What Is Axilla?
Axilla is an opinionated LLM (Language Model) framework specifically designed for TypeScript developers with a product-focused approach. The framework was created by a team experienced in applying AI to self-driving cars and aims to provide an AI shortcut for developers across different domains. Axilla offers a family of modular libraries that can be incrementally adopted, forming an end-to-end framework for AI development.
The first key feature of Axilla is its ability to ingest documents from any source. It efficiently chunks up data and indexes it into a vector store for future augmented retrieval, simplifying data handling for developers. Next, Axilla enables developers to query LLM models through a simple and configurable prompt class. This feature supports both streaming and batch responses, offering flexibility for handling different types of queries.
Axilla comes equipped with an evaluation framework that allows developers to monitor the quality of model responses over time, specifically on production data. Continuous evaluation ensures datasets are continuously improved, leading to enhanced model performance. Additionally, the framework empowers developers to build and deploy LLM agents with autonomous reasoning capabilities. Once provided with direction, these agents can take actions on their own.
Axilla supports various model types, giving developers the freedom to use open-source models, fine-tune them with their own data, or integrate proprietary models like OpenAI’s chatGPT. Lastly, Axilla simplifies monitoring and logging through built-in functionalities. Developers can easily track quality and performance metrics, including metadata, prompts, and responses, providing comprehensive oversight of AI operations.
Axilla is a powerful and opinionated LLM framework catered to TypeScript developers with a focus on product development. By offering modular libraries, easy data ingestion, querying, evaluation, and agent deployment capabilities, Axilla streamlines the AI development process. Its compatibility with various model types and built-in monitoring further enhances its accessibility and usability, making it a valuable tool for developers looking to integrate AI into their projects efficiently.
