What are the best practices for reducing OpenAI token usage through prompt engineering when building a developer documentation search bot?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
What are the best practices for reducing OpenAI token usage through prompt engineering when building a developer documentation search bot?
1 real search · 1 real-search pass
OpenAI API prompt caching guide token counting input tokens embeddings retrieval documentation officialGoogle ↗
OBSERVED
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
Classifying 1 queries…
Searches and sources
ChatGPT1 real searches · gpt-6
OpenAI API prompt caching guide token counting input tokens embeddings retrieval documentation official Google ↗
- Prompt caching · developers.openai.com
- Prompt caching · developers.openai.com
- Counting tokens · developers.openai.com
- Understanding and counting tokens · help.openai.com