Silo — Local AI Coding Assistant

A fully local AI coding assistant for VS Code. No API keys, no cloud, no data leaving your machine.

Powered by Ollama + Qwen2.5-Coder.

Requirements

• Ollama installed and running
• A capable GPU (8GB+ VRAM recommended) or fast CPU
• The Silo backend running locally

Setup (one time)

1. Install Ollama

Download from ollama.com/download and install it.

2. Pull the model

Open a terminal and run:

ollama pull qwen2.5-coder:32b

Lower VRAM? Use a smaller model instead:

ollama pull qwen2.5-coder:14b

3. Download and start the backend

Clone the repo and start the backend:

git clone https://github.com/danielmadridg/silo.git
cd silo

# Create virtual environment
cd backend
python -m venv .venv

# Windows
.venv\Scripts\activate
# Mac/Linux
source .venv/bin/activate

pip install fastapi "uvicorn[standard]" httpx pydantic sse-starlette aiofiles
uvicorn main:app --host 127.0.0.1 --port 8942

On Windows you can also just double-click start-backend.bat

4. Install the extension

Install from the VS Code Marketplace by searching Silo or from the Extensions panel.

Features

• Chat panel — ask anything about your code with full project context
• Inline completions — Tab to accept AI suggestions as you type
• File analysis — detect bugs, performance issues and get refactoring suggestions
• Inline refactoring — select code, give an instruction, changes apply directly in the editor
• Code explanation — select any code and ask Silo to explain it

Usage

Access commands via Ctrl+Shift+P (or Cmd+Shift+P on Mac).

Right-click on selected code for quick access to Refactor and Explain.

Configuration

To use a different model, edit backend/config.py:

MODEL_NAME = "qwen2.5-coder:14b"  # or any model in Ollama

Source

github.com/danielmadridg/silo