Thoth – open-source Local-first AI Assistant
Thoth is a local-first, open-source AI assistant designed to prioritize user control and data privacy by keeping durable data on the user's device. It offers a wide range of functionalities including a knowledge graph, design studio, automation workflows, and multi-channel messaging, with optional integration of cloud-based AI models. The application runs natively on Windows and macOS with no need for complex setup, emphasizing ease of use and personal AI sovereignty.
- ▪Thoth stores user knowledge as a graph of entities and relationships, supporting export to an Obsidian-compatible wiki vault.
- ▪It includes a Designer Studio for creating documents, mockups, and media, with support for image and video generation via integrated AI services.
- ▪The assistant uses a LangGraph ReAct agent with 30 core tools, enabling web browsing, file management, email, calendar access, and safe shell execution with approval guards.
- ▪Thoth supports automation through scheduled workflows with conditional logic, approvals, and background execution modes.
- ▪All API keys and subscription tokens are stored in the operating system's credential store, and the app operates without accounts, servers, or telemetry.
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𓁟 Thoth — Personal AI Sovereignty Thoth is a local-first AI assistant for personal AI sovereignty: a desktop agent with memory, tools, workflows, design creation, messaging, plugins, and optional cloud models while your durable data stays on your machine. It runs fully local through Ollama with 39 curated tool-calling models, or you can opt into OpenAI, Anthropic, Google AI, xAI, OpenRouter, and ChatGPT / Codex when you want frontier reasoning or do not have a GPU. API keys and in-app subscription tokens are stored in the OS credential store when available; Thoth has no account system, server, or telemetry pipeline. 🖥️ One-click install on Windows & macOS — download, run, done. No terminal, Docker, or config files required. Get it here.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Hacker News: Front Page.