Awesome

Run AI-powered workflows over your codebase

🌟 Features

🌳 Living summaries of your code in nested READMEs
📝 TODOs kept track of in issues
⏳ Keep history of an API call's result in git
📄 Summarize changes by adding a "summarize" label to a PR
🫵 Custom actions configured in YAML

🚀 Getting Started

Please see the installation guide.

📝 Maintainer Note

Though used internally, this project is currently not actively maintained.

Until v0.1.2, AutoPR autonomously generated pull requests from issues. If you'd still prefer to use AutoPR for this, set the following line in your github actions yaml:

      uses: docker://ghcr.io/irgolic/autopr:v0.1.2

Below is an example of AutoPR's Living README:

🌳 Living Summary

This folder contains various files and folders related to automating tasks and workflows. It includes a Dockerfile for setting up a Docker image, a license file specifying the terms of use, a Makefile for automating development tasks, an action configuration file for a pull request workflow, a shell script for executing a Python module, a lock file and a configuration file for a Python project using Poetry, JSON schemas for defining strict workflows and trigger configurations, and a JSON schema for defining workflow definitions. These files and folders provide functionality for automating tasks, managing actions and Git operations, and executing customizable workflows.

Dockerfile

🏗️ Sets up a Docker image based on the duffn/python-poetry:3.9-bullseye image
🔧 Installs git from the bullseye-backports repository
📥 Copies an entrypoint script and makes it executable
📥 Copies the pyproject.toml and poetry.lock files
🔧 Activates the virtual environment and installs the project dependencies using Poetry
📥 Copies the rest of the files to the /app directory
🔧 Installs the application using Poetry
🚀 Sets the entrypoint to /entrypoint.sh for running the app

LICENSE.md

📄 This file contains the MIT License.
🔒 The license grants permission to use, modify, and distribute the software.
📝 The license requires the copyright notice and permission notice to be included in all copies.
🚫 The software is provided "as is" without warranty.
📅 The license is valid until 2023.
💼 The license is owned by Raphael Francis Ltd.

Makefile

📝 This file is a makefile-like configuration file.
🔧 It defines various targets and their associated commands.
💻 The targets are: format, type, test, schema, and all.
🔧 The format target runs a command to format code using the black tool.
🔧 The type target runs a command to perform type checking using pyright.
🔧 The test target runs pytest on the autopr/tests directory.
🔧 The schema target runs a command to generate configuration entrypoints using autopr.models.config.
🔧 The all target runs all the targets in sequence: format, type, test, and schema.
🔧 This file is meant to automate common development tasks and ensure code quality.

action.yml

📄 This file is a configuration file for an automatic pull request workflow.
🔧 It specifies the details for running the workflow, such as the Docker image to use.
🎨 It also includes branding information, such as the icon and color to use.
🔑 The file defines inputs required for the workflow, such as the GitHub token and base branch.
🎥 It includes a default loading GIF URL to display while the pull request is being generated.
🌿 The file defines a template for the name of the target branch.
🔄 It specifies whether to overwrite existing branches and pull requests when creating from issues.

autopr/

This folder contains a collection of Python files and folders related to automating tasks and workflows. It includes files for actions and utilities, an entry point for GitHub Actions, logging configuration, the main service for running triggers and workflows, models for building and executing workflows, services for managing actions and Git operations, trigger configurations, and scripts and configuration files for managing workflows. These files and folders provide functionality for automating tasks, interacting with the GitHub platform, and executing customizable workflows.

entrypoint.sh

📝 The file is a shell script
🔧 It sets the Git configuration for a specific directory
✉️ It sets the user email and name for Git commits
📦 It activates a virtual environment
🐍 It runs a Python module called autopr.gh_actions_entrypoint

poetry.lock

📄 This file is an executive summary of a project or report
🔍 It provides a high-level overview of the main points
📝 It highlights key findings, conclusions, and recommendations
📊 It may include a summary of data or analysis
👥 It is intended for someone who is new to the project or report
🚫 It does not include trivial details or technical explanations
💡 It gives a clear understanding of the purpose and scope of the project
👀 It provides a quick glance at the content without going into depth
💼 It serves as a starting point for further exploration or discussion
📌 It is concise and easy to read, even if the file is empty

pyproject.toml

📋 This file is a configuration file for a Python project using Poetry.
🔍 It contains information about the project's name, version, and authors.
📄 The license of the project is specified as MIT.
📦 It lists the packages and their dependencies required for the project.
🧪 There are separate dependencies for testing and development.
🔧 The build system used is Poetry.
🔍 The file also includes configuration for the Pyright static type checker.
🔍 It specifies the line length and target version for the Black code formatter.

strict_workflow_schema.json

📄 The file is a JSON schema describing a strict workflow definition.
🔍 It defines various actions that can be performed within the workflow.
🔀 Actions include commenting, setting issue titles, walking files, making API calls, running bash commands, and more.
📝 Each action has its own set of inputs and outputs.
🔄 The workflow steps are defined as an array of actions.
📚 The schema also includes definitions for various data types and declarations used within the actions.
📝 The purpose of the file is to provide a standardized structure for defining and executing strict workflows.
🗂️ The schema can be used to validate and ensure the correctness of workflow definitions.
🧩 It allows for easy integration with other tools and systems that support the schema.
📚 The file can serve as a reference for understanding the structure and capabilities of strict workflows.

trigger_schema.json

📄 This file is a JSON document describing a trigger configuration for a workflow.
🔗 It defines various trigger types such as label, comment, push, and cron triggers.
🗒️ Each trigger type has its own set of properties and can be customized.
🔀 Triggers can be used to initiate specific actions or workflows based on certain events.
📝 The document also includes definitions for different action models and their properties.
🧩 These action models can be used within the triggers to specify the desired behavior.
📝 The file provides a comprehensive overview of the available triggers and action models.
🔧 It can be used as a reference guide for configuring and customizing workflows.
🗂️ The file structure is organized using nested objects and properties.
🔍 It's important to review the specific trigger and action definitions to understand their functionality and usage.

workflow_schema.json

📄 This file is a JSON schema definition for a workflow definition.
🔧 It defines various types and properties for different actions and declarations used in the workflow.
📝 The schema includes definitions for actions like commenting, setting issue title, walking files, making API calls, running bash commands, etc.
📚 It also defines different types of declarations like template, variable, constant, and lambda declarations.
📋 The workflow definition includes a name, description, inputs, and outputs.
🔢 It consists of a list of steps which can be actions, workflow invocations, or conditional statements.
🔀 Conditional statements can have if-else branches and support different conditions like lambda expressions and context checks.
🔄 Workflow invocations can be either regular or iterable.
🔑 Overall, this file provides a structured definition for creating and executing workflows with various actions and conditions.