import re

with open("D:/AgentSkill/MCNVideo AI/project/编导AI脚本对话记录分析/剧本大纲情绪改善案例.html", "r", encoding="utf-8") as f:
    content = f.read()

# Time mappings per script
script1_times = ["0-4s","4-12s","12-20s","20-25s","25-32s","32-42s","42-55s","55-60s"]
script2_times = ["0-5s","5-12s","12-18s","18-25s","25-32s","32-42s","42-52s","52-60s"]
script3_times = ["0-5s","5-14s","14-20s","20-26s","26-32s","32-38s","38-52s","52-60s"]
script4_times = ["0-5s","5-12s","12-18s","18-24s","24-30s","30-38s","38-46s","46-54s","54-60s"]

# Scene content anchors for each script (unique keywords from each scene)
script1_anchors = ["\u5916\u5356\u7bb1\u91cc\u653e\u7740\u4e00\u4e2a\u7c89\u8272\u793c\u76d2", "\u4eca\u65e5\u5df2\u63a542\u5355", "\u7a81\u7136\u4e0b\u96e8", "\u96e8\u505c\u4e86\uff0c\u4ed6\u8def\u8fc7\u73a9\u5177\u5e97", "\u63a5\u5230\u6700\u540e\u4e00\u5355\uff0c\u9001\u5230\u540e\u5ba2\u4eba\u7ed9\u4e86\u5dee\u8bc4", "\u96e8\u4e2d\u9a91\u884c\u7279\u5199", "\u56de\u5230\u5bb6\uff0c\u5973\u513f\u5df2\u7761\u7740", "\u6700\u540e\u4e00\u4e2a\u955c\u5934\uff1a\u624b\u673a\u5c4f\u5e55"]
script2_anchors = ["\u5de5\u8d44\u5361\u653e\u5728\u684c\u4e0a\u63a8\u8fc7\u53bb", "\u4fbf\u5229\u5e97\u4e70\u4e24\u4e2a\u996d\u56e2", "\u5403\u996d\u6342\u80c3", "\u7537\u4e3b\u9000\u6389\u80c3\u836f", "\u9001\u56f4\u5dfe\u3002\u5973\u751f\u8bd5\u56f4\u5dfe", "\u65e5\u5e38\u8499\u592a\u5947", "\u5973\u751f\u628a\u56f4\u5dfe\u5305\u597d\u653e\u56de", "\u7537\u4e3b\u56de\u6765\u770b\u5230\u7eb8\u6761"]
script3_anchors = ["\u63a8\u95e8\u56de\u5bb6\uff0c\u5bf9\u7740\u7a7a\u5c4b\u5b50\u8bf4", "\u653e\u94a5\u5319\u65f6\u63a8\u4e86\u4e00\u4e0b\u8001\u82b1\u955c", "\u5403\u9762\uff0c\u558a", "\u51fa\u95e8\u5fd8\u5e26\u4f1e", "\u978b\u67dc\u4e0a\u591a\u4e86\u4e00\u628a\u4f1e", "\u6c99\u53d1\u4e0a\u7761\u7740\uff0c\u591a\u4e86\u6bdb\u6bef", "\u6536\u62fe\u67dc\u5b50\uff0c\u53d1\u73b0\u4fdd\u6e29\u996d\u76d2", "\u62b1\u7740\u996d\u76d2\uff0c\u7b11\u4e86"]
script4_anchors = ["\u6e05\u6668\uff0c\u7537\u4e3b\u5728\u53a8\u623f\u5e2e\u5973\u4e3b\u7cfb\u56f4\u88d9", "\u51fa\u95e8\u6563\u6b65\uff0c\u4e24\u4eba\u8d70\u5f97\u5f88\u6162", "\u7537\u4e3b\u770b\u624b\u673a\uff0c\u5c4f\u5e55\u62ff\u5f97\u5f88\u8fdc", "\u5973\u4e3b\u5728\u9633\u53f0\u8ddf\u697c\u4e0b\u5e7f\u573a\u821e", "\u4f60\u6bcf\u6b21\u90fd\u8bf4\u8fd9\u53e5", "\u7537\u4e3b\u7ffb\u62bd\u5c49\uff0c\u7ffb\u5230\u6cdb\u9ec4\u7167\u7247", "\u7537\u4e3b\u8def\u8fc7\u955c\u5b50\uff0c\u505c\u4f4f", "\u5973\u4e3b\u8d70\u8fc7\u6765\u63e1\u4f4f\u4ed6\u7684\u624b", "\u6700\u540e\u4e00\u4e2a\u955c\u5934\uff1a\u4e24\u4eba\u624b\u63e1\u624b"]

old_times = ["0-3s","3-10s","10-18s","18-25s","25-35s","35-48s","48-55s","55-60s"]
old_times_s4 = ["0-3s","3-10s","10-18s","18-25s","25-35s","35-48s","48-53s","53-58s","58-60s"]

def replace_times(content, anchors, old_t, new_t):
    for i, anchor in enumerate(anchors):
        old_str = 'class="time-col">' + old_t[i] + '</td><td class="act-col'
        idx = content.find(old_str)
        while idx != -1:
            context = content[idx:idx+500]
            if anchor in context:
                new_str = 'class="time-col">' + new_t[i] + '</td><td class="act-col'
                content = content[:idx] + new_str + content[idx+len(old_str):]
                print("  Replaced: " + old_t[i] + " -> " + new_t[i] + " for [" + anchor[:10] + "]")
                break
            idx = content.find(old_str, idx+1)
        else:
            print("  WARNING: No match for anchor [" + anchor[:10] + "] with time " + old_t[i])
    return content

print("=== Script 1 ===")
content = replace_times(content, script1_anchors, old_times, script1_times)
print("=== Script 2 ===")
content = replace_times(content, script2_anchors, old_times, script2_times)
print("=== Script 3 ===")
content = replace_times(content, script3_anchors, old_times, script3_times)
print("=== Script 4 ===")
content = replace_times(content, script4_anchors, old_times_s4, script4_times)

with open("D:/AgentSkill/MCNVideo AI/project/编导AI脚本对话记录分析/剧本大纲情绪改善案例.html", "w", encoding="utf-8") as f:
    f.write(content)

print("\nDone!")