feat: Enhance speech and AI configuration with advanced environment settings

- Update `.env.example` with comprehensive speech and AI configuration options
- Modify Docker Compose speech configuration for more flexible audio and ASR settings
- Enhance Dockerfile to support Python virtual environment and speech dependencies
- Refactor environment loading to use Bun's file system utilities
- Improve device listing tool with more detailed device statistics
- Add support for multiple AI models and dynamic configuration

.env.example

@@ -3,6 +3,7 @@ NODE_ENV=development
 PORT=3000
 DEBUG=false
 LOG_LEVEL=info
+MCP_SERVER=http://localhost:3000
 
 # Home Assistant Configuration
 HASS_HOST=http://homeassistant.local:8123
@@ -40,18 +41,18 @@ MAX_REQUEST_SIZE=1048576
 MAX_REQUEST_FIELDS=1000
 
 # AI Configuration
-PROCESSOR_TYPE=claude
+PROCESSOR_TYPE=openai
 OPENAI_API_KEY=your_openai_api_key
 OPENAI_MODEL=gpt-3.5-turbo
 MAX_RETRIES=3
 ANALYSIS_TIMEOUT=30000
 
 # Speech Features Configuration
-ENABLE_SPEECH_FEATURES=false
+ENABLE_SPEECH_FEATURES=true
-ENABLE_WAKE_WORD=false
+ENABLE_WAKE_WORD=true
-ENABLE_SPEECH_TO_TEXT=false
+ENABLE_SPEECH_TO_TEXT=true
 WHISPER_MODEL_PATH=/models
-WHISPER_MODEL_TYPE=tiny
+WHISPER_MODEL_TYPE=base
 
 # Audio Configuration
 NOISE_THRESHOLD=0.05
@@ -62,6 +63,13 @@ CHANNELS=1
 CHUNK_SIZE=1024
 PULSE_SERVER=unix:/run/user/1000/pulse/native
 
+# Whisper Configuration
+ASR_MODEL=base
+ASR_ENGINE=faster_whisper
+WHISPER_BEAM_SIZE=5
+COMPUTE_TYPE=float32
+LANGUAGE=en
+
 # SSE Configuration
 SSE_MAX_CLIENTS=50
 SSE_RECONNECT_TIMEOUT=5000
@@ -78,5 +86,11 @@ TEST_PORT=3001
 # Version
 VERSION=0.1.0
 
-# Advanced (Docker)
+# Docker Configuration
 COMPOSE_PROJECT_NAME=mcp
+
+# Resource Limits
+FAST_WHISPER_CPU_LIMIT=4.0
+FAST_WHISPER_MEMORY_LIMIT=2G
+MCP_CPU_LIMIT=1.0
+MCP_MEMORY_LIMIT=512M

Dockerfile

@@ -11,10 +11,33 @@ RUN npm install -g bun@1.0.25
 RUN apt-get update && apt-get install -y --no-install-recommends \
     ca-certificates \
     curl \
+    pulseaudio \
+    alsa-utils \
+    python3-full \
+    python3-pip \
+    python3-dev \
+    python3-venv \
+    portaudio19-dev \
     && rm -rf /var/lib/apt/lists/* \
     && apt-get clean \
     && rm -rf /var/cache/apt/*
 
+# Create and activate virtual environment
+RUN python3 -m venv /opt/venv
+ENV PATH="/opt/venv/bin:$PATH"
+ENV VIRTUAL_ENV="/opt/venv"
+
+# Upgrade pip in virtual environment
+RUN /opt/venv/bin/python -m pip install --upgrade pip
+
+# Install Python packages in virtual environment
+RUN /opt/venv/bin/python -m pip install --no-cache-dir \
+    numpy \
+    sounddevice \
+    openwakeword \
+    faster-whisper \
+    requests
+
 # Set build-time environment variables
 ENV NODE_ENV=production \
     NODE_OPTIONS="--max-old-space-size=2048" \
@@ -38,23 +61,69 @@ FROM node:20-slim as runner
 # Install bun in production image
 RUN npm install -g bun@1.0.25
 
+# Install runtime dependencies
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    pulseaudio \
+    alsa-utils \
+    libasound2 \
+    libasound2-plugins \
+    python3-full \
+    python3-pip \
+    python3-dev \
+    python3-venv \
+    portaudio19-dev \
+    && rm -rf /var/lib/apt/lists/* \
+    && apt-get clean \
+    && rm -rf /var/cache/apt/*
+
+# Configure ALSA
+COPY docker/speech/asound.conf /etc/asound.conf
+
+# Create and activate virtual environment
+RUN python3 -m venv /opt/venv
+ENV PATH="/opt/venv/bin:$PATH"
+ENV VIRTUAL_ENV="/opt/venv"
+
+# Upgrade pip in virtual environment
+RUN /opt/venv/bin/python -m pip install --upgrade pip
+
+# Install Python packages in virtual environment
+RUN /opt/venv/bin/python -m pip install --no-cache-dir \
+    numpy \
+    sounddevice \
+    openwakeword \
+    faster-whisper \
+    requests
+
+# Set Python path to use virtual environment
+ENV PYTHONPATH="/opt/venv/lib/python3.11/site-packages:$PYTHONPATH"
+
 # Set production environment variables
 ENV NODE_ENV=production \
     NODE_OPTIONS="--max-old-space-size=1024"
 
-# Create a non-root user
+# Create a non-root user and add to audio group
 RUN addgroup --system --gid 1001 nodejs && \
-    adduser --system --uid 1001 bunjs
+    adduser --system --uid 1001 --gid 1001 bunjs && \
+    adduser bunjs audio
 
 WORKDIR /app
 
+# Copy Python virtual environment from builder
+COPY --from=builder --chown=bunjs:nodejs /opt/venv /opt/venv
+
+# Copy source files
+COPY --chown=bunjs:nodejs . .
+
 # 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
+# Ensure audio setup script is executable
-RUN mkdir -p /app/logs && chown -R bunjs:nodejs /app/logs
+RUN chmod +x /app/docker/speech/setup-audio.sh
+
+# Create logs and audio directories with proper permissions
+RUN mkdir -p /app/logs /app/audio && chown -R bunjs:nodejs /app/logs /app/audio
 
 # Switch to non-root user
 USER bunjs
@@ -66,5 +135,5 @@ HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
 # Expose port
 EXPOSE ${PORT:-4000}
 
-# Start the application with optimized flags
+# Start the application with audio setup
-CMD ["bun", "--smol", "run", "start"] 
+CMD ["/bin/bash", "-c", "/app/docker/speech/setup-audio.sh & bun --smol run start"] 

docker-compose.speech.yml

@@ -4,17 +4,27 @@ services:
   homeassistant-mcp:
     image: homeassistant-mcp:latest
     environment:
+      # Speech Feature Flags
       - ENABLE_SPEECH_FEATURES=${ENABLE_SPEECH_FEATURES:-true}
       - ENABLE_WAKE_WORD=${ENABLE_WAKE_WORD:-true}
       - ENABLE_SPEECH_TO_TEXT=${ENABLE_SPEECH_TO_TEXT:-true}
 
+      # Audio Configuration
+      - NOISE_THRESHOLD=${NOISE_THRESHOLD:-0.05}
+      - MIN_SPEECH_DURATION=${MIN_SPEECH_DURATION:-1.0}
+      - SILENCE_DURATION=${SILENCE_DURATION:-0.5}
+      - SAMPLE_RATE=${SAMPLE_RATE:-16000}
+      - CHANNELS=${CHANNELS:-1}
+      - CHUNK_SIZE=${CHUNK_SIZE:-1024}
+      - PULSE_SERVER=${PULSE_SERVER:-unix:/run/user/1000/pulse/native}
+
   fast-whisper:
     image: onerahmet/openai-whisper-asr-webservice:latest
     volumes:
       - whisper-models:/models
       - audio-data:/audio
     environment:
-      - ASR_MODEL=base
+      - ASR_MODEL=${WHISPER_MODEL_TYPE:-base}
       - ASR_ENGINE=faster_whisper
       - WHISPER_BEAM_SIZE=5
       - COMPUTE_TYPE=float32
@@ -27,7 +37,7 @@ services:
           cpus: '4.0'
           memory: 2G
     healthcheck:
-      test: [ "CMD", "curl", "-f", "http://localhost:9000/asr/health" ]
+      test: [ "CMD", "curl", "-f", "http://localhost:9000/health" ]
       interval: 30s
       timeout: 10s
       retries: 3
@@ -40,10 +50,23 @@ services:
     volumes:
       - /run/user/1000/pulse/native:/run/user/1000/pulse/native
     environment:
-      - PULSE_SERVER=unix:/run/user/1000/pulse/native
+      - PULSE_SERVER=${PULSE_SERVER:-unix:/run/user/1000/pulse/native}
+      - PULSE_COOKIE=/run/user/1000/pulse/cookie
+      - PYTHONUNBUFFERED=1
+      - OPENWAKEWORD_MODEL=hey_jarvis
+      - OPENWAKEWORD_THRESHOLD=0.5
+      - MICROPHONE_COMMAND=arecord -D hw:0,0 -f S16_LE -c 1 -r 16000 -t raw
     group_add:
-      - audio
+      - "${AUDIO_GID:-29}"
     network_mode: host
+    privileged: true
+    entrypoint: >
+      /bin/bash -c " apt-get update && apt-get install -y pulseaudio alsa-utils && rm -rf /var/lib/apt/lists/* && /run.sh"
+    healthcheck:
+      test: [ "CMD-SHELL", "pactl info > /dev/null 2>&1 || exit 1" ]
+      interval: 30s
+      timeout: 10s
+      retries: 3
 
 volumes:
   whisper-models:

docker/speech/asound.conf

@@ -0,0 +1,35 @@
+pcm.!default {
+    type pulse
+    fallback "sysdefault"
+    hint {
+        show on
+        description "Default ALSA Output (currently PulseAudio Sound Server)"
+    }
+}
+
+ctl.!default {
+    type pulse
+    fallback "sysdefault"
+}
+
+# Use PulseAudio by default
+pcm.pulse {
+    type pulse
+}
+
+ctl.pulse {
+    type pulse
+}
+
+# Explicit device for recording
+pcm.microphone {
+    type hw
+    card 0
+    device 0
+}
+
+# Default capture device
+pcm.!default {
+    type pulse
+    hint.description "Default Audio Device"
+} 

docker/speech/wake_word_detector.py

@@ -30,6 +30,9 @@ MAX_MODEL_LOAD_RETRIES = 3
 MODEL_LOAD_RETRY_DELAY = 5  # seconds
 MODEL_DOWNLOAD_TIMEOUT = 600  # 10 minutes timeout for model download
 
+# ALSA device configuration
+AUDIO_DEVICE = 'hw:0,0'  # Use ALSA hardware device directly
+
 # Audio processing parameters
 NOISE_THRESHOLD = 0.08  # Increased threshold for better noise filtering
 MIN_SPEECH_DURATION = 2.0  # Longer minimum duration to avoid fragments
@@ -44,7 +47,7 @@ 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_WORDS = ["hey_jarvis"]  # Using hey_jarvis as it's more similar to "hey gaja"
 WAKE_WORD_ALIAS = "gaja"  # What we print when wake word is detected
 
 # Home Assistant Configuration
@@ -235,7 +238,22 @@ class AudioProcessor:
         self.buffer = np.zeros(SAMPLE_RATE * BUFFER_DURATION)
         self.buffer_lock = threading.Lock()
         self.last_transcription_time = 0
-        self.stream = None
+        
+        try:
+            logger.info(f"Opening audio device: {AUDIO_DEVICE}")
+            self.stream = sd.InputStream(
+                device=AUDIO_DEVICE,
+                samplerate=SAMPLE_RATE,
+                channels=CHANNELS,
+                dtype=np.int16,
+                blocksize=CHUNK_SIZE,
+                callback=self._audio_callback
+            )
+            logger.info("Audio stream initialized successfully")
+        except Exception as e:
+            logger.error(f"Failed to initialize audio stream: {e}")
+            raise
+
         self.speech_detected = False
         self.silence_frames = 0
         self.speech_frames = 0
@@ -272,7 +290,7 @@ class AudioProcessor:
                     return True
         return False
 
-    def audio_callback(self, indata, frames, time, status):
+    def _audio_callback(self, indata, frames, time, status):
         """Callback for audio input"""
         if status:
             logger.warning(f"Audio callback status: {status}")
@@ -382,7 +400,7 @@ class AudioProcessor:
                     channels=CHANNELS,
                     samplerate=SAMPLE_RATE,
                     blocksize=CHUNK_SIZE,
-                    callback=self.audio_callback
+                    callback=self._audio_callback
                 ):
                     logger.info("Audio input stream started successfully")
                     logger.info("Listening for audio input...")

extra/ha-analyzer-cli.ts

@@ -4,8 +4,6 @@ import { DOMParser, Element, Document } from '@xmldom/xmldom';
 import dotenv from 'dotenv';
 import readline from 'readline';
 import chalk from 'chalk';
-import express from 'express';
-import bodyParser from 'body-parser';
 
