Definition and Usage
Analyzes and identifies the sentiment (positive, negative, or neutral) expressed in the provided text. This action uses AI language models to evaluate the emotional tone of text content and provides a sentiment analysis result.
Parameter Values
Input parameters
Parameter | Description | Required | Options / Notes |
LLM model | Select the language model that best suits your scenario | Yes | Requires platform credits for execution |
Text content | Please provide the text content for sentiment analysis | Yes | Can use variable input {x} |
Error handling
Parameter Name | Description |
Throw error & stop | When an error occurs, the action will trigger an error and stop the execution of the entire app. |
Retry command | If an error occurs, the action will retry the command in an attempt to resolve the issue and continue the process. |
Ignore error & continue | When an error occurs, the action will be ignored, and the workflow will continue without interruption. |
Variables produced
This action produces a sentiment analysis result variable that contains the identified sentiment (positive, negative, or neutral) of the analyzed text.
Using Variables in Conditions
When configuring this action, you can use variables from previous steps in your workflow by clicking the {x} button next to the Text content field. This allows you to dynamically analyze text that was generated or collected in earlier steps.
The output variable can be used in subsequent steps to make decisions based on the sentiment analysis result, such as taking different actions for positive versus negative feedback.
Notes
The accuracy of sentiment analysis depends on the selected language model and the clarity of the provided text.
For best results, provide clear and concise text without ambiguous language.
The analysis works best with text in languages supported by the selected model.
Platform credits are consumed when executing this action. The cost per execution depends on the selected model and the length of the analyzed text.