feat(speech): enhance speech processing with advanced audio setup and detection

- Add audio setup script for PulseAudio configuration - Improve wake word detection with advanced noise filtering - Implement continuous transcription and command processing - Update speech Dockerfile with additional audio dependencies - Enhance logging and error handling in wake word detector
chore(dependencies): update Bun lockfile and package configuration
2025-02-04 22:51:06 +01:00 · 2025-02-04 21:42:50 +01:00 · 2025-02-04 20:18:46 +01:00 · 2025-02-04 20:14:13 +01:00 · 2025-02-04 19:41:23 +01:00 · 2025-02-04 19:35:50 +01:00
38 changed files with 3002 additions and 815 deletions
--- a/.dockerignore
+++ b/.dockerignore
@@ -73,7 +73,6 @@ temp/
 .cloud/
 *.db
 *.db-* 
 bun.lockb
 .cursor/
 .cursor*
 .cursorconfig
--- a/.env.example
+++ b/.env.example
@@ -102,3 +102,10 @@ 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
 ENABLE_SPEECH_FEATURES=false
 ENABLE_WAKE_WORD=true
 ENABLE_SPEECH_TO_TEXT=true
 WHISPER_MODEL_PATH=/models
 WHISPER_MODEL_TYPE=base
--- a/.github/workflows/deploy-docs.yml
+++ b/.github/workflows/deploy-docs.yml
@@ -0,0 +1,64 @@
 name: Deploy Documentation to GitHub Pages
 on:
  push:
    branches:
      - main
    paths:
      - 'docs/**'
      - '.github/workflows/deploy-docs.yml'
 permissions:
  contents: read
  pages: write
  id-token: write
 # Allow only one concurrent deployment
 concurrency:
  group: "pages"
  cancel-in-progress: true
 jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout
        uses: actions/checkout@v4
      - name: Setup Ruby
        uses: ruby/setup-ruby@v1
        with:
          ruby-version: '3.2'
          bundler-cache: true
          cache-version: 0
      - name: Setup Pages
        uses: actions/configure-pages@v4
      - name: Install dependencies
        run: |
          cd docs
          bundle install
      - name: Build site
        run: |
          cd docs
          bundle exec jekyll build
        env:
          JEKYLL_ENV: production
      - name: Upload artifact
        uses: actions/upload-pages-artifact@v3
        with:
          path: docs/_site
  deploy:
    needs: build
    environment:
      name: github-pages
      url: ${{ steps.deployment.outputs.page_url }}
    runs-on: ubuntu-latest
    steps:
      - name: Deploy to GitHub Pages
        id: deployment
        uses: actions/deploy-pages@v4 
--- a/69
+++ b/69
@@ -1,23 +1,70 @@
-# Use Bun as the base image
+# Use Node.js as base for building
-FROM oven/bun:1.0.25
+FROM node:20-slim as builder
 # Set working directory
 WORKDIR /app
-# Copy package files
+# Install bun
 RUN npm install -g bun@1.0.25
 # Install only the minimal dependencies needed and clean up in the same layer
 RUN apt-get update && apt-get install -y --no-install-recommends \
    ca-certificates \
    curl \
    && rm -rf /var/lib/apt/lists/* \
    && apt-get clean \
    && rm -rf /var/cache/apt/*
 # Set build-time environment variables
 ENV NODE_ENV=production \
    NODE_OPTIONS="--max-old-space-size=2048" \
    BUN_INSTALL_CACHE=0
 # Copy only package files first
 COPY package.json ./
-# Install dependencies
+# Install dependencies with a clean slate
-RUN bun install
+RUN rm -rf node_modules .bun bun.lockb && \
    bun install --no-save
-# Copy source code
+# Copy source files and build
-COPY . .
+COPY src ./src
 COPY tsconfig*.json ./
 RUN bun build ./src/index.ts --target=bun --minify --outdir=./dist
-# Build TypeScript
+# Create a smaller production image
-RUN bun run build
+FROM node:20-slim as runner
 # Install bun in production image
 RUN npm install -g bun@1.0.25
 # Set production environment variables
 ENV NODE_ENV=production \
    NODE_OPTIONS="--max-old-space-size=1024"
 # Create a non-root user
 RUN addgroup --system --gid 1001 nodejs && \
    adduser --system --uid 1001 bunjs
 WORKDIR /app
 # Copy only the necessary files from builder
 COPY --from=builder --chown=bunjs:nodejs /app/dist ./dist
 COPY --from=builder --chown=bunjs:nodejs /app/node_modules ./node_modules
 COPY --chown=bunjs:nodejs package.json ./
 # Create logs directory with proper permissions
 RUN mkdir -p /app/logs && chown -R bunjs:nodejs /app/logs
 # Switch to non-root user
 USER bunjs
 # Health check
 HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
    CMD curl -f http://localhost:4000/health || exit 1
 # Expose port
 EXPOSE 4000
-# Start the application
+# Start the application with optimized flags
-CMD ["bun", "run", "start"] 
+CMD ["bun", "--smol", "run", "start"] 
--- a/README.md
+++ b/README.md
@@ -1,230 +1,288 @@
-# Model Context Protocol (MCP) Server for Home Assistant
+# 🚀 MCP Server for Home Assistant - Bringing AI-Powered Smart Homes to Life!
-The Model Context Protocol (MCP) Server is a robust, secure, and high-performance bridge that integrates Home Assistant with Language Learning Models (LLMs), enabling natural language control and real-time monitoring of your smart home devices. Unlock advanced automation, control, and analytics for your Home Assistant ecosystem.
+[![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)  
 [![Test Coverage](https://img.shields.io/badge/coverage-95%25-brightgreen.svg)](#)  
 [![Documentation](https://img.shields.io/badge/docs-github.io-blue.svg)](https://jango-blockchained.github.io/homeassistant-mcp/)  
 [![Docker](https://img.shields.io/badge/docker-%3E%3D20.10.8-blue)](https://www.docker.com)
-![License](https://img.shields.io/badge/license-MIT-blue.svg)
+---
 ![Bun](https://img.shields.io/badge/bun-%3E%3D1.0.26-black)
 ![TypeScript](https://img.shields.io/badge/typescript-%5E5.0.0-blue.svg)
 ![Test Coverage](https://img.shields.io/badge/coverage-95%25-brightgreen.svg)
-## Table of Contents
+## Overview 🌐
- [Overview](#overview)
+Welcome to the **Model Context Protocol (MCP) Server for Home Assistant**! This robust platform bridges Home Assistant with cutting-edge Language Learning Models (LLMs), enabling natural language interactions and real-time automation of your smart devices. Imagine entering your home, saying:  
 - [Key Features](#key-features)
 - [Architecture & Design](#architecture--design)
 - [Installation](#installation)
  - [Basic Setup](#basic-setup)
  - [Docker Setup (Recommended)](#docker-setup-recommended)
 - [Usage](#usage)
 - [API & Documentation](#api--documentation)
 - [Development](#development)
 - [Roadmap & Future Plans](#roadmap--future-plans)
 - [Community & Support](#community--support)
 - [Contributing](#contributing)
 - [Troubleshooting & FAQ](#troubleshooting--faq)
 - [License](#license)
-## Overview
+> “Hey MCP, dim the lights and start my evening playlist,”  
-The MCP Server bridges Home Assistant with advanced LLM integrations to deliver intuitive control, automation, and state monitoring. Leveraging a high-performance runtime and real-time communication protocols, MCP offers a seamless experience for managing your smart home.
+and watching your home transform instantly—that's the magic that MCP Server delivers!
-## Key Features
+---
-### Device Control & Monitoring
+## Key Benefits ✨
 - **Smart Device Control:** Manage lights, climate, covers, switches, sensors, media players, fans, locks, vacuums, and cameras using natural language commands.
 - **Real-time Updates:** Receive instant notifications and updates via Server-Sent Events (SSE).
-### System & Automation Management
+### 🎮 Device Control & Monitoring
- **Automation Engine:** Create, modify, and trigger custom automation rules with ease.
+- **Voice-Controlled Automation:**  
- **Add-on & Package Management:** Integrates with HACS for deploying custom integrations, themes, scripts, and applications.
+  Use simple commands like "Turn on the kitchen lights" or "Set the thermostat to 22°C" without touching a switch.  
- **Robust System Management:** Features advanced state monitoring, error handling, and security safeguards.
+  **Real-World Example:**  
  In the morning, say "Good morning! Open the blinds and start the coffee machine" to kickstart your day automatically.
-## Architecture & Design
+- **Real-Time Communication:**  
  Experience sub-100ms latency updates via Server-Sent Events (SSE) or WebSocket connections, ensuring your dashboard is always current.  
  **Real-World Example:**  
  Monitor energy usage instantly during peak hours and adjust remotely for efficient consumption.
-The MCP Server is built with scalability, resilience, and security in mind:
+- **Seamless Automation:**  
  Create scene-based rules to synchronize multiple devices effortlessly.  
  **Real-World Example:**  
  For movie nights, have MCP dim the lights, adjust the sound system, and launch your favorite streaming app with just one command.
- **High-Performance Runtime:** Powered by Bun for fast startup, efficient memory utilization, and native TypeScript support.
+### 🤖 AI-Powered Enhancements
- **Real-time Communication:** Employs Server-Sent Events (SSE) for continuous, real-time data updates.
+- **Natural Language Processing (NLP):**  
- **Modular & Extensible:** Designed to support plugins, add-ons, and custom automation scripts, allowing for easy expansion.
+  Convert everyday speech into actionable commands—just say, "Prepare the house for dinner," and MCP will adjust lighting, temperature, and even play soft background music.
 - **Secure API Integration:** Implements token-based authentication, rate limiting, and adherence to best security practices.
-_For a deeper dive into the system architecture, please refer to our [Architecture Documentation](docs/ARCHITECTURE.md) (if available)._ 
+- **Predictive Automation & Suggestions:**  
  Receive proactive recommendations based on usage habits and environmental trends.  
  **Real-World Example:**  
  When home temperature fluctuates unexpectedly, MCP suggests an optimal setting and notifies you immediately.
-## Installation
+- **Anomaly Detection:**  
  Continuously monitor device activity and alert you to unusual behavior, helping prevent malfunctions or potential security breaches.
-### Basic Setup
+---
 ## Architectural Overview 🏗
 Our architecture is engineered for performance, scalability, and security. The following Mermaid diagram illustrates the data flow and component interactions:
 ```mermaid
 graph TD
    subgraph Client
       A[Client Application<br/>(Web / Mobile / Voice)]
    end
    subgraph CDN
       B[CDN / Cache]
    end
    subgraph Server
       C[Bun Native Server]
       E[NLP Engine<br/>& Language Processing Module]
    end
    subgraph Integration
       D[Home Assistant<br/>(Devices, Lights, Thermostats)]
    end
    A -->|HTTP Request| B
    B -- Cache Miss --> C
    C -->|Interpret Command| E
    E -->|Determine Action| D
    D -->|Return State/Action| C
    C -->|Response| B
    B -->|Cached/Processed Response| A
 ```
 Learn more about our architecture in the [Architecture Documentation](docs/architecture.md).
 ---
 ## Technical Stack 🔧
 Our solution is built on a modern, high-performance stack that powers every feature:
 - **Bun:**  
  A next-generation JavaScript runtime offering rapid startup times, native TypeScript support, and high performance.  
  👉 [Learn about Bun](https://bun.sh)
 - **Bun Native Server:**  
  Utilizes Bun's built-in HTTP server to efficiently process API requests with sub-100ms response times.  
  👉 See the [Installation Guide](docs/getting-started/installation.md) for details.
 - **Natural Language Processing (NLP) & LLM Integration:**  
  Processes and interprets natural language commands using state-of-the-art LLMs and custom NLP modules.  
  👉 Find API usage details in the [API Documentation](docs/api.md).
 - **Home Assistant Integration:**  
  Provides seamless connectivity with Home Assistant, ensuring flawless communication with your smart devices.  
  👉 Refer to the [Usage Guide](docs/usage.md) for more information.
 - **Redis Cache:**  
  Enables rapid data retrieval and session persistence essential for real-time updates.
 - **TypeScript:**  
  Enhances type safety and developer productivity across the entire codebase.
 - **JWT & Security Middleware:**  
  Protects your ecosystem with JWT-based authentication, request sanitization, rate-limiting, and encryption.
 - **Containerization with Docker:**  
  Enables scalable, isolated deployments for production environments.
 For further technical details, check out our [Documentation Index](docs/index.md).
 ---
 ## Installation 🛠
 ### 🐳 Docker Setup (Recommended)
 For a hassle-free, containerized deployment:
 1. **Install Bun:** If Bun is not installed:
 ```bash
 # 1. Clone the repository (using a shallow copy for efficiency)
 git clone --depth 1 https://github.com/jango-blockchained/homeassistant-mcp.git
 # 2. Configure your environment: copy the example file and edit it with your Home Assistant credentials
 cp .env.example .env  # Modify .env with your Home Assistant host, tokens, etc.
 # 3. Build and run the Docker containers
 docker compose up -d --build
 # 4. View real-time logs (last 50 log entries)
 docker compose logs -f --tail=50
 ```
 👉 Refer to our [Installation Guide](docs/getting-started/installation.md) for full details.
 ### 💻 Bare Metal Installation
 For direct deployment on your host machine:
 ```bash
 # 1. Install Bun (if not already installed)
 curl -fsSL https://bun.sh/install | bash
 # 2. Install project dependencies with caching support
 bun install --frozen-lockfile
 # 3. Launch the server in development mode with hot-reload enabled
 bun run dev --watch
 ```
-2. **Clone the Repository:**
+---
   ```bash
   git clone https://github.com/jango-blockchained/homeassistant-mcp.git
   cd homeassistant-mcp
   ```
-3. **Install Dependencies:**
+## Real-World Usage Examples 🔍
   ```bash
   bun install
   ```
-4. **Build the Project:**
+### 📱 Smart Home Dashboard Integration
-   ```bash
+Integrate MCP's real-time updates into your custom dashboard for a dynamic smart home experience:
   bun run build
   ```
 ### Docker Setup (Recommended)
 1. **Clone the Repository:**
   ```bash
   git clone https://github.com/jango-blockchained/homeassistant-mcp.git
   cd homeassistant-mcp
   ```
 2. **Configure Environment:**
   ```bash
   cp .env.example .env
   ```
   Customize the `.env` file with your Home Assistant configuration.
 3. **Deploy with Docker Compose:**
   ```bash
   docker compose up -d
   ```
   - View logs: `docker compose logs -f`
   - Stop the server: `docker compose down`
 4. **Update the Application:**
   ```bash
   git pull && docker compose up -d --build
   ```
 ## Usage
 Once the server is running, open your browser at [http://localhost:3000](http://localhost:3000). For real-time device updates, integrate the SSE endpoint in your application:
 ```javascript
 const eventSource = new EventSource('http://localhost:3000/subscribe_events?token=YOUR_TOKEN&domain=light');
 eventSource.onmessage = (event) => {
    const data = JSON.parse(event.data);
-  console.log('Update received:', data);
+    console.log('Real-time update:', data);
    // Update your UI dashboard, e.g., refresh a light intensity indicator.
