if not self.collection:
raise RuntimeError("请先创建集合")
生成查询向量
query_embedding = self.generate_embedding(query_text)
搜索参数
search_params = {
"metric_type": "L2",
"params": {"nprobe": 16}
}
执行搜索
print(f"正在搜索相似文本: '{query_text}'")
print('--------query_embedding----------------')
print(query_text)
print(query_embedding)
print('--------query_embedding----------------')
results = self.collection.search(
data=query_embedding,
anns_field="embedding",
param=search_params,
limit=top_k,
output_fields="text", "metadata"
)
print('-----------------------results--------------------')
print(results)
print('-----------------------results--------------------')
正在搜索相似文本: '人工智能是计算机科学的一个分支'
--------query_embedding----------------
人工智能是计算机科学的一个分支
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0.6957444 0.28894326 0.44469547 0.9105798 0.21184073 0.8289437 ]
--------query_embedding----------------
-----------------------results--------------------
data: \[{'id': 462627561339618327, 'distance': 0.0, 'entity': {'text': '人工智能是计算机科学的一个分支', 'metadata': {'category': 'AI基础', 'priority': 1}}}, {'id': 462627561339618331, 'distance': 58.727821350097656, 'entity': {'text': '计算机视觉让机器能够理解图像', 'metadata': {'category': 'AI应用', 'priority': 3}}}, {'id': 462627561339618329, 'distance': 62.76405334472656, 'entity': {'text': '深度学习是机器学习的一个子集', 'metadata': {'category': '深度学习', 'priority': 2}}}]
-----------------------results--------------------