homeassistant-mcp

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src/ai/endpoints/ai-router.ts
import express from 'express';
import { z } from 'zod';
import { NLPProcessor } from '../nlp/processor.js';
import { AIRateLimit, AIContext, AIResponse, AIError, AIModel } from '../types/index.js';
import rateLimit from 'express-rate-limit';

const router = express.Router();
const nlpProcessor = new NLPProcessor();

// Rate limiting configuration
const rateLimitConfig: AIRateLimit = {
    requests_per_minute: 100,
    requests_per_hour: 1000,
    concurrent_requests: 10,
    model_specific_limits: {
        claude: {
            requests_per_minute: 100,
            requests_per_hour: 1000
        },
        gpt4: {
            requests_per_minute: 50,
            requests_per_hour: 500
        },
        custom: {
            requests_per_minute: 200,
            requests_per_hour: 2000
        }
    }
};

// Request validation schemas
const interpretRequestSchema = z.object({
    input: z.string(),
    context: z.object({
        user_id: z.string(),
        session_id: z.string(),
        timestamp: z.string(),
        location: z.string(),
        previous_actions: z.array(z.any()),
        environment_state: z.record(z.any())
    }),
    model: z.enum(['claude', 'gpt4', 'custom']).optional()
});

// Rate limiters
const globalLimiter = rateLimit({
    windowMs: 60 * 1000, // 1 minute
    max: rateLimitConfig.requests_per_minute
});

const modelSpecificLimiter = (model: string) => rateLimit({
    windowMs: 60 * 1000,
    max: rateLimitConfig.model_specific_limits[model as AIModel]?.requests_per_minute ||
        rateLimitConfig.requests_per_minute
});

// Error handler middleware
const errorHandler = (
    error: Error,
    req: express.Request,
    res: express.Response,
    next: express.NextFunction
) => {
    const aiError: AIError = {
        code: 'PROCESSING_ERROR',
        message: error.message,
        suggestion: 'Please try again with a different command format',
        recovery_options: [
            'Simplify your command',
            'Use standard command patterns',
            'Check device names and parameters'
        ],
        context: req.body.context
    };

    res.status(500).json({ error: aiError });
};

// Endpoints
router.post(
    '/interpret',
    globalLimiter,
    async (req: express.Request, res: express.Response, next: express.NextFunction) => {
        try {
            const { input, context, model = 'claude' } = interpretRequestSchema.parse(req.body);

            // Apply model-specific rate limiting
            modelSpecificLimiter(model)(req, res, async () => {
                const { intent, confidence, error } = await nlpProcessor.processCommand(input, context);

                if (error) {
                    return res.status(400).json({ error });
                }

                const isValid = await nlpProcessor.validateIntent(intent, confidence);

                if (!isValid) {
                    const suggestions = await nlpProcessor.suggestCorrections(input, {
                        code: 'INVALID_INTENT',
                        message: 'Could not understand the command with high confidence',
                        suggestion: 'Please try rephrasing your command',
                        recovery_options: [],
                        context
                    });

                    return res.status(400).json({
                        error: {
                            code: 'INVALID_INTENT',
                            message: 'Could not understand the command with high confidence',
                            suggestion: 'Please try rephrasing your command',
                            recovery_options: suggestions,
                            context
                        }
                    });
                }

                const response: AIResponse = {
                    natural_language: `I'll ${intent.action} the ${intent.target.split('.').pop()}`,
                    structured_data: {
                        success: true,
                        action_taken: intent.action,
                        entities_affected: [intent.target],
                        state_changes: intent.parameters
                    },
                    next_suggestions: [
                        'Would you like to adjust any settings?',
                        'Should I perform this action in other rooms?',
                        'Would you like to schedule this action?'
                    ],
                    confidence,
                    context
                };

                res.json(response);
            });
        } catch (error) {
            next(error);
        }
    }
);

router.post(
    '/execute',
    globalLimiter,
    async (req: express.Request, res: express.Response, next: express.NextFunction) => {
        try {
            const { intent, context, model = 'claude' } = req.body;

            // Apply model-specific rate limiting
            modelSpecificLimiter(model)(req, res, async () => {
                // Execute the intent through Home Assistant
                // This would integrate with your existing Home Assistant service

                const response: AIResponse = {
                    natural_language: `Successfully executed ${intent.action} on ${intent.target}`,
                    structured_data: {
                        success: true,
                        action_taken: intent.action,
                        entities_affected: [intent.target],
                        state_changes: intent.parameters
                    },
                    next_suggestions: [
                        'Would you like to verify the state?',
                        'Should I perform any related actions?',
                        'Would you like to undo this action?'
                    ],
                    confidence: { overall: 1, intent: 1, entities: 1, context: 1 },
                    context
                };

                res.json(response);
            });
        } catch (error) {
            next(error);
        }
    }
);

router.get(
    '/suggestions',
    globalLimiter,
    async (req: express.Request, res: express.Response, next: express.NextFunction) => {
        try {
            const { context, model = 'claude' } = req.body;

            // Apply model-specific rate limiting
            modelSpecificLimiter(model)(req, res, async () => {
                // Generate context-aware suggestions
                const suggestions = [
                    'Turn on the lights in the living room',
                    'Set the temperature to 72 degrees',
                    'Show me the current state of all devices',
                    'Start the evening routine'
                ];

                res.json({ suggestions });
            });
        } catch (error) {
            next(error);
        }
    }
);

// Apply error handler
router.use(errorHandler);

export default router; 