Sentiment Operations

Sentiment | Analyzer

The Sentiment analyzer operation is a simple prompt request operation to the configured LLM. It uses a plain text prompt as input and responds with a sentiment for the input text. The sentiment value can be NEUTRAL, POSITIVE, or NEGATIVE.

Input Configuration

Module Configuration

This refers to the MuleSoft AI Chain LLM Configuration set up in the Getting Started section.

General Operation Fields

Prompt: Contains the plain text prompt for the operation. This is the text that will be analyzed for its sentiment.

XML Configuration

Below is the XML configuration for this operation:

<ms-aichain:sentiment-analyze 
  doc:name="Sentiment analyze" 
  doc:id="cad4ef27-5c85-47f7-a68c-f666809b0846" 
  config-ref="MAC_AI_Llm_configuration" 
  data="#[payload.inputText]"
/>

Output Configuration

Response Payload

This operation responds with a json payload containing the sentiment of the input text. Additionally, attributes such as token usage and sentiment details are included as part of the metadata (attributes) but not within the main payload.

Example Response Payload

{
    "response": "POSITIVE"
}

Attributes

Along with the JSON payload, the operation also returns attributes, which include information about token usage:

{
  "tokenUsage": {
      "outputCount": 2,
      "totalCount": 39,
      "inputCount": 37
  },
  "additionalAttributes": {
      "isPositive": "false"
  }
}

Example Use Cases

This operation is particularly useful in scenarios where you need to analyze the sentiment of text, such as:

Customer Feedback Analysis: Determining whether customer feedback is positive, negative, or neutral.
Social Media Monitoring: Analyzing the sentiment of social media posts or comments to gauge public opinion.
Market Research: Assessing the sentiment of survey responses or market research data.

Rag Tools