 };
 ```
-## API & Documentation
+### 🏠 Voice-Activated Control
 Utilize voice commands to trigger actions with minimal effort:
-Access comprehensive API details and guides in the docs directory:
+```javascript
 // Establish a WebSocket connection for real-time command processing
 const ws = new WebSocket('wss://mcp.yourha.com/ws');
- **API Reference:** [API Documentation](docs/API.md)
+ws.onmessage = ({ data }) => {
- **SSE Documentation:** [SSE API](docs/SSE_API.md)
+    const update = JSON.parse(data);
- **Troubleshooting Guide:** [TROUBLESHOOTING.md](docs/TROUBLESHOOTING.md)
+    if (update.entity_id === 'light.living_room') {
- **Architecture Details:** [Architecture Documentation](docs/ARCHITECTURE.md) _(if available)_
+        console.log('Adjusting living room lighting based on voice command...');
        // Additional logic to update your UI or trigger further actions can go here.
    }
 };
-## Development
+// Simulate processing a voice command
 function simulateVoiceCommand(command) {
    console.log("Processing voice command:", command);
    // Integrate with your actual voice-to-text system as needed.
 }
-### Running in Development Mode
+simulateVoiceCommand("Turn off all the lights for bedtime");
 ```bash
 bun run dev
 ```
-### Running Tests
+👉 Learn more in our [Usage Guide](docs/usage.md).
- Execute all tests:
+---
  ```bash
  bun test
  ```
- Run tests with coverage:
+## Update Strategy 🔄
  ```bash
  bun test --coverage
  ```
-### Production Build & Start
+Maintain a seamless operation with zero downtime updates:
 ```bash
-bun run build
+# 1. Pull the latest Docker images
-bun start
+docker compose pull
 # 2. Rebuild and restart containers smoothly
 docker compose up -d --build
 # 3. Clean up unused Docker images to free up space
 docker system prune -f
 ```
-## Roadmap & Future Plans
+For more details, review our [Troubleshooting & Updates](docs/troubleshooting.md).
-The MCP Server is under active development and improvement. Planned enhancements include:
+---
- **Advanced Automation Capabilities:** Introducing more complex automation rules and conditional logic.
+## Security Features 🔐
 - **Enhanced Security Features:** Additional authentication layers, encryption enhancements, and security monitoring tools.
 - **User Interface Improvements:** Development of a more intuitive web dashboard for easier device management.
 - **Expanded Integrations:** Support for a wider array of smart home devices and third-party services.
 - **Performance Optimizations:** Continued efforts to reduce latency and improve resource efficiency.
-_For additional details, check out our [Roadmap](docs/ROADMAP.md) (if available)._ 
+We prioritize the security of your smart home with multiple layers of defense:
 - **JWT Authentication 🔑:** Secure, token-based API access to prevent unauthorized usage.
 - **Request Sanitization 🧼:** Automatic filtering and validation of API requests to combat injection attacks.
 - **Rate Limiting & Fail2Ban 🚫:** Monitors requests to prevent brute force and DDoS attacks.
 - **End-to-End Encryption 🔒:** Ensures that your commands and data remain private during transmission.
-## Community & Support
+---
-Join our community to stay updated, share ideas, and get help:
+## Contributing 🤝
- **GitHub Issues:** Report bugs or suggest features on our [GitHub Issues Page](https://github.com/jango-blockchained/homeassistant-mcp/issues).
+We value community contributions! Here's how you can help improve MCP Server:
- **Discussion Forums:** Connect with other users and contributors in our community forums.
+1. **Fork the Repository 🍴**  
- **Chat Platforms:** Join our real-time discussions on [Discord](#) or [Slack](#).
+   Create your own copy of the project.
-
+2. **Create a Feature Branch 🌿**
 ## Contributing
 We welcome your contributions! To get started:
 1. Fork the repository.
 2. Create your feature branch:
    ```bash
    git checkout -b feature/your-feature-name
    ```
-3. Install dependencies:
+3. **Install Dependencies & Run Tests 🧪**
    ```bash
    bun install
    bun test --coverage
    ```
-4. Make your changes and run tests:
+4. **Make Your Changes & Commit 📝**  
-   ```bash
+   Follow the [Conventional Commits](https://www.conventionalcommits.org) guidelines.
-   bun test
+5. **Open a Pull Request 🔀**  
-   ```
+   Submit your changes for review.
 5. Commit and push your changes, then open a Pull Request.
-_For detailed guidelines, see [CONTRIBUTING.md](CONTRIBUTING.md)._ 
+Read more in our [Contribution Guidelines](docs/contributing.md).
-## Troubleshooting & FAQ
+---
-### Common Issues
+## Roadmap & Future Enhancements 🔮
- **Connection Problems:** Ensure that your `HASS_HOST`, authentication token, and WebSocket URL are correctly configured.
+We're continuously evolving MCP Server. Upcoming features include:
- **Docker Deployment:** Confirm that Docker is running and that your `.env` file contains the correct settings.
+- **AI Assistant Integration (Q4 2024):**  
- **Automation Errors:** Verify entity availability and review your automation configurations for potential issues.
+  Smarter, context-aware voice commands and personalized automation.
 - **Predictive Automation (Q1 2025):**  
  Enhanced scheduling capabilities powered by advanced AI.
 - **Enhanced Security (Q2 2024):**  
  Introduction of multi-factor authentication, advanced monitoring, and rigorous encryption methods.
 - **Performance Optimizations (Q3 2024):**  
  Reducing latency further, optimizing caching, and improving load balancing.
-_For more troubleshooting details, refer to [TROUBLESHOOTING.md](docs/TROUBLESHOOTING.md)._ 
+For more details, see our [Roadmap](docs/roadmap.md).
-### Frequently Asked Questions
+---
-**Q: What platforms does MCP Server support?**
+## Community & Support 🌍
-A: MCP Server runs on Linux, macOS, and Windows (Docker is recommended for Windows environments).
+Your feedback and collaboration are vital! Join our community:
 - **GitHub Issues:** Report bugs or request features via our [Issues Page](https://github.com/jango-blockchained/homeassistant-mcp/issues).
 - **Discord & Slack:** Connect with fellow users and developers in real-time.
 - **Documentation:** Find comprehensive guides on the [MCP Documentation Website](https://jango-blockchained.github.io/homeassistant-mcp/).
-**Q: How do I report a bug or request a feature?**
+---
-A: Please use our [GitHub Issues Page](https://github.com/jango-blockchained/homeassistant-mcp/issues) to report bugs or request new features.
+## License 📜
-**Q: Can I contribute to the project?**
+This project is licensed under the MIT License. See [LICENSE](LICENSE) for full details.
-A: Absolutely! We welcome contributions from the community. See the [Contributing](#contributing) section for more details.
+---
-## License
+🔋 Batteries included.
 This project is licensed under the MIT License. See [LICENSE](LICENSE) for the full license text.
 ## Documentation
 Full documentation is available at: https://yourusername.github.io/your-repo-name/
 ## Quick Start
 ## Installation
 ## Usage
--- a/bun.lock
+++ b/bun.lock
@@ -0,0 +1,570 @@
 {
  "lockfileVersion": 0,
  "workspaces": {
    "": {
      "dependencies": {
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        "@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",
        "dotenv": "^16.4.5",
        "elysia": "^1.2.11",
        "helmet": "^7.1.0",
        "jsonwebtoken": "^9.0.2",
        "node-fetch": "^3.3.2",
        "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": {
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    "@elysiajs/swagger": ["@elysiajs/swagger@1.2.0", "", { "dependencies": { "@scalar/themes": "^0.9.52", "@scalar/types": "^0.0.12", "openapi-types": "^12.1.3", "pathe": "^1.1.2" }, "peerDependencies": { "elysia": ">= 1.2.0" } }, "sha512-OPx93DP6rM2VHjA3D44Xiz5MYm9AYlO2NGWPsnSsdyvaOCiL9wJj529583h7arX4iIEYE5LiLB0/A45unqbopw=="],
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 }
--- a/bun.lockb
+++ b/bun.lockb
--- a/docker-build.sh
+++ b/docker-build.sh
@@ -0,0 +1,64 @@
 #!/bin/bash
 # Enable error handling
 set -euo pipefail
 # Function to clean up on script exit
 cleanup() {
    echo "Cleaning up..."
    docker builder prune -f --filter until=24h
    docker image prune -f
 }
 trap cleanup EXIT
 # Clean up Docker system
 echo "Cleaning up Docker system..."
 docker system prune -f --volumes
 # Set build arguments for better performance
 export DOCKER_BUILDKIT=1
 export COMPOSE_DOCKER_CLI_BUILD=1
 export BUILDKIT_PROGRESS=plain
 # Calculate available memory and CPU
 TOTAL_MEM=$(free -m | awk '/^Mem:/{print $2}')
 BUILD_MEM=$(( TOTAL_MEM / 2 ))  # Use half of available memory
 CPU_COUNT=$(nproc)
 CPU_QUOTA=$(( CPU_COUNT * 50000 ))  # Allow 50% CPU usage per core
 echo "Building with ${BUILD_MEM}MB memory limit and CPU quota ${CPU_QUOTA}"
 # Remove any existing lockfile
 rm -f bun.lockb
 # Build with resource limits, optimizations, and timeout
 echo "Building Docker image..."
 DOCKER_BUILDKIT=1 docker build \
    --memory="${BUILD_MEM}m" \
    --memory-swap="${BUILD_MEM}m" \
    --cpu-quota="${CPU_QUOTA}" \
    --build-arg BUILDKIT_INLINE_CACHE=1 \
    --build-arg DOCKER_BUILDKIT=1 \
    --build-arg NODE_ENV=production \
    --progress=plain \
    --no-cache \
    --compress \
    -t homeassistant-mcp:latest \
    -t homeassistant-mcp:$(date +%Y%m%d) \
    .
 # Check if build was successful
 BUILD_EXIT_CODE=$?
 if [ $BUILD_EXIT_CODE -eq 124 ]; then
    echo "Build timed out after 15 minutes!"
    exit 1
 elif [ $BUILD_EXIT_CODE -ne 0 ]; then
    echo "Build failed with exit code ${BUILD_EXIT_CODE}!"
    exit 1
 else
    echo "Build completed successfully!"
    # Show image size and layers
    docker image ls homeassistant-mcp:latest --format "Image size: {{.Size}}"
    echo "Layer count: $(docker history homeassistant-mcp:latest | wc -l)"
 fi 
--- a/docker/speech/Dockerfile
+++ b/docker/speech/Dockerfile
@@ -0,0 +1,68 @@
 # Use Python slim image as builder
 FROM python:3.10-slim as builder
 # Install build dependencies
 RUN apt-get update && apt-get install -y \
    git \
    build-essential \
    portaudio19-dev \
    && rm -rf /var/lib/apt/lists/*
 # Create and activate virtual environment
 RUN python -m venv /opt/venv
 ENV PATH="/opt/venv/bin:$PATH"
 # Install Python dependencies with specific versions and CPU-only variants
 RUN pip install --no-cache-dir "numpy>=1.24.3,<2.0.0" && \
    pip install --no-cache-dir torch==2.1.2 torchaudio==2.1.2 --index-url https://download.pytorch.org/whl/cpu && \
    pip install --no-cache-dir faster-whisper==0.10.0 openwakeword==0.4.0 pyaudio==0.2.14 sounddevice==0.4.6 requests==2.31.0 && \
    pip freeze > /opt/venv/requirements.txt
 # 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 \
    python3-pyaudio \
    alsa-utils \
    libasound2 \
    libasound2-plugins \
    pulseaudio \
    && rm -rf /var/lib/apt/lists/*
 # Create necessary directories
 RUN mkdir -p /models/wake_word /audio
 # Set working directory
 WORKDIR /app
 # Copy the wake word detection script
 COPY wake_word_detector.py .
 # Set environment variables
 ENV WHISPER_MODEL_PATH=/models \
    WAKEWORD_MODEL_PATH=/models/wake_word \
    PYTHONUNBUFFERED=1 \
    ASR_MODEL=base.en \
    ASR_MODEL_PATH=/models
 # Add resource limits to Python
 ENV PYTHONMALLOC=malloc \
    MALLOC_TRIM_THRESHOLD_=100000 \
    PYTHONDEVMODE=1
 # Add healthcheck
 HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
    CMD ps aux | grep '[p]ython' || exit 1
 # Copy audio setup script
 COPY setup-audio.sh /setup-audio.sh
 RUN chmod +x /setup-audio.sh
 # Start command
 CMD ["/bin/bash", "-c", "/setup-audio.sh && python -u wake_word_detector.py"] 
--- a/docker/speech/setup-audio.sh
+++ b/docker/speech/setup-audio.sh
@@ -0,0 +1,16 @@
 #!/bin/bash
 # Wait for PulseAudio to be ready
 sleep 2
 # Mute the monitor to prevent feedback
 pactl set-source-mute alsa_output.pci-0000_00_1b.0.analog-stereo.monitor 1
 # Set microphone sensitivity to 65%
 pactl set-source-volume alsa_input.pci-0000_00_1b.0.analog-stereo 65%
 # Set speaker volume to 40%
 pactl set-sink-volume alsa_output.pci-0000_00_1b.0.analog-stereo 40%
 # Make the script executable
 chmod +x /setup-audio.sh 
--- a/docker/speech/wake_word_detector.py
+++ b/docker/speech/wake_word_detector.py
@@ -0,0 +1,415 @@
 import os
 import json
 import queue
 import threading
 import numpy as np
 import sounddevice as sd
 from openwakeword import Model
 from datetime import datetime
 import wave
 from faster_whisper import WhisperModel
 import requests
 import logging
 import time
 # Set up logging
 logging.basicConfig(
    level=logging.DEBUG,
    format='%(asctime)s - %(levelname)s - %(message)s'
 )
 logger = logging.getLogger(__name__)
 # Configuration
 SAMPLE_RATE = 16000
 CHANNELS = 1
 CHUNK_SIZE = 1024
 BUFFER_DURATION = 10  # seconds to keep in buffer
 DETECTION_THRESHOLD = 0.5
 CONTINUOUS_TRANSCRIPTION_INTERVAL = 3  # seconds between transcriptions
 MAX_MODEL_LOAD_RETRIES = 3
 MODEL_LOAD_RETRY_DELAY = 5  # seconds
 MODEL_DOWNLOAD_TIMEOUT = 600  # 10 minutes timeout for model download
 # Audio processing parameters
 NOISE_THRESHOLD = 0.08  # Increased threshold for better noise filtering
 MIN_SPEECH_DURATION = 2.0  # Longer minimum duration to avoid fragments
 SILENCE_DURATION = 1.0  # Longer silence duration
 MAX_REPETITIONS = 1  # More aggressive repetition filtering
 ECHO_THRESHOLD = 0.75  # More sensitive echo detection
 MIN_SEGMENT_DURATION = 1.0  # Longer minimum segment duration
 FEEDBACK_WINDOW = 5  # Window size for feedback detection in seconds
 # Feature flags from environment
 WAKE_WORD_ENABLED = os.environ.get('ENABLE_WAKE_WORD', 'false').lower() == 'true'
 SPEECH_ENABLED = os.environ.get('ENABLE_SPEECH_FEATURES', 'true').lower() == 'true'
 # Wake word models to use (only if wake word is enabled)
 WAKE_WORDS = ["alexa"]  # Using 'alexa' as temporary replacement for 'gaja'
 WAKE_WORD_ALIAS = "gaja"  # What we print when wake word is detected
 # Home Assistant Configuration
 HASS_HOST = os.environ.get('HASS_HOST', 'http://homeassistant.local:8123')
 HASS_TOKEN = os.environ.get('HASS_TOKEN')
 def initialize_asr_model():
    """Initialize the ASR model with retries and timeout"""
    model_path = os.environ.get('ASR_MODEL_PATH', '/models')
    model_name = os.environ.get('ASR_MODEL', 'large-v3')
    start_time = time.time()
    for attempt in range(MAX_MODEL_LOAD_RETRIES):
        try:
            if time.time() - start_time > MODEL_DOWNLOAD_TIMEOUT:
                logger.error("Model download timeout exceeded")
                raise TimeoutError("Model download took too long")
            logger.info(f"Loading ASR model (attempt {attempt + 1}/{MAX_MODEL_LOAD_RETRIES})")
            model = WhisperModel(
                model_size_or_path=model_name,
                device="cpu",
                compute_type="int8",
                download_root=model_path,
                num_workers=1  # Reduce concurrent downloads
            )
            logger.info("ASR model loaded successfully")
            return model
        except Exception as e:
            logger.error(f"Failed to load ASR model (attempt {attempt + 1}): {e}")
            if attempt < MAX_MODEL_LOAD_RETRIES - 1:
                logger.info(f"Retrying in {MODEL_LOAD_RETRY_DELAY} seconds...")
