From ccc32dbde14ec9b63c6deda61b548bd0eaaad943 Mon Sep 17 00:00:00 2001
From: Charis <26616127+charislam@users.noreply.github.com>
Date: Wed, 3 Jul 2024 11:53:37 -0400
Subject: [PATCH] fix: linting issues (#27577)

---
 .../20240626184716_misc_database_fixes.sql    | 151 ++++++++++++++++++
 1 file changed, 151 insertions(+)
 create mode 100644 supabase/migrations/20240626184716_misc_database_fixes.sql

diff --git a/supabase/migrations/20240626184716_misc_database_fixes.sql b/supabase/migrations/20240626184716_misc_database_fixes.sql
new file mode 100644
index 0000000000..5c3770e2a9
--- /dev/null
+++ b/supabase/migrations/20240626184716_misc_database_fixes.sql
@@ -0,0 +1,151 @@
+alter function public.update_last_changed_checksum
+set search_path = '';
+
+alter function public.cleanup_last_changed_pages
+set search_path = '';
+
+-- Return a setof page_section so that we can use PostgREST resource embeddings (joins with other tables)
+create or replace function match_page_sections_v2(
+  embedding vector(1536),
+  match_threshold float,
+  min_content_length int
+)
+returns setof page_section
+language plpgsql
+set search_path = ''
+as $$
+#variable_conflict use_variable
+begin
+  return query
+  select *
+  from public.page_section
+
+  -- We only care about sections that have a useful amount of content
+  where length(page_section.content) >= min_content_length
+
+  -- The dot product is negative because of a Postgres limitation, so we negate it
+  and (page_section.embedding operator(public.<#>) embedding) * -1 > match_threshold
+
+  -- OpenAI embeddings are normalized to length 1, so
+  -- cosine similarity and dot product will produce the same results.
+  -- Using dot product which can be computed slightly faster.
+  --
+  -- For the different syntaxes, see https://github.com/pgvector/pgvector
+  order by page_section.embedding operator(public.<#>) embedding;
+end;
+$$;
+
+create or replace function ipv6_active_status (
+  project_ref text
+)
+returns table (
+  pgbouncer_active boolean,
+  vercel_active boolean
+)
+set search_path = '' 
+as $$
+declare
+  pgbouncer_active boolean;
+  vercel_active boolean;
+begin
+  select exists (
+    select 1 
+    from public.active_pgbouncer_projects ap
+    where ap.project_ref = $1
+  ) into pgbouncer_active;
+
+  select exists (
+    select 1
+    from public.vercel_project_connections_without_supavisor vp
+    where vp.project_ref = $1
+  ) into vercel_active;
+
+  return query select pgbouncer_active, vercel_active;
+end;
+$$ language plpgsql security definer;
+
+create or replace function docs_search_embeddings(
+  embedding vector(1536),
+  match_threshold float
+)
+returns table (
+  id int8,
+  path text,
+  type text,
+  title text,
+  subtitle text,
+  description text,
+  headings text[],
+  slugs text[]
+)
+language plpgsql
+set search_path = ''
+as $$
+#variable_conflict use_variable
+begin
+  return query
+  with match as(
+	select *
+	from public.page_section
+	-- The dot product is negative because of a Postgres limitation, so we negate it
+	where (page_section.embedding operator(public.<#>) embedding) * -1 > match_threshold	
+	-- OpenAI embeddings are normalized to length 1, so
+	-- cosine similarity and dot product will produce the same results.
+	-- Using dot product which can be computed slightly faster.
+	--
+	-- For the different syntaxes, see https://github.com/pgvector/pgvector
+	order by page_section.embedding operator(public.<#>) embedding
+	limit 10
+  )
+  select
+	page.id,
+	page.path,
+	page.type,
+	page.meta ->> 'title' as title,
+	page.meta ->> 'subtitle' as title,
+	page.meta ->> 'description' as description,
+	array_agg(match.heading) as headings,
+	array_agg(match.slug) as slugs
+  from public.page
+  join match on match.page_id = page.id
+  group by page.id;
+end;
+$$;
+
+create or replace function docs_search_fts(query text)
+returns table (
+  id int8,
+  path text,
+  type text,
+  title text,
+  subtitle text,
+  description text
+)
+language plpgsql
+set search_path = ''
+as $$
+#variable_conflict use_variable
+begin
+  return query
+  select
+	page.id,
+	page.path,
+	page.type,
+	page.meta ->> 'title' as title,
+	page.meta ->> 'subtitle' as subtitle,
+	page.meta ->> 'description' as description
+  from public.page
+  where title_tokens @@ websearch_to_tsquery(query) or fts_tokens @@ websearch_to_tsquery(query)
+  order by greatest(
+	  -- Title is more important than body, so use 10 as the weighting factor
+	  -- Cut off at max rank of 1
+	  least(10 * ts_rank(title_tokens, websearch_to_tsquery(query)), 1),
+	  ts_rank(fts_tokens, websearch_to_tsquery(query))
+  ) desc
+  limit 10;
+end;
+$$;
+
+drop function public.match_page_sections;
+
+drop function public.get_page_parents;
\ No newline at end of file