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INSTALL.md

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Installation

Method 1: Use Docker image (no installation required)

To request a review for a PR, or ask a question about a PR, you can run directly from the Docker image. Here's how:

  1. To request a review for a PR, run the following command:
docker run --rm -it -e OPENAI.KEY=<your key> -e GITHUB.USER_TOKEN=<your token> codiumai/pr-agent --pr_url <pr_url> review
  1. To ask a question about a PR, run the following command:
docker run --rm -it -e OPENAI.KEY=<your key> -e GITHUB.USER_TOKEN=<your token> codiumai/pr-agent --pr_url <pr_url> ask "<your question>"

Possible questions you can ask include:

  • What is the main theme of this PR?
  • Is the PR ready for merge?
  • What are the main changes in this PR?
  • Should this PR be split into smaller parts?
  • Can you compose a rhymed song about this PR?

Method 2: Run as a GitHub Action

You can use our pre-built Github Action Docker image to run PR-Agent as a Github Action.

  1. Add the following file to your repository under .github/workflows/pr_agent.yml:
on:
  pull_request:
  issue_comment:
jobs:
  pr_agent_job:
    runs-on: ubuntu-latest
    name: Run pr agent on every pull request, respond to user comments
    steps:
      - name: PR Agent action step
        id: pragent
        uses: Codium-ai/pr-agent@main
        env:
          OPENAI_KEY: ${{ secrets.OPENAI_KEY }}
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
  1. Add the following secret to your repository under Settings > Secrets:
OPENAI_KEY: <your key>

The GITHUB_TOKEN secret is automatically created by GitHub.

  1. Merge this change to your main branch. When you open your next PR, you should see a comment from github-actions bot with a review of your PR, and instructions on how to use the rest of the tools.

  2. You may configure PR-Agent by adding environment variables under the env section corresponding to any configurable property in the configuration file. Some examples:

      env:
        # ... previous environment values
        OPENAI.ORG: "<Your organization name under your OpenAI account>"
        PR_REVIEWER.REQUIRE_TESTS_REVIEW: "false" # Disable tests review
        PR_CODE_SUGGESTIONS.NUM_CODE_SUGGESTIONS: 6 # Increase number of code suggestions

Method 3: Run from source

  1. Clone this repository:
git clone https://github.com/Codium-ai/pr-agent.git
  1. Install the requirements in your favorite virtual environment:
pip install -r requirements.txt
  1. Copy the secrets template file and fill in your OpenAI key and your GitHub user token:
cp pr_agent/settings/.secrets_template.toml pr_agent/settings/.secrets.toml
# Edit .secrets.toml file
  1. Add the pr_agent folder to your PYTHONPATH, then run the cli.py script:
export PYTHONPATH=[$PYTHONPATH:]<PATH to pr_agent folder>
python pr_agent/cli.py --pr_url <pr_url> review
python pr_agent/cli.py --pr_url <pr_url> ask <your question>
python pr_agent/cli.py --pr_url <pr_url> describe
python pr_agent/cli.py --pr_url <pr_url> improve

Method 4: Run as a polling server

Request reviews by tagging your Github user on a PR

Follow steps 1-3 of method 2. Run the following command to start the server:

python pr_agent/servers/github_polling.py

Method 5: Run as a GitHub App

Allowing you to automate the review process on your private or public repositories.

  1. Create a GitHub App from the Github Developer Portal.

    • Set the following permissions:
      • Pull requests: Read & write
      • Issue comment: Read & write
      • Metadata: Read-only
    • Set the following events:
      • Issue comment
      • Pull request

  2. Generate a random secret for your app, and save it for later. For example, you can use:

WEBHOOK_SECRET=$(python -c "import secrets; print(secrets.token_hex(10))")

  1. Acquire the following pieces of information from your app's settings page:

    • App private key (click "Generate a private key" and save the file)
    • App ID

  2. Clone this repository:

git clone https://github.com/Codium-ai/pr-agent.git
  1. Copy the secrets template file and fill in the following: 
    cp pr_agent/settings/.secrets_template.toml pr_agent/settings/.secrets.toml
# Edit .secrets.toml file
    • Your OpenAI key.
    • Copy your app's private key to the private_key field.
    • Copy your app's ID to the app_id field.
    • Copy your app's webhook secret to the webhook_secret field.
    • Set deployment_type to 'app' in configuration.toml

The .secrets.toml file is not copied to the Docker image by default, and is only used for local development. If you want to use the .secrets.toml file in your Docker image, you can add remove it from the .dockerignore file. In most production environments, you would inject the secrets file as environment variables or as mounted volumes. For example, in order to inject a secrets file as a volume in a Kubernetes environment you can update your pod spec to include the following, assuming you have a secret named pr-agent-settings with a key named .secrets.toml:

       volumes:
        - name: settings-volume
          secret:
            secretName: pr-agent-settings
// ...
       containers:
// ...
          volumeMounts:
            - mountPath: /app/pr_agent/settings_prod
              name: settings-volume

Another option is to set the secrets as environment variables in your deployment environment, for example OPENAI.KEY and GITHUB.USER_TOKEN.

  1. Build a Docker image for the app and optionally push it to a Docker repository. We'll use Dockerhub as an example:
docker build . -t codiumai/pr-agent:github_app --target github_app -f docker/Dockerfile
docker push codiumai/pr-agent:github_app  # Push to your Docker repository

  1. Host the app using a server, serverless function, or container environment. Alternatively, for development and debugging, you may use tools like smee.io to forward webhooks to your local machine. You can check Deploy as a Lambda Function

  2. Go back to your app's settings, and set the following:

    • Webhook URL: The URL of your app's server or the URL of the smee.io channel.
    • Webhook secret: The secret you generated earlier.

  3. Install the app by navigating to the "Install App" tab and selecting your desired repositories.

Deploy as a Lambda Function

  1. Follow steps 1-5 of Method 5.
  2. Build a docker image that can be used as a lambda function 
    docker buildx build --platform=linux/amd64 . -t codiumai/pr-agent:serverless -f docker/Dockerfile.lambda
  3. Push image to ECR 
    docker tag codiumai/pr-agent:serverless <AWS_ACCOUNT>.dkr.ecr.<AWS_REGION>.amazonaws.com/codiumai/pr-agent:serverless
docker push <AWS_ACCOUNT>.dkr.ecr.<AWS_REGION>.amazonaws.com/codiumai/pr-agent:serverless
  4. Create a lambda function that uses the uploaded image. Set the lambda timeout to be at least 3m.
  5. Configure the lambda function to have a Function URL.
  6. Go back to steps 8-9 of Method 5 with the function url as your Webhook URL. The Webhook URL would look like https://<LAMBDA_FUNCTION_URL>/api/v1/github_webhooks