Terminal rebuilt around AI agents: orchestrate Claude Code, Codex, and Warp's own agent in parallel, each with codebase indexing and scoped permissions. Run them locally or in the cloud, and bring your own model via Bedrock, LiteLLM, OpenRouter.
Runs pretrained diffusion models for image, video, and audio generation through composable pipelines. It separates pipelines, schedulers, models, adapters, and memory optimizations so teams can prototype quickly without locking into one model family.
Enlarges and enhances low-resolution images using AI models (Real-ESRGAN) through a cross-platform desktop app. Runs on a local NCNN/Vulkan backend (requires a Vulkan-compatible GPU), offers an Electron GUI plus a CLI backend (upscayl-ncnn), and supports custom models for different image types.
Runs a local AI assistant across WeChat/Feishu/DingTalk/WeCom/QQ/MP/Web, with an Agent mode for task planning, long-term memory, Skills, and tool calling so it can keep working toward goals rather than just chat.
Framework for building multi-channel AI assistants that autonomously plan tasks, invoke tools/skills, and keep long-term memory; supports many LLM providers and channels (WeChat, Feishu, QQ, web) for local or server 24/7 deployment.
Runs a self-hosted web server and React-based UI to generate, edit, and manage images using Stable Diffusion, SDXL and other foundation models. Includes a model manager, unified canvas, node-based workflows, gallery, and support for ckpt, diffusers and some gguf checkpoints.
Browser-based control panel for running Stable Diffusion locally, built on Gradio. Bundles txt2img, img2img, inpainting, outpainting, and upscalers (ESRGAN, GFPGAN, CodeFormer), plus an extension ecosystem and support for NVIDIA, AMD, and Intel GPUs.
Turns text prompts into images through latent diffusion, from local-ready releases to professional SD 3.5 models. Its impact comes from deployability: self-hosting, API access, and community tooling made image generation broadly hackable.
Unifies successive YOLO generations — YOLOv8, YOLO11, YOLOv3 and newer — under one package and a single `YOLO` API spanning detection, segmentation, classification, pose, oriented boxes and tracking, plus one-line export to ONNX, TensorRT and CoreML.
Smart model router for personal AI agents that sends each request to the cheapest model capable of handling it — cutting API costs by up to ~70%. Uses a fast 23-dimension scorer, automatic fallbacks, per-tier controls, and supports local Docker self-hosting or a cloud app; ideal for cost-sensitive personal agents.