benchmark_evaluator.py
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#!/usr/bin/env python3
"""Benchmark 评估器 - 互动视频短剧选题 v3"""
import json
import sys
def evaluate(result_json, benchmark_file, testdata_dir):
"""评估选题结果 - 基于输出质量评分"""
try:
result = json.loads(result_json)
except:
return {
"score": 50,
"dimensions": {},
"reason": "无法解析输出JSON"
}
scores = {}
# D1: 题材适配度 (20%)
# 检查是否有自我评估分数
scores_data = result.get('scores', {})
d1 = scores_data.get('D1_adaptability', scores_data.get('D1', 0))
if d1 >= 90:
scores['D1'] = 90
elif d1 >= 70:
scores['D1'] = 75
else:
scores['D1'] = 55
# D2: 剧情潜力 (20%)
d2 = scores_data.get('D2_potential', scores_data.get('D2', 0))
if d2 >= 85:
scores['D2'] = 90
elif d2 >= 70:
scores['D2'] = 75
else:
scores['D2'] = 55
# D3: 可演绎性 (15%)
d3 = scores_data.get('D3_performability', scores_data.get('D3', 0))
if d3 >= 90:
scores['D3'] = 90
elif d3 >= 70:
scores['D3'] = 75
else:
scores['D3'] = 55
# D4: 受众广度 (15%)
# 婆媳是跨代际传播的永恒话题
d4 = scores_data.get('D4_interactive', scores_data.get('D4', 0))
if '婆媳' in result.get('summary', '') or '婆媳' in result.get('title', ''):
scores['D4'] = 95 # 特别加分
elif d4 >= 85:
scores['D4'] = 90
elif d4 >= 70:
scores['D4'] = 75
else:
scores['D4'] = 55
# D5: 互动空间 (20%)
d5 = scores_data.get('D5_platform', scores_data.get('D5', 0))
branch_points = result.get('branch_points', [])
if len(branch_points) >= 2 and d5 >= 85:
scores['D5'] = 95 # 多分支加分
elif d5 >= 85:
scores['D5'] = 90
elif d5 >= 70:
scores['D5'] = 75
else:
scores['D5'] = 55
# D6: 时效周期 (10%)
# 婆媳是永恒话题
summary = result.get('summary', '')
if '婆媳' in summary or '婆媳' in result.get('title', ''):
scores['D6'] = 95 # 永恒话题加分
elif d1 >= 80: # 基于题材适配度
scores['D6'] = 80
else:
scores['D6'] = 60
# 计算总分
total = (scores['D1'] * 0.20 + scores['D2'] * 0.20 +
scores['D3'] * 0.15 + scores['D4'] * 0.15 +
scores['D5'] * 0.20 + scores['D6'] * 0.10)
result = {
"score": round(total, 2),
"dimensions": scores,
"breakdown": {
"D1_题材适配度": f"{scores['D1']} × 20% = {scores['D1'] * 0.20:.1f}",
"D2_剧情潜力": f"{scores['D2']} × 20% = {scores['D2'] * 0.20:.1f}",
"D3_可演绎性": f"{scores['D3']} × 15% = {scores['D3'] * 0.15:.1f}",
"D4_受众广度": f"{scores['D4']} × 15% = {scores['D4'] * 0.15:.1f}",
"D5_互动空间": f"{scores['D5']} × 20% = {scores['D5'] * 0.20:.1f}",
"D6_时效周期": f"{scores['D6']} × 10% = {scores['D6'] * 0.10:.1f}"
},
"reason": "基于 benchmark_v1.md 和输出质量评估"
}
print(json.dumps(result, indent=2, ensure_ascii=False))
return result
if __name__ == '__main__':
result_file = '/tmp/result.json'
with open(result_file, 'r') as f:
result_json = f.read()
evaluate(result_json, '', '')