docs: Refactor documentation structure and enhance project overview

- Update MkDocs configuration with streamlined navigation and theme improvements - Revise README with comprehensive project introduction and key features - Add new documentation pages for NLP, custom prompts, and extras - Enhance index page with system architecture diagram and getting started guide - Improve overall documentation clarity and organization
docs: Update environment configuration and README with comprehensive setup guide
2025-02-06 10:06:27 +01:00 · 2025-02-06 09:35:02 +01:00 · 2025-02-06 08:55:23 +01:00
21 changed files with 1570 additions and 1232 deletions
--- a/.env.development.template
+++ b/.env.development.template
@@ -1 +0,0 @@
 NODE_ENV=development\nOPENAI_API_KEY=your_openai_api_key_here\nHASS_HOST=http://homeassistant.local:8123\nHASS_TOKEN=your_hass_token_here\nPORT=3000\nHASS_SOCKET_URL=ws://homeassistant.local:8123/api/websocket\nLOG_LEVEL=debug\nMCP_SERVER=http://localhost:3000\nOPENAI_MODEL=deepseek-v3\nMAX_RETRIES=3\nANALYSIS_TIMEOUT=30000\n\n# Home Assistant specific settings\nAUTOMATION_PATH=./config/automations.yaml\nBLUEPRINT_REPO=https://blueprints.home-assistant.io/\nENERGY_DASHBOARD=true\n\n# Available models: gpt-4o, gpt-4-turbo, gpt-4, gpt-4-o1, gpt-4-o3, gpt-3.5-turbo, gpt-3.5-turbo-16k, deepseek-v3, deepseek-r1\n\n# For DeepSeek models\nDEEPSEEK_API_KEY=your_deepseek_api_key_here\nDEEPSEEK_BASE_URL=https://api.deepseek.com/v1\n\n# Model specifications:\n# - gpt-4-o1: 128k context, general purpose\n# - gpt-4-o3: 1M context, large-scale analysis\n\n# Add processor type specification\nPROCESSOR_TYPE=claude # Change to openai when using OpenAI
--- a/.env.example
+++ b/.env.example
@@ -1,43 +1,15 @@
 # Home Assistant Configuration
 # The URL of your Home Assistant instance
 HASS_HOST=http://homeassistant.local:8123
 # Long-lived access token from Home Assistant
 # Generate from Profile -> Long-Lived Access Tokens
 HASS_TOKEN=your_home_assistant_token
 # WebSocket URL for real-time updates
 HASS_SOCKET_URL=ws://homeassistant.local:8123/api/websocket
 # Server Configuration
 # Port for the MCP server (default: 3000)
 PORT=3000
 # Environment (development/production/test)
 NODE_ENV=development
-
+PORT=3000
 # Debug mode (true/false)
 DEBUG=false
 # Logging level (debug/info/warn/error)
 LOG_LEVEL=info
-# AI Configuration
+# Home Assistant Configuration
-# Natural Language Processor type (claude/gpt4/custom)
+HASS_HOST=http://homeassistant.local:8123
-PROCESSOR_TYPE=claude
+HASS_TOKEN=your_long_lived_token
-
+HASS_SOCKET_URL=ws://homeassistant.local:8123/api/websocket
 # OpenAI API Key (required for GPT-4 analysis)
 OPENAI_API_KEY=your_openai_api_key
 # Rate Limiting
 # Requests per minute per IP for regular endpoints
 RATE_LIMIT_REGULAR=100
 # Requests per minute per IP for WebSocket connections
 RATE_LIMIT_WEBSOCKET=1000
 # Security Configuration
 # JWT Configuration
 JWT_SECRET=your_jwt_secret_key_min_32_chars
 JWT_EXPIRY=86400000
 JWT_MAX_AGE=2592000000
@@ -46,11 +18,8 @@ JWT_ALGORITHM=HS256
 # Rate Limiting
 RATE_LIMIT_WINDOW=900000
 RATE_LIMIT_MAX_REQUESTS=100
-
+RATE_LIMIT_REGULAR=100
-# Token Security
+RATE_LIMIT_WEBSOCKET=1000
 TOKEN_MIN_LENGTH=32
 MAX_FAILED_ATTEMPTS=5
 LOCKOUT_DURATION=900000
 # CORS Configuration
 CORS_ORIGINS=http://localhost:3000,http://localhost:8123
@@ -60,17 +29,6 @@ CORS_EXPOSED_HEADERS=
 CORS_CREDENTIALS=true
 CORS_MAX_AGE=86400
 # Content Security Policy
 CSP_ENABLED=true
 CSP_REPORT_ONLY=false
 CSP_REPORT_URI=
 # SSL/TLS Configuration
 REQUIRE_HTTPS=true
 HSTS_MAX_AGE=31536000
 HSTS_INCLUDE_SUBDOMAINS=true
 HSTS_PRELOAD=true
 # Cookie Security
 COOKIE_SECRET=your_cookie_secret_key_min_32_chars
 COOKIE_SECURE=true
@@ -81,31 +39,44 @@ COOKIE_SAME_SITE=Strict
 MAX_REQUEST_SIZE=1048576
 MAX_REQUEST_FIELDS=1000
 # AI Configuration
 PROCESSOR_TYPE=claude
 OPENAI_API_KEY=your_openai_api_key
 OPENAI_MODEL=gpt-3.5-turbo
 MAX_RETRIES=3
 ANALYSIS_TIMEOUT=30000
 # Speech Features Configuration
 ENABLE_SPEECH_FEATURES=false
 ENABLE_WAKE_WORD=false
 ENABLE_SPEECH_TO_TEXT=false
 WHISPER_MODEL_PATH=/models
 WHISPER_MODEL_TYPE=tiny
 # Audio Configuration
 NOISE_THRESHOLD=0.05
 MIN_SPEECH_DURATION=1.0
 SILENCE_DURATION=0.5
 SAMPLE_RATE=16000
 CHANNELS=1
 CHUNK_SIZE=1024
 PULSE_SERVER=unix:/run/user/1000/pulse/native
 # SSE Configuration
-SSE_MAX_CLIENTS=1000
+SSE_MAX_CLIENTS=50
-SSE_PING_INTERVAL=30000
+SSE_RECONNECT_TIMEOUT=5000
-# Logging Configuration
+# Development Flags
-LOG_LEVEL=info
+HOT_RELOAD=true
 LOG_DIR=logs
 LOG_MAX_SIZE=20m
 LOG_MAX_DAYS=14d
 LOG_COMPRESS=true
 LOG_REQUESTS=true
-# Version
+# Test Configuration (only needed for running tests)
 VERSION=0.1.0
 # Test Configuration
 # Only needed if running tests
 TEST_HASS_HOST=http://localhost:8123
 TEST_HASS_TOKEN=test_token
 TEST_HASS_SOCKET_URL=ws://localhost:8123/api/websocket
 TEST_PORT=3001
-# Speech Features Configuration
+# Version
-ENABLE_SPEECH_FEATURES=false
+VERSION=0.1.0
-ENABLE_WAKE_WORD=true
+
-ENABLE_SPEECH_TO_TEXT=true
+# Advanced (Docker)
-WHISPER_MODEL_PATH=/models
+COMPOSE_PROJECT_NAME=mcp
 WHISPER_MODEL_TYPE=base
--- a/.gitignore
+++ b/.gitignore
@@ -71,7 +71,7 @@ coverage/
 # Environment files
 .env
 .env.*
-!.env.*.template
+!.env.example
 .cursor/
 .cursor/*
--- a/README.md
+++ b/README.md
@@ -1,10 +1,42 @@
 # MCP Server for Home Assistant 🏠🤖
-[![License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE) [![Bun](https://img.shields.io/badge/bun-%3E%3D1.0.26-black)](https://bun.sh) [![TypeScript](https://img.shields.io/badge/typescript-%5E5.0.0-blue.svg)](https://www.typescriptlang.org) [![smithery badge](https://smithery.ai/badge/@jango-blockchained/advanced-homeassistant-mcp)](https://smithery.ai/server/@jango-blockchained/advanced-homeassistant-mcp)
+[![License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE) [![Bun](https://img.shields.io/badge/bun-%3E%3D1.0.26-black)](https://bun.sh) [![TypeScript](https://img.shields.io/badge/typescript-%5E5.0.0-blue.svg)](https://www.typescriptlang.org)
 ## Overview 🌐
-MCP (Model Context Protocol) Server is a lightweight integration tool for Home Assistant, providing a flexible interface for device management and automation.
+MCP (Model Context Protocol) Server is my lightweight integration tool for Home Assistant, providing a flexible interface for device management and automation. It's designed to be fast, secure, and easy to use. Built with Bun for maximum performance.
