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Press a configurable shortcut, speak, and have your words transcribed and pasted into the active app. Runs Whisper or the CPU-friendly Parakeet V3 fully offline; a Tauri + Rust build with Silero voice-activity detection and optional GPU acceleration.
Retrieval-augmented generation framework for videos spanning hundreds of hours, runnable on a single RTX 3090. Builds multi-modal knowledge graphs over visual and audio content so you can query and chat across many long videos at once.
Lets you build, generate, and run multi-agent LLM workflows from natural-language prompts with no coding. Automatically profiles agents, creates tools/workflows, and supports multiple LLM providers plus CLI/Docker deployment.
Provides real-time, local audio recording and transcription on macOS using Whisper and Parakeet engines, with global hotkeys and hold-to-record behavior. Includes model download, microphone selection, drag-and-drop file transcription, multilingual auto-detection and Asian-language autocorrect; Apple Silicon only.
Performs automated, citation-backed deep research across web, arXiv, PubMed and your private documents using configurable local or cloud LLMs. Runs locally with per-user SQLCipher encryption, Docker/pip installs, LangChain integrations, and an MCP server for assistant integration.
Optimizes and tests AI prompts in the browser, comparing original and rewritten versions side by side against any connected model. Runs fully client-side—keys go straight to the provider—and ships as web app, Chrome extension, and desktop builds.
Feeds simplified Figma layout and style metadata to AI coding agents like Cursor and Claude Code to implement designs in one shot. Sends descriptive JSON (1px border, 16px padding) rather than code, leaving framework choices to the model.
Desktop AI client that unifies cloud and local LLMs, tool calling (MCP), installable Skills, and ACP agent integration into a single multi-window workspace. Supports local Ollama models, multi-provider configuration, remote control, and privacy-focused local storage.
Curates 80+ hands-on LLM-powered examples, tutorials and recipes for building agents, RAG systems, voice assistants, and agentic workflows. Includes starter templates, course playlists, and reference apps for rapid prototyping and learning.
Provides high-throughput, low-latency GPU communication kernels for Mixture-of-Experts (MoE) and expert-parallel workloads, with NVLink↔RDMA-aware forwarding, FP8/BF16 support, and low-latency RDMA hooks for inference decoding.
Performs fast static type checking and provides a language server with code navigation, semantic highlighting, and completions for Python. Processes ~1.85M lines/sec and completes IDE rechecks typically under 10ms — intended for responsive editor workflows and large codebases.