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{
"samples": [
{
"id": "python_documentation_demo",
"name": "Python Documentation Assistant Demo",
"description": "Comprehensive example showing RAG-powered AI assistant handling multi-turn programming inquiry with knowledge search, detailed explanations, code examples, performance analysis, and interactive learning",
"trace_file": "traces/python_documentation_inquiry.json",
"knowledge_graph_file": "knowledge_graphs/kg_python_documentation_enhanced.json",
"tags": [
"programming",
"rag_assistant",
"documentation",
"failure_detection",
"optimization"
],
"complexity": "enhanced",
"trace_type": "documentation_search",
"trace_source": "sample_data",
"features": [
"rag_search",
"failure_detection",
"optimization_recommendations",
"content_references",
"quality_scoring"
]
},
{
"id": "algorithm_sample_1",
"name": "Location-Based Restaurant Discovery System",
"description": "Complex location-based services example showcasing geographic analysis, time-based filtering, and data verification failures. Features Location-Based Services Expert, Eateries Expert, Data Verification Expert, and Computer Terminal collaborating on restaurant discovery near Harkness Memorial State Park with specific time constraints.",
"trace_file": "traces/algorithm_sample_1.json",
"knowledge_graph_file": "knowledge_graphs/kg_algorithm_sample_1.json",
"tags": [
"multi_agent",
"algorithm_generated",
"location_services",
"data_verification",
"real_failure",
"geographic_analysis",
"time_constraints",
"api_integration"
],
"complexity": "expert",
"trace_type": "location_based_services",
"trace_source": "algorithm_generated",
"features": [
"geographic_proximity_analysis",
"time_based_filtering",
"data_verification_failures",
"api_integration_challenges",
"multi_source_validation",
"real_world_constraints",
"execution_error_analysis",
"tool_enhancement_recommendations",
"temporal_replay",
"progressive_knowledge_evolution",
"window_based_visualization",
"independent_window_analysis",
"stage_specific_processing",
"non_cumulative_visualization"
],
"supports_replay": true,
"window_info": {
"window_count": 3,
"processing_run_id": "sample_replay_002",
"window_files": [
"knowledge_graphs/kg_algorithm_sample_1_window_0.json",
"knowledge_graphs/kg_algorithm_sample_1_window_1.json",
"knowledge_graphs/kg_algorithm_sample_1_window_2.json"
],
"progression_stages": [
"User Query & Geographic Analysis",
"Restaurant Data Collection",
"Data Verification & Delivery"
],
"stage_descriptions": [
"用户输入餐厅查询，位置专家进行地理分析，计算工具提供支持",
"餐厅专家独立收集和处理餐厅数据信息",
"数据验证专家验证信息质量并向用户交付最终推荐结果"
],
"window_mode": "independent",
"window_description": "每个窗口代表餐厅发现流程中的独立处理阶段，展示不同专家和工具的专门职责"
}
},
{
"id": "algorithm_sample_3",
"name": "Probability Game Theory Analysis System",
"description": "Cross-disciplinary collaboration between probability and theoretical chemistry experts solving complex riddle scenarios. Demonstrates interdisciplinary problem-solving with game theory, statistical modeling, and chemical process analysis.",
"trace_file": "traces/algorithm_sample_3.json",
"knowledge_graph_file": "knowledge_graphs/kg_algorithm_sample_3.json",
"tags": [
"multi_agent",
"algorithm_generated",
"probability",
"theoretical_chemistry",
"game_theory",
"simulation",
"cross_disciplinary",
"complex_riddles"
],
"complexity": "expert",
"trace_type": "probability_game_theory",
"trace_source": "algorithm_generated",
"features": [
"cross_disciplinary_collaboration",
"probability_calculations",
"chemical_modeling",
"game_theory_analysis",
"simulation_implementation",
"interdisciplinary_validation",
"execution_error_analysis",
"tool_enhancement_recommendations",
"temporal_replay",
"independent_window_analysis",
"multi_disciplinary_analysis"
],
"supports_replay": true,
"window_info": {
"window_count": 3,
"processing_run_id": "sample_replay_algo3",
"window_files": [
"knowledge_graphs/kg_algorithm_sample_3_window_0.json",
"knowledge_graphs/kg_algorithm_sample_3_window_1.json",