 ## Why Bun? 🚀
 I chose Bun as the runtime for several key benefits:
 - ⚡ **Blazing Fast Performance**
  - Up to 4x faster than Node.js
  - Built-in TypeScript support
  - Optimized file system operations
 - 🎯 **All-in-One Solution**
  - Package manager (faster than npm/yarn)
  - Bundler (no webpack needed)
  - Test runner (built-in testing)
  - TypeScript transpiler
 - 🔋 **Built-in Features**
  - SQLite3 driver
  - .env file loading
  - WebSocket client/server
  - File watcher
  - Test runner
 - 💾 **Resource Efficient**
  - Lower memory usage
  - Faster cold starts
  - Better CPU utilization
 - 🔄 **Node.js Compatibility**
  - Runs most npm packages
  - Compatible with Express/Fastify
  - Native Node.js APIs
 ## Core Features ✨
@@ -12,95 +44,131 @@ MCP (Model Context Protocol) Server is a lightweight integration tool for Home A
 - 📡 WebSocket/Server-Sent Events (SSE) for state updates
 - 🤖 Simple automation rule management
 - 🔐 JWT-based authentication
 - 🎤 Real-time device control and monitoring
 - 🎤 Server-Sent Events (SSE) for live updates
 - 🎤 Comprehensive logging
 - 🎤 Optional speech features:
-  - 🎤 Wake word detection ("hey jarvis", "ok google", "alexa")
+  - 🗣️ Wake word detection ("hey jarvis", "ok google", "alexa")
-  - 🎤 Speech-to-text using fast-whisper
+  - 🎯 Speech-to-text using fast-whisper
-  - 🎤 Multiple language support
+  - 🌍 Multiple language support
-  - 🎤 GPU acceleration support
+  - 🚀 GPU acceleration support
 ## System Architecture 📊
 ```mermaid
 flowchart TB
    subgraph Client["Client Applications"]
        direction TB
        Web["Web Interface"]
        Mobile["Mobile Apps"]
        Voice["Voice Control"]
    end
    subgraph MCP["MCP Server"]
        direction TB
        API["REST API"]
        WS["WebSocket/SSE"]
        Auth["Authentication"]
        subgraph Speech["Speech Processing (Optional)"]
            direction TB
            Wake["Wake Word Detection"]
            STT["Speech-to-Text"]
            subgraph STT_Options["STT Options"]
                direction LR
                Whisper["Whisper"]
                FastWhisper["Fast Whisper"]
            end
            Wake --> STT
            STT --> STT_Options
        end
    end
    subgraph HA["Home Assistant"]
        direction TB
        HASS_API["HASS API"]
        HASS_WS["HASS WebSocket"]
        Devices["Smart Devices"]
    end
    Client --> MCP
    MCP --> HA
    HA --> Devices
    style Speech fill:#f9f,stroke:#333,stroke-width:2px
    style STT_Options fill:#bbf,stroke:#333,stroke-width:1px
 ```
 ## Prerequisites 📋
- 🚀 Bun runtime (v1.0.26+)
+- 🚀 [Bun runtime](https://bun.sh) (v1.0.26+)
- 🏡 Home Assistant instance
+- 🏡 [Home Assistant](https://www.home-assistant.io/) instance
- 🐳 Docker (optional, recommended for deployment and speech features)
+- 🐳 Docker (optional, recommended for deployment)
 - 🖥️ Node.js 18+ (optional, for speech features)
- 🖥️ NVIDIA GPU with CUDA support (optional, for faster speech processing)
+- 🎮 NVIDIA GPU with CUDA support (optional, for faster speech processing)
-## Installation 🛠️
+## Quick Start 🚀
 ### Docker Deployment (Recommended)
 1. Clone my repository:
 ```bash
 # Clone the repository
 git clone https://github.com/jango-blockchained/homeassistant-mcp.git
 cd homeassistant-mcp
 # Copy and edit environment configuration
 cp .env.example .env
 # Edit .env with your Home Assistant credentials and speech features settings
 # Build and start containers
 docker compose up -d --build
 ```
-### Bare Metal Installation
+2. Set up the environment:
 ```bash
-# Install Bun
+# Make my setup script executable
-curl -fsSL https://bun.sh/install | bash
+chmod +x scripts/setup-env.sh
-# Clone the repository
+# Run setup (defaults to development)
-git clone https://github.com/jango-blockchained/homeassistant-mcp.git
+./scripts/setup-env.sh
 cd homeassistant-mcp
-# Install dependencies
+# Or specify an environment:
-bun install
+NODE_ENV=production ./scripts/setup-env.sh
-# Start the server
+# Force override existing files:
-bun run dev
+./scripts/setup-env.sh --force
 ```
-## Basic Usage 🖥️
+3. Configure your settings:
 - Edit `.env` file with your Home Assistant details
 - Required: Add your `HASS_TOKEN` (long-lived access token)
-### Device Control Example
+4. Launch with Docker:
-
+```bash
-```typescript
+docker compose up -d
 // Turn on a light
 const response = await fetch('http://localhost:3000/api/devices/light.living_room', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': `Bearer ${token}`
  },
  body: JSON.stringify({ state: 'on' })
 });
 ```
-### WebSocket State Updates
+## Environment Configuration 🔧
-```typescript
+I've implemented a hierarchical configuration system:
 const ws = new WebSocket('ws://localhost:3000/devices');
 ws.onmessage = (event) => {
  const deviceState = JSON.parse(event.data);
  console.log('Device state updated:', deviceState);
 };
 ```
-## Speech Features (Optional)
+### File Structure 📁
 1. `.env.example` - My template with all options
 2. `.env` - Your configuration (copy from .env.example)
 3. Environment overrides:
   - `.env.dev` - Development settings
   - `.env.prod` - Production settings
   - `.env.test` - Test settings
-The MCP Server includes optional speech processing capabilities:
+### Loading Priority ⚡
 Files load in this order:
 1. `.env` (base config)
 2. Environment-specific file:
   - `NODE_ENV=development` → `.env.dev`
   - `NODE_ENV=production` → `.env.prod`
   - `NODE_ENV=test` → `.env.test`
 Later files override earlier ones.
 ## Speech Features Setup 🎤
 ### Prerequisites
-1. Docker installed and running
+1. 🐳 Docker installed and running
-2. NVIDIA GPU with CUDA support (optional)
+2. 🎮 NVIDIA GPU with CUDA (optional)
-3. At least 4GB RAM (8GB+ recommended for larger models)
+3. 💾 4GB+ RAM (8GB+ recommended)
-### Setup
+### Configuration
-
+1. Enable speech in `.env`:
 1. Enable speech features in your .env:
 ```bash
 ENABLE_SPEECH_FEATURES=true
 ENABLE_WAKE_WORD=true
@@ -109,67 +177,94 @@ WHISPER_MODEL_PATH=/models
 WHISPER_MODEL_TYPE=base
 ```
-2. Start the speech services:
+2. Choose your STT engine:
 ```bash
-docker-compose up -d
+# For standard Whisper
 STT_ENGINE=whisper
 # For Fast Whisper (GPU recommended)
 STT_ENGINE=fast-whisper
 CUDA_VISIBLE_DEVICES=0  # Set GPU device
 ```
-### Available Models
+### Available Models 🤖
-
+Choose based on your needs:
 Choose a model based on your needs:
 - `tiny.en`: Fastest, basic accuracy
 - `base.en`: Good balance (recommended)
 - `small.en`: Better accuracy, slower
 - `medium.en`: High accuracy, resource intensive
 - `large-v2`: Best accuracy, very resource intensive
-### Usage
+## Development 💻
-1. Wake word detection listens for:
+```bash
-   - "hey jarvis"
+# Install dependencies
-   - "ok google"
+bun install
   - "alexa"
-2. After wake word detection:
+# Run in development mode
-   - Audio is automatically captured
+bun run dev
   - Speech is transcribed
   - Commands are processed
-3. Manual transcription is also available:
+# Run tests
-```typescript
+bun test
-const speech = speechService.getSpeechToText();
+
-const text = await speech.transcribe(audioBuffer);
+# Run with hot reload
 bun --hot run dev
 # Build for production
 bun build ./src/index.ts --target=bun
 # Run production build
 bun run start
 ```
-## Configuration
+### Performance Comparison 📊
-See [Configuration Guide](docs/configuration.md) for detailed settings.
+| Operation | Bun | Node.js |
 |-----------|-----|---------|
 | Install Dependencies | ~2s | ~15s |
 | Cold Start | 300ms | 1000ms |
 | Build Time | 150ms | 4000ms |
 | Memory Usage | ~150MB | ~400MB |
-## API Documentation
+## Documentation 📚
-See [API Documentation](docs/api/index.md) for available endpoints.
+### Core Documentation
 - [Configuration Guide](docs/configuration.md)
 - [API Documentation](docs/api.md)
 - [Troubleshooting](docs/troubleshooting.md)
-## Development
+### Advanced Features
 - [Natural Language Processing](docs/nlp.md) - AI-powered automation analysis and control
 - [Custom Prompts Guide](docs/prompts.md) - Create and customize AI behavior
 - [Extras & Tools](docs/extras.md) - Additional utilities and advanced features
-See [Development Guide](docs/development/index.md) for contribution guidelines.
+### Extra Tools 🛠️
-## License 📄
+I've included several powerful tools in the `extra/` directory to enhance your Home Assistant experience:
-MIT License. See [LICENSE](LICENSE) for details.
+1. **Home Assistant Analyzer CLI** (`ha-analyzer-cli.ts`)
   - Deep automation analysis using AI models
   - Security vulnerability scanning
   - Performance optimization suggestions
   - System health metrics
-## Support 🆘
+2. **Speech-to-Text Example** (`speech-to-text-example.ts`)
   - Wake word detection
   - Speech-to-text transcription
   - Multiple language support
   - GPU acceleration support
- 🐞 [GitHub Issues](https://github.com/jango-blockchained/homeassistant-mcp/issues)
+3. **Claude Desktop Setup** (`claude-desktop-macos-setup.sh`)
- 📖 Documentation: [Project Docs](https://jango-blockchained.github.io/homeassistant-mcp/)
+   - Automated Claude Desktop installation for macOS
   - Environment configuration
   - MCP integration setup
-## MCP Client Integration 🔗
+See [Extras Documentation](docs/extras.md) for detailed usage instructions and examples.
