https://github.com/drew2a/ai-review
A GitHub Action that provides automated code review using AI to analyze pull request changes.
https://github.com/drew2a/ai-review
Last synced: 3 months ago
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A GitHub Action that provides automated code review using AI to analyze pull request changes.
- Host: GitHub
- URL: https://github.com/drew2a/ai-review
- Owner: drew2a
- License: mit
- Created: 2025-02-23T13:58:04.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-12-27T15:48:43.000Z (5 months ago)
- Last Synced: 2025-12-29T07:46:17.811Z (5 months ago)
- Language: Python
- Homepage:
- Size: 101 KB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
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# AI Code Review Action
A GitHub Action that provides automated code review using AI to analyze pull request changes.
## Features
- Automatically reviews pull request changes using AI
- Provides detailed code suggestions and improvements
- Adds review comments directly to the PR
- Works with any programming language
- Supports different AI models and API endpoints
- Optional review resolution statuses (e.g., "APPROVE", "REQUEST_CHANGES", "COMMENT")
- Debug mode for enhanced logging
## Supported models
This action uses [LiteLLM](https://docs.litellm.ai/docs/providers), so it supports **100+ LLMs** including:
- **OpenAI** (GPT-4o, o1, etc.)
- **Anthropic** (Claude 3.5 Sonnet, Claude 3.7 Sonnet, etc.)
- **Google VertexAI / Gemini** (Gemini 1.5 Pro, Gemini 2.0 Flash, etc.)
- **Azure OpenAI**
- **HuggingFace**
- **Ollama**
- ... and many more.
See the [LiteLLM Providers documentation](https://docs.litellm.ai/docs/providers) for the full list of supported models and the required environment variables for each provider.
### My (Subjective) Review of the Particular Models
I’ll grade them on a scale from **0 to 10**, where:
- **0** → Completely irrelevant comments
- **3** → My fresh junior/mid-level colleague
- **5** → My mid-level colleague who reads Stack Overflow
- **8** → Me
- **10** → My very smart colleague
So, based on this **(highly unscientific) scale**:
- **gpt-4o** → **2**
- **o1** → **3**
- **claude-3-5-sonnet** → **5**
- **claude-3-7-sonnet** → **6**
- **gemini-2.0-flash** → **2**
- **gemini-2.5-pro** → **3**
## Inputs
| Name | Description | Required | Default |
|-------------------------|-----------------------------------------------------------|----------|----------------------|
| `github_token` | GitHub token for authentication | true | - |
| `debug` | Enable debug mode (true/false) | false | `false` |
| `add_review_resolution` | Add review resolution (APPROVE, REQUEST_CHANGES, COMMENT) | false | `false` |
| `add_joke` | Add a joke to the review comment | false | `false` |
| `author_customization` | YAML configuration for customizing reviews based on PR author | false | - |
## Environment Variables
The action relies on environment variables for LLM configuration, handled by [litellm](https://docs.litellm.ai/docs/).
| Name | Description | Required |
|------|-------------|----------|
| `LLM_MODEL` | The model name to use (e.g. `gpt-4o`, `claude-3-5-sonnet`, `gemini/gemini-1.5-pro`) | Yes |
| `OPENAI_API_KEY` | API Key for OpenAI (if using OpenAI models) | Conditional |
| `ANTHROPIC_API_KEY` | API Key for Anthropic (if using Claude models) | Conditional |
| `GEMINI_API_KEY` | API Key for Google Gemini (if using Gemini models) | Conditional |
| `OPENAI_API_BASE` | Custom API endpoint (if needed) | Optional |
*Note: Check the [LiteLLM documentation](https://docs.litellm.ai/docs/providers) for the specific environment variables required for your chosen provider.*
## Usage
To use this action in your GitHub workflow, add the following step:
```yaml
- uses: drew2a/ai-review@v1
env:
LLM_MODEL: gpt-4o
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
debug: false
add_review_resolution: false
add_joke: false
author_customization: |
torvalds: "This is an experienced developer. Focus on architecture and design patterns."
defunkt: "This is a junior developer. Provide educational feedback and explanations."
```
### Example Workflow
```yaml
name: AI Code Review
on: [ pull_request ]
permissions:
pull-requests: write
jobs:
review:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: drew2a/ai-review@v1
env:
LLM_MODEL: ${{ secrets.LLM_MODEL }}
OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
# Add other env vars required by litellm for your specific provider
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
debug: true
add_review_resolution: false
add_joke: false
```
## Author Customization
The `author_customization` parameter allows you to customize the review behavior based on the PR author's GitHub username. This is useful for providing different types of feedback for team members with different experience levels or roles.
### Configuration Format
The customization is provided as YAML using actual GitHub usernames:
```yaml
torvalds: "Custom review guidance for this user"
defunkt: "Different guidance for another user"
```
### Example Configuration
Here's an example for a team with users who get customized behavior:
```yaml
author_customization: |
torvalds: "Use a more friendly manner since they're beginners. Give more examples and explanations to help them learn."
defunkt: "Use a super formal tone and provide low-level grounding. Focus on technical precision and detailed analysis."
```
### Role-Based Example
You can also organize by roles using GitHub usernames:
```yaml
author_customization: |
torvalds: "Focus on architectural decisions and design patterns. This developer prefers concise, high-level feedback."
defunkt: "Provide educational explanations and learning opportunities. Focus on best practices and code quality fundamentals."
octocat: "Be welcoming and provide clear explanations. Focus on project conventions and coding standards."
```
### Usage in Workflow
```yaml
- uses: drew2a/ai-review@v1
with:
# ... other parameters ...
author_customization: |
torvalds: "Focus on performance and security concerns"
defunkt: "Educational feedback welcomed"
```
## License
Released under the [MIT License](LICENSE).