[]
Users can use the AI.TEXTSENTIMENT function to analyze the sentiment of text in a cell, returning Positive, Negative, or Neutral results.
AI.TEXTSENTIMENT(array, positive, negative, [neutral])
This function has these arguments:
Argument | Description |
|---|---|
array | [Required] The array of data to be passed to the function, such as a range reference. |
positive | [Required] The value to return when the sentiment analysis result is positive. |
negative | [Required] The value to return when the sentiment analysis result is negative. |
neutral | [Optional] The value to return when the sentiment analysis result is neutral. |
The following example shows how to invoke the OpenAI GPT-4.1 model and use the AI.TRANSLATE function for single sentence and batch text translation.
// To use this example, add the following dependency to your project: com.openai:openai-java:4.6.1
// Configure the model request handler and choose different large model providers as needed. Here the example uses OpenAI GPT-4.1; replace with your API key when using.
Workbook.setAIModelRequestHandler(new OpenAIModelRequestHandler("https://api.openai.com/v1", "sk-xxxx", "gpt-4.1"));
// DeepSeek model.
// Workbook.setAIModelRequestHandler(new OpenAIModelRequestHandler("https://api.deepseek.com/v1", "sk-xxxx", "deepseek-chat"));
// Qwen model.
// Workbook.setAIModelRequestHandler(new OpenAIModelRequestHandler("https://dashscope.aliyuncs.com/compatible-mode/v1", "sk-xxxx", "qwen-plus"));
// Initialize the workbook and set data.
Workbook workbook = new Workbook();
IWorksheet sheet = workbook.getWorksheets().get(0);
sheet.getColumns().get(0).setColumnWidth(55);
sheet.getColumns().get(1).setColumnWidth(55);
sheet.getRange("A1:B1").merge();
sheet.getRange("A1").setValue("Example: Customer Product Reviews");
sheet.getRange("A1").getFont().setBold(true);
sheet.getRange("A1").getFont().setSize(16);
sheet.getRange("A1").getFont().setColor(Color.GetWhite());
sheet.getRange("A1").getInterior().setColor(Color.FromArgb(90, 126, 158));
sheet.getRange("A1").setHorizontalAlignment(HorizontalAlignment.Center);
sheet.getRange("A1").setVerticalAlignment(VerticalAlignment.Center);
sheet.getRange("A1").setRowHeight(35);
sheet.getRange("A3").setValue("Formula:");
sheet.getRange("A3").getFont().setBold(true);
sheet.getRange("A3").getFont().setSize(11);
sheet.getRange("A3").getInterior().setColor(Color.FromArgb(217, 225, 242));
sheet.getRange("B3").setValue("=AI.TEXTSENTIMENT(A6:A13,\"Positive\",\"Negative\",\"Neutral\")");
sheet.getRange("B3").getFont().setItalic(true);
sheet.getRange("B3").getFont().setColor(Color.FromArgb(68, 114, 196));
sheet.getRange("B3").setWrapText(true);
sheet.getRange("A5:B5").setValue(new Object[][] {
{ "Review Text", "AI Sentiment" }
});
sheet.getRange("A5:B5").getFont().setBold(true);
sheet.getRange("A5:B5").getInterior().setColor(Color.FromArgb(155, 194, 230));
sheet.getRange("A5:B5").setHorizontalAlignment(HorizontalAlignment.Center);
sheet.getRange("A6:A13").setValue(new Object[][] {
{ "I absolutely love this product! It exceeded all my expectations!" },
{ "This is the worst purchase I've ever made. Total waste of money." },
{ "The product is okay, nothing special but does the job." },
{ "Outstanding quality and excellent customer service!" },
{ "Disappointed with the quality. Not worth the price." },
{ "It's average. Works fine but could be better." },
{ "Amazing! Best product ever! Highly recommend to everyone!" },
{ "Terrible experience. Would not recommend to anyone." }
});
for (int i = 6; i <= 13; i++) {
if ((i - 6) % 2 == 0) {
sheet.getRange("A" + i).getInterior().setColor(Color.FromArgb(242, 242, 242));
}
sheet.getRange("A" + i).getBorders().setLineStyle(BorderLineStyle.Thin);
sheet.getRange("A" + i).getBorders().setColor(Color.FromArgb(200, 200, 200));
sheet.getRange("A" + i).setWrapText(true);
}
// Define an AI sentiment analysis formula that classifies the contents of the range A6:A13 as Positive, Negative, or Neutral.
sheet.getRange("B6").setFormula2("=AI.TEXTSENTIMENT(A6:A13,\"Positive\",\"Negative\",\"Neutral\")");
for (int i = 6; i <= 13; i++) {
sheet.getRange("B" + i).getFont().setBold(true);
sheet.getRange("B" + i).getFont().setSize(11);
sheet.getRange("B" + i).setHorizontalAlignment(HorizontalAlignment.Center);
sheet.getRange("B" + i).getBorders().setLineStyle(BorderLineStyle.Medium);
sheet.getRange("B" + i).getBorders().setColor(Color.FromArgb(200, 200, 200));
}
// Apply conditional formatting to the sentiment analysis results.
IFormatCondition positiveCondition = (IFormatCondition) sheet.getRange("B6:B13").getFormatConditions().add(
FormatConditionType.CellValue,
FormatConditionOperator.Equal,
"=\"Positive\"",
null);
positiveCondition.getInterior().setColor(Color.FromArgb(226, 239, 218));
positiveCondition.getFont().setColor(Color.FromArgb(0, 128, 0));
IFormatCondition negativeCondition = (IFormatCondition) sheet.getRange("B6:B13").getFormatConditions().add(
FormatConditionType.CellValue,
FormatConditionOperator.Equal,
"=\"Negative\"",
null);
negativeCondition.getInterior().setColor(Color.FromArgb(255, 199, 206));
negativeCondition.getFont().setColor(Color.FromArgb(192, 0, 0));
IFormatCondition neutralCondition = (IFormatCondition) sheet.getRange("B6:B13").getFormatConditions().add(
FormatConditionType.CellValue,
FormatConditionOperator.Equal,
"=\"Neutral\"",
null);
neutralCondition.getInterior().setColor(Color.FromArgb(255, 242, 204));
neutralCondition.getFont().setColor(Color.FromArgb(128, 100, 0));
// The AI function is executed as an asynchronous calculation, so you need to wait for the calculation to complete.
workbook.calculate();
workbook.waitForCalculationToFinish();
// Set the page to fit on a single page.
sheet.getPageSetup().setFitToPagesTall(1);
sheet.getPageSetup().setFitToPagesWide(1);
sheet.getPageSetup().setIsPercentScale(false);
// Save as a PDF file.
workbook.save("AITEXTSENTIMENT.pdf");/**
* Implementation of IAIModelRequestHandler for OpenAI API.
*/
public class OpenAIModelRequestHandler implements IAIModelRequestHandler {
private String _apiEndpoint;
private String _apiKey;
private String _model;
public OpenAIModelRequestHandler(String apiEndpoint, String apiKey, String model) {
if (apiEndpoint == null || apiEndpoint.trim().isEmpty())
throw new IllegalArgumentException("API endpoint cannot be null or empty.");
if (apiKey == null || apiKey.trim().isEmpty())
throw new IllegalArgumentException("API key cannot be null or empty.");
_apiEndpoint = apiEndpoint.replaceAll("/$", "");
_apiKey = apiKey;
_model = model;
}
@Override
public CompletableFuture<AIModelResponse> sendRequestAsync(AIModelRequest request) {
CompletableFuture<AIModelResponse> result = new CompletableFuture<>();
if (request == null) {
AIModelResponse modelResponse = new AIModelResponse();
modelResponse.setSuccess(false);
System.err.println("Request cannot be null.");
result.complete(modelResponse);
return result;
}
OpenAIClientAsync openAIClient = OpenAIOkHttpClientAsync.builder()
.apiKey(_apiKey)
.baseUrl(_apiEndpoint)
.build();
ChatCompletionCreateParams.Builder builder = ChatCompletionCreateParams.builder();
for (AIMessage item : request.getMessages()) {
switch (item.getRole().toLowerCase()) {
case "system":
builder.addSystemMessage(item.getContent());
break;
case "user":
builder.addUserMessage(item.getContent());
break;
default:
throw new RuntimeException("Unknown message role:" + item.getRole());
}
}
builder.model(_model);
ChatCompletionCreateParams params = builder.build();
CompletableFuture<ChatCompletion> chatCompletion = openAIClient.chat().completions().create(params);
chatCompletion.whenComplete((response, exception) -> {
try {
if (exception != null) {
AIModelResponse errorResponse = new AIModelResponse();
errorResponse.setSuccess(false);
System.err.println("An error occurred: " + exception.getMessage());
result.complete(errorResponse);
} else {
if (response != null && !response.choices().isEmpty()) {
StringBuilder contentBuilder = new StringBuilder();
for (ChatCompletion.Choice choice : response.choices()) {
choice.message();
if (choice.message().content().isPresent()) {
contentBuilder.append(choice.message().content().get());
}
}
AIModelResponse successResponse = new AIModelResponse();
successResponse.setSuccess(true);
successResponse.setContent(contentBuilder.toString());
result.complete(successResponse);
} else {
AIModelResponse noContentResponse = new AIModelResponse();
noContentResponse.setSuccess(false);
System.err.println("No content received from the model.");
result.complete(noContentResponse);
}
}
} finally {
try {
openAIClient.close();
} catch (Exception e) {
System.err.println("Error closing OpenAI client: " + e.getMessage());
}
}
});
return result;
}
}The output is shown below:
