Add OpenAI-powered Home Assistant Analysis Tool
- Implemented comprehensive AI-driven system analysis using OpenAI's GPT-4 - Created interactive CLI tool for Home Assistant device and system insights - Added support for standard and custom prompt-based analysis - Integrated MCP server data collection with intelligent AI processing - Updated package.json with new OpenAI and XML dependencies - Enhanced README with detailed OpenAI integration documentation
This commit is contained in:
jango-blockchained
72
README.md
72
README.md
@@ -59,6 +59,9 @@ See [SSE_API.md](docs/SSE_API.md) for complete documentation of the SSE system.
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- [Add-on Management](#add-on-management)
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- [Package Management](#package-management)
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- [Automation Management](#automation-management)
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- [OpenAI Integration](#openai-integration)
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- [Standard Analysis](#1-standard-analysis)
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- [Custom Prompt Analysis](#2-custom-prompt-analysis)
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- [Natural Language Integration](#natural-language-integration)
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- [Troubleshooting](#troubleshooting)
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- [Project Status](#project-status)
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@@ -667,6 +670,75 @@ async function executeAction() {
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}
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```
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## OpenAI Integration
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The server includes powerful AI analysis capabilities powered by OpenAI's GPT-4 model. This feature provides intelligent analysis of your Home Assistant setup through two main modes:
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### 1. Standard Analysis
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Performs a comprehensive system analysis including:
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- System Overview
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- Performance Analysis
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- Security Assessment
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- Optimization Recommendations
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- Maintenance Tasks
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```bash
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# Run standard analysis
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npm run test:openai
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# Select option 1 when prompted
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```
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### 2. Custom Prompt Analysis
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Allows you to ask specific questions about your Home Assistant setup. The analysis can include:
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- Device States
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- Configuration Details
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- Active Devices
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- Device Attributes (brightness, temperature, etc.)
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```bash
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# Run custom analysis
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npm run test:openai
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# Select option 2 when prompted
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```
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#### Available Variables
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When using custom prompts, you can use these variables:
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- `{device_count}`: Total number of devices
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- `{device_types}`: List of device types
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- `{device_states}`: Current states of devices
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- `{device_examples}`: Example devices and their states
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#### Example Custom Prompts
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```
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"Show me all active lights"
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"Which devices in {device_types} need maintenance?"
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"Analyze my {device_count} devices and suggest automations"
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```
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### Configuration
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To use the OpenAI integration, you need to set up your OpenAI API key in the `.env` file:
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```env
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OPENAI_API_KEY=your_openai_api_key_here
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```
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### Features
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- 🔍 Intelligent device state analysis
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- 📊 System health assessment
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- 🤖 Smart automation suggestions
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- 🔧 Maintenance recommendations
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- 💡 Custom query support
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- 🔄 Real-time device state information
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### Token Usage Optimization
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The analysis tool includes smart token usage optimization:
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- Automatic filtering of relevant devices based on query
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- Fallback to summarized data for large systems
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- Intelligent attribute selection based on device types
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- Automatic retry with condensed information if token limit is reached
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## Development
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```bash
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580
openai_test.ts
Normal file
580
openai_test.ts
Normal file
@@ -0,0 +1,580 @@
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import fetch from "node-fetch";
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import OpenAI from "openai";
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import { DOMParser, Element, Document } from '@xmldom/xmldom';
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import dotenv from 'dotenv';
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import readline from 'readline';
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// Load environment variables
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dotenv.config();
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// Retrieve API keys from environment variables
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const openaiApiKey = process.env.OPENAI_API_KEY;
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const hassToken = process.env.HASS_TOKEN;
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if (!openaiApiKey) {
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console.error("Please set the OPENAI_API_KEY environment variable.");
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process.exit(1);
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}
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if (!hassToken) {
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console.error("Please set the HASS_TOKEN environment variable.");
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process.exit(1);
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}
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const openai = new OpenAI({
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apiKey: openaiApiKey,
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});
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// MCP Server configuration
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const MCP_SERVER = process.env.MCP_SERVER || 'http://localhost:3000';
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interface McpTool {
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name: string;
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description: string;
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parameters: {
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properties: Record<string, any>;
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required: string[];
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};
