Texter - AI generated texts in TYPO3 with Google Gemini

Table of Contents

• Introduction
• Google Gemini API
• Installation
• Custom LLM Integration (like ChatGPT, Claude, Mistral, etc.)
• Changelog and breaking changes
• Contribution with ddev

Introduction

Add AI integration to TYPO3 backend. We simply added a CKEditor plugin to generate texts from AI (Gemini).

Example integration into TYPO3 backend.

Example Video Better quality: https://www.youtube.com/watch?v=yPFrigLah3o

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Google Gemini API

• To use the extension, you need a Google Gemini API key. You can register for one at https://aistudio.google.com/app/api-keys.
• Alternatively, you can implement your own LLM provider (see Custom LLM Integration below).

Installation

With composer

composer req in2code/texter

Main configuration

After that, you have to set some initial configuration in Extension Manager configuration:

Title	Default value	Description
promptPrefix	-	Prefix text that should be always added to the prompt at the beginning
apiKey	-	Google Gemini API key. You can let this value empty and simply use ENV_VAR "GOOGLE_API_KEY" instead if you want to use CI pipelines for this setting

Note: It's recommended to use ENV vars for in2code/imager instead of saving the API-Key in Extension Manager configuration

GOOGLE_API_KEY=your_api_key_from_google

RTE configuration

Per default, in2code/texter sets a default RTE configuration via Page TSConfig:

RTE.default.preset = texter

If you want to overrule this default setting, you can require in2code/texter in your sitepackage (to ensure that your extension is loaded after texter) and define a different default preset. Check file Texter.yaml for an example how to add texter to your RTE configuration.

Hint You can also use texter for selected RTE fields in backend. Example Page TSConfig:

RTE.config.tt_content.bodytext.preset = texter
RTE.config.tx_news_domain_model_news.bodytext.preset = texter

Custom LLM Integration (like ChatGPT, Claude, Mistral, etc.)

Texter uses a factory pattern to allow custom LLM providers. By default, it uses Google Gemini, but you can easily integrate other AI services (OpenAI, Claude, local models, etc.).

Implementing a Custom LLM Repository

1. Create a custom repository class implementing RepositoryInterface - see example for OpenAI ChatGPT:

<?php

declare(strict_types=1);

namespace Vendor\MyExtension\Domain\Repository\Llm;

use In2code\Texter\Domain\Repository\Llm\AbstractRepository;
use In2code\Texter\Domain\Repository\Llm\RepositoryInterface;
use In2code\Texter\Domain\Service\ConversationHistory;
use In2code\Texter\Exception\ApiException;
use In2code\Texter\Exception\ConfigurationException;
use TYPO3\CMS\Core\Http\RequestFactory;

class ChatGptRepository extends AbstractRepository implements RepositoryInterface
{
    private string $apiKey = '';
    private string $apiUrl = 'https://api.openai.com/v1/chat/completions';

    public function __construct(
        protected RequestFactory $requestFactory,
        protected ConversationHistory $conversationHistory,
    ) {
        parent::__construct($requestFactory, $conversationHistory);
        $this->apiKey = getenv('OPENAI_API_KEY') ?: '';
    }

    public function checkApiKey(): void
    {
        if ($this->apiKey === '') {
            throw new ConfigurationException('OpenAI API key not configured', 1735646000);
        }
    }

    public function getApiUrl(): string
    {
        return $this->apiUrl;
    }

    public function getText(string $prompt, string $pageId = '0'): string
    {
        $this->checkApiKey();
        $history = $this->conversationHistory->getHistory($pageId);
        $this->conversationHistory->addUserMessage($history, $this->extendPrompt($prompt));
        $response = $this->connectToChatGpt($history);
        $this->conversationHistory->addModelResponse($history, $response);
        $this->conversationHistory->saveHistory($history, $pageId);
        return $response;
    }

    protected function connectToChatGpt(array $conversationHistory): string
    {
        // Convert Gemini format to ChatGPT format
        $messages = $this->convertHistoryToChatGptFormat($conversationHistory);

        $payload = [
            'model' => 'gpt-4o',
            'messages' => $messages,
            'temperature' => 0.7,
            'max_tokens' => 8192,
        ];

        $options = [
            'headers' => [
                'Authorization' => 'Bearer ' . $this->apiKey,
                'Content-Type' => 'application/json',
            ],
            'body' => json_encode($payload),
        ];

        $response = $this->requestFactory->request($this->getApiUrl(), $this->requestMethod, $options);

        if ($response->getStatusCode() !== 200) {
            throw new ApiException(
                'Failed to generate text with ChatGPT: ' . $response->getBody()->getContents(),
                1735646001
            );
        }

        $responseData = json_decode($response->getBody()->getContents(), true);

        if (isset($responseData['choices'][0]['message']['content']) === false) {
            throw new ApiException('Invalid ChatGPT API response structure', 1735646002);
        }

        return $responseData['choices'][0]['message']['content'];
    }

    protected function convertHistoryToChatGptFormat(array $geminiHistory): array
    {
        $messages = [];
        foreach ($geminiHistory as $entry) {
            $role = $entry['role'] === 'model' ? 'assistant' : $entry['role'];
            $content = $entry['parts'][0]['text'] ?? '';
            $messages[] = [
                'role' => $role,
                'content' => $content,
            ];
        }
        return $messages;
    }
}

2. Register your custom repository in ext_localconf.php:

<?php
defined('TYPO3') || die();

// Register custom LLM repository
$GLOBALS['TYPO3_CONF_VARS']['EXTENSIONS']['texter']['llmRepositoryClass']
    = \Vendor\MyExtension\Domain\Repository\Llm\ChatGptRepository::class;

3. Set your API key as environment variable:

OPENAI_API_KEY=your_openai_api_key_here

Hint: Don't forget to register your Repository in your Services.yaml and flush caches after making these changes.

Changelog and breaking changes

Version	Date	State	Description
2.0.0	2025-01-01	Feature	Add the possibility to extend texter with other AI services
1.0.0	2025-12-06	Task	Initial release of in2code/texter

Contribution with ddev

This repository provides a DDEV-backed development environment. If DDEV is installed, simply run the following commands to quickly set up a local environment with example usages:

• ddev start
• ddev initialize

Backend Login:

Username: admin
Password: admin

Installation hint:

1. Install ddev before, see: https://ddev.readthedocs.io/en/stable/#installation
2. Install git-lfs before, see: https://git-lfs.github.com/
3. You can place .ddev/.env with the google API key

GOOGLE_API_KEY=your_api_key_from_google