​
Prerequisites

You'll need an API key to use the Moderation API. To get one, you'll need to create a project.

​
1. Install SDK

We currently don’t have an official SDK for Java, but you can use the OpenAPI Generator to generate a Java client or simply call the API directly using Java’s built-in HttpClient.

​
2. Submit content

Grab the API key from your project and begin submitting text, images, or other media to your project for moderation.

import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import org.json.JSONObject;

public class TextModeration {
    public static void main(String[] args) {
        String API_KEY = "your-api-key"; // Replace with your API key
        String BASE_URL = "https://moderationapi.com/api/v1";

        try {
            HttpClient client = HttpClient.newHttpClient();

            // Create request body
            JSONObject requestBody = new JSONObject()
                .put("value", "Hello world!")
                .put("authorId", "123")
                .put("contextId", "456")
                .put("metadata", new JSONObject()
                    .put("customField", "value")
                );

            HttpRequest request = HttpRequest.newBuilder()
                .uri(URI.create(BASE_URL + "/moderate/text"))
                .header("Authorization", "Bearer " + API_KEY)
                .header("Content-Type", "application/json")
                .POST(HttpRequest.BodyPublishers.ofString(requestBody.toString()))
                .build();

            HttpResponse<String> response = client.send(request,
                HttpResponse.BodyHandlers.ofString());

            JSONObject textAnalysis = new JSONObject(response.body());

            if (textAnalysis.getBoolean("flagged")) {
                System.out.println("Text content flagged");
                // Block the content, show an error, etc...
            } else {
                System.out.println("Text content is safe.");
                // Save to database or proceed...
            }

        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}

Dry-run mode: If you want to analyze production data but don't want to block content, enable "dry-run" in your project settings.

With dry-run enabled, the API still analyzes content but it always returns flagged: false - yet content still shows in the review queue. This way you can implement your moderation workflows and start testing your project configuration without actually blocking content.

​
3. Review flagged content (optional)

If the AI flags the content, it will appear in the Review Queue.

Head to the review queue to validate that the content is submitted correctly.

Review queue for reviewing and improving automated moderation

You can use review queues to implement moderation workflows or simply check how the AI is performing.

​
All Done!

Congratulations! You've run your first moderation checks. Here are a few next steps:

  • Continue tweaking your project settings and models to find the best moderation outcomes.
  • Create an AI agent and add your guidelines to it.
  • Explore advanced features like context-aware moderation.
  • If you have questions, reach out to our support team.

We love hearing from you—please share how you're using the service and let us know if you have suggestions or need help. Happy moderating!

​
Prerequisites

You'll need an API key to use the Moderation API. To get one, you'll need to create a project.

​
1. Install SDK

We currently don’t have an official SDK for Java, but you can use the OpenAPI Generator to generate a Java client or simply call the API directly using Java’s built-in HttpClient.

​
2. Submit content

Grab the API key from your project and begin submitting text, images, or other media to your project for moderation.

import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import org.json.JSONObject;

public class TextModeration {
    public static void main(String[] args) {
        String API_KEY = "your-api-key"; // Replace with your API key
        String BASE_URL = "https://moderationapi.com/api/v1";

        try {
            HttpClient client = HttpClient.newHttpClient();

            // Create request body
            JSONObject requestBody = new JSONObject()
                .put("value", "Hello world!")
                .put("authorId", "123")
                .put("contextId", "456")
                .put("metadata", new JSONObject()
                    .put("customField", "value")
                );

            HttpRequest request = HttpRequest.newBuilder()
                .uri(URI.create(BASE_URL + "/moderate/text"))
                .header("Authorization", "Bearer " + API_KEY)
                .header("Content-Type", "application/json")
                .POST(HttpRequest.BodyPublishers.ofString(requestBody.toString()))
                .build();

            HttpResponse<String> response = client.send(request,
                HttpResponse.BodyHandlers.ofString());

            JSONObject textAnalysis = new JSONObject(response.body());

            if (textAnalysis.getBoolean("flagged")) {
                System.out.println("Text content flagged");
                // Block the content, show an error, etc...
            } else {
                System.out.println("Text content is safe.");
                // Save to database or proceed...
            }

        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}

Dry-run mode: If you want to analyze production data but don't want to block content, enable "dry-run" in your project settings.

With dry-run enabled, the API still analyzes content but it always returns flagged: false - yet content still shows in the review queue. This way you can implement your moderation workflows and start testing your project configuration without actually blocking content.

​
3. Review flagged content (optional)

If the AI flags the content, it will appear in the Review Queue.

Head to the review queue to validate that the content is submitted correctly.

Review queue for reviewing and improving automated moderation

You can use review queues to implement moderation workflows or simply check how the AI is performing.

​
All Done!

Congratulations! You've run your first moderation checks. Here are a few next steps:

  • Continue tweaking your project settings and models to find the best moderation outcomes.
  • Create an AI agent and add your guidelines to it.
  • Explore advanced features like context-aware moderation.
  • If you have questions, reach out to our support team.

We love hearing from you—please share how you're using the service and let us know if you have suggestions or need help. Happy moderating!