Friday Gemini AI

Ruby gem for integrating with Google’s Gemini AI models.

gem install friday_gemini_ai

Set your API key in .env:

GEMINI_API_KEY=your_api_key

HarperBot provides automated PR code reviews using Google's Gemini AI. It supports two deployment modes:

• Self-hosted on Vercel for centralized, scalable analysis
• Install the HarperBot GitHub App once for all repositories
• No per-repository setup required
• Note: For self-hosting outside Vercel, use a production WSGI server like Gunicorn instead of Flask's development server for security and performance.

• Repository-specific GitHub Actions workflow
• Requires secrets setup per repository
• Automated setup: curl -fsSL https://raw.githubusercontent.com/bniladridas/friday_gemini_ai/main/bin/setup-harperbot | bash (use --update to update, --dry-run to preview)
• Note: This is legacy mode for existing users. New installations should use Webhook Mode for better scalability and centralized management

For detailed setup instructions, see harperbot/HarperBot.md.

Security Note for Automated Setup: The recommended curl | bash method downloads and executes code from the internet. For security, review the script at https://github.com/bniladridas/friday_gemini_ai/blob/main/bin/setup-harperbot before running. Alternatively, download first: curl -O https://raw.githubusercontent.com/bniladridas/friday_gemini_ai/main/bin/setup-harperbot, inspect, then bash setup-harperbot.

require 'friday_gemini_ai'
GeminiAI.load_env

client = GeminiAI::Client.new               # Default: gemini-2.5-pro
fast_client = GeminiAI::Client.new(model: :flash)

• Text: content generation, summaries, documentation
• Chat: multi-turn Q&A and assistants
• Image: image-to-text analysis
• CLI: for quick prototyping and automation

• Multiple Model Support: Gemini 2.5 + 2.0 families with automatic fallback
• Text Generation: configurable parameters, safety settings
• Image Analysis: base64 image input, detailed descriptions
• Chat: context retention, system instructions
• Security: API key masking, retries, and rate limits (1s default, 3s CI)

Gemini 1.5 models have been deprecated. Use:

• :pro → gemini-2.5-pro
• :flash → gemini-2.5-flash

Legacy options (:flash_2_0, :flash_lite) remain supported for backward compatibility.

# Required
GEMINI_API_KEY=your_api_key_here

# Optional
GEMINI_LOG_LEVEL=debug  # debug | info | warn | error

./bin/gemini test
./bin/gemini generate "Your prompt"
./bin/gemini chat

Friday Gemini AI includes a built-in GitHub Actions workflow for automated PR reviews via HarperBot, powered by Gemini AI.

💡 Install the HarperBot GitHub App for automated PR reviews across repositories.

HarperBot provides AI-driven code review and analysis directly in pull requests.

Key Capabilities:

• Configurable focus: all, security, performance, quality
• Code quality, documentation, and test coverage analysis
• Security & performance issue detection
• Inline review comments with actionable suggestions
• Clean, minimal, and structured feedback output

Workflow Mode (default)

1. Add repository secrets:

   • GEMINI_API_KEY
   • GITHUB_TOKEN (auto-provided by GitHub)

2. Configure .github/workflows/harperbot.yml

3. Optional: tune behavior via harperbot/config.yaml

Webhook Mode (Recommended)

• Deploy webhook-vercel branch to Vercel
• Create a GitHub App and set environment variables:
  • GEMINI_API_KEY: Your Google Gemini API key
  • HARPER_BOT_APP_ID: App ID from your GitHub App settings (found under "About" section)
  • HARPER_BOT_PRIVATE_KEY: Private key content (paste the entire .pem file)
  • WEBHOOK_SECRET: Random secret string for webhook verification
• Install the GitHub App on your repositories
• Webhooks will handle PR events automatically
• Preferred for scalability and centralized management

• Pull Requests: triggered on open, update, or reopen
• Push to main: runs Gemini CLI verification
• Concurrency control: cancels redundant runs for efficiency

Required permissions:

permissions:
  contents: read
  pull-requests: write
  issues: write
  statuses: write

bundle exec rake test          # Run tests
bundle exec rake rubocop       # Optional lint check
gem build *.gemspec            # Verify build

Using act:

brew install act
act -j test --container-architecture linux/amd64

client = GeminiAI::Client.new
puts client.generate_text('Write a haiku about Ruby')

image_data = Base64.strict_encode64(File.binread('path/to/image.jpg'))
puts client.generate_image_text(image_data, 'Describe this image')

messages = [
  { role: 'user', content: 'Hello!' },
  { role: 'model', content: 'Hi there!' },
  { role: 'user', content: 'Tell me about Ruby.' }
]
puts client.chat(messages, system_instruction: 'Be helpful and concise.')

Consistent commit messages are enforced via a local Git hook.

cp scripts/commit-msg .git/hooks/
chmod +x .git/hooks/commit-msg

Types: feat, fix, docs, style, refactor, test, chore Example:

git commit -m "feat: add user authentication"

• Overview
• Quickstart
• API Reference
• Cookbook
• Best Practices
• Changelog

Fork → Branch → Commit → Pull Request.

MIT – see LICENSE.