34e75bef96
- Add 6 specialized quality assessment commands - Implement risk-based testing with scoring - Create quality gate system with deterministic decisions - Add comprehensive test design and NFR validation - Update documentation with stage-based workflow integration
110 lines
5.2 KiB
Markdown
110 lines
5.2 KiB
Markdown
# BMad Expansion Pack: Google Cloud Vertex AI Agent System
|
|
|
|
[](https://opensource.org/licenses/MIT)
|
|
[](https://www.google.com/search?q=https://github.com/antmikinka/BMAD-METHOD)
|
|
[](https://cloud.google.com/)
|
|
|
|
This expansion pack provides a complete, deployable starter kit for building and hosting sophisticated AI agent systems on Google Cloud Platform (GCP). It bridges the gap between the BMad Method's natural language framework and a production-ready cloud environment, leveraging Google Vertex AI, Cloud Run, and the Google Agent Development Kit (ADK).
|
|
|
|
## Features
|
|
|
|
- **Automated GCP Setup**: `gcloud` scripts to configure your project, service accounts, and required APIs in minutes.
|
|
- **Production-Ready Deployment**: Includes a `Dockerfile` and `cloudbuild.yaml` for easy, repeatable deployments to Google Cloud Run.
|
|
- **Rich Template Library**: A comprehensive set of BMad-compatible templates for Teams, Agents, Tasks, Workflows, Documents, and Checklists.
|
|
- **Pre-configured Agent Roles**: Includes powerful master templates for key agent archetypes like Orchestrators and Specialists.
|
|
- **Highly Customizable**: Easily adapt the entire system with company-specific variables and industry-specific configurations.
|
|
- **Powered by Google ADK**: Built on the official Google Agent Development Kit for robust and native integration with Vertex AI services.
|
|
|
|
## Prerequisites
|
|
|
|
Before you begin, ensure you have the following installed and configured:
|
|
|
|
- A Google Cloud Platform (GCP) Account with an active billing account.
|
|
- The [Google Cloud SDK (`gcloud` CLI)](<https://www.google.com/search?q=%5Bhttps://cloud.google.com/sdk/docs/install%5D(https://cloud.google.com/sdk/docs/install)>) installed and authenticated.
|
|
- [Docker](https://www.docker.com/products/docker-desktop/) installed on your local machine.
|
|
- Python 3.11+
|
|
|
|
## Quick Start Guide
|
|
|
|
Follow these steps to get your own AI agent system running on Google Cloud.
|
|
|
|
### 1\. Configure Setup Variables
|
|
|
|
The setup scripts use placeholder variables. Before running them, open the files in the `/scripts` directory and replace the following placeholders with your own values:
|
|
|
|
- `{{PROJECT_ID}}`: Your unique Google Cloud project ID.
|
|
- `{{COMPANY_NAME}}`: Your company or project name (used for naming resources).
|
|
- `{{LOCATION}}`: The GCP region you want to deploy to (e.g., `us-central1`).
|
|
|
|
### 2\. Run the GCP Setup Scripts
|
|
|
|
Execute the setup scripts to prepare your Google Cloud environment.
|
|
|
|
```bash
|
|
# Navigate to the scripts directory
|
|
cd scripts/
|
|
|
|
# Run the project configuration script
|
|
sh 1-initial-project-config.sh
|
|
|
|
# Run the service account setup script
|
|
sh 2-service-account-setup.sh
|
|
```
|
|
|
|
These scripts will enable the necessary APIs, create a service account, assign permissions, and download a JSON key file required for authentication.
|
|
|
|
### 3\. Install Python Dependencies
|
|
|
|
Install the required Python packages for the application.
|
|
|
|
```bash
|
|
# From the root of the expansion pack
|
|
pip install -r requirements.txt
|
|
```
|
|
|
|
### 4\. Deploy to Cloud Run
|
|
|
|
Deploy the entire agent system as a serverless application using Cloud Build.
|
|
|
|
```bash
|
|
# From the root of the expansion pack
|
|
gcloud builds submit --config deployment/cloudbuild.yaml .
|
|
```
|
|
|
|
This command will build the Docker container, push it to the Google Container Registry, and deploy it to Cloud Run. Your agent system is now live\!
|
|
|
|
## How to Use
|
|
|
|
Once deployed, the power of this system lies in its natural language templates.
|
|
|
|
1. **Define Your Organization**: Go to `/templates/teams` and use the templates to define your agent teams (e.g., Product Development, Operations).
|
|
2. **Customize Your Agents**: In `/templates/agents`, use the `Master-Agent-Template.yaml` to create new agents or customize the existing Orchestrator and Specialist templates. Define their personas, skills, and commands in plain English.
|
|
3. **Build Your Workflows**: In `/templates/workflows`, link agents and tasks together to create complex, automated processes.
|
|
|
|
The deployed application reads these YAML and Markdown files to dynamically construct and run your AI workforce. When you update a template, your live agents automatically adopt the new behaviors.
|
|
|
|
## What's Included
|
|
|
|
This expansion pack has a comprehensive structure to get you started:
|
|
|
|
```
|
|
/
|
|
├── deployment/ # Dockerfile and cloudbuild.yaml for deployment
|
|
├── scripts/ # GCP setup scripts (project config, service accounts)
|
|
├── src/ # Python source code (main.py, settings.py)
|
|
├── templates/
|
|
│ ├── agents/ # Master, Orchestrator, Specialist agent templates
|
|
│ ├── teams/ # Team structure templates
|
|
│ ├── tasks/ # Generic and specialized task templates
|
|
│ ├── documents/ # Document and report templates
|
|
│ ├── checklists/ # Quality validation checklists
|
|
│ ├── workflows/ # Workflow definition templates
|
|
│ └── ...and more
|
|
├── config/ # Customization guides and variable files
|
|
└── requirements.txt # Python package dependencies
|
|
```
|
|
|
|
## Contributing
|
|
|
|
Contributions are welcome\! Please follow the main project's `CONTRIBUTING.md` guidelines. For major changes or new features for this expansion pack, please open an issue or discussion first.
|