import json

import duckdb
import pytest

from database import MotionDatabase


def test_fuse_for_window(tmp_path):
    db_path = str(tmp_path / "motions.db")

    # Create MotionDatabase (this will initialize schema except embeddings)
    db = MotionDatabase(db_path=db_path)

    # Create embeddings table (migration not run by MotionDatabase)
    conn = duckdb.connect(db_path)
    conn.execute("CREATE SEQUENCE IF NOT EXISTS embeddings_id_seq START 1")
    conn.execute(
        """
        CREATE TABLE IF NOT EXISTS embeddings (
            id INTEGER DEFAULT nextval('embeddings_id_seq'),
            motion_id INTEGER NOT NULL,
            model TEXT NOT NULL,
            vector JSON NOT NULL,
            created_at TIMESTAMP DEFAULT current_timestamp,
            PRIMARY KEY (id)
        )
        """
    )
    conn.close()

    # Insert 3 synthetic SVD vectors (k=4)
    svd1 = [0.1, 0.2, 0.3, 0.4]
    svd2 = [0.2, 0.1, 0.0, -0.1]
    svd3 = [0.9, 0.8, 0.7, 0.6]

    db.store_svd_vector("2024-Q1", "motion", "1", svd1)
    db.store_svd_vector("2024-Q1", "motion", "2", svd2)
    db.store_svd_vector("2024-Q1", "motion", "3", svd3)

    # Insert text embeddings for motions 1 and 2 (16 dims)
    text1 = [float(i) / 100.0 for i in range(16)]
    text2 = [float(i) / 50.0 for i in range(16)]

    conn = duckdb.connect(db_path)
    conn.execute(
        "INSERT INTO embeddings (motion_id, model, vector, created_at) VALUES (?, ?, ?, current_timestamp)",
        (1, "text-model-1", json.dumps(text1)),
    )
    conn.execute(
        "INSERT INTO embeddings (motion_id, model, vector, created_at) VALUES (?, ?, ?, current_timestamp)",
        (2, "text-model-1", json.dumps(text2)),
    )
    conn.close()

    # Import fuse function here to ensure module available
    from pipeline.fusion import fuse_for_window

    result = fuse_for_window("2024-Q1", db_path=db_path)

    assert result["inserted"] == 2
    assert result["skipped_missing_text"] == 1

    # Verify fused embeddings stored
    conn = duckdb.connect(db_path)
    rows = conn.execute(
        "SELECT motion_id, vector, svd_dims, text_dims FROM fused_embeddings WHERE window_id = ?",
        ("2024-Q1",),
    ).fetchall()
    conn.close()

    # Expect two rows for motions 1 and 2
    assert len(rows) == 2

    for motion_id, vector_json, svd_dims, text_dims in rows:
        vec = json.loads(vector_json)
        assert svd_dims == 4
        assert text_dims == 16
        assert len(vec) == 20