Private local model studio, AI chat, and agent workspace powered by WebGPU and WebLLM.
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Updated
Aug 12, 2026 - TypeScript
Private local model studio, AI chat, and agent workspace powered by WebGPU and WebLLM.
Detect and redact PII locally with SOTA performance
Extract structured data from local or remote LLM models
guidance for coding with agents in production, from pet projects to startups and big tech
A chrome extention for quering a local llm model using llama-cpp-python, includes a pip package for running the server, 'pip install local-llama' to install
面向本地部署模型的极简 Agent 平台 · A local-first minimalist agent platform with explicit context lifecycle controls.
entirely oss and locally running version of recall (originally revealed by msft for copilot+pcs)
A simple framework for using Claude Code or Codex CLI as the frontend to any cloud or local LLM on Apple Silicon. Connect locally via LiteLLM + MLX or LM Studio, or remotely via Z.AI, Gemini/Google AI Studio, DeepSeek, or OpenRouter.
Make the leaked Claude Code runnable with unified local model support.
A small VLM that sees everything
Bell inequalities and local models via Frank-Wolfe algorithms
A 💅 stylish 💅 local multi-model AI assistant and API.
Local-model (Ollama) integration for DeepSeek Harness: discover, pull, remove, and inspect local models, route requests to them by task type or keyword with automatic fallback to the cloud, and get a one-shot status overview via /ollama.
The AI-OS in userspace.
LiAgent OS is a local-first AI agent OS for building a private personal assistant with governed autonomy across local models and hybrid cloud services. It brings conversation, tool use, multi-agent orchestration, task scheduling, heartbeat execution, human approval, and auditability into one long-lived loop.
Applied Geometric Intelligence (AGI) - See papers for specifics
Facts the model cannot know -- the date, the machine, and your git state -- delivered to pi as <pi-note> blocks.
Open-source AI Software Engineer CLI and terminal coding assistant built in Go.
Main code chunks used for models in the publication "Exploring the Potential of Adaptive, Local Machine Learning (ML) in Comparison ton the Prediction Performance of Global Models: A Case Study from Bayer's Caco-2 Permeability Database"
Auto-discover local model providers (Ollama) and register their models with Pi on startup. Per-model context windows and capabilities, no /reload required.
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