                time.sleep(MODEL_LOAD_RETRY_DELAY)
            else:
                logger.error("Failed to load ASR model after all retries")
                raise
 # Initialize the ASR model with retries
 try:
    asr_model = initialize_asr_model()
 except Exception as e:
    logger.error(f"Critical error initializing ASR model: {e}")
    raise
 def send_command_to_hass(domain, service, entity_id):
    """Send command to Home Assistant"""
    if not HASS_TOKEN:
        logger.error("Error: HASS_TOKEN not set")
        return False
    headers = {
        "Authorization": f"Bearer {HASS_TOKEN}",
        "Content-Type": "application/json",
    }
    url = f"{HASS_HOST}/api/services/{domain}/{service}"
    data = {"entity_id": entity_id}
    try:
        response = requests.post(url, headers=headers, json=data)
        response.raise_for_status()
        logger.info(f"Command sent: {domain}.{service} for {entity_id}")
        return True
    except Exception as e:
        logger.error(f"Error sending command to Home Assistant: {e}")
        return False
 def is_speech(audio_data, threshold=NOISE_THRESHOLD):
    """Detect if audio segment contains speech based on amplitude and frequency content"""
    # Calculate RMS amplitude
    rms = np.sqrt(np.mean(np.square(audio_data)))
    # Calculate signal energy in speech frequency range (100-4000 Hz)
    fft = np.fft.fft(audio_data)
    freqs = np.fft.fftfreq(len(audio_data), 1/SAMPLE_RATE)
    speech_mask = (np.abs(freqs) >= 100) & (np.abs(freqs) <= 4000)
    speech_energy = np.sum(np.abs(fft[speech_mask])) / len(audio_data)
    # Enhanced echo detection
    # 1. Check for periodic patterns in the signal
    autocorr = np.correlate(audio_data, audio_data, mode='full')
    autocorr = autocorr[len(autocorr)//2:]  # Use only positive lags
    peaks = np.where(autocorr > ECHO_THRESHOLD * np.max(autocorr))[0]
    peak_spacing = np.diff(peaks)
    has_periodic_echo = len(peak_spacing) > 2 and np.std(peak_spacing) < 0.1 * np.mean(peak_spacing)
    # 2. Check for sudden amplitude changes
    amplitude_envelope = np.abs(audio_data)
    amplitude_changes = np.diff(amplitude_envelope)
    has_feedback_spikes = np.any(np.abs(amplitude_changes) > threshold * 2)
    # 3. Check frequency distribution
    freq_magnitudes = np.abs(fft)[:len(fft)//2]
    peak_freqs = freqs[:len(fft)//2][np.argsort(freq_magnitudes)[-3:]]
    has_feedback_freqs = np.any((peak_freqs > 2000) & (peak_freqs < 4000))
    # Combine all criteria
    is_valid_speech = (
        rms > threshold and
        speech_energy > threshold and
        not has_periodic_echo and
        not has_feedback_spikes and
        not has_feedback_freqs
    )
    return is_valid_speech
 def process_command(text):
    """Process the transcribed command and execute appropriate action"""
    text = text.lower().strip()
    # Skip if text is too short or contains numbers (likely noise)
    if len(text) < 5 or any(char.isdigit() for char in text):
        logger.debug("Text too short or contains numbers, skipping")
        return
    # Enhanced noise pattern detection
    noise_patterns = ["lei", "los", "und", "aber", "nicht mehr", "das das", "und und"]
    for pattern in noise_patterns:
        if text.count(pattern) > 1:  # More aggressive pattern filtering
            logger.debug(f"Detected noise pattern '{pattern}', skipping")
            return
    # More aggressive repetition detection
    words = text.split()
    if len(words) >= 2:
        # Check for immediate word repetitions
        for i in range(len(words)-1):
            if words[i] == words[i+1]:
                logger.debug(f"Detected immediate word repetition: '{words[i]}', skipping")
                return
        # Check for phrase repetitions
        phrases = [' '.join(words[i:i+2]) for i in range(len(words)-1)]
        phrase_counts = {}
        for phrase in phrases:
            phrase_counts[phrase] = phrase_counts.get(phrase, 0) + 1
            if phrase_counts[phrase] > MAX_REPETITIONS:
                logger.debug(f"Skipping due to excessive repetition: '{phrase}'")
                return
    # German command mappings
    commands = {
        "ausschalten": "turn_off",
        "einschalten": "turn_on",
        "an": "turn_on",
        "aus": "turn_off"
    }
    rooms = {
        "wohnzimmer": "living_room",
        "küche": "kitchen",
        "schlafzimmer": "bedroom",
        "bad": "bathroom"
    }
    # Detect room
    detected_room = None
    for german_room, english_room in rooms.items():
        if german_room in text:
            detected_room = english_room
            break
    # Detect command
    detected_command = None
    for german_cmd, english_cmd in commands.items():
        if german_cmd in text:
            detected_command = english_cmd
            break
    if detected_room and detected_command:
        # Construct entity ID (assuming light)
        entity_id = f"light.{detected_room}"
        # Send command to Home Assistant
        if send_command_to_hass("light", detected_command, entity_id):
            logger.info(f"Executed: {detected_command} for {entity_id}")
        else:
            logger.error("Failed to execute command")
    else:
        logger.debug(f"No command found in text: '{text}'")
 class AudioProcessor:
    def __init__(self):
        logger.info("Initializing AudioProcessor...")
        self.audio_buffer = queue.Queue()
        self.recording = False
        self.buffer = np.zeros(SAMPLE_RATE * BUFFER_DURATION)
        self.buffer_lock = threading.Lock()
        self.last_transcription_time = 0
        self.stream = None
        self.speech_detected = False
        self.silence_frames = 0
        self.speech_frames = 0
        # Initialize wake word detection only if enabled
        if WAKE_WORD_ENABLED:
            try:
                logger.info("Initializing wake word model...")
                self.wake_word_model = Model(vad_threshold=0.5)
                self.last_prediction = None
                logger.info("Wake word model initialized successfully")
            except Exception as e:
                logger.error(f"Failed to initialize wake word model: {e}")
                raise
        else:
            self.wake_word_model = None
            self.last_prediction = None
            logger.info("Wake word detection disabled")
    def should_transcribe(self):
        """Determine if we should transcribe based on mode and timing"""
        current_time = datetime.now().timestamp()
        if not WAKE_WORD_ENABLED:
            # Check if enough time has passed since last transcription
            time_since_last = current_time - self.last_transcription_time
            if time_since_last >= CONTINUOUS_TRANSCRIPTION_INTERVAL:
                # Only transcribe if we detect speech
                frames_per_chunk = CHUNK_SIZE
                min_speech_frames = int(MIN_SPEECH_DURATION * SAMPLE_RATE / frames_per_chunk)
                if self.speech_frames >= min_speech_frames:
                    self.last_transcription_time = current_time
                    self.speech_frames = 0  # Reset counter
                    return True
        return False
    def audio_callback(self, indata, frames, time, status):
        """Callback for audio input"""
        if status:
            logger.warning(f"Audio callback status: {status}")
        # Convert to mono if necessary
        if CHANNELS > 1:
            audio_data = np.mean(indata, axis=1)
        else:
            audio_data = indata.flatten()
        # Check for speech
        if is_speech(audio_data):
            self.speech_frames += 1
            self.silence_frames = 0
        else:
            self.silence_frames += 1
            frames_per_chunk = CHUNK_SIZE
            silence_frames_threshold = int(SILENCE_DURATION * SAMPLE_RATE / frames_per_chunk)
            if self.silence_frames >= silence_frames_threshold:
                self.speech_frames = 0
        # Update circular buffer
        with self.buffer_lock:
            self.buffer = np.roll(self.buffer, -len(audio_data))
            self.buffer[-len(audio_data):] = audio_data
        if WAKE_WORD_ENABLED:
            # Process for wake word detection
            self.last_prediction = self.wake_word_model.predict(audio_data)
            # Check if wake word detected
            for wake_word in WAKE_WORDS:
                confidence = self.last_prediction[wake_word]
                if confidence > DETECTION_THRESHOLD:
                    logger.info(
                        f"Wake word: {WAKE_WORD_ALIAS} (confidence: {confidence:.2f})"
                    )
                    self.process_audio()
                    break
        else:
            # Continuous transcription mode
            if self.should_transcribe():
                self.process_audio()
    def process_audio(self):
        """Process the current audio buffer (save and transcribe)"""
        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
        filename = f"/audio/audio_segment_{timestamp}.wav"
        # Save the audio buffer to a WAV file
        with wave.open(filename, 'wb') as wf:
            wf.setnchannels(CHANNELS)
            wf.setsampwidth(2)  # 16-bit audio
            wf.setframerate(SAMPLE_RATE)
            # Convert float32 to int16
            audio_data = (self.buffer * 32767).astype(np.int16)
            wf.writeframes(audio_data.tobytes())
        logger.info(f"Saved audio segment to {filename}")
        # Transcribe the audio with German language preference
        try:
            segments, info = asr_model.transcribe(
                filename,
                language="de",  # Set German as preferred language
                beam_size=5,
                temperature=0
            )
            # Get the full transcribed text
            transcribed_text = " ".join(segment.text for segment in segments)
            logger.info(f"Transcribed text: {transcribed_text}")
            # Process the command
            process_command(transcribed_text)
        except Exception as e:
            logger.error(f"Error during transcription or processing: {e}")
    def start(self):
        """Start audio processing"""
        try:
            logger.info("Starting audio processor...")
            # Log configuration
            logger.debug(f"Sample Rate: {SAMPLE_RATE}")
            logger.debug(f"Channels: {CHANNELS}")
            logger.debug(f"Chunk Size: {CHUNK_SIZE}")
            logger.debug(f"Buffer Duration: {BUFFER_DURATION}")
            logger.debug(f"Wake Word Enabled: {WAKE_WORD_ENABLED}")
            logger.debug(f"Speech Enabled: {SPEECH_ENABLED}")
            logger.debug(f"ASR Model: {os.environ.get('ASR_MODEL')}")
            if WAKE_WORD_ENABLED:
                logger.info("Initializing wake word detection...")
                logger.info(f"Loaded wake words: {', '.join(WAKE_WORDS)}")
            else:
                logger.info("Starting continuous transcription mode...")
                interval = CONTINUOUS_TRANSCRIPTION_INTERVAL
                logger.info(f"Will transcribe every {interval} seconds")
            try:
                logger.debug("Setting up audio input stream...")
                with sd.InputStream(
                    channels=CHANNELS,
                    samplerate=SAMPLE_RATE,
                    blocksize=CHUNK_SIZE,
                    callback=self.audio_callback
                ):
                    logger.info("Audio input stream started successfully")
                    logger.info("Listening for audio input...")
                    logger.info("Press Ctrl+C to stop")
                    while True:
                        sd.sleep(1000)  # Sleep for 1 second
            except sd.PortAudioError as e:
                logger.error(f"Error setting up audio stream: {e}")
                logger.error("Check if microphone is connected and accessible")
                raise
            except Exception as e:
                logger.error(f"Unexpected error in audio stream: {e}")
                raise
        except KeyboardInterrupt:
            logger.info("\nStopping audio processing...")
        except Exception as e:
            logger.error("Critical error in audio processing", exc_info=True)
            raise
 if __name__ == "__main__":
    try:
        logger.info("Initializing AudioProcessor...")
        processor = AudioProcessor()
        processor.start()
    except Exception as e:
        logger.error("Failed to start AudioProcessor", exc_info=True)
        raise 
--- a/docs/Gemfile
+++ b/docs/Gemfile
@@ -4,6 +4,9 @@ gem "github-pages", group: :jekyll_plugins
 gem "jekyll-theme-minimal"
 gem "jekyll-relative-links"
 gem "jekyll-seo-tag"
 gem "jekyll-remote-theme"
 gem "jekyll-github-metadata"
 gem "faraday-retry"
 # Windows and JRuby does not include zoneinfo files, so bundle the tzinfo-data gem
 # and associated library.
@@ -11,3 +14,10 @@ platforms :mingw, :x64_mingw, :mswin, :jruby do
  gem "tzinfo", ">= 1"
  gem "tzinfo-data"
 end
 # Lock `http_parser.rb` gem to `v0.6.x` on JRuby builds since newer versions of the gem
 # do not have a Java counterpart.
 gem "http_parser.rb", "~> 0.6.0", :platforms => [:jruby]
 # Add webrick for Ruby 3.0+
 gem "webrick", "~> 1.7" 
--- a/docs/README.md
+++ b/docs/README.md
@@ -1,60 +0,0 @@
 # Home Assistant MCP Documentation
 Welcome to the Home Assistant MCP (Master Control Program) documentation. This documentation provides comprehensive information about setting up, configuring, and using the Home Assistant MCP.
 ## Table of Contents
 1. [Getting Started](./getting-started.md)
   - Installation
   - Configuration
   - First Steps
 2. [API Reference](./API.md)
   - REST API Endpoints
   - Authentication
   - Error Handling
 3. [SSE (Server-Sent Events)](./SSE_API.md)
   - Event Subscriptions
   - Real-time Updates
   - Connection Management
 4. [Tools](./tools/README.md)
   - Device Control
   - Automation Management
   - Add-on Management
   - Package Management
 5. [Configuration](./configuration/README.md)
   - Environment Variables
   - Security Settings
   - Performance Tuning
 6. [Development](./development/README.md)
   - Project Structure
   - Contributing Guidelines
   - Testing
 7. [Troubleshooting](./troubleshooting.md)
   - Common Issues
   - Debugging
   - FAQ
 ## Quick Links
 - [GitHub Repository](https://github.com/yourusername/homeassistant-mcp)
 - [Issue Tracker](https://github.com/yourusername/homeassistant-mcp/issues)
 - [Change Log](./CHANGELOG.md)
 - [Security Policy](./SECURITY.md)
 ## Support
 If you need help or have questions:
 1. Check the [Troubleshooting Guide](./troubleshooting.md)
 2. Search existing [Issues](https://github.com/yourusername/homeassistant-mcp/issues)
 3. Create a new issue if your problem isn't already reported
 ## License
 This project is licensed under the MIT License - see the [LICENSE](../LICENSE) file for details. 
--- a/docs/ROADMAP.md
+++ b/docs/ROADMAP.md
@@ -1,51 +0,0 @@
 # Roadmap for MCP Server
 The following roadmap outlines our planned enhancements and future directions for the Home Assistant MCP Server. This document is a living artifact and will be updated regularly as new features are planned and developed.
 ## Near-Term Goals
 - **Advanced Automation Capabilities:**
  - Integrate more sophisticated automation rules with conditional logic and multi-step execution.
  - Introduce a visual automation builder to simplify rule creation.
 - **Enhanced Security Features:**
  - Implement multi-factor authentication for critical actions.
  - Strengthen encryption methods and data handling practices.
  - Expand monitoring and alerting for potential security breaches.
 - **Performance Optimizations:**
  - Refine the server's resource utilization to reduce latency.
  - Optimize real-time data streaming via SSE for higher throughput.
  - Introduce advanced caching mechanisms for frequently requested data.
 ## Mid-Term Goals
 - **User Interface Improvements:**
  - Develop an intuitive, web-based dashboard for easier device management and monitoring.
  - Provide real-time analytics and performance metrics in the dashboard.
 - **Expanded Integrations:**
  - Support a broader range of smart home devices and brands.
  - Integrate with additional home automation platforms and third-party services.
 - **Developer Experience Enhancements:**
  - Improve documentation and developer tooling.
  - Streamline contribution guidelines and testing setups.
 ## Long-Term Vision
 - **Ecosystem Expansion:**
  - Build a modular plugin system that allows community-driven extensions and integrations.
  - Enable seamless integration with future technologies in the smart home and AI domains.
 - **Scalability and Resilience:**
  - Architect the system to support large-scale deployments across multiple instances.
  - Incorporate advanced load balancing and failover mechanisms.
 ## How to Follow the Roadmap
 - **Community Involvement:** We encourage community feedback and contributions to help refine and prioritize our roadmap.
 - **Regular Updates:** This document is regularly updated with new goals, milestones, and completed tasks.
 - **Transparency:** Check the project's GitHub repository and issues for ongoing discussions and updates related to roadmap items.
 *This roadmap is intended to serve as a guide and may evolve based on community needs, technological advancements, and strategic priorities.* 
--- a/docs/_config.yml
+++ b/docs/_config.yml
@@ -2,9 +2,24 @@ title: Model Context Protocol (MCP)
 description: A bridge between Home Assistant and Language Learning Models
 theme: jekyll-theme-minimal
 markdown: kramdown
 # Repository settings
 repository: jango-blockchained/advanced-homeassistant-mcp
 github: [metadata]
 # Add base URL and URL settings
 baseurl: "/advanced-homeassistant-mcp" # the subpath of your site
 url: "https://jango-blockchained.github.io" # the base hostname & protocol
 # Theme settings
 logo: /assets/img/logo.png # path to logo (create this if you want a logo)
 show_downloads: true # show download buttons for your repo
 plugins:
  - jekyll-relative-links
  - jekyll-seo-tag
  - jekyll-remote-theme
  - jekyll-github-metadata
 # Enable relative links
 relative_links:
@@ -16,7 +31,39 @@ header_pages:
  - index.md
  - getting-started.md
  - api.md
  - usage.md
  - tools/tools.md
  - development/development.md
  - troubleshooting.md
  - contributing.md
  - roadmap.md
 # Collections
 collections:
  tools:
    output: true
    permalink: /:collection/:name
  development:
    output: true
    permalink: /:collection/:name
 # Default layouts
 defaults:
  - scope:
      path: ""
      type: "pages"
    values:
      layout: "default"
  - scope:
      path: "tools"
      type: "tools"
    values:
      layout: "default"
  - scope:
      path: "development"
      type: "development"
    values:
      layout: "default"
 # Exclude files from processing
 exclude:
@@ -24,3 +71,8 @@ exclude:
  - Gemfile.lock
  - node_modules
  - vendor
 # Sass settings
 sass:
  style: compressed
  sass_dir: _sass 
--- a/docs/api.md
+++ b/docs/api.md
@@ -1,4 +1,290 @@
-# API Reference
+# 🚀 Home Assistant MCP API Documentation
 ![API Version](https://img.shields.io/badge/API-v2.1-blueviolet) ![Rate Limit](https://img.shields.io/badge/Rate%20Limit-100%2Fmin-brightgreen)
 ## 🌟 Quick Start
 ```bash
 # Get API schema with caching
 curl -X GET http://localhost:3000/mcp \
  -H "Cache-Control: max-age=3600" # Cache for 1 hour
 ```
 ## 🔌 Core Functions ⚙️
 ### State Management (`/api/state`)
 ```http
 GET /api/state?cache=true  # Enable client-side caching
 POST /api/state
 ```
 **Example Request:**
 ```json
 {
  "context": "living_room",
  "state": {
    "lights": "on",
    "temperature": 22
  },
  "_cache": {  // Optional caching config
    "ttl": 300,  // 5 minutes
    "tags": ["lights", "climate"]
  }
 }
 ```
 ## ⚡ Action Endpoints
 ### Execute Action with Cache Validation
 ```http
 POST /api/action
 If-None-Match: "etag_value"  // Prevent duplicate actions
 ```
 **Batch Processing:**
 ```json
 {
  "actions": [
    { "action": "🌞 Morning Routine", "params": { "brightness": 80 } },
    { "action": "❄️ AC Control", "params": { "temp": 21 } }
  ],
  "_parallel": true  // Execute actions concurrently
 }
 ```
 ## 🔍 Query Functions
 ### Available Actions with ETag
 ```http
 GET /api/actions
 ETag: "a1b2c3d4"  // Client-side cache validation
 ```
 **Response Headers:**
 ```
 Cache-Control: public, max-age=86400  // 24-hour cache
 ETag: "a1b2c3d4"
 ```
 ## 🌐 WebSocket Events
 ```javascript
 const ws = new WebSocket('wss://ha-mcp/ws');
 ws.onmessage = ({ data }) => {
  const event = JSON.parse(data);
  if(event.type === 'STATE_UPDATE') {
    updateUI(event.payload);  // 🎨 Real-time UI sync
  }
 };
 ```
 ## 🗃️ Caching Strategies
 ### Client-Side Caching
 ```http
 GET /api/devices
 Cache-Control: max-age=300, stale-while-revalidate=60
 ```
 ### Server-Side Cache-Control
 ```typescript
 // Example middleware configuration
 app.use(
  cacheMiddleware({
    ttl: 60 * 5,  // 5 minutes
    paths: ['/api/devices', '/mcp'],
    vary: ['Authorization']  // User-specific caching
  })
 );
 ```
 ## ❌ Error Handling
 **429 Too Many Requests:**
 ```json
 {
  "error": {
    "code": "RATE_LIMITED",
    "message": "Slow down! 🐢",
    "retry_after": 30,
    "docs": "https://ha-mcp/docs/rate-limits"
  }
 }
 ```
 ## 🚦 Rate Limiting Tiers
 | Tier          | Requests/min | Features               |
 |---------------|--------------|------------------------|
 | Guest         | 10           | Basic read-only        |
 | User          | 100          | Full access            |
 | Power User    | 500          | Priority queue         |
 | Integration   | 1000         | Bulk operations        |
 ## 🛠️ Example Usage
 ### Smart Cache Refresh
 ```javascript
 async function getDevices() {
  const response = await fetch('/api/devices', {
    headers: {
      'If-None-Match': localStorage.getItem('devicesETag')
    }
  });
  if(response.status === 304) {  // Not Modified
    return JSON.parse(localStorage.devicesCache);
  }
  const data = await response.json();
  localStorage.setItem('devicesETag', response.headers.get('ETag'));
  localStorage.setItem('devicesCache', JSON.stringify(data));
  return data;
 }
 ```
 ## 🔒 Security Middleware (Enhanced)
 ### Cache-Aware Rate Limiting
 ```typescript
 app.use(
  rateLimit({
    windowMs: 15 * 60 * 1000, // 15 minutes
    max: 100, // Limit each IP to 100 requests per window
    cache: new RedisStore(), // Distributed cache
    keyGenerator: (req) => {
      return `${req.ip}-${req.headers.authorization}`;
    }
  })
 );
 ```
 ### Security Headers
 ```http
 Content-Security-Policy: default-src 'self';
 Strict-Transport-Security: max-age=31536000;
 X-Content-Type-Options: nosniff;
 Cache-Control: public, max-age=600;
 ETag: "abc123"
 ```
 ## 📘 Best Practices
 1. **Cache Wisely:** Use `ETag` and `Cache-Control` headers for state data
 2. **Batch Operations:** Combine requests using `/api/actions/batch`
 3. **WebSocket First:** Prefer real-time updates over polling
 4. **Error Recovery:** Implement exponential backoff with jitter
 5. **Cache Invalidation:** Use tags for bulk invalidation
 ```mermaid
 graph LR
 A[Client] -->|Cached Request| B{CDN}
 B -->|Cache Hit| C[Return 304]
 B -->|Cache Miss| D[Origin Server]
 D -->|Response| B
 B -->|Response| A
 ```
 > Pro Tip: Use `curl -I` to inspect cache headers! 🔍
 ## Device Control
 ### Common Entity Controls
 ```json
 {
  "tool": "control",
  "command": "turn_on",  // Options: "turn_on", "turn_off", "toggle"
  "entity_id": "light.living_room"
 }
 ```
 ### Light Control
 ```json
 {
  "tool": "control",
  "command": "turn_on",
  "entity_id": "light.living_room",
  "brightness": 128,
  "color_temp": 4000,
  "rgb_color": [255, 0, 0]
 }
 ```
 ## Add-on Management
 ### List Available Add-ons
 ```json
 {
  "tool": "addon",
  "action": "list"
 }
 ```
 ### Install Add-on
 ```json
 {
  "tool": "addon",
  "action": "install",
  "slug": "core_configurator",
  "version": "5.6.0"
 }
 ```
 ### Manage Add-on State
 ```json
 {
  "tool": "addon",
  "action": "start",  // Options: "start", "stop", "restart"
  "slug": "core_configurator"
 }
 ```
 ## Package Management
 ### List HACS Packages
 ```json
 {
  "tool": "package",
  "action": "list",
  "category": "integration"  // Options: "integration", "plugin", "theme", "python_script", "appdaemon", "netdaemon"
 }
 ```
 ### Install Package
 ```json
 {
  "tool": "package",
  "action": "install",
  "category": "integration",
  "repository": "hacs/integration",
  "version": "1.32.0"
 }
 ```
 ## Automation Management
 For automation management details and endpoints, please refer to the [Tools Documentation](tools/tools.md).
 ## Security Considerations
 - Validate and sanitize all user inputs.
 - Enforce rate limiting to prevent abuse.
 - Apply proper security headers.
 - Gracefully handle errors based on the environment.
 ## Troubleshooting
 If you experience issues with the API:
 - Verify the endpoint and request payload.
 - Check authentication tokens and required headers.
 - Consult the [Troubleshooting Guide](troubleshooting.md) for further guidance.
 ## MCP Schema Endpoint
@@ -43,119 +329,6 @@ Example response:
 Note: The `/mcp` endpoint is publicly accessible and does not require authentication, as it only provides schema information.
 ## Device Control
 ### Common Entity Controls
 ```json
 {
  "tool": "control",
  "command": "turn_on",  // or "turn_off", "toggle"
  "entity_id": "light.living_room"
 }
 ```
 ### Light Control
 ```json
 {
  "tool": "control",
  "command": "turn_on",
  "entity_id": "light.living_room",
  "brightness": 128,
  "color_temp": 4000,
  "rgb_color": [255, 0, 0]
 }
 ```
 ## Add-on Management
 ### List Available Add-ons
 ```json
 {
  "tool": "addon",
  "action": "list"
 }
 ```
 ### Install Add-on
 ```json
 {
  "tool": "addon",
  "action": "install",
  "slug": "core_configurator",
  "version": "5.6.0"
 }
 ```
 ### Manage Add-on State
 ```json
 {
  "tool": "addon",
  "action": "start",  // or "stop", "restart"
  "slug": "core_configurator"
 }
 ```
 ## Package Management
 ### List HACS Packages
 ```json
 {
  "tool": "package",
  "action": "list",
  "category": "integration"  // or "plugin", "theme", "python_script", "appdaemon", "netdaemon"
 }
 ```
 ### Install Package
 ```json
 {
  "tool": "package",
  "action": "install",
  "category": "integration",
  "repository": "hacs/integration",
  "version": "1.32.0"
 }
 ```
 ## Automation Management
 ### Create Automation
 ```json
 {
  "tool": "automation_config",
  "action": "create",
  "config": {
    "alias": "Motion Light",
    "description": "Turn on light when motion detected",
    "mode": "single",
    "trigger": [
      {
        "platform": "state",
        "entity_id": "binary_sensor.motion",
        "to": "on"
      }
    ],
    "action": [
      {
        "service": "light.turn_on",
        "target": {
          "entity_id": "light.living_room"
        }
      }
    ]
  }
 }
 ```
 ### Duplicate Automation
 ```json
 {
  "tool": "automation_config",
  "action": "duplicate",
  "automation_id": "automation.motion_light"
 }
 ```
 ## Core Functions
 ### State Management
--- a/docs/architecture.md
+++ b/docs/architecture.md
@@ -43,3 +43,26 @@ The MCP Server is designed as a high-performance, secure, and scalable bridge be
 The architecture of the MCP Server prioritizes performance, scalability, and security. By leveraging Bun's high-performance runtime, employing real-time communication through SSE, and maintaining a modular, secure design, the MCP Server provides a robust platform for integrating Home Assistant with modern LLM functionalities.
 *This document is a living document and will be updated as the system evolves.* 
 ## Key Components
 - **API Module:** Handles RESTful endpoints, authentication, and error management.
 - **SSE Module:** Provides real-time updates through Server-Sent Events.
 - **Tools Module:** Offers various utilities for device control, automation, and data processing.
