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Local-first voice cloning studio that runs on your machine to clone voices, generate speech in 23 languages, apply audio effects, and compose multi-voice projects. Includes five switchable TTS engines, a REST API, and native GPU/MLX support for privacy-sensitive offline workflows.
Fetches multi-source content (webpages, YouTube, PDFs, WeChat, paywalled articles, podcasts), uploads it to Google NotebookLM, and generates outputs such as podcasts, PPTs, mind maps, or quizzes. Differentiators: automatic paywall-bypass pipeline, Claude Code Skill integration, and CLI + MCP components for WeChat and document scraping.
A transparent proxy that lets Claude Code CLI and the VSCode extension run without an Anthropic API key by routing requests to NVIDIA NIM, OpenRouter, LM Studio, or llama.cpp; supports per-model mapping, thinking-token parsing, and messaging integration.
Models an AI agent's context as a file system, unifying memory, resources, and skills instead of flat vector RAG. Uses L0/L1/L2 tiered loading to cut tokens, directory-recursive plus semantic retrieval, and visualized retrieval traces for debugging.
Self-hosted coding assistant that runs frozen local LLMs with constraint-driven planning, energy-based verification, and self-verified repair to produce verified code. Emphasizes offline inference (no cloud), Docker/bare-metal deployment, and requires a 16GB+ GPU.
Self-hosted personal AI agent runtime that runs chats, tools, automations and long-term memory for persistent workflows. Small, readable core with a bundled WebUI, multi-chat integrations, an OpenAI-compatible API and a Python SDK for easy extension and deployment.
Multimodal OCR and document-understanding toolkit for recognizing complex layouts, tables, formulas and code. Uses Multi-Token Prediction and stable RL for better training; ships as a 0.9B-parameter model with a Python SDK and deployment guides for vLLM, SGLang and Ollama.
Enables research-grade character animation with neural networks in a single NumPy/PyTorch environment — train models, run inference, and visualize results without leaving Python. Includes ECS-style architecture, mocap import (GLB/FBX/BVH), built-in renderer, and headless/standalone modes for rapid prototyping.
An open, intuition-first textbook that teaches the maths, computing, and practical foundations needed for AI engineering. Organized into focused chapters (vectors, matrices, calculus, ML, NLP, CV, GPU/Inference, ML systems) with code-first explanations and interview-ready emphasis.
Train robot reinforcement-learning agents with a heterogeneous runtime that streams CPU-parallel physics simulations (MuJoCo / Motrix) via shared memory into GPU/accelerator policy learners; provides a unified CLI, cross-platform backend support and demo checkpoints.
Generates complete Godot 4 projects from a natural-language game description: it designs the architecture, generates assets, writes C# code, runs the project, captures screenshots for visual QA, and iterates until a runnable game repo is produced. Requires API keys and Godot .NET.
Turns natural-language directions into end-to-end video editing workflows: LLM-powered planning, media search/organization, ASR rough-cut, and reusable Style Skills for consistent storytelling. Integrates agent Skills (OpenClaw/Claude Code) and optional AIGC transitions.