Introduction to xef.ai
xef.ai is a comprehensive library designed to integrate the advanced capabilities of modern artificial intelligence into any application or service. This includes functionalities like Large Language Models (LLMs) and image generation. The goal of xef.ai is to simplify the adoption of these cutting-edge technologies for developers, offering both core libraries and integrations with other supportive libraries.
Core Libraries and Integrations
xef.ai is structured into two main components:
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Core Libraries: These libraries provide essential services for AI applications. They are designed to offer a user-friendly, idiomatic interface, catering to developers in specific programming languages. Currently, xef.ai supports Kotlin.
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Integrations: xef.ai offers additional library integrations that complement its core objectives, enhancing the overall functionality.
The inspiration for xef.ai comes from established projects like LangChain and Hugging Face, indicating its commitment to leveraging well-regarded AI community projects.
Data Transmission and Privacy
Users should be aware that xef.ai may transmit source code and user input data to third-party services as part of its operations. It's crucial to understand this aspect to ensure data security and privacy. Developers are advised to thoroughly review the privacy policies of third-party services to ensure alignment with personal or organizational data privacy expectations. By using xef.ai, developers agree to these data transmission practices.
Accessing the Libraries
xef.ai's libraries are available through Maven Central under the com.xebia group. The core library, named xef-core, and any additional integrations can be included in a project's build using common dependency management tools. Developers might need to set up the Maven Central repository in their build configurations if it's not already in use.
For example, in a Gradle build using Kotlin:
repositories { mavenCentral() }
dependencies {
implementation("com.xebia:xef-core:<version>")
}
All libraries are released under the same version, making version catalogs a useful feature for managing dependencies.
Getting Started
For new users, xef.ai provides a Quick Introduction that explores the library's main features. Additionally, practical examples are available on GitHub to showcase the practical use of the library.
Local Development
For those interested in contributing to xef.ai or customizing it for their specific needs, local development is straightforward. Developers can build the project locally using a series of simple shell commands. Note that some tests related to servers and databases may require Docker, as they rely on Testcontainers for execution.
In summary, xef.ai is a robust, user-friendly library designed to make modern AI technologies easily accessible for developers across various applications. Through its core functionalities and additional integrations, it aims to bridge the gap between state-of-the-art AI capabilities and practical implementation.