AutoPR — AI-powered Pull Request Generator & Reviewer
AutoPR automates the repetitive parts of pull requests: it writes concise PR titles & descriptions, validates CI/tests, runs deterministic static and lint checks, and provides an AI-assisted review summary.
Quickstart
1. Install
pip install autopr-core
2. Configure your API key
AutoPR requires your own OpenAI or Anthropic API key. Run the interactive setup:
autopr configure
This will prompt you to:
- Choose a provider (
openaioranthropic) - Enter your API key (stored locally in
.env, never shared)
Or set environment variables manually:
# For OpenAI
export OPENAI_API_KEY="your-openai-api-key"
export AUTOPR_PROVIDER="openai"
# For Anthropic
export ANTHROPIC_API_KEY="your-anthropic-api-key"
export AUTOPR_PROVIDER="anthropic"
3. Use AutoPR
# Generate a PR title & description
autopr gen --diff "$(git diff)" --commits "feat: add helper"
# AI-assisted code review
autopr review --diff "$(git diff)"
# Run static analysis
autopr analyze --diff "$(git diff)" --summary
Command Cheat Sheet
| Command | Description |
|---|---|
autopr configure |
Interactive setup — set your AI provider and API key |
autopr gen |
Generate PR title and description |
autopr review |
Perform AI-assisted code review |
autopr analyze |
Run static analysis on code diffs |
autopr analyze-files |
Batch-analyze files in a directory |
autopr ci-parse |
Parse CI/test logs |
autopr coverage-compare |
Compare coverage reports |
autopr validate-issue |
Check if changes align with an issue |
autopr doctor |
Check system health and configuration |
autopr init |
Initialize AutoPR config in your repo |
autopr suggest-reviewers |
Suggest reviewers based on git history |
Features
- AI-Powered PR Generation — Titles, descriptions, and risk assessments
- AI Code Review — Senior-engineer-level review with actionable findings
- Static Analysis — Deterministic Python code analysis (security, complexity, style)
- CI/Test Parsing — Parse pytest, unittest, and GitHub Actions logs
- Coverage Comparison — Diff coverage reports before and after changes
- Multiple LLM Providers — OpenAI and Anthropic with robust error handling
- FastAPI Backend — REST API with
/generateand/reviewendpoints - CLI Tool — Full-featured command-line interface
API Server
Run the FastAPI server for REST API access:
uvicorn autopr.main:app --reload --port 8000
Visit http://127.0.0.1:8000/docs for interactive API docs.
Install from Source
git clone https://github.com/surenkotian/AutoPR.git
cd AutoPR
pip install -e .
autopr configure
License
MIT
Metadata
Release files for autopr-core 0.5.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| autopr_core-0.5.1.tar.gz | 53.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| autopr_core-0.5.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 105.8 kB
Release files / autopr_core-0.5.1.tar.gz
| Download URL | autopr_core-0.5.1.tar.gz |
|---|---|
| Size | 53.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
d84a7773ebca943bd185ab6ddb36aaf991db43a0fef575579b12e73f7bdb597d
|
|
BLAKE2b-256 checksum How to use checksums |
22f34d5f38f75690860a30b779c1655909f05034bb060e3004fe87e611aca38b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.10.9
|
Release files / autopr_core-0.5.1-py3-none-any.whl
| Download URL | autopr_core-0.5.1-py3-none-any.whl |
|---|---|
| Size | 52.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
fd143c705c9951fb5c199bffe14dcc8dde16aea771ef4e2120fb272f81a0ec0f
|
|
BLAKE2b-256 checksum How to use checksums |
22a72794e81e625d9cb43e981526f97500805cea60e127671906f1b1d06c9ce7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.10.9
|