Provides a Spotify-like local UI for running ACE-Step 1.5 to generate full songs (including vocals), batch variations, and manage a local music library, with reference-audio styling and built-in editing/stem tools for users running the model locally.
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.
Converts scene intent into production-ready Seedance 2.0 prompts, reference-role mappings, and IP-safe rewrites for multimodal (text/image/audio/video) video generation. Ships as a modular agent-skill OS with multilingual examples, troubleshooting tools, and pro filmmaker handoff artifacts.
Generates production-ready App Store and Google Play screenshots from app metadata and style preferences using AI. Scaffolds a Next.js project, composes ad-style slides with localized/RTL support, and exports PNGs at all required Apple and Google resolutions.
Multi-agent workbench for long- and short-form fiction, scriptwriting, interactive narrative games and multilingual translation. Offers Studio/CLI/TUI tools that plan, draft, audit and revise chapters while maintaining structured story state, branching forecasts, cover generation and multi-model routing. Suited for authors and teams automating long-horizon narrative workflows.
Transforms articulated 3D asset creation into a programmatic, LLM-driven code-generation workflow that produces objects with semantic parts, robust geometry, and physical joints. Includes CLI generation, a local viewer, and pipelines for large-scale dataset contribution.
Generative-AI-enabled timeline video editor for macOS that lets creators generate and edit videos and images directly inside the timeline. Includes a local MCP server for agent integrations (Claude/Codex/Cursor); editor is open-source while generative processing is closed-source and subscription-based; macOS 26 on Apple Silicon only.
An open text-to-image generation model built on an 8B Diffusion Transformer that focuses on layout-sensitive, text-heavy, and instruction-following image synthesis. Notable for accurate text rendering, structured/compositional generation (posters, comics), and ability to run on consumer 24GB GPUs when paired with prompt enhancement.
Unifies multimodal understanding, reasoning, and image generation in a single end-to-end architecture using the NEO-unify paradigm. Models pixels and words jointly without a separate visual encoder, and provides interleaved image–text generation, infographic editing, and GGUF/low‑VRAM inference options.
A 1.4M image–text style dataset for text-to-image generation and style transfer, produced by mapping 170K curated style prompts to 400K content prompts via Qwen-Image to yield strong intra-style consistency. Designed for training and evaluating style-aware generative models; license: other.
Generates expressive, scene-aware speech from XML-style prompts and supports zero-shot voice cloning from 10–20s references. Produces emotional acting, ambient SFX, multilingual output, and continuous long-form narration; requires large model weights and gated Gemma text-encoder access.
Contains ~1,973 distilled roleplay conversations with character-perspective chain-of-thought traces (<think> blocks) for fine-tuning persona-focused chat models. Includes teacher provenance, safety/review flags, and filters for NSFW/borderline samples — suited for SFT and character retention tests.