This document explains the Categorizer node, which uses AI to classify text into custom categories.

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Node Inputs

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Required Fields

  • Input: Text to categorize
  • Categories: Define your classification groups:
    • Category Name: Label for the category
    • Category Description: Explain what belongs in this category

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Optional Fields

  • Include Justification: Get AI’s reasoning for selections
  • Additional Context: Extra guidance for categorization
  • Temperature: Controls AI decision-making (0-1)
  • Cache Response: Save responses for reuse

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Show As Input Options

You can expose these fields as inputs:

  • Additional Context
  • Temperature

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Node Output

  • Selected Category: Chosen category name
  • Justification: AI’s reasoning (if enabled)

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Node Functionality

The Categorizer node:

  • Analyzes input text
  • Matches to best category
  • Provides reasoning (optional)
  • Handles batch processing
  • Supports custom categories

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Available AI Models

  • Claude 3.5 Sonnet
  • Claude 3 Haiku
  • OpenAI o1
  • OpenAI o1 mini
  • GPT-4o
  • GPT-4o Mini
  • Gemini 1.5 Pro/Flash
  • And more

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Example Use Cases

  1. Sentiment Analysis:
Categories:
- Positive: "Expresses satisfaction or approval"
- Negative: "Shows dissatisfaction or criticism"
- Neutral: "States facts without emotion"
  1. Support Tickets:
Categories:
- Bug Report: "Technical issues or errors"
- Feature Request: "New functionality suggestions"
- Account Issue: "Login or access problems"
  1. Content Classification:
Categories:
- News: "Current events and reporting"
- Opinion: "Personal views and analysis"
- Tutorial: "How-to guides and instructions"

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Loop Mode

Input: List of customer feedback
Process: Categorize each item
Output: Category per item + justifications

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Important Considerations

  1. Expert models (OpenAI o1) cost 30 credits, advanced models (GPT-4o & Claude 3.5) cost 20 credits, and standard models cost 2 credits per run
  2. You can drop the credit cost to 1 by providing your own API key under the credentials page
  3. Write clear category descriptions for accurate outputs
  4. Enable justification for important decisions
  5. Use additional context for complex rules

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Additional Information

Video Tutorial

In summary, the Categorizer node helps organize text into meaningful groups using AI, with optional explanations for each decision.

SummarizerScorer