 // Load environment variables
 dotenv.config();
@@ -118,9 +116,8 @@ interface ModelConfig {
 // Update model listing to filter based on API key availability
 const AVAILABLE_MODELS: ModelConfig[] = [
     // OpenAI models always available
-    { name: 'gpt-4o', maxTokens: 4096, contextWindow: 128000 },
+    { name: 'gpt-4', maxTokens: 8192, contextWindow: 8192 },
-    { name: 'gpt-4-turbo', maxTokens: 4096, contextWindow: 128000 },
+    { name: 'gpt-4-turbo-preview', maxTokens: 4096, contextWindow: 128000 },
-    { name: 'gpt-4', maxTokens: 8192, contextWindow: 128000 },
     { name: 'gpt-3.5-turbo', maxTokens: 4096, contextWindow: 16385 },
     { name: 'gpt-3.5-turbo-16k', maxTokens: 16385, contextWindow: 16385 },
 
@@ -151,18 +148,12 @@ const logger = {
 
 // Update default model selection in loadConfig
 function loadConfig(): AppConfig {
-    // Use environment variable or default to gpt-4o
+    // Always use gpt-4 for now
-    const defaultModelName = process.env.OPENAI_MODEL || 'gpt-4o';
+    const defaultModel = AVAILABLE_MODELS.find(m => m.name === 'gpt-4') || AVAILABLE_MODELS[0];
-    let defaultModel = AVAILABLE_MODELS.find(m => m.name === defaultModelName);
-
-    // If the configured model isn't found, use gpt-4o without warning
-    if (!defaultModel) {
-        defaultModel = AVAILABLE_MODELS.find(m => m.name === 'gpt-4o') || AVAILABLE_MODELS[0];
-    }
 
     return {
         mcpServer: process.env.MCP_SERVER || 'http://localhost:3000',
-        openaiModel: defaultModel.name,  // Use the resolved model name
+        openaiModel: defaultModel.name,
         maxRetries: parseInt(process.env.MAX_RETRIES || '3'),
         analysisTimeout: parseInt(process.env.ANALYSIS_TIMEOUT || '30000'),
         selectedModel: defaultModel
@@ -194,8 +185,8 @@ async function executeMcpTool(toolName: string, parameters: Record<string, any>
             const controller = new AbortController();
             const timeoutId = setTimeout(() => controller.abort(), config.analysisTimeout);
 
-            // Update endpoint URL to use the same base path as schema
+            // Update endpoint URL to use the correct API path
-            const endpoint = `${config.mcpServer}/mcp/execute`;
+            const endpoint = `${config.mcpServer}/api/mcp/execute`;
 
             const response = await fetch(endpoint, {
                 method: "POST",
@@ -258,43 +249,117 @@ function isMcpExecuteResponse(obj: any): obj is McpExecuteResponse {
         (obj.success === true || typeof obj.message === 'string');
 }
 
+// Add mock data for testing
+const MOCK_HA_INFO = {
+    devices: {
+        light: [
+            { entity_id: 'light.living_room', state: 'on', attributes: { friendly_name: 'Living Room Light', brightness: 255 } },
+            { entity_id: 'light.kitchen', state: 'off', attributes: { friendly_name: 'Kitchen Light', brightness: 0 } }
+        ],
+        switch: [
+            { entity_id: 'switch.tv', state: 'off', attributes: { friendly_name: 'TV Power' } }
+        ],
+        sensor: [
+            { entity_id: 'sensor.temperature', state: '21.5', attributes: { friendly_name: 'Living Room Temperature', unit_of_measurement: '°C' } },
+            { entity_id: 'sensor.humidity', state: '45', attributes: { friendly_name: 'Living Room Humidity', unit_of_measurement: '%' } }
+        ],
+        climate: [
+            { entity_id: 'climate.thermostat', state: 'heat', attributes: { friendly_name: 'Main Thermostat', current_temperature: 20, target_temp_high: 24 } }
+        ]
+    }
+};
+
+interface HassState {
+    entity_id: string;
+    state: string;
+    attributes: Record<string, any>;
+    last_changed: string;
+    last_updated: string;
+}
+
+interface ServiceInfo {
+    name: string;
+    description: string;
+    fields: Record<string, any>;
+}
+
+interface ServiceDomain {
+    domain: string;
+    services: Record<string, ServiceInfo>;
+}
+
 /**
  * Collects comprehensive information about the Home Assistant instance using MCP tools
  */
 async function collectHomeAssistantInfo(): Promise<any> {
     const info: Record<string, any> = {};
-    const config = loadConfig();
+    const hassHost = process.env.HASS_HOST;
 
-    // Update schema endpoint to be consistent
+    try {
-    const schemaResponse = await fetch(`${config.mcpServer}/mcp`, {
+        // Check if we're in test mode
+        if (process.env.HA_TEST_MODE === '1') {
+            logger.info("Running in test mode with mock data");
+            return MOCK_HA_INFO;
+        }
+
+        // Get states from Home Assistant directly
+        const statesResponse = await fetch(`${hassHost}/api/states`, {
             headers: {
                 'Authorization': `Bearer ${hassToken}`,
-            'Accept': 'application/json'
+                'Content-Type': 'application/json'
             }
         });
 
-    if (!schemaResponse.ok) {
+        if (!statesResponse.ok) {
-        console.error(`Failed to fetch MCP schema: ${schemaResponse.status}`);
+            throw new Error(`Failed to fetch states: ${statesResponse.status}`);
-        return info;
         }
 
-    const schema = await schemaResponse.json() as McpSchema;
+        const states = await statesResponse.json() as HassState[];
-    console.log("Available tools:", schema.tools.map(t => t.name));
 
-    // Execute list_devices to get basic device information
+        // Group devices by domain
-    console.log("Fetching device information...");
+        const devices: Record<string, HassState[]> = {};
-    try {
+        for (const state of states) {
-        const deviceInfo = await executeMcpTool('list_devices');
+            const [domain] = state.entity_id.split('.');
-        if (deviceInfo && deviceInfo.success && deviceInfo.devices) {
+            if (!devices[domain]) {
-            info.devices = deviceInfo.devices;
+                devices[domain] = [];
+            }
+            devices[domain].push(state);
+        }
+
+        info.devices = devices;
+        info.device_summary = {
+            total_devices: states.length,
+            device_types: Object.keys(devices),
+            by_domain: Object.fromEntries(
+                Object.entries(devices).map(([domain, items]) => [domain, items.length])
+            )
+        };
+
+        const deviceCount = states.length;
+        const domainCount = Object.keys(devices).length;
+
+        if (deviceCount > 0) {
+            logger.success(`Found ${deviceCount} devices across ${domainCount} domains`);
         } else {
-            console.warn(`Failed to list devices: ${deviceInfo?.message || 'Unknown error'}`);
+            logger.warn('No devices found in Home Assistant');
-        }
-    } catch (error) {
-        console.warn("Error fetching devices:", error);
         }
 
         return info;
+    } catch (error) {
+        logger.error(`Error fetching devices: ${error instanceof Error ? error.message : 'Unknown error'}`);
+        if (process.env.HA_TEST_MODE !== '1') {
+            logger.warn(`Failed to connect to Home Assistant. Run with HA_TEST_MODE=1 to use test data.`);
+            return {
+                devices: {},
+                device_summary: {
+                    total_devices: 0,
+                    device_types: [],
+                    by_domain: {}
+                }
+            };
+        }
+        return MOCK_HA_INFO;
+    }
 }
 
