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Supabase vector self querying retriever #10304

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merged 7 commits into from
Sep 7, 2023
Merged

Supabase vector self querying retriever #10304

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d64f3ee
feat: supabase vector self querying
gregnr Sep 6, 2023
14a172d
fix: tests, formatting, linting
gregnr Sep 6, 2023
4537a1c
fix: raise exception if comparator isn't supported
gregnr Sep 7, 2023
40ff358
fix: enum value on v3.11
gregnr Sep 7, 2023
398c8e4
fix: lint errors
gregnr Sep 7, 2023
14fad20
Merge branch 'master' into feat/supabase-vector-self-query
gregnr Sep 7, 2023
13dcadc
fix: remove contain from supabase allowed comparators
gregnr Sep 7, 2023
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68 changes: 33 additions & 35 deletions docs/extras/integrations/vectorstores/supabase.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -28,43 +28,41 @@
"The following function determines cosine similarity, but you can adjust to your needs.\n",
"\n",
"```sql\n",
" -- Enable the pgvector extension to work with embedding vectors\n",
" create extension vector;\n",
"-- Enable the pgvector extension to work with embedding vectors\n",
"create extension if not exists vector;\n",
"\n",
" -- Create a table to store your documents\n",
" create table documents (\n",
" id uuid primary key,\n",
" content text, -- corresponds to Document.pageContent\n",
" metadata jsonb, -- corresponds to Document.metadata\n",
" embedding vector(1536) -- 1536 works for OpenAI embeddings, change if needed\n",
" );\n",
"-- Create a table to store your documents\n",
"create table\n",
" documents (\n",
" id uuid primary key,\n",
" content text, -- corresponds to Document.pageContent\n",
" metadata jsonb, -- corresponds to Document.metadata\n",
" embedding vector (1536) -- 1536 works for OpenAI embeddings, change if needed\n",
" );\n",
"\n",
" CREATE FUNCTION match_documents(query_embedding vector(1536), match_count int)\n",
" RETURNS TABLE(\n",
" id uuid,\n",
" content text,\n",
" metadata jsonb,\n",
" -- we return matched vectors to enable maximal marginal relevance searches\n",
" embedding vector(1536),\n",
" similarity float)\n",
" LANGUAGE plpgsql\n",
" AS $$\n",
" # variable_conflict use_column\n",
" BEGIN\n",
" RETURN query\n",
" SELECT\n",
" id,\n",
" content,\n",
" metadata,\n",
" embedding,\n",
" 1 -(documents.embedding <=> query_embedding) AS similarity\n",
" FROM\n",
" documents\n",
" ORDER BY\n",
" documents.embedding <=> query_embedding\n",
" LIMIT match_count;\n",
" END;\n",
" $$;\n",
"-- Create a function to search for documents\n",
"create function match_documents (\n",
" query_embedding vector (1536),\n",
" filter jsonb default '{}'\n",
") returns table (\n",
" id uuid,\n",
" content text,\n",
" metadata jsonb,\n",
" similarity float\n",
") language plpgsql as $$\n",
"#variable_conflict use_column\n",
"begin\n",
" return query\n",
" select\n",
" id,\n",
" content,\n",
" metadata,\n",
" 1 - (documents.embedding <=> query_embedding) as similarity\n",
" from documents\n",
" where metadata @> filter\n",
" order by documents.embedding <=> query_embedding;\n",
"end;\n",
"$$;\n",
"```"
]
},
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