Discover the Best AI Resources
Curated essentials, no noise — just what matters
Provides Gymnasium-style APIs and tooling to run isolated, networked execution environments for agentic reinforcement learning. Offers async/sync EnvClients, Docker/Kubernetes container providers, a web UI and CLI for scaffolding and deploying environments (Hugging Face Spaces); experimental and evolving.
Provides a Gymnasium-style API and tooling to create, deploy, and interact with isolated execution environments for agentic RL training. Includes async/sync clients, a web interface, CLI, Docker-based deployment, and Hugging Face Spaces integration.
Worked examples and reusable abstractions for fine-tuning open LLMs via the Tinker training API: you write the training loop while distributed execution runs remotely. Covers SFT, math/code RL, DPO, three-stage RLHF, distillation, and tool use.
Runs text-to-speech with instant voice cloning fully on-device, from phones to GPUs. Built on small LLM backbones (120M-360M params) plus a 50Hz neural codec; clones a voice from ~3 seconds of audio across English, Spanish, German, and French.
Enhances web AI chat interfaces (Gemini, AI Studio, Claude, ChatGPT) with folder-based conversation organization, timeline navigation, prompt vault, cloud sync, chat export, UI fixes and a plugin engine. Runs as a browser extension and includes cross-site prompt management and Mermaid rendering.
Turns clinical text into structured, de-identified clinical signals—entity extraction and PII de-identification—that run entirely on local hardware. Provides 1,000+ specialized medical NER models, multilingual support, Apple MLX acceleration, and Apache‑2.0 licensing.
Provides 99,870 system/user/assistant chat triples for defensive cybersecurity instruction‑tuning, with built‑in refusal patterns and mapping to OWASP, MITRE ATT&CK, NIST, and CIS standards; Apache‑2.0 licensed.
Enforces a brainstorm → plan → test-driven → review workflow on AI coding agents instead of letting them jump straight to code. Ships as composable skills that auto-trigger by context and run across Claude Code, Cursor, Copilot CLI, Gemini and more.
Packages Every's 'compound engineering' workflow into 26 slash commands for AI coding agents like Claude Code — brainstorm, plan, work, review, debug. Skews effort toward planning and review, and saves each run's lessons so the next task is easier.
Autonomously performs end-to-end data science tasks — from cleaning and exploration to modeling, visualization, and analyst-grade reports — via an agentic LLM. Open-source model, code, datasets and demos; supports vLLM deployment, Jupyter/CLI/Web UIs, and OpenAI-style APIs.
Provides a persistent, dependency-aware structured memory for coding agents — replacing scattered markdown plans with a versioned task/issue graph backed by Dolt. Agent-optimized features include JSON output, dependency tracking, zero-conflict IDs, and semantic compaction for long-horizon workflows.
A dependency-aware issue tracker for AI coding agents that stores tasks as a version-controlled graph in a Dolt database, so agents keep context across long-horizon work. Content-hash IDs prevent merge conflicts when multiple agents edit in parallel.