The answer
The API response object contains a usage field showing prompt_tokens, completion_tokens, and total_tokens which you should log.
How to Manage LLM API Costs and Token Usage in Production
How do I track usage in code?
More FAQs in How to Manage LLM API Costs and Token Usage in Production
Caching responses based on the similarity of query embeddings, rather than exact string matches, to return cached data for slightly rephrased questions.
Because every new message requires sending the entire conversational history back to the model, meaning you pay for historical tokens repeatedly.
No, streaming tokens in chunks costs the exact same as receiving the full response at once.
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