 - **Security Module:** Implements token-based authentication and secure communications.
 - **Integration Module:** Bridges data between Home Assistant and external systems.
 ## Data Flow
 1. Requests enter via the API endpoints.
 2. Security middleware validates and processes requests.
 3. Core modules process data and execute the necessary business logic.
 4. Real-time notifications are managed by the SSE module.
 ## Future Enhancements
 - Expand modularity with potential microservices.
 - Enhance security with multi-factor authentication.
 - Improve scalability through distributed architectures.
 *Further diagrams and detailed breakdowns will be added in future updates.* 
--- a/docs/contributing.md
+++ b/docs/contributing.md
@@ -1,27 +1,27 @@
 # Contributing to Home Assistant MCP
-We welcome contributions from the community! Your help and feedback are essential to improving the MCP Server. Please review the following guidelines before contributing.
+We welcome community contributions to improve the MCP Server. Please review the following guidelines before contributing.
 ## How to Contribute
-1. **Fork the Repository**: Create your personal fork of the project on GitHub.
+1. **Fork the Repository:** Create your personal fork on GitHub.
-2. **Create a Feature Branch**: Use clear branch names, e.g., `feature/your-feature` or `bugfix/short-description`.
+2. **Create a Feature Branch:** Use a clear name (e.g., `feature/your-feature` or `bugfix/short-description`).
-3. **Make Changes**: Develop your feature or fix bugs. Ensure your code follows the project's coding conventions.
+3. **Make Changes:** Develop your feature or fix bugs while following our coding standards.
-4. **Write Tests**: Include tests for new features or bug fixes. We aim for high code coverage.
+4. **Write Tests:** Include tests for new features or bug fixes.
-5. **Submit a Pull Request (PR)**: Once your changes are complete, submit a PR. Our team will review your request and provide feedback.
+5. **Submit a Pull Request:** Once your changes are complete, submit a PR for review.
-6. **Address Feedback**: Make any necessary revisions based on code review feedback.
+6. **Address Feedback:** Revise your PR based on maintainers' suggestions.
 ## Code Style Guidelines
 - Follow the project's established coding style.
 - Use Bun tooling for linting and formatting:
-  - `bun run lint` for linting
+  - `bun run lint`
-  - `bun run format` for formatting
+  - `bun run format`
 ## Documentation
- Update relevant documentation alongside your code changes.
+- Update documentation alongside your code changes.
- Ensure that tests pass and coverage remains high.
+- Ensure tests pass and coverage remains high.
 ## Reporting Issues
--- a/docs/development/development.md
+++ b/docs/development/development.md
--- a/docs/getting-started.md
+++ b/docs/getting-started.md
@@ -1,122 +1,30 @@
-# Getting Started with Home Assistant MCP
+# Getting Started
-This guide will help you get started with the Home Assistant MCP (Master Control Program).
+Begin your journey with the Home Assistant MCP Server by following these steps:
-## Prerequisites
+- **API Documentation:** Read the [API Documentation](api.md) for available endpoints.
-
+- **Real-Time Updates:** Learn about [Server-Sent Events](sse-api.md) for live communication.
-Before you begin, ensure you have:
+- **Tools:** Explore available [Tools](tools/tools.md) for device control and automation.
-
+- **Configuration:** Refer to the [Configuration Guide](configuration.md) for setup and advanced settings.
 1. Node.js (v16 or higher)
 2. A running Home Assistant instance
 3. A Home Assistant Long-Lived Access Token
 ## Installation
 1. Clone the repository:
   ```bash
   git clone https://github.com/yourusername/homeassistant-mcp.git
   cd homeassistant-mcp
   ```
 2. Install dependencies:
   ```bash
   bun install
   ```
 3. Copy the example environment file:
   ```bash
   cp .env.example .env
   ```
 4. Edit the `.env` file with your configuration:
   ```env
   # Server Configuration
   PORT=3000
   BUN_ENV=development
   # Home Assistant Configuration
   HASS_HOST=http://your-hass-instance:8123
   HASS_TOKEN=your-long-lived-access-token
   # Security Configuration
   JWT_SECRET=your-secret-key
   ```
 ## Configuration
 ### Environment Variables
 - `PORT`: The port number for the MCP server (default: 3000)
 - `BUN_ENV`: The environment mode (development, production, test)
 - `HASS_HOST`: Your Home Assistant instance URL
 - `HASS_TOKEN`: Your Home Assistant Long-Lived Access Token
 - `JWT_SECRET`: Secret key for JWT token generation
 ### Development Mode
 For development, you can use:
 ```bash
 bun run dev
 ```
 This will start the server in development mode with hot reloading.
 ### Production Mode
 For production, build and start the server:
 ```bash
 bun run build
 bun start
 ```
 ## First Steps
 1. Check the server is running:
   ```bash
   curl http://localhost:3000/api/health
   ```
 2. List available devices:
   ```bash
   curl -H "Authorization: Bearer your-token" http://localhost:3000/api/tools/devices
   ```
 3. Subscribe to events:
   ```bash
   curl -H "Authorization: Bearer your-token" http://localhost:3000/api/sse/subscribe?events=state_changed
   ```
 ## Next Steps
 - Read the [API Documentation](./API.md) for available endpoints
 - Learn about [Server-Sent Events](./SSE_API.md) for real-time updates
 - Explore available [Tools](./tools/README.md) for device control
 - Check the [Configuration Guide](./configuration/README.md) for advanced settings
 ## Troubleshooting
-If you encounter issues:
+If you encounter any issues:
-
+1. Verify that your Home Assistant instance is accessible.
-1. Verify your Home Assistant instance is accessible
+2. Ensure that all required environment variables are properly set.
-2. Check your environment variables are correctly set
+3. Consult the [Troubleshooting Guide](troubleshooting.md) for additional solutions.
 3. Look for errors in the server logs
 4. Consult the [Troubleshooting Guide](./troubleshooting.md)
 ## Development
-For development and contributing:
+For contributors:
-
+1. Fork the repository.
-1. Fork the repository
+2. Create a feature branch.
-2. Create a feature branch
+3. Follow the [Development Guide](development/development.md) for contribution guidelines.
-3. Follow the [Development Guide](./development/README.md)
+4. Submit a pull request with your enhancements.
 4. Submit a pull request
 ## Support
-Need help? Check out:
+Need help?
-
+- Visit our [GitHub Issues](https://github.com/jango-blockchained/homeassistant-mcp/issues).
- [GitHub Issues](https://github.com/yourusername/homeassistant-mcp/issues)
+- Review the [Troubleshooting Guide](troubleshooting.md).
- [Troubleshooting Guide](./troubleshooting.md)
+- Check the [FAQ](troubleshooting.md#faq) for common questions. 
 - [FAQ](./troubleshooting.md#faq) 
--- a/docs/index.md
+++ b/docs/index.md
@@ -4,11 +4,34 @@ title: Home
 nav_order: 1
 ---
 # 📚 Home Assistant MCP Documentation
 Welcome to the documentation for the Home Assistant MCP (Model Context Protocol) Server.
 ## 📑 Documentation Index
 - [Getting Started Guide](getting-started.md)
 - [API Documentation](api.md)
 - [Troubleshooting](troubleshooting.md)
 - [Contributing Guide](contributing.md)
 For project overview, installation, and general information, please see our [main README](../README.md).
 ## 🔗 Quick Links
 - [GitHub Repository](https://github.com/jango-blockchained/homeassistant-mcp)
 - [Issue Tracker](https://github.com/jango-blockchained/homeassistant-mcp/issues)
 - [GitHub Discussions](https://github.com/jango-blockchained/homeassistant-mcp/discussions)
 ## 📝 License
 This project is licensed under the MIT License. See [LICENSE](../LICENSE) for details.
 # Model Context Protocol (MCP) Server
 ## Overview
-The Model Context Protocol (MCP) Server is a cutting-edge bridge between Home Assistant and Language Learning Models (LLMs), designed to revolutionize smart home automation and control.
+The Model Context Protocol (MCP) Server is a cutting-edge bridge between Home Assistant and Language Learning Models (LLMs), designed to revolutionize smart home automation and control. This documentation provides comprehensive information about setting up, configuring, and using the Home Assistant MCP.
 ## Key Features
@@ -29,18 +52,59 @@ The Model Context Protocol (MCP) Server is a cutting-edge bridge between Home As
 ## Documentation
- [Getting Started](getting-started.md) - Installation and basic setup
+### Core Documentation
- [API Reference](api.md) - Complete API documentation
+1. [Getting Started](getting-started.md)
- [SSE API](sse-api.md) - Server-Sent Events API documentation
+   - Installation and basic setup
- [Architecture](architecture.md) - System architecture and design
+   - Configuration
- [Contributing](contributing.md) - How to contribute to the project
+   - First Steps
- [Troubleshooting](troubleshooting.md) - Common issues and solutions
+
 2. [API Reference](api.md)
   - REST API Endpoints
   - Authentication
   - Error Handling
 3. [SSE API](sse-api.md)
   - Event Subscriptions
   - Real-time Updates
   - Connection Management
 ### Advanced Topics
 4. [Architecture](architecture.md)
   - System Design
   - Components
   - Data Flow
 5. [Configuration](getting-started.md#configuration)
   - Environment Variables
   - Security Settings
   - Performance Tuning
 6. [Development Guide](development/development.md)
   - Project Structure
   - Contributing Guidelines
   - Testing
 7. [Troubleshooting](troubleshooting.md)
   - Common Issues
   - Debugging
   - FAQ
 ## Quick Links
 - [GitHub Repository](https://github.com/jango-blockchained/homeassistant-mcp)
 - [Issue Tracker](https://github.com/jango-blockchained/homeassistant-mcp/issues)
 - [Contributing Guide](contributing.md)
 - [Roadmap](roadmap.md)
 ## Community and Support
- [GitHub Issues](https://github.com/jango-blockchained/homeassistant-mcp/issues) - Report bugs and request features
+If you need help or have questions:
- [GitHub Discussions](https://github.com/jango-blockchained/homeassistant-mcp/discussions) - Ask questions and share ideas
+
 1. Check the [Troubleshooting Guide](troubleshooting.md)
 2. Search existing [Issues](https://github.com/jango-blockchained/homeassistant-mcp/issues)
 3. Join our [GitHub Discussions](https://github.com/jango-blockchained/homeassistant-mcp/discussions)
 4. Create a new issue if your problem isn't already reported
 ## License
-Licensed under the MIT License. See [LICENSE](https://github.com/jango-blockchained/homeassistant-mcp/blob/main/LICENSE) for details. 
+This project is licensed under the MIT License. See [LICENSE](https://github.com/jango-blockchained/homeassistant-mcp/blob/main/LICENSE) for details. 
--- a/docs/roadmap.md
+++ b/docs/roadmap.md
@@ -0,0 +1,51 @@
 # Roadmap for MCP Server
 The following roadmap outlines our planned enhancements and future directions for the Home Assistant MCP Server. This document is a living guide that will be updated as new features are planned and developed.
 ## Near-Term Goals
 - **Advanced Automation Capabilities:**
  - Integrate sophisticated automation rules with conditional logic and multi-step execution.
  - Introduce a visual automation builder for simplified rule creation.
 - **Enhanced Security Features:**
  - Implement multi-factor authentication for critical actions.
  - Strengthen encryption methods and data handling practices.
  - Expand monitoring and alerting for potential security breaches.
 - **Performance Optimizations:**
  - Refine resource utilization to reduce latency.
  - Optimize real-time data streaming via SSE.
  - Introduce advanced caching mechanisms for frequently requested data.
 ## Mid-Term Goals
 - **User Interface Improvements:**
  - Develop an intuitive web-based dashboard for device management and monitoring.
  - Provide real-time analytics and performance metrics.
 - **Expanded Integrations:**
  - Support a broader range of smart home devices and brands.
  - Integrate with additional home automation platforms and third-party services.
 - **Developer Experience Enhancements:**
  - Improve documentation and developer tooling.
  - Streamline contribution guidelines and testing setups.
 ## Long-Term Vision
 - **Ecosystem Expansion:**
  - Build a modular plugin system for community-driven extensions and integrations.
  - Enable seamless integration with future technologies in smart home and AI domains.
 - **Scalability and Resilience:**
  - Architect the system to support large-scale deployments.
  - Incorporate advanced load balancing and failover mechanisms.
 ## How to Follow the Roadmap
 - **Community Involvement:** We welcome and encourage feedback.
 - **Regular Updates:** This document is updated regularly with new goals and milestones.
 - **Transparency:** Check our GitHub repository and issue tracker for ongoing discussions.
 *This roadmap is intended as a guide and may evolve based on community needs, technological advancements, and strategic priorities.* 
--- a/docs/testing.md
+++ b/docs/testing.md
@@ -7,23 +7,24 @@
 bun test                    # Run all tests
 bun test --watch           # Run tests in watch mode
 bun test --coverage        # Run tests with coverage
-bun test path/to/test.ts   # Run specific test file
+bun test path/to/test.ts   # Run a specific test file
 # Additional Options
 DEBUG=true bun test        # Run with debug output
-bun test --pattern "auth"  # Run tests matching pattern
+bun test --pattern "auth"  # Run tests matching a pattern
-bun test --timeout 60000   # Run with custom timeout
+bun test --timeout 60000   # Run with a custom timeout
 ```
 ## Overview
-This document describes the testing setup and practices used in the Home Assistant MCP project. The project uses Bun's test runner for unit and integration testing, with a comprehensive test suite covering security, SSE (Server-Sent Events), middleware, and other core functionalities.
+This document describes the testing setup and practices used in the Home Assistant MCP project. We use Bun's test runner for both unit and integration testing, ensuring comprehensive coverage across modules.
 ## Test Structure
 Tests are organized in two main locations:
 1. **Root Level Integration Tests** (`/__tests__/`):
 ```
 __tests__/
 ├── ai/              # AI/ML component tests
@@ -40,6 +41,7 @@ Tests are organized in two main locations:
 ```
 2. **Component Level Unit Tests** (`src/**/`):
 ```
 src/
 ├── __tests__/   # Global test setup and utilities
@@ -49,8 +51,6 @@ Tests are organized in two main locations:
 │   └── component.ts
 ```
 The root level `__tests__` directory contains integration and end-to-end tests that verify the interaction between different components of the system, while the component-level tests focus on unit testing individual modules.
 ## Test Configuration
 ### Bun Test Configuration (`bunfig.toml`)
@@ -88,26 +88,21 @@ bun run format
 ### Global Configuration
-The project uses a global test setup file (`src/__tests__/setup.ts`) that provides:
+A global test setup file (`src/__tests__/setup.ts`) provides:
 - Environment configuration
 - Mock utilities
 - Test helper functions
- Global test lifecycle hooks
+- Global lifecycle hooks
 ### Test Environment
-Tests run with the following configuration:
+- Environment variables are loaded from `.env.test`.
-
+- Console output is minimized unless `DEBUG=true`.
- Environment variables are loaded from `.env.test`
+- JWT secrets and tokens are preconfigured for testing.
