Ollama Code Review Extension
Supercharge Your Code Reviews with Self-Hosted AI
Welcome to the Ollama Code Review Extension – your new ally in building top-notch software! This extension seamlessly integrates Ollama's powerful self-hosted language models into your Azure DevOps pipeline, transforming code reviews into an intelligent and efficient process while keeping your code secure on your own infrastructure.
Get Started Now!
Enhance your development workflow with Ollama Code Review. Start receiving intelligent and actionable insights on your code changes using your own self-hosted AI models. Install the extension today and experience the future of code reviews with complete control over your data!
Why Choose Ollama Code Review?
- Self-Hosted & Secure: Keep your code and reviews completely private on your own infrastructure. No data sent to external cloud services.
- Automated Code Reviews: Say goodbye to manual code inspections! Let Ollama analyze your code changes, catching bugs, performance issues, and suggesting best practices.
- AI-Powered Insights: Leverage powerful open-source language models like CodeLlama, Llama 3, DeepSeek Coder, and more to receive insightful comments on your pull requests.
- Faster Reviews: Reduce the time spent on code reviews. Let Ollama handle the routine, allowing your team to focus on impactful work.
- Configurable and Customizable: Tailor the extension to your needs with customizable settings. Choose from various Ollama models, define file exclusions, and more.
- Cost-Effective: No API costs or per-token charges. Run unlimited code reviews on your own hardware.
Prerequisites
- A running Ollama instance accessible from your build agents
- Ollama models installed (e.g.,
ollama pull codellama or ollama pull llama3.1)
Getting started
Set up Ollama:
- Install Ollama on your server or local machine following the Ollama installation guide
- Pull your preferred model:
ollama pull codellama (or llama3.1, deepseek-coder, qwen2.5-coder, etc.)
- Ensure Ollama is running and accessible from your Azure DevOps build agents
Install the Ollama Code Review DevOps Extension.
Add Ollama Code Review Task to Your Pipeline:
trigger:
branches:
exclude:
- '*'
pr:
branches:
include:
- '*'
jobs:
- job: CodeReview
pool:
vmImage: 'ubuntu-latest'
steps:
- task: OllamaCodeReview@1
inputs:
ollama_endpoint: 'http://your-ollama-server:11434/api/chat'
ai_model: 'codellama'
bugs: true
performance: true
best_practices: true
file_extensions: 'js,ts,css,html'
file_excludes: 'file1.js,file2.py,secret.txt'
additional_prompts: 'Fix variable naming, Ensure consistent indentation, Review error handling approach'`
If you do not already have Build Validation configured for your branch already add Build validation to your branch policy to trigger the code review when a Pull Request is created
FAQ
Q: What agent job settings are required?
A: Ensure that "Allow scripts to access OAuth token" is enabled as part of the agent job. Follow the documentation for more details.
Q: What permissions are required for Build Administrators?
A: Build Administrators must be given "Contribute to pull requests" access. Check this Stack Overflow answer for guidance on setting up permissions.
Bug Reports
If you find a bug or unexpected behavior, please open a bug report.
Feature Requests
If you have ideas for new features or enhancements, please submit a feature request.
Learn More
Visit our GitHub repository for additional documentation, updates, and support.
Securing Your Ollama API with nginx
If you want to expose your Ollama API over the internet or add authentication, you can use nginx as a reverse proxy with Bearer token authentication:
server {
listen 443 ssl http2;
server_name ollama.example.com;
# SSL certificates
ssl_certificate /etc/letsencrypt/live/ollama.example.com/fullchain.pem;
ssl_certificate_key /etc/letsencrypt/live/ollama.example.com/privkey.pem;
# -------------------------------
# PROXY TO OLLAMA
# -------------------------------
location / {
proxy_set_header Authorization $http_authorization;
# Validate Authorization header
set $expected "Bearer YOUR_SECRET_TOKEN_HERE";
if ($http_authorization != $expected) {
return 401;
}
proxy_pass http://127.0.0.1:11434;
proxy_http_version 1.1;
proxy_set_header Connection "";
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
proxy_buffering off;
}
# Optional: return proper WWW-Authenticate header
error_page 401 = @unauth;
location @unauth {
add_header WWW-Authenticate "Bearer realm=\"Ollama API\"" always;
return 401 "Unauthorized";
}
}
Important: Replace ollama.example.com, SSL certificate paths, and YOUR_SECRET_TOKEN_HERE with your actual values.
Then use the Bearer Token field in the extension configuration to authenticate:
- task: OllamaCodeReview@1
inputs:
ollama_endpoint: 'https://ollama.example.com/api/chat'
ai_model: 'codellama'
bearer_token: '$(OllamaApiToken)' # Store as pipeline variable
Supported Ollama Models
This extension works with any Ollama model, but these are particularly well-suited for code reviews:
- codellama - Meta's specialized code model
- llama3.1 / llama3.2 - General-purpose with strong reasoning
- deepseek-coder - Optimized for code understanding
- qwen2.5-coder - Advanced code analysis
- mistral / mixtral - Efficient general-purpose models
Run ollama list on your Ollama server to see all available models.
