Compresses high-dimensional embeddings into low-bit TurboQuant indexes for fast, memory-efficient local vector search. Supports online ingest (no train/rebuild), SIMD kernels that match or beat FAISS, per-vector length-renormalization, and runtime allowlists — suited for privacy-sensitive, low-latency RAG.
Maps a codebase plus docs, PDFs, media and configs into a local, queryable knowledge graph; parses code with a local tree-sitter AST (no LLM), uses configurable backends for semantic extraction of non-code, and outputs graph.json, graph.html and a brief report.
Provides a cloud-backed shared memory and skill-propagation layer for coding agents: captures session traces, mines recurring patterns into reusable SKILL.md, and shares capabilities across agents in real time. Features hybrid semantic+lexical search, BYOC storage, and a VFS for traces — built for team workflows and agent orchestration.
Stores conversation history verbatim and retrieves it via local semantic search with a structured index (wings/rooms/drawers). Pluggable vector backends and a local-first default mean high recall (benchmarked) without cloud or API keys—useful for agent memory and private RAG.
Desktop app for local voice cloning, real-time dictation, and end-to-end video dubbing using zero-shot TTS across 600+ languages; features multi-engine TTS/ASR, speaker diarization, vocal isolation, batch pipelines, and invisible audio watermarking — all run fully offline.
Turns a codebase into a live structural knowledge graph that coding agents can query in milliseconds. Bi-temporal, replay-aware indexing of symbols and relationships performed locally with zero LLM API calls; Rust-native, MCP-native integrations and fast incremental updates.
Provides a local-first web-intelligence layer for AI agents: search, fetch, crawl, extract, cache, find-similar and agent-style research without API keys or per-query billing, running as an MCP server, REST daemon, or SDK.
Provides deduplicated, sanitized Usenet posts (1980–2013) for language-model pretraining and linguistic research. Includes a ~103.1B-token full corpus (408M posts) with freely downloadable sample files; full corpus access requires a license and PII redaction was applied.
Detects and masks personally identifiable information (PII) in text using a bidirectional token-classification model for high-throughput, on‑premises sanitization. Key traits: 1.5B parameters, 128k-token context, Apache 2.0 license, and tunable precision/recall operating points.
Collects ML Intern coding-agent session traces as Claude‑Code‑style JSONL event streams for viewing with the Hugging Face Agent Trace Viewer. Each file is one session (messages, tool calls, outputs, timestamps); automated scrubbing is applied but no comprehensive human redaction—treat as potentially sensitive.
A Chinese public-transit route-planning dataset for training and benchmarking LLMs that generate structured transit routes from origin–destination pairs. Releases include a large CPT corpus, SFT train/test splits, and a 30K real-world benchmark; anonymized and real testsets are provided for privacy-aware, fair evaluation.