typescriptadvanced

AI Model Router for Cost Optimization

Route prompts to different LLM models based on complexity to optimize cost and response quality.

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import OpenAI from 'openai';

const openai = new OpenAI();

type ModelTier = 'fast' | 'balanced' | 'powerful';

const MODEL_MAP: Record<ModelTier, string> = {
  fast: 'gpt-4o-mini',
  balanced: 'gpt-4o',
  powerful: 'gpt-4o',
};

function classifyComplexity(prompt: string): ModelTier {
  const wordCount = prompt.split(/\s+/).length;
  const hasCode = /```|function |class |import /.test(prompt);
  const hasAnalysis = /analyze|compare|evaluate|design/i.test(prompt);

  if (wordCount < 50 && !hasCode && !hasAnalysis) return 'fast';
  if (hasCode || hasAnalysis) return 'powerful';
  return 'balanced';
}

export async function routedCompletion(
  prompt: string,
  systemPrompt?: string,
): Promise<{ response: string; model: string; tier: ModelTier }> {
  const tier = classifyComplexity(prompt);
  const model = MODEL_MAP[tier];

  const res = await openai.chat.completions.create({
    model,
    messages: [
      ...(systemPrompt ? [{ role: 'system' as const, content: systemPrompt }] : []),
      { role: 'user', content: prompt },
    ],
  });

  return {
    response: res.choices[0].message.content ?? '',
    model,
    tier,
  };
}

const result = await routedCompletion('What is 2+2?');
console.log(`Used ${result.tier} tier (${result.model}): ${result.response}`);