🧭 Life Copilot

Life Copilot is your intelligent daily assistant that transforms how you prepare for and manage your day. It's like having a personal concierge that analyzes your calendar, weather, commute, and upcoming events to provide proactive recommendations, reminders, and essential preparations.

🎯 What Life Copilot Does

Life Copilot acts as your daily preparation partner by:

• 📅 Calendar Intelligence: Connects to your Google Calendar and analyzes upcoming events
• 🌤️ Weather-Aware Planning: Considers weather conditions for outdoor events and commutes
• 🚗 Smart Commute Management: Calculates optimal departure times and suggests on-the-way stops
• 🛍️ Proactive Shopping: Identifies what you need for special occasions and finds the best products
• 📱 Automated Reminders: Creates calendar reminders for purchases, departures, and preparations
• 🤖 AI-Powered Insights: Uses LLM to understand event context and provide tailored recommendations

🌟 Key Features

📊 Daily Brief System

• Automated Morning Reports: Generated every morning at 7:00 AM (configurable)
• Comprehensive Overview: Weather, commute times, first 3 events, and personalized plans
• Smart Reminders: Automatically creates "Leave by" reminders in your calendar
• Markdown Reports: Saves detailed reports to data/reports/brief-YYYYMMDD.md

🎯 Event-Specific Intelligence

• Date Night Planning: Suggests flowers, restaurants, and romantic stops along your route
• Interview Preparation: Recommends professional attire, accessories, and preparation items
• Birthday Party Prep: Identifies gifts, decorations, and party essentials
• Outdoor Event Planning: Considers weather and suggests appropriate gear
• Generic Meeting Support: Provides standard preparation checklists

🛒 Smart Shopping Integration

• Amazon Product Search: Finds the best products using Rainforest API
• Intelligent Scoring: Evaluates products on quality, value, delivery speed, and relevance
• Order-by Reminders: Automatically calculates when to order items for timely delivery
• Budget-Aware Recommendations: Considers your budget preferences and event timing

🗺️ On-the-Way (OTW) Stops

• Route-Optimized Suggestions: Finds coffee shops, florists, gift shops along your commute
• Detour Analysis: Shows how much extra time each stop adds to your journey
• Contact Information: Provides phone numbers and addresses for easy calling/ordering
• Calendar Integration: Can add stop reminders directly to your calendar

📅 Calendar Management

• Google Calendar Integration: Full OAuth2 integration with your calendar
• Event Analysis: Understands event context and timing
• Smart Reminders: Creates contextual reminders based on event type
• Schedule Import: Upload and parse various schedule formats (CSV, PDF, images)

🌤️ Weather Integration

• Real-time Conditions: Current temperature, UV index, and precipitation
• Hourly Forecasts: Next 6 hours of weather data
• Event Planning: Weather-aware recommendations for outdoor activities
• Commute Planning: Considers weather impact on travel times

🎬 Real-World Use Cases

💕 Date Night Scenario

"I have a dinner date at 7 PM at a fancy restaurant downtown"

What Life Copilot does:

1. Analyzes the event: Identifies it as a romantic dinner
2. Checks weather: "It's 75°F and sunny - perfect for the outdoor seating area"
3. Calculates commute: "Leave by 6:15 PM to arrive on time (45 min drive)"
4. Suggests preparations:
   • "Order flowers by 2 PM today" → Creates calendar reminder
   • "Pick up flowers at Rose Garden Florist (+8 min detour, call 555-0123)"
   • "Consider a nice bottle of wine from Wine & Spirits (+5 min detour)"
5. Creates reminders: "Leave by 6:15 PM" automatically added to calendar

💼 Job Interview Scenario

"I have a job interview tomorrow at 2 PM at TechCorp"

What Life Copilot does:

1. Identifies the event type: Professional interview
2. Recommends essentials:
   • "Professional leather belt - $25, Prime delivery by tomorrow"
   • "Portfolio folder - $12, same-day delivery available"
   • "Tie clip - $15, order by 6 PM today"
3. Weather considerations: "Partly cloudy, 68°F - perfect for a blazer"
4. Route planning: "Leave by 1:15 PM (30 min drive + 15 min buffer)"
5. OTW suggestions: "Coffee shop 2 blocks from interview location for pre-interview coffee"

