lines.append(' | '.join(['---'] * len(headers)))
+
+        for row_cells in rows:
+            padded_cells = row_cells + [''] * (len(headers) - len(row_cells)) if headers else row_cells
+            table_lines.append(' | '.join(padded_cells))
+
+        return '\n'.join(table_lines)

src/langbot/pkg/rag/knowledge/services/retriever.py

@@ -0,0 +1,53 @@
+from __future__ import annotations
+
+from . import base_service
+from ....core import app
+from ....provider.modelmgr.requester import RuntimeEmbeddingModel
+from langbot_plugin.api.entities.builtin.rag import context as rag_context
+from langbot_plugin.api.entities.builtin.provider.message import ContentElement
+
+
+class Retriever(base_service.BaseService):
+    def __init__(self, ap: app.Application):
+        super().__init__()
+        self.ap = ap
+
+    async def retrieve(
+        self, kb_id: str, query: str, embedding_model: RuntimeEmbeddingModel, k: int = 5
+    ) -> list[rag_context.RetrievalResultEntry]:
+        self.ap.logger.info(
+            f"Retrieving for query: '{query[:10]}' with k={k} using {embedding_model.model_entity.uuid}"
+        )
+
+        query_embedding: list[float] = await embedding_model.provider.invoke_embedding(
+            model=embedding_model,
+            input_text=[query],
+            extra_args={},  # TODO: add extra args
+            knowledge_base_id=kb_id,
+            query_text=query,
+            call_type='retrieve',
+        )
+
+        vector_results = await self.ap.vector_db_mgr.vector_db.search(kb_id, query_embedding[0], k)
+
+        # 'ids' shape mirrors the Chroma-style response contract for compatibility
+        matched_vector_ids = vector_results.get('ids', [[]])[0]
+        distances = vector_results.get('distances', [[]])[0]
+        vector_metadatas = vector_results.get('metadatas', [[]])[0]
+
+        if not matched_vector_ids:
+            self.ap.logger.info('No relevant chunks found in vector database.')
+            return []
+
+        result: list[rag_context.RetrievalResultEntry] = []
+
+        for i, id in enumerate(matched_vector_ids):
+            entry = rag_context.RetrievalResultEntry(
+                id=id,
+                content=[ContentElement.from_text(vector_metadatas[i].get('text', ''))],
+                metadata=vector_metadatas[i],
+                distance=distances[i],
+            )
+            result.append(entry)
+
+        return result

src/langbot/pkg/rag/service/__init__.py

@@ -1 +0,0 @@
-from .runtime import RAGRuntimeService as RAGRuntimeService

src/langbot/pkg/rag/service/runtime.py

@@ -1,116 +0,0 @@
-from __future__ import annotations
-
-import posixpath
-from typing import Any
-from langbot.pkg.core import app
-
-
-class RAGRuntimeService:
-    """Service to handle RAG-related requests from plugins (Runtime).
-
-    This service acts as the bridge between plugin RPC requests and
-    LangBot's infrastructure (embedding models, vector databases, file storage).
-    """
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-
-    async def vector_upsert(
-        self,
-        collection_id: str,
-        vectors: list[list[float]],
-        ids: list[str],
-        metadata: list[dict[str, Any]] | None = None,
-        documents: list[str] | None = None,
-    ) -> None:
-        """Handle VECTOR_UPSERT action."""
-        metadatas = metadata if metadata else [{} for _ in vectors]
-        await self.ap.vector_db_mgr.upsert(
-            collection_name=collection_id,
-            vectors=vectors,
-            ids=ids,
-            metadata=metadatas,
-            documents=documents,
-        )
-
-    async def vector_search(
-        self,
-        collection_id: str,
-        query_vector: list[float],
-        top_k: int,
-        filters: dict[str, Any] | None = None,
-        search_type: str = 'vector',
-        query_text: str = '',
-        vector_weight: float | None = None,
-    ) -> list[dict[str, Any]]:
-        """Handle VECTOR_SEARCH action."""
-        return await self.ap.vector_db_mgr.search(
-            collection_name=collection_id,
-            query_vector=query_vector,
-            limit=top_k,
-            filter=filters,
-            search_type=search_type,
-            query_text=query_text,
-            vector_weight=vector_weight,
-        )
-
-    async def vector_delete(
-        self, collection_id: str, file_ids: list[str] | None = None, filters: dict[str, Any] | None = None
-    ) -> int:
-        """Handle VECTOR_DELETE action.
-
-        Deletes vectors associated with the given file IDs from the collection.
-        Each file_id corresponds to a document whose vectors will be removed.
-
-        Args:
-            collection_id: The collection to delete from.
-            file_ids: File IDs whose associated vectors should be deleted.
-                Each file_id maps to a set of vectors stored with that file_id
-                in their metadata.
-            filters: Filter-based deletion (not yet supported, will raise).
-        """
-        count = 0
-        if file_ids:
-            await self.ap.vector_db_mgr.delete_by_file_id(collection_name=collection_id, file_ids=file_ids)
-            count = len(file_ids)
-        elif filters:
-            count = await self.ap.vector_db_mgr.delete_by_filter(collection_name=collection_id, filter=filters)
-        return count
-
-    async def vector_list(
-        self,
-        collection_id: str,
-        filters: dict[str, Any] | None = None,
-        limit: int = 20,
-        offset: int = 0,
-    ) -> tuple[list[dict[str, Any]], int]:
-        """Handle VECTOR_LIST action.
-
-        Args:
-            collection_id: The collection to list from.
-            filters: Optional metadata filters.
-            limit: Maximum number of items to return.
-            offset: Number of items to skip.
-
-        Returns:
-            Tuple of (items, total).
-        """
-        return await self.ap.vector_db_mgr.list_by_filter(
-            collection_name=collection_id,
-            filter=filters,
-            limit=limit,
-            offset=offset,
-        )
-
-    async def get_file_stream(self, storage_path: str) -> bytes:
-        """Handle GET_KNOWLEDEGE_FILE_STREAM action.
-
-        Uses the storage manager abstraction to load file content,
-        regardless of the underlying storage provider.
-        """
-        # Validate storage_path to prevent path traversal
-        normalized = posixpath.normpath(storage_path)
-        if normalized.startswith('/') or '..' in normalized.split('/'):
-            raise ValueError('Invalid storage path')
-        content_bytes = await self.ap.storage_mgr.storage_provider.load(normalized)
-        return content_bytes if content_bytes else b''

src/langbot/pkg/storage/mgr.py

@@ -3,7 +3,7 @@ from __future__ import annotations
 
 from ..core import app
 from . import provider
-from .providers import localstorage
+from .providers import localstorage, s3storage
 
 
 class StorageMgr:
@@ -21,8 +21,6 @@ class StorageMgr:
         storage_type = storage_config.get('use', 'local')
 
         if storage_type == 's3':
-            from .providers import s3storage
-
             self.storage_provider = s3storage.S3StorageProvider(self.ap)
             self.ap.logger.info('Initialized S3 storage backend.')
         else:

src/langbot/pkg/storage/provider.py

@@ -43,13 +43,6 @@ class StorageProvider(abc.ABC):
     ):
         pass
 
-    @abc.abstractmethod
-    async def size(
-        self,
-        key: str,
-    ) -> int:
-        pass
-
     @abc.abstractmethod
     async def delete_dir_recursive(
         self,

src/langbot/pkg/storage/providers/localstorage.py

@@ -47,12 +47,6 @@ class LocalStorageProvider(provider.StorageProvider):
     ):
         os.remove(os.path.join(LOCAL_STORAGE_PATH, f'{key}'))
 
-    async def size(
-        self,
-        key: str,
-    ) -> int:
-        return os.path.getsize(os.path.join(LOCAL_STORAGE_PATH, f'{key}'))
-
     async def delete_dir_recursive(
         self,
         dir_path: str,

src/langbot/pkg/storage/providers/s3storage.py

@@ -117,21 +117,6 @@ class S3StorageProvider(provider.StorageProvider):
             self.ap.logger.error(f'Failed to delete from S3: {e}')
             raise
 
