1862 Readme Jeremy Plugins 07594597

Jeremy's Production AI Agent Development Plugins

Date: 2025-10-27 Status: Production Ready Author: Jeremy Longshore

Overview

Complete suite of production-ready plugins for building, deploying, and scaling AI agents using Google Cloud Platform, Vertex AI, Firebase Genkit, and multi-model support (Gemini, Claude, GPT).

🚀 Plugins Created

1. jeremy-google-adk

Google Agent Development Kit (ADK) SDK Starter Kit

• Build React-pattern agents (Reasoning + Acting loops)
• Multi-agent orchestration systems
• Production scaffolding with testing frameworks
• Based on: https://github.com/google/adk-python

Installation:

/plugin install jeremy-google-adk@jeremylongshore

2. jeremy-vertex-ai

Vertex AI & Gemini Integration Plugin

• Gemini 1.5 Pro/Flash model integration
• RAG implementation with Vertex AI Search
• Multi-modal processing (text, image, video, audio)
• Production deployment on Cloud Run/GKE
• Based on: https://github.com/GoogleCloudPlatform/generative-ai

Installation:

/plugin install jeremy-vertex-ai@jeremylongshore

3. jeremy-genkit

Firebase Genkit Multi-Model Framework

• Support for JavaScript, Python, and Go
• Multi-model orchestration (Gemini, Claude, OpenAI)
• Built-in developer UI and testing tools
• RAG pipelines and function calling
• Based on: https://github.com/firebase/genkit

Installation:

/plugin install jeremy-genkit@jeremylongshore

4. jeremy-container-agent (Coming Soon)

Docker + Terraform + Cloud Run Deployment

• Production Docker containers
• Terraform infrastructure as code
• Auto-scaling on Cloud Run
• Kubernetes deployment options

5. jeremy-agent-starter (Coming Soon)

Production Agent Templates

• Based on GoogleCloudPlatform/agent-starter-pack
• 60-second agent setup
• CI/CD pipelines included
• Monitoring and observability

6. jeremy-docker-agent (Coming Soon)

Docker Container Generator

• Multi-stage builds
• Security hardening
• Health checks and metrics
• Docker Compose orchestration

🎯 Key Features

Multi-Model Support

All plugins support multiple LLM providers:

• Google: Gemini 1.5 Pro, Gemini 1.5 Flash, PaLM 2
• Anthropic: Claude 3.5 Sonnet, Claude 3 Haiku
• OpenAI: GPT-4, GPT-3.5 Turbo
• Open Source: Llama 2, Mistral, via Ollama

Production Ready

• Comprehensive error handling
• Retry logic with exponential backoff
• Structured logging (JSON format)
• Prometheus metrics export
• Health check endpoints
• Rate limiting and caching

Cloud Native

• Deploy to Cloud Run (scale to zero)
• Kubernetes manifests included
• Terraform configurations
• Secret Manager integration
• Cloud Monitoring dashboards

📚 Documentation Structure

Each plugin includes:

jeremy-[plugin-name]/
├── plugin.json                 # Plugin manifest
├── skills/                     # Auto-invoked skills
│   └── [skill-name]/
│       └── SKILL.md           # Comprehensive documentation
├── slash-commands/             # Manual triggers
│   ├── create-*.md
│   └── deploy-*.md
├── examples/                   # Working examples
│   ├── simple-agent/
│   ├── multi-agent/
│   └── production/
├── tests/                      # Test suites
│   ├── unit/
│   └── integration/
├── terraform/                  # Infrastructure as code
│   ├── cloud-run/
│   └── gke/
├── docker/                     # Container configs
│   ├── Dockerfile
│   └── docker-compose.yml
└── README.md                   # Getting started guide

🛠️ Quick Start

1. Install a Plugin

# Install the Google ADK plugin
/plugin install jeremy-google-adk@jeremylongshore

# Install Vertex AI plugin
/plugin install jeremy-vertex-ai@jeremylongshore

# Install Firebase Genkit plugin
/plugin install jeremy-genkit@jeremylongshore

2. Create Your First Agent

# Using ADK
adk-agent create \
  --name my-agent \
  --pattern react \
  --model gemini-1.5-pro

# Using Vertex AI
vertex-agent create \
  --name my-agent \
  --type rag-enhanced \
  --deploy-target cloud-run

# Using Genkit
genkit-app create \
  --name my-app \
  --language typescript \
  --models gemini,claude

3. Deploy to Production

# Build container
docker build -t my-agent .

# Deploy to Cloud Run
gcloud run deploy my-agent \
  --image gcr.io/project/my-agent \
  --platform managed \
  --region us-central1

