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Use large language models to interpret chat messages

Project description

Entari Plugin HYW

PyPI version License: MIT Python Versions

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Entari Plugin HYW is an advanced agentic chat plugin for the Entari framework. It leverages Large Language Models (LLMs) to provide intelligent, context-aware, and multi-modal responses within instant messaging environments (OneBot 11, Satori).

The plugin implements a three-stage pipeline (Vision, Instruct, Agent) to autonomously decide when to search the web, crawl pages, or analyze images to answer user queries effectively.

Features

  • 📖 Agentic Workflow
    Autonomous decision-making process to search, browse, and reason.

  • 🎑 Multi-Modal Support
    Native support for image analysis using Vision Language Models (VLMs).

  • 🔍 Web Search & Crawling
    Integrated DuckDuckGo and Crawl4AI for real-time information retrieval.

  • 🎨 Rich Rendering
    Responses are rendered as images containing Markdown, syntax-highlighted code, LaTeX math, and citation badges.

  • 🔌 Protocol Support
    Deep integration with OneBot 11 and Satori protocols, handling reply context and JSON cards perfectly.

Installation

pip install entari-plugin-hyw

Configuration

Configure the plugin in your entari.yml.

Minimal Configuration

plugins:
  entari_plugin_hyw:
    model_name: google/gemini-2.0-flash-exp
    api_key: "your-or-api-key-here"
    # Rendering Configuration
    render_timeout_ms: 6000 # Browser wait timeout
    render_image_timeout_ms: 3000 # Image load wait timeout

Usage

Commands

  • Text Query

    /q What's the latest news on Rust 1.83?
    
  • Image Analysis (Send an image with command, or reply to an image)

    /q [Image] Explain this error.
    
  • Quote Query

    [quote: User Message] /q
    
  • Follow-up Reply to the bot's message to continue the conversation.

Documentation for AI/LLMs


License

This project is licensed under the MIT License.

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