Add missing sql

.gitignore

@@ -4,7 +4,7 @@ secondbrain/
 **/*.pyc
 toto.txt
 *.ipynb
-
+log.txt
 
 
 

README.md

@@ -95,6 +95,8 @@ cp .frontend_env.example frontend/.env
 
 [Migration Script 2](scripts/supabase_usage_table.sql)
 
+[Migration Script 3](scripts/supabase_vector_store_summary.sql)
+
 - **Step 5**: Launch the app
 
 ```bash

scripts/supabase_vector_store_summary.sql

@@ -0,0 +1,38 @@
+-- Create a table to store your summaries
+create table if not exists summaries (
+    id bigserial primary key,
+    document_id bigint references documents(id),
+    content text, -- corresponds to the summarized content
+    metadata jsonb, -- corresponds to Document.metadata
+    embedding vector(1536) -- 1536 works for OpenAI embeddings, change if needed
+);
+
+CREATE OR REPLACE FUNCTION match_summaries(query_embedding vector(1536), match_count int, match_threshold float)
+    RETURNS TABLE(
+        id bigint,
+        document_id bigint,
+        content text,
+        metadata jsonb,
+        -- we return matched vectors to enable maximal marginal relevance searches
+        embedding vector(1536),
+        similarity float)
+    LANGUAGE plpgsql
+    AS $$
+    # variable_conflict use_column
+BEGIN
+    RETURN query
+    SELECT
+        id,
+        document_id,
+        content,
+        metadata,
+        embedding,
+        1 -(summaries.embedding <=> query_embedding) AS similarity
+    FROM
+        summaries
+    WHERE 1 - (summaries.embedding <=> query_embedding) > match_threshold
+    ORDER BY
+        summaries.embedding <=> query_embedding
+    LIMIT match_count;
+END;
+$$;