feat(v3): PR 6 — HookOptimizer + MicroSignals (3 signals)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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sinmb79
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"""
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bots/quality
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Quality signal computation for shorts content.
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V3.0 signals:
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- motion_variation_score
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- script_diversity_score
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- tts_cost_efficiency
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V3.1+ additions:
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- semantic_visual_score
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- caption_overlap_score
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- pacing_variation_score
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"""
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from .micro_signals import compute_signal, SIGNALS_V1
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__all__ = ['compute_signal', 'SIGNALS_V1']
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"""
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bots/quality/micro_signals.py
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Micro-failure quality signals for shorts content.
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V3.0 scope: 3 signals
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- motion_variation_score: detects repetitive motion patterns
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- script_diversity_score: detects structural overlap with recent scripts
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- tts_cost_efficiency: monitors TTS credit usage
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Each signal returns a float 0.0-1.0 where:
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- 1.0 = perfect / no issue
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- 0.0 = critical problem
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- threshold = action trigger point
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"""
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import logging
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from pathlib import Path
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from typing import Callable, Any
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logger = logging.getLogger(__name__)
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SIGNALS_V1 = {
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'motion_variation_score': {
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'description': 'Consecutive clips using same motion pattern',
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'threshold': 0.6,
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'action': 'auto_fix', # pick different pattern automatically
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'higher_is_better': True,
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},
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'script_diversity_score': {
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'description': 'Script structure overlap with last 7 days',
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'threshold': 0.5,
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'action': 'regenerate', # request different structure from LLM
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'higher_is_better': True,
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},
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'tts_cost_efficiency': {
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'description': 'TTS credit usage vs monthly limit',
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'threshold': 0.8,
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'action': 'switch_engine', # downgrade to local TTS
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'higher_is_better': False, # lower usage = better
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},
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}
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def compute_signal(signal_name: str, **kwargs) -> float:
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"""
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Compute a quality signal value.
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Args:
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signal_name: One of SIGNALS_V1 keys
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**kwargs: Signal-specific inputs (see individual compute functions)
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Returns: float 0.0-1.0
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Raises: ValueError if signal_name unknown
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"""
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if signal_name not in SIGNALS_V1:
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raise ValueError(f'Unknown signal: {signal_name}. Available: {list(SIGNALS_V1.keys())}')
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compute_fns = {
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'motion_variation_score': _compute_motion_variation,
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'script_diversity_score': _compute_script_diversity,
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'tts_cost_efficiency': _compute_tts_cost_efficiency,
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}
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fn = compute_fns[signal_name]
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try:
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value = fn(**kwargs)
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logger.debug(f'[품질] {signal_name} = {value:.3f}')
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return value
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except Exception as e:
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logger.warning(f'[품질] 신호 계산 실패 ({signal_name}): {e}')
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return 1.0 # Neutral value on error (don't trigger action)
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def check_and_act(signal_name: str, value: float) -> dict:
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"""
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Check if signal value crosses threshold and return action.
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Returns: {
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'triggered': bool,
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'action': str or None,
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'value': float,
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'threshold': float,
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}
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"""
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if signal_name not in SIGNALS_V1:
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return {'triggered': False, 'action': None, 'value': value, 'threshold': 0}
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config = SIGNALS_V1[signal_name]
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threshold = config['threshold']
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higher_is_better = config.get('higher_is_better', True)
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if higher_is_better:
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triggered = value < threshold
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else:
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triggered = value > threshold
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return {
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'triggered': triggered,
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'action': config['action'] if triggered else None,
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'value': value,
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'threshold': threshold,
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}
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def _compute_motion_variation(clips: list, **kwargs) -> float:
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"""
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Compute motion variation score.
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Args:
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clips: list of dicts with 'pattern' key, e.g. [{'pattern': 'ken_burns_in'}, ...]
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Returns: 0.0-1.0 diversity score
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"""
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if not clips or len(clips) < 2:
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return 1.0
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patterns = [c.get('pattern', '') for c in clips if c.get('pattern')]
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if not patterns:
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return 1.0
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# Count consecutive same-pattern pairs
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consecutive_same = sum(
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1 for i in range(len(patterns) - 1)
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if patterns[i] == patterns[i+1]
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)
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# Unique patterns ratio
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unique_ratio = len(set(patterns)) / len(patterns)
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consecutive_penalty = consecutive_same / max(len(patterns) - 1, 1)
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score = unique_ratio * (1 - consecutive_penalty)
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return round(min(1.0, max(0.0, score)), 3)
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def _compute_script_diversity(script: dict, history: list = None, **kwargs) -> float:
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"""
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Compute script structure diversity vs recent history.
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Args:
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script: Current script dict with 'hook', 'body', 'closer'
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history: List of recent scripts (last 7 days), each same format
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Returns: 0.0-1.0 diversity score (1.0 = very diverse)
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"""
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if not history:
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return 1.0
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# Compare script structure fingerprints
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def _fingerprint(s: dict) -> tuple:
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hook = s.get('hook', '')
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body = s.get('body', [])
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closer = s.get('closer', '')
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return (
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len(hook) // 10, # rough length bucket
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len(body), # number of body sentences
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hook[:5] if hook else '', # hook start
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)
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current_fp = _fingerprint(script)
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overlaps = sum(
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1 for h in history
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if _fingerprint(h) == current_fp
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)
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overlap_rate = overlaps / len(history)
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return round(1.0 - overlap_rate, 3)
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def _compute_tts_cost_efficiency(usage: float, limit: float, **kwargs) -> float:
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"""
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Compute TTS cost efficiency.
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Args:
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usage: Characters used this period
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limit: Monthly/daily character limit
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Returns: ratio (usage/limit), where > threshold triggers engine switch
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"""
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if limit <= 0:
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return 0.0
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return round(min(1.0, usage / limit), 3)
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# ── Standalone test ──────────────────────────────────────────────
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if __name__ == '__main__':
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import sys
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if '--test' in sys.argv:
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print("=== Micro Signals Test ===")
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# Test motion variation
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test_clips = [
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{'pattern': 'ken_burns_in'},
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{'pattern': 'ken_burns_in'}, # repeat!
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{'pattern': 'pan_left'},
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{'pattern': 'pan_right'},
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]
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mv = compute_signal('motion_variation_score', clips=test_clips)
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result = check_and_act('motion_variation_score', mv)
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print(f"motion_variation_score = {mv:.3f} (triggered: {result['triggered']}, action: {result['action']})")
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# Test script diversity
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current_script = {'hook': '이거 모르면 손해', 'body': ['첫째', '둘째', '셋째'], 'closer': '구독'}
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history = [
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{'hook': '이거 모르면 손해2', 'body': ['a', 'b', 'c'], 'closer': '팔로우'},
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]
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sd = compute_signal('script_diversity_score', script=current_script, history=history)
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result2 = check_and_act('script_diversity_score', sd)
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print(f"script_diversity_score = {sd:.3f} (triggered: {result2['triggered']})")
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# Test TTS cost
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tce = compute_signal('tts_cost_efficiency', usage=8500, limit=10000)
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result3 = check_and_act('tts_cost_efficiency', tce)
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print(f"tts_cost_efficiency = {tce:.3f} (triggered: {result3['triggered']}, action: {result3['action']})")
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