AI Topic: AI Development Libraries

A pure JavaScript port of Google's JAX ML framework that compiles and runs neural networks directly in the browser via auto-generated WebGPU kernels—with autodiff, JIT, and vectorization built in.

An open-source, TypeScript-first AI SDK that provides a unified interface across multiple AI providers to avoid vendor lock-in.

Independent AI model benchmarking platform providing comprehensive performance analysis across intelligence, speed, cost, and quality metrics

Keras is an open-source, high-level deep learning API that enables building, training, and deploying neural networks across JAX, TensorFlow, and PyTorch backends.

Open-source React component library and registry of 41 composable, accessible UI components built for shadcn/ui and Tailwind CSS.

End-to-end, open-source recipe to train and serve a small chat LLM (~560M params) for about $100 on one 8×H100 node, with tokenizer, pretrain→midtrain→SFT→optional RL, FastAPI web UI, and a KV-cached inference engine.

Open-source CLI and Python library to run prompts, chat, embeddings, schemas, and tool-use across OpenAI, Claude, Gemini, and local models (Ollama, llama.cpp). Stores logs and vectors in SQLite and is extensible via plugins.

Domain-specific language and toolchain for type-safe LLM functions, structured outputs, and multi-provider orchestration.

TypeScript framework for building and shipping MCP applications with file system routing, hot reloading, and flexible deployment options.

Open-source LLM gateway and Python SDK that unifies 100+ providers behind an OpenAI-compatible API with cost tracking, budgets, rate limits, and fallbacks.