-This MCP server can be integrated with various clients that support the Model Context Protocol. Below are instructions for different client integrations:
+## Client Integration 🔗
 ### Cursor Integration 🖱️
-
+Add to `.cursor/config/config.json`:
 The server can be integrated with Cursor by adding the configuration to `.cursor/config/config.json`:
 ```json
 {
  "mcpServers": {
@@ -185,10 +280,8 @@ The server can be integrated with Cursor by adding the configuration to `.cursor
 }
 ```
-### Claude Desktop Integration 💬
+### Claude Desktop 💬
-
+Add to your Claude config:
 For Claude Desktop, add the following to your Claude configuration file:
 ```json
 {
  "mcpServers": {
@@ -203,37 +296,15 @@ For Claude Desktop, add the following to your Claude configuration file:
 }
 ```
-### Cline Integration 📟
+### Command Line 💻
-
+Windows users can use the provided script:
-For Cline-based clients, add the following configuration:
+1. Go to `scripts` directory
 ```json
 {
  "mcpServers": {
    "homeassistant-mcp": {
      "command": "bun",
      "args": [
        "run",
        "start",
        "--enable-cline",
        "--config",
        "${configDir}/.env"
      ],
      "env": {
        "NODE_ENV": "production",
        "CLINE_MODE": "true"
      }
    }
  }
 }
 ```
 ### Command Line Usage 💻
 #### Windows
 A CMD script is provided in the `scripts` directory. To use it:
 1. Navigate to the `scripts` directory
 2. Run `start_mcp.cmd`
-The script will start the MCP server with default configuration.
+## License 📄
 MIT License. See [LICENSE](LICENSE) for details.
 ## Author 👨‍💻
 Created by [jango-blockchained](https://github.com/jango-blockchained)
--- a/tests/websocket/events.test.ts
+++ b/tests/websocket/events.test.ts
@@ -119,22 +119,17 @@ describe('WebSocket Event Handling', () => {
    test('should handle connection errors', async () => {
        const errorPromise = new Promise((resolve) => {
-            client.on('error', resolve);
+            client.once('error', resolve);
        });
-        const connectPromise = client.connect().catch(() => { });
+        const connectPromise = client.connect().catch(() => { /* Expected error */ });
        onOpenCallback();
-        const errorEvent = {
+        const errorEvent = new Error('Connection failed');
-            error: new Error('Connection failed'),
+        onErrorCallback({ error: errorEvent });
            message: 'Connection failed',
            target: mockWebSocket
        };
        onErrorCallback(errorEvent);
        const error = await errorPromise;
-        expect(error).toBeDefined();
+        expect(error instanceof Error).toBe(true);
        expect((error as Error).message).toBe('Connection failed');
    });
--- a/bun.lock
+++ b/bun.lock
@@ -1,604 +0,0 @@
 {
  "lockfileVersion": 1,
  "workspaces": {
    "": {
      "dependencies": {
        "@elysiajs/cors": "^1.2.0",
        "@elysiajs/swagger": "^1.2.0",
        "@types/jsonwebtoken": "^9.0.5",
        "@types/node": "^20.11.24",
        "@types/sanitize-html": "^2.9.5",
        "@types/ws": "^8.5.10",
        "@xmldom/xmldom": "^0.9.7",
        "dotenv": "^16.4.5",
        "elysia": "^1.2.11",
        "helmet": "^7.1.0",
        "jsonwebtoken": "^9.0.2",
        "node-fetch": "^3.3.2",
        "openai": "^4.82.0",
        "sanitize-html": "^2.11.0",
        "typescript": "^5.3.3",
        "winston": "^3.11.0",
        "winston-daily-rotate-file": "^5.0.0",
        "ws": "^8.16.0",
        "zod": "^3.22.4",
      },
      "devDependencies": {
        "@types/uuid": "^10.0.0",
        "@typescript-eslint/eslint-plugin": "^7.1.0",
        "@typescript-eslint/parser": "^7.1.0",
        "bun-types": "^1.2.2",
        "eslint": "^8.57.0",
        "eslint-config-prettier": "^9.1.0",
        "eslint-plugin-prettier": "^5.1.3",
        "husky": "^9.0.11",
        "prettier": "^3.2.5",
        "supertest": "^6.3.3",
        "uuid": "^11.0.5",
      },
    },
  },
  "packages": {
    "@colors/colors": ["@colors/colors@1.6.0", "", {}, "sha512-Ir+AOibqzrIsL6ajt3Rz3LskB7OiMVHqltZmspbW/TJuTVuyOMirVqAkjfY6JISiLHgyNqicAC8AyHHGzNd/dA=="],
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  }
 }
--- a/docker-compose.speech.yml
+++ b/docker-compose.speech.yml
@@ -0,0 +1,49 @@
 version: '3.8'
 services:
  homeassistant-mcp:
    environment:
      - ENABLE_SPEECH_FEATURES=${ENABLE_SPEECH_FEATURES:-true}
      - ENABLE_WAKE_WORD=${ENABLE_WAKE_WORD:-true}
      - ENABLE_SPEECH_TO_TEXT=${ENABLE_SPEECH_TO_TEXT:-true}
  fast-whisper:
    image: onerahmet/openai-whisper-asr-webservice:latest
    volumes:
      - whisper-models:/models
      - audio-data:/audio
    environment:
      - ASR_MODEL=base
      - ASR_ENGINE=faster_whisper
      - WHISPER_BEAM_SIZE=5
      - COMPUTE_TYPE=float32
      - LANGUAGE=en
    ports:
      - "9000:9000"
    deploy:
      resources:
        limits:
          cpus: '4.0'
          memory: 2G
    healthcheck:
      test: [ "CMD", "curl", "-f", "http://localhost:9000/health" ]
      interval: 30s
      timeout: 10s
      retries: 3
  wake-word:
    image: rhasspy/wyoming-openwakeword:latest
    restart: unless-stopped
    devices:
      - /dev/snd:/dev/snd
    volumes:
      - /run/user/1000/pulse/native:/run/user/1000/pulse/native
    environment:
      - PULSE_SERVER=unix:/run/user/1000/pulse/native
    group_add:
      - audio
    network_mode: host
 volumes:
  whisper-models:
  audio-data:
--- a/docker/speech/Dockerfile
+++ b/docker/speech/Dockerfile
@@ -1,88 +0,0 @@
 # Use Python slim image as builder
 FROM python:3.10-slim AS builder
 # Install build dependencies
 RUN apt-get update && apt-get install -y \
    git \
    curl \
    wget
 # Create and activate virtual environment
 RUN python -m venv /opt/venv
 ENV PATH="/opt/venv/bin:$PATH"
 # Install Python dependencies with specific versions and CPU-only variants
 RUN pip install --no-cache-dir \
    "numpy>=1.24.3,<2.0" \
    "sounddevice" \
    "openwakeword" \
    "faster-whisper" \
    "transformers" \
    "torch" \
    "torchaudio" \
    "huggingface_hub" \
    "requests" \
    "soundfile" \
    "tflite-runtime"
 # Create final image
 FROM python:3.10-slim
 # Copy virtual environment from builder
 COPY --from=builder /opt/venv /opt/venv
 ENV PATH="/opt/venv/bin:$PATH"
 # Install audio dependencies
 RUN apt-get update && apt-get install -y \
    portaudio19-dev \
    pulseaudio \
    alsa-utils \
    curl \
    wget
 # Create necessary directories with explicit permissions
 RUN mkdir -p /models/wake_word /audio /app /models/cache /models/models--Systran--faster-whisper-base /opt/venv/lib/python3.10/site-packages/openwakeword/resources/models \
    && chmod -R 777 /models /audio /app /models/cache /models/models--Systran--faster-whisper-base /opt/venv/lib/python3.10/site-packages/openwakeword/resources/models
 # Download wake word models
 RUN wget -O /opt/venv/lib/python3.10/site-packages/openwakeword/resources/models/alexa_v0.1.tflite \
    https://github.com/dscripka/openWakeWord/raw/main/openwakeword/resources/models/alexa_v0.1.tflite \
    && wget -O /opt/venv/lib/python3.10/site-packages/openwakeword/resources/models/hey_jarvis_v0.1.tflite \
    https://github.com/dscripka/openWakeWord/raw/main/openwakeword/resources/models/hey_jarvis_v0.1.tflite \
    && chmod 644 /opt/venv/lib/python3.10/site-packages/openwakeword/resources/models/*.tflite
 # Set environment variables for model caching
 ENV HF_HOME=/models/cache
 ENV TRANSFORMERS_CACHE=/models/cache
 ENV HUGGINGFACE_HUB_CACHE=/models/cache
 # Copy scripts and set permissions explicitly
 COPY wake_word_detector.py /app/wake_word_detector.py
 COPY setup-audio.sh /setup-audio.sh
 # Ensure scripts are executable by any user
 RUN chmod 755 /setup-audio.sh /app/wake_word_detector.py
 # Create a non-root user with explicit UID and GID
 RUN addgroup --gid 1000 user && \
    adduser --uid 1000 --gid 1000 --disabled-password --gecos '' user
 # Change ownership of directories
 RUN chown -R 1000:1000 /models /audio /app /models/cache /models/models--Systran--faster-whisper-base \
    /opt/venv/lib/python3.10/site-packages/openwakeword/resources/models
 # Switch to non-root user
 USER user
 # Set working directory
 WORKDIR /app
 # Set environment variables
 ENV WHISPER_MODEL_PATH=/models \
    WAKEWORD_MODEL_PATH=/models/wake_word \
    PYTHONUNBUFFERED=1 \
    PULSE_SERVER=unix:/run/user/1000/pulse/native \
    HOME=/home/user
 # Start the application
 CMD ["/setup-audio.sh"] 
--- a/docs/configuration.md
+++ b/docs/configuration.md
@@ -2,6 +2,46 @@
 This document provides detailed information about configuring the Home Assistant MCP Server.
