AI.TEXTSENTIMENT

// 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;
    }
}

// To use this example, add the following dependency to your project: com.anthropic:anthropic-java:2.57.0
// Configure the model request handler and choose different large model providers as needed. Here the example uses deepseek-v4-flash; replace with your API key when using.
Workbook.setAIModelRequestHandler(new AnthropicModelRequestHandler("https://api.deepseek.com/anthropic", "sk-xxxx", "deepseek-v4-flash"));
// Anthropic Claude model.
// Workbook.setAIModelRequestHandler(new AnthropicModelRequestHandler("https://api.anthropic.com", "sk-xxxx", "claude-haiku-4-5"));

// Initialize the workbook and set data.
var workbook = new Workbook();
IWorksheet sheet = workbook.Worksheets[0];
sheet.Columns[0].ColumnWidth = 55;
sheet.Columns[1].ColumnWidth = 55;
sheet.Range["A1:B1"].Merge();
sheet.Range["A1"].Value = "Example: Customer Product Reviews (Anthropic-compatible)";
sheet.Range["A1"].Font.Bold = true;
sheet.Range["A1"].Font.Size = 16;
sheet.Range["A1"].Font.Color = Color.White;
sheet.Range["A1"].Interior.Color = Color.FromArgb(90, 126, 158);
sheet.Range["A1"].HorizontalAlignment = HorizontalAlignment.Center;
sheet.Range["A1"].VerticalAlignment = VerticalAlignment.Center;
sheet.Range["A1"].RowHeight = 35;
sheet.Range["A3"].Value = "Formula:";
sheet.Range["A3"].Font.Bold = true;
sheet.Range["A3"].Font.Size = 11;
sheet.Range["A3"].Interior.Color = Color.FromArgb(217, 225, 242);
sheet.Range["B3"].Value = "=AI.TEXTSENTIMENT(A6:A13,\"Positive\",\"Negative\",\"Neutral\")";
sheet.Range["B3"].Font.Italic = true;
sheet.Range["B3"].Font.Color = Color.FromArgb(68, 114, 196);
sheet.Range["B3"].WrapText = true;
sheet.Range["A5:B5"].Value = new object[,] {
    { "Review Text", "AI Sentiment" }
};
sheet.Range["A5:B5"].Font.Bold = true;
sheet.Range["A5:B5"].Interior.Color = Color.FromArgb(155, 194, 230);
sheet.Range["A5:B5"].HorizontalAlignment = HorizontalAlignment.Center;
sheet.Range["A6:A13"].Value = 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.Range["A" + i].Interior.Color = Color.FromArgb(242, 242, 242);
    }
    sheet.Range["A" + i].Borders.LineStyle = BorderLineStyle.Thin;
    sheet.Range["A" + i].Borders.Color = Color.FromArgb(200, 200, 200);
    sheet.Range["A" + i].WrapText = true;
}
// Define an AI sentiment analysis formula that classifies the contents of the range A6:A13 as Positive, Negative, or Neutral.
sheet.Range["B6"].Formula2 = "=AI.TEXTSENTIMENT(A6:A13,\"Positive\",\"Negative\",\"Neutral\")";
for (int i = 6; i <= 13; i++)
{
    sheet.Range["B" + i].Font.Bold = true;
    sheet.Range["B" + i].Font.Size = 11;
    sheet.Range["B" + i].HorizontalAlignment = HorizontalAlignment.Center;
    sheet.Range["B" + i].Borders.LineStyle = BorderLineStyle.Medium;
    sheet.Range["B" + i].Borders.Color = Color.FromArgb(200, 200, 200);
}
// Apply conditional formatting to the sentiment analysis results.
IFormatCondition positiveCondition = (IFormatCondition)sheet.Range["B6:B13"].FormatConditions.Add(
    FormatConditionType.CellValue,
    FormatConditionOperator.Equal,
    "=\"Positive\"",
    null
);
positiveCondition.Interior.Color = Color.FromArgb(226, 239, 218);
positiveCondition.Font.Color = Color.FromArgb(0, 128, 0);
IFormatCondition negativeCondition = (IFormatCondition)sheet.Range["B6:B13"].FormatConditions.Add(
    FormatConditionType.CellValue,
    FormatConditionOperator.Equal,
    "=\"Negative\"",
    null
);
negativeCondition.Interior.Color = Color.FromArgb(255, 199, 206);
negativeCondition.Font.Color = Color.FromArgb(192, 0, 0);
IFormatCondition neutralCondition = (IFormatCondition)sheet.Range["B6:B13"].FormatConditions.Add(
     FormatConditionType.CellValue,
     FormatConditionOperator.Equal,
     "=\"Neutral\"",
     null
);
neutralCondition.Interior.Color = Color.FromArgb(255, 242, 204);
neutralCondition.Font.Color = 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.PageSetup.FitToPagesTall = 1;
sheet.PageSetup.FitToPagesWide = 1;
sheet.PageSetup.IsPercentScale = false;