-    async def size(
-        self,
-        key: str,
-    ) -> int:
-        """Get object size from S3 without downloading it"""
-        try:
-            response = self.s3_client.head_object(
-                Bucket=self.bucket_name,
-                Key=key,
-            )
-            return response['ContentLength']
-        except Exception as e:
-            self.ap.logger.error(f'Failed to get size from S3: {e}')
-            raise
-
     async def delete_dir_recursive(
         self,
         dir_path: str,

src/langbot/pkg/survey/__init__.py

@@ -1 +0,0 @@
-"""Survey module for in-product surveys triggered by events."""

src/langbot/pkg/survey/manager.py

@@ -1,148 +0,0 @@
-"""Survey manager: tracks events, communicates with Space to fetch/submit surveys."""
-
-from __future__ import annotations
-
-import asyncio
-import json
-import typing
-import httpx
-import sqlalchemy
-
-from ..core import app as core_app
-from ..entity.persistence.metadata import Metadata
-from ..utils import constants
-
-SURVEY_TRIGGERED_KEY = 'survey_triggered_events'
-
-
-class SurveyManager:
-    """Manages survey lifecycle: event tracking, pending survey fetch, submission."""
-
-    def __init__(self, ap: core_app.Application):
-        self.ap = ap
-        self._triggered_events: set[str] = set()
-        self._pending_survey: typing.Optional[dict] = None
-        self._space_url: str = ''
-
-    async def initialize(self):
-        space_config = self.ap.instance_config.data.get('space', {})
-        self._space_url = space_config.get('url', '').rstrip('/')
-        await self._load_triggered_events()
-
-    async def _load_triggered_events(self):
-        """Load previously triggered events from metadata table."""
-        try:
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.select(Metadata).where(Metadata.key == SURVEY_TRIGGERED_KEY)
-            )
-            row = result.first()
-            if row:
-                self._triggered_events = set(json.loads(row[0].value))
-        except Exception:
-            self._triggered_events = set()
-
-    async def _save_triggered_events(self):
-        """Persist triggered events to metadata table."""
-        try:
-            value = json.dumps(list(self._triggered_events))
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.select(Metadata).where(Metadata.key == SURVEY_TRIGGERED_KEY)
-            )
-            if result.first():
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.update(Metadata).where(Metadata.key == SURVEY_TRIGGERED_KEY).values(value=value)
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.insert(Metadata).values(key=SURVEY_TRIGGERED_KEY, value=value)
-                )
-        except Exception as e:
-            self.ap.logger.debug(f'Failed to save survey triggered events: {e}')
-
-    def _is_space_configured(self) -> bool:
-        space_config = self.ap.instance_config.data.get('space', {})
-        if space_config.get('disable_telemetry', False):
-            return False
-        return bool(self._space_url)
-
-    async def trigger_event(self, event: str):
-        """Called when an event occurs. Checks Space for a pending survey."""
-        if event in self._triggered_events:
-            return
-        if not self._is_space_configured():
-            return
-
-        self._triggered_events.add(event)
-        await self._save_triggered_events()
-
-        # Check for pending survey asynchronously
-        asyncio.create_task(self._fetch_pending_survey(event))
-
-    async def _fetch_pending_survey(self, event: str):
-        """Fetch pending survey from Space for this event."""
-        try:
-            url = f'{self._space_url}/api/v1/survey/pending'
-            payload = {
-                'instance_id': constants.instance_id,
-                'event': event,
-            }
-            async with httpx.AsyncClient(timeout=httpx.Timeout(10)) as client:
-                resp = await client.post(url, json=payload)
-                if resp.status_code == 200:
-                    data = resp.json()
-                    if data.get('code') == 0 and data.get('data', {}).get('survey'):
-                        self._pending_survey = data['data']['survey']
-                        self.ap.logger.info(f'Survey pending: {self._pending_survey.get("survey_id")}')
-        except Exception as e:
-            self.ap.logger.debug(f'Failed to fetch pending survey: {e}')
-
-    def get_pending_survey(self) -> typing.Optional[dict]:
-        """Return the current pending survey (if any) for the frontend to display."""
-        return self._pending_survey
-
-    def clear_pending_survey(self):
-        """Clear the pending survey (after user responds or dismisses)."""
-        self._pending_survey = None
-
-    async def submit_response(self, survey_id: str, answers: dict, completed: bool = True) -> bool:
-        """Submit a survey response to Space."""
-        if not self._is_space_configured():
-            return False
-        try:
-            url = f'{self._space_url}/api/v1/survey/respond'
-            payload = {
-                'survey_id': survey_id,
-                'instance_id': constants.instance_id,
-                'answers': answers,
-                'metadata': {
-                    'version': constants.semantic_version,
-                },
-                'completed': completed,
-            }
-            async with httpx.AsyncClient(timeout=httpx.Timeout(10)) as client:
-                resp = await client.post(url, json=payload)
-                if resp.status_code == 200:
-                    self.clear_pending_survey()
-                    return True
-        except Exception as e:
-            self.ap.logger.warning(f'Failed to submit survey response: {e}')
-        return False
-
-    async def dismiss_survey(self, survey_id: str) -> bool:
-        """Dismiss a survey."""
-        if not self._is_space_configured():
-            return False
-        try:
-            url = f'{self._space_url}/api/v1/survey/dismiss'
-            payload = {
-                'survey_id': survey_id,
-                'instance_id': constants.instance_id,
-            }
-            async with httpx.AsyncClient(timeout=httpx.Timeout(10)) as client:
-                resp = await client.post(url, json=payload)
-                if resp.status_code == 200:
-                    self.clear_pending_survey()
-                    return True
-        except Exception as e:
-            self.ap.logger.warning(f'Failed to dismiss survey: {e}')
-        return False