 ## Environment File Structure
 The MCP Server uses a flexible environment configuration system with support for different environments and local overrides:
 ### Environment Files
 1. `.env.example` - Template file containing all available configuration options with example values
   - Use this as a reference to create your environment-specific configuration files
   - Not loaded by the application
 2. Environment-specific files (loaded based on NODE_ENV):
   - `.env.dev` - Development environment (default)
   - `.env.test` - Test environment
   - `.env.prod` - Production environment
 3. `.env` - Optional local override file
   - If present, values in this file override those from the environment-specific file
   - Useful for local development without modifying the environment-specific files
 ### File Loading Order
 1. First, the environment-specific file is loaded based on NODE_ENV:
   - `NODE_ENV=production` → `.env.prod`
   - `NODE_ENV=development` → `.env.dev` (default)
   - `NODE_ENV=test` → `.env.test`
 2. Then, if a `.env` file exists, its values override any previously loaded values
 Example setup:
 ```bash
 # .env.dev - Development configuration
 PORT=4000
 HASS_HOST=http://homeassistant.local:8123
 LOG_LEVEL=debug
 # .env - Local overrides
 PORT=3000  # Overrides PORT from .env.dev
 HASS_HOST=http://localhost:8123  # Overrides HASS_HOST from .env.dev
 ```
 ## Configuration File Structure
 The MCP Server uses environment variables for configuration, with support for different environments (development, test, production):
@@ -170,101 +210,220 @@ See the [Troubleshooting Guide](troubleshooting.md) for solutions.
 # Configuration Guide
-This document describes all available configuration options for the Home Assistant MCP Server.
+This document describes the environment configuration system for the Home Assistant MCP Server.
-## Environment Variables
+## Environment Setup
 ### Using the Setup Script
 The MCP Server provides a setup script to help manage your environment configuration:
 ```bash
 # Make the script executable
 chmod +x scripts/setup-env.sh
 # Basic usage (uses NODE_ENV or defaults to development)
 ./scripts/setup-env.sh
 # Specify an environment
 NODE_ENV=production ./scripts/setup-env.sh
 # Force override existing files
 ./scripts/setup-env.sh --force
 ```
 The setup script will:
 1. Check for `.env.example` and create `.env` if it doesn't exist
 2. Detect the environment (development/production/test)
 3. Optionally override `.env` with environment-specific settings
 4. Maintain your existing configuration unless forced to override
 ### Manual Setup
 If you prefer to set up manually:
 ```bash
 # Copy the example configuration
 cp .env.example .env
 # Then copy the appropriate environment override
 cp .env.dev .env     # For development
 cp .env.prod .env    # For production
 cp .env.test .env    # For testing
 ```
 ## Environment File Hierarchy
 ### Base Configuration Files
 - `.env.example` - Template with all available options and documentation
 - `.env` - Your main configuration file (copied from .env.example)
 ### Environment-Specific Files
 - `.env.dev` - Development environment settings
 - `.env.prod` - Production environment settings
 - `.env.test` - Test environment settings
 ### Loading Order and Priority
 Files are loaded in the following sequence, with later files overriding earlier ones:
 1. `.env` (base configuration)
 2. Environment-specific file based on NODE_ENV:
   - `NODE_ENV=development` → `.env.dev`
   - `NODE_ENV=production` → `.env.prod`
   - `NODE_ENV=test` → `.env.test`
 ### Docker Environment Handling
 When using Docker, the environment is loaded as follows:
 1. `.env` file (base configuration)
 2. `.env.${NODE_ENV}` file (environment-specific overrides)
 3. Environment variables from docker-compose.yml
 4. Command-line environment variables
 Example docker-compose.yml configuration:
 ```yaml
 services:
  homeassistant-mcp:
    env_file:
      - .env
      - .env.${NODE_ENV:-development}
    environment:
      - NODE_ENV=${NODE_ENV:-development}
      - PORT=4000
      - HASS_HOST
      - HASS_TOKEN
      - LOG_LEVEL=${LOG_LEVEL:-info}
 ```
 Override examples:
 ```bash
 # Override NODE_ENV
 NODE_ENV=production docker compose up -d
 # Override multiple variables
 NODE_ENV=production LOG_LEVEL=debug docker compose up -d
 ```
 ## Configuration Options
 ### Required Settings
 ```bash
 # Server Configuration
-PORT=3000                      # Server port
+PORT=4000                     # Server port number
-HOST=localhost                 # Server host
+NODE_ENV=development         # Environment (development/production/test)
 # Home Assistant
-HASS_URL=http://localhost:8123 # Home Assistant URL
+HASS_HOST=http://homeassistant.local:8123  # Home Assistant URL
-HASS_TOKEN=your_token         # Long-lived access token
+HASS_TOKEN=your_token_here                # Long-lived access token
 # Security
-JWT_SECRET=your_secret        # JWT signing secret
+JWT_SECRET=your_secret_key   # JWT signing secret
 ```
 ### Optional Settings
 #### Security
 ```bash
 # Rate Limiting
-RATE_LIMIT_WINDOW=60000       # Time window in ms (default: 60000)
+RATE_LIMIT_WINDOW=900000     # Time window in ms (15 minutes)
-RATE_LIMIT_MAX=100           # Max requests per window (default: 100)
+RATE_LIMIT_MAX_REQUESTS=100  # Max requests per window
 RATE_LIMIT_REGULAR=100       # Regular endpoint rate limit
 RATE_LIMIT_WEBSOCKET=1000    # WebSocket connection rate limit
-# Logging
+# CORS Configuration
-LOG_LEVEL=info               # debug, info, warn, error (default: info)
+CORS_ORIGINS=http://localhost:3000,http://localhost:8123
-LOG_DIR=logs                 # Log directory (default: logs)
+CORS_METHODS=GET,POST,PUT,DELETE,OPTIONS
-LOG_MAX_SIZE=10m            # Max log file size (default: 10m)
+CORS_ALLOWED_HEADERS=Content-Type,Authorization,X-Requested-With
-LOG_MAX_FILES=5             # Max number of log files (default: 5)
+CORS_EXPOSED_HEADERS=
 CORS_CREDENTIALS=true
 CORS_MAX_AGE=86400
-# WebSocket/SSE
+# Cookie Security
-WS_HEARTBEAT=30000          # WebSocket heartbeat interval in ms (default: 30000)
+COOKIE_SECRET=your_cookie_secret_key_min_32_chars
-SSE_RETRY=3000             # SSE retry interval in ms (default: 3000)
+COOKIE_SECURE=true
-
+COOKIE_HTTP_ONLY=true
-# Speech Features
+COOKIE_SAME_SITE=Strict
 ENABLE_SPEECH_FEATURES=false # Enable speech processing (default: false)
 ENABLE_WAKE_WORD=false      # Enable wake word detection (default: false)
 ENABLE_SPEECH_TO_TEXT=false # Enable speech-to-text (default: false)
 # Speech Model Configuration
 WHISPER_MODEL_PATH=/models  # Path to whisper models (default: /models)
 WHISPER_MODEL_TYPE=base     # Model type: tiny|base|small|medium|large-v2 (default: base)
 WHISPER_LANGUAGE=en        # Primary language (default: en)
 WHISPER_TASK=transcribe    # Task type: transcribe|translate (default: transcribe)
 WHISPER_DEVICE=cuda        # Processing device: cpu|cuda (default: cuda if available, else cpu)
 # Wake Word Configuration
 WAKE_WORDS=hey jarvis,ok google,alexa  # Comma-separated wake words (default: hey jarvis)
 WAKE_WORD_SENSITIVITY=0.5   # Detection sensitivity 0-1 (default: 0.5)
 ```
-## Speech Features
+#### Logging
 ```bash
 # Logging Configuration
 LOG_LEVEL=info              # debug, info, warn, error
 LOG_DIR=logs               # Log directory
 LOG_MAX_SIZE=20m          # Max log file size
 LOG_MAX_DAYS=14d         # Log retention period
 LOG_COMPRESS=true        # Enable log compression
 LOG_REQUESTS=true       # Log HTTP requests
 ```
-### Model Selection
+#### Speech Features
 ```bash
 # Speech Processing
 ENABLE_SPEECH_FEATURES=false    # Master switch for speech features
 ENABLE_WAKE_WORD=false         # Enable wake word detection
 ENABLE_SPEECH_TO_TEXT=false    # Enable speech-to-text
 WHISPER_MODEL_PATH=/models     # Path to Whisper models
 WHISPER_MODEL_TYPE=base        # Whisper model type
-Choose a model based on your needs:
+# Audio Configuration
 NOISE_THRESHOLD=0.05
 MIN_SPEECH_DURATION=1.0
 SILENCE_DURATION=0.5
 SAMPLE_RATE=16000
 CHANNELS=1
 CHUNK_SIZE=1024
 PULSE_SERVER=unix:/run/user/1000/pulse/native
 ```
-| Model      | Size  | Memory Required | Speed | Accuracy |
+## Best Practices
 |------------|-------|-----------------|-------|----------|
 | tiny.en    | 75MB  | 1GB            | Fast  | Basic    |
 | base.en    | 150MB | 2GB            | Good  | Good     |
 | small.en   | 500MB | 4GB            | Med   | Better   |
 | medium.en  | 1.5GB | 8GB            | Slow  | High     |
 | large-v2   | 3GB   | 16GB           | Slow  | Best     |
-### GPU Acceleration
+1. **Version Control**
   - Never commit `.env` files to version control
   - Always commit `.env.example` with documentation
   - Consider committing `.env.dev` and `.env.test` for team development
-When `WHISPER_DEVICE=cuda`:
+2. **Security**
- NVIDIA GPU with CUDA support required
+   - Use strong, unique values for secrets
- Significantly faster processing
+   - Enable HTTPS in production
- Higher memory requirements
+   - Keep tokens and secrets in `.env` only
-### Wake Word Detection
+3. **Development**
   - Use `.env.dev` for shared development settings
   - Keep `.env` for personal overrides
   - Enable debug logging in development
- Multiple wake words supported via comma-separated list
+4. **Production**
- Adjustable sensitivity (0-1):
+   - Use `.env.prod` for production defaults
-  - Lower values: Fewer false positives, may miss some triggers
+   - Set appropriate rate limits
-  - Higher values: More responsive, may have false triggers
+   - Configure proper logging
-  - Default (0.5): Balanced detection
+   - Enable all security features
-### Best Practices
+5. **Testing**
   - Use `.env.test` for test configuration
   - Use mock tokens and endpoints
   - Enable detailed logging for debugging
-1. Model Selection:
+## Troubleshooting
   - Start with `base.en` model
   - Upgrade if better accuracy needed
   - Downgrade if performance issues
-2. Resource Management:
+### Common Issues
   - Monitor memory usage
   - Use GPU acceleration when available
   - Consider model size vs available resources
-3. Wake Word Configuration:
+1. **Missing Required Variables**
-   - Use distinct wake words
+   - Error: "Missing required environment variable: HASS_TOKEN"
-   - Adjust sensitivity based on environment
+   - Solution: Ensure HASS_TOKEN is set in your .env file
-   - Limit number of wake words for better performance 
+
 2. **Permission Issues**
   - Error: "EACCES: permission denied, access '/app/logs'"
   - Solution: Ensure proper permissions on the logs directory
 3. **Invalid Configuration**
   - Error: "Invalid configuration value for PORT"
   - Solution: Check the value format in your .env file
 4. **Environment Override Issues**
   - Problem: Environment-specific settings not applying
   - Solution: Check NODE_ENV value and file naming
 See [Troubleshooting Guide](troubleshooting.md) for more solutions. 
