AI Infrastructure

igel lets users train, test, and use machine learning models without writing code.

Synthetic data and AI feedback pipelines can be built with Distilabel, a framework based on research papers.

LiteLLM provides an AI gateway and LLM proxy with model routing, usage tracking, spend controls, and support for many providers.

Build neural networks and support machine learning research with Sonnet, a library based on TensorFlow.

UnDatasIO transforms unstructured documents into data assets for AI applications, including document parsing.

Promptitude lets teams test, manage, and improve prompts for integrating GPT into apps and workflows.

Omnisearch indexes audio, video, documents, and text so users can search across their website content.

Lucent brings the Lucid library approach to PyTorch, according to its repository description.

Hypernets offers a general automated machine learning framework for developing end to end AutoML toolkits in specific domains.

C-based/Cached/Core Computer Vision Library, A Modern Computer Vision Library.

This site explains machine learning operations, commonly shortened to MLOps.

Fiber presents a simple approach to distributed computing for AI workloads.

The Feast repository describes an open source feature store for AI and machine learning projects.

Unsloth provides a local interface for running and training language and diffusion models, including GGUF and MLX support.

MLX provides an array computing framework designed for Apple silicon devices.

Kubeflow provides a machine learning toolkit for deploying workflows on Kubernetes.

The Hydrosphere repository describes an MLOps platform for machine learning operations.

OpenAI compatible API for LLMs and embeddings (LLaMA, Vicuna, ChatGLM and many others).

Parris, the automated infrastructure setup tool for machine learning algorithms.

Supermemory provides memory and continual-learning tools for AI agents through an API, plugins, and an MCP interface.

Entroly reduces AI context size with reversible compression and receipts for recovering the original content.

Flama serves predictive and generative AI models as APIs, with compatible endpoints, a chat interface, and MCP support.

Upstage builds large language models and document-processing engines for workplace workflows.

Keras provides a deep learning API for building and training machine learning models.