Setting up Cline and Ollama with Visual Studio Code

As developers, we're always looking for ways to enhance our coding workflow with AI assistance. Today, we'll walk through setting up Cline (an AI coding assistant) with Ollama (local LLM runtime) in Visual Studio Code. This powerful combination gives you AI-powered coding assistance while keeping everything running locally on your machine. And yeah It's FREE :)

What You'll Need

Before we dive in, make sure you have:

• Visual Studio Code installed
• Node.js (version 18 or higher)
• At least 8GB of RAM (16GB recommended for larger models)
• A decent GPU (optional but recommended for faster inference)

Step 1: Installing Ollama

On macOS

1# Install via Homebrew
2brew install ollama
3
4# Or download directly from ollama.ai
5curl -fsSL https://ollama.ai/install.sh | sh

On Linux

1# Install script
2curl -fsSL https://ollama.ai/install.sh | sh
3
4# Or via package managers
5# Ubuntu/Debian
6sudo apt install ollama
7
8# Arch Linux
9yay -S ollama

On Windows

1. Download the installer from ollama.ai
2. Run the installer and follow the setup wizard
3. Restart your terminal/PowerShell

Verify Installation

1ollama --version

Step 2: Setting up Ollama Models

Start the Ollama service:

1ollama serve

In a new terminal, download and run your preferred model. Here are some popular options:

For Code Generation (Recommended)

1# CodeLlama - Excellent for code completion and generation
2ollama pull codellama:7b
3
4# DeepSeek Coder - Specifically trained for coding tasks
5ollama pull deepseek-coder:6.7b
6
7# Phind CodeLlama - Optimized for code explanation
8ollama pull phind-codellama:34b

For General Purpose

1# Llama 2 - Good balance of capability and speed
2ollama pull llama2:7b
3
4# Mistral - Fast and capable
5ollama pull mistral:7b
6
7# Code-specific Mistral variant
8ollama pull codestral:22b

Test your model:

1ollama run codellama:7b

Step 3: Installing Cline Extension

1. Open Visual Studio Code
2. Go to the Extensions view (Ctrl+Shift+X or Cmd+Shift+X)
3. Search for "Cline"
4. Install the Cline extension by the official publisher
5. Restart VS Code

Alternatively, install via command line:

1code --install-extension cline.cline

Step 4: Configuring Cline with Ollama

Access Cline Settings

1. Open VS Code Command Palette (Ctrl+Shift+P or Cmd+Shift+P)
2. Type "Cline: Open Settings" and select it
3. Or navigate to Settings → Extensions → Cline

Configure Ollama Connection

In the Cline settings:

1{
2  "cline.provider": "ollama",
3  "cline.ollama.baseUrl": "http://localhost:11434",
4  "cline.ollama.model": "codellama:7b",
5  "cline.temperature": 0.3,
6  "cline.maxTokens": 2048,
7  "cline.contextWindow": 4096
8}

Key Configuration Options

Provider Settings:

• provider: Set to "ollama"
• baseUrl: Ollama's default URL (usually http://localhost:11434)
• model: The model name you downloaded (e.g., "codellama:7b")

Performance Tuning:

• temperature: Controls randomness (0.1-0.5 for code, 0.7-1.0 for creative tasks)
• maxTokens: Maximum response length
• contextWindow: How much previous conversation to remember

Alternative Configuration via VS Code Settings UI

1. File → Preferences → Settings
2. Search for "Cline"
3. Configure the following:
   • Cline: Provider → "ollama"
   • Cline: Ollama Base URL → "http://localhost:11434"
   • Cline: Ollama Model → "codellama:7b" (or your preferred model)

Step 5: Testing Your Setup

Basic Functionality Test

1. Open a new file in VS Code (e.g., test.py)
2. Open Command Palette (Ctrl+Shift+P)
3. Run "Cline: Start Chat" or use the Cline panel
4. Try a simple request: "Write a Python function to calculate fibonacci numbers"

Troubleshooting Common Issues

Cline can't connect to Ollama:

1# Check if Ollama is running
2ps aux | grep ollama
3
4# Restart Ollama service
5ollama serve
6
7# Check port availability
8netstat -an | grep 11434

Model not found error:

1# List available models
2ollama list
3
4# Pull the model if missing
5ollama pull codellama:7b

Slow responses:

• Try smaller models (7B instead of 13B/34B)
• Reduce context window size
• Close other memory-intensive applications

Step 6: Optimizing Your Workflow

Recommended Model Selection by Use Case

For Fast Code Completion:

• codellama:7b - Quick responses, good for autocompletion
• deepseek-coder:1.3b - Ultra-fast, basic code assistance