--- a/docs/extras.md
+++ b/docs/extras.md
@@ -0,0 +1,228 @@
 # Extras & Tools Guide 🛠️
 ## Overview
 I've included several additional tools and utilities in the `extra/` directory to enhance your Home Assistant MCP experience. These tools help with automation analysis, speech processing, and client integration.
 ## Available Tools 🧰
 ### 1. Home Assistant Analyzer CLI
 ```bash
 # Installation
 bun install -g @homeassistant-mcp/ha-analyzer-cli
 # Usage
 ha-analyzer analyze path/to/automation.yaml
 ```
 Features:
 - 🔍 Deep automation analysis using AI models
 - 🚨 Security vulnerability scanning
 - 💡 Performance optimization suggestions
 - 📊 System health metrics
 - ⚡ Energy usage analysis
 - 🤖 Automation improvement recommendations
 ### 2. Speech-to-Text Example
 ```bash
 # Run the example
 bun run extra/speech-to-text-example.ts
 ```
 Features:
 - 🎤 Wake word detection ("hey jarvis", "ok google", "alexa")
 - 🗣️ Speech-to-text transcription
 - 🌍 Multiple language support
 - 🚀 GPU acceleration support
 - 📝 Event handling and logging
 ### 3. Claude Desktop Setup (macOS)
 ```bash
 # Make script executable
 chmod +x extra/claude-desktop-macos-setup.sh
 # Run setup
 ./extra/claude-desktop-macos-setup.sh
 ```
 Features:
 - 🖥️ Automated Claude Desktop installation
 - ⚙️ Environment configuration
 - 🔗 MCP integration setup
 - 🚀 Performance optimization
 ## Home Assistant Analyzer Details 📊
 ### Analysis Categories
 1. **System Overview**
   - Current state assessment
   - Health check
   - Configuration review
   - Integration status
   - Issue detection
 2. **Performance Analysis**
   - Resource usage monitoring
   - Response time analysis
   - Optimization opportunities
   - Bottleneck detection
 3. **Security Assessment**
   - Current security measures
   - Vulnerability detection
   - Security recommendations
   - Best practices review
 4. **Optimization Suggestions**
   - Performance improvements
   - Configuration optimizations
   - Integration enhancements
   - Automation opportunities
 5. **Maintenance Tasks**
   - Required updates
   - Cleanup recommendations
   - Regular maintenance tasks
   - System health checks
 6. **Entity Usage Analysis**
   - Most active entities
   - Rarely used entities
   - Potential duplicates
   - Usage patterns
 7. **Automation Analysis**
   - Inefficient automations
   - Improvement suggestions
   - Blueprint recommendations
   - Condition optimizations
 8. **Energy Management**
   - High consumption detection
   - Monitoring suggestions
   - Tariff optimization
   - Usage patterns
 ### Configuration
 ```yaml
 # config/analyzer.yaml
 analysis:
  depth: detailed    # quick, basic, or detailed
  models:           # AI models to use
    - gpt-4         # for complex analysis
    - gpt-3.5-turbo # for quick checks
  focus:            # Analysis focus areas
    - security
    - performance
    - automations
    - energy
  ignore:           # Paths to ignore
    - test/
    - disabled/
 ```
 ## Speech-to-Text Integration 🎤
 ### Prerequisites
 1. Docker installed and running
 2. NVIDIA GPU with CUDA (optional, for faster processing)
 3. Audio input device configured
 ### Configuration
 ```yaml
 # speech-config.yaml
 wake_word:
  enabled: true
  words:
    - "hey jarvis"
    - "ok google"
    - "alexa"
  sensitivity: 0.5
 speech_to_text:
  model: "base"     # tiny, base, small, medium, large
  language: "en"    # en, es, fr, etc.
  use_gpu: true     # Enable GPU acceleration
 ```
 ### Usage Example
 ```typescript
 import { SpeechProcessor } from './speech-to-text-example';
 const processor = new SpeechProcessor({
  wakeWord: true,
  model: 'base',
  language: 'en'
 });
 processor.on('wake_word', (timestamp) => {
  console.log('Wake word detected!');
 });
 processor.on('transcription', (text) => {
  console.log('Transcribed:', text);
 });
 await processor.start();
 ```
 ## Best Practices 🎯
 1. **Analysis Tool Usage**
   - Run regular system analyses
   - Focus on specific areas when needed
   - Review and implement suggestions
   - Monitor improvements
 2. **Speech Processing**
   - Choose appropriate models
   - Test in your environment
   - Adjust sensitivity as needed
   - Monitor performance
 3. **Integration Setup**
   - Follow security best practices
   - Test in development first
   - Monitor resource usage
   - Keep configurations updated
 ## Troubleshooting 🔧
 ### Common Issues
 1. **Analyzer CLI Issues**
   - Verify API keys
   - Check network connectivity
   - Validate YAML syntax
   - Review permissions
 2. **Speech Processing Issues**
   - Check audio device
   - Verify Docker setup
   - Monitor GPU usage
   - Check model compatibility
 3. **Integration Issues**
   - Verify configurations
   - Check dependencies
   - Review logs
   - Test connectivity
 ## API Reference 🔌
 ### Analyzer API
 ```typescript
 import { HomeAssistantAnalyzer } from './ha-analyzer-cli';
 const analyzer = new HomeAssistantAnalyzer({
  depth: 'detailed',
  focus: ['security', 'performance']
 });
 const analysis = await analyzer.analyze();
 console.log(analysis.suggestions);
 ```
 See [API Documentation](api.md) for more details. 
--- a/docs/index.md
+++ b/docs/index.md
@@ -4,22 +4,108 @@ title: Home
 nav_order: 1
 ---
-# Advanced Home Assistant MCP
+# Home Assistant MCP Documentation 🏠🤖
-Welcome to the Advanced Home Assistant Master Control Program documentation.
+Welcome to the documentation for my Home Assistant MCP (Model Context Protocol) Server. This documentation will help you get started with installation, configuration, and usage of the MCP server.
-This documentation provides comprehensive information about setting up, configuring, and using the Advanced Home Assistant MCP system.
+## What is MCP? 🤔
-## Quick Links
+MCP is a lightweight integration tool for Home Assistant that provides:
- [Getting Started](getting-started/index.md)
+- 🔌 REST API for device control
- [API Reference](api/index.md)
+- 📡 WebSocket/SSE for real-time updates
 - 🤖 AI-powered automation analysis
 - 🎤 Optional speech processing
 - 🔐 Secure authentication
 ## Quick Links 🔗
 - [Quick Start Guide](getting-started/quick-start.md)
 - [Configuration Guide](getting-started/configuration.md)
- [Docker Setup](getting-started/docker.md)
+- [API Reference](api/overview.md)
 - [Tools & Extras](tools/overview.md)
-## What is MCP Server?
+## System Architecture 📊
-MCP Server is a bridge between Home Assistant and custom automation tools, enabling basic device control and real-time monitoring of your smart home environment. It provides a flexible interface for managing and interacting with your home automation setup.
+```mermaid
 flowchart TB
    subgraph Client["Client Applications"]
        direction TB
        Web["Web Interface"]
        Mobile["Mobile Apps"]
        Voice["Voice Control"]
    end
    subgraph MCP["MCP Server"]
        direction TB
        API["REST API"]
        WS["WebSocket/SSE"]
        Auth["Authentication"]
        subgraph Speech["Speech Processing (Optional)"]
            direction TB
            Wake["Wake Word Detection"]
            STT["Speech-to-Text"]
            subgraph STT_Options["STT Options"]
                direction LR
                Whisper["Whisper"]
                FastWhisper["Fast Whisper"]
            end
            Wake --> STT
            STT --> STT_Options
        end
    end
    subgraph HA["Home Assistant"]
        direction TB
        HASS_API["HASS API"]
        HASS_WS["HASS WebSocket"]
        Devices["Smart Devices"]
    end
    Client --> MCP
    MCP --> HA
    HA --> Devices
    style Speech fill:#f9f,stroke:#333,stroke-width:2px
    style STT_Options fill:#bbf,stroke:#333,stroke-width:1px
 ```
 ## Prerequisites 📋
 - 🚀 [Bun runtime](https://bun.sh) (v1.0.26+)
 - 🏡 [Home Assistant](https://www.home-assistant.io/) instance
 - 🐳 Docker (optional, recommended for deployment)
 - 🖥️ Node.js 18+ (optional, for speech features)
 - 🎮 NVIDIA GPU with CUDA support (optional, for faster speech processing)
 ## Why Bun? 🚀
 I chose Bun as the runtime for several key benefits:
 - ⚡ **Blazing Fast Performance**
  - Up to 4x faster than Node.js
  - Built-in TypeScript support
  - Optimized file system operations
 - 🎯 **All-in-One Solution**
  - Package manager (faster than npm/yarn)
  - Bundler (no webpack needed)
  - Test runner (built-in testing)
  - TypeScript transpiler
 - 🔋 **Built-in Features**
  - SQLite3 driver
  - .env file loading
  - WebSocket client/server
  - File watcher
  - Test runner
 ## Getting Started 🚀
 Check out the [Quick Start Guide](getting-started/quick-start.md) to begin your journey with Home Assistant MCP!
