AI Infra2022
A continuously-updated, categorized self-hosting guide that catalogs tools, deployment notes and resources for containers, networking, home automation and running LLMs/chatbots locally; provided as a long, structured README with links and quick setup tips.
AI Audio2024
Provides low‑latency on‑device speech-to-text, intent recognition, and text-to-speech for building real‑time voice agents and interfaces. Streaming-optimized models, incremental caching, multilingual TTS/ASR and cross-platform bindings (Python, iOS, Android, Linux, Raspberry Pi) target live voice use cases where sub-200ms responsiveness matters.
AI Client2026
Provides a local browser workspace for browsing and managing pi coding agent sessions — real-time chat, model configuration, skill management, and project file preview. Runs from a single npx/global install, scopes file access to the selected project, and follows Git worktrees.
AI Agent2026
Runs an LLM-driven agent loop that iteratively proposes, applies, tests, and commits small repo changes—each successful iteration becomes a separate git commit while failures are rolled back or preserved for repair. Supports multiple agent backends, worktrees for concurrency, live terminal status, and optional per-iteration pushes.
AI Agent2026
Lets AI coding agents compile your documents and chat histories into a maintained Obsidian vault: it ingests sources, distills them into interconnected markdown pages, tracks deltas and provenance, and exposes query/lint/export skills across many agents.
AI Agent2026
Generates editorial-quality diagrams as self-contained HTML files with inline SVG across 27 visual types; includes brand onboarding, agent-skill integrations (Claude Code, Codex, Pi), draw.io/Mermaid import, and static-first output with optional accessible motion.
AI Agent2026
Runs coding and long-running research workflows inside a persistent IPython environment with programmatic subagents and a durable 'Continual Harness' for session-level refinements. Key features include recursive subagents (RLM), executable Python skills, background daemon sessions, and evidence-backed local refinements. Best for reproducible, long-horizon coding, experiments, and evaluation pipelines where auditable agent-driven updates matter.
AI Dataset2026
Collects raw coding-agent sessions—developer prompts, model replies, tool calls, and command output—donated from public repositories and anonymized locally. Organized by agent harness (raw session files + Parquet table), useful for studying agent behavior and tool use; anonymization is best-effort.
AI Dataset2026
Provides verified, model-attested end-to-end agent coding and debugging trajectories (JSONL). Each whole-session trace was produced by moonshotai/kimi-k3 on the pi/openrouter runtime, passed acceptance tests and independent model screening — useful for SFT, distillation, and analyzing tool-use behavior.
AI Dataset2026
10,005 single-turn prompts and metadata derived from Ox Alpha chat traces, labeled by category, subcategory, and difficulty. Built for response-teacher generation and distillation workflows, with topic and difficulty distributions to aid dataset curation.