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Use large language models to interpret chat messages

Project description

Entari Plugin HYW

Entari 智能聊天解释插件

License PyPI Python

IM 环境下的 LLM 智能解释方案

🎑 效果展示

Chat Demo

✨ 功能特性

  • 关于搜索:目前推荐使用 OpenRouter 的 :online 参数,该参数会优先使用模型提供商的搜索、其次 exa(较贵) 进行网页搜索。推荐使用 x-ai/grok-4.1-fast:online
  • 给予 AlconnaMessageChain 混合处理, 深度优化触发体验`。
  • 网页获取:支持通过 Jina AIPlaywright 进行实时页面获取。
  • 多模态理解:无缝处理文本与图片。自动对文档/截图进行 OCR 文字识别,对照片进行视觉分析。
  • 上下文感知:维护对话历史记录,支持自然、连续的多轮对话。支持保存对话历史记录搭到本地研究。
  • OneBot 优化:针对 OneBot 11 协议深度优化,支持解析 JSON 卡片、引用消息等特殊元素。
  • reaction 表情, 表示任务开始。

📦 安装

基础安装

pip install entari-plugin-hyw

启用 Playwright 支持

如果你希望使用 Playwright 进行本地网页渲染(而非仅使用 Jina AI):

pip install entari-plugin-hyw[playwright]
playwright install chromium

⚙️ 配置

请在 entari.yml 中添加以下配置:

plugins:
  entari_plugin_hyw:
    # --- 基础设置 ---
    # 触发机器人的命令列表
    command_name_list: ["/hyw", "hyw"]
    
    # 主 LLM 模型配置(必需)(online 模式), 如 x-ai/grok-4.1-fast:online、perplexity/sonar
    model_name: "gx-ai/grok-4.1-fast:online"
    api_key: "your-api-key"
    base_url: "https://dashscope.aliyuncs.com/compatible-mode/v1"
    
    # --- 浏览器与搜索 ---
    # 网页浏览工具: "jina" (默认) 或 "playwright"
    browser_tool: "jina"
    
    # 可选: Jina AI API Key (配置以获得更高限额)(免费方案20/min)
    jina_api_key: "jina_..."
    
    # Playwright 设置
    headless: true
    
    # --- 视觉配置 (可选) ---
    # 如果未设置,将回退使用主模型
    vision_model_name: "qwen-vl-plus"
    vision_api_key: "your-vision-api-key"
    vision_base_url: "https://dashscope.aliyuncs.com/compatible-mode/v1"
    
    # --- 调试 ---
    save_conversation: false

📖 使用方法

基础指令

使用配置的命令前缀与机器人交互:

hyw 最近LLM有啥新闻, 是不是claude又被秒了
hyw [图片消息] 里面这人写代码怎么我一句都看不懂
hyw https://koishi.chat/ 怎么安装
[回复消息] hyw 
[回复消息<[图片消息]>] hyw -t
[回复消息] hyw 补充: 这个rf的意思是github用户RF-Tar-Railt
[回复消息(hyw插件的输出)] /1 详细点描述
[回复消息(hyw插件的输出>] /那谁有多余解释器?

选项参数

  • -t / --text: 强制纯文本模式(跳过图片分析,节省 Token 或时间)。
hyw -t 一大段话。

引用回复

支持引用消息进行追问,机器人会自动读取被引用的消息作为上下文:

  • 引用 + 命令:机器人将理解被引用消息的内容(包括图片)通过 MessageChain 操作拼接 TextImage 与部分 Custom

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