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}
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interface ToolsResponse {
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tools: McpTool[];
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}
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interface SystemAnalysis {
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overview: {
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state: string;
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health: string;
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configurations: string[];
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integrations: string[];
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issues: string[];
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};
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performance: {
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resource_usage: string[];
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response_times: string[];
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optimization_areas: string[];
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};
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security: {
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current_measures: string[];
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vulnerabilities: string[];
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recommendations: string[];
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};
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optimization: {
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performance_suggestions: string[];
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config_optimizations: string[];
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integration_improvements: string[];
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automation_opportunities: string[];
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};
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maintenance: {
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required_updates: string[];
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cleanup_tasks: string[];
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regular_tasks: string[];
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};
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}
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interface McpSchema {
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tools: McpTool[];
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prompts: any[];
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resources: {
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name: string;
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url: string;
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}[];
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}
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interface McpExecuteResponse {
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success: boolean;
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message?: string;
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devices?: Record<string, any[]>;
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}
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interface ListDevicesResponse {
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success: boolean;
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message?: string;
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devices?: Record<string, any[]>;
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}
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/**
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* Executes a tool on the MCP server
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*/
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async function executeMcpTool(toolName: string, parameters: Record<string, any> = {}): Promise<any> {
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try {
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const response = await fetch(`${MCP_SERVER}/mcp/execute`, {
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method: "POST",
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headers: {
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'Authorization': `Bearer ${hassToken}`,
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'Content-Type': "application/json",
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'Accept': 'application/json'
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},
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body: JSON.stringify({
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tool: toolName,
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parameters
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})
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});
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if (response.ok) {
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return await response.json();
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}
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console.warn(`Failed to execute tool ${toolName}: ${response.status}`);
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if (response.status === 401) {
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console.error("Authentication failed. Please check your HASS_TOKEN.");
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}
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return null;
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} catch (error) {
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console.warn(`Error executing tool ${toolName}:`, error);
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return null;
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}
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}
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/**
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* Collects comprehensive information about the Home Assistant instance using MCP tools
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*/
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async function collectHomeAssistantInfo(): Promise<any> {
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const info: Record<string, any> = {};
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// First, get the MCP schema which contains available tools
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const schemaResponse = await fetch(`${MCP_SERVER}/mcp`, {
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headers: {
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'Accept': 'application/json'
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}
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});
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if (!schemaResponse.ok) {
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console.error(`Failed to fetch MCP schema: ${schemaResponse.status}`);
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return info;
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}
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const schema = await schemaResponse.json() as McpSchema;
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console.log("Available tools:", schema.tools.map(t => t.name));
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// Execute list_devices to get basic device information
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console.log("Fetching device information...");
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try {
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const deviceInfo = await executeMcpTool('list_devices');
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if (deviceInfo && deviceInfo.success && deviceInfo.devices) {
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info.devices = deviceInfo.devices;
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} else {
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console.warn(`Failed to list devices: ${deviceInfo?.message || 'Unknown error'}`);
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}
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} catch (error) {
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console.warn("Error fetching devices:", error);
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}
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return info;
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}
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/**
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* Formats the analysis into a nice looking console output
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*/
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function formatAnalysis(analysis: SystemAnalysis): string {
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const formatSection = (items: string[]): string =>
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items.map(item => ` • ${item}`).join('\n');
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return `
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=== System Overview ===
