google-github-actions/run-gemini-cli

README

run-gemini-cli

Overview

run-gemini-cli is a GitHub Action that integrates Gemini into your development workflow via the Gemini CLI. It acts both as an autonomous agent for critical routine coding tasks, and an on-demand collaborator you can quickly delegate work to.

Use it to perform GitHub pull request reviews, triage issues, perform code analysis and modification, and more using Gemini conversationally (e.g., @gemini-cli fix this issue) directly inside your GitHub repositories.

run-gemini-cli

Features

Automation: Trigger workflows based on events (e.g. issue opening) or schedules (e.g. nightly).
On-demand Collaboration: Trigger workflows in issue and pull request comments by mentioning the Gemini CLI (e.g., @gemini-cli /review).
Extensible with Tools: Leverage Gemini models' tool-calling capabilities to interact with other CLIs like the GitHub CLI (gh).
Customizable: Use a GEMINI.md file in your repository to provide project-specific instructions and context to Gemini CLI.

Quick Start

Get started with Gemini CLI in your repository in just a few minutes:

1. Get a Gemini API Key

Obtain your API key from Google AI Studio with generous free-of-charge quotas

2. Add it as a GitHub Secret

Store your API key as a secret named GEMINI_API_KEY in your repository:

Go to your repository's Settings > Secrets and variables > Actions
Click New repository secret
Name: GEMINI_API_KEY, Value: your API key

3. Update your .gitignore

Add the following entries to your .gitignore file:

# gemini-cli settings
.gemini/

# GitHub App credentials
gha-creds-*.json

4. Choose a Workflow

You have two options to set up a workflow:

Option A: Use setup command (Recommended)

Start the Gemini CLI in your terminal:
```
gemini
```
In Gemini CLI in your terminal, type:
```
/setup-github
```

Option B: Manually copy workflows

Copy the pre-built workflows from the examples/workflows directory to your repository's .github/workflows directory. Note: the gemini-dispatch.yml workflow must also be copied, which triggers the workflows to run.

5. Try it out!

Pull Request Review:

Open a pull request in your repository and wait for automatic review
Comment @gemini-cli /review on an existing pull request to manually trigger a review

Issue Triage:

Open an issue and wait for automatic triage
Comment @gemini-cli /triage on existing issues to manually trigger triaging

General AI Assistance:

In any issue or pull request, mention @gemini-cli followed by your request
Examples:
- @gemini-cli explain this code change
- @gemini-cli suggest improvements for this function
- @gemini-cli help me debug this error
- @gemini-cli write unit tests for this component

Workflows

This action provides several pre-built workflows for different use cases. Each workflow is designed to be copied into your repository's .github/workflows directory and customized as needed.

Gemini Dispatch

This workflow acts as a central dispatcher for Gemini CLI, routing requests to the appropriate workflow based on the triggering event and the command provided in the comment. For a detailed guide on how to set up the dispatch workflow, go to the Gemini Dispatch workflow documentation.

Issue Triage

This action can be used to triage GitHub Issues automatically or on a schedule. For a detailed guide on how to set up the issue triage system, go to the GitHub Issue Triage workflow documentation.

Pull Request Review

This action can be used to automatically review pull requests when they are opened. For a detailed guide on how to set up the pull request review system, go to the GitHub PR Review workflow documentation.

Gemini CLI Assistant

This type of action can be used to invoke a general-purpose, conversational Gemini AI assistant within the pull requests and issues to perform a wide range of tasks. For a detailed guide on how to set up the general-purpose Gemini CLI workflow, go to the Gemini Assistant workflow documentation.

Configuration

Inputs

gcp_location: (Optional) The Google Cloud location.

gcp_project_id: (Optional) The Google Cloud project ID.

gcp_service_account: (Optional) The Google Cloud service account email.

gcp_workload_identity_provider: (Optional) The Google Cloud Workload Identity Provider.

gcp_token_format: (Optional, default: access_token) The token format for authentication. Set to "access_token" to generate access tokens (requires service account), or set to empty string for direct WIF. Can be "access_token" or "id_token".

gcp_access_token_scopes: (Optional, default: https://www.googleapis.com/auth/cloud-platform,https://www.googleapis.com/auth/userinfo.email,https://www.googleapis.com/auth/userinfo.profile) The access token scopes when using token_format "access_token". Comma-separated list of OAuth 2.0 scopes.

gemini_api_key: (Optional) The API key for the Gemini API.

gemini_cli_version: (Optional, default: latest) The version of the Gemini CLI to install. Can be "latest", "preview", "nightly", a specific version number, or a git branch, tag, or commit. For more information, see Gemini CLI releases.
gemini_debug: (Optional) Enable debug logging and output streaming.

gemini_model: (Optional) The model to use with Gemini.

google_api_key: (Optional) The Vertex AI API key to use with Gemini.

prompt: (Optional, default: You are a helpful assistant.) A string passed to the Gemini CLI's --prompt argument.
settings: (Optional) A JSON string written to .gemini/settings.json to configure the CLI's project settings. For more details, see the documentation on settings files.
use_gemini_code_assist: (Optional, default: false) Whether to use Code Assist for Gemini model access instead of the default Gemini API key. For more information, see the Gemini CLI documentation.
use_vertex_ai: (Optional, default: false) Whether to use Vertex AI for Gemini model access instead of the default Gemini API key. For more information, see the Gemini CLI documentation.
extensions: (Optional) A list of Gemini CLI extensions to install.

upload_artifacts: (Optional, default: false) Whether to upload artifacts to the github action.

use_pnpm: (Optional, default: false) Whether or not to use pnpm instead of npm to install gemini-cli

workflow_name: (Optional, default: ${{ github.workflow }}) The GitHub workflow name, used for telemetry purposes.

github_pr_number: (Optional, default: ${{ github.event.pull_request.number }}) The Pull Request number the CLI is operating on. Defaults to the event payload.

github_issue_number: (Optional, default: ${{ github.event.issue.number }}) The Issue number (or comma-separated list of issue numbers) the CLI is operating on. Defaults to the event payload.