# Or use Terraform
cd terraform/
terraform init
terraform apply

💰 Cost Optimization

All plugins include cost optimization strategies:

Model Selection

# Automatic model selection based on complexity
models = {
    "simple": "gemini-1.5-flash",     # $0.35/1M tokens
    "standard": "gemini-1.5-pro",     # $3.50/1M tokens
    "complex": "claude-3.5-sonnet"    # $3/1M tokens
}

Caching

• Response caching for repeated queries
• Embedding caching for RAG
• Tool result caching

Infrastructure

• Cloud Run scale-to-zero for development
• Spot/Preemptible instances for batch processing
• Committed use discounts for production

🔒 Security

API Key Management

• Google Secret Manager integration
• Environment variable injection
• Never hardcoded in source

Container Security

• Non-root user execution
• Minimal base images
• Regular vulnerability scanning
• Network policies

Data Protection

• Encryption at rest
• TLS for all communications
• VPC Service Controls
• IAM least privilege

📊 Monitoring & Observability

Metrics

• Request latency (p50, p95, p99)
• Token usage and costs
• Error rates by type
• Model performance scores

Logging

{
  "timestamp": "2025-10-27T10:30:00Z",
  "request_id": "abc-123",
  "agent": "my-agent",
  "model": "gemini-1.5-pro",
  "latency_ms": 450,
  "tokens": {
    "prompt": 150,
    "completion": 200
  },
  "cost": 0.001225
}

Dashboards

• Cloud Monitoring dashboards
• Custom Grafana templates
• Cost tracking reports
• Performance analytics

🧪 Testing

Unit Tests

pytest tests/unit --cov=agent --cov-report=html

Integration Tests

pytest tests/integration --env=staging

Load Tests

locust -f tests/load/locustfile.py --users 100 --spawn-rate 10

🚦 CI/CD

GitHub Actions

name: Deploy Agent
on:
  push:
    branches: [main]

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - run: pytest tests/

  deploy:
    needs: test
    runs-on: ubuntu-latest
    steps:
      - run: gcloud run deploy

Cloud Build

steps:
  - name: 'gcr.io/cloud-builders/docker'
    args: ['build', '-t', 'gcr.io/$PROJECT_ID/agent', '.']

  - name: 'gcr.io/cloud-builders/docker'
    args: ['push', 'gcr.io/$PROJECT_ID/agent']

  - name: 'gcr.io/google.com/cloudsdktool/cloud-sdk'
    args: ['run', 'deploy', 'agent', '--image', 'gcr.io/$PROJECT_ID/agent']

📈 Performance Benchmarks

🤝 Integration Examples

Combining Plugins

# Use ADK for agent structure
from jeremy_google_adk import ReactAgent

# Use Vertex AI for LLM
from jeremy_vertex_ai import GeminiModel

# Use Genkit for multi-model
from jeremy_genkit import ModelOrchestrator

class HybridAgent(ReactAgent):
    def __init__(self):
        self.primary_model = GeminiModel("gemini-1.5-pro")
        self.fallback_model = ClaudeModel("claude-3.5-sonnet")
        self.orchestrator = ModelOrchestrator([
            self.primary_model,
            self.fallback_model
        ])

🔄 Roadmap

Q4 2025

• jeremy-google-adk
• jeremy-vertex-ai
• jeremy-genkit
• jeremy-container-agent
• jeremy-agent-starter
• jeremy-docker-agent

Q1 2026

• jeremy-langchain integration
• jeremy-llamaindex support
• jeremy-autogen compatibility
• jeremy-crew-ai orchestration

📞 Support

• GitHub Issues: https://github.com/jeremylongshore/jeremy-plugins/issues
• Documentation: https://claudecodeplugins.io/jeremy-plugins
• Email: jeremy@claudecodeplugins.io

📄 License

All plugins are MIT licensed and open source.

Built with production experience from:

• Google Cloud Platform official samples
• Firebase Genkit framework
• Vertex AI production deployments
• Real-world agent architectures

Ready to scale from 0 to millions of requests.

Let's build the future of AI agents together! 🚀