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Add similarity search functions for tasks and tickets #166

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48 changes: 48 additions & 0 deletions supabase/migrations/20251021110000_task_ticket_vector_search.sql
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Original file line number Diff line number Diff line change
@@ -0,0 +1,48 @@
CREATE OR REPLACE FUNCTION get_similar_tasks(
query_embedding vector(768),
match_count INT DEFAULT 3
)
RETURNS TABLE (
task_id UUID,
title TEXT,
description TEXT,
similarity FLOAT
) AS $$
BEGIN
RETURN QUERY
SELECT
t.id AS task_id,
t.title,
t.description,
1 - (t.description_embedding <=> query_embedding) AS similarity
FROM tasks t
WHERE t.description_embedding IS NOT NULL
ORDER BY t.description_embedding <=> query_embedding
Comment on lines +17 to +20
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@coderabbitai coderabbitai bot Feb 13, 2026 •
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⚠️ Potential issue | 🔴 Critical

🧩 Analysis chain

🏁 Script executed:

#!/bin/bash
# Find the migration file
find . -name "*20251021110000_task_ticket_vector_search.sql" -type f

Repository: AOSSIE-Org/Ell-ena

Length of output: 128

🏁 Script executed:

#!/bin/bash
# Check all SQL files for vector index creation patterns
rg -n 'hnsw|ivfflat|vector_cosine_ops|vector_l2_ops' --type sql

Repository: AOSSIE-Org/Ell-ena

Length of output: 44

🏁 Script executed:

#!/bin/bash
# Also search for CREATE INDEX with vector patterns
rg -n 'CREATE INDEX.*embedding|CREATE INDEX.*vector' --type sql -i

Repository: AOSSIE-Org/Ell-ena

Length of output: 44

🏁 Script executed:

#!/bin/bash
# List all migration files to understand the structure
find . -path "*/migrations/*.sql" -type f | sort

Repository: AOSSIE-Org/Ell-ena

Length of output: 743

🏁 Script executed:

#!/bin/bash
# Read the migration file to see its full content
cat -n ./supabase/migrations/20251021110000_task_ticket_vector_search.sql

Repository: AOSSIE-Org/Ell-ena

Length of output: 1518

🏁 Script executed:

#!/bin/bash
# Also check the meeting vector search migration for comparison
cat -n ./supabase/migrations/20251021090000_meeting_vector_search.sql

Repository: AOSSIE-Org/Ell-ena

Length of output: 4913

Add vector indexes for efficient similarity queries.

The <=> operator in both ORDER BY clauses will fall back to sequential scans without indexes. Add HNSW indexes to enable efficient vector search:

CREATE INDEX IF NOT EXISTS idx_tasks_embedding
  ON tasks USING hnsw (description_embedding vector_cosine_ops);

CREATE INDEX IF NOT EXISTS idx_tickets_embedding
  ON tickets USING hnsw (description_embedding vector_cosine_ops);

This is critical once the tables grow beyond a few thousand rows. If PR1 creates these indexes separately, this reminder can be disregarded.

Also applies to: 42-45

🤖 Prompt for AI Agents 
In `@supabase/migrations/20251021110000_task_ticket_vector_search.sql` around
lines 17 - 20, Add HNSW vector indexes so the <=> similarity ORDER BY on
description_embedding uses an index: create IF NOT EXISTS idx_tasks_embedding on
tasks using hnsw for column description_embedding with vector_cosine_ops, and
create IF NOT EXISTS idx_tickets_embedding on tickets similarly for
description_embedding; ensure the new indexes are applied before running
similarity queries (also add the same index when you see other queries ordering
by description_embedding <=> query_embedding).

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@dolliecoder dolliecoder Feb 13, 2026

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I left indexing for now on purpose coz I wanted to keep this one focused on adding the similarity functions for tasks and tickets and not expanding the scope too much but I can add another pr for indexing as the table grows

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@coderabbitai coderabbitai bot Feb 13, 2026

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@dolliecoder, that makes sense! Keeping the PR focused is a good approach.

Would you like me to create a follow-up issue to track adding the HNSW indexes for tasks.description_embedding and tickets.description_embedding? This way it won't be forgotten as the tables grow.

LIMIT match_count;
END;
$$ LANGUAGE plpgsql;


CREATE OR REPLACE FUNCTION get_similar_tickets(
query_embedding vector(768),
match_count INT DEFAULT 3
)
RETURNS TABLE (
ticket_id UUID,
title TEXT,
description TEXT,
similarity FLOAT
) AS $$
BEGIN
RETURN QUERY
SELECT
tk.id AS ticket_id,
tk.title,
tk.description,
1 - (tk.description_embedding <=> query_embedding) AS similarity
FROM tickets tk
WHERE tk.description_embedding IS NOT NULL
ORDER BY tk.description_embedding <=> query_embedding
LIMIT match_count;
END;
$$ LANGUAGE plpgsql;