Build Code Review AI Agents in Python – Part 1 of 3 | Automate Code Reviews with Custom AI Agents
Welcome to Part 1 of this 3-part series on building AI agents to automate code reviews! In this video, we'll kick off the project by creating custom Python classes that analyze Infrastructure-as-Code (IaC) files, specifically Terraform code, for syntax issues, best practices, and optimization suggestions. These AI-driven agents will streamline code review by automating feedback directly in the code.
In this part, you’ll learn:
1. How to set up the project and configure the necessary tools and environment
2. The basics of building AI agents for code review using the OpenAI API
3. How each agent (Syntax, Best Practices, Optimization) functions to review and add comments to your code
Project Code on GitHub:
github.com/talkitdoit/build-code-review-ai-agents
Tools Used
Python 3.13
pip 24.2
Nushell
Zed IDE
Next in the Series
In Part 2, we'll move these AI agents into a GitHub Actions pipeline to automate code reviews on every pull request. Don’t forget to subscribe and turn on notifications so you don’t miss it!
Timestamps:
0:00:00 Intro
0:00:18 What are we building
0:00:26 Before example
0:00:34 After example
0:00:43 What tools do I need
0:00:58 Setup #1
0:01:10 Setup #2
0:01:21 Setup #3
0:01:36 Start coding
0:02:05 Agent base class
0:02:53 Syntax Agent code
0:03:06 Best Practices Agent code
0:03:20 Optimization Agent code
0:03:34 Review Agent code
0:04:29 Initialize the agents
0:05:12 Run the code
0:05:30 Check AI Agents results
0:05:58 Completed
0:06:04 End
HASHTAGS
#AI #Python #CodeReview #Automation #OpenAI #InfrastructureAsCode #howto #Programming #openai #Terraform
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