AI specialist, Martin Anderson-Clutz, joins to discuss AI in Drupal. They cover topics like AI in relation to image fields, configuring API keys for the Augmenter module, prompt engineering, and exploring AI integration in Drupal. They also touch on the use of AI in solving arithmetic problems and automating blog post creation.
Augmenter AI allows integration of multiple AI services with Drupal, providing configurable settings and user-friendly interface.
AI Interpolator automates content summarization process, generating concise and relevant summaries for improved content organization.
Drupal offers AI-powered image generation and search modules like OpenAI Images and Pinecone, enhancing visual and search functionalities of websites.
Deep dives
Augmenter AI: Integrating Multiple AI Services with Drupal
Augmenter AI is a highly configurable module that allows you to integrate multiple AI services with your Drupal site. It provides a way to define Augmenter configuration entities that determine the AI service to use and the configuration options available. With Augmenter AI, you can generate responses from AI models based on prompts and configure various settings such as randomness and response length. The module offers an intuitive user interface and allows you to expose Augmenters to content creators through CKEditor buttons or fields. It also provides integration with various AI services, including Chat GPT, Google Cloud Vision, and AWS AI.
AI Interpolation: Automatic Generation of Content Summaries
AI Interpolator is a Drupal module that enables the automatic generation of content summaries. It is designed for site builders or backend users who want to automate the process of summarizing content. With AI Interpolator, you can automatically generate summaries for articles, blog posts, or any other type of content. By providing a text-based query, the module utilizes AI capabilities to generate concise and relevant summaries. This module eliminates the need for content creators to manually write summaries, saving time and effort. It offers a powerful tool for improving content organization and user experience.
AI-powered Image Generation and Search
Drupal offers several modules that leverage AI for image generation and search. The OpenAI Images module allows you to generate images using AI and seamlessly integrates them into your Drupal site. It provides a user-friendly interface, making it easy to use AI-generated images in various contexts. Additionally, there are search modules like Pinecone, which is a vector-based search service. Pinecone allows for highly specific queries, enabling deep search capabilities within your Drupal site. These AI-powered image generation and search modules enhance the visual and search functionalities of your website, delivering an enriched user experience.
AI Prompt Engineering and Contextual Responses
Prompt engineering is an important aspect of using AI. It involves carefully constructing prompts to get the desired results. Factors such as the core ask, additional context or framing, specifying personas or profiles, providing examples or references, and specifying formats or tones can significantly impact the output. Context is crucial when interacting with AI models, as follow-ups can be contextual without requiring a complete rephrasing of the prompt. Providing the right context and gradually modifying prompts can help improve the accuracy and relevance of the AI's responses.
AI Integration with Drupal and Foreseeable Future
AI integration with Drupal is expanding in various ways. One popular AI module is Open AI, which provides compelling functionality through API integration. It offers options like generating content within CK editor, sentiment analysis, tag suggestions, and more. Prompt chaining and metaprompting are emerging techniques that enable AI tools to be incorporated with Drupal effectively. Prompt chaining involves using one tool to generate prompts for another downstream tool, while metaprompting goes a step further, allowing an AI model to handle multiple queries and orchestrate the overall task. AI has the potential to enhance Drupal sites by suggesting architectural approaches, assisting with content generation, and enabling powerful content augmentation.
Today we are talking about AI within Drupal, How AI can help, and Modules to use with guest Martin Anderson-Clutz. We’ll also cover Augmentor AI as our module of the week.
NLP - work with text provided in a conversational format, understand the intended meaning, and provide a relevant response
AI - A subset of CS that aims to develop systems that can mimic human response, or automating sophisticated behavior
ML - subset of AI that aims to act without explicit guidance, by extrapolating from known data
Deep learning - a subset of ML which uses artificial neural networks with representational learning to develop and leverage their own means of classification and other feature detection
LLM - an AI algorithm that uses Deep Learning techniques to accomplish NLP tasks such as responding to unstructured user prompts. LLMs are trained on massive data sets, often gathered from the internet, but sometimes using more specialized data
Typically the AI interfaces our listeners are already using are based on an LLM, but the nature and recency of the data they’ve been trained on can vary widely. Recently Mike Miles created Drupal Droid, a GPT model specifically trained for Drupal developers, and you can find a demo of that in our YouTube channel
Have you ever wanted a highly configurable way to integrate multiple AI services with your Drupal site? There’s a module for that.
Brief history
How old: created in Oct 2022 by murrayw of Morpht, though recent releases are by elonel
Versions available: 1.1.2 which works with Drupal 9.5 and 10
Maintainership
Actively maintained, most recent release was earlier this month
Documentation available
Number of open issues: 11, 3 of which are bugs
Usage stats:
82 sites
Module features and usage
To use Augmentor AI, you need to define one or more “augmentor” configuration entities. An augmenter entity implements an augmentor type, which determines what AI service it can use, what configuration options it will have available, and so on.
The augmentor will define one or more “messages” that provide structure to the prompt that will be passed to the AI model in order to generate a response. It can also be configured in a variety of ways, such as how much randomness to use, a maximum response length, and more.
You can expose your augmentor(s) to content creators by adding a CKEditor button, or by adding fields to your site’s entity forms. For each field use can choose the widget to use, and how it should interact with any existing data in the field you want to target.
For example, you could have it generate a summary from your body field and have it automatically populate the summary field. Or, you can have it suggest tags, but the specialized widget renders each suggestion as a clickable element that will add the tag to a core tag field.
There are currently modules available to integrate Augmentor AI with ChatGPT, Google Cloud Vision, AWS AI, and more.
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