🎂 Birthday Party Scenario

"My daughter's birthday party is this Saturday at 3 PM"

What Life Copilot does:

1. Party planning mode: Identifies birthday celebration
2. Gift recommendations:
   • "Age-appropriate toys and games"
   • "Party decorations and balloons"
   • "Cake decorations and candles"
3. Weather planning: "Sunny, 78°F - perfect for outdoor party games"
4. Shopping timeline: "Order decorations by Thursday for Saturday delivery"
5. OTW stops: "Party City on your way home (+12 min detour) for last-minute items"

🏃 Outdoor Event Scenario

"I have a 5K run this Sunday morning at 8 AM"

What Life Copilot does:

1. Weather analysis: "Cool morning, 55°F - perfect running weather"
2. Gear recommendations:
   • "Moisture-wicking running shirt - $18, Prime delivery"
   • "Energy gels for race day - $12, order by Friday"
3. Preparation reminders: "Lay out running clothes tonight"
4. Route planning: "Leave by 7:30 AM (20 min drive to start line)"
5. Post-race planning: "Coffee shop near finish line for post-race celebration"

🔄 Daily Workflow

🌅 Morning Routine (7:00 AM)

1. Daily Brief Generated: Comprehensive report with weather, commute, and first 3 events
2. Leave-by Reminder: Automatically calculated and added to calendar
3. Event Analysis: AI reviews upcoming events and suggests preparations
4. Shopping Alerts: Notifications for items that need to be ordered today

🚗 Commute Time

1. Real-time Traffic: Current ETA and optimal departure time
2. OTW Suggestions: Coffee shops, florists, or gift shops along your route
3. Weather Updates: Current conditions and hourly forecast
4. Event Reminders: Last-minute preparations for today's events

🛍️ Shopping & Preparation

1. Smart Product Search: AI finds the best items for your specific needs
2. Order Timing: Calculates when to order items for timely delivery
3. Calendar Integration: Shopping reminders automatically added to calendar
4. Budget Management: Considers your spending preferences and event budgets

📅 Event Day

1. Final Reminders: Last-minute preparations and departure times
2. Weather Check: Current conditions and any weather-related adjustments
3. OTW Navigation: Real-time suggestions for stops along your route
4. Post-Event: Follow-up reminders and preparation for next events

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🛠️ Tech Stack

• Backend: FastAPI (Python 3.11+)
• Frontend: Streamlit
• LLM: Ollama (local), optional HuggingFace/Groq later
• Scheduler: APScheduler (daily brief automation)
• APIs:
  • Weather (open/free)
  • Commute (Mapbox/OSM)
  • Amazon Catalog (Rainforest API)
  • Google Calendar API (OAuth2)

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🚀 Quick Start

Prerequisites

• Python 3.11+
• Ollama installed and running
• Google Calendar API credentials
• Mapbox API key (for commute routing)
• Rainforest API key (for Amazon product search)
• OpenWeather API key (for weather data)

Installation

1. Clone the repository

   git clone <repository-url>
   cd life_copilot

2. Install dependencies

   pip install -r requirements.txt

3. Set up environment variables Create a .env file in the project root:

   # API Keys
   OPENWEATHER_API_KEY=your_openweather_key
   MAPBOX_ACCESS_TOKEN=your_mapbox_token
   RAINFOREST_API_KEY=your_rainforest_key
   
   # Google Calendar (will be set up during first run)
   GOOGLE_CREDENTIALS_FILE=data/google_token.json
   
   # Location (default to Phoenix, AZ)
   DEFAULT_LAT=33.424
   DEFAULT_LON=-111.928
   
   # Daily Brief Settings
   BRIEF_ENABLED=true
   BRIEF_TIME=07:00

4. Configure your profile Create data/profile.json:

   {
     "user_role": "student",
     "default_gift_budget": 30,
     "default_interview_budget": 25,
     "prime_preferred": true,
     "lat": 33.424,
     "lon": -111.928
   }

5. Set up commute configuration Create data/commute.json:

   {
     "home": {"lat": 33.424, "lon": -111.928},
     "office": {"lat": 33.448, "lon": -111.928},
     "arrive_by": "09:00",
     "buffer_minutes": 10
   }

