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-- Enable extension vector
create extension vector;
-- Create documents table to hold embeddings
CREATE TABLE IF NOT EXISTS court_opinion (
id SERIAL PRIMARY KEY,
embedding vector(768),
opinion text,
created_at timestamptz DEFAULT now()
);
CREATE TABLE IF NOT EXISTS alito (
id SERIAL PRIMARY KEY,
embedding vector(768),
opinion text,
created_at timestamptz DEFAULT now()
);
CREATE TABLE IF NOT EXISTS barrett (
id SERIAL PRIMARY KEY,
embedding vector(768),
opinion text,
created_at timestamptz DEFAULT now()
);
CREATE TABLE IF NOT EXISTS breyer (
id SERIAL PRIMARY KEY,
embedding vector(768),
opinion text,
created_at timestamptz DEFAULT now()
);
CREATE TABLE IF NOT EXISTS ginsburg (
id SERIAL PRIMARY KEY,
embedding vector(768),
opinion text,
created_at timestamptz DEFAULT now()
);
CREATE TABLE IF NOT EXISTS gorsuch (
id SERIAL PRIMARY KEY,
embedding vector(768),
opinion text,
created_at timestamptz DEFAULT now()
);
CREATE TABLE IF NOT EXISTS jackson (
id SERIAL PRIMARY KEY,
embedding vector(768),
opinion text,
created_at timestamptz DEFAULT now()
);
CREATE TABLE IF NOT EXISTS kagan (
id SERIAL PRIMARY KEY,
embedding vector(768),
opinion text,
created_at timestamptz DEFAULT now()
);
CREATE TABLE IF NOT EXISTS kavanaugh (
id SERIAL PRIMARY KEY,
embedding vector(768),
opinion text,
created_at timestamptz DEFAULT now()
);
CREATE TABLE IF NOT EXISTS kennedy (
id SERIAL PRIMARY KEY,
embedding vector(768),
opinion text,
created_at timestamptz DEFAULT now()
);
CREATE TABLE IF NOT EXISTS roberts (
id SERIAL PRIMARY KEY,
embedding vector(768),
opinion text,
created_at timestamptz DEFAULT now()
);
CREATE TABLE IF NOT EXISTS scalia (
id SERIAL PRIMARY KEY,
embedding vector(768),
opinion text,
created_at timestamptz DEFAULT now()
);
CREATE TABLE IF NOT EXISTS sotomayor (
id SERIAL PRIMARY KEY,
embedding vector(768),
opinion text,
created_at timestamptz DEFAULT now()
);
CREATE TABLE IF NOT EXISTS thomas (
id SERIAL PRIMARY KEY,
embedding vector(768),
opinion text,
created_at timestamptz DEFAULT now()
);
-- Create function for similarity search
-- create or replace function match_documents (
-- query_embedding vector(768),
-- match_table text,
-- match_threshold float,
-- match_count int
-- )
-- returns table (
-- id bigint,
-- content text,
-- similarity float
-- )
-- language sql stable
-- as $$
-- select
-- match_table.id,
-- match_table.opinion,
-- 1 - (match_table.embedding <=> query_embedding) as similarity
-- from match_table
-- where 1 - (match_table.embedding <=> query_embedding) > match_threshold
-- order by similarity desc
-- limit match_count;
-- $$;
-- Instantiate HNSW indexes
-- create index on items using hnsw (column_name vector_l2_ops);
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