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How to connect GPTs to SQL databases without incurring massive cloud compute costs on AWS
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
How to connect GPTs to SQL databases without incurring massive cloud compute costs on AWS
2 real searches · 1 real-search pass
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.
ChatGPT real searches (2)
Classes come from the query-classifier (a local Laya model). 2 of 2 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT2 real searches · gpt-6
AWS Lambda RDS database connection pooling RDS Proxy pricing HTTP API cost optimization official documentation Google ↗
OpenAI GPT Actions authentication API schema documentation custom GPT actions Google ↗
- Automatically connecting a Lambda function and a DB instance · docs.aws.amazon.com
- Configuring actions in GPTs · help.openai.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
AWS Lambda RDS database connection pooling RDS Proxy pricing HTTP API cost optimization official documentation OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
OpenAI GPT Actions authentication API schema documentation custom GPT actions OBSERVED | Google ↗ AI Mode ↗ | — | Instruction | — | — | 1x of 1 |