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基于 LLM 的深度迭代搜索与推理服务。擅长处理复杂问题，通过自动分解查询、多轮迭代检索、信息评估与验证，最终生成全面且结构化的深度分析报告。
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Based on SOC occupation classification
| name | deepsearch-service |
| description | 基于 LLM 的深度迭代搜索与推理服务。擅长处理复杂问题，通过自动分解查询、多轮迭代检索、信息评估与验证，最终生成全面且结构化的深度分析报告。 |
基于 LLM 的迭代式深度搜索服务，能够：
from services.deepsearch_service.client import DeepSearchClient
client = DeepSearchClient()
# 健康检查
status = client.health_check()
# 深度搜索（默认参数）
result = client.search("Python异步编程的最佳实践有哪些？")
# 自定义参数
result = client.search(
query="如何设计一个高可用的微服务架构？",
max_iterations=3, # 最大迭代次数 (1-5)
queries_per_iteration=3, # 每轮查询数 (1-5)
depth_level="deep" # 搜索深度: quick/normal/deep
)
# 获取报告和来源
print(result["report"])
for source in result["sources"]:
print(f"- {source['title']}: {source['url']}")
{
"query": "Python异步编程的最佳实践有哪些？",
"report": "# Python异步编程最佳实践\n\n## 1. 核心概念...",
"sources": [
{
"title": "Python官方asyncio文档",
"url": "https://docs.python.org/...",
"relevance": 0.95,
"snippet": "asyncio是Python标准库中的异步I/O框架..."
}
],
"iterations": [
{
"iteration": 1,
"queries": ["Python asyncio 教程", "async await 用法"],
"results_count": 6,
"key_findings": ["asyncio是标准库组件"]
}
],
"total_iterations": 2,
"total_sources": 8,
"elapsed_seconds": 45.32,
"search_timestamp": "2025-12-28T18:30:00"
}
| 特性 | WebSearch | DeepSearch |
|---|---|---|
| 搜索模式 | 单轮搜索 | 迭代多轮搜索 |
| 查询策略 | 直接使用输入 | LLM 分解/优化 |
| 输出格式 | 结构化列表 | 综合报告 + 来源 |
| 响应时间 | 10-30s | 30-120s |
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