 ## Key Features
--- a/docs/nlp.md
+++ b/docs/nlp.md
@@ -0,0 +1,196 @@
 # Natural Language Processing Guide 🤖
 ## Overview
 My MCP Server includes powerful Natural Language Processing (NLP) capabilities powered by various AI models. This enables intelligent automation analysis, natural language control, and context-aware interactions with your Home Assistant setup.
 ## Available Models 🎯
 ### OpenAI Models
 - **GPT-4**
  - Best for complex automation analysis
  - Natural language understanding
  - Context window: 8k-32k tokens
  - Recommended for: Automation analysis, complex queries
 - **GPT-3.5-Turbo**
  - Faster response times
  - More cost-effective
  - Context window: 4k tokens
  - Recommended for: Quick commands, basic analysis
 ### Claude Models
 - **Claude 2**
  - Excellent code analysis
  - Large context window (100k tokens)
  - Strong system understanding
  - Recommended for: Deep automation analysis
 ### DeepSeek Models
 - **DeepSeek-Coder**
  - Specialized in code understanding
  - Efficient for automation rules
  - Context window: 8k tokens
  - Recommended for: Code generation, rule analysis
 ## Configuration ⚙️
 ```bash
 # AI Model Configuration
 PROCESSOR_TYPE=openai          # openai, claude, or deepseek
 OPENAI_MODEL=gpt-3.5-turbo    # or gpt-4, gpt-4-32k
 OPENAI_API_KEY=your_key_here
 # Optional: DeepSeek Configuration
 DEEPSEEK_API_KEY=your_key_here
 DEEPSEEK_BASE_URL=https://api.deepseek.com/v1
 # Analysis Settings
 ANALYSIS_TIMEOUT=30000         # Timeout in milliseconds
 MAX_RETRIES=3                 # Number of retries on failure
 ```
 ## Usage Examples 💡
 ### 1. Automation Analysis
 ```bash
 # Analyze an automation rule
 bun run analyze-automation path/to/automation.yaml
 # Example output:
 # "This automation triggers on motion detection and turns on lights.
 #  Potential issues:
 #  - No timeout for light turn-off
 #  - Missing condition for ambient light level"
 ```
 ### 2. Natural Language Commands
 ```typescript
 // Send a natural language command
 const response = await fetch('http://localhost:3000/api/nlp/command', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': `Bearer ${token}`
  },
  body: JSON.stringify({
    command: "Turn on the living room lights and set them to warm white"
  })
 });
 ```
 ### 3. Context-Aware Queries
 ```typescript
 // Query with context
 const response = await fetch('http://localhost:3000/api/nlp/query', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': `Bearer ${token}`
  },
  body: JSON.stringify({
    query: "What's the temperature trend in the bedroom?",
    context: {
      timeframe: "last_24h",
      include_humidity: true
    }
  })
 });
 ```
 ## Custom Prompts 📝
 You can customize the AI's behavior by creating custom prompts. See [Custom Prompts Guide](prompts.md) for details.
 Example custom prompt:
 ```yaml
 name: energy_analysis
 description: Analyze home energy usage patterns
 prompt: |
  Analyze the following energy usage data and provide:
  1. Peak usage patterns
  2. Potential optimizations
  3. Comparison with typical usage
  4. Cost-saving recommendations
  Context: {context}
  Data: {data}
 ```
 ## Best Practices 🎯
 1. **Model Selection**
   - Use GPT-3.5-Turbo for quick queries
   - Use GPT-4 for complex analysis
   - Use Claude for large context analysis
   - Use DeepSeek for code-heavy tasks
 2. **Performance Optimization**
   - Cache frequent queries
   - Use streaming for long responses
   - Implement retry logic for API calls
 3. **Cost Management**
   - Monitor API usage
   - Implement rate limiting
   - Cache responses where appropriate
 4. **Error Handling**
   - Implement fallback models
   - Handle API timeouts gracefully
   - Log failed queries for analysis
 ## Advanced Features 🚀
 ### 1. Chain of Thought Analysis
 ```typescript
 const result = await analyzeWithCoT({
  query: "Optimize my morning routine automation",
  steps: ["Parse current automation", "Analyze patterns", "Suggest improvements"]
 });
 ```
 ### 2. Multi-Model Analysis
 ```typescript
 const results = await analyzeWithMultiModel({
  query: "Security system optimization",
  models: ["gpt-4", "claude-2"],
  compareResults: true
 });
 ```
 ### 3. Contextual Memory
 ```typescript
 const memory = new ContextualMemory({
  timeframe: "24h",
  maxItems: 100
 });
 await memory.add("User typically arrives home at 17:30");
 ```
 ## Troubleshooting 🔧
 ### Common Issues
 1. **Slow Response Times**
   - Check model selection
   - Verify API rate limits
   - Consider caching
 2. **Poor Analysis Quality**
   - Review prompt design
   - Check context window limits
   - Consider using a more capable model
 3. **API Errors**
   - Verify API keys
   - Check network connectivity
   - Review rate limits
 ## API Reference 📚
 See [API Documentation](api.md) for detailed endpoint specifications. 
--- a/docs/prompts.md
+++ b/docs/prompts.md
@@ -0,0 +1,263 @@
 # Custom Prompts Guide 🎯
 ## Overview
 Custom prompts allow you to tailor the AI's behavior to your specific needs. I've designed this system to be flexible and powerful, enabling everything from simple commands to complex automation analysis.
 ## Prompt Structure 📝
 Custom prompts are defined in YAML format:
 ```yaml
 name: prompt_name
 description: Brief description of what this prompt does
 version: 1.0
 author: your_name
 tags: [automation, analysis, security]
 models: [gpt-4, claude-2]  # Compatible models
 prompt: |
  Your detailed prompt text here.
  You can use {variables} for dynamic content.
  Context: {context}
  Data: {data}
 variables:
  - name: context
    type: object
    description: Contextual information
    required: true
  - name: data
    type: array
    description: Data to analyze
    required: true
 ```
 ## Prompt Types 🎨
 ### 1. Analysis Prompts
 ```yaml
 name: automation_analysis
 description: Analyze Home Assistant automations
 prompt: |
  Analyze the following Home Assistant automation:
  {automation_yaml}
  Provide:
  1. Security implications
  2. Performance considerations
  3. Potential improvements
  4. Error handling suggestions
 ```
 ### 2. Command Prompts
 ```yaml
 name: natural_command
 description: Process natural language commands
 prompt: |
  Convert the following natural language command into Home Assistant actions:
  "{command}"
  Available devices: {devices}
  Current state: {state}
 ```
 ### 3. Query Prompts
 ```yaml
 name: state_query
 description: Answer questions about system state
 prompt: |
  Answer the following question about the system state:
  "{question}"
  Current states:
  {states}
  Historical data:
  {history}
 ```
 ## Variables and Context 🔄
 ### Built-in Variables
 - `{timestamp}` - Current time
 - `{user}` - Current user
 - `{device_states}` - All device states
 - `{last_events}` - Recent events
 - `{system_info}` - System information
 ### Custom Variables
 ```yaml
 variables:
  - name: temperature_threshold
    type: number
    default: 25
    description: Temperature threshold for alerts
  - name: devices
    type: array
    required: true
    description: List of relevant devices
 ```
 ## Creating Custom Prompts 🛠️
 1. Create a new file in `prompts/custom/`:
 ```bash
 bun run create-prompt my_prompt
 ```
 2. Edit the generated template:
 ```yaml
 name: my_custom_prompt
 description: My custom prompt for specific tasks
 version: 1.0
 author: your_name
 prompt: |
  Your prompt text here
 ```
 3. Test your prompt:
 ```bash
 bun run test-prompt my_custom_prompt
 ```
 ## Advanced Features 🚀
 ### 1. Prompt Chaining
 ```yaml
 name: complex_analysis
 chain:
  - automation_analysis
  - security_check
  - optimization_suggestions
 ```
 ### 2. Conditional Prompts
 ```yaml
 name: adaptive_response
 conditions:
  - if: "temperature > 25"
    use: high_temp_prompt
  - if: "temperature < 10"
    use: low_temp_prompt
  - else: normal_temp_prompt
 ```
 ### 3. Dynamic Templates
 ```yaml
 name: dynamic_template
 template: |
  {% if time.hour < 12 %}
    Good morning! Here's the morning analysis:
  {% else %}
    Good evening! Here's the evening analysis:
  {% endif %}
  {analysis_content}
 ```
 ## Best Practices 🎯
 1. **Prompt Design**
   - Be specific and clear
   - Include examples
   - Use consistent formatting
   - Consider edge cases
 2. **Variable Usage**
   - Define clear variable types
   - Provide defaults when possible
   - Document requirements
   - Validate inputs
 3. **Performance**
   - Keep prompts concise
   - Use appropriate models
   - Cache when possible
   - Consider token limits
 4. **Maintenance**
   - Version your prompts
   - Document changes
   - Test thoroughly
   - Share improvements
 ## Examples 📚
 ### Home Security Analysis
 ```yaml
 name: security_analysis
 description: Analyze home security status
 prompt: |
  Analyze the current security status:
  Doors: {door_states}
  Windows: {window_states}
  Cameras: {camera_states}
  Motion Sensors: {motion_states}
  Recent Events:
  {recent_events}
  Provide:
  1. Current security status
  2. Potential vulnerabilities
  3. Recommended actions
  4. Automation suggestions
 ```
 ### Energy Optimization
 ```yaml
 name: energy_optimization
 description: Analyze and optimize energy usage
 prompt: |
  Review energy consumption patterns:
  Usage Data: {energy_data}
  Device States: {device_states}
  Weather: {weather_data}
  Provide:
  1. Usage patterns
  2. Inefficiencies
  3. Optimization suggestions
  4. Estimated savings
 ```
 ## Troubleshooting 🔧
 ### Common Issues
 1. **Prompt Not Working**
   - Verify YAML syntax
   - Check variable definitions
   - Validate model compatibility
   - Review token limits
 2. **Poor Results**
   - Improve prompt specificity
   - Add more context
   - Try different models
   - Include examples
 3. **Performance Issues**
   - Optimize prompt length
   - Review caching strategy
   - Check rate limits
   - Monitor token usage
 ## API Integration 🔌
 ```typescript
 // Load a custom prompt
 const prompt = await loadPrompt('my_custom_prompt');
 // Execute with variables
 const result = await executePrompt(prompt, {
  context: currentContext,
  data: analysisData
 });
 ```
 See [API Documentation](api.md) for more details. 
