Cross-platform downloader that uses AI-assisted chunking and acceleration to improve success rates across protocols. Supports HTTP/FTP/M3U8/MPEG‑DASH/Magnet/BT plus YouTube/Bilibili parsing, a browser extension, aria2-compatible RPC and an Android client — aimed at multi-protocol, long-running and streaming download tasks.
Runs open-weight LLMs (Llama, Gemma, Qwen, GGUF) offline on your machine, with an optional bridge to OpenAI/Anthropic/Mistral. Exposes an OpenAI-compatible API at localhost:1337, so SDK code built for OpenAI switches by changing one base URL.
Coordinates multiple LLM agents that converse to solve a task, splitting work across customizable roles that call tools, run code, and loop in humans. The v0.4 redesign adds async messaging and Python/.NET interoperability across distributed networks.
Detects file content types with a compact deep‑learning model that runs in milliseconds on a single CPU. Trained on ~100M samples across 200+ content types; offered as a Rust CLI plus Python, JS, and Go bindings for large‑scale security and file‑routing use.
Role-playing LLM agents — CEO, CTO, programmer, tester — collaborate through staged dialogues to turn a one-line prompt into a working software project. Now generalized into a zero-code platform for building custom multi-agent workflows beyond coding.
Converts microphone or streamed audio to text with sub-second latency, pairing WebRTC/Silero voice-activity detection and wake-word activation with swappable local backends — faster-whisper by default, plus whisper.cpp, Moonshine, and sherpa-onnx.
Agent framework for building tool-using applications on Qwen 3+ LLMs. Provides function calling, MCP, a Dockerized code interpreter, and RAG over documents up to 1M tokens; powers the Qwen Chat backend and a Chrome browser-assistant extension.
Swaps a face from a single photo onto a live webcam feed or video in real time, using the inswapper_128 model with GFPGAN enhancement. Runs on NVIDIA, Apple Silicon, and Intel GPUs, with a built-in filter that blocks explicit or sensitive media.
Converts videos between languages by transcribing audio, translating subtitles, and producing AI dubbing—supports local and online ASR/LLM/TTS providers, speaker diarization, voice cloning, and GUI/CLI workflows for batch or headless use.
Self-hosted browser chat interface for interacting with local or remote LLMs. Supports multiple backends (Ollama, OpenAI-compatible endpoints, llama.cpp), RAG/document chat, plugins/actions, and Docker-based deployment — aimed at teams that need private, customizable LLM UIs.
Generates expressive multilingual speech from text, with sub-word control over prosody and emotion via inline tags like [whisper] or [angry]. Handles multi-speaker, multi-turn dialogue; the weights ship under a research-only license.
Builds stateful LLM agents whose memory persists across sessions: a tiered, self-editing memory system lets an agent rewrite its own context window so it remembers, learns, and improves over time. Model-agnostic, with Python/TypeScript SDKs.