Auto Learning Agents

Auto Learning Agents provides a robust, open-source operating system designed for dynamic digital assistants. Key capabilities include: * Deep internal memory for continuous learning * Dynamic, session-less context retrieval * Web-based user interface for major language models * Local operation with platforms like Ollama * Integrated file browser, code editor, and 40+ tools * Background execution for continuous operation This platform allows digital assistants to maintain rich internal memory and dynamically retrieve relevant context for each interaction. This ensures that assistants can pick up tasks where they left off and progressively improve at recurring activities. The system offers a flexible web UI compatible with various large language models, alongside the option to run entirely locally, providing versatile deployment choices for users. Built on Elixir/OTP, the platform is engineered for resilience, with each assistant operating as a supervised process capable of recovering from crashes. Deployment is simplified with a single Docker command, making it accessible for developers, researchers, and organizations looking to implement stable and continuously improving digital assistant systems for various computational tasks and data processing needs.