update system to use find Highlights *not tested

package/video_editing/highlights.py

@@ -267,20 +267,48 @@ def format_timestamp(seconds):
     return f"{h:02d}:{m:02d}:{s:02d}" if h > 0 else f"{m:02d}:{s:02d}"
 
 def highlights(video_path, keywords=None, top_n=5, clip_len=8, min_gap=12):
-    if keywords is None:
-        keywords = DEFAULT_KEYWORDS
-
     av_score, duration = get_av_scores(video_path, sample_fps=0.5)
+    
     segments = load_text_from_srt(video_path.replace('.mp4', '.srt')) 
     kw_score, kw_hits = score_keywords(segments, duration, keywords)
 
+    # FINAL SCORE: AV + keyword boost (keyword is huge if found)
     final_score = av_score + (kw_score * 1.5)
     final_score = (final_score - final_score.min()) / (final_score.max() - final_score.min() + 1e-6)
-    final_score = np.convolve(final_score, np.ones(3)/3, mode='same')
+    final_score = np.convolve(final_score, np.ones(3)/3, mode='same') # smooth
 
     highlights = find_highlights(final_score, duration, top_n=top_n, clip_len=clip_len)
 
-    return highlights, kw_hits
+    # --- OUTPUT ---
+    print("\n" + "="*60)
+    print("KEYWORD HITS:")
+    for h in kw_hits:
+        print(f" [{format_timestamp(h['timestamp'])}] ({h['keyword']}) -> {h['text']}")
+
+    print("\n" + "="*60)
+    print("FINAL HIGHLIGHTS:")
+    output_data = []
+    for i, (start, end, score) in enumerate(highlights, 1):
+        # find transcript in that window
+        texts_in_window = [s['text'].strip() for s in segments if not (s['end'] < start or s['start'] > end)]
+        transcript = " ".join(texts_in_window)[:120]
+
+        print(f"{i}. {format_timestamp(start)} - {format_timestamp(end)} (score {score:.2f}) | {transcript}")
+        output_data.append({
+            "id": i,
+            "start_sec": float(start),
+            "end_sec": float(end),
+            "start_timestamp": format_timestamp(start),
+            "end_timestamp": format_timestamp(end),
+            "score": float(score),
+            "transcript": transcript
+        })
+
+    # Save timestamps to JSON
+    with open("highlights.json", "w") as f:
+        json.dump({"video": video_path, "keywords": keywords, "highlights": output_data, "keyword_hits": kw_hits}, f, indent=2)
+    print(f"\nTimestamps saved to highlights.json")
+
 
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description="Find highlights with Whisper keywords + timestamps")