src/langbot/pkg/telemetry/telemetry.py

@@ -60,7 +60,7 @@ class TelemetryManager:
                     except Exception:
                         sanitized['query_id'] = str(sanitized.get('query_id', ''))
 
-                for sfield in ('adapter', 'runner', 'runner_category', 'model_name', 'version', 'error', 'timestamp'):
+                for sfield in ('adapter', 'runner', 'model_name', 'version', 'error', 'timestamp'):
                     v = sanitized.get(sfield)
                     sanitized[sfield] = '' if v is None else str(v)
 

src/langbot/pkg/utils/constants.py

@@ -2,7 +2,7 @@ import langbot
 
 semantic_version = f'v{langbot.__version__}'
 
-required_database_version = 24
+required_database_version = 18
 """Tag the version of the database schema, used to check if the database needs to be migrated"""
 
 debug_mode = False

src/langbot/pkg/utils/httpclient.py

@@ -1,43 +0,0 @@
-"""Shared aiohttp.ClientSession to avoid repeated SSL context creation.
-
-Each call to `aiohttp.ClientSession()` creates a new `TCPConnector` which in turn
-creates a new `ssl.SSLContext` and loads all system root certificates. This is
-extremely expensive in both CPU and memory (~270MB total allocations observed via
-memray profiling).
-
-This module provides a shared session pool so that all HTTP client code in LangBot
-reuses the same underlying SSL context and connection pool.
-"""
-
-from __future__ import annotations
-
-import aiohttp
-
-_sessions: dict[str, aiohttp.ClientSession] = {}
-
-
-def get_session(*, trust_env: bool = False) -> aiohttp.ClientSession:
-    """Get or create a shared aiohttp.ClientSession.
-
-    Args:
-        trust_env: Whether to trust environment variables for proxy settings.
-
-    Returns:
-        A shared aiohttp.ClientSession instance.
-    """
-    key = f'trust_env={trust_env}'
-
-    session = _sessions.get(key)
-    if session is None or session.closed:
-        session = aiohttp.ClientSession(trust_env=trust_env)
-        _sessions[key] = session
-
-    return session
-
-
-async def close_all():
-    """Close all shared sessions. Call on application shutdown."""
-    for session in _sessions.values():
-        if not session.closed:
-            await session.close()
-    _sessions.clear()