"""Initial schema Revision ID: 001 Revises: Create Date: 2026-02-22 """ from typing import Sequence, Union import sqlalchemy as sa from alembic import op from pgvector.sqlalchemy import Vector revision: str = "001" down_revision: Union[str, None] = None branch_labels: Union[str, Sequence[str], None] = None depends_on: Union[str, Sequence[str], None] = None def upgrade() -> None: # Enable pgvector extension op.execute("CREATE EXTENSION IF NOT EXISTS vector") # Tracks op.create_table( "tracks", sa.Column("id", sa.BigInteger, primary_key=True), sa.Column("title", sa.Text, nullable=False), sa.Column("artist", sa.Text, nullable=False), sa.Column("album", sa.Text), sa.Column("fingerprint", sa.Text, unique=True, nullable=False), sa.Column("lastfm_url", sa.Text), sa.Column("itunes_track_id", sa.BigInteger), sa.Column("itunes_preview_url", sa.Text), sa.Column("apple_music_id", sa.Text), sa.Column("duration_ms", sa.Integer), sa.Column("genre", sa.Text), sa.Column("embedding_status", sa.Text, nullable=False, server_default="pending"), sa.Column("embedding_error", sa.Text), sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.func.now()), sa.Column("updated_at", sa.DateTime(timezone=True), server_default=sa.func.now()), ) # Listen events op.create_table( "listen_events", sa.Column("id", sa.BigInteger, primary_key=True), sa.Column("track_id", sa.BigInteger, sa.ForeignKey("tracks.id"), nullable=False), sa.Column("source", sa.Text, nullable=False, server_default="music_assistant"), sa.Column("speaker_name", sa.Text), sa.Column("listened_at", sa.DateTime(timezone=True), server_default=sa.func.now()), sa.Column("duration_played", sa.Integer), sa.Column("raw_payload", sa.dialects.postgresql.JSONB), ) # Track embeddings (512-dim CLAP) op.create_table( "track_embeddings", sa.Column("id", sa.BigInteger, primary_key=True), sa.Column("track_id", sa.BigInteger, sa.ForeignKey("tracks.id"), unique=True, nullable=False), sa.Column("embedding", Vector(512), nullable=False), sa.Column("model_version", sa.Text, nullable=False, server_default="laion/larger_clap_music"), sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.func.now()), ) op.execute( "CREATE INDEX ix_track_embeddings_hnsw ON track_embeddings " "USING hnsw (embedding vector_cosine_ops)" ) # Similarity links op.create_table( "similarity_links", sa.Column("id", sa.BigInteger, primary_key=True), sa.Column("source_track_id", sa.BigInteger, sa.ForeignKey("tracks.id"), nullable=False), sa.Column("target_track_id", sa.BigInteger, sa.ForeignKey("tracks.id"), nullable=False), sa.Column("lastfm_match", sa.REAL), sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.func.now()), sa.UniqueConstraint("source_track_id", "target_track_id", name="uq_similarity_link"), ) # Taste profiles op.create_table( "taste_profiles", sa.Column("id", sa.BigInteger, primary_key=True), sa.Column("name", sa.Text, unique=True, nullable=False, server_default="default"), sa.Column("embedding", Vector(512), nullable=False), sa.Column("track_count", sa.Integer, nullable=False), sa.Column("updated_at", sa.DateTime(timezone=True), server_default=sa.func.now()), ) # Playlists op.create_table( "playlists", sa.Column("id", sa.BigInteger, primary_key=True), sa.Column("name", sa.Text), sa.Column("known_pct", sa.Integer, nullable=False), sa.Column("total_tracks", sa.Integer, nullable=False), sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.func.now()), ) op.create_table( "playlist_tracks", sa.Column("id", sa.BigInteger, primary_key=True), sa.Column("playlist_id", sa.BigInteger, sa.ForeignKey("playlists.id", ondelete="CASCADE"), nullable=False), sa.Column("track_id", sa.BigInteger, sa.ForeignKey("tracks.id"), nullable=False), sa.Column("position", sa.Integer, nullable=False), sa.Column("is_known", sa.Boolean, nullable=False), sa.Column("similarity_score", sa.REAL), ) def downgrade() -> None: op.drop_table("playlist_tracks") op.drop_table("playlists") op.drop_table("taste_profiles") op.drop_table("similarity_links") op.execute("DROP INDEX IF EXISTS ix_track_embeddings_hnsw") op.drop_table("track_embeddings") op.drop_table("listen_events") op.drop_table("tracks") op.execute("DROP EXTENSION IF EXISTS vector")