gemini-cli-on-adk

Gemini CLI Integration

This project demonstrates how Gemini CLI's non-interactive mode can significantly enhance ADK development workflows. The integration in app/agent.py provides a powerful gemini_cli tool that enables automated development tasks.

Key Benefits

• Automated Code Analysis: The agent can analyze codebases without manual file selection using Gemini CLI's intelligent file discovery
• Streamlined Development: Eliminates the need to manually specify which files to send to the agent
• Command Execution: Automated execution of development commands based on analysis results
• File Editing: Intelligent file modifications based on code analysis recommendations
• Error Handling: Built-in timeout and robust error handling for reliable execution

Development Efficiency Gains

The non-interactive mode saves significant development time by:

1. Intelligent File Selection: Automatically determines relevant files for specific tasks
2. Automated Code Generation: Generates boilerplate code, tests, and documentation
3. Command Automation: Executes development commands without manual intervention
4. Contextual Analysis: Provides codebase insights with full project context

Usage Example

The integrated gemini_cli function accepts tasks like:

• "Explain this codebase"
• "Generate a test plan"
• "Create unit tests for the agent module"
• "Analyze code quality and suggest improvements"

This integration demonstrates how Gemini CLI can serve as a powerful development accelerator within ADK agents.

Project Structure

This project is organized as follows:

gemini-cli-on-adk/
├── app/                 # Core application code
│   ├── agent.py         # Main agent logic
│   ├── server.py        # FastAPI Backend server
│   └── utils/           # Utility functions and helpers
├── deployment/          # Infrastructure and deployment scripts
├── notebooks/           # Jupyter notebooks for prototyping and evaluation
├── tests/               # Unit, integration, and load tests
├── Makefile             # Makefile for common commands
├── GEMINI.md            # AI-assisted development guide
└── pyproject.toml       # Project dependencies and configuration

Deployment

The ADK agent is designed to run on Google Cloud Run. It includes a Dockerfile and Cloud Build YAML configuration for seamless deployment using Google Cloud Build.

Prerequisites

• Vertex AI API must be enabled in your Google Cloud project
• Cloud Run service account must have access to Vertex AI services

Cloud Run Deployment

Build the container image using Cloud Build:

gcloud builds submit --config cloudbuild.yaml

You can also override the default substitution variables:

gcloud builds submit --config cloudbuild.yaml --substitutions=_REGION=us-east1,_REPO_NAME=my-repo,_SERVICE_NAME=my-service,_IMAGE_TAG=v1.0.0

Available substitution variables:

• _REGION: Deployment region (default: us-central1)
• _REPO_NAME: Artifact Registry repository name (default: container)
• _SERVICE_NAME: Cloud Run service name (default: gemini-cli-adk)
• _IMAGE_TAG: Docker image tag (default: latest)