// Save as a PDF file.
workbook.Save("AITEXTSENTIMENT.pdf");

/** IAIModelRequestHandler implementation using the official Anthropic SDK. */
public class AnthropicModelRequestHandler implements IAIModelRequestHandler {
    private final String apiEndpoint;
    private final String apiKey;
    private final String model;

    public AnthropicModelRequestHandler(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.");
        if (model == null || model.trim().isEmpty())
            throw new IllegalArgumentException("Model cannot be null or empty.");
        this.apiEndpoint = apiEndpoint;
        this.apiKey = apiKey;
        this.model = model;
    }

    @Override    public CompletableFuture<AIModelResponse> sendRequestAsync(AIModelRequest request) {
        if (request == null) {
            System.err.println("Request cannot be null.");
            return CompletableFuture.completedFuture(failedResponse());
        }
        try {
            MessageCreateParams.Builder builder = MessageCreateParams.builder()
                    .model(model)
                    .maxTokens(4096);
            StringBuilder system = new StringBuilder();
            int userMessageCount = 0;
            for (AIMessage message : request.getMessages()) {
                if ("system".equalsIgnoreCase(message.getRole())) {
                    if (system.length() > 0) system.append("\n\n");
                    system.append(message.getContent());
                } else if ("user".equalsIgnoreCase(message.getRole())) {
                    builder.addUserMessage(message.getContent());
                    userMessageCount++;
                } else {
                    throw new IllegalArgumentException("Unknown message role: " + message.getRole());
                }
            }
            if (userMessageCount == 0)
                throw new IllegalArgumentException("The request must contain at least one user message.");
            if (system.length() > 0) builder.system(system.toString());

            MessageCreateParams params = builder.build();
            AnthropicClientAsync client = AnthropicOkHttpClientAsync.builder()
                    .apiKey(apiKey)
                    .baseUrl(apiEndpoint)
                    .build();
            try {
                return client.messages().create(params)
                        .thenApply(message -> {
                            StringBuilder content = new StringBuilder();
                            for (ContentBlock block : message.content())
                                if (block.isText()) content.append(block.asText().text());
                            if (content.length() == 0) {
                                System.err.println("No text content received from the model.");
                                return failedResponse();
                            }
                            AIModelResponse response = new AIModelResponse();
                            response.setSuccess(true);
                            response.setContent(content.toString());
                            return response;
                        })
                        .exceptionally(ex -> {
                            System.err.println(ex);
                            return failedResponse();
                        })
                        .whenComplete((response, ex) -> closeClient(client));
            } catch (Exception ex) {
                closeClient(client);
                throw ex;
            }
        } catch (Exception ex) {
            System.err.println(ex);
            return CompletableFuture.completedFuture(failedResponse());
        }
    }

    private static void closeClient(AnthropicClientAsync client) {
        try {
            client.close();
        } catch (Exception ex) {
            System.err.println("Error closing Anthropic client: " + ex.getMessage());
        }
    }

    private static AIModelResponse failedResponse() {
        AIModelResponse response = new AIModelResponse();
        response.setSuccess(false);
        return response;
    }
}