How to Use Local AI Models with Shakespeare#

Want complete control over your AI-powered website building? Local AI models offer enhanced privacy, faster responses, and dramatically reduced costs in your development workflow. With Shakespeare's support for local models including GPT-OSS, DeepSeek-R1, Gemma 3 and other models running on your machine, you can build websites entirely offline while keeping your projects and data completely private.

Why Choose Local AI Models?#

Complete Privacy#

• No data ever leaves your machine
• Perfect for sensitive business projects
• Full control over your intellectual property
• No concerns about terms of service changes

Zero Ongoing Costs#

• Pay once for hardware, use forever
• No per-request charges
• No monthly subscriptions
• Unlimited usage without budget worries

Full Customization#

• Fine-tune models for your specific needs
• Complete control over model behavior
• No rate limits or usage restrictions
• Experiment freely without costs

Getting Started: Installing Ollama#

System Requirements#

Installation Steps#

macOS Installation#

# Install via Homebrew
brew install ollama

# Or download from ollama.ai
curl -fsSL https://ollama.ai/install.sh | sh

Linux Installation#

# Install via curl
curl -fsSL https://ollama.ai/install.sh | sh

# Or use package manager
sudo apt install ollama  # Ubuntu/Debian
sudo pacman -S ollama     # Arch Linux

Windows Installation#

1. Download the installer from ollama.ai
2. Run the installer as administrator
3. Restart your system after installation

Choosing the Right Model#

For Website Building: Top Local Model Recommendations#

GPT-OSS - OpenAI's Open-Weight Powerhouse#

ollama pull gpt-oss

Best for: Powerful reasoning, agentic tasks, versatile developer use cases

Trade-offs:

• ✓ Excellent at complex web development
• ⚠ Requires decent hardware

DeepSeek-R1 - Enterprise-Grade Reasoning#

ollama pull deepseek-r1

Best for: Open reasoning with performance approaching O3 and Gemini 2.5 Pro

Trade-offs:

• ✓ Leading-edge reasoning capabilities
• ⚠ Slower inference due to reasoning depth

Gemma 3 - Google's Single-GPU Solution#

ollama pull gemma3

Best for: Google's most capable model that runs on a single GPU

Trade-offs:

• ✓ Excellent performance on consumer hardware
• ⚠ May need more guidance for complex tasks

Quick Model Comparison#

Configuring CORS for Browser Access#

Important: CORS Configuration Required

Since Shakespeare runs in your browser, you need to configure Ollama to accept cross-origin requests (CORS). This is a crucial step that allows Shakespeare to communicate with your local Ollama instance.

Checking CORS Status#

First, verify if CORS is already enabled:

curl -X OPTIONS http://localhost:11434 -H "Origin: http://example.com" -H "Access-Control-Request-Method: GET" -I

If you see HTTP/1.1 403 Forbidden, CORS is not enabled and needs configuration.

Enabling CORS by Platform#

Enabling CORS on macOS#

# Allow all origins (easiest for local development)
launchctl setenv OLLAMA_ORIGINS "*"

# Or specify specific origins for better security
launchctl setenv OLLAMA_ORIGINS "localhost:3000,localhost:5173,shakespeare.app"

# Optional: Make Ollama accessible on your network
launchctl setenv OLLAMA_HOST "0.0.0.0"

# Restart Ollama for changes to take effect

Enabling CORS on Linux#

Edit the Ollama service configuration:

sudo systemctl edit ollama.service

Add these environment variables:

[Service]
Environment="OLLAMA_HOST=0.0.0.0"
Environment="OLLAMA_ORIGINS=*"

Then restart the service:

sudo service ollama restart

Enabling CORS on Windows#

1. Open System Properties → Environment Variables
2. Add new system variables:
   • OLLAMA_ORIGINS with value * (or specific origins)
   • OLLAMA_HOST with value 0.0.0.0 (optional, for network access)
3. Restart Ollama from the system tray

Verifying CORS Configuration#

After configuration, test again:

curl -X OPTIONS http://localhost:11434 -H "Origin: http://example.com" -H "Access-Control-Request-Method: GET" -I

Success looks like:

HTTP/1.1 204 No Content
Access-Control-Allow-Origin: *

Configuring Local Models in Shakespeare#

Step 1: Start Ollama Service#

# Start Ollama server (with CORS already configured)
ollama serve

# The service will run on http://localhost:11434

Step 2: Test Your Model#

ollama run gpt-oss "Write a simple HTML page with a header"

Step 3: Configure in Shakespeare#

1. Open Shakespeare and go to Settings > AI Settings
2. Scroll to "Add Custom Provider"
3. Click to expand the custom provider section
4. Enter the following configuration:
   • Provider Name: "ollama"
   • API Endpoint: http://localhost:11434/v1

The Bottom Line#

Local Models with Shakespeare Provide#

• ✓ Enhanced privacy - Your code never leaves your machine
• ✓ Faster responses - No network latency
• ✓ Reduced costs - Zero API fees after initial setup
• ✓ Complete control - Run any compatible model

Ready to supercharge your development workflow? Start with GPT-OSS and experience the benefits of local AI models in Shakespeare.

Ready to Build with Shakespeare?#

Start building amazing projects with AI-powered development on Nostr.

• Try Shakespeare
• More Resources

Turn your ideas into reality through natural conversation with AI.

This article was originally published on Soapbox.pub