Response length is proportional to query complexity

Unbounded max_tokens with no length guidance produces two failure modes at once: the model either pads simple answers into three-paragraph essays (burning tokens against the cost-efficiency taxon) or gets cut off mid-sentence on complex queries because the default context is exhausted. Users wait longer, pay more per request, and read padding that obscures the answer. At scale, a single missing max_tokens parameter can triple your OpenAI bill without anyone noticing until the invoice.

Set a context-appropriate max_tokens ceiling and add length calibration to the system prompt so the model adapts output length to query complexity. Apply this at every call site in lib/ai/chat.ts.

await openai.chat.completions.create({
  model: 'gpt-4o',
  max_tokens: 1024,
  messages: [{ role: 'system', content: 'Answer concisely. Simple questions: 1-2 sentences. Complex topics: structured paragraphs. Never pad.' }, ...]
})