cim_summary/backend/create-rpc-function.js

const { createClient } = require('@supabase/supabase-js');

// Load environment variables
require('dotenv').config();

const supabaseUrl = process.env.SUPABASE_URL;
const supabaseServiceKey = process.env.SUPABASE_SERVICE_KEY;

const supabase = createClient(supabaseUrl, supabaseServiceKey);

async function createRPCFunction() {
    console.log('🚀 Creating match_document_chunks RPC function in Supabase...');
    
    // The SQL to create the vector search function
    const createFunctionSQL = `
CREATE OR REPLACE FUNCTION match_document_chunks(
    query_embedding VECTOR(1536),
    match_threshold FLOAT DEFAULT 0.7,
    match_count INTEGER DEFAULT 10
)
RETURNS TABLE (
    id UUID,
    document_id TEXT,
    content TEXT,
    metadata JSONB,
    chunk_index INTEGER,
    similarity FLOAT
)
LANGUAGE SQL STABLE
AS $$
    SELECT
        document_chunks.id,
        document_chunks.document_id,
        document_chunks.content,
        document_chunks.metadata,
        document_chunks.chunk_index,
        1 - (document_chunks.embedding <=> query_embedding) AS similarity
    FROM document_chunks
    WHERE document_chunks.embedding IS NOT NULL
    AND 1 - (document_chunks.embedding <=> query_embedding) > match_threshold
    ORDER BY document_chunks.embedding <=> query_embedding
    LIMIT match_count;
$$;
    `;
    
    // Try to execute via a simple query since we can't use rpc to create rpc
    console.log('📝 Function SQL prepared');
    console.log('');
    console.log('🛠️  Please run this SQL in the Supabase SQL Editor:');
    console.log('1. Go to https://supabase.com/dashboard/project/gzoclmbqmgmpuhufbnhy/sql');
    console.log('2. Paste and run the following SQL:');
    console.log('');
    console.log('-- Enable pgvector extension (if not already enabled)');
    console.log('CREATE EXTENSION IF NOT EXISTS vector;');
    console.log('');
    console.log(createFunctionSQL);
    console.log('');
    console.log('-- Test the function');
    console.log('SELECT match_document_chunks(');
    console.log("  ARRAY[" + new Array(1536).fill('0.1').join(',') + "]::vector,");
    console.log('  0.5,');
    console.log('  5');
    console.log(');');
    
    // Let's try to test if the function exists after creation
    console.log('');
    console.log('🧪 After running the SQL, test with:');
    console.log('node test-vector-search.js');
}

createRPCFunction();