Create pacing.py

utils/pacing.py

@@ -0,0 +1,241 @@
+"""
+pacing.py
+---------------------------------------
+Retention & Pacing Optimization Engine (V8)
+
+Purpose:
+- Adjust video pacing for maximum retention
+- Compress slow segments
+- Emphasize high-value moments
+- Create TikTok / Reels optimized flow
+
+Works in CPU-only environments (FFmpeg-based).
+"""
+
+import subprocess
+import os
+
+
+# =====================================================
+# CONFIG
+# =====================================================
+
+OUTPUT_FILE = "pacing_optimized.mp4"
+
+SLOW_THRESHOLD = 1.25   # speed multiplier for slow segments
+FAST_THRESHOLD = 1.75   # speed multiplier for filler segments
+
+
+# =====================================================
+# BASIC SEGMENT ESTIMATION (NO ML DEPENDENCY)
+# =====================================================
+
+def estimate_segment_value(text):
+    """
+    Heuristic scoring system:
+    determines importance of spoken segment.
+    """
+
+    text = text.lower()
+
+    high_value_keywords = [
+        "you", "secret", "important", "stop",
+        "crazy", "insane", "listen", "this",
+        "money", "success", "life", "truth"
+    ]
+
+    filler_keywords = [
+        "um", "uh", "like", "you know", "so",
+        "actually", "basically"
+    ]
+
+    score = 1.0
+
+    # boost high value words
+    for w in high_value_keywords:
+        if w in text:
+            score += 0.6
+
+    # penalize filler speech
+    for w in filler_keywords:
+        if w in text:
+            score -= 0.4
+
+    return max(0.5, min(score, 2.0))
+
+
+# =====================================================
+# SPEED MAP GENERATOR
+# =====================================================
+
+def build_speed_map(words):
+    """
+    Converts transcript into pacing instructions
+    """
+
+    segments = []
+    buffer = []
+
+    for w in words:
+        buffer.append(w)
+
+        # group into micro segments
+        if len(buffer) >= 6:
+            segments.append(buffer)
+            buffer = []
+
+    if buffer:
+        segments.append(buffer)
+
+    speed_map = []
+
+    for seg in segments:
+
+        text = " ".join([w["word"] for w in seg])
+        score = estimate_segment_value(text)
+
+        start = seg[0]["start"]
+        end = seg[-1]["end"]
+
+        # decide speed
+        if score > 1.4:
+            speed = 1.0   # keep normal (important content)
+        elif score > 1.0:
+            speed = 1.15  # slight compression
+        else:
+            speed = FAST_THRESHOLD  # aggressive speed-up
+
+        speed_map.append({
+            "start": start,
+            "end": end,
+            "speed": speed
+        })
+
+    return speed_map
+
+
+# =====================================================
+# FFMEG FILTER BUILDER
+# =====================================================
+
+def build_filter(speed_map):
+    """
+    Creates FFmpeg atempo + setpts filter chain
+    """
+
+    filters = []
+
+    for i, seg in enumerate(speed_map):
+
+        start = seg["start"]
+        end = seg["end"]
+        speed = seg["speed"]
+
+        # video speed
+        filters.append(
+            f"[0:v]trim=start={start}:end={end},setpts=PTS/{speed}[v{i}]"
+        )
+
+        # audio speed
+        filters.append(
+            f"[0:a]atrim=start={start}:end={end},asetpts=PTS-STARTPTS,"
+            f"atempo={speed}[a{i}]"
+        )
+
+    v_streams = "".join([f"[v{i}]" for i in range(len(speed_map))])
+    a_streams = "".join([f"[a{i}]" for i in range(len(speed_map))])
+
+    filters.append(
+        f"{v_streams}{a_streams}concat=n={len(speed_map)}:v=1:a=1[outv][outa]"
+    )
+
+    return ";".join(filters)
+
+
+# =====================================================
+# MAIN ENGINE
+# =====================================================
+
+def optimize_pacing(video_path, words=None):
+    """
+    Main entry point for V8 pacing system
+    """
+
+    print("[PACING] Starting optimization...")
+
+    if not words:
+        print("[PACING] No transcript provided — returning original video")
+        return video_path
+
+    # Step 1: build speed map
+    speed_map = build_speed_map(words)
+
+    print(f"[PACING] Segments: {len(speed_map)}")
+
+    # Step 2: build ffmpeg filter
+    filter_complex = build_filter(speed_map)
+
+    output_path = OUTPUT_FILE
+
+    # Step 3: render optimized video
+    cmd = [
+        "ffmpeg", "-y",
+        "-i", video_path,
+        "-filter_complex", filter_complex,
+        "-map", "[outv]",
+        "-map", "[outa]",
+        "-c:v", "libx264",
+        "-preset", "ultrafast",
+        "-c:a", "aac",
+        output_path
+    ]
+
+    subprocess.run(cmd, check=True)
+
+    print("[PACING] Done:", output_path)
+
+    return output_path
+
+
+# =====================================================
+# LIGHTWEIGHT MODE (FAST FALLBACK)
+# =====================================================
+
+def fast_pacing(video_path):
+    """
+    Simple fallback: global speed-up only
+    """
+
+    output = "fast_pacing.mp4"
+
+    cmd = [
+        "ffmpeg", "-y",
+        "-i", video_path,
+        "-filter_complex",
+        "[0:v]setpts=0.92*PTS[v];[0:a]atempo=1.08[a]",
+        "-map", "[v]",
+        "-map", "[a]",
+        "-c:v", "libx264",
+        "-preset", "ultrafast",
+        "-c:a", "aac",
+        output
+    ]
+
+    subprocess.run(cmd, check=True)
+
+    return output
+
+
+# =====================================================
+# PUBLIC API
+# =====================================================
+
+def pacing_engine(video_path, words=None, mode="smart"):
+    """
+    Entry point used by main.py
+    """
+
+    if mode == "fast":
+        return fast_pacing(video_path)
+
+    return optimize_pacing(video_path, words)