should our university incubator team use Supabase vector or pgvector for connecting our GPT wrapper to SQL databases
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
should our university incubator team use Supabase vector or pgvector for connecting our GPT wrapper to SQL databases
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
Supabase official docs pgvector vector embeddings PostgreSQL extension features RLS indexes 2026 Google ↗
pgvector official GitHub PostgreSQL vector similarity search HNSW IVFFlat filtering Google ↗
- AI & Vectors · supabase.com
- Vector columns · supabase.com
- GitHub - pgvector/pgvector: Open-source vector similarity search for Postgres · github.com
- Vector indexes · supabase.com
- RAG with Permissions · supabase.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Supabase official docs pgvector vector embeddings PostgreSQL extension features RLS indexes 2026 OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
pgvector official GitHub PostgreSQL vector similarity search HNSW IVFFlat filtering OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 |