48 lines
1.3 KiB
Python
Executable File
48 lines
1.3 KiB
Python
Executable File
#!/usr/bin/env python
|
|
# -*- coding: utf-8 -*-
|
|
"""
|
|
File: vectorize_save_noun.py
|
|
Date: 2025-05-15
|
|
Description: 专业名词向量化和保存的示例程序
|
|
"""
|
|
|
|
import os
|
|
import json
|
|
from dotenv import load_dotenv
|
|
import sys
|
|
from rag2_0.intent_recognition import ProfessionalNounVectorizer
|
|
import logging
|
|
|
|
# 加载环境变量
|
|
load_dotenv()
|
|
|
|
def main():
|
|
"""
|
|
主函数：创建索引并保存
|
|
"""
|
|
# 指定文件路径
|
|
current_dir = os.path.dirname(os.path.abspath(__file__))
|
|
output_dir = os.path.join(current_dir, "..", "..", "data", "nouns")
|
|
|
|
# 创建向量化器并指定路径
|
|
noun_vectorizer = ProfessionalNounVectorizer(
|
|
output_dir=output_dir
|
|
)
|
|
file_paths = [
|
|
os.path.join(current_dir, "..", "..", "data/nouns/merged_nouns.json"),
|
|
]
|
|
# 执行向量化和保存（一步完成）
|
|
success = noun_vectorizer.vectorize_files_and_save(file_paths)
|
|
if success:
|
|
logging.info("✓ 索引创建和保存成功")
|
|
logging.info(f" 索引保存路径: {os.path.join(output_dir, 'professional_nouns_index')}")
|
|
else:
|
|
logging.error("✗ 索引创建失败")
|
|
|
|
if __name__ == "__main__":
|
|
# 配置日志输出到控制台
|
|
logging.basicConfig(
|
|
level=logging.INFO,
|
|
format='%(message)s'
|
|
)
|
|
main() |