City Garden

A smart garden design assistant that analyzes garden conditions and provides personalized recommendations.

Overview

City Garden is an AI-powered application that helps urban gardeners design and optimize their garden spaces. It analyzes various factors such as sun exposure, micro-climate, hardscape elements, and environmental conditions to provide tailored plant recommendations and design suggestions.

Features

• Garden Analysis: Analyzes sun exposure, micro-climate, and existing hardscape elements
• Environmental Factors: Retrieves climate data based on location
• Wind Pattern Analysis: Analyzes wind patterns and their impact on garden design
• Style Preferences: Incorporates user style preferences into recommendations
• Comprehensive Reports: Generates detailed garden design reports with plant recommendations
• Garden Visualization: Generates visual representations of the recommended garden design
• Content Safety: Validates images for appropriate content
• REST API: Provides a FastAPI endpoint for garden planning

Project Structure

city-garden/
├── src/
│   ├── main.py                        # Main application entry point
│   ├── api.py                         # FastAPI implementation
│   ├── run_api.py                     # API server runner
│   └── city_garden/
│       ├── __init__.py
│       ├── city_garden_nodes.py       # Graph node implementations
│       ├── garden_state.py            # State management
│       ├── graph_builder.py           # Graph construction
│       ├── llm.py                     # LLM configuration
│       └── services/
│           ├── image_loader.py        # Azure blob storage image loader
│           ├── content_safety.py      # Image/Text safety analysis
│           └── image_generation.py    # Garden visualization service
├── tests/
├── .env                               # Environment variables
├── requirements.txt                   # Project dependencies
└── README.md                          # This file

Architecture

graph TD
    subgraph Frontend
        UI[User Interface]
    end

    subgraph API Layer
        API[FastAPI Server]
        CORS[CORS Middleware]
        API --> CORS
    end

    subgraph Core Services
        Graph[Garden Graph]
        State[Garden State]
        Graph --> State
    end

    subgraph External Services
        AzureStorage[Azure Blob Storage]
        ContentSafety[Azure Content Safety]
        OpenAI[OpenAI GPT]
        WeatherAPI[Weather API]
    end

    subgraph Processing Pipeline
        ImageLoader[Image Loader]
        ImageGen[Image Generation]
        PlantRec[Plant Recommendations]
        SafetyCheck[Content Safety Check]
    end

    %% Connections
    UI -->|HTTP Request| API
    API -->|Process| Graph
    Graph -->|Load| ImageLoader
    ImageLoader -->|Store| AzureStorage
    Graph -->|Generate| ImageGen
    ImageGen -->|Use| OpenAI
    Graph -->|Check| SafetyCheck
    SafetyCheck -->|Validate| ContentSafety
    Graph -->|Get| PlantRec
    PlantRec -->|Use| OpenAI
    Graph -->|Get Weather| WeatherAPI

    %% Data Flow
    ImageLoader -.->|Base64 Images| State
    ImageGen -.->|Generated Image| State
    PlantRec -.->|Recommendations| State
    SafetyCheck -.->|Validation| State
    State -.->|Response| API
    API -.->|JSON Response| UI

Loading

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/city-garden.git
   cd city-garden

2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables: Create a .env file in the root directory with the following variables:

   # Azure Storage credentials
   AZURE_STORAGE_ACCOUNT_NAME=your_account_name
   AZURE_STORAGE_ACCOUNT_KEY=your_account_key
   
   # Azure Content Safety API credentials
   AZURE_CONTENT_SAFETY_ENDPOINT=your_endpoint
   AZURE_CONTENT_SAFETY_KEY=your_key
   
   # OpenAI API credentials
   OPENAI_API_KEY=your_key
   

Usage

Running the API Server

python src/run_api.py

The API will be available at http://localhost:8000

API Endpoints

POST /api/garden_plan

Request body:

{
  "image_urls": [
    "https://your-storage-account.blob.core.windows.net/images/example.jpg"
  ],
  "user_preferences": {
    "growType": "edible",
    "subType": "herbs",
    "cycleType": "perennial",
    "winterType": "outdoors"
  },
  "location": {
    "latitude": 52.52,
    "longitude": 13.405,
    "address": "Berlin, Germany"
  }
}

Response:

{
  "garden_image_url": "https://your-storage-account.blob.core.windows.net/images/garden_design.png",
  "plant_recommendations": [
    {
      "name": "Plant Name",
      "description": "Plant description",
      "care_tips": "Care instructions"
    }
  ]
}

License

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

Acknowledgments

• Azure Blob Storage for image storage
• Azure Content Safety for image validation
• OpenAI for image generation and plant recommendations
• FastAPI for the API framework