rag-code-mcp

🐳 Docker Setup for RagCode

This guide explains how to run the RagCode infrastructure (Qdrant + Ollama) using Docker, while leveraging your existing local Ollama models.

Why run Ollama in Docker?

• Isolation: Keeps your system clean.
• Consistency: Ensures you run the exact version required.
• Integration: Easy to orchestrate with Qdrant via docker-compose.

🚀 The “Smart” Setup (Model Mapping)

We have configured docker-compose.yml to map your local Ollama models (~/.ollama) into the container. This means:

1. You don’t need to re-download models.
2. Models downloaded inside Docker appear on your host.
3. You save massive amounts of disk space.

Prerequisites

• Docker & Docker Compose installed.
• For GPU Support (Recommended): NVIDIA Container Toolkit installed.
• Existing models in ~/.ollama (optional, but recommended).

Usage

1. Start the stack:

   docker-compose up -d
   

2. Verify Ollama is running:

   docker logs ragcode-ollama
   

3. Check available models (inside container):

   docker exec -it ragcode-ollama ollama list
   

   You should see all your locally downloaded models here!

4. Pull a new model (if needed):

   docker exec -it ragcode-ollama ollama pull phi3:medium
   

⚠️ Troubleshooting

“Error: could not connect to ollama”

• Ensure port 11434 is not being used by a local Ollama instance.
• Stop your local Ollama before running the container: systemctl stop ollama or pkill ollama.

GPU not working

• If you don’t have an NVIDIA GPU or the container toolkit, remove the deploy section from docker-compose.yml to run in CPU-only mode (slower).

This site is open source. Improve this page.