from moviepy.video.io.VideoFileClip import VideoFileClip
from pathlib import Path
import sqlite3

# === Setup ===
input_video = Path("input/testVideoShort.mov")
output_dir = Path("output")
output_dir.mkdir(parents=True, exist_ok=True)

# === SQLite DB lesen ===
db_path = "clips_openai.db"
conn = sqlite3.connect(db_path)
cursor = conn.cursor()

# Nur die Top 10 Clips mit höchstem score_total
cursor.execute("""
    SELECT start, end, text
    FROM highlights
    ORDER BY score_total DESC
    LIMIT 10
""")
highlights = cursor.fetchall()

# === Video laden ===
video = VideoFileClip(str(input_video))

# === Clips schneiden ===
for i, (start, end, text) in enumerate(highlights):
    output_file = output_dir / f"highlight_{i+1}.mp4"
    end = min(end, video.duration)  # Sicherstellen, dass das Ende nicht über das Video hinausgeht
    print(f"🎬 Exportiere Clip {i+1}: {start:.2f}s – {end:.2f}s → {output_file.name}")
    clip = video.subclipped(start, end)
    clip.write_videofile(str(output_file), codec="libx264", audio_codec="aac")

# === Cleanup ===
conn.close()
video.close()
print("✅ Top 10 Clips exportiert.")