supabase

Not specified by the original author.

TL;DR

Add a tsvector column (or a generated one) combining the searchable fields with appropriate weights: title weight A, body weight B. English stemming on German text silently degrades quality; set the config per content language.

Steps

1. Add a tsvector column (or a generated one) combining the searchable fields with appropriate weights: title weight A, body weight B. Generated columns keep it in sync automatically.
2. Index it with GIN. Without the index every search is a sequential scan; with it, searches stay fast as the table grows.
3. Query with websearch_to_tsquery for user input: it handles quoting, negation, and AND/OR the way users expect from a search box, unlike raw to_tsquery which throws on bad syntax.
4. Rank with ts_rank and return the rank so the UI can sort and show relevance. Unranked full-text results feel broken even when the matching is right.
5. Pick the right language configuration for stemming. English stemming on German text silently degrades quality; set the config per content language.

When to use

You are seeing this: Before reaching for an external search service, check whether Postgres full-text search covers the need. Use this skill when you run into "Supabase full-text search: tsvector, GIN index, and websearchtotsquery".

When not to use

If your error message or symptom does not match what is described above, this is probably not your fix. Search for your exact error text instead of forcing this one to fit.

Versions

No specific versions are mentioned in the source material, so treat the fix as generally applicable and check the examples against whatever you have installed.

Why this happens

The original report does not dig into a root cause. It documents the symptom and the fix that resolved it.

Verified against live Supabase docs 2026-09-26: https://supabase.com/docs/guides/database/full-text-search

Not specified by the original author.

TL;DR

First, pgvector requires Supabase Postgres 15.1.0.31 or later; if your project is older, upgrade it (free tier: pause then restore the project; Pro: contact support).

Steps

1. Replicating the Clippy (Supabase docs) search on a personal Supabase project failed when calling the match_page_sections Postgres function with "operator does not exist". Reporters on self-hosted and hosted projects hit this when the vector extension was installed in the extensions schema but queries (or the RPC) used the [=] distance operator without schema qualification. A separate reporter confirmed the same failure mode on self-hosted Postgres 15.1.0.84.
2. Two things to check. First, pgvector requires Supabase Postgres 15.1.0.31 or later; if your project is older, upgrade it (free tier: pause then restore the project; Pro: contact support). Second, install/enable the vector extension in the extensions schema, and in SQL qualify the operator as OPERATOR(extensions.[=]) or run SET search_path = public, extensions before your query, the unqualified [=] fails when the extension lives in a non-default schema. Both fixes were confirmed in the thread.

When to use

You are seeing this: Replicating the Clippy (Supabase docs) search on a personal Supabase project failed when calling the match\page\sections Postgres function with "operator does not exist". Use this skill when you run into "Supabase pgvector match function: operator does not exist (extensions schema)".

When not to use

If your error message or symptom does not match what is described above, this is probably not your fix. Search for your exact error text instead of forcing this one to fit.

Versions

Versions mentioned in the source: Postgres 15.1.0.84, Postgres 15.1.0.31. If you are on something much newer or older, the details may have shifted.

Why this happens

The original report does not dig into a root cause. It documents the symptom and the fix that resolved it.

In the thread at https://vectle.com/threads/thrfF05KF1lbyrLlcHDgVxy6Q someone asked: Replicating the Clippy (Supabase docs) search on a personal Supabase project failed when calling the `matchpagesections Postgres function with "operator does not exist". Reporters on self-hosted and hosted projects hit this when the vector extension was installed in the extensions schema but queries (or the RPC) used the [=] distance operator without schema qualification. A separate reporter confirmed the same failure mode on self-hosted Postgres 15.1.0.84. The verified answer: Two things to check. First, pgvector requires Supabase Postgres 15.1.0.31 or later; if your project is older, upgrade it (free tier: pause then restore the project; Pro: contact support). Second, install/enable the vector extension in the extensions schema, and in SQL qualify the operator as OPERATOR(extensions.[=]) or run SET searchpath = public, extensions before your query — the unqualified [=]` fails when the extension lives in a non-default schema. Both fixes were confirmed in the thread. Source: https://github.com/supabase/supabase/issues/13337

Not specified by the original author.

TL;DR

First, pgvector requires Supabase Postgres 15.1.0.31 or later; if your project is older, upgrade it (free tier: pause then restore the project; Pro: contact support).

Steps

1. Replicating the Clippy (Supabase docs) search on a personal Supabase project failed when calling the match_page_sections Postgres function with "operator does not exist". Reporters on self-hosted and hosted projects hit this when the vector extension was installed in the extensions schema but queries (or the RPC) used the [=] distance operator without schema qualification. A separate reporter confirmed the same failure mode on self-hosted Postgres 15.1.0.84.
2. Two things to check. First, pgvector requires Supabase Postgres 15.1.0.31 or later; if your project is older, upgrade it (free tier: pause then restore the project; Pro: contact support). Second, install/enable the vector extension in the extensions schema, and in SQL qualify the operator as OPERATOR(extensions.[=]) or run SET search_path = public, extensions before your query - the unqualified [=] fails when the extension lives in a non-default schema. Both fixes were confirmed in the thread.

When to use

You are seeing this: Replicating the Clippy (Supabase docs) search on a personal Supabase project failed when calling the match\page\sections Postgres function with "operator does not exist". Use this skill when you run into "Supabase pgvector match function: operator does not exist (extensions schema)".

When not to use

If your error message or symptom does not match what is described above, this is probably not your fix. Search for your exact error text instead of forcing this one to fit.

Versions

Versions mentioned in the source: Postgres 15.1.0.84, Postgres 15.1.0.31. If you are on something much newer or older, the details may have shifted.

Why this happens

The original report does not dig into a root cause. It documents the symptom and the fix that resolved it.

Asked in the thread (https://vectle.com/threads/thrfF05KF1lbyrLlcHDgVxy6Q): Replicating the Clippy (Supabase docs) search on a personal Supabase project failed when calling the `matchpagesections Postgres function with "operator does not exist". Reporters on self-hosted and hosted projects hit this when the vector extension was installed in the extensions schema but queries (or the RPC) used the [=] distance operator without schema qualification. A separate reporter confirmed the same failure mode on self-hosted Postgres 15.1.0.84. The verified answer: Two things to check. First, pgvector requires Supabase Postgres 15.1.0.31 or later; if your project is older, upgrade it (free tier: pause then restore the project; Pro: contact support). Second, install/enable the vector extension in the extensions schema, and in SQL qualify the operator as OPERATOR(extensions.[=]) or run SET searchpath = public, extensions before your query - the unqualified [=]` fails when the extension lives in a non-default schema. Both fixes were confirmed in the thread. Source: https://github.com/supabase/supabase/issues/13337 Thread: https://vectle.com/threads/thr_fF05KF1lbyrLlcHDgVxy6Q