- Console output is suppressed during tests (unless DEBUG=true)
+- Rate limiting and security features are initialized appropriately.
 - JWT secrets and tokens are automatically configured for testing
 - Rate limiting and other security features are properly initialized
 ## Running Tests
 To run the test suite:
 ```bash
 # Basic test run
 bun test
@@ -115,7 +110,7 @@ bun test
 # Run tests with coverage
 bun test --coverage
-# Run specific test file
+# Run a specific test file
 bun test path/to/test.test.ts
 # Run tests in watch mode
@@ -131,82 +126,61 @@ bun test --timeout 60000
 bun test --pattern "auth"
 ```
-### Test Environment Setup
+## Advanced Debugging
-1. **Prerequisites**:
+### Using Node Inspector
   - Bun >= 1.0.0
   - Node.js dependencies (see package.json)
-2. **Environment Files**:
+```bash
-   - `.env.test` - Test environment variables
+# Start tests with inspector
-   - `.env.development` - Development environment variables
+bun test --inspect
-3. **Test Data**:
+# Start tests with inspector and break on first line
-   - Mock responses in `__tests__/mock-responses/`
+bun test --inspect-brk
-   - Test fixtures in `__tests__/fixtures/`
+```
-### Continuous Integration
+### Using VS Code
-The project uses GitHub Actions for CI/CD. Tests are automatically run on:
+Create a launch configuration in `.vscode/launch.json`:
- Pull requests
+
- Pushes to main branch
+```json
- Release tags
+{
  "version": "0.2.0",
  "configurations": [
    {
      "type": "bun",
      "request": "launch",
      "name": "Debug Tests",
      "program": "${workspaceFolder}/node_modules/bun/bin/bun",
      "args": ["test", "${file}"],
      "cwd": "${workspaceFolder}",
      "env": { "DEBUG": "true" }
    }
  ]
 }
 ```
 ### Test Isolation
 To run a single test in isolation:
 ```typescript
 describe.only("specific test suite", () => {
  it.only("specific test case", () => {
    // Only this test will run
  });
 });
 ```
 ## Writing Tests
 ### Test File Naming
- Test files should be placed in a `__tests__` directory adjacent to the code being tested
+- Place test files in a `__tests__` directory adjacent to the code being tested.
- Test files should be named `*.test.ts`
+- Name files with the pattern `*.test.ts`.
- Test files should mirror the structure of the source code
+- Mirror the structure of the source code in your test organization.
-### Test Structure
+### Example Test Structure
 ```typescript
 import { describe, expect, it, beforeEach } from "bun:test";
 describe("Module Name", () => {
  beforeEach(() => {
    // Setup for each test
  });
  describe("Feature/Function Name", () => {
    it("should do something specific", () => {
      // Test implementation
    });
  });
 });
 ```
 ### Test Utilities
 The project provides several test utilities:
 ```typescript
 import { testUtils } from "../__tests__/setup";
 // Available utilities:
 - mockWebSocket()      // Mock WebSocket for SSE tests
 - mockResponse()       // Mock HTTP response for API tests
 - mockRequest()        // Mock HTTP request for API tests
 - createTestClient()   // Create test SSE client
 - createTestEvent()    // Create test event
 - createTestEntity()   // Create test Home Assistant entity
 - wait()              // Helper to wait for async operations
 ```
 ## Testing Patterns
 ### Security Testing
 Security tests cover:
 - Token validation and encryption
 - Rate limiting
 - Request validation
 - Input sanitization
 - Error handling
 Example:
 ```typescript
 describe("Security Features", () => {
  it("should validate tokens correctly", () => {
@@ -218,83 +192,17 @@ describe("Security Features", () => {
 });
 ```
-### SSE Testing
+## Coverage
-SSE tests cover:
+The project maintains strict coverage:
- Client authentication
+- Overall coverage: at least 80%
- Message broadcasting
+- Critical paths: 90%+
- Rate limiting
+- New features: ≥85% coverage
 - Subscription management
 - Client cleanup
-Example:
+Generate a coverage report with:
 ```typescript
 describe("SSE Features", () => {
  it("should authenticate valid clients", () => {
    const client = createTestClient("test-client");
    const result = sseManager.addClient(client, validToken);
    expect(result?.authenticated).toBe(true);
  });
 });
 ```
-### Middleware Testing
+```bash
-
+bun test --coverage
 Middleware tests cover:
 - Request validation
 - Input sanitization
 - Error handling
 - Response formatting
 Example:
 ```typescript
 describe("Middleware", () => {
  it("should sanitize HTML in request body", () => {
    const req = mockRequest({
      body: { text: '<script>alert("xss")</script>' }
    });
    sanitizeInput(req, res, next);
    expect(req.body.text).toBe("");
  });
 });
 ```
 ### Integration Testing
 Integration tests in the root `__tests__` directory cover:
 - **AI/ML Components**: Testing machine learning model integrations and predictions
 - **API Integration**: End-to-end API route testing
 - **Context Management**: Testing context persistence and state management
 - **Home Assistant Integration**: Testing communication with Home Assistant
 - **Schema Validation**: Testing data validation across the application
 - **Security Integration**: Testing security features in a full system context
 - **WebSocket Communication**: Testing real-time communication
 - **Server Integration**: Testing the complete server setup and configuration
 Example integration test:
 ```typescript
 describe("API Integration", () => {
  it("should handle a complete authentication flow", async () => {
    // Setup test client
    const client = await createTestClient();
    // Test registration
    const regResponse = await client.register(testUser);
    expect(regResponse.status).toBe(201);
    // Test authentication
    const authResponse = await client.authenticate(testCredentials);
    expect(authResponse.status).toBe(200);
    expect(authResponse.body.token).toBeDefined();
    // Test protected endpoint access
    const protectedResponse = await client.get("/api/protected", {
      headers: { Authorization: `Bearer ${authResponse.body.token}` }
    });
    expect(protectedResponse.status).toBe(200);
  });
 });
 ```
 ## Security Middleware Testing
--- a/docs/tools/README.md
+++ b/docs/tools/README.md
--- a/docs/troubleshooting.md
+++ b/docs/troubleshooting.md
@@ -1,144 +1,135 @@
 # Troubleshooting Guide
-This guide helps you diagnose and fix common issues with the Home Assistant MCP.
+This guide provides solutions to common issues encountered with the Home Assistant MCP Server.
 ## Common Issues
-### Connection Issues
+- **Server Not Starting:**
  - Verify that all required environment variables are correctly set.
  - Check for port conflicts or missing dependencies.
  - Review the server logs for error details.
-#### Cannot Connect to Home Assistant
+- **Connection Problems:**
  - Ensure your Home Assistant instance is reachable.
  - Confirm that the authentication token is valid.
  - Check network configurations and firewalls.
 ## Tool Issues
 ### Tool Not Found
 **Symptoms:**
- Connection timeout errors
+- "Tool not found" errors or 404 responses.
 - "Failed to connect to Home Assistant" messages
 - 401 Unauthorized errors
 **Solutions:**
-1. Verify Home Assistant is running
+- Double-check the tool name spelling.
-2. Check HASS_HOST environment variable
+- Verify that the tool is correctly registered.
-3. Validate HASS_TOKEN is correct
+- Review tool imports and documentation.
 4. Ensure network connectivity
 5. Check firewall settings
-#### SSE Connection Drops
+### Tool Execution Failures
 **Symptoms:**
- Frequent disconnections
+- Execution errors or timeouts.
 - Missing events
 - Connection reset errors
 **Solutions:**
-1. Check network stability
+- Validate input parameters.
-2. Increase connection timeout
+- Check and review error logs.
-3. Implement reconnection logic
+- Debug the tool implementation.
-4. Monitor server resources
+- Ensure proper permissions in Home Assistant.
-### Authentication Issues
+## Debugging Steps
 #### Invalid Token
 **Symptoms:**
 - 401 Unauthorized responses
 - "Invalid token" messages
 - Authentication failures
 **Solutions:**
 1. Generate new Long-Lived Access Token
 2. Check token expiration
 3. Verify token format
 4. Update environment variables
 #### Rate Limiting
 **Symptoms:**
 - 429 Too Many Requests
 - "Rate limit exceeded" messages
 **Solutions:**
 1. Implement request throttling
 2. Adjust rate limit settings
 3. Cache responses
 4. Optimize request patterns
 ### Tool Issues
 #### Tool Not Found
 **Symptoms:**
 - "Tool not found" errors
 - 404 Not Found responses
 **Solutions:**
 1. Check tool name spelling
 2. Verify tool registration
 3. Update tool imports
 4. Check tool availability
 #### Tool Execution Fails
 **Symptoms:**
 - Tool execution errors
 - Unexpected responses
 - Timeout issues
 **Solutions:**
 1. Validate input parameters
 2. Check error logs
 3. Debug tool implementation
 4. Verify Home Assistant permissions
 ## Debugging
 ### Server Logs
-1. Enable debug logging:
+1. Enable debug logging by setting:
   ```env
   LOG_LEVEL=debug
   ```
 2. Check logs:
   ```bash
   npm run logs
   ```
-
+3. Filter errors:
 3. Filter logs:
   ```bash
   npm run logs | grep "error"
   ```
 ### Network Debugging
-1. Check API endpoints:
+1. Test API endpoints:
   ```bash
   curl -v http://localhost:3000/api/health
   ```
 2. Monitor SSE connections:
   ```bash
   curl -N http://localhost:3000/api/sse/stats
   ```
-
+3. Test WebSocket connectivity:
 3. Test WebSocket:
   ```bash
   wscat -c ws://localhost:3000
   ```
 ### Performance Issues
-1. Monitor memory usage:
+- Monitor memory usage with:
  ```bash
  npm run stats
  ```
-2. Check response times:
+## Security Middleware Troubleshooting
   ```bash
   curl -w "%{time_total}\n" -o /dev/null -s http://localhost:3000/api/health
   ```
-3. Profile code:
+### Rate Limiting Problems
-   ```bash
+
-   npm run profile
+**Symptoms:** Receiving 429 (Too Many Requests) errors.
-   ```
+
 **Solutions:**
 - Adjust and fine-tune rate limit settings.
 - Consider different limits for critical versus non-critical endpoints.
 ### Request Validation Failures
 **Symptoms:** 400 or 415 errors on valid requests.
 **Solutions:**
 - Verify that the `Content-Type` header is set correctly.
 - Inspect request payload size and format.
 ### Input Sanitization Issues
 **Symptoms:** Unexpected data transformation or loss.
 **Solutions:**
 - Test sanitization with various input types.
 - Implement custom sanitization for complex data if needed.
 ### Security Header Configuration
 **Symptoms:** Missing or improper security headers.
 **Solutions:**
 - Review and update security header configurations (e.g., Helmet settings).
 - Ensure environment-specific header settings are in place.
 ### Error Handling and Logging
 **Symptoms:** Inconsistent error responses.
 **Solutions:**
 - Enhance logging for detailed error tracking.
 - Adjust error handlers for production and development differences.
 ## Additional Resources
 - [OWASP Security Guidelines](https://owasp.org/www-project-top-ten/)
 - [Helmet.js Documentation](https://helmetjs.github.io/)
 - [JWT Security Best Practices](https://jwt.io/introduction)
 ## Getting Help
 If issues persist:
 1. Review detailed logs.
 2. Verify your configuration and environment.
 3. Consult the GitHub issue tracker or community forums.
 ## FAQ
@@ -167,7 +158,7 @@ A: Adjust SSE_MAX_CLIENTS in configuration or clean up stale connections.
 1. Documentation
   - [API Reference](./API.md)
   - [Configuration Guide](./configuration/README.md)
-   - [Development Guide](./development/README.md)
+   - [Development Guide](./development/development.md)
 2. Community
   - GitHub Issues
--- a/docs/usage.md
+++ b/docs/usage.md
@@ -1,5 +1,34 @@
 # Usage Guide
 This guide explains how to use the Home Assistant MCP Server for smart home device management and integration with language learning systems.
 ## Basic Usage
 1. **Starting the Server:**
   - For development: run `npm run dev`.
   - For production: run `npm run build` followed by `npm start`.
 2. **Accessing the Web Interface:**
   - Open [http://localhost:3000](http://localhost:3000) in your browser.
 3. **Real-Time Updates:**
   - Connect to the SSE endpoint at `/subscribe_events?token=YOUR_TOKEN&domain=light` to receive live updates.
 ## Advanced Features
 1. **API Interactions:**
   - Use the REST API for operations such as device control, automation, and add-on management.
   - See [API Documentation](api.md) for details.
 2. **Tool Integrations:**
   - Multiple tools are available (see [Tools Documentation](tools/tools.md)), for tasks like automation management and notifications.
 3. **Security Settings:**
   - Configure token-based authentication and environment variables as per the [Configuration Guide](getting-started/configuration.md).
 4. **Customization and Extensions:**
   - Extend server functionality by developing new tools as outlined in the [Development Guide](development/development.md).
 ## Troubleshooting
 If you experience issues, review the [Troubleshooting Guide](troubleshooting.md). 
--- a/examples/README.md
+++ b/examples/README.md
@@ -0,0 +1,91 @@
 # Speech-to-Text Examples
 This directory contains examples demonstrating how to use the speech-to-text integration with wake word detection.
 ## Prerequisites
 1. Make sure you have Docker installed and running
 2. Build and start the services:
   ```bash
   docker-compose up -d
   ```
 ## Running the Example
 1. Install dependencies:
   ```bash
   npm install
   ```
 2. Run the example:
   ```bash
   npm run example:speech
   ```
   Or using `ts-node` directly:
   ```bash
   npx ts-node examples/speech-to-text-example.ts
   ```
 ## Features Demonstrated
 1. **Wake Word Detection**
   - Listens for wake words: "hey jarvis", "ok google", "alexa"
   - Automatically saves audio when wake word is detected
   - Transcribes the detected speech
 2. **Manual Transcription**
   - Example of how to transcribe audio files manually
   - Supports different models and configurations
 3. **Event Handling**
   - Wake word detection events
   - Transcription results
   - Progress updates
   - Error handling
 ## Example Output
 When a wake word is detected, you'll see output like this:
 ```
 🎤 Wake word detected!
  Timestamp: 20240203_123456
  Audio file: /path/to/audio/wake_word_20240203_123456.wav
  Metadata file: /path/to/audio/wake_word_20240203_123456.wav.json
 📝 Transcription result:
  Full text: This is what was said after the wake word.
  Segments:
    1. [0.00s - 1.52s] (95.5% confidence)
       "This is what was said"
    2. [1.52s - 2.34s] (98.2% confidence)
       "after the wake word."
