Docker-Powered RAG for Your Private Codebase

Ever wish you could ask questions about your own internal documentation or a sprawling private codebase and get instant, accurate answers? Manually searching through READMEs, wikis, and source files is slow and often misses the context you need. Setting up a Retrieval-Augmented Generation (RAG) system to solve this usually means a mountain of configuration, service orchestration, and infrastructure headaches.

What if you could spin up a private, AI-powered question-answering system for your internal knowledge with just a few commands? That's exactly the itch the Knowledge Base Self-Hosting Kit aims to scratch.

What It Does

The Knowledge Base Self-Hosting Kit is a pre-packaged, Docker-powered system that builds a RAG pipeline for your private documents and code. You feed it your files—markdown, PDFs, text files, source code—and it handles the rest: chunking the text, generating embeddings, storing them in a vector database, and providing a query interface. The end result is a local web application where you can ask questions in natural language and get answers sourced directly from your provided materials.

Why It's Cool

The clever part here is the packaging. This kit bundles all the moving parts of a RAG system—Ollama for running local LLMs (like Llama 3.1 or Mistral), Open WebUI for a clean chat interface, and the necessary backend logic for ingestion and retrieval—into a cohesive stack defined with Docker Compose. It turns a complex architecture into a single docker-compose up command.

It's designed for privacy and simplicity. Since everything runs locally in Docker containers, your proprietary code and docs never leave your machine. There's no need for API keys to external services, and you can tune the underlying local LLM to your needs. It's a fantastic solution for teams wanting to create a searchable, conversational interface for their internal wiki, legacy code documentation, or even a personal knowledge base.

How to Try It

Getting started is straightforward, assuming you have Docker and Docker Compose installed.

1. Clone the repository:

   git clone https://github.com/2dogsandanerd/Knowledge-Base-Self-Hosting-Kit
   cd Knowledge-Base-Self-Hosting-Kit
   

2. The key step is adding your own knowledge. Place all the documents, markdown files, or code you want to index into the data/ directory within the project.

3. Spin up the entire stack:

   docker-compose up
   

4. Once the containers are running (the first boot will pull images and may take a minute), navigate to http://localhost:3000 in your browser. You should see the Open WebUI interface. You can start asking questions about the content you placed in the data/ folder.

For detailed configuration options, like changing the local LLM model, check out the docker-compose.yml file and the documentation in the project's README.

Final Thoughts

As codebases and internal documentation grow, tools like this shift from being a neat trick to a genuine productivity booster. The Knowledge Base Self-Hosting Kit lowers the barrier to experimenting with private RAG systems significantly. It's not a magical, production-ready enterprise suite, but it's an excellent, zero-cost starting point. It's perfect for a developer weekend project, a small team looking to make their docs more accessible, or anyone curious about how RAG works under the hood without managing a dozen services manually. Give it a spin with your notes or a project repo and see if it answers your questions.

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