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Locally

Using pip package

Install the package:

pip install pr-agent

Then run the relevant tool with the script below.
Make sure to fill in the required parameters (user_token, openai_key, pr_url, command):

from pr_agent import cli
from pr_agent.config_loader import get_settings

def main():
    # Fill in the following values
    provider = "github" # github/gitlab/bitbucket/azure_devops
    user_token = "..."  #  user token
    openai_key = "..."  # OpenAI key
    pr_url = "..."      # PR URL, for example 'https://github.com/Codium-ai/pr-agent/pull/809'
    command = "/review" # Command to run (e.g. '/review', '/describe', '/ask="What is the purpose of this PR?"', ...)

    # Setting the configurations
    get_settings().set("CONFIG.git_provider", provider)
    get_settings().set("openai.key", openai_key)
    get_settings().set("github.user_token", user_token)

    # Run the command. Feedback will appear in GitHub PR comments
    cli.run_command(pr_url, command)


if __name__ == '__main__':
    main()

Using Docker image

A list of the relevant tools can be found in the tools guide.

To invoke a tool (for example review), you can run directly from the Docker image. Here's how:

  • For GitHub: 

    docker run --rm -it -e OPENAI.KEY=<your key> -e GITHUB.USER_TOKEN=<your token> codiumai/pr-agent:latest --pr_url <pr_url> review
    If you are using GitHub enterprise server, you need to specify the custom url as variable. For example, if your GitHub server is at https://github.mycompany.com, add the following to the command: 
    -e GITHUB.BASE_URL=https://github.mycompany.com/api/v3

  • For GitLab: 

    docker run --rm -it -e OPENAI.KEY=<your key> -e CONFIG.GIT_PROVIDER=gitlab -e GITLAB.PERSONAL_ACCESS_TOKEN=<your token> codiumai/pr-agent:latest --pr_url <pr_url> review

    If you have a dedicated GitLab instance, you need to specify the custom url as variable: 

    -e GITLAB.URL=<your gitlab instance url>

  • For BitBucket: 

    docker run --rm -it -e CONFIG.GIT_PROVIDER=bitbucket -e OPENAI.KEY=$OPENAI_API_KEY -e BITBUCKET.BEARER_TOKEN=$BITBUCKET_BEARER_TOKEN codiumai/pr-agent:latest --pr_url=<pr_url> review

For other git providers, update CONFIG.GIT_PROVIDER accordingly and check the pr_agent/settings/.secrets_template.toml file for environment variables expected names and values. The pr_agent uses Dynaconf to load settings from configuration files.

It is also possible to provide or override the configuration by setting the corresponding environment variables. You can define the corresponding environment variables by following this convention: <TABLE>__<KEY>=<VALUE> or <TABLE>.<KEY>=<VALUE>. The <TABLE> refers to a table/section in a configuration file and <KEY>=<VALUE> refers to the key/value pair of a setting in the configuration file.

For example, suppose you want to run pr_agent that connects to a self-hosted GitLab instance similar to an example above. You can define the environment variables in a plain text file named .env with the following content:

Warning: Never commit the .env file to version control system as it might contains sensitive credentials!

CONFIG__GIT_PROVIDER="gitlab"
GITLAB__URL="<your url>"
GITLAB__PERSONAL_ACCESS_TOKEN="<your token>"
OPENAI__KEY="<your key>"

Then, you can run pr_agent using Docker with the following command:

docker run --rm -it --env-file .env codiumai/pr-agent:latest <tool> <tool parameter>

Run from source

  1. Clone this repository:
git clone https://github.com/Codium-ai/pr-agent.git
  1. Navigate to the /pr-agent folder and install the requirements in your favorite virtual environment:
pip install -e .

Note: If you get an error related to Rust in the dependency installation then make sure Rust is installed and in your PATH, instructions: https://rustup.rs

  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
chmod 600 pr_agent/settings/.secrets.toml
# Edit .secrets.toml file
  1. Run the cli.py script:
python3 -m pr_agent.cli --pr_url <pr_url> review
python3 -m pr_agent.cli --pr_url <pr_url> ask <your question>
python3 -m pr_agent.cli --pr_url <pr_url> describe
python3 -m pr_agent.cli --pr_url <pr_url> improve
python3 -m pr_agent.cli --pr_url <pr_url> add_docs
python3 -m pr_agent.cli --pr_url <pr_url> generate_labels
python3 -m pr_agent.cli --issue_url <issue_url> similar_issue
...

[Optional] Add the pr_agent folder to your PYTHONPATH 

export PYTHONPATH=$PYTHONPATH:<PATH to pr_agent folder>

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