 ```
 ## Customization
 You can customize the behavior by:
 1. Changing the wake word models in `docker/speech/Dockerfile`
 2. Modifying transcription options in the example file
 3. Adding your own event handlers
 4. Implementing different audio processing logic
 ## Troubleshooting
 1. **Docker Issues**
   - Make sure Docker is running
   - Check container logs: `docker-compose logs fast-whisper`
   - Verify container is up: `docker ps`
 2. **Audio Issues**
   - Check audio device permissions
   - Verify audio file format (WAV files recommended)
   - Check audio file permissions
 3. **Performance Issues**
   - Try using a smaller model (tiny.en or base.en)
   - Adjust beam size and patience parameters
   - Consider using GPU acceleration if available 
--- a/examples/speech-to-text-example.ts
+++ b/examples/speech-to-text-example.ts
@@ -0,0 +1,91 @@
 import { SpeechToText, TranscriptionResult, WakeWordEvent } from '../src/speech/speechToText';
 import path from 'path';
 async function main() {
    // Initialize the speech-to-text service
    const speech = new SpeechToText('fast-whisper');
    // Check if the service is available
    const isHealthy = await speech.checkHealth();
    if (!isHealthy) {
        console.error('Speech service is not available. Make sure Docker is running and the fast-whisper container is up.');
        console.error('Run: docker-compose up -d');
        process.exit(1);
    }
    console.log('Speech service is ready!');
    console.log('Listening for wake words: "hey jarvis", "ok google", "alexa"');
    console.log('Press Ctrl+C to exit');
    // Set up event handlers
    speech.on('wake_word', (event: WakeWordEvent) => {
        console.log('\n🎤 Wake word detected!');
        console.log('  Timestamp:', event.timestamp);
        console.log('  Audio file:', event.audioFile);
        console.log('  Metadata file:', event.metadataFile);
    });
    speech.on('transcription', (event: { audioFile: string; result: TranscriptionResult }) => {
        console.log('\n📝 Transcription result:');
        console.log('  Full text:', event.result.text);
        console.log('\n  Segments:');
        event.result.segments.forEach((segment, index) => {
            console.log(`    ${index + 1}. [${segment.start.toFixed(2)}s - ${segment.end.toFixed(2)}s] (${(segment.confidence * 100).toFixed(1)}% confidence)`);
            console.log(`       "${segment.text}"`);
        });
    });
    speech.on('progress', (event: { type: string; data: string }) => {
        if (event.type === 'stderr' && !event.data.includes('Loading model')) {
            console.error('❌ Error:', event.data);
        }
    });
    speech.on('error', (error: Error) => {
        console.error('❌ Error:', error.message);
    });
    // Example of manual transcription
    async function transcribeFile(filepath: string) {
        try {
            console.log(`\n🎯 Manually transcribing: ${filepath}`);
            const result = await speech.transcribeAudio(filepath, {
                model: 'base.en',  // You can change this to tiny.en, small.en, medium.en, or large-v2
                language: 'en',
                temperature: 0,
                beamSize: 5
            });
            console.log('\n📝 Transcription result:');
            console.log('  Text:', result.text);
        } catch (error) {
            console.error('❌ Transcription failed:', error instanceof Error ? error.message : error);
        }
    }
    // Create audio directory if it doesn't exist
    const audioDir = path.join(__dirname, '..', 'audio');
    if (!require('fs').existsSync(audioDir)) {
        require('fs').mkdirSync(audioDir, { recursive: true });
    }
    // Start wake word detection
    speech.startWakeWordDetection(audioDir);
    // Example: You can also manually transcribe files
    // Uncomment the following line and replace with your audio file:
    // await transcribeFile('/path/to/your/audio.wav');
    // Keep the process running
    process.on('SIGINT', () => {
        console.log('\nStopping speech service...');
        speech.stopWakeWordDetection();
        process.exit(0);
    });
 }
 // Run the example
 main().catch(error => {
    console.error('Fatal error:', error);
    process.exit(1);
 }); 
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -1,4 +1,4 @@
-site_name: Project Documentation
+site_name: Home Assistant Model Context Protocol (MCP)
 site_url: https://yourusername.github.io/your-repo-name/
 repo_url: https://github.com/yourusername/your-repo-name
--- a/package.json
+++ b/package.json
@@ -1,7 +1,7 @@
 {
  "name": "homeassistant-mcp",
  "version": "1.0.0",
-  "description": "Home Assistant Master Control Program",
+  "description": "Home Assistant Model Context Protocol",
  "main": "dist/index.js",
  "type": "module",
  "scripts": {
@@ -21,7 +21,7 @@
    "profile": "bun --inspect src/index.ts",
    "clean": "rm -rf dist .bun coverage",
    "typecheck": "bun x tsc --noEmit",
-    "preinstall": "bun install --frozen-lockfile"
+    "example:speech": "bun run examples/speech-to-text-example.ts"
  },
  "dependencies": {
    "@elysiajs/cors": "^1.2.0",
@@ -37,6 +37,8 @@
    "node-fetch": "^3.3.2",
    "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"
  },
--- a/src/config/app.config.ts
+++ b/src/config/app.config.ts
@@ -24,7 +24,7 @@ config({ path: resolve(process.cwd(), envFile) });
 */
 export const AppConfigSchema = z.object({
  /** Server Configuration */
-  PORT: z.number().default(4000),
+  PORT: z.coerce.number().default(4000),
  NODE_ENV: z
    .enum(["development", "production", "test"])
    .default("development"),
@@ -33,6 +33,21 @@ export const AppConfigSchema = z.object({
  HASS_HOST: z.string().default("http://192.168.178.63:8123"),
  HASS_TOKEN: z.string().optional(),
  /** Speech Features Configuration */
  SPEECH: z.object({
    ENABLED: z.boolean().default(false),
    WAKE_WORD_ENABLED: z.boolean().default(false),
    SPEECH_TO_TEXT_ENABLED: z.boolean().default(false),
    WHISPER_MODEL_PATH: z.string().default("/models"),
    WHISPER_MODEL_TYPE: z.string().default("base"),
  }).default({
    ENABLED: false,
    WAKE_WORD_ENABLED: false,
    SPEECH_TO_TEXT_ENABLED: false,
    WHISPER_MODEL_PATH: "/models",
    WHISPER_MODEL_TYPE: "base",
  }),
  /** Security Configuration */
  JWT_SECRET: z.string().default("your-secret-key"),
  RATE_LIMIT: z.object({
@@ -113,4 +128,11 @@ export const APP_CONFIG = AppConfigSchema.parse({
    LOG_REQUESTS: process.env.LOG_REQUESTS === "true",
  },
  VERSION: "0.1.0",
  SPEECH: {
    ENABLED: process.env.ENABLE_SPEECH_FEATURES === "true",
    WAKE_WORD_ENABLED: process.env.ENABLE_WAKE_WORD === "true",
    SPEECH_TO_TEXT_ENABLED: process.env.ENABLE_SPEECH_TO_TEXT === "true",
    WHISPER_MODEL_PATH: process.env.WHISPER_MODEL_PATH || "/models",
    WHISPER_MODEL_TYPE: process.env.WHISPER_MODEL_TYPE || "base",
  },
 });
--- a/src/index.ts
+++ b/src/index.ts
@@ -25,6 +25,8 @@ import {
  climateCommands,
  type Command,
 } from "./commands.js";
 import { speechService } from "./speech/index.js";
 import { APP_CONFIG } from "./config/app.config.js";
 // Load environment variables based on NODE_ENV
 const envFile =
@@ -129,8 +131,19 @@ app.get("/health", () => ({
  status: "ok",
  timestamp: new Date().toISOString(),
  version: "0.1.0",
  speech_enabled: APP_CONFIG.SPEECH.ENABLED,
  wake_word_enabled: APP_CONFIG.SPEECH.WAKE_WORD_ENABLED,
  speech_to_text_enabled: APP_CONFIG.SPEECH.SPEECH_TO_TEXT_ENABLED,
 }));
 // Initialize speech service if enabled
 if (APP_CONFIG.SPEECH.ENABLED) {
  console.log("Initializing speech service...");
  speechService.initialize().catch((error) => {
    console.error("Failed to initialize speech service:", error);
  });
 }
 // Create API endpoints for each tool
 tools.forEach((tool) => {
  app.post(`/api/tools/${tool.name}`, async ({ body }: { body: Record<string, unknown> }) => {
@@ -145,7 +158,12 @@ app.listen(PORT, () => {
 });
 // Handle server shutdown
-process.on("SIGTERM", () => {
+process.on("SIGTERM", async () => {
  console.log("Received SIGTERM. Shutting down gracefully...");
  if (APP_CONFIG.SPEECH.ENABLED) {
    await speechService.shutdown().catch((error) => {
      console.error("Error shutting down speech service:", error);
    });
  }
  process.exit(0);
 });
--- a/src/speech/tests/fixtures/test.wav
+++ b/src/speech/tests/fixtures/test.wav
--- a/src/speech/tests/speechToText.test.ts
+++ b/src/speech/tests/speechToText.test.ts
@@ -0,0 +1,116 @@
 import { SpeechToText, WakeWordEvent, TranscriptionError } from '../speechToText';
 import fs from 'fs';
 import path from 'path';
 describe('SpeechToText', () => {
    let speechToText: SpeechToText;
    const testAudioDir = path.join(__dirname, 'test_audio');
    beforeEach(() => {
        speechToText = new SpeechToText('fast-whisper');
        // Create test audio directory if it doesn't exist
        if (!fs.existsSync(testAudioDir)) {
            fs.mkdirSync(testAudioDir, { recursive: true });
        }
    });
    afterEach(() => {
        speechToText.stopWakeWordDetection();
        // Clean up test files
        if (fs.existsSync(testAudioDir)) {
            fs.rmSync(testAudioDir, { recursive: true, force: true });
        }
    });
    describe('checkHealth', () => {
        it('should handle Docker not being available', async () => {
            const isHealthy = await speechToText.checkHealth();
            expect(isHealthy).toBeDefined();
            expect(isHealthy).toBe(false);
        });
    });
    describe('wake word detection', () => {
        it('should detect new audio files and emit wake word events', (done) => {
            const testFile = path.join(testAudioDir, 'wake_word_test_123456.wav');
            const testMetadata = `${testFile}.json`;
            speechToText.startWakeWordDetection(testAudioDir);
            speechToText.on('wake_word', (event: WakeWordEvent) => {
                expect(event).toBeDefined();
                expect(event.audioFile).toBe(testFile);
                expect(event.metadataFile).toBe(testMetadata);
                expect(event.timestamp).toBe('123456');
                done();
            });
            // Create a test audio file to trigger the event
            fs.writeFileSync(testFile, 'test audio content');
        }, 1000);
        it('should handle transcription errors when Docker is not available', (done) => {
            const testFile = path.join(testAudioDir, 'wake_word_test_123456.wav');
            let errorEmitted = false;
            let wakeWordEmitted = false;
            const checkDone = () => {
                if (errorEmitted && wakeWordEmitted) {
                    done();
                }
            };
            speechToText.on('error', (error) => {
                expect(error).toBeDefined();
                expect(error).toBeInstanceOf(TranscriptionError);
                expect(error.message).toContain('Failed to start Docker process');
                errorEmitted = true;
                checkDone();
            });
            speechToText.on('wake_word', () => {
                wakeWordEmitted = true;
                checkDone();
            });
            speechToText.startWakeWordDetection(testAudioDir);
            // Create a test audio file to trigger the event
            fs.writeFileSync(testFile, 'test audio content');
        }, 1000);
    });
    describe('transcribeAudio', () => {
        it('should handle Docker not being available for transcription', async () => {
            await expect(
                speechToText.transcribeAudio('/audio/test.wav')
            ).rejects.toThrow(TranscriptionError);
        });
        it('should emit progress events on error', (done) => {
            let progressEmitted = false;
            let errorThrown = false;
            const checkDone = () => {
                if (progressEmitted && errorThrown) {
                    done();
                }
            };
            speechToText.on('progress', (event: { type: string; data: string }) => {
                expect(event.type).toBe('stderr');
                expect(event.data).toBe('Failed to start Docker process');
                progressEmitted = true;
                checkDone();
            });
            speechToText.transcribeAudio('/audio/test.wav')
                .catch((error) => {
                    expect(error).toBeInstanceOf(TranscriptionError);
                    errorThrown = true;
                    checkDone();
                });
        }, 1000);
    });
 }); 
--- a/src/speech/index.ts
+++ b/src/speech/index.ts
@@ -0,0 +1,110 @@
 import { APP_CONFIG } from "../config/app.config.js";
 import { logger } from "../utils/logger.js";
 import type { IWakeWordDetector, ISpeechToText } from "./types.js";
 class SpeechService {
    private static instance: SpeechService | null = null;
    private isInitialized: boolean = false;
    private wakeWordDetector: IWakeWordDetector | null = null;
    private speechToText: ISpeechToText | null = null;
    private constructor() { }
    public static getInstance(): SpeechService {
        if (!SpeechService.instance) {
            SpeechService.instance = new SpeechService();
        }
        return SpeechService.instance;
    }
    public async initialize(): Promise<void> {
        if (this.isInitialized) {
            return;
        }
        if (!APP_CONFIG.SPEECH.ENABLED) {
            logger.info("Speech features are disabled. Skipping initialization.");
            return;
        }
        try {
            // Initialize components based on configuration
            if (APP_CONFIG.SPEECH.WAKE_WORD_ENABLED) {
                logger.info("Initializing wake word detection...");
                // Dynamic import to avoid loading the module if not needed
                const { WakeWordDetector } = await import("./wakeWordDetector.js");
                this.wakeWordDetector = new WakeWordDetector() as IWakeWordDetector;
                await this.wakeWordDetector.initialize();
            }
            if (APP_CONFIG.SPEECH.SPEECH_TO_TEXT_ENABLED) {
                logger.info("Initializing speech-to-text...");
                // Dynamic import to avoid loading the module if not needed
                const { SpeechToText } = await import("./speechToText.js");
                this.speechToText = new SpeechToText({
                    modelPath: APP_CONFIG.SPEECH.WHISPER_MODEL_PATH,
                    modelType: APP_CONFIG.SPEECH.WHISPER_MODEL_TYPE,
                }) as ISpeechToText;
                await this.speechToText.initialize();
            }
            this.isInitialized = true;
            logger.info("Speech service initialized successfully");
        } catch (error) {
            logger.error("Failed to initialize speech service:", error);
            throw error;
        }
    }
    public async shutdown(): Promise<void> {
        if (!this.isInitialized) {
            return;
        }
        try {
            if (this.wakeWordDetector) {
                await this.wakeWordDetector.shutdown();
                this.wakeWordDetector = null;
            }
            if (this.speechToText) {
                await this.speechToText.shutdown();
                this.speechToText = null;
            }
            this.isInitialized = false;
            logger.info("Speech service shut down successfully");
        } catch (error) {
            logger.error("Error during speech service shutdown:", error);
            throw error;
        }
    }
    public isEnabled(): boolean {
        return APP_CONFIG.SPEECH.ENABLED;
    }
    public isWakeWordEnabled(): boolean {
        return APP_CONFIG.SPEECH.WAKE_WORD_ENABLED;
    }
    public isSpeechToTextEnabled(): boolean {
        return APP_CONFIG.SPEECH.SPEECH_TO_TEXT_ENABLED;
    }
    public getWakeWordDetector(): IWakeWordDetector {
        if (!this.isInitialized || !this.wakeWordDetector) {
            throw new Error("Wake word detector is not initialized");
        }
        return this.wakeWordDetector;
    }
    public getSpeechToText(): ISpeechToText {
        if (!this.isInitialized || !this.speechToText) {
            throw new Error("Speech-to-text is not initialized");
        }
        return this.speechToText;
    }
 }
 export const speechService = SpeechService.getInstance(); 
--- a/src/speech/speechToText.ts
+++ b/src/speech/speechToText.ts
@@ -0,0 +1,247 @@
 import { spawn } from 'child_process';
 import { EventEmitter } from 'events';
 import { watch } from 'fs';
 import path from 'path';
 import { ISpeechToText, SpeechToTextConfig } from "./types.js";
 export interface TranscriptionOptions {
    model?: 'tiny.en' | 'base.en' | 'small.en' | 'medium.en' | 'large-v2';
    language?: string;
    temperature?: number;
    beamSize?: number;
    patience?: number;
    device?: 'cpu' | 'cuda';
 }
 export interface TranscriptionResult {
    text: string;
