Maintaining Quality Solo

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import anthropic
import json

def evaluate_response(user_input: str, ai_response: str, criteria: list[str]) -> dict:
    client = anthropic.Anthropic()
    
    criteria_text = "\n".join(f"- {c}" for c in criteria)
    
    evaluation_prompt = f"""Evaluate this AI response against the given criteria.

User Input: {user_input}

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import { expect, test, describe } from 'vitest';
import { generateProductDescription } from './ai-service';

describe('AI Product Description Generator', () => {
  const testProducts = [
    { name: 'Wireless Headphones', category: 'Electronics', price: 79.99 },
    { name: 'Yoga Mat', category: 'Fitness', price: 29.99 },
    { name: 'Coffee Maker', category: 'Kitchen', price: 149.99 },
  ];

  test.each(testProducts)('generates valid description for %s', async (product) => {
    const description = await generateProductDescription(product);

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class AIService {
  private primaryProvider: OpenAI;
  private fallbackProvider: Anthropic;
  private cache: Map<string, CachedResponse>;
  
  async generateCompletion(prompt: string, options: AIOptions): Promise<AIResponse> {
    const cacheKey = this.getCacheKey(prompt, options);
    
    // Check cache first for identical requests
    if (this.cache.has(cacheKey)) {
      const cached = this.cache.get(cacheKey)!;
      if (Date.now() - cached.timestamp < options.cacheTTL) {

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import { z } from 'zod';
import Anthropic from '@anthropic-ai/sdk';

// Define expected response structure
const AIResponseSchema = z.object({
  content: z.string().min(10).max(10000),
  confidence: z.number().min(0).max(1).optional(),
  sources: z.array(z.string()).optional(),
  reasoning: z.string().optional()
});

type AIResponse = z.infer<typeof AIResponseSchema>;

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import { z } from 'zod';

// Feedback schema for AI responses
const AIFeedbackSchema = z.object({
  responseId: z.string().uuid(),
  rating: z.enum(['helpful', 'not_helpful', 'harmful']),
  category: z.enum([
    'accuracy',
    'completeness', 
    'relevance',
    'speed',
    'formatting',

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import { EventEmitter } from 'events';

interface QualityMetrics {
  timestamp: Date;
  endpoint: string;
  latencyMs: number;
  tokenCount: number;
  qualityScore: number;
  errorType?: string;
  userId?: string;
}