🚀CodiumAI PR-Agent: An AI-Powered 🤖 Tool for Automated Pull Request Analysis, Feedback, Suggestions and More! 💻🔍

Making pull requests less painful with an AI agent

/describe:

/review:

/reflect_and_review:

/ask:

/improve:

Overview

PR-Agent offers extensive pull request functionalities across various git providers:

Examples for invoking the different tools via the CLI:

• Review: python cli.py --pr-url=<pr_url> review
• Describe: python cli.py --pr-url=<pr_url> describe
• Improve: python cli.py --pr-url=<pr_url> improve
• Ask: python cli.py --pr-url=<pr_url> ask "Write me a poem about this PR"
• Reflect: python cli.py --pr-url=<pr_url> reflect
• Update changelog: python cli.py --pr-url=<pr_url> update_changelog

"<pr_url>" is the url of the relevant PR (for example: #50).

In the configuration file you can select your git provider (GitHub, Gitlab, Bitbucket), and further configure the different tools.

Try it now

Try GPT-4 powered PR-Agent on your public GitHub repository for free. Just mention @CodiumAI-Agent and add the desired command in any PR comment! The agent will generate a response based on your command.

To set up your own PR-Agent, see the Installation section

Installation

To get started with PR-Agent quickly, you first need to acquire two tokens:

1. An OpenAI key from here, with access to GPT-4.
2. A GitHub personal access token (classic) with the repo scope.

There are several ways to use PR-Agent:

• Method 1: Use Docker image (no installation required)
• Method 2: Run as a GitHub Action
• Method 3: Run from source
• Method 4: Run as a polling server
  • Request reviews by tagging your GitHub user on a PR
• Method 5: Run as a GitHub App
  • Allowing you to automate the review process on your private or public repositories

Usage and Tools

PR-Agent provides five types of interactions ("tools"): "PR Reviewer", "PR Q&A", "PR Description", "PR Code Sueggestions" and "PR Reflect and Review".

• The "PR Reviewer" tool automatically analyzes PRs, and provides various types of feedback.
• The "PR Q&A" tool answers free-text questions about the PR.
• The "PR Description" tool automatically sets the PR Title and body.
• The "PR Code Suggestion" tool provide inline code suggestions for the PR that can be applied and committed.
• The "PR Reflect and Review" tool initiates a dialog with the user, asks them to reflect on the PR, and then provides a more focused review.

How it works

Check out the PR Compression strategy page for more details on how we convert a code diff to a manageable LLM prompt

Why use PR-Agent?

A reasonable question that can be asked is: "Why use PR-Agent? What make it stand out from existing tools?"

Here are some of the reasons why:

• We emphasize real-life practical usage. Each tool (review, improve, ask, ...) has a single GPT-4 call, no more. We feel that this is critical for realistic team usage - obtaining an answer quickly (~30 seconds) and affordably.
• Our PR Compression strategy is a core ability that enables to effectively tackle both short and long PRs.
• Our JSON prompting strategy enables to have modular, customizable tools. For example, the '/review' tool categories can be controlled via the configuration file. Adding additional categories is easy and accessible.
• We support multiple git providers (GitHub, Gitlab, Bitbucket), and multiple ways to use the tool (CLI, GitHub Action, Docker, ...).
• We are open-source, and welcome contributions from the community.

Roadmap

• Support open-source models, as a replacement for OpenAI models. (Note - a minimal requirement for each open-source model is to have 8k+ context, and good support for generating JSON as an output)
• Support other Git providers, such as Gitlab and Bitbucket.
• Develop additional logic for handling large PRs, and compressing git patches
• Add additional context to the prompt. For example, repo (or relevant files) summarization, with tools such a ctags
• Adding more tools. Possible directions:
  • PR description
  • Inline code suggestions
  • Reflect and review
  • Enforcing CONTRIBUTING.md guidelines
  • Performance (are there any performance issues)
  • Documentation (is the PR properly documented)
  • Rank the PR importance
  • ...

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