    segments: Array<{
        text: string;
        start: number;
        end: number;
        confidence: number;
    }>;
 }
 export interface WakeWordEvent {
    timestamp: string;
    audioFile: string;
    metadataFile: string;
 }
 export class TranscriptionError extends Error {
    constructor(message: string) {
        super(message);
        this.name = 'TranscriptionError';
    }
 }
 export class SpeechToText extends EventEmitter implements ISpeechToText {
    private containerName: string;
    private audioWatcher?: ReturnType<typeof watch>;
    private modelPath: string;
    private modelType: string;
    private isInitialized: boolean = false;
    constructor(config: SpeechToTextConfig) {
        super();
        this.containerName = config.containerName || 'fast-whisper';
        this.modelPath = config.modelPath;
        this.modelType = config.modelType;
    }
    public async initialize(): Promise<void> {
        if (this.isInitialized) {
            return;
        }
        try {
            // Initialization logic will be implemented here
            await this.setupContainer();
            this.isInitialized = true;
            this.emit('ready');
        } catch (error) {
            this.emit('error', error);
            throw error;
        }
    }
    public async shutdown(): Promise<void> {
        if (!this.isInitialized) {
            return;
        }
        try {
            // Cleanup logic will be implemented here
            await this.cleanupContainer();
            this.isInitialized = false;
            this.emit('shutdown');
        } catch (error) {
            this.emit('error', error);
            throw error;
        }
    }
    public async transcribe(audioData: Buffer): Promise<string> {
        if (!this.isInitialized) {
            throw new Error("Speech-to-text service is not initialized");
        }
        try {
            // Transcription logic will be implemented here
            this.emit('transcribing');
            const result = await this.processAudio(audioData);
            this.emit('transcribed', result);
            return result;
        } catch (error) {
            this.emit('error', error);
            throw error;
        }
    }
    private async setupContainer(): Promise<void> {
        // Container setup logic will be implemented here
        await new Promise(resolve => setTimeout(resolve, 100)); // Placeholder
    }
    private async cleanupContainer(): Promise<void> {
        // Container cleanup logic will be implemented here
        await new Promise(resolve => setTimeout(resolve, 100)); // Placeholder
    }
    private async processAudio(audioData: Buffer): Promise<string> {
        // Audio processing logic will be implemented here
        await new Promise(resolve => setTimeout(resolve, 100)); // Placeholder
        return "Transcription placeholder";
    }
    startWakeWordDetection(audioDir: string = './audio'): void {
        // Watch for new audio files from wake word detection
        this.audioWatcher = watch(audioDir, (eventType, filename) => {
            if (eventType === 'rename' && filename && filename.startsWith('wake_word_') && filename.endsWith('.wav')) {
                const audioFile = path.join(audioDir, filename);
                const metadataFile = `${audioFile}.json`;
                const parts = filename.split('_');
                const timestamp = parts[parts.length - 1].split('.')[0];
                // Emit wake word event
                this.emit('wake_word', {
                    timestamp,
                    audioFile,
                    metadataFile
                } as WakeWordEvent);
                // Automatically transcribe the wake word audio
                this.transcribeAudio(audioFile)
                    .then(result => {
                        this.emit('transcription', { audioFile, result });
                    })
                    .catch(error => {
                        this.emit('error', error);
                    });
            }
        });
    }
    stopWakeWordDetection(): void {
        if (this.audioWatcher) {
            this.audioWatcher.close();
            this.audioWatcher = undefined;
        }
    }
    async transcribeAudio(
        audioFilePath: string,
        options: TranscriptionOptions = {}
    ): Promise<TranscriptionResult> {
        const {
            model = 'base.en',
            language = 'en',
            temperature = 0,
            beamSize = 5,
            patience = 1,
            device = 'cpu'
        } = options;
        return new Promise((resolve, reject) => {
            const args = [
                'exec',
                this.containerName,
                'fast-whisper',
                '--model', model,
                '--language', language,
                '--temperature', temperature.toString(),
                '--beam-size', beamSize.toString(),
                '--patience', patience.toString(),
                '--device', device,
                '--output-json',
                audioFilePath
            ];
            let process;
            try {
                process = spawn('docker', args);
            } catch (error) {
                this.emit('progress', { type: 'stderr', data: 'Failed to start Docker process' });
                reject(new TranscriptionError('Failed to start Docker process'));
                return;
            }
            let stdout = '';
            let stderr = '';
            process.stdout?.on('data', (data: Buffer) => {
                stdout += data.toString();
                this.emit('progress', { type: 'stdout', data: data.toString() });
            });
            process.stderr?.on('data', (data: Buffer) => {
                stderr += data.toString();
                this.emit('progress', { type: 'stderr', data: data.toString() });
            });
            process.on('error', (error: Error) => {
                this.emit('progress', { type: 'stderr', data: error.message });
                reject(new TranscriptionError(`Failed to execute Docker command: ${error.message}`));
            });
            process.on('close', (code: number) => {
                if (code !== 0) {
                    reject(new TranscriptionError(`Transcription failed: ${stderr}`));
                    return;
                }
                try {
                    const result = JSON.parse(stdout) as TranscriptionResult;
                    resolve(result);
                } catch (error: unknown) {
                    if (error instanceof Error) {
                        reject(new TranscriptionError(`Failed to parse transcription result: ${error.message}`));
                    } else {
                        reject(new TranscriptionError('Failed to parse transcription result: Unknown error'));
                    }
                }
            });
        });
    }
    async checkHealth(): Promise<boolean> {
        try {
            const process = spawn('docker', ['ps', '--filter', `name=${this.containerName}`, '--format', '{{.Status}}']);
            return new Promise((resolve) => {
                let output = '';
                process.stdout?.on('data', (data: Buffer) => {
                    output += data.toString();
                });
                process.on('error', () => {
                    resolve(false);
                });
                process.on('close', (code: number) => {
                    resolve(code === 0 && output.toLowerCase().includes('up'));
                });
            });
        } catch (error) {
            return false;
        }
    }
 } 
--- a/src/speech/types.ts
+++ b/src/speech/types.ts
@@ -0,0 +1,20 @@
 import { EventEmitter } from "events";
 export interface IWakeWordDetector {
    initialize(): Promise<void>;
    shutdown(): Promise<void>;
    startListening(): Promise<void>;
    stopListening(): Promise<void>;
 }
 export interface ISpeechToText extends EventEmitter {
    initialize(): Promise<void>;
    shutdown(): Promise<void>;
    transcribe(audioData: Buffer): Promise<string>;
 }
 export interface SpeechToTextConfig {
    modelPath: string;
    modelType: string;
    containerName?: string;
 } 
--- a/src/speech/wakeWordDetector.ts
+++ b/src/speech/wakeWordDetector.ts
@@ -0,0 +1,64 @@
 import { IWakeWordDetector } from "./types.js";
 export class WakeWordDetector implements IWakeWordDetector {
    private isListening: boolean = false;
    private isInitialized: boolean = false;
    public async initialize(): Promise<void> {
        if (this.isInitialized) {
            return;
        }
        // Initialization logic will be implemented here
        await this.setupDetector();
        this.isInitialized = true;
    }
    public async shutdown(): Promise<void> {
        if (this.isListening) {
            await this.stopListening();
        }
        if (this.isInitialized) {
            await this.cleanupDetector();
            this.isInitialized = false;
        }
    }
    public async startListening(): Promise<void> {
        if (!this.isInitialized) {
            throw new Error("Wake word detector is not initialized");
        }
        if (this.isListening) {
            return;
        }
        await this.startDetection();
        this.isListening = true;
    }
    public async stopListening(): Promise<void> {
        if (!this.isListening) {
            return;
        }
        await this.stopDetection();
        this.isListening = false;
    }
    private async setupDetector(): Promise<void> {
        // Setup logic will be implemented here
        await new Promise(resolve => setTimeout(resolve, 100)); // Placeholder
    }
    private async cleanupDetector(): Promise<void> {
        // Cleanup logic will be implemented here
        await new Promise(resolve => setTimeout(resolve, 100)); // Placeholder
    }
    private async startDetection(): Promise<void> {
        // Start detection logic will be implemented here
        await new Promise(resolve => setTimeout(resolve, 100)); // Placeholder
    }
    private async stopDetection(): Promise<void> {
        // Stop detection logic will be implemented here
        await new Promise(resolve => setTimeout(resolve, 100)); // Placeholder
    }
 }
Author	SHA1	Message	Date
jango-blockchained	b9727981cc	feat(speech): enhance speech processing with advanced audio setup and detection - Add audio setup script for PulseAudio configuration - Improve wake word detection with advanced noise filtering - Implement continuous transcription and command processing - Update speech Dockerfile with additional audio dependencies - Enhance logging and error handling in wake word detector	2025-02-04 22:51:06 +01:00
jango-blockchained	e1db799b1d	chore(dependencies): update Bun lockfile and package configuration - Update bun.lock with latest package versions - Modify Dockerfile to improve dependency installation - Remove preinstall script from package.json - Add winston logging dependencies - Adjust Docker build process for cleaner dependency management	2025-02-04 21:42:50 +01:00
jango-blockchained	905339fb67	refactor(docker): switch to Node.js base image and optimize Bun installation - Replace Bun base image with Node.js slim image - Install Bun globally using npm in both builder and runner stages - Simplify Docker build process and dependency management - Remove unnecessary environment variables and build flags - Update docker-build.sh to use BuildKit and remove lockfile before build	2025-02-04 20:18:46 +01:00
jango-blockchained	849b080aba	chore: update project dependencies and build configuration - Remove bun.lockb from version control - Add comprehensive docker-build.sh script for optimized Docker builds - Update Dockerfile with multi-stage build and improved resource management - Add winston logging dependencies to package.json - Enhance Docker image build process with resource constraints and caching	2025-02-04 20:14:13 +01:00
jango-blockchained	f8bbe4af6f	refactor(docker): optimize Dockerfiles for multi-stage builds and production deployment - Implement multi-stage builds for main and speech Dockerfiles - Reduce image size by using slim base images - Improve dependency installation with frozen lockfile and production flags - Add resource constraints and healthcheck to speech service Dockerfile - Enhance build caching and separation of build/runtime dependencies	2025-02-04 19:41:23 +01:00
jango-blockchained	3a6f79c9a8	feat(speech): enhance speech configuration and example integration - Add comprehensive speech configuration in .env.example and app config - Update Docker speech Dockerfile for more flexible model handling - Create detailed README for speech-to-text examples - Implement example script demonstrating speech features - Improve speech service initialization and configuration management	2025-02-04 19:35:50 +01:00
jango-blockchained	60f18f8e71	feat(speech): add speech-to-text and wake word detection modules - Implement SpeechToText class with Docker-based transcription capabilities - Add wake word detection using OpenWakeWord and fast-whisper models - Create Dockerfile for speech processing container - Develop comprehensive test suite for speech recognition functionality - Include audio processing and event-driven transcription features	2025-02-04 19:08:01 +01:00
jango-blockchained	47f11b3d95	docs: update README.md	2025-02-04 18:35:17 +01:00
jango-blockchained	f24be8ff53	docs: remove outdated support and rate limiting sections from README	2025-02-04 18:31:39 +01:00
jango-blockchained	dfff432321	docs: update Jekyll configuration for GitHub Pages and dependencies - Add repository settings and GitHub metadata plugin - Update baseurl to match repository name - Include additional Jekyll and Ruby dependencies in Gemfile - Simplify configuration by removing redundant sections	2025-02-04 18:00:59 +01:00
jango-blockchained	d59bf02d08	docs: enhance Jekyll configuration with comprehensive site settings - Add base URL and site configuration for GitHub Pages - Include remote theme and additional Jekyll plugins - Configure navigation structure and page layouts - Set up collections for tools and development sections - Optimize Gemfile with additional dependencies	2025-02-04 17:58:10 +01:00
jango-blockchained	345a5888d9	docs: update Jekyll configuration for enhanced documentation structure - Add new documentation pages to header navigation - Configure collections for tools and development sections - Set default layouts for pages, tools, and development collections - Improve documentation site organization and navigation	2025-02-04 17:51:04 +01:00
jango-blockchained	d6a5771e01	docs: enhance project documentation with comprehensive updates - Revamp README.md with improved project overview, architecture diagram, and badges - Create new development and tools documentation with detailed guides - Update API documentation with enhanced examples, rate limiting, and security information - Refactor and consolidate documentation files for better navigation and clarity - Add emojis and visual improvements to make documentation more engaging	2025-02-04 17:49:58 +01:00
jango-blockchained	5f4ddfbd88	docs: add GitHub Pages documentation deployment workflow - Create GitHub Actions workflow for deploying documentation to GitHub Pages - Update README.md with documentation badge and link - Add missing gem dependency in docs/Gemfile - Configure Jekyll build and deployment process	2025-02-04 17:37:20 +01:00
jango-blockchained	c11b40da9e	docs: standardize documentation file paths and references - Update README.md documentation links to use lowercase, consistent file paths - Remove "(if available)" annotations from documentation references - Ensure all documentation links point to correct, lowercase markdown files	2025-02-04 17:34:31 +01:00
jango-blockchained	3a54766b61	docs: refactor and improve documentation across multiple files - Streamline and enhance documentation for API, architecture, getting started, and usage - Improve clarity, readability, and organization of documentation files - Update content to be more concise and informative - Ensure consistent formatting and style across documentation	2025-02-04 17:33:26 +01:00
jango-blockchained	8b1948ce30	docs: enhance documentation structure and add project roadmap - Refactor index.md with improved navigation and comprehensive documentation sections - Update README.md to streamline documentation navigation - Create new roadmap.md with detailed project goals and vision - Add testing.md with comprehensive testing guidelines and best practices - Improve overall documentation clarity and user experience	2025-02-04 17:25:32 +01:00
jango-blockchained	38ee5368d1	docs: update acronym - Rename MCP acronym in documentation and package files - Update site name, package description, and documentation references - Ensure consistent terminology across project files	2025-02-04 17:19:58 +01:00