# probot

**Repository Path**: mirrors_pytorch/probot

## Basic Information

- **Project Name**: probot
- **Description**: PyTorch GitHub bot written in probot
- **Primary Language**: Unknown
- **License**: ISC
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-10-22
- **Last Updated**: 2025-09-27

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# This repository is archived and our Probot stuff has moved to https://github.com/pytorch/test-infra/tree/main/torchci


# pytorch-probot

A GitHub App built with [Probot](https://github.com/probot/probot) that implements bot actions for PyTorch

This bot implements a few behaviors.  **This bot currently only
implements idempotent behaviors (i.e., it is harmless if the bot process
events multiple times.**  If you add support for non-idempotent
behaviors, you need to make sure only the GitHub Action or AWS Lambda is
enabled.

## auto-cc-bot

Add an issue to your project like https://github.com/pytorch/pytorch/issues/24422
and add a `.github/pytorch-probot.yml` file with:

```yml
tracking_issue: 24422
```

Based on who is listed in the tracking issue, the bot will automatically
CC people when labels are added to an issue.

## auto-label-bot

* If an issue is labeled **high priority**, also label it
  **triage review**
* If an issue is labeled **topic: flaky-tests**, also label it
  **high priority** and **triage review**
* If an issue or pull request contains a regex in its title, label
  it accordingly, e.g., a title containing 'ROCm' would yield the
  **module: rocm** label.

## trigger-circleci-workflows

* Trigger circleci workflows based off of labeling events / push events

Configuration (`.github/pytorch-circleci-labels.yml`) should look similar to this:
```yml
labels_to_circle_params:
  # Refers to github labels
  ci/binaries:
    # Refers to circleci parameters
    # For circleci documentation on pipeline parameters check:
    #      https://circleci.com/docs/2.0/pipeline-variables/#pipeline-parameters-in-configuration
    parameter: run_binaries_tests
    # [[optional]] Automatically trigger workflows with parameters on push
    default_true_on:
      branches:
        - nightly
        # Regex is allowed as well
        - ci-all/.*
      # Even works on tags!
      tags:
        - v[0-9]+(\.[0-9]+)*-rc[0-9]+
  # Multiple label / parameters can be defined
  ci/bleh:
    parameter: run_bleh_tests
  ci/foo:
    parameter: run_foo_tests
```

## Setup

```sh
# Install dependencies
yarn install

# Run the tests
yarn test

# Run the bot
yarn start
```

## Live testing as a GitHub App

If you want to smoketest the bot on a test repository, you'll need to
create a GitHub app.  Go to the webpage from probot; it will walk
through the process.

## Deploying GitHub Actions

Although a GitHub App is convenient for testing, it requires an actual
server to deploy in prod.  Previously we ran the server on AWS, but this
deployment process was substantially more involved.  GitHub Actions
deployment is simpler.  Follow the instructions at
https://github.com/actions/toolkit/blob/master/docs/action-versioning.md

Right now the GitHub Actions deployment is a little rocky because
massive queueing in the PyTorch repository means it takes something
like 30min before actions are run.  So we are also running AWS
side-by-side.

## Deploying to AWS

[`.github/workflows/build.yml`](.github/workflows/build.yml) will build and deploy the code on every push to `main`.

## Contributing

If you have suggestions for how pytorchbot could be improved, or want to report a bug, open an issue! We'd love all and any contributions.

For more, check out the [Contributing Guide](CONTRIBUTING.md).

## License

[ISC](LICENSE) © 2019 Edward Z. Yang <ezyang@fb.com> (https://pytorch.org)