AI-powered Pull Request Description Generator
Project description
AIPR - Agentic Pull Request Description Generator
Automatically analyze git diffs and vulnerabilities to generate comprehensive, well-structured pull request descriptions. By intelligently detecting changes, performing security scans, and leveraging state-of-the-art AI models, AIPR helps teams save time while maintaining high-quality, consistent pull request descriptions.
AI-Driven Development
This project follows an AI-driven development workflow:
- 🤖 Built with AI - Developed using Claude Code with comprehensive AI guidance
- 📋 AI Task Assignment - Structured workflow for AI agents documented in CONTRIBUTING.md
- 📚 AI-Friendly Documentation - Comprehensive guides for AI agents in CLAUDE.md and Architecture Decision Records
- 🏗️ Architecture-First Design - ADRs define behavior and guide implementation patterns
# Install with pipx (recommended)
pipx install pr-generator-agent
# Or with pip
pip install pr-generator-agent
# Set the environment variable for the API key
export ANTHROPIC_API_KEY="your-api-key"
# Generate a PR description
aipr
# Generate a conventional commit message
aipr commit
# Custom usage - Analyze changes against main branch
# Include: Vulnerability scanning
# Use: Azure OpenAI o1-mini model
# Prompt: meta template
# Output: Verbose
aipr pr -t main --vulns -p meta -m azure/o1-mini -v
# Inline with merge request creation
gh pr create -b "$(aipr pr -s)" -t "feat: New Feature"
# Inline with commit creation
git commit -m "$(aipr commit)"
Key Features
- 🔍 Smart Detection: Automatically analyzes working tree changes or compares branches
- 📝 Conventional Commits: Generate conventional commit messages from staged changes
- 🛡️ Security First: Optional vulnerability scanning between branches using Trivy
- 🤖 AI-Powered: Multiple AI providers (Azure OpenAI, OpenAI, Anthropic, Gemini) for optimal results
- 🔄 CI/CD Ready: Seamless integration with GitLab and GitHub workflows
Example Output
Change Summary:
1. **Added User Authentication**
- Implemented JWT middleware
- Added login/register endpoints
- Updated bcrypt to v5.1.1
2. **Security Updates**
- Fixed 2 medium severity vulnerabilities
- Updated deprecated crypto functions
Security Analysis:
✓ No new vulnerabilities introduced
Commit Message Generation
$ git add src/auth.py tests/test_auth.py
$ aipr commit
feat(auth): add OAuth2 authentication support
$ git add requirements.txt
$ aipr commit
build(deps): update dependencies to latest versions
$ git add README.md docs/guide.md
$ aipr commit
docs: update installation and usage documentation
Requirements
- Python 3.11 or higher (3.11, 3.12 officially supported)
- Git
- LLM API Key (Anthropic, OpenAI, or Azure OpenAI)
- Trivy (used for
--vulnsscanning)
Environment Variables
Anthropic (Default)
ANTHROPIC_API_KEY: Anthropic API key
Azure OpenAI
AZURE_API_KEY: Azure OpenAI API keyAZURE_API_BASE: Azure endpoint URLAZURE_API_VERSION: API version (default: "2024-02-15-preview")
OpenAI
OPENAI_API_KEY: OpenAI API key
Google Gemini
GEMINI_API_KEY: Google Gemini API key
Usage
AIPR provides two main commands:
PR Command (Pull Request Descriptions)
aipr pr [options] # or just 'aipr' for backward compatibility
Options:
-t, --target: Compare changes with specific branch (default: auto-detects main/master)-p, --prompt: Select prompt template (e.g., 'meta')--vulns: Include vulnerability scanning--working-tree: Use working tree changes
Global Options:
-v, --verbose: Show API interaction details-d, --debug: Preview prompts without API calls-s, --silent: Output only the description-m, --model: Specify AI model to use
The tool intelligently detects changes by:
- Using staged/unstaged changes if present
- Comparing against target branch if working tree is clean
Commit Command (Conventional Commit Messages)
aipr commit [options]
Options:
--conventional: Generate conventional commit message (default)--format: Message format (currently only 'conventional')--context: Additional context for the commit message
Examples:
# Basic commit message generation
git add .
aipr commit
# With additional context
aipr commit --context "upstream sync"
# Use in automation
git commit -m "$(aipr commit)"
Supported AI Models
Choose from multiple AI providers:
| Provider | Model | Notes |
|---|---|---|
| Anthropic | claude-4 |
default |
claude-4.0 |
alias for claude-4 |
|
claude-3.5-sonnet |
latest | |
claude-3.5-haiku |
latest | |
claude-3-haiku |
||
claude |
alias for claude-4 |
|
| Azure OpenAI | azure/o1-mini |
|
azure/gpt-4o-mini |
||
azure/gpt-4o |
||
azure |
alias for azure/gpt-4o-mini |
|
| OpenAI | gpt-4o |
|
gpt-4-turbo |
||
gpt-3.5-turbo |
||
openai |
alias for gpt-4o |
|
| Google Gemini | gemini-1.5-pro |
default for Gemini |
gemini-1.5-flash |
||
gemini-2.5-pro-experimental |
maps to gemini-2.5-pro-exp-03-25 |
|
gemini |
alias for gemini-2.5-pro-experimental |
Custom Prompts
AIPR supports custom prompt templates that allow you to tailor merge request descriptions to your team's specific needs. Custom prompts enable you to:
- Define consistent formatting across your team
- Include organization-specific requirements
- Add custom sections and validation rules
- Provide examples that match your team's standards
For detailed information on creating and using custom prompts, see our Custom Prompts Tutorial.
Contributing
We welcome contributions! See our Contributing Guide for details on:
- Setting up your development environment
- Our development workflow
- Code style guidelines
- Pull request process
- Running tests
License
This project is licensed under the MIT License - see the LICENSE file for details.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file pr_generator_agent-1.3.0.tar.gz.
File metadata
- Download URL: pr_generator_agent-1.3.0.tar.gz
- Upload date:
- Size: 100.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
062956ecf3fca31fba4c6b68f318725cee8a6c9df8bfc36b44b274179d035e04
|
|
| MD5 |
ee386d88d0903d3a5bdf34837846340f
|
|
| BLAKE2b-256 |
b87090dea5a86ca469ff23df5f9216f54f9946bb3625771dee4423672f865520
|
File details
Details for the file pr_generator_agent-1.3.0-py3-none-any.whl.
File metadata
- Download URL: pr_generator_agent-1.3.0-py3-none-any.whl
- Upload date:
- Size: 28.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
bfa2fb99b42102e34e642d8e7cb01d4f63634d4bac710428e52b9bd12124ad7f
|
|
| MD5 |
fde0bf1db5e26a6a0c6360814d690faa
|
|
| BLAKE2b-256 |
c442b0ef175abf5fa9e80ed9194893302052e8d7bc4513fd26f58bd1a062cbe6
|