AI
Categorizer
Overview:
The Categorizer block streamlines the process of classifying text data into predefined categories using AI. This block is essential for transforming unstructured text into structured, actionable insights.
Inputs & Outputs
| I/O | Feature | Type | Simple Explanation |
|---|---|---|---|
| input | categories | list | A list containing all the category names and their descriptions that will guide the AI in classifying input text. |
| input | input | string | The actual text string that you wish to classify according to your predefined categories. |
| input | include_justification | boolean | When enabled, it ensures that the categorization process also provides reasoning or explanation for its choices. |
| input | model | selector | Specifies which LLM model to utilize for inference from the available supported models. |
| input | cache_response | boolean | When activated, this feature stores previous AI responses and returns them if the inputs have not changed, saving time on subsequent calls. |
Use Cases
Consider how this block can enhance efficiency in diverse situations:
- Customer Feedback Analysis: Automatically classify customer feedback into themes or topics such as satisfaction, service issues, or product features—enabling quicker decision-making on areas needing attention.
- Product Categorization: Sort and categorize various products based on their descriptions without manual effort, ensuring a well-organized catalog for easier viewing.
- Document Organization: Implement an automatic labeling system where documents related to specific topics get categorized appropriately—streamlining access and retrieval.
- Interpretability Enhancement: Understand why certain decisions were made by analyzing justification provided by AI when processing inputs; this adds depth to AI-driven insights.
In summary, any scenario requiring enhanced organization of textual information can benefit greatly from utilizing the Categorizer block!