128 lines
5.2 KiB
JSON
128 lines
5.2 KiB
JSON
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{
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"query": "数据研发运营一体化(DataOps)是数据开发的哪种范式?",
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"answer": "数据研发运营一体化（DataOps）是一种整合了数据开发、数据管理和数据运营的新型工作模式。它旨在通过跨职能团队的协作、自动化工具的使用以及数据生命周期管理的优化，提高数据处理效率和质量，加速数据价值的实现。然而，关于数据研发运营一体化（DataOps）是否属于数据开发的特定范式或者其确切分类或位置的具体信息未能在当前检索到的数据中找到。DataOps 的核心理念是强调数据在整个生命周期中的流动性和可访问性，以及开发、运维和业务团队之间的紧密协作。这表明 DataOps 可能融合了传统数据开发范式的某些元素，并扩展了其边界，以适应现代大数据环境下的需求。尽管如此，DataOps 并未被明确归类为单一的传统数据开发范式，而更像是一种跨领域的实践方法论。为了获得更准确的分类或位置信息，可能需要查阅更多专业的技术文档或行业报告。",
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"query_complexity": {
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"is_complex": true,
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"complexity_level": "complex",
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"confidence": 0.95,
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"reason": "这是一个复杂查询，因为它涉及到理解并解释数据研发运营一体化(DataOps)的概念以及它与数据开发范式的联系。可能需要从多个角度和来源收集信息来提供全面的答案，因此可能需要生成多个子查询来深入探讨这个问题。"
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},
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"is_complex_query": true,
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"retrieval_path": "complex_hipporag",
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"iterations": 1,
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"total_passages": 0,
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"sub_queries": [
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"什么是数据研发运营一体化（DataOps）？",
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"数据研发运营一体化（DataOps）属于数据开发的哪一种范式？",
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"数据研发运营一体化（DataOps）的具体定义是什么？",
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"数据研发运营一体化（DataOps）在数据开发范式中的具体分类或位置是什么？"
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],
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"decomposed_sub_queries": [
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"什么是数据研发运营一体化（DataOps）？",
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"数据研发运营一体化（DataOps）属于数据开发的哪一种范式？"
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],
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"initial_retrieval_details": {},
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"sufficiency_check": {
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"is_sufficient": false,
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"confidence": 0.5,
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"reason": "检索信息中未提供关于数据研发运营一体化（DataOps）属于数据开发的哪一种范式的具体答案。",
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"iteration": 1
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},
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"current_sub_queries": [],
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"is_sufficient": false,
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"all_documents": [],
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"all_passages": [],
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"passage_sources": [],
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"pagerank_data_available": true,
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"pagerank_summary": {},
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"concept_exploration_results": {},
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"exploration_round": 0,
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"debug_info": {
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"total_time": 15.651340961456299,
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"retrieval_calls": 1,
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"llm_calls": 7,
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"langsmith_project": "hipporag-retriever",
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"token_usage_summary": {
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"has_llm": true,
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"has_generator": true,
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"last_call": {
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"prompt_tokens": 256,
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"completion_tokens": 201,
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"total_tokens": 457
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},
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"total_usage": {
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"prompt_tokens": 2061,
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"completion_tokens": 567,
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"total_tokens": 2628,
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"call_count": 6
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},
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"model_name": "qwen2-7b-instruct",
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"has_last_usage": true,
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"has_total_usage": true
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},
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"complexity_analysis": {
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"is_complex": true,
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"complexity_level": "complex",
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"confidence": 0.95,
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"reason": "这是一个复杂查询，因为它涉及到理解并解释数据研发运营一体化(DataOps)的概念以及它与数据开发范式的联系。可能需要从多个角度和来源收集信息来提供全面的答案，因此可能需要生成多个子查询来深入探讨这个问题。"
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},
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"debug_mode_analysis": {
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"debug_mode": "0",
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"debug_override": {},
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"path_override_applied": false
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},
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"sufficiency_analysis": {
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"final_sufficiency": false,
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"sufficiency_check_details": {
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"is_sufficient": false,
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"confidence": 0.5,
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"reason": "检索信息中未提供关于数据研发运营一体化（DataOps）属于数据开发的哪一种范式的具体答案。",
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"iteration": 1
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},
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"iteration_sufficiency_history": [],
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"sufficiency_progression": {
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"status": "no_sufficiency_checks"
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}
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},
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"routing_analysis": {
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"total_routing_decisions": 2,
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"sub_query_generation_count": 0,
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"parallel_retrieval_count": 0,
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"pagerank_collection_count": 0
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},
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"concept_exploration_analysis": {
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"exploration_enabled": false,
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"exploration_rounds": 0,
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"pagerank_nodes_analyzed": 0,
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"successful_branches_total": 0,
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"total_branches_attempted": 0
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}
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},
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"iteration_history": [
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{
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"iteration": 0,
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"query": "并行检索: 原始查询 + 2 个子查询",
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"passages_count": 0,
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"action": "retrieval"
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},
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{
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"iteration": 0,
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"action": "sufficiency_check",
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"is_sufficient": false,
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"confidence": 0.5,
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"sub_queries_count": 0
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},
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{
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"iteration": 1,
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"action": "sufficiency_check",
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"is_sufficient": false,
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"confidence": 0.5,
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"sub_queries_count": 0
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},
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{
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"iteration": 1,
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"action": "final_answer_generation",
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"answer_length": 366
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}
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]
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}
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