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Rag Service
ASecurity高性能 RAG 多路检索服务。集成 Milvus 向量数据库进行语义检索,并结合 Rerank 模型进行精准重排序,支持海量文档的高效存储与历史内容召回。
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- Added June 3, 2026
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[](https://www.skillsdirectory.com/skills/majiayu000-rag-service)---
name: rag-service
description: 高性能 RAG 多路检索服务。集成 Milvus 向量数据库进行语义检索,并结合 Rerank 模型进行精准重排序,支持海量文档的高效存储与历史内容召回。
---
## 功能
RAG 多路检索服务,提供:
1. 向量语义检索 - 基于 Milvus 的向量相似度搜索
2. Rerank 重排序 - 对检索结果进行精排
3. 文档存储 - 保存文档到向量数据库
## 调用方式
```python
from services.rag_service.client import RAGServiceClient
client = RAGServiceClient()
# 健康检查
status = client.health()
# 语义检索
result = client.retrieve(
query="Python 异步编程最佳实践",
top_k=5,
min_score=0.85,
rerank=True
)
print(result["results"])
# 便捷方法:只获取文本列表
texts = client.retrieve_texts(query="Python 异步编程", top_k=5)
# 保存文档
client.save(documents=[
{"text": "文档内容...", "metadata": {"title": "标题", "url": "..."}}
])
```
## 返回格式
### retrieve
```json
{
"query": "Python 异步编程",
"results": [
{
"id": "abc123",
"text": "Python异步编程基于asyncio库...",
"score": 0.92,
"metadata": {"title": "Python官方文档", "url": "..."}
}
],
"total": 3,
"elapsed_ms": 45.2,
"from_cache": false
}
```
### save
```json
{
"saved_count": 5,
"collection_name": "websearch_results"
}
```
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