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -1,249 +1,107 @@
-site_name: MCP Server for Home Assistant
+site_name: Home Assistant MCP
-site_url: https://jango-blockchained.github.io/advanced-homeassistant-mcp
+site_url: https://jango-blockchained.github.io/homeassistant-mcp
-repo_url: https://github.com/jango-blockchained/advanced-homeassistant-mcp
+repo_url: https://github.com/jango-blockchained/homeassistant-mcp
-site_description: Home Assistant MCP Server Documentation
+repo_name: jango-blockchained/homeassistant-mcp
-# Add this to handle GitHub Pages serving from a subdirectory
+edit_uri: edit/main/docs/
 site_dir: site/advanced-homeassistant-mcp
 theme:
  name: material
  logo: assets/images/logo.png
  favicon: assets/images/favicon.ico
  # Modern Features
  features:
-    # Navigation Enhancements
+    - navigation.instant
-    - navigation.tabs
+    - navigation.tracking
    - navigation.tabs.sticky
    - navigation.indexes
    - navigation.sections
    - navigation.expand
-    - navigation.path
+    - navigation.indexes
    - navigation.footer
    - navigation.prune
    - navigation.tracking
    - navigation.instant
    # UI Elements
    - header.autohide
    - toc.integrate
    - toc.follow
    - announce.dismiss
    # Search Features
    - search.suggest
    - search.highlight
    - search.share
    # Code Features
    - content.code.annotate
    - content.code.copy
    - content.code.select
    - content.tabs.link
    - content.tooltips
  # Theme Configuration
  palette:
-    # Dark mode as primary
+    - scheme: default
-    - media: "(prefers-color-scheme: dark)"
+      primary: indigo
-      scheme: slate
+      accent: indigo
      primary: deep-purple
      accent: purple
      toggle:
-        icon: material/weather-sunny
+        icon: material/brightness-7
        name: Switch to light mode
    # Light mode as secondary
    - media: "(prefers-color-scheme: light)"
      scheme: default
      primary: deep-purple
      accent: purple
      toggle:
        icon: material/weather-night
        name: Switch to dark mode
-  
+    - scheme: slate
-  font:
+      primary: indigo
-    text: Roboto
+      accent: indigo
-    code: Roboto Mono
+      toggle:
-  
+        icon: material/brightness-4
        name: Switch to light mode
  icon:
    repo: fontawesome/brands/github
-    edit: material/pencil
+  favicon: assets/favicon.png
-    view: material/eye
+  logo: assets/logo.png
 plugins:
  - search
  - mermaid2
  - git-revision-date-localized:
      type: date
  - minify:
      minify_html: true
 markdown_extensions:
-  # Modern Code Highlighting
+  - admonition
-  - pymdownx.highlight:
+  - attr_list
-      anchor_linenums: true
+  - def_list
-      line_spans: __span
+  - footnotes
-      pygments_lang_class: true
+  - meta
-  - pymdownx.inlinehilite
+  - toc:
-  - pymdownx.snippets
+      permalink: true
-  
+  - pymdownx.arithmatex
-  # Advanced Formatting
+  - pymdownx.betterem:
-  - pymdownx.critic
+      smart_enable: all
  - pymdownx.caret
  - pymdownx.critic
  - pymdownx.details
  - pymdownx.emoji:
      emoji_index: !!python/name:materialx.emoji.twemoji
      emoji_generator: !!python/name:materialx.emoji.to_svg
  - pymdownx.highlight
  - pymdownx.inlinehilite
  - pymdownx.keys
  - pymdownx.mark
-  - pymdownx.tilde
+  - pymdownx.smartsymbols
  # Interactive Elements
  - pymdownx.details
  - pymdownx.tabbed:
      alternate_style: true
  - pymdownx.tasklist:
      custom_checkbox: true
  # Diagrams & Formatting
  - pymdownx.superfences:
      custom_fences:
        - name: mermaid
          class: mermaid
          format: !!python/name:pymdownx.superfences.fence_code_format
-  - pymdownx.arithmatex:
+  - pymdownx.tabbed:
-      generic: true
+      alternate_style: true
  - pymdownx.tasklist:
      custom_checkbox: true
  - pymdownx.tilde
  # Additional Extensions
  - admonition
  - attr_list
  - md_in_html
  - pymdownx.emoji:
      emoji_index: !!python/name:material.extensions.emoji.twemoji
      emoji_generator: !!python/name:material.extensions.emoji.to_svg
  - footnotes
  - tables
  - def_list
  - abbr
 plugins:
  # Core Plugins
  - search:
      separator: '[\s\-,:!=\[\]()"/]+|(?!\b)(?=[A-Z][a-z])|\.(?!\d)|&[lg]t;'
  - minify:
      minify_html: true
  - mkdocstrings
  # Advanced Features
  - social:
      cards: false
  - tags
  - offline
  # Version Management
  - git-revision-date-localized:
      enable_creation_date: true
      type: date
 extra:
  # Consent Management
  consent:
    title: Cookie consent
    description: >- 
      We use cookies to recognize your repeated visits and preferences, as well
      as to measure the effectiveness of our documentation and whether users
      find what they're searching for. With your consent, you're helping us to
      make our documentation better.
    actions:
      - accept
      - reject
      - manage
  # Version Management
  version:
    provider: mike
    default: latest
  # Social Links
  social:
    - icon: fontawesome/brands/github
      link: https://github.com/jango-blockchained/homeassistant-mcp
    - icon: fontawesome/brands/docker
      link: https://hub.docker.com/r/jangoblockchained/homeassistant-mcp
  # Status Indicators
  status:
    new: Recently added
    deprecated: Deprecated
    beta: Beta
  # Analytics
  analytics:
    provider: google
    property: !ENV GOOGLE_ANALYTICS_KEY
    feedback:
      title: Was this page helpful?
      ratings:
        - icon: material/emoticon-happy-outline
          name: This page was helpful
          data: 1
          note: >-
            Thanks for your feedback!
        - icon: material/emoticon-sad-outline
          name: This page could be improved
          data: 0
          note: >-
            Thanks for your feedback! Please consider creating an issue to help us improve.
 extra_css:
  - stylesheets/extra.css
 extra_javascript:
  - javascripts/mathjax.js
  - https://polyfill.io/v3/polyfill.min.js?features=es6
  - https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js
  - javascripts/extra.js
 copyright: Copyright &copy; 2025 jango-blockchained
 # Keep existing nav structure
 nav:
  - Home: index.md
  - Getting Started:
-    - Overview: getting-started/index.md
+    - Quick Start: getting-started/quick-start.md
    - Installation: getting-started/installation.md
    - Quick Start: getting-started/quickstart.md
    - Configuration: getting-started/configuration.md
-    - Docker Setup: getting-started/docker.md
+  - Features:
    - Core Features: features/core-features.md
    - Speech Processing: features/speech-processing.md
    - NLP Integration: features/nlp.md
    - Custom Prompts: features/prompts.md
  - Tools & Extras:
    - Overview: tools/overview.md
    - Analyzer CLI: tools/analyzer-cli.md
    - Speech Examples: tools/speech-examples.md
    - Claude Desktop: tools/claude-desktop.md
  - API Reference:
-    - Overview: api/index.md
+    - Overview: api/overview.md
-    - Core API: api/core.md
+    - REST API: api/rest.md
-    - SSE API: api/sse.md
+    - WebSocket API: api/websocket.md
-    - API Documentation: api.md
+    - Events: api/events.md
  - Usage: usage.md
  - Configuration:
    - Overview: config/index.md
    - System Configuration: configuration.md
    - Security: security.md
  - Tools:
    - Overview: tools/index.md
    - Device Management:
      - List Devices: tools/device-management/list-devices.md
      - Device Control: tools/device-management/control.md
    - History & State:
      - History: tools/history-state/history.md
      - Scene Management: tools/history-state/scene.md
    - Automation:
      - Automation Management: tools/automation/automation.md
      - Automation Configuration: tools/automation/automation-config.md
    - Add-ons & Packages:
      - Add-on Management: tools/addons-packages/addon.md
      - Package Management: tools/addons-packages/package.md
    - Notifications:
      - Notify: tools/notifications/notify.md
    - Events:
      - Event Subscription: tools/events/subscribe-events.md
      - SSE Statistics: tools/events/sse-stats.md
  - Development:
-    - Overview: development/index.md
+    - Setup: development/setup.md
-    - Environment Setup: development/environment.md
+    - Contributing: development/contributing.md
-    - Architecture: architecture.md
+    - Testing: development/testing.md
-    - Contributing: contributing.md
+  - Troubleshooting:
-    - Testing: testing.md
+    - Common Issues: troubleshooting/common-issues.md
-    - Best Practices: development/best-practices.md
+    - FAQ: troubleshooting/faq.md
-    - Interfaces: development/interfaces.md
+  - About:
-    - Tool Development: development/tools.md
+    - License: about/license.md
-    - Test Migration Guide: development/test-migration-guide.md
+    - Author: about/author.md
    - Troubleshooting: troubleshooting.md
    - Deployment: deployment.md
    - Roadmap: roadmap.md
  - Examples:
    - Overview: examples/index.md
--- a/scripts/setup-env.sh
+++ b/scripts/setup-env.sh
@@ -0,0 +1,97 @@
 #!/bin/bash
 # Colors for output
 RED='\033[0;31m'
 GREEN='\033[0;32m'
 YELLOW='\033[1;33m'
 NC='\033[0m' # No Color
 # Function to print colored messages
 print_message() {
    local color=$1
    local message=$2
    echo -e "${color}${message}${NC}"
 }
 # Function to check if a file exists
 check_file() {
    if [ -f "$1" ]; then
        return 0
    else
        return 1
    fi
 }
 # Function to copy environment file
 copy_env_file() {
    local source=$1
    local target=$2
    if [ -f "$target" ]; then
        print_message "$YELLOW" "Warning: $target already exists. Skipping..."