6. Start the services

   # Terminal 1: Start the API server
   uvicorn api.main:app --reload --port 8000
   
   # Terminal 2: Start the web interface
   streamlit run web/app.py --server.port 8501

7. Access the application

   • Web Interface: http://localhost:8501
   • API Documentation: http://localhost:8000/docs

First-Time Setup

1. Connect Google Calendar: Click "Connect Google Calendar" in the web interface
2. Test Weather: Click "Fetch weather" to verify weather API
3. Test Commute: Click "Check commute" to verify routing
4. Run Daily Brief: Click "Run brief now" to generate your first report

📂 Project Structure

life_copilot/
├── api/                    # FastAPI backend
│   ├── main.py            # Main API server
│   ├── agent.py           # LLM planning and decision making
│   ├── brief.py           # Daily brief generation
│   ├── llm.py             # LLM integration (Ollama)
│   ├── scoring.py         # Product scoring algorithm
│   ├── tools_*.py         # API integrations (weather, commute, calendar, etc.)
│   └── schedule_*.py      # Schedule parsing and import
├── web/                   # Streamlit frontend
│   └── app.py             # Main web interface
├── data/                  # Configuration and data storage
│   ├── profile.json       # User profile and preferences
│   ├── commute.json       # Home/office locations and commute settings
│   ├── google_token.json  # Google Calendar OAuth tokens
│   └── reports/           # Generated daily briefs
├── agent/                 # LangGraph agent components
│   ├── graph.py           # Agent workflow graph
│   └── prompts.py         # LLM prompts and templates
└── requirements.txt       # Python dependencies

🔧 Configuration

Daily Brief Settings

• Time: Configure when the daily brief is generated (default: 7:00 AM)
• Enable/Disable: Turn daily brief on or off
• Leave-by Reminders: Automatically create calendar reminders for departure times

Event Scenarios

The system recognizes these event types and provides tailored recommendations:

• dinner_date - Romantic dinner planning
• child_birthday - Birthday party preparation
• interview - Job interview preparation
• morning_commute - Standard work commute
• generic_meeting - Business meeting preparation
• outdoor_event - Weather-dependent outdoor activities

Shopping Preferences

• Budget Defaults: Set default budgets for different event types
• Prime Preference: Prefer Amazon Prime eligible items
• Delivery Timing: Calculate optimal order times for event deadlines

🤖 AI Integration

LLM Configuration

• Default: Ollama (local, privacy-focused)
• Models: Supports various Ollama models
• Fallback: Graceful degradation if LLM is unavailable

Planning Intelligence

• Event Analysis: Understands event context and requirements
• Weather Integration: Considers weather in all recommendations
• Timing Optimization: Calculates optimal order and departure times
• Route Planning: Suggests efficient stops along commute routes

📱 API Endpoints

Core Services

• GET /weather - Current weather and hourly forecast
• GET /commute - Commute times and route optimization
• GET /calendar/events - Today and tomorrow's calendar events
• POST /calendar/reminder - Create calendar reminders

Planning & Recommendations

• POST /agent/plan - Generate event-specific plans
• POST /agent/act - Get product recommendations and OTW stops
• GET /catalog/search - Search Amazon products
• POST /catalog/order_reminder - Create order-by reminders

Daily Brief

• POST /brief/run - Generate daily brief immediately
• POST /brief/config - Configure daily brief settings

Schedule Import

• POST /schedule/ingest - Upload and parse schedule files
• POST /schedule/commit - Add parsed events to calendar

🔒 Privacy & Security

• Local LLM: Ollama runs locally, keeping your data private
• OAuth2: Secure Google Calendar integration
• No Data Storage: Personal data is not stored permanently
• API Keys: All external API keys are environment variables

🐛 Troubleshooting

Common Issues

1. Ollama not running: Start Ollama service before running the application
2. API keys missing: Ensure all required API keys are in your .env file
3. Calendar connection failed: Check Google Calendar API credentials
4. Weather data unavailable: Verify OpenWeather API key and location settings

Debug Mode

Enable debug logging by setting DEBUG=true in your .env file.

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

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Life Copilot - Your intelligent daily preparation assistant. Never be unprepared for life's important moments again! 🚀