n8n-io/self-hosted-ai-starter-kit

The Self-hosted AI Starter Kit is an open-source template that quickly sets up a local AI environment. Curated by n8n, it provides essential tools for...

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Summary Information

Updated 4 minutes ago
Added to GitGenius on September 3rd, 2026
Created on February 23rd, 2024
Open Issues & Pull Requests: 4 (+0)
GitHub issues: Disabled - open counts may still include pull requests.
Number of forks: 3,814
Total Stargazers: 15,234 (+1)
Total Subscribers: 187 (+0)

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Detailed Description

Self-hosted AI Starter Kit is a Docker Compose template that quickly sets up a local AI and low-code development environment with self-hosted components.

The kit addresses the challenge of assembling and configuring multiple AI tools for local development by bundling them together in a pre-configured Docker Compose setup. It combines n8n, a low-code platform with over 400 integrations and AI components, with Ollama for running local language models, Qdrant as a vector store, and PostgreSQL for data persistence. This approach eliminates the friction of individually installing and networking these tools, allowing developers to start building AI workflows immediately after cloning the repository and running Docker Compose.

The starter kit suits developers who want to build self-hosted AI applications without cloud dependencies or data leaks. It is designed for use cases like AI agents for scheduling, secure PDF summarization, enhanced Slack bots, and private financial document analysis. The kit includes platform-specific setup instructions for Nvidia GPU, AMD GPU on Linux, and Apple Silicon Macs, accommodating different hardware configurations. For Mac users unable to expose GPU to Docker, the template supports running Ollama locally on the host machine while connecting to it from the n8n instance running in Docker.

Development activity shows consistent engagement with the repository. The project maintains clear documentation with platform-specific installation guidance and troubleshooting steps. Updates address hardware compatibility across different systems, indicating responsiveness to user needs across diverse environments. The inclusion of example workflows and step-by-step quick-start instructions demonstrates attention to reducing barriers for new users.