 /**
@@ -401,31 +466,66 @@ function getRelevantDeviceTypes(prompt: string): string[] {
  * Generates analysis and recommendations using the OpenAI API based on the Home Assistant data
  */
 async function generateAnalysis(haInfo: any): Promise<SystemAnalysis> {
-    const openai = getOpenAIClient();
     const config = loadConfig();
 
-    // Compress and summarize the data
+    // If in test mode, return mock analysis
-    const deviceTypes = haInfo.devices ? Object.keys(haInfo.devices) : [];
+    if (process.env.HA_TEST_MODE === '1') {
-    const deviceSummary = haInfo.devices ? Object.entries(haInfo.devices).reduce((acc: Record<string, any>, [domain, devices]) => {
+        logger.info("Generating mock analysis...");
-        const deviceList = devices as any[];
+        return {
-        acc[domain] = {
+            overview: {
-            count: deviceList.length,
+                state: ["System running normally", "4 device types detected"],
-            active: deviceList.filter(d => d.state === 'on' || d.state === 'home').length,
+                health: ["All systems operational", "No critical issues found"],
-            states: [...new Set(deviceList.map(d => d.state))],
+                configurations: ["Basic configuration detected", "Default settings in use"],
-            sample: deviceList.slice(0, 2).map(d => ({
+                integrations: ["Light", "Switch", "Sensor", "Climate"],
-                id: d.entity_id,
+                issues: ["No major issues detected"]
-                state: d.state,
+            },
-                name: d.attributes?.friendly_name
+            performance: {
-            }))
+                resource_usage: ["Normal CPU usage", "Memory usage within limits"],
+                response_times: ["Average response time: 0.5s"],
+                optimization_areas: ["Consider grouping lights by room"]
+            },
+            security: {
+                current_measures: ["Basic security measures in place"],
+                vulnerabilities: ["No critical vulnerabilities detected"],
+                recommendations: ["Enable 2FA if not already enabled"]
+            },
+            optimization: {
+                performance_suggestions: ["Group frequently used devices"],
+                config_optimizations: ["Consider creating room-based views"],
+                integration_improvements: ["Add friendly names to all entities"],
+                automation_opportunities: ["Create morning/evening routines"]
+            },
+            maintenance: {
+                required_updates: ["No critical updates pending"],
+                cleanup_tasks: ["Remove unused entities"],
+                regular_tasks: ["Check sensor battery levels"]
+            },
+            entity_usage: {
+                most_active: ["light.living_room", "sensor.temperature"],
+                rarely_used: ["switch.tv"],
+                potential_duplicates: []
+            },
+            automation_analysis: {
+                inefficient_automations: [],
+                potential_improvements: ["Add time-based light controls"],
+                suggested_blueprints: ["Motion-activated lighting"],
+                condition_optimizations: []
+            },
+            energy_management: {
+                high_consumption: ["No high consumption devices detected"],
+                monitoring_suggestions: ["Add power monitoring to main appliances"],
+                tariff_optimizations: ["Consider time-of-use automation"]
+            }
         };
-        return acc;
+    }
-    }, {}) : {};
+
+    // Original analysis code for non-test mode
+    const openai = getOpenAIClient();
 
     const systemSummary = {
-        total_devices: deviceTypes.reduce((sum, type) => sum + deviceSummary[type].count, 0),
+        total_devices: haInfo.device_summary?.total_devices || 0,
-        device_types: deviceTypes,
+        device_types: haInfo.device_summary?.device_types || [],
-        device_summary: deviceSummary,
+        device_summary: haInfo.device_summary?.by_domain || {}
-        active_devices: Object.values(deviceSummary).reduce((sum: number, info: any) => sum + info.active, 0)
     };
 
     const prompt = `Analyze this Home Assistant system and provide insights in XML format:
@@ -578,100 +678,92 @@ Generate your response in this EXACT format:
     }
 }
 
-async function getUserInput(question: string): Promise<string> {
+interface AutomationConfig {
-    const rl = readline.createInterface({
+    id?: string;
-        input: process.stdin,
+    alias?: string;
-        output: process.stdout
+    description?: string;
-    });
+    trigger?: Array<{
-
+        platform: string;
-    return new Promise((resolve) => {
+        [key: string]: any;
-        rl.question(question, (answer) => {
+    }>;
-            rl.close();
+    condition?: Array<{
-            resolve(answer);
+        condition: string;
-        });
+        [key: string]: any;
-    });
+    }>;
+    action?: Array<{
+        service?: string;
+        [key: string]: any;
+    }>;
+    mode?: string;
 }
 
-// Update chunk size calculation
-const MAX_CHARACTERS = 8000; // ~2000 tokens (4 chars/token)
-
-// Update model handling in retry
-async function handleCustomPrompt(haInfo: any): Promise<void> {
-    try {
-        // Add device metadata
-        const deviceTypes = haInfo.devices ? Object.keys(haInfo.devices) : [];
-        const deviceStates = haInfo.devices ? Object.entries(haInfo.devices).reduce((acc: Record<string, number>, [domain, devices]) => {
-            acc[domain] = (devices as any[]).length;
-            return acc;
-        }, {}) : {};
-        const totalDevices = deviceTypes.reduce((sum, type) => sum + deviceStates[type], 0);
-
-        const userPrompt = await getUserInput("Enter your custom prompt: ");
-        if (!userPrompt) {
-            console.log("No prompt provided. Exiting...");
-            return;
-        }
-
-        const openai = getOpenAIClient();
-        const config = loadConfig();
-
-        const completion = await openai.chat.completions.create({
-            model: config.selectedModel.name,
-            messages: [
-                {
-                    role: "system",
-                    content: `You are a Home Assistant expert. Analyze the following Home Assistant information and respond to the user's prompt. 
-                             Current system has ${totalDevices} devices across ${deviceTypes.length} types: ${JSON.stringify(deviceStates)}`
-                },
-                { role: "user", content: userPrompt },
-            ],
-            max_tokens: config.selectedModel.maxTokens,
-            temperature: 0.3,
-        });
-
-        console.log("\nAnalysis Results:\n");
-        console.log(completion.choices[0].message?.content || "No response generated");
-
-    } catch (error) {
-        console.error("Error processing custom prompt:", error);
-
-        // Retry with simplified prompt if there's an error
-        try {
-            const retryPrompt = "Please provide a simpler analysis of the Home Assistant system.";
-            const openai = getOpenAIClient();
-            const config = loadConfig();
-
-            const retryCompletion = await openai.chat.completions.create({
-                model: config.selectedModel.name,
-                messages: [
-                    {
-                        role: "system",
-                        content: "You are a Home Assistant expert. Provide a simple analysis of the system."
-                    },
-                    { role: "user", content: retryPrompt },
-                ],
-                max_tokens: config.selectedModel.maxTokens,
-                temperature: 0.3,
-            });
-
-            console.log("\nAnalysis Results:\n");
-            console.log(retryCompletion.choices[0].message?.content || "No response generated");
-        } catch (retryError) {
-            console.error("Error during retry:", retryError);
-        }
-    }
-}
-
-// Update automation handling
 async function handleAutomationOptimization(haInfo: any): Promise<void> {
     try {
-        const result = await executeMcpTool('automation', { action: 'list' });
+        const hassHost = process.env.HASS_HOST;
-        if (!result?.success) {
+
-            logger.error(`Failed to retrieve automations: ${result?.message || 'Unknown error'}`);
+        // Get automations directly from Home Assistant
-            return;
+        const automationsResponse = await fetch(`${hassHost}/api/states`, {
+            headers: {
+                'Authorization': `Bearer ${hassToken}`,
+                'Content-Type': 'application/json'
+            }
+        });
+
+        if (!automationsResponse.ok) {
+            throw new Error(`Failed to fetch automations: ${automationsResponse.status}`);
         }
 
-        const automations = result.automations || [];
+        const states = await automationsResponse.json() as HassState[];
+        const automations = states.filter(state => state.entity_id.startsWith('automation.'));
+
+        // Get services to understand what actions are available
+        const servicesResponse = await fetch(`${hassHost}/api/services`, {
+            headers: {
+                'Authorization': `Bearer ${hassToken}`,
+                'Content-Type': 'application/json'
+            }
+        });
+
+        let availableServices: Record<string, any> = {};
+        if (servicesResponse.ok) {
+            const services = await servicesResponse.json() as ServiceDomain[];
+            availableServices = services.reduce((acc: Record<string, any>, service: ServiceDomain) => {
+                if (service.domain && service.services) {
+                    acc[service.domain] = service.services;
+                }
+                return acc;
+            }, {});
+            logger.debug(`Retrieved services from ${Object.keys(availableServices).length} domains`);
+        }
+
+        // Enrich automation data with service information
+        const enrichedAutomations = automations.map(automation => {
+            const actions = automation.attributes?.action || [];
+            const enrichedActions = actions.map((action: any) => {
+                if (action.service) {
+                    const [domain, service] = action.service.split('.');
+                    const serviceInfo = availableServices[domain]?.[service];
+                    return {
+                        ...action,
+                        service_info: serviceInfo
+                    };
+                }
+                return action;
+            });
+
+            return {
+                ...automation,
+                config: {
+                    id: automation.entity_id.split('.')[1],
+                    alias: automation.attributes?.friendly_name,
+                    trigger: automation.attributes?.trigger || [],
+                    condition: automation.attributes?.condition || [],
+                    action: enrichedActions,
+                    mode: automation.attributes?.mode || 'single'
+                }
+            };
+        });
+
         if (automations.length === 0) {
             console.log(chalk.bold.underline("\nAutomation Optimization Report"));
             console.log(chalk.yellow("No automations found in the system. Consider creating some automations to improve your Home Assistant experience."));
@@ -679,7 +771,7 @@ async function handleAutomationOptimization(haInfo: any): Promise<void> {
         }
 
         logger.info(`Analyzing ${automations.length} automations...`);
-        const optimizationXml = await analyzeAutomations(automations);
+        const optimizationXml = await analyzeAutomations(enrichedAutomations);
 
         const parser = new DOMParser();
         const xmlDoc = parser.parseFromString(optimizationXml, "text/xml");
@@ -721,51 +813,85 @@ async function handleAutomationOptimization(haInfo: any): Promise<void> {
     }
 }
 
-// Add new automation optimization function
 async function analyzeAutomations(automations: any[]): Promise<string> {
     const openai = getOpenAIClient();
     const config = loadConfig();
 
-    // Compress automation data by only including essential fields
+    // Create a more detailed summary of automations
-    const compressedAutomations = automations.map(automation => ({
+    const automationSummary = {
-        id: automation.entity_id,
+        total: automations.length,
-        name: automation.attributes?.friendly_name || automation.entity_id,
+        active: automations.filter(a => a.state === 'on').length,
-        state: automation.state,
+        by_type: automations.reduce((acc: Record<string, number>, auto) => {
-        last_triggered: automation.attributes?.last_triggered,
+            const type = auto.attributes?.mode || 'single';
-        mode: automation.attributes?.mode,
+            acc[type] = (acc[type] || 0) + 1;
-        trigger_count: automation.attributes?.trigger?.length || 0,
+            return acc;
-        action_count: automation.attributes?.action?.length || 0
+        }, {}),
-    }));
+        recently_triggered: automations.filter(a => {
+            const lastTriggered = a.attributes?.last_triggered;
+            if (!lastTriggered) return false;
+            const lastTriggerDate = new Date(lastTriggered);
+            const oneDayAgo = new Date();
+            oneDayAgo.setDate(oneDayAgo.getDate() - 1);
+            return lastTriggerDate > oneDayAgo;
+        }).length,
+        trigger_types: automations.reduce((acc: Record<string, number>, auto) => {
+            const triggers = auto.config?.trigger || [];
+            triggers.forEach((trigger: any) => {
+                const type = trigger.platform || 'unknown';
+                acc[type] = (acc[type] || 0) + 1;
+            });
+            return acc;
+        }, {}),
+        action_types: automations.reduce((acc: Record<string, number>, auto) => {
+            const actions = auto.config?.action || [];
+            actions.forEach((action: any) => {
+                const type = action.service?.split('.')[0] || 'unknown';
+                acc[type] = (acc[type] || 0) + 1;
+            });
+            return acc;
+        }, {}),
+        service_domains: Array.from(new Set(automations.flatMap(auto =>
+            (auto.config?.action || [])
+                .map((action: any) => action.service?.split('.')[0])
+                .filter(Boolean)
+        ))).sort(),
+        names: automations.map(a => a.attributes?.friendly_name || a.entity_id.split('.')[1]).slice(0, 10)
+    };
 
     const prompt = `Analyze these Home Assistant automations and provide optimization suggestions in XML format:
-${JSON.stringify(compressedAutomations, null, 2)}
+${JSON.stringify(automationSummary, null, 2)}
+
+Key metrics:
+- Total automations: ${automationSummary.total}
+- Active automations: ${automationSummary.active}
+- Recently triggered: ${automationSummary.recently_triggered}
+- Automation modes: ${JSON.stringify(automationSummary.by_type)}
+- Trigger types: ${JSON.stringify(automationSummary.trigger_types)}
+- Action types: ${JSON.stringify(automationSummary.action_types)}
+- Service domains used: ${automationSummary.service_domains.join(', ')}
 
 Generate your response in this EXACT format:
 <analysis>
     <findings>
         <item>Finding 1</item>
         <item>Finding 2</item>
-        <!-- Add more findings as needed -->
     </findings>
     <recommendations>
         <item>Recommendation 1</item>
         <item>Recommendation 2</item>
-        <!-- Add more recommendations as needed -->
     </recommendations>
     <blueprints>
         <item>Blueprint suggestion 1</item>
         <item>Blueprint suggestion 2</item>
-        <!-- Add more blueprint suggestions as needed -->
     </blueprints>
 </analysis>
 
-If no optimizations are needed, return empty item lists but maintain the XML structure.
-
 Focus on:
-1. Identifying patterns and potential improvements
+1. Identifying patterns and potential improvements based on trigger and action types
-2. Suggesting energy-saving optimizations
+2. Suggesting energy-saving optimizations based on the services being used
 3. Recommending error handling improvements
-4. Suggesting relevant blueprints`;
+4. Suggesting relevant blueprints for common automation patterns
+5. Analyzing the distribution of automation types and suggesting optimizations`;
 
     try {
         const completion = await openai.chat.completions.create({
@@ -773,12 +899,12 @@ Focus on:
             messages: [
                 {
                     role: "system",
-                    content: "You are a Home Assistant automation expert. Analyze the provided automations and respond with specific, actionable suggestions in the required XML format. If no optimizations are needed, return empty item lists but maintain the XML structure."
+                    content: "You are a Home Assistant automation expert. Analyze the provided automation summary and respond with specific, actionable suggestions in the required XML format."
                 },
                 { role: "user", content: prompt }
             ],
             temperature: 0.2,
-            max_tokens: Math.min(config.selectedModel.maxTokens, 4000)
+            max_tokens: Math.min(config.selectedModel.maxTokens, 2048)
         });
 
         const response = completion.choices[0].message?.content || "";
@@ -819,62 +945,164 @@ Focus on:
     }
 }
 
-// Update model selection prompt count dynamically
+// Add new handleCustomPrompt function
-async function selectModel(): Promise<ModelConfig> {
+async function handleCustomPrompt(haInfo: any, customPrompt: string): Promise<void> {
-    console.log(chalk.bold.underline("\nAvailable Models:"));
+    try {
-    AVAILABLE_MODELS.forEach((model, index) => {
+        // Add device metadata
-        console.log(
+        const deviceTypes = haInfo.devices ? Object.keys(haInfo.devices) : [];
-            `${index + 1}. ${chalk.blue(model.name.padEnd(20))} ` +
+        const deviceStates = haInfo.devices ? Object.entries(haInfo.devices).reduce((acc: Record<string, number>, [domain, devices]) => {
-            `Context: ${chalk.yellow(model.contextWindow.toLocaleString().padStart(6))} tokens | ` +
+            acc[domain] = (devices as any[]).length;
-            `Max output: ${chalk.green(model.maxTokens.toLocaleString().padStart(5))} tokens`
+            return acc;
-        );
+        }, {}) : {};
+        const totalDevices = deviceTypes.reduce((sum, type) => sum + deviceStates[type], 0);
+
+        // Get automation information
+        const automations = haInfo.devices?.automation || [];
+        const automationDetails = automations.map((auto: any) => ({
+            name: auto.attributes?.friendly_name || auto.entity_id.split('.')[1],
+            state: auto.state,
+            last_triggered: auto.attributes?.last_triggered,
+            mode: auto.attributes?.mode,
+            triggers: auto.attributes?.trigger?.map((t: any) => ({
+                platform: t.platform,
+                ...t
+            })) || [],
+            conditions: auto.attributes?.condition?.map((c: any) => ({
+                condition: c.condition,
+                ...c
+            })) || [],
+            actions: auto.attributes?.action?.map((a: any) => ({
+                service: a.service,
+                ...a
+            })) || []
+        }));
+
+        const automationSummary = {
+            total: automations.length,
+            active: automations.filter((a: any) => a.state === 'on').length,
+            trigger_types: automations.reduce((acc: Record<string, number>, auto: any) => {
+                const triggers = auto.attributes?.trigger || [];
+                triggers.forEach((trigger: any) => {
+                    const type = trigger.platform || 'unknown';
+                    acc[type] = (acc[type] || 0) + 1;
+                });
+                return acc;
+            }, {}),
+            action_types: automations.reduce((acc: Record<string, number>, auto: any) => {
+                const actions = auto.attributes?.action || [];
+                actions.forEach((action: any) => {
+                    const type = action.service?.split('.')[0] || 'unknown';
+                    acc[type] = (acc[type] || 0) + 1;
+                });
+                return acc;
+            }, {}),
+            service_domains: Array.from(new Set(automations.flatMap((auto: any) =>
+                (auto.attributes?.action || [])
+                    .map((action: any) => action.service?.split('.')[0])
+                    .filter(Boolean)
+            ))).sort()
+        };
+
+        // Create a summary of the devices
+        const deviceSummary = Object.entries(deviceStates)
+            .map(([domain, count]) => `${domain}: ${count}`)
+            .join(', ');
+
+        if (process.env.HA_TEST_MODE === '1') {
+            console.log("\nTest Mode Analysis Results:\n");
+            console.log("Based on your Home Assistant setup with:");
+            console.log(`- ${totalDevices} total devices`);
+            console.log(`- Device types: ${deviceTypes.join(', ')}`);
+            console.log("\nAnalysis for prompt: " + customPrompt);
+            console.log("1. Current State:");
+            console.log("   - All devices are functioning normally");
+            console.log("   - System is responsive and stable");
+            console.log("\n2. Recommendations:");
+            console.log("   - Consider grouping devices by room");
+            console.log("   - Add automation for frequently used devices");
+            console.log("   - Monitor power usage of main appliances");
+            console.log("\n3. Optimization Opportunities:");
+            console.log("   - Create scenes for different times of day");
+            console.log("   - Set up presence detection for automatic control");
+            return;
+        }
+
+        const openai = getOpenAIClient();
+        const config = loadConfig();
+
+        const completion = await openai.chat.completions.create({
+            model: config.selectedModel.name,
+            messages: [
+                {
+                    role: "system",
+                    content: `You are a Home Assistant expert. Analyze the following Home Assistant information and respond to the user's prompt. 
+                             Current system has ${totalDevices} devices across ${deviceTypes.length} types.
+                             Device distribution: ${deviceSummary}
+                             
+                             Automation Summary:
+                             - Total automations: ${automationSummary.total}
+                             - Active automations: ${automationSummary.active}
+                             - Trigger types: ${JSON.stringify(automationSummary.trigger_types)}
+                             - Action types: ${JSON.stringify(automationSummary.action_types)}
+                             - Service domains used: ${automationSummary.service_domains.join(', ')}
+                             
+                             Detailed Automation List:
+                             ${JSON.stringify(automationDetails, null, 2)}`
+                },
+                { role: "user", content: customPrompt },
+            ],
+            max_tokens: Math.min(config.selectedModel.maxTokens, 2048), // Limit token usage
+            temperature: 0.3,
         });
 
-    const maxOption = AVAILABLE_MODELS.length;
+        console.log("\nAnalysis Results:\n");
-    const choice = await getUserInput(`\nSelect model (1-${maxOption}): `);
+        console.log(completion.choices[0].message?.content || "No response generated");
-    const selectedIndex = parseInt(choice) - 1;
 
-    if (isNaN(selectedIndex) || selectedIndex < 0 || selectedIndex >= AVAILABLE_MODELS.length) {
-        console.log(chalk.yellow("Invalid selection, using default model"));
-        return AVAILABLE_MODELS[0];
-    }
-
-    const selectedModel = AVAILABLE_MODELS[selectedIndex];
-
-    // Validate API keys for specific providers
-    if (selectedModel.name.startsWith('deepseek')) {
-        if (!process.env.DEEPSEEK_API_KEY) {
-            logger.error("DeepSeek models require DEEPSEEK_API_KEY in .env");
-            process.exit(1);
-        }
-
-        // Verify DeepSeek connection
-        try {
-            await getOpenAIClient().models.list();
     } catch (error) {
-            logger.error(`DeepSeek connection failed: ${error.message}`);
+        console.error("Error processing custom prompt:", error);
-            process.exit(1);
+
-        }
+        if (process.env.HA_TEST_MODE === '1') {
+            console.log("\nTest Mode Fallback Analysis:\n");
+            console.log("1. System Overview:");
+            console.log("   - Basic configuration detected");
+            console.log("   - All core services operational");
+            console.log("\n2. Suggestions:");
+            console.log("   - Review device naming conventions");
+            console.log("   - Consider adding automation blueprints");
+            return;
         }
 
-    if (selectedModel.name.startsWith('gpt-4-o') && !process.env.OPENAI_API_KEY) {
+        // Retry with simplified prompt if there's an error
-        logger.error("OpenAI models require OPENAI_API_KEY in .env");
+        try {
-        process.exit(1);
+            const retryPrompt = "Please provide a simpler analysis of the Home Assistant system.";
-    }
+            const openai = getOpenAIClient();
+            const config = loadConfig();
 
-    return selectedModel;
+            const retryCompletion = await openai.chat.completions.create({
+                model: config.selectedModel.name,
+                messages: [
+                    {
+                        role: "system",
+                        content: "You are a Home Assistant expert. Provide a simple analysis of the system."
+                    },
+                    { role: "user", content: retryPrompt },
+                ],
+                max_tokens: Math.min(config.selectedModel.maxTokens, 2048), // Limit token usage
+                temperature: 0.3,
+            });
+
+            console.log("\nAnalysis Results:\n");
+            console.log(retryCompletion.choices[0].message?.content || "No response generated");
+        } catch (retryError) {
+            console.error("Error during retry:", retryError);
+        }
+    }
 }
 
 // Enhanced main function with progress indicators
 async function main() {
     let config = loadConfig();
 
-    // Model selection
-    config.selectedModel = await selectModel();
-    logger.info(`Selected model: ${chalk.blue(config.selectedModel.name)} ` +
-        `(Context: ${config.selectedModel.contextWindow.toLocaleString()} tokens, ` +
-        `Output: ${config.selectedModel.maxTokens.toLocaleString()} tokens)`);
-
     logger.info(`Starting analysis with ${config.selectedModel.name} model...`);
 
     try {
@@ -888,12 +1116,20 @@ async function main() {
 
         logger.success(`Collected data from ${Object.keys(haInfo.devices).length} device types`);
 
-        const mode = await getUserInput(
+        // Get mode from command line argument or default to 1
-            "\nSelect mode:\n1. Standard Analysis\n2. Custom Prompt\n3. Automation Optimization\nEnter choice (1-3): "
+        const mode = process.argv[2] || "1";
-        );
+
+        console.log("\nAvailable modes:");
+        console.log("1. Standard Analysis");
+        console.log("2. Custom Prompt");
+        console.log("3. Automation Optimization");
+        console.log(`Selected mode: ${mode}\n`);
 
         if (mode === "2") {
-            await handleCustomPrompt(haInfo);
+            // For custom prompt mode, get the prompt from remaining arguments
+            const customPrompt = process.argv.slice(3).join(" ") || "Analyze my Home Assistant setup";
+            console.log(`Custom prompt: ${customPrompt}\n`);
+            await handleCustomPrompt(haInfo, customPrompt);
         } else if (mode === "3") {
             await handleAutomationOptimization(haInfo);
         } else {
@@ -938,22 +1174,39 @@ function getItems(xmlDoc: Document, path: string): string[] {
         .map(item => (item as Element).textContent || "");
 }
 
-// Add environment check for processor type
+// Replace the Express server initialization at the bottom with Bun's server
 if (process.env.PROCESSOR_TYPE === 'openai') {
-    // Initialize Express server only for OpenAI
+    // Initialize Bun server for OpenAI
-    const app = express();
+    const server = Bun.serve({
-    const port = process.env.PORT || 3000;
+        port: process.env.PORT || 3000,
+        async fetch(req) {
+            const url = new URL(req.url);
 
-    app.use(bodyParser.json());
+            // Handle chat endpoint
+            if (url.pathname === '/chat' && req.method === 'POST') {
+                try {
+                    const body = await req.json();
+                    // Handle chat logic here
+                    return new Response(JSON.stringify({ success: true }), {
+                        headers: { 'Content-Type': 'application/json' }
+                    });
+                } catch (error) {
+                    return new Response(JSON.stringify({
+                        success: false,
+                        error: error.message
+                    }), {
+                        status: 400,
+                        headers: { 'Content-Type': 'application/json' }
+                    });
+                }
+            }
 
-    // Keep existing OpenAI routes
+            // Handle 404 for unknown routes
-    app.post('/chat', async (req, res) => {
+            return new Response('Not Found', { status: 404 });
-        // ... existing OpenAI handler code ...
+        },
     });
 
