How do you store and query vector embeddings with pgvector in a real schema design?

-- Pattern 1: Embedding column on the same table as the content
CREATE TABLE articles (
    id           BIGSERIAL   PRIMARY KEY,
    title        TEXT        NOT NULL,
    body         TEXT        NOT NULL,
    author_id    BIGINT      REFERENCES users(id),
    category     TEXT,
    published_at TIMESTAMPTZ,
    is_published BOOLEAN     DEFAULT FALSE,
    embedding    VECTOR(1536)                    -- text-embedding-3-small
);

-- Pattern 2: Separate embeddings table (useful when embedding
-- the same content with multiple models or at multiple granularities)
CREATE TABLE article_chunks (
    id           BIGSERIAL   PRIMARY KEY,
    article_id   BIGINT      REFERENCES articles(id) ON DELETE CASCADE,
    chunk_index  INTEGER,    -- which chunk within the article
    chunk_text   TEXT,
    embedding    VECTOR(1536),
    model_name   TEXT        DEFAULT 'text-embedding-3-small'
);

-- Pattern 3: Multi-modal embeddings (different models on different columns)
CREATE TABLE products (
    id              BIGSERIAL   PRIMARY KEY,
    name            TEXT,
    description     TEXT,
    image_url       TEXT,
    text_embedding  VECTOR(1536),   -- text-embedding-3-small on description
    image_embedding VECTOR(512)     -- CLIP on product image
);

-- Indexes on each:
CREATE INDEX ON articles        USING hnsw (embedding vector_cosine_ops);
CREATE INDEX ON article_chunks  USING hnsw (embedding vector_cosine_ops);
CREATE INDEX ON products        USING hnsw (text_embedding  vector_cosine_ops);
CREATE INDEX ON products        USING hnsw (image_embedding vector_cosine_ops);