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Current State: ${analysis.overview.state}
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Health: ${analysis.overview.health}
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Notable Configurations:
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${formatSection(analysis.overview.configurations)}
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Active Integrations:
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${formatSection(analysis.overview.integrations)}
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Identified Issues:
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${formatSection(analysis.overview.issues)}
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=== Performance Analysis ===
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Resource Usage:
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${formatSection(analysis.performance.resource_usage)}
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Response Times:
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${formatSection(analysis.performance.response_times)}
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Areas Needing Optimization:
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${formatSection(analysis.performance.optimization_areas)}
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=== Security Assessment ===
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Current Security Measures:
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${formatSection(analysis.security.current_measures)}
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Potential Vulnerabilities:
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${formatSection(analysis.security.vulnerabilities)}
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Security Recommendations:
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${formatSection(analysis.security.recommendations)}
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=== Optimization Recommendations ===
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Performance Improvements:
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${formatSection(analysis.optimization.performance_suggestions)}
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Configuration Optimizations:
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${formatSection(analysis.optimization.config_optimizations)}
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Integration Improvements:
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${formatSection(analysis.optimization.integration_improvements)}
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Automation Opportunities:
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${formatSection(analysis.optimization.automation_opportunities)}
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=== Maintenance Tasks ===
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Required Updates:
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${formatSection(analysis.maintenance.required_updates)}
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Cleanup Tasks:
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${formatSection(analysis.maintenance.cleanup_tasks)}
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Regular Maintenance:
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${formatSection(analysis.maintenance.regular_tasks)}
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`;
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}
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/**
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* Generates analysis and recommendations using the OpenAI API based on the Home Assistant data
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*/
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async function generateAnalysis(haInfo: any): Promise<SystemAnalysis> {
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// Prepare a summarized version of the data to reduce token count
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const deviceTypes = haInfo.devices ? Object.keys(haInfo.devices) : [];
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const deviceStates = haInfo.devices ? Object.entries(haInfo.devices).reduce((acc: Record<string, number>, [domain, devices]) => {
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acc[domain] = (devices as any[]).length;
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return acc;
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}, {}) : {};
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const summarizedInfo = {
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device_summary: {
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total_count: deviceTypes.reduce((sum, type) => sum + deviceStates[type], 0),
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types: deviceTypes,
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by_type: deviceStates,
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examples: deviceTypes.slice(0, 3).flatMap(type =>
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(haInfo.devices[type] as any[]).slice(0, 1).map(device => ({
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type,
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entity_id: device.entity_id,
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state: device.state,
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attributes: device.attributes
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}))
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)
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}
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};
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const prompt = `
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Analyze this Home Assistant device summary and provide a concise analysis in XML format.
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Focus on key insights and actionable recommendations.
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Device Summary:
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${JSON.stringify(summarizedInfo, null, 2)}
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Provide your analysis in this XML format:
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<analysis>
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<overview>
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<state>Brief overall state</state>
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<health>Brief health assessment</health>
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<configurations>
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<item>Key configuration insight</item>
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</configurations>
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<integrations>
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<item>Key integration insight</item>
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</integrations>
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<issues>
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<item>Critical issue if any</item>
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</issues>
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</overview>
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<optimization>
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<performance_suggestions>
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<item>Key performance tip</item>
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</performance_suggestions>
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<automation_opportunities>
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<item>Key automation suggestion</item>
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</automation_opportunities>
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</optimization>
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<maintenance>
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<required_updates>
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<item>Critical update if needed</item>
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</required_updates>
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<regular_tasks>
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<item>Key maintenance task</item>
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</regular_tasks>
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</maintenance>
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</analysis>`;
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try {
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const completion = await openai.chat.completions.create({
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model: "gpt-4",
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messages: [
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{
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role: "system",
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content: "You are an expert Home Assistant analyst. Provide very concise, actionable insights in the specified XML format."
