AI
AI Filter
Overview:
The AI Filter block is designed to process input data by applying a specified natural language condition, facilitating effective data filtering and decision-making.
Inputs & Outputs
| I/O | Feature | Type | Simple Explanation |
|---|---|---|---|
| input | input | string | The text to apply the filter on. |
| input | condition | string | The natural language condition that will dictate how the inputs are filtered. |
| input | model | selector | Select from a range of supported LLM models for carrying out inference based on provided inputs. |
| input | cache_response | boolean | When enabled, this feature saves AI calls by returning the same response if the inputs have not changed since the last processing instance. |
| output | filtered_output | string | - This represents the filtered result of your data evaluation. If your input satisfies the defined condition, it appears here unchanged; otherwise, it will be empty. |
Use Cases
Consider how this block can enhance various processes:
- Filtering Customer Inquiries: Efficiently identify and isolate customer inquiries that meet certain criteria expressed in everyday language, ensuring prompt responses.
- Data Categorization: Automatically sort and organize textual information into distinct categories based on predefined conditions—useful for managing large datasets or incoming messages.
- Automated Decision Making: Incorporate dynamic decision capabilities into automation workflows whereby textual content determines subsequent actions or outputs in a streamlined manner.
In essence, when there is a need to filter or make decisions based on textual data seamlessly, the AI Filter block emerges as an essential tool!