merge(feat/wecom): 合并 feat/jjl 的增强改动

Author: bjhx2003

Dockerfile

@@ -1,3 +1,4 @@
+# ========== 前端构建阶段 ==========
 FROM node:22-alpine AS node
 
 WORKDIR /app
@@ -14,6 +15,7 @@ WORKDIR /app
 COPY pyproject.toml uv.lock README.md LICENSE main.py ./
 COPY src ./src
 
+# 安装系统依赖和 Python 依赖（排除开发依赖）
 RUN apt update \
     && apt install gcc -y \
     && python -m pip install --no-cache-dir uv \
@@ -23,9 +25,6 @@ RUN apt update \
     && rm -rf /var/lib/apt/lists/* \
     && touch /.dockerenv
 
-# 再复制其余运行时文件，避免无关文件变更导致依赖重装
-COPY . .
-
 COPY --from=node /app/web/out ./web/out
 
 CMD [ "uv", "run", "--no-sync", "main.py" ]

README.md

@@ -36,6 +36,20 @@ English / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本
 
 LangBot is an **open-source, production-grade platform** for building AI-powered instant messaging bots. It connects Large Language Models (LLMs) to any chat platform, enabling you to create intelligent agents that can converse, execute tasks, and integrate with your existing workflows.
 
+## Enhancements in This Branch
+
+Compared with the upstream official branch, this maintained branch includes several practical enhancements focused on WeCom / WeChat operations and long-running session reliability:
+
+- **WeCom Customer Service runtime enhancements** — Redis-backed scheduling, state persistence, retry handling, token cache, and sharded processing for more stable large-volume customer service workloads.
+- **WeCom app managed customer service adapter** — Added `wecom_kf_app` support for scenarios where customer service is managed through a WeCom application authorization model.
+- **Dify conversation persistence** — Persist Dify `conversation_id` bindings in Redis and clear them on explicit session resets, reducing context loss after runtime restarts.
+- **OpenClaw WeChat adapter support** — Added OpenClaw-based WeChat integration for additional WeChat connectivity scenarios.
+- **WeCom / WeChat integration hardening** — Additional fixes and runtime improvements around session isolation, callback handling, and customer-service message processing.
+
+These enhancements are especially useful for teams running LangBot in private deployments with heavier WeCom / WeChat customer-service traffic and stronger context-continuity requirements.
+
+---
+
 ### Key Capabilities
 
 - **AI Conversations & Agents** — Multi-turn dialogues, tool calling, multi-modal support, streaming output. Built-in RAG (knowledge base) with deep integration to [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).

README_CN.md

@@ -34,16 +34,14 @@
 
 ---
 
-## 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
 
 - **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，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，跨进程的事件驱动架构，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。
 

docker/docker-compose.yaml

@@ -4,6 +4,21 @@ version: "3"
 
 services:
 
+  redis:
+    image: redis:7-alpine
+    container_name: langbot_redis
+    restart: on-failure
+    command: ["redis-server", "--appendonly", "yes"]
+    volumes:
+      - ./data/redis:/data
+    environment:
+      - TZ=Asia/Shanghai
+    ports:
+      - 6379:6379
+    networks:
+      - langbot_network
+
+
   langbot_plugin_runtime:
     image: rockchin/langbot:latest
     container_name: langbot_plugin_runtime