Live Engagement Animal Scheduling Hub

An open-source solution for Google Calendar integration of your pet care routines and preferences.

Click the thumbnail below to watch LEASH in action...

This project integrates multiple services to provide AI-powered pet care calendar suggestions using local LLM models.

🏗️ Architecture Overview

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Frontend      │    │  Email Server   │    │  Agent Server   │
│   (React/Vite)  │    │   (FastAPI)     │    │   (FastAPI)     │
│   Port: 5173    │    │   Port: 5001    │    │   Port: 5002    │
└─────────────────┘    └─────────────────┘    └─────────────────┘
         │                       │                       │
         │                       │                       │
         ▼                       ▼                       ▼
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│      Profiles   │    │ Google Calendar │    │  Ollama LLM     │
│   (Static JSON) │    │      API        │    │  (Local Host)   │
└─────────────────┘    └─────────────────┘    └─────────────────┘

🚀 Quick Start

Prerequisites

1. Ollama - Install from https://ollama.ai
2. Node.js - For the frontend
3. Python 3.11+ - For backend services
4. Google Calendar API - Setup required for email server

1. Start Ollama

# Install a model
# ollama pull llama3.2
ollama pull mistral

# Start Ollama service
ollama serve

2. Start Agent Server

cd project/agent_server
conda create -n agent_server python=3.11
conda activate agent_server
pip install -r requirements.txt
python server.py
# Runs on http://localhost:5002

3. Start Email Server

cd project/email_server
conda create -n email_server python=3.11
conda activate email_server
pip install -r requirements.txt
python server.py
# Runs on http://localhost:5001

4. Start Frontend

cd project/frontend
npm install
npm run dev
# Runs on http://localhost:5173

🎯 How to Use

Schedule Dog Care Feature

1. Open the app at http://localhost:5173
2. Login to authenticate with Google Calendar
3. Navigate to any day in the calendar view
4. Click "Schedule Dog Care" button
5. Review AI suggestions in the modal popup
6. Accept or reject individual suggestions
7. Accepted events are automatically added to your Google Calendar

The AI Process

1. Data Collection: The frontend loads pet and owner profiles from public/profiles/
2. Context Building: Current calendar events and profile data are combined
3. AI Generation: Agent server uses Ollama LLM to generate personalized suggestions
4. Event Creation: Accepted suggestions are added to Google Calendar via email server

📁 Project Structure

project/
├── agent_server/          # AI service for calendar suggestions
│   ├── api/              # Swagger documentation
│   ├── app/              # FastAPI application
│   │   ├── router/       # API endpoints
│   │   └── services/     # Ollama integration
│   ├── models/           # Pydantic models
│   └── server.py         # Main server
├── email_server/         # Google Calendar integration
│   ├── app/              # FastAPI application
│   │   ├── auth/         # OAuth & session management
│   │   ├── router/       # API endpoints
│   │   └── services/     # Google Calendar API
│   └── server.py         # Main server
└── frontend/             # React application
    ├── public/profiles/  # User and pet profiles
    ├── src/components/   # React components
    └── src/services/     # API integration

🔧 Key Features

Agent Server

• Local LLM Integration: Uses Ollama for privacy-first AI
• Custom System Prompts: Tailored prompts for pet care scheduling
• Multiple Model Support: Works with llama3.2, mistral, etc.
• Intelligent Suggestions: Considers pet needs, owner schedule, existing events

Frontend Integration

• Profile Management: JSON-based pet and owner profiles
• Interactive UI: Modal-based suggestion review
• Real-time Updates: Calendar refreshes after accepting suggestions
• Error Handling: Graceful fallbacks for service issues

Calendar Integration

• Google Calendar API: Full read/write access to calendar
• OAuth Authentication: Secure Google login
• Event Validation: Prevents scheduling conflicts
• Bulk Operations: Efficient event creation

🐕 Profile Configuration

Pet Profiles (public/profiles/pets.json)

{
  "pets": [
    {
      "name": "Luna",
      "age": "4 years",
      "breed": "Border Collie",
      "weight": "45 lbs",
      "walk-time-per-day": "90 minutes",
      "energy-level": "high",
      "current_medications": [...],
      "behavioral-notes": "Highly intelligent, needs mental stimulation"
    }
  ]
}

User Profiles (public/profiles/users.json)

{
  "userDetails": [
    {
      "name": "Your Name",
      "email": "your.email@gmail.com",
      "yard-access": true,
      "preferred-walk-times": ["early morning", "late evening"],
      "exercise-level": "high"
    }
  ]
}

🤖 AI System Prompt

The agent server creates dynamic system prompts that include:

• Pet Details: Breed, age, energy level, medications, special needs
• Owner Context: Schedule, preferences, yard access, work hours
• Calendar Analysis: Current events to avoid conflicts
• Activity Types: Walks, feeding, medication, play, grooming, training

📊 API Endpoints

Agent Server (Port 5002)

• POST /leash-daily-calendar-fill - Generate calendar suggestions
• GET /health - Service health check
• GET /models - List available Ollama models
• POST /query - General LLM queries

Email Server (Port 5001)

• POST /calendar/events - Create calendar events
• GET /calendar/events - Get events for date
• GET /auth/status - Check authentication status
• GET /auth/login - Google OAuth login

🔍 Troubleshooting

Common Issues

Agent Server Not Responding

• Ensure Ollama is running: ollama serve
• Check if model is available: ollama list
• Verify port 5002 is free

Calendar Events Not Creating

• Check Google Calendar authentication
• Verify email server is running on port 5001
• Check browser console for API errors

Profile Data Not Loading

• Ensure profiles are in frontend/public/profiles/
• Check JSON file formatting
• Verify frontend dev server is serving static files

Debug Information

• Frontend: Check browser console for detailed logs
• Agent Server: Visit http://localhost:5002 for Swagger UI
• Email Server: Check server logs for authentication issues

🛠️ Development

Testing Agent Server

# Test basic connectivity
curl http://localhost:5002/health

# Test LLM query
curl -X POST http://localhost:5002/query \
  -H "Content-Type: application/json" \
  -d '{"query": "Hello!", "model": "llama3.2"}'

Adding New Features

1. New Activity Types: Update system prompt in ollama_service.py
2. Profile Fields: Modify JSON structure and conversion logic
3. UI Enhancements: Add components to frontend/src/components/

📄 License

This project is for the Microsoft Senior Applied Scientist application demonstration.

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💡 Next Steps

• Calendar template system
• Accident prediction network ;)