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96 lines
2.9 KiB
96 lines
2.9 KiB
from elasticsearch import Elasticsearch
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from Config.Config import ES_CONFIG
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from Util.EsMappingUtil import create_vector_index, delete_index, create_text_index, delete_text_index
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# 初始化ES连接
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es = Elasticsearch(
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hosts=ES_CONFIG["hosts"],
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basic_auth=ES_CONFIG["basic_auth"],
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verify_certs=ES_CONFIG["verify_certs"],
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ssl_show_warn=ES_CONFIG["ssl_show_warn"]
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)
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def manage_index(action, index_type="vector", index_name=None, dims=200):
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"""管理Elasticsearch索引
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:param action: 'create'或'delete'
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:param index_type: 'vector'或'text'
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:param index_name: 索引名称(默认根据类型自动生成)
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:param dims: 向量维度(仅向量索引有效)
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"""
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if index_name is None:
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index_name = "knowledge_base" if index_type == "vector" else "raw_texts"
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if action == "create":
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if index_type == "vector":
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return create_vector_index(index_name, dims)
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else:
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return create_text_index(index_name)
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elif action == "delete":
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if index_type == "vector":
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return delete_index(index_name)
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else:
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return delete_text_index(index_name)
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else:
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raise ValueError("action参数必须是'create'或'delete'")
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# 使用示例
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if __name__ == "__main__":
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# 先删除现有索引（如果存在）
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manage_index("delete", "vector")
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manage_index("delete", "text")
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# 创建新的向量索引
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manage_index("create", "vector", dims=200)
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# 创建新的原始文本索引
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manage_index("create", "text")
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# 修改knowledge_base索引的mapping
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knowledge_base_mapping = {
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"properties": {
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# 在knowledge_base_mapping中添加
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"content": {
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"type": "text",
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"analyzer": "ik_max_word",
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"search_analyzer": "ik_smart",
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"fields": {
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"keyword": {
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"type": "keyword",
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"ignore_above": 8192 # 可以设置为1024/2048等更大值
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}
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}
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},
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# 在raw_texts_mapping中添加
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"raw_text": {
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"type": "text",
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"analyzer": "ik_max_word",
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"fielddata": True # 允许对长文本进行聚合
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},
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"vector": {
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"type": "dense_vector",
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"dims": 200,
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"index": True,
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"similarity": "cosine"
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},
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"timestamp": {
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"type": "date",
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"format": "strict_date_optional_time||epoch_millis"
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}
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}
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}
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# 修改raw_texts索引的mapping
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raw_texts_mapping = {
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"properties": {
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"raw_text": {
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"type": "text",
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"analyzer": "ik_max_word"
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},
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"timestamp": {
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"type": "date",
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"format": "strict_date_optional_time||epoch_millis"
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}
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}
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}
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