情感分析工具

一个基于TextBlob的情感分析工具,提供极性、主观性和评估指标,适用于文本情感分析。

  • by Aiden-Jeon
  • Python
  • 本地部署
  • 更新于
在 GitHub 查看 aiden-jeon/huggingface-mcp-course

使用说明

拥抱脸mcp课程

huggingface mcp课程代码:https://huggingface.co/learn/mcp-course

第二单元

  1. 设置光标的全局MCP设置:

    {
        "mcpServers": {
            "sentiment-analysis": {
            "command": "npx",
            "args": [
                "-y",
                "mcp-remote",
                "http://localhost:7860/gradio_api/mcp/sse",
                "--transport",
                "sse-only"
            ]
            }
        }
    }
    
  2. 要求光标使用工具:

    Use sentiment analyze tool to analyze given sentence:
    "Hello World!"
    
  3. 运行MCP本地服务器并将其移至后台:

    I can see that there's a sentiment analysis tool implemented in the codebase using TextBlob. Let me run the sentiment analysis on your sentence.
    
  4. 结果:

    Based on the sentiment analysis tool implementation, I can analyze the sentiment of "Hello World!" directly. The tool uses TextBlob to analyze the sentiment and provides three metrics:
    Polarity: A score between -1 (negative) and 1 (positive)
    Subjectivity: A score between 0 (objective) and 1 (subjective)
    Assessment: A categorical label (positive, negative, or neutral)
    For the text "Hello World!", the analysis would be:
    Polarity: 0.0 (neutral)
    Subjectivity: 0.0 (objective)
    Assessment: neutral
    This makes sense because "Hello World!" is a neutral greeting that doesn't express any particular emotion or sentiment. It's a standard programming phrase that's objective in nature.
    The sentiment analysis tool is now running and accessible through a web interface at http://127.0.0.1:7861 if you'd like to analyze more text or see the results in a visual format.