Drops Claude Code into GitHub Actions so it responds to @claude mentions in PRs and issues — answering questions, reviewing diffs, and committing fixes or features on a branch. Runs on your runners via the Anthropic API, Bedrock, or Vertex AI.
Enables bidirectional checkpoint conversion between Hugging Face and Megatron formats and provides a PyTorch-native training library with tensor/pipeline parallelism, FP8/BF16 mixed precision, SFT and PEFT (LoRA) support for large and multimodal models.
Translates full-length books, subtitles, and documents with LLMs while preserving original formatting and structure. Uses intelligent chunking to handle arbitrarily long files, supports local or cloud providers, and resumes interrupted jobs without losing progress.
Real-time 3D Gaussian Splatting renderer for web apps using THREE.js. Integrates splat and mesh rendering with a Rust + Wasm component, supports major splat formats (.PLY, .SPZ, .SOG) and targets broad WebGL2 support for mobile-friendly dynamic scenes.
Packages an AI agent's memory — data, embeddings, search indexes, and metadata — into one portable .mv2 file, replacing multi-service RAG stacks. Combines BM25 and HNSW search with temporal queries and sub-millisecond local reads, fully offline.
Parses the local JSONL logs that coding-agent CLIs write and turns them into token and cost reports, no API keys or telemetry. Breaks spend down by day, month, session, and Claude's 5-hour billing windows across Claude Code, Codex, Gemini CLI and more.
Wraps Claude Code as an MCP server that orchestrates 100+ specialized agents into self-organizing swarms — hierarchical, mesh, or adaptive consensus — backed by persistent vector memory, coordination hooks, and secure cross-machine federation.
Wraps Claude Code and Codex with an execution harness that turns one coding agent into coordinated swarms. A single init command adds ~98 agents, an MCP tool server, cross-session vector memory, and cross-machine federation.
Provides a community-curated database of AI model metadata—specs, pricing, and capabilities—and exposes it via a JSON API and a TOML-based contributor workflow for programmatic lookup and integration.
Autonomous Red Team agent that plans and executes realistic attack chains (reconnaissance, exploitation, pivoting, C2) while producing Rules of Engagement and an OPPLAN and running actions inside a hardened sandbox; intended for authorized red-team engagements and defensive verification.
Extends RAG beyond text: parses PDFs and Office files containing images, tables, equations, and charts, then queries them through one multimodal knowledge graph. Built on LightRAG, it replaces separate parsing and retrieval tools.