Introduction
The integration of Large Language Models (LLMs) like GPT-4, Claude, or Llama into production applications brings tremendous capabilities, but also introduces a critical challenge: managing token consumption and associated API costs. For businesses building AI-powered SaaS products, uncontrolled token usage can quickly transform a promising application into an financially unsustainable venture.
This comprehensive guide explores proven strategies for efficiently managing token usage while maintaining high-quality AI functionalities. We’ll focus on understanding the underlying concepts, explaining the rationale behind each optimization technique, and providing practical Python implementations that you can adapt for your production applications.
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