Runs a local-first, full AI stack—LLM inference, chat UI, voice, agents, workflows, RAG, and image generation—deployable with one command. Auto-detects hardware and bootstraps a small model for instant chat while larger models download; supports Linux, Windows, macOS and optional cloud/hybrid modes.
A challenge repository for training the best language model that fits inside a 16,000,000‑byte (16MB) submission artifact; provides baseline training code, FineWeb bpb evaluation, a public leaderboard, and compute-grant instructions for short 8×H100 runs.
Cleaned reasoning dataset of problem→thinking→solution triplets derived from Opus 4.6, provided in Parquet with ~2,160 cleaned rows (original 3,305). Filters remove empty/short/refusal/non‑substantive responses; hosted on Hugging Face under Apache‑2.0.
Local LLM inference server for Apple Silicon that exposes an OpenAI-compatible API and a macOS menubar app. Uses continuous batching and a two-tier KV cache (RAM + SSD in safetensors) to persist context across restarts, enabling practical multi-model serving and fast local coding workflows.
Provides 1.06M web interaction trajectories (state, action, next_state) represented primarily as A11y trees for training browser world models and web agents. Covers diverse real‑web domains, English/Chinese pages, and long contexts (up to 30K tokens); residual PII and dynamic content may limit reproducibility.
Provides a reliability layer for self-hosted LLM tool-calling and multi-step agent workflows. Adds guardrails — rescue parsing, response validation, retry nudges, and a synthetic respond tool — and ships a Drop-in OpenAI-compatible proxy plus a WorkflowRunner for structured loops.
Optimizes websites for AI-first search by providing GEO-focused SEO audits: citation-readiness scoring, AI-crawler access checks, schema generation, platform-specific recommendations, and client-ready PDF reports — delivered as a Claude Code skill with CLI commands.
Desktop-first personal agent that compresses your connected accounts into a local memory tree and runs agentic workflows. Key features include 118+ one‑click integrations, TokenJuice token compression into an Obsidian‑style vault, model routing with optional local models (Ollama).
Aggregates and deduplicates stories from Hacker News, Reddit, RSS, Telegram, GitHub and more, then uses LLMs to score, enrich, and produce bilingual (EN/CN) daily briefings. Supports customizable sources, comment summarization, multi-provider scoring, and delivery via GitHub Pages, email, or webhooks — designed for self-hosted, configurable news digests.
A 26M-parameter LLM distilled for reliable function-call generation on tiny devices, with open weights, local finetuning tooling, and a web playground for on-device testing. Pretrained at scale then post-trained on a single-shot function-call dataset for tool integration.
Runs local AI models on Apple Silicon as an OpenAI‑compatible server, emphasizing low latency, prompt caching, and reliable tool-calling. Optimized for M1–M4 Macs with multimodal support and drop‑in compatibility for IDEs and agent frameworks.
Convenes 18 deliberately polarized AI personas to produce structured, multi-round deliberations on hard questions across multiple LLM providers. Key features: multi-provider auto-routing, enforced dissent/novelty rules, triad/panel modes and CLI integration for Claude Code/Codex. Good for high-stakes product, strategy, or safety decisions.