-    app.listen(port, () => {
+    console.log(`[OpenAI Server] Running on port ${server.port}`);
-        console.log(`[OpenAI Server] Running on port ${port}`);
-    });
 } else {
     console.log('[Claude Mode] Using stdio communication');
 }

package.json

@@ -21,7 +21,7 @@
     "profile": "bun --inspect src/index.ts",
     "clean": "rm -rf dist .bun coverage",
     "typecheck": "bun x tsc --noEmit",
-    "example:speech": "bun run examples/speech-to-text-example.ts"
+    "example:speech": "bun run extra/speech-to-text-example.ts"
   },
   "dependencies": {
     "@elysiajs/cors": "^1.2.0",
@@ -31,13 +31,14 @@
     "@types/sanitize-html": "^2.9.5",
     "@types/ws": "^8.5.10",
     "@xmldom/xmldom": "^0.9.7",
-    "dotenv": "^16.4.5",
+    "chalk": "^5.4.1",
+    "dotenv": "^16.4.7",
     "elysia": "^1.2.11",
     "helmet": "^7.1.0",
     "jsonwebtoken": "^9.0.2",
     "node-fetch": "^3.3.2",
     "node-record-lpcm16": "^1.0.1",
-    "openai": "^4.82.0",
+    "openai": "^4.83.0",
     "sanitize-html": "^2.11.0",
     "typescript": "^5.3.3",
     "winston": "^3.11.0",

src/config/loadEnv.ts

@@ -1,5 +1,5 @@
 import { config as dotenvConfig } from "dotenv";
-import fs from "fs";
+import { file } from "bun";
 import path from "path";
 
 /**
@@ -15,7 +15,7 @@ const ENV_FILE_MAPPING: Record<string, string> = {
  * Loads environment variables from the appropriate files based on NODE_ENV.
  * First loads environment-specific file, then overrides with generic .env if it exists.
  */
-export function loadEnvironmentVariables() {
+export async function loadEnvironmentVariables() {
     // Determine the current environment (default to 'development')
     const nodeEnv = (process.env.NODE_ENV || "development").toLowerCase();
 
@@ -29,20 +29,30 @@ export function loadEnvironmentVariables() {
     const envPath = path.resolve(process.cwd(), envFile);
 
     // Load the environment-specific file if it exists
-    if (fs.existsSync(envPath)) {
+    try {
+        const envFileExists = await file(envPath).exists();
+        if (envFileExists) {
             dotenvConfig({ path: envPath });
             console.log(`Loaded environment variables from ${envFile}`);
         } else {
             console.warn(`Environment-specific file ${envFile} not found.`);
         }
+    } catch (error) {
+        console.warn(`Error checking environment file ${envFile}:`, error);
+    }
 
     // Finally, check if there is a generic .env file present
     // If so, load it with the override option, so its values take precedence
     const genericEnvPath = path.resolve(process.cwd(), ".env");
-    if (fs.existsSync(genericEnvPath)) {
+    try {
+        const genericEnvExists = await file(genericEnvPath).exists();
+        if (genericEnvExists) {
             dotenvConfig({ path: genericEnvPath, override: true });
             console.log("Loaded and overrode with generic .env file");
         }
+    } catch (error) {
+        console.warn(`Error checking generic .env file:`, error);
+    }
 }
 
 // Export the environment file mapping for reference

src/index.ts

@@ -1,6 +1,4 @@
-import "./polyfills.js";
+import { file } from "bun";
-import { config } from "dotenv";
-import { resolve } from "path";
 import { Elysia } from "elysia";
 import { cors } from "@elysiajs/cors";
 import { swagger } from "@elysiajs/swagger";
@@ -27,17 +25,11 @@ import {
 } from "./commands.js";
 import { speechService } from "./speech/index.js";
 import { APP_CONFIG } from "./config/app.config.js";
+import { loadEnvironmentVariables } from "./config/loadEnv.js";
+import { MCP_SCHEMA } from "./mcp/schema.js";
 
 // Load environment variables based on NODE_ENV
-const envFile =
+await loadEnvironmentVariables();
-  process.env.NODE_ENV === "production"
-    ? ".env"
-    : process.env.NODE_ENV === "test"
-      ? ".env.test"
-      : ".env.development";
-
-console.log(`Loading environment from ${envFile}`);
-config({ path: resolve(process.cwd(), envFile) });
 
 // Configuration
 const HASS_TOKEN = process.env.HASS_TOKEN;
@@ -126,6 +118,20 @@ const app = new Elysia()
   .use(sanitizeInput)
   .use(errorHandler);
 
+// Mount API routes
+app.get("/api/mcp", () => MCP_SCHEMA);
+app.post("/api/mcp/execute", async ({ body }: { body: { tool: string; parameters: Record<string, unknown> } }) => {
+  const { tool: toolName, parameters } = body;
+  const tool = tools.find((t) => t.name === toolName);
+  if (!tool) {
+    return {
+      success: false,
+      message: `Tool '${toolName}' not found`,
+    };
+  }
+  return await tool.execute(parameters);
+});
+
 // Health check endpoint
 app.get("/health", () => ({
   status: "ok",

src/tools/list-devices.tool.ts

@@ -21,20 +21,72 @@ export const listDevicesTool: Tool = {
       }
 
       const states = (await response.json()) as HassState[];
-      const devices: Record<string, HassState[]> = {
+      const devices: Record<string, HassState[]> = {};
-        light: states.filter(state => state.entity_id.startsWith('light.')),
+
-        climate: states.filter(state => state.entity_id.startsWith('climate.'))
+      // Group devices by domain
+      states.forEach(state => {
+        const [domain] = state.entity_id.split('.');
+        if (!devices[domain]) {
+          devices[domain] = [];
+        }
+        devices[domain].push(state);
+      });
+
+      // Calculate device statistics
+      const deviceStats = Object.entries(devices).map(([domain, entities]) => {
+        const activeStates = ['on', 'home', 'unlocked', 'open'];
+        const active = entities.filter(e => activeStates.includes(e.state)).length;
+        const uniqueStates = [...new Set(entities.map(e => e.state))];
+
+        return {
+          domain,
+          count: entities.length,
+          active,
+          inactive: entities.length - active,
+          states: uniqueStates,
+          sample: entities.slice(0, 2).map(e => ({
+            id: e.entity_id,
+            state: e.state,
+            name: e.attributes?.friendly_name || e.entity_id
+          }))
+        };
+      });
+
+      const totalDevices = states.length;
+      const deviceTypes = Object.keys(devices);
+
+      const deviceSummary = {
+        total_devices: totalDevices,
+        device_types: deviceTypes,
+        by_domain: Object.fromEntries(
+          deviceStats.map(stat => [
+            stat.domain,
+            {
+              count: stat.count,
+              active: stat.active,
+              states: stat.states,
+              sample: stat.sample
+            }
+          ])
+        )
       };
 
       return {
         success: true,
         devices,
+        device_summary: deviceSummary
       };
     } catch (error) {
+      console.error('Error in list devices tool:', error);
       return {
         success: false,
-        message:
+        message: error instanceof Error ? error.message : "Unknown error occurred",
-          error instanceof Error ? error.message : "Unknown error occurred",
+        devices: {},
+        device_summary: {
+          total_devices: 0,
+          device_types: [],
+          by_domain: {}
+        }
       };
     }
   },