Open Source Elixir Artificial Intelligence Software

Symphony is an open-source framework designed to transform project tasks into autonomous implementation runs managed by AI coding agents. It allows teams to manage and prioritize work while the system automatically assigns coding agents to complete tasks. Instead of directly supervising AI agents, engineers can oversee higher-level workflows and project outcomes. Symphony integrates with project management tools to detect new tasks and initiate isolated environments where agents implement solutions. Each run generates proof of work such as CI results, pull requests, code reviews, and analysis to validate the completed task. By automating execution and verification, Symphony helps engineering teams scale development workflows with minimal manual oversight.

Dagger is an open source automation engine designed to build, test, and deliver software in a consistent and programmable way. It enables developers to define software delivery workflows using code instead of complex shell scripts or configuration files. Dagger executes tasks inside containers, ensuring that automation runs in identical environments across local machines, CI servers, or cloud infrastructure. Dagger provides a core execution engine and system API that orchestrates containers, filesystems, secrets, repositories, and other resources needed during development pipelines. Developers can write pipelines using SDKs available for multiple programming languages, enabling integration with existing development stacks and tools. It focuses on repeatability and efficiency by running tasks incrementally and caching intermediate results so that only affected operations are re-executed when changes occur.

Frontman is an open-source AI coding agent that lives inside your running web app. Click any element, describe the change, and Frontman edits the real source files with hot reload. Unlike IDE-only coding tools, Frontman sees the live DOM, component tree, computed CSS, routes, source maps, screenshots, console output, and server logs. That runtime context helps product managers, designers, and frontend teams fix copy, spacing, colors, layout bugs, and internal UI polish without guessing which file owns a rendered element. Works with Next.js, Astro, Vite, React, Vue, Svelte, and SvelteKit. BYOK model support includes OpenAI, Anthropic, OpenRouter, Google, xAI, Fireworks, NVIDIA, and more. Use Frontman when visual frontend edits get stuck in design QA, product review, or developer handoff.

Nx-powered Neural Networks for Elixir. Axon consists of the following components. Functional API – A low-level API of numerical definitions (defn) of which all other APIs build on. Model Creation API – A high-level model creation API which manages model initialization and application. Optimization API – An API for creating and using first-order optimization techniques based on the Optax library. Training API – An API for quickly training models, inspired by PyTorch Ignite. Axon provides abstractions that enable easy integration while maintaining a level of separation between each component. You should be able to use any of the APIs without dependencies on others. By decoupling the APIs, Axon gives you full control over each aspect of creating and training a neural network. At the lowest-level, Axon consists of a number of modules with functional implementations of common methods in deep learning.

Deep Chat is a highly customizable web component designed to simplify the integration of AI-powered chat interfaces into websites. It allows developers to embed a fully functional chatbot using minimal setup, while still offering extensive control over behavior, appearance, and integrations. Deep Chat supports connections to a wide range of AI services as well as custom backends, enabling flexible deployment for different use cases. It is built as a framework-agnostic solution, meaning it can work across various frontend environments, with additional support provided for React through a dedicated wrapper. Deep Chat includes advanced interaction capabilities such as speech input and output, file handling, and multimedia communication, making it suitable for rich conversational experiences. Internally, it uses a structured architecture that manages input, message handling, and service communication, allowing developers to intercept and customize requests and responses.

Traditional machine learning tools built on top of Nx. Scholar implements several algorithms for classification, regression, clustering, dimensionality reduction, metrics, and preprocessing.