"knowledge_graphs/kg_algorithm_sample_3_window_2.json"
],
"progression_stages": [
"Probability Analysis & Statistics",
"Chemical Process Modeling",
"Verification & Solution Delivery"
],
"stage_descriptions": [
"概率专家接收博弈理论查询，进行统计分析和概率计算",
"理论化学专家独立进行化学过程建模分析",
"验证专家进行解决方案验证并向游戏参与者交付最终结果"
],
"window_mode": "independent",
"window_description": "展示概率博弈理论的多专业分析流程，每个窗口聚焦不同专业领域"
}
},
{
"id": "algorithm_sample_14",
"name": "Academic Literature Research System",
"description": "Scholarly research system combining literary analysis and Norse mythology expertise for academic paper investigation. Features specialized academic database research and interdisciplinary scholarly analysis.",
"trace_file": "traces/algorithm_sample_14.json",
"knowledge_graph_file": "knowledge_graphs/kg_algorithm_sample_14.json",
"tags": [
"multi_agent",
"algorithm_generated",
"academic_research",
"literature_analysis",
"norse_mythology",
"scholarly_work",
"database_research",
"interdisciplinary_studies"
],
"complexity": "advanced",
"trace_type": "academic_literature_analysis",
"trace_source": "algorithm_generated",
"features": [
"academic_database_research",
"literary_analysis_methods",
"mythological_expertise",
"scholarly_validation",
"interdisciplinary_coordination",
"retrieval_error_analysis",
"database_tool_enhancement",
"workflow_integration",
"temporal_replay",
"independent_window_analysis",
"specialized_expert_workflow"
],
"supports_replay": true,
"window_info": {
"window_count": 3,
"processing_run_id": "sample_replay_algo14",
"window_files": [
"knowledge_graphs/kg_algorithm_sample_14_window_0.json",
"knowledge_graphs/kg_algorithm_sample_14_window_1.json",
"knowledge_graphs/kg_algorithm_sample_14_window_2.json"
],
"progression_stages": [
"Literature Investigation",
"Mythological Analysis",
"Academic Validation"
],
"stage_descriptions": [
"文学分析专家接收查询并进行学术文章调研",
"北欧神话专家进行神话参考文献分析",
"验证专家进行学术来源验证并交付研究结果"
],
"window_mode": "independent",
"window_description": "展示学术文献研究的多专业协作流程，每个窗口聚焦不同的研究领域"
}
},
{
"id": "algorithm_sample_16",
"name": "Wildlife Data Analysis and Ecological Monitoring System",
"description": "Comprehensive ecological data analysis system specializing in government wildlife datasets and invasive species monitoring. Demonstrates data science applications in conservation and ecological research.",
"trace_file": "traces/algorithm_sample_16.json",
"knowledge_graph_file": "knowledge_graphs/kg_algorithm_sample_16.json",
"tags": [
"multi_agent",
"algorithm_generated",
"data_analysis",
"wildlife_research",
"statistical_analysis",
"ecological_data",
"government_datasets",
"conservation_science"
],
"complexity": "advanced",
"trace_type": "wildlife_data_analysis",
"trace_source": "algorithm_generated",
"features": [
"government_dataset_processing",
"statistical_population_analysis",
"ecological_data_validation",
"temporal_trend_analysis",
"invasive_species_monitoring",
"data_retrieval_challenges",
"pipeline_optimization",
"conservation_applications",
"temporal_replay",
"independent_window_analysis",
"specialized_expert_workflow"
],
"supports_replay": true,
"window_info": {
"window_count": 3,
"processing_run_id": "sample_replay_algo16",
"window_files": [
"knowledge_graphs/kg_algorithm_sample_16_window_0.json",
"knowledge_graphs/kg_algorithm_sample_16_window_1.json",
"knowledge_graphs/kg_algorithm_sample_16_window_2.json"
],
"progression_stages": [
"Data Processing",
"Statistical Analysis",
"Ecological Validation"
],
"stage_descriptions": [
"数据分析专家接收查询并处理政府数据集",
"统计分析专家进行种群统计计算",
"数据验证专家进行生态数据验证并交付结果"
],
"window_mode": "independent",
"window_description": "展示野生动物数据分析的专业化处理流程，每个窗口代表不同的分析阶段"
}
}
],
"metadata": {
"version": "2.4.0",
"created": "2025-01-27",
"updated": "2025-01-27",
"description": "Comprehensive AgentGraph sample data showcasing diverse multi-agent interactions across multiple domains including location services, probability theory, academic research, and ecological data analysis"
}
}
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