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},
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{ role: "user", content: prompt },
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],
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max_tokens: 500,
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temperature: 0.7,
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});
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const result = completion.choices[0].message?.content || "";
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// Parse XML response into structured data
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const parser = new DOMParser();
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const xmlDoc = parser.parseFromString(result, "text/xml");
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const getItems = (path: string): string[] => {
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const items = Array.from(xmlDoc.getElementsByTagName('item'))
|
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.filter(item => {
|
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let parent = item.parentNode;
|
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let pathParts = path.split('>').map(p => p.trim());
|
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for (let i = pathParts.length - 1; i >= 0; i--) {
|
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if (!parent || parent.nodeName !== pathParts[i]) return false;
|
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parent = parent.parentNode;
|
||||
}
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return true;
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});
|
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return items.map(item => (item as unknown as Element).textContent || "");
|
||||
};
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||||
|
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const getText = (path: string): string => {
|
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const pathParts = path.split('>').map(p => p.trim());
|
||||
let currentElement: Document | Element = xmlDoc;
|
||||
for (const part of pathParts) {
|
||||
const elements = currentElement.getElementsByTagName(part);
|
||||
if (elements.length === 0) return "";
|
||||
currentElement = elements[0] as Element;
|
||||
}
|
||||
return currentElement.textContent || "";
|
||||
};
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||||
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const analysis: SystemAnalysis = {
|
||||
overview: {
|
||||
state: getText("analysis > overview > state"),
|
||||
health: getText("analysis > overview > health"),
|
||||
configurations: getItems("analysis > overview > configurations"),
|
||||
integrations: getItems("analysis > overview > integrations"),
|
||||
issues: getItems("analysis > overview > issues"),
|
||||
},
|
||||
performance: {
|
||||
resource_usage: getItems("analysis > performance > resource_usage"),
|
||||
response_times: getItems("analysis > performance > response_times"),
|
||||
optimization_areas: getItems("analysis > performance > optimization_areas"),
|
||||
},
|
||||
security: {
|
||||
current_measures: getItems("analysis > security > current_measures"),
|
||||
vulnerabilities: getItems("analysis > security > vulnerabilities"),
|
||||
recommendations: getItems("analysis > security > recommendations"),
|
||||
},
|
||||
optimization: {
|
||||
performance_suggestions: getItems("analysis > optimization > performance_suggestions"),
|
||||
config_optimizations: getItems("analysis > optimization > config_optimizations"),
|
||||
integration_improvements: getItems("analysis > optimization > integration_improvements"),
|
||||
automation_opportunities: getItems("analysis > optimization > automation_opportunities"),
|
||||
},
|
||||
maintenance: {
|
||||
required_updates: getItems("analysis > maintenance > required_updates"),
|
||||
cleanup_tasks: getItems("analysis > maintenance > cleanup_tasks"),
|
||||
regular_tasks: getItems("analysis > maintenance > regular_tasks"),
|
||||
},
|
||||
};
|
||||
|
||||
return analysis;
|
||||
} catch (error) {
|
||||
console.error("Error during OpenAI API call:", error);
|
||||
throw new Error("Failed to generate analysis");
|
||||
}
|
||||
}
|
||||
|
||||
async function getUserInput(question: string): Promise<string> {
|
||||
const rl = readline.createInterface({
|
||||
input: process.stdin,
|
||||
output: process.stdout
|
||||
});
|
||||
|
||||
return new Promise((resolve) => {
|
||||
rl.question(question, (answer) => {
|
||||
rl.close();
|
||||
resolve(answer);
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
async function handleCustomPrompt(haInfo: any): Promise<void> {
|
||||
console.log("\nEnter your custom prompt. Available variables:");
|
||||
console.log("- {device_count}: Total number of devices");
|
||||
console.log("- {device_types}: List of device types");
|
||||
console.log("- {device_states}: Current states of devices");
|
||||
console.log("- {device_examples}: Example devices and their states");
|
||||
console.log("\nExample: 'Analyze my {device_count} devices and suggest automations for {device_types}'");
|
||||
|
||||
const customPrompt = await getUserInput("\nEnter your prompt: ");
|
||||
|
||||
// Prepare the data for variable replacement
|
||||
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);
|
||||
|
||||
// Function to filter relevant devices based on the prompt
|
||||
const getRelevantDevices = (prompt: string, devices: any) => {
|
||||
const relevantTypes = deviceTypes.filter(type =>
|
||||
prompt.toLowerCase().includes(type.toLowerCase()) ||
|
||||
type === 'light' && prompt.toLowerCase().includes('lights') ||
|
||||
type === 'switch' && prompt.toLowerCase().includes('switches')
|
||||
);
|
||||
|
||||
if (relevantTypes.length === 0) {
|
||||
// If no specific types mentioned, return a summary of all types
|
||||
return Object.entries(devices).reduce((acc: any, [domain, deviceList]) => {
|
||||
acc[domain] = {
|
||||
count: (deviceList as any[]).length,
|
||||
example: (deviceList as any[])[0]
|
||||
};
|
||||
return acc;
|
||||
}, {});
|
||||
}
|
||||
|
||||
return relevantTypes.reduce((acc: any, type) => {
|
||||
if (devices[type]) {
|
||||
acc[type] = devices[type];
|
||||
}
|
||||
return acc;
|
||||
}, {});
|
||||
};
|
||||
|
||||
const relevantDevices = getRelevantDevices(customPrompt, haInfo.devices);
|
||||
|
||||
// Replace variables in the prompt
|
||||
let formattedPrompt = `
|
||||
Here is the current state of your Home Assistant devices:
|
||||
|
||||
Total Devices: ${totalDevices}
|
||||
Device Types: ${deviceTypes.join(', ')}
|
||||
|
||||
Relevant Device Information:
|
||||
${JSON.stringify(relevantDevices, null, 2)}
|
||||
|
||||
User Query: ${customPrompt}
|
||||
|
||||
Please analyze this information and provide a detailed response focusing specifically on what was asked.
|
||||
If the query is about specific device types, please filter and show only relevant information.
|
||||
Include specific entity IDs and states in your response when applicable.
|
||||
`;
|
||||
|
||||
try {
|
||||
const completion = await openai.chat.completions.create({
|
||||
model: "gpt-4",
|
||||
messages: [
|
||||
{
|
||||
role: "system",
|
||||
content: `You are an expert Home Assistant analyst with direct access to the current state of a Home Assistant instance.
|
||||
When analyzing device states:
|
||||
- Always mention specific entity IDs when discussing devices
|
||||
- Include current state values and relevant attributes
|
||||
- If discussing lights, mention brightness levels if available
|
||||
- For climate devices, include temperature and mode information
|
||||
- For switches and other binary devices, clearly state if they are on/off
|
||||
- Group related devices together in your analysis
|
||||
- Provide specific, actionable insights based on the current states`
|
||||
},
|
||||
{ role: "user", content: formattedPrompt },
|
||||
],
|
||||
max_tokens: 1000,
|
||||
temperature: 0.3,
|
||||
});
|
||||
|
||||
console.log("\nAnalysis Results:\n");
|
||||
console.log(completion.choices[0].message?.content || "No response generated");
|
||||
} catch (error) {
|
||||
console.error("Error during OpenAI API call:", error);
|
||||
if (error instanceof Error && error.message.includes('maximum context length')) {
|
||||
console.log("\nTrying with more concise data...");
|
||||
// Retry with even more summarized data
|
||||
const summarizedDevices = Object.entries(relevantDevices).reduce((acc: any, [type, devices]) => {
|
||||
if (Array.isArray(devices)) {
|
||||
const activeDevices = devices.filter((d: any) =>
|
||||
d.state === 'on' ||
|
||||
d.state === 'home' ||
|
||||
(typeof d.state === 'number' && d.state > 0)
|
||||
);
|
||||
|
||||
acc[type] = {
|
||||
total: devices.length,
|
||||
active: activeDevices.length,
|
||||
active_devices: activeDevices.map((d: any) => ({
|
||||
entity_id: d.entity_id,
|
||||
state: d.state,
|
||||
name: d.attributes?.friendly_name || d.entity_id,
|
||||
...(d.attributes?.brightness && { brightness: Math.round((d.attributes.brightness / 255) * 100) + '%' }),
|
||||
...(d.attributes?.temperature && { temperature: d.attributes.temperature }),
|
||||
...(d.attributes?.hvac_mode && { mode: d.attributes.hvac_mode })
|
||||
}))
|
||||
};
|
||||
}
|
||||
return acc;
|
||||
}, {});
|
||||
|
||||
const retryPrompt = `
|
||||
Analyzing Home Assistant devices:
|
||||
Total Devices: ${totalDevices}
|
||||
Device Types: ${deviceTypes.join(', ')}
|
||||
|
||||
Relevant Device Summary:
|
||||
${JSON.stringify(summarizedDevices, null, 2)}
|
||||
|
||||
User Query: ${customPrompt}
|
||||
|
||||
Please provide a detailed analysis focusing on active devices.
|
||||
Include specific device names, states, and any relevant attributes (brightness, temperature, etc.).
|
||||
Group similar devices together in your response.
|
||||
`;
|
||||
|
||||
try {
|
||||
const retryCompletion = await openai.chat.completions.create({
|
||||
model: "gpt-4",
|
||||
messages: [
|
||||
{
|
||||
role: "system",
|
||||
content: "You are an expert Home Assistant analyst. Provide concise, focused answers about device states and configurations."
|
||||
},
|
||||
{ role: "user", content: retryPrompt },
|
||||
],
|
||||
max_tokens: 1000,
|
||||
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);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
async function main() {
|
||||
console.log("Collecting Home Assistant information...");
|
||||
const haInfo = await collectHomeAssistantInfo();
|
||||
if (!Object.keys(haInfo).length) {
|
||||
console.error("Failed to collect any Home Assistant information. Exiting.");
|
||||
return;
|
||||
}
|
||||
|
||||
const mode = await getUserInput(
|
||||
"\nSelect mode:\n1. Standard Analysis\n2. Custom Prompt\nEnter choice (1 or 2): "
|
||||
);
|
||||
|
||||
if (mode === "2") {
|
||||
await handleCustomPrompt(haInfo);
|
||||
} else {
|
||||
console.log("Generating standard analysis and recommendations...");
|
||||
try {
|
||||
const analysis = await generateAnalysis(haInfo);
|
||||
const formattedAnalysis = formatAnalysis(analysis);
|
||||
console.log("\nHome Assistant Analysis and Recommendations:\n");
|
||||
console.log(formattedAnalysis);
|
||||
} catch (error) {
|
||||
console.error("Error generating analysis:", error);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
main().catch((error) => {
|
||||
console.error("Unexpected error:", error);
|
||||
});
|
||||
@@ -11,6 +11,7 @@
|
||||
"test": "NODE_OPTIONS=--experimental-vm-modules jest --config=jest.config.cjs",
|
||||
"test:coverage": "NODE_OPTIONS=--experimental-vm-modules jest --config=jest.config.cjs --coverage",
|
||||
"test:watch": "NODE_OPTIONS=--experimental-vm-modules jest --config=jest.config.cjs --watch",
|
||||
"test:openai": "tsx openai_test.ts",
|
||||
"lint": "eslint src --ext .ts",
|
||||
"lint:fix": "eslint src --ext .ts --fix",
|
||||
"prepare": "npm run build",
|
||||
@@ -21,6 +22,8 @@
|
||||
"dependencies": {
|
||||
"@digital-alchemy/core": "^24.11.4",
|
||||
"@digital-alchemy/hass": "^24.11.4",
|
||||
"@types/xmldom": "^0.1.34",
|
||||
"@xmldom/xmldom": "^0.9.7",
|
||||
"ajv": "^8.12.0",
|
||||
"dotenv": "^16.3.1",
|
||||
"express": "^4.18.2",
|
||||
@@ -41,6 +44,8 @@
|
||||
"@types/uuid": "^9.0.8",
|
||||
"@types/ws": "^8.5.10",
|
||||
"jest": "^29.7.0",
|
||||
"node-fetch": "^3.3.2",
|
||||
"openai": "^4.82.0",
|
||||
"rimraf": "^5.0.5",
|
||||
"ts-jest": "^29.1.2",
|
||||
"tsx": "^4.7.0",
|
||||
@@ -48,4 +53,4 @@
|
||||
},
|
||||
"author": "Jango Blockchained",
|
||||
"license": "MIT"
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user