How do I connect our PostgreSQL database to an AI embedding model to get started with vector search without needing a degree in data science
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
How do I connect our PostgreSQL database to an AI embedding model to get started with vector search without needing a degree in data science
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.
Classifying 2 queries…
Searches and sources
ChatGPT2 real searches · gpt-6
official pgvector PostgreSQL extension installation vector similarity search README GitHub Google ↗
OpenAI official embeddings API text-embedding-3-small dimensions documentation Google ↗
- GitHub - pgvector/pgvector: Open-source vector similarity search for Postgres · github.com
- Create embeddings · developers.openai.com
- Vector embeddings · developers.openai.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
official pgvector PostgreSQL extension installation vector similarity search README GitHub OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
OpenAI official embeddings API text-embedding-3-small dimensions documentation OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |