Inline AI-Powered Translations: Integrating ChatGPT with Payload CMS

15 dicembre 2024 di Moritz Thomas

In modern translation management systems, the ability to quickly generate high-quality translation suggestions directly within the editing interface can significantly streamline the translation workflow. This article explores how we integrated OpenAI's ChatGPT API with Payload CMS to provide inline translation suggestions, creating a seamless experience for content editors and translators.

Overview

The system combines several key components:

  1. A custom Payload CMS field component for the user interface

  2. An API endpoint that interfaces with OpenAI's ChatGPT

  3. Integration with our Settings global for configuration

  4. Function calling for structured translation responses

This integration allows translators to:

  • Receive AI-powered translation suggestions directly in the editing interface

  • Choose from multiple translation variations

  • Maintain context awareness through description fields

  • Customize the AI's behavior through configurable prompts

Custom Translation Field

The heart of our implementation is a custom Payload CMS field that extends the standard text input with AI translation capabilities:

const InputField: React.FC<Props & { 
  minVariations: number; 
  maxVariations: number 
}> = ({
  path,
  label,
  required,
  admin: { readOnly },
  minVariations,
  maxVariations,
}) => {
  const documentInfo = useDocumentInfo();
  const { code: locale } = useLocale();
  const [translations, setTranslations] = useState([]);
  const [load, setLoad] = useState("");
  const [term, setTerm] = useState("");
  const [context, setContext] = useState("");

  // ... component implementation
};

Key features of the field component:

  • Extends Payload's text field functionality

  • Provides a familiar interface for manual translation

  • Adds an "Ask ChatGPT" button for AI suggestions

  • Displays multiple translation options in a dropdown

  • Preserves context through description fields

The component is designed to be non-intrusive - it maintains all standard text field functionality while adding AI capabilities when appropriate:

return (
  <div className="custom-translation-picker field-type text">
    <Label htmlFor={path} label={`${label} (${locale})`} required={required} />
    <input
      type="text"
      id={path}
      value={value.toString()}
      onChange={(e) => setValue(e.target.value)}
      disabled={readOnly}
    />
    {locale !== defaultLocale && documentInfo.id && (
      // AI translation interface
    )}
  </div>
);

ChatGPT Integration

The translation endpoint leverages OpenAI's function calling feature to ensure structured responses:

const tools = [
  {
    type: "function",
    function: {
      name: "display_translation_options",
      description: `Display a list of translation options...`,
      parameters: {
        type: "object",
        properties: {
          translations: {
            type: "array",
            items: {
              type: "string",
            },
            description: "List of translation options",
          },
        },
      },
    },
  },
];

This approach offers several advantages:

  1. Structured responses that can be reliably parsed

  2. Clear guidance to the AI about expected output format

  3. Flexibility in the number of variations requested

  4. Easy extension for additional metadata in the future

Configuration Through Settings

The system uses our previously implemented Settings global for configuration:

const settings = await payload.findGlobal({
  slug: "payload-settings",
}) as PayloadSetting;

const model = settings.chatgptModel ?? "gpt-4-turbo-preview";
let content = settings.askChatgptPrompt;

This allows administrators to:

  • Select the ChatGPT model to use

  • Customize prompts for different scenarios

  • Configure the number of variations

  • Set default behaviors

Usage in Different Contexts

The custom field can be used in various contexts throughout the CMS:

Article Titles

{
  name: "title",
  label: "Title",
  type: "text",
  localized: true,
  admin: {
    components: {
      Field: (props) => (
        <InputField {...props} minVariations={3} maxVariations={5} />
      ),
    },
  },
}

UI String Translations

{
  name: "text",
  type: "text",
  label: "Text",
  localized: true,
  admin: {
    components: {
      Field: (props) => (
        <InputField {...props} minVariations={3} maxVariations={5} />
      ),
    },
  },
}

Context-Aware Translations

The system maintains translation context by:

  1. Fetching the original content and description

  2. Including context in the ChatGPT prompt

  3. Allowing customization of context handling through settings

await fetch(`/api/${documentInfo.slug}/${documentInfo.id}?draft=false&depth=1`)
  .then((response) => response.json())
  .then((data) => {
    setContext(data.description);
    setTerm(data[path]);
  });

Future Enhancements

Several areas have been identified for future improvement:

  1. Enhanced Error Handling

    • Better validation of API responses

    • Graceful fallback for API failures

    • User-friendly error messages

  2. Performance Optimization

    • Caching of common translations

    • Batch translation capabilities

    • Request rate limiting

  3. Quality Assurance

    • Translation confidence scores

    • Automatic quality checks

    • Context-specific validation

  4. User Interface Improvements

    • Preview of translations in context

    • Keyboard shortcuts for efficiency

    • Bulk translation interface

Conclusion

The integration of AI-powered translations directly into the CMS editing interface represents a significant improvement in translation workflow efficiency. By combining the power of ChatGPT with a carefully designed user interface, we've created a system that:

  • Reduces translation time and effort

  • Maintains translation quality through context awareness

  • Provides flexibility through configuration

  • Integrates seamlessly with existing workflows

This implementation demonstrates how modern AI capabilities can be thoughtfully integrated into content management systems to enhance productivity while maintaining user control and content quality.

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© 2024 da Moritz Thomas