Outputs

summary: The summarized output from the Gemini CLI execution.

error: The error output from the Gemini CLI execution, if any.

Repository Variables

We recommend setting the following values as repository variables so they can be reused across all workflows. Alternatively, you can set them inline as action inputs in individual workflows or to override repository-level values.

Name	Description	Type	Required	When Required
`GEMINI_DEBUG`	Enables debug logging for the Gemini CLI.	Variable	No	Never
`GEMINI_CLI_VERSION`	Controls which version of the Gemini CLI is installed.	Variable	No	Pinning the CLI version
`GCP_WIF_PROVIDER`	Full resource name of the Workload Identity Provider.	Variable	No	Using Google Cloud
`GOOGLE_CLOUD_PROJECT`	Google Cloud project for inference and observability.	Variable	No	Using Google Cloud
`SERVICE_ACCOUNT_EMAIL`	Google Cloud service account email address. Optional - only needed for WIF with service account (not required for direct WIF).	Variable	No	Using WIF with service account
`GOOGLE_CLOUD_LOCATION`	Region of the Google Cloud project.	Variable	No	Using Google Cloud
`GOOGLE_GENAI_USE_VERTEXAI`	Set to `true` to use Vertex AI	Variable	No	Using Vertex AI
`GOOGLE_GENAI_USE_GCA`	Set to `true` to use Gemini Code Assist	Variable	No	Using Gemini Code Assist
`APP_ID`	GitHub App ID for custom authentication.	Variable	No	Using a custom GitHub App

Warning

Do not use the DEBUG environment variable as it causes the Gemini CLI to hang waiting for node debugger to attach.

To add a repository variable:

Go to your repository's Settings > Secrets and variables > Actions > New variable.
Enter the variable name and value.
Save.

For details about repository variables, refer to the GitHub documentation on variables.

Secrets

You can set the following secrets in your repository:

Name	Description	Required	When Required
`GEMINI_API_KEY`	Your Gemini API key from Google AI Studio.	No	You don't have a GCP project.
`APP_PRIVATE_KEY`	Private key for your GitHub App (PEM format).	No	Using a custom GitHub App.
`GOOGLE_API_KEY`	Your Google API Key to use with Vertex AI.	No	You have a express Vertex AI account.

To add a secret:

Go to your repository's Settings > Secrets and variables >Actions > New repository secret.
Enter the secret name and value.
Save.

For more information, refer to the official GitHub documentation on creating and using encrypted secrets.

Authentication

This action requires authentication to both Google services (for Gemini AI) and the GitHub API.

Google Authentication

Choose the authentication method that best fits your use case:

Gemini API Key: The simplest method for projects that don't require Google Cloud integration
Workload Identity Federation: The most secure method for authenticating to Google Cloud services

GitHub Authentication

You can authenticate with GitHub in two ways:

Default GITHUB_TOKEN: For simpler use cases, the action can use the default GITHUB_TOKEN provided by the workflow.
Custom GitHub App (Recommended): For the most secure and flexible authentication, we recommend creating a custom GitHub App.

For detailed setup instructions for both Google and GitHub authentication, go to the Authentication documentation.

Observability

This action can be configured to send telemetry data (traces, metrics, and logs) to your own Google Cloud project. This allows you to monitor the performance and behavior of the Gemini CLI within your workflows, providing valuable insights for debugging and optimization.

For detailed instructions on how to set up and configure observability, go to the Observability documentation.

Extensions

The Gemini CLI can be extended with additional functionality through extensions. These extensions are installed from source from their GitHub repositories.

For detailed instructions on how to set up and configure extensions, go to the Extensions documentation.

Best Practices

To ensure the security, reliability, and efficiency of your automated workflows, we strongly recommend following our best practices. These guidelines cover key areas such as repository security, workflow configuration, and monitoring.

Key recommendations include:

Securing Your Repository: Implementing branch and tag protection, and restricting pull request approvers.
Workflow Configuration: Using Workload Identity Federation for secure authentication to Google Cloud, managing secrets effectively, and pinning action versions to prevent unexpected changes.
Monitoring and Auditing: Regularly reviewing action logs and enabling OpenTelemetry for deeper insights into performance and behavior.

For a comprehensive guide on securing your repository and workflows, please refer to our Best Practices documentation.

Customization

Create a GEMINI.md file in the root of your repository to provide project-specific context and instructions to Gemini CLI. This is useful for defining coding conventions, architectural patterns, or other guidelines the model should follow for a given repository.

Contributing

Contributions are welcome! Check out the Gemini CLI Contributing Guide for more details on how to get started.