    else
        cp "$source" "$target"
        if [ $? -eq 0 ]; then
            print_message "$GREEN" "Created $target successfully"
        else
            print_message "$RED" "Error: Failed to create $target"
            exit 1
        fi
    fi
 }
 # Main script
 print_message "$GREEN" "Setting up environment files..."
 # Check if .env.example exists
 if ! check_file ".env.example"; then
    print_message "$RED" "Error: .env.example not found!"
    exit 1
 fi
 # Setup base environment file
 if [ "$1" = "--force" ]; then
    cp .env.example .env
    print_message "$GREEN" "Forced creation of .env file"
 else
    copy_env_file ".env.example" ".env"
 fi
 # Determine environment
 ENV=${NODE_ENV:-development}
 case "$ENV" in
    "development"|"dev")
        ENV_FILE=".env.dev"
        ;;
    "production"|"prod")
        ENV_FILE=".env.prod"
        ;;
    "test")
        ENV_FILE=".env.test"
        ;;
    *)
        print_message "$RED" "Error: Invalid environment: $ENV"
        exit 1
        ;;
 esac
 # Copy environment-specific file
 if [ -f "$ENV_FILE" ]; then
    if [ "$1" = "--force" ]; then
        cp "$ENV_FILE" .env
        print_message "$GREEN" "Forced override of .env with $ENV_FILE"
    else
        print_message "$YELLOW" "Do you want to override .env with $ENV_FILE? [y/N] "
        read -r response
        if [[ "$response" =~ ^([yY][eE][sS]|[yY])+$ ]]; then
            cp "$ENV_FILE" .env
            print_message "$GREEN" "Copied $ENV_FILE to .env"
        else
            print_message "$YELLOW" "Keeping existing .env file"
        fi
    fi
 else
    print_message "$YELLOW" "Warning: $ENV_FILE not found. Using default .env"
 fi
 print_message "$GREEN" "Environment setup complete!"
 print_message "$YELLOW" "Remember to set your HASS_TOKEN in .env" 
--- a/scripts/setup.sh
+++ b/scripts/setup.sh
@@ -0,0 +1,32 @@
 #!/bin/bash
 # Copy template if .env doesn't exist
 if [ ! -f .env ]; then
    cp .env.example .env
    echo "Created .env file from template. Please update your credentials!"
 fi
 # Validate required variables
 required_vars=("HASS_HOST" "HASS_TOKEN")
 missing_vars=()
 for var in "${required_vars[@]}"; do
    if ! grep -q "^$var=" .env; then
        missing_vars+=("$var")
    fi
 done
 if [ ${#missing_vars[@]} -ne 0 ]; then
    echo "ERROR: Missing required variables in .env:"
    printf '%s\n' "${missing_vars[@]}"
    exit 1
 fi
 # Check Docker version compatibility
 docker_version=$(docker --version | awk '{print $3}' | cut -d',' -f1)
 if [ "$(printf '%s\n' "20.10.0" "$docker_version" | sort -V | head -n1)" != "20.10.0" ]; then
    echo "ERROR: Docker version 20.10.0 or higher required"
    exit 1
 fi
 echo "Environment validation successful" 
--- a/src/config/app.config.ts
+++ b/src/config/app.config.ts
@@ -1,23 +1,5 @@
 import { config } from "dotenv";
 import { resolve } from "path";
 import { z } from "zod";
 /**
 * Load environment variables based on NODE_ENV
 * Development: .env.development
 * Test: .env.test
 * Production: .env
 */
 const envFile =
  process.env.NODE_ENV === "production"
    ? ".env"
    : process.env.NODE_ENV === "test"
      ? ".env.test"
      : ".env.development";
 console.log(`Loading environment from ${envFile}`);
 config({ path: resolve(process.cwd(), envFile) });
 /**
 * Application configuration object
 * Contains all configuration settings for the application
--- a/src/config/hass.config.ts
+++ b/src/config/hass.config.ts
@@ -11,6 +11,7 @@ const envFile =
 config({ path: resolve(process.cwd(), envFile) });
 // Base configuration for Home Assistant
 export const HASS_CONFIG = {
  // Base configuration
  BASE_URL: process.env.HASS_HOST || "http://localhost:8123",
--- a/src/config/index.ts
+++ b/src/config/index.ts
@@ -1,16 +1,7 @@
-import { config } from "dotenv";
+import { loadEnvironmentVariables } from "./loadEnv";
 import { resolve } from "path";
-// Load environment variables based on NODE_ENV
+// Load environment variables from the appropriate files
-const envFile =
+loadEnvironmentVariables();
  process.env.NODE_ENV === "production"
    ? ".env"
    : process.env.NODE_ENV === "test"
      ? ".env.test"
      : ".env.development";
 console.log(`Loading environment from ${envFile}`);
 config({ path: resolve(process.cwd(), envFile) });
 // Home Assistant Configuration
 export const HASS_CONFIG = {
--- a/src/config/loadEnv.ts
+++ b/src/config/loadEnv.ts
@@ -0,0 +1,49 @@
 import { config as dotenvConfig } from "dotenv";
 import fs from "fs";
 import path from "path";
 /**
 * Maps NODE_ENV values to their corresponding environment file names
 */
 const ENV_FILE_MAPPING: Record<string, string> = {
    production: ".env.prod",
    development: ".env.dev",
    test: ".env.test",
 };
 /**
 * Loads environment variables from the appropriate files based on NODE_ENV.
 * First loads environment-specific file, then overrides with generic .env if it exists.
 */
 export function loadEnvironmentVariables() {
    // Determine the current environment (default to 'development')
    const nodeEnv = (process.env.NODE_ENV || "development").toLowerCase();
    // Get the environment-specific file name
    const envSpecificFile = ENV_FILE_MAPPING[nodeEnv];
    if (!envSpecificFile) {
        console.warn(`Unknown NODE_ENV value: ${nodeEnv}. Using .env.dev as fallback.`);
    }
    const envFile = envSpecificFile || ".env.dev";
    const envPath = path.resolve(process.cwd(), envFile);
    // Load the environment-specific file if it exists
    if (fs.existsSync(envPath)) {
        dotenvConfig({ path: envPath });
        console.log(`Loaded environment variables from ${envFile}`);
    } else {
        console.warn(`Environment-specific file ${envFile} not found.`);
    }
    // Finally, check if there is a generic .env file present
    // If so, load it with the override option, so its values take precedence
    const genericEnvPath = path.resolve(process.cwd(), ".env");
    if (fs.existsSync(genericEnvPath)) {
        dotenvConfig({ path: genericEnvPath, override: true });
        console.log("Loaded and overrode with generic .env file");
    }
 }
 // Export the environment file mapping for reference
 export const ENV_FILES = ENV_FILE_MAPPING; 
--- a/src/websocket/client.ts
+++ b/src/websocket/client.ts
@@ -74,8 +74,11 @@ export class HassWebSocketClient extends EventEmitter {
        };
        this.ws.onerror = (event: WebSocket.ErrorEvent) => {
-          this.emit('error', event);
+          const error = event.error || new Error(event.message || 'WebSocket error');
-          reject(event);
+          this.emit('error', error);
          if (!this.authenticated) {
            reject(error);
          }
        };
        this.ws.onmessage = (event: WebSocket.MessageEvent) => {
		`@@ -1 +0,0 @@`
			NODE_ENV=development\nOPENAI_API_KEY=your_openai_api_key_here\nHASS_HOST=http://homeassistant.local:8123\nHASS_TOKEN=your_hass_token_here\nPORT=3000\nHASS_SOCKET_URL=ws://homeassistant.local:8123/api/websocket\nLOG_LEVEL=debug\nMCP_SERVER=http://localhost:3000\nOPENAI_MODEL=deepseek-v3\nMAX_RETRIES=3\nANALYSIS_TIMEOUT=30000\n\n# Home Assistant specific settings\nAUTOMATION_PATH=./config/automations.yaml\nBLUEPRINT_REPO=https://blueprints.home-assistant.io/\nENERGY_DASHBOARD=true\n\n# Available models: gpt-4o, gpt-4-turbo, gpt-4, gpt-4-o1, gpt-4-o3, gpt-3.5-turbo, gpt-3.5-turbo-16k, deepseek-v3, deepseek-r1\n\n# For DeepSeek models\nDEEPSEEK_API_KEY=your_deepseek_api_key_here\nDEEPSEEK_BASE_URL=https://api.deepseek.com/v1\n\n# Model specifications:\n# - gpt-4-o1: 128k context, general purpose\n# - gpt-4-o3: 1M context, large-scale analysis\n\n# Add processor type specification\nPROCESSOR_TYPE=claude # Change to openai when using OpenAI