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154 lines
4.0 KiB
Markdown
154 lines
4.0 KiB
Markdown
# Vibe Coding in VS Code
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> Use DGX Spark as a local or remote Vibe Coding assistant with Ollama and Continue.dev
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## Table of Contents
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- [Overview](#overview)
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- [What You'll Accomplish](#what-youll-accomplish)
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- [Prerequisites](#prerequisites)
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- [Requirements](#requirements)
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- [Instructions](#instructions)
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- [Troubleshooting](#troubleshooting)
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---
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## Overview
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## DGX Spark Vibe Coding
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This playbook walks you through setting up DGX Spark as a **Vibe Coding assistant** — locally or as a remote coding companion for VSCode with Continue.dev.
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While NVIDIA NIMs are not yet widely supported, this guide uses **Ollama** with **GPT-OSS 120B** to provide a high-performance local LLM environment.
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### What You'll Accomplish
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You’ll have a fully configured DGX Spark system capable of:
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- Running local code assistance through Ollama.
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- Serving models remotely for Continue.dev and VSCode integration.
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- Hosting large LLMs like GPT-OSS 120B using unified memory.
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### Prerequisites
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- DGX Spark (128GB unified memory recommended)
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- Internet access for model downloads
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- Basic familiarity with the terminal
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- Optional: firewall control for remote access configuration
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### Requirements
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- **Ollama** and an LLM of your choice (e.g., `gpt-oss:120b`)
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- **VSCode**
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- **Continue.dev** VSCode extension
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## Instructions
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## Step 1. Install Ollama
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Install the latest version of Ollama using the following command:
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```bash
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curl -fsSL https://ollama.com/install.sh | sh
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```
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Start the Ollama service:
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```bash
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ollama serve
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```
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Once the service is running, pull the desired model:
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```bash
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ollama pull gpt-oss:120b
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```
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## Step 2. (Optional) Enable Remote Access
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To allow remote connections (e.g., from a workstation using VSCode and Continue.dev), modify the Ollama systemd service:
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```bash
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sudo systemctl edit ollama
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```
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Add the following lines beneath the commented section:
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```ini
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[Service]
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Environment="OLLAMA_HOST=0.0.0.0:11434"
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Environment="OLLAMA_ORIGINS=*"
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```
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Reload and restart the service:
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```bash
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sudo systemctl daemon-reload
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sudo systemctl restart ollama
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```
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If using a firewall, open port 11434:
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```bash
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sudo ufw allow 11434/tcp
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```
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## Step 3. Install VSCode
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For DGX Spark (ARM-based), download and install VSCode:
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```bash
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wget https://code.visualstudio.com/sha/download?build=stable&os=linux-deb-arm64 -O vscode-arm64.deb
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sudo apt install ./vscode-arm64.deb
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```
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If using a remote workstation, install VSCode appropriate for your system architecture.
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## Step 4. Install Continue.dev Extension
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Open VSCode and install **Continue.dev** from the Marketplace.
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After installation, click the Continue icon on the right-hand bar.
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Skip login and open the manual configuration via the **gear (⚙️)** icon.
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This opens `config.yaml`, which controls model settings.
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## Step 5. Local Inference Setup
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- In the Continue chat window, use `Ctrl/Cmd + L` to focus the chat.
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- Click **Select Model → + Add Chat Model**
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- Choose **Ollama** as the provider.
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- Set **Install Provider** to default.
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- For **Model**, select **Autodetect**.
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- Click **Connect**.
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You can now select your downloaded model (e.g., `gpt-oss:120b`) for local inference.
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## Step 6. Remote Setup for DGX Spark
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To connect Continue.dev to a remote DGX Spark instance, edit `config.yaml` in Continue and add:
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```yaml
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models:
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- model: gpt-oss:120b
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title: gpt-oss:120b
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apiBase: http://YOUR_SPARK_IP:11434/
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provider: ollama
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```
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Replace `YOUR_SPARK_IP` with the IP address of your DGX Spark.
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Add additional model entries for any other Ollama models you wish to host remotely.
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## Troubleshooting
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## Common Issues
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**1. Ollama not starting**
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- Verify Docker and GPU drivers are installed correctly.
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- Run `ollama serve` manually to view errors.
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**2. VSCode can’t connect**
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- Ensure port 11434 is open and accessible from your workstation.
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- Check `OLLAMA_HOST` and `OLLAMA_ORIGINS` in `/etc/systemd/system/ollama.service.d/override.conf`.
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**3. High memory usage**
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- Use smaller models such as `gpt-oss:20b` for lightweight usage.
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- Confirm no other large models or containers are running with `nvidia-smi`.
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