For Complex Code Analysis:

• codellama:13b - Better understanding, slower responses
• phind-codellama:34b - Excellent for debugging and explanations

For General Programming Help:

• mistral:7b - Good balance of speed and capability
• codestral:22b - Specialized for code tasks

Performance Tips

System Optimization:

1# Increase Ollama's memory allocation
2export OLLAMA_HOST=127.0.0.1:11434
3export OLLAMA_MAX_LOADED_MODELS=2
4export OLLAMA_NUM_PARALLEL=2

VS Code Settings:

1{
2  "cline.autoSuggest": true,
3  "cline.inlineCompletion": true,
4  "cline.debounceTime": 300,
5  "cline.enableFileContext": true
6}

Step 7: Advanced Configuration

Custom Model Parameters

Create an Ollama Modelfile for fine-tuned behavior:

 1FROM codellama:7b
 2
 3# Set custom parameters
 4PARAMETER temperature 0.2
 5PARAMETER top_k 40
 6PARAMETER top_p 0.9
 7PARAMETER repeat_penalty 1.1
 8
 9# Custom system prompt for coding
10SYSTEM """
11You are a helpful coding assistant. Provide concise, accurate code solutions.
12Focus on clean, readable code with appropriate comments.
13"""

Apply the custom model:

1ollama create my-code-assistant -f ./Modelfile
2ollama run my-code-assistant

Update Cline to use the custom model:

1{
2  "cline.ollama.model": "my-code-assistant"
3}

Project-Specific Settings

Create .vscode/settings.json in your project:

1{
2  "cline.provider": "ollama",
3  "cline.ollama.model": "deepseek-coder:6.7b",
4  "cline.temperature": 0.1,
5  "cline.enableProjectContext": true,
6  "cline.includeFileTypes": [".js", ".ts", ".py", ".go", ".rs"]
7}

Usage Examples

Code Generation

Prompt: "Create a React component for a user profile card"

Result: Cline will generate a complete React component with props, styling, and proper structure.

Code Explanation

Prompt: "Explain this regex pattern: ^(?:[a-z0-9!#$%&'*+/=?^_{|}~-]+(?:.[a-z0-9!#$%&'*+/=?^_{|}~-]+)*|"(?:[\x01-\x08\x0b\x0c\x0e-\x1f\x21\x23-\x5b\x5d-\x7f]|\\[\x01-\x09\x0b\x0c\x0e-\x7f])*")@"

Result: Cline will break down the regex and explain each component clearly.

Debugging Assistance

Prompt: "This function is throwing a null pointer exception, can you help debug it?"

Result: Cline will analyze your code and suggest potential fixes.

Best Practices

Model Management

1# Keep only models you actively use
2ollama list
3ollama rm unused-model:tag
4
5# Update models regularly
6ollama pull codellama:7b

Resource Monitoring

1# Monitor Ollama resource usage
2ollama ps
3
4# Check GPU utilization (if using GPU)
5nvidia-smi

Backup Your Configuration

Save your working Cline configuration:

1# Export VS Code settings
2cp ~/.config/Code/User/settings.json ~/cline-backup-settings.json

Troubleshooting Guide

Common Issues and Solutions

Issue: "Connection refused" error

1# Solution: Ensure Ollama is running
2ollama serve &

Issue: Model responses are too slow

• Switch to a smaller model (7B instead of 13B)
• Reduce context window size
• Close unnecessary applications

Issue: Out of memory errors

1# Solution: Limit concurrent requests
2export OLLAMA_MAX_LOADED_MODELS=1

Issue: Cline suggestions are irrelevant

• Adjust temperature (lower for more focused responses)
• Update your system prompt
• Ensure you're using a code-specific model

Security Considerations

Since everything runs locally:

• ✅ Your code never leaves your machine
• ✅ No API keys or external services required
• ✅ Complete privacy and data control
• ✅ Works offline once models are downloaded

Performance Benchmarks

Based on typical setups:

Conclusion

Setting up Cline with Ollama gives you a powerful, privacy-focused coding assistant that runs entirely on your local machine. The combination provides:

• Local AI assistance without cloud dependencies
• Customizable models for different coding tasks
• Privacy and security with no data sharing
• Cost-effective solution with no API fees

Start with a smaller model like codellama:7b to test your setup, then experiment with larger models based on your hardware capabilities and specific needs.

Next Steps

• Explore different models for various programming languages
• Create custom Ollama models fine-tuned for your specific projects
• Set up project-specific Cline configurations
• Integrate with your existing development workflow

Happy coding! 🚀

Have questions or run into issues? The Cline and Ollama communities are very helpful. Check out their respective GitHub repositories and Discord servers for support.