Multi-agent framework that assigns GPT roles (PM, engineer, QA) to solve complex software tasks end-to-end.

High-throughput, memory-efficient LLM inference engine with PagedAttention and continuous batching.

Lightning-fast open-source search engine with typo-tolerance, semantic hybrid search, and sub-50ms response times.

ML experiment tracking and visualization — log metrics, hyperparameters, models, and media in real time.

Official GitHub MCP server — give your AI agent full read/write access to repos, issues, PRs, and actions.

Hugging Face's state-of-the-art library for diffusion-based image, video, and audio generation models.

The Natural Language Toolkit — Python's foundational NLP library for tokenization, POS tagging, parsing, and corpora.

Official TypeScript/JavaScript SDK for building MCP servers and clients — the Node.js foundation for the Model Context Protocol.

Fast and flexible image augmentation library with 70+ transforms for computer vision model training.

End-to-end ML lifecycle platform — experiment tracking, model registry, serving, and LLM evaluation.

In-process OLAP SQL database that runs inside your Python, R, or Node.js process — no server required.

Fast, memory-mapped dataset library for NLP and ML — 50,000+ datasets, streaming, and Arrow-backed processing.

Conversational AI coding agent that builds entire codebases from natural-language specs with one prompt.

Ultra-fast tokenizer library (Rust core) — BPE, WordPiece, SentencePiece — tokenize GBs in seconds.

Industrial-strength NLP library for Python with pre-trained pipelines for tokenization, NER, parsing, and more.

Low-code visual builder for LLM-powered agents and multi-step AI workflows with 100+ pre-built components.

Distributed Python framework for scaling ML workloads — training, serving, hyperparameter tuning, and pipelines.

Drop a screenshot or Figma design and get clean HTML/Tailwind/React/Vue code generated by GPT-4o or Claude.

Open-source AI software engineering agent that writes, edits, runs, and tests code autonomously in a sandboxed environment.

Apache-2.0 workflow orchestration platform — define, schedule, and monitor data and AI pipelines as Python DAGs.

The world's most popular computer vision library with Python bindings — image processing, video, and ML pipelines.

Run PyTorch training scripts on any hardware — single GPU, multi-GPU, TPU — with minimal code changes.

High-performance, model-agnostic Python framework for building, running, and managing production AI agents at scale.

Open-source durable execution platform for building reliable distributed workflows and long-running processes.