n8n-nodes-sentor

This is an n8n community node that lets you perform sentiment analysis using the Sentor ML API in your n8n workflows.

n8n is a fair-code licensed workflow automation platform.

Installation

Follow the installation guide in the n8n community nodes documentation.

Community Nodes (Recommended)

1. Go to Settings > Community Nodes in your n8n instance
2. Select Install a community node
3. Enter n8n-nodes-sentor in the npm package name field
4. Click Install

Manual Installation

To get started with local development or manual installation:

npm install n8n-nodes-sentor

Operations

The Sentor ML node currently supports the following operation:

Document > Predict Sentiment

Analyzes the sentiment of text documents and returns:

• Predicted label (positive, negative, or neutral)
• Confidence probabilities for each sentiment
• Sentence-level sentiment details

Configuration

Credentials

You need a Sentor ML API key to use this node:

1. Get your API key from Sentor ML
2. In n8n, go to Credentials > New
3. Search for "Sentor API"
4. Enter your API key
5. Click Save

Node Parameters

• Language: Choose between English (en) or Dutch (nl)
• Document Text: The text content to analyze (supports expressions for dynamic input)
• Entities (optional): Comma-separated list of entities to analyze within the text (e.g., "company, product, service")
• Simplify Output: When enabled (default), returns a simplified JSON structure with just label, probability, and details. When disabled, returns the full API response.

Example Usage

Basic Sentiment Analysis

Input:

{
  "documentText": "I love this product! It works great.",
  "language": "en"
}

Output (simplified):

{
  "label": "positive",
  "probability": 0.95,
  "details": [
    {
      "sentence": "I love this product!",
      "sentiment": "positive",
      "score": 0.97
    },
    {
      "sentence": "It works great.",
      "sentiment": "positive",
      "score": 0.93
    }
  ]
}

With Entities

Input:

{
  "documentText": "Apple's new iPhone is expensive but the camera quality is amazing.",
  "language": "en",
  "entities": "Apple, iPhone, camera"
}

The API will provide sentiment analysis with special attention to the specified entities.

Batch Processing

This node supports batch processing. When you pass multiple items to the node, it will:

1. Collect all input items
2. Send them in a single batch request to the API
3. Return individual results mapped to each input item

This is more efficient than processing items one by one.

Compatibility

• Tested with n8n version 1.0.0+
• Requires an active Sentor ML API subscription

Resources

• n8n community nodes documentation
• Sentor ML Homepage
• Sentor ML API Documentation
• GitHub Repository

Version History

0.1.0

• Initial release
• Support for sentiment prediction
• English and Dutch language support
• Entity-based analysis
• Batch processing support

License

MIT

Support

For issues, questions, or contributions:

• GitHub Issues: https://github.com/NIKX-Tech/n8n-nodes-sentor/issues
• Email: erfan@nikx.one

Development

Local Development

1. Clone the repository:

git clone https://github.com/NIKX-Tech/n8n-nodes-sentor.git
cd n8n-nodes-sentor

2. Install dependencies:

npm install

3. Build the node:

npm run build

4. Test locally:

npm run dev

This will start n8n with your local node loaded. You can then test it in your workflows.

Testing

To test the node in a local n8n instance:

1. Link the package locally:

npm link

2. In your n8n installation directory:

npm link n8n-nodes-sentor

3. Restart n8n and the node will be available

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request