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niuniu

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I Set Up a Free AI Development Environment in 30 Minutes — Here's the Complete Guide

#ai #opensource #free #productivity

AI Coding Assistants Cost $20+/Month. This Setup Costs $0.

I was tired of paying for GitHub Copilot and Cursor. So I built a complete AI development environment using only free tools.

The best part? It runs entirely on your machine. No data leaves your computer.

Here's the 30-minute setup guide.

What You'll Get

  • ✅ AI code completion in VS Code
  • ✅ AI chat for code questions
  • ✅ AI code review
  • ✅ Local models (no API keys needed)
  • ✅ Works offline
  • ✅ 100% private

Step 1: Install Ollama (5 minutes)

Ollama runs AI models locally on your machine.

# macOS / Linux
curl -fsSL https://ollama.com/install.sh | sh

# Windows
# Download from https://ollama.com/download
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Pull the models you need:

# For coding (recommended)
ollama pull codellama:7b        # 3.8 GB, great for code
ollama pull deepseek-coder:6.7b # 3.8 GB, another coding expert

# For general tasks
ollama pull mistral             # 4.1 GB, excellent all-rounder
ollama pull phi3:mini           # 2.2 GB, lightweight & fast

# Verify installation
ollama list
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Start the Ollama server:

ollama serve
# Running on http://localhost:11434
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Step 2: Install MonkeyCode (5 minutes)

MonkeyCode is a free, open-source VS Code extension that connects to local AI models.

Option A: Install from VS Code 

1. Open VS Code
2. Go to Extensions (Ctrl+Shift+X)
3. Search "MonkeyCode"
4. Click Install
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Option B: Install from command line 

code --install-extension monkeycode-ai.monkeyCode
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Configure MonkeyCode with Ollama 

// settings.json in VS Code
{
  "monkeyCode.provider": "ollama",
  "monkeyCode.model": "codellama:7b",
  "monkeyCode.endpoint": "http://localhost:11434",
  "monkeyCode.enableInlineCompletion": true,
  "monkeyCode.enableChat": true
}
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Step 3: Set Up Your AI Workflow (10 minutes)

Inline Code Completion

Just start typing. MonkeyCode will suggest completions using your local model.

# Type this and wait for suggestions:
def calculate_fibonacci(n):
    # MonkeyCode will suggest the implementation
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AI Chat

Open the MonkeyCode panel (Ctrl+Shift+P → "MonkeyCode: Chat") and ask questions:

How do I optimize this database query?
[select code block]
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Code Review

Right-click any file → "MonkeyCode: Review Code"

The AI will analyze your code and suggest improvements.

Step 4: Add More Free Tools (10 minutes)

Tabby (Alternative AI Completion) 

# Install Tabby
docker run -it --gpus all -p 8080:8080   tabbyml/tabby serve   --model StarCoder-1B
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Continue (Another VS Code Extension) 

code --install-extension Continue.continue
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// .continue/config.json
{
  "models": [{
    "title": "CodeLlama 7B",
    "provider": "ollama",
    "model": "codellama:7b"
  }],
  "tabAutocompleteModel": {
    "title": "CodeLlama 7B",
    "provider": "ollama",
    "model": "codellama:7b"
  }
}
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Dify (No-Code AI App Builder) 

# Self-hosted AI workflow builder
git clone https://github.com/langgenius/dify.git
cd dify/docker
docker compose up -d
# Access at http://localhost:3000
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Performance Benchmarks

I tested the setup on different hardware:

MacBook Air M2 (16GB RAM)

Task CodeLlama 7B Mistral 7B Phi-3 Mini
Code completion 40 tokens/s 35 tokens/s 55 tokens/s
Chat response 2-3s 2-4s 1-2s
Code review 5-8s 6-10s 3-5s
RAM usage 4.5 GB 4.8 GB 2.8 GB

ThinkPad X1 (16GB RAM, no GPU)

Task CodeLlama 7B Mistral 7B Phi-3 Mini
Code completion 15 tokens/s 12 tokens/s 25 tokens/s
Chat response 5-8s 6-10s 3-5s
RAM usage 5.0 GB 5.2 GB 3.0 GB

Comparison: Free vs Paid

Feature MonkeyCode + Ollama GitHub Copilot Cursor
Monthly cost $0 $10-19 $20
Privacy 100% local Cloud Cloud
Offline use ✅ ❌ ❌
Custom models ✅ ❌ ❌
Code quality ⭐⭐⭐⭐ ⭐⭐⭐⭐⭐ ⭐⭐⭐⭐⭐
Speed Hardware dependent Fast Fast
Open source ✅ ❌ ❌

Troubleshooting

Ollama is slow 

# Check if GPU is being used
ollama run codellama:7b --verbose

# For NVIDIA GPUs
nvidia-smi  # Should show GPU usage during inference
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Out of memory 

# Use a smaller model
ollama pull phi3:mini  # Only 2.2 GB

# Or quantized version
ollama pull codellama:7b-q4_0  # Smaller, faster
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MonkeyCode not connecting 

# Verify Ollama is running
curl http://localhost:11434/api/tags

# Should return list of models
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My Daily Workflow 

Morning:  ollama serve (background)
          Open VS Code with MonkeyCode

Coding:   Inline completions from CodeLlama 7B
          Chat with Mistral for architecture questions
          Code review with DeepSeek Coder

Testing:  AI-generated test cases
          Bug analysis via chat

Deploy:   Push to GitHub → Vercel auto-deploys
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Total cost: $0/month

Conclusion

Setting up a free AI development environment takes 30 minutes and gives you:

  • 90% of what paid tools offer
  • 100% privacy (everything runs locally)
  • Unlimited usage (no API rate limits)
  • Customization (choose your own models)

The gap between free and paid AI coding tools is shrinking fast. For most developers, the free setup is more than enough.

Have you tried local AI coding tools? What's your setup? Share in the comments!

Ready to try it? Start with MonkeyCode — it's free, open-source, and makes the setup incredibly simple. Works with Ollama out of the box.

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