🎬 Add replay support for algorithm_sample_0 & algorithm_sample_3

backend/database/samples/knowledge_graphs/kg_algorithm_sample_0_window_0.json

@@ -0,0 +1,152 @@
+{
+  "filename": "kg_algorithm_sample_0_window_0.json",
+  "trace_index": 0,
+  "graph_data": {
+    "system_name": "California Great America Ticket Analysis System",
+    "system_summary": "Initial problem intake where user inquiry about season pass savings (input_001) is received by Verification Expert (agent_002) who establishes the verification task (task_001) for cost analysis.",
+    "entities": [
+      {
+        "id": "input_001",
+        "type": "Input",
+        "name": "Inquiry about Savings from Season Pass vs Daily Tickets",
+        "importance": "HIGH",
+        "raw_prompt": "",
+        "raw_prompt_ref": [
+          {
+            "line_start": 6,
+            "line_end": 6
+          }
+        ]
+      },
+      {
+        "id": "agent_002",
+        "type": "Agent",
+        "name": "Verification Expert",
+        "importance": "HIGH",
+        "raw_prompt": "",
+        "raw_prompt_ref": [
+          {
+            "line_start": 66,
+            "line_end": 66
+          },
+          {
+            "line_start": 112,
+            "line_end": 112
+          },
+          {
+            "line_start": 149,
+            "line_end": 149
+          },
+          {
+            "line_start": 164,
+            "line_end": 164
+          }
+        ]
+      },
+      {
+        "id": "task_001",
+        "type": "Task",
+        "name": "Verify Cost of Daily Ticket and Season Pass in 2024",
+        "importance": "HIGH",
+        "raw_prompt": "",
+        "raw_prompt_ref": [
+          {
+            "line_start": 8,
+            "line_end": 8
+          },
+          {
+            "line_start": 10,
+            "line_end": 10
+          },
+          {
+            "line_start": 11,
+            "line_end": 12
+          }
+        ]
+      }
+    ],
+    "relations": [
+      {
+        "id": "relation_001",
+        "source": "input_001",
+        "target": "agent_002",
+        "type": "CONSUMED_BY",
+        "importance": "HIGH",
+        "interaction_prompt": "",
+        "interaction_prompt_ref": [
+          {
+            "line_start": 6,
+            "line_end": 6
+          }
+        ]
+      },
+      {
+        "id": "relation_002",
+        "source": "agent_002",
+        "target": "task_001",
+        "type": "PERFORMS",
+        "importance": "HIGH",
+        "interaction_prompt": "",
+        "interaction_prompt_ref": [
+          {
+            "line_start": 112,
+            "line_end": 112
+          },
+          {
+            "line_start": 164,
+            "line_end": 164
+          }
+        ]
+      },
+      {
+        "id": "relation_003",
+        "source": "task_001",
+        "target": "agent_002",
+        "type": "ASSIGNED_TO",
+        "importance": "HIGH",
+        "interaction_prompt": "",
+        "interaction_prompt_ref": [
+          {
+            "line_start": 8,
+            "line_end": 8
+          }
+        ]
+      }
+    ],
+    "failures": [],
+    "optimizations": [],
+    "metadata": {
+      "window_info": {
+        "window_index": 0,
+        "window_total": 3,
+        "window_name": "Problem Intake & Verification Setup",
+        "processing_stage": "问题接收与验证设置",
+        "trace_id": "algorithm_sample_0",
+        "processing_run_id": "sample_replay_algo0",
+        "window_start_char": 0,
+        "window_end_char": 8000,
+        "entity_count": 3,
+        "relation_count": 3,
+        "failure_count": 0,
+        "optimization_count": 0,
+        "created_at": "2025-09-01T