openai/gpt-5.6-luna · d2_pgvector · rep 3

set -e
printf 'URL=%s\nREF=%s\n' "$SUPABASE_URL" "$SUPABASE_PROJECT_REF"
command -v psql || true
command -v curl || true
python3 - <<'PY'
import os
for k in ['SUPABASE_URL','SUPABASE_DB_URL','SUPABASE_ANON_KEY','SUPABASE_SERVICE_ROLE_KEY']:
 print(k, 'set' if os.getenv(k) else 'MISSING')
PY

URL=https://<ref>.supabase.co
REF=<ref>
/usr/bin/psql
/usr/bin/curl
SUPABASE_URL set
SUPABASE_DB_URL set
SUPABASE_ANON_KEY set
SUPABASE_SERVICE_ROLE_KEY set

set -e
psql "$SUPABASE_DB_URL" -v ON_ERROR_STOP=1 -P pager=off -c "select id,title,embedding_json from public.documents order by id;" -c "select name,default_version,installed_version from pg_available_extensions where name='vector';"

 id |  title  |  embedding_json  
----+---------+------------------
  1 | alpha   | [10, 0.5, 0, 0]
  2 | bravo   | [0.9, 0.3, 0, 0]
  3 | delta   | [20, 60, 0, 0]
  4 | echo    | [0, 1, 0, 0]
  5 | foxtrot | [-5, 0.1, 0, 0]
  6 | golf    | [0.1, 0.1, 3, 4]
(6 rows)

  name  | default_version | installed_version 
--------+-----------------+-------------------
 vector | 0.8.2           | 
(1 row)

set -e
psql "$SUPABASE_DB_URL" -v ON_ERROR_STOP=1 -P pager=off <<'SQL'
create extension if not exists vector with schema extensions;

alter table public.documents
  add column if not exists embedding extensions.vector(4);

update public.documents
set embedding = embedding_json::text::extensions.vector
where embedding_json is not null;

create index if not exists documents_embedding_hnsw_cosine_idx
  on public.documents using hnsw (embedding extensions.vector_cosine_ops);

create or replace function public.match_documents(
  query_embedding extensions.vector(4),
  match_count integer
)
returns table (id integer, title text, distance double precision)
language sql
stable
as $$
  select d.id, d.title,
         (d.embedding <=> query_embedding)::double precision as distance
  from public.documents as d
  where d.embedding is not null
  order by d.embedding <=> query_embedding
  limit match_count;
$$;

grant execute on function public.match_documents(extensions.vector, integer) to anon;
SQL

psql "$SUPABASE_DB_URL" -v ON_ERROR_STOP=1 -P pager=off -c "select id,title,embedding from public.documents order by id;" -c "select indexname,indexdef from pg_indexes where schemaname='public' and tablename='documents';" -c "select * from public.match_documents('[1,0,0,0]'::extensions.vector(4), 3);"

CREATE EXTENSION
ALTER TABLE
UPDATE 6
CREATE INDEX
CREATE FUNCTION
GRANT
 id |  title  |   embedding   
----+---------+---------------
  1 | alpha   | [10,0.5,0,0]
  2 | bravo   | [0.9,0.3,0,0]
  3 | delta   | [20,60,0,0]
  4 | echo    | [0,1,0,0]
  5 | foxtrot | [-5,0.1,0,0]
  6 | golf    | [0.1,0.1,3,4]
(6 rows)

              indexname              |                                                   indexdef                                                    
-------------------------------------+---------------------------------------------------------------------------------------------------------------
 documents_embedding_hnsw_cosine_idx | CREATE INDEX documents_embedding_hnsw_cosine_idx ON public.documents USING hnsw (embedding vector_cosine_ops)
 documents_pkey                      | CREATE UNIQUE INDEX documents_pkey ON public.documents USING btree (id)
(2 rows)

 id | title |      distance       
----+-------+---------------------
  1 | alpha | 0.00124766112215546
  2 | bravo |  0.0513167145152487
  3 | delta |   0.683772233983162
(3 rows)

set -e
curl --fail-with-body -sS -X POST "$SUPABASE_URL/rest/v1/rpc/match_documents" \
  -H "apikey: $SUPABASE_ANON_KEY" \
  -H "Authorization: Bearer $SUPABASE_ANON_KEY" \
  -H "Content-Type: application/json" \
  -d '{"query_embedding":[1,0,0,0],"match_count":3}' | tee /tmp/match.json
printf '\n'

[{"id":1,"title":"alpha","distance":0.00124766112215546}, 
 {"id":2,"title":"bravo","distance":0.0513167145152487}, 
 {"id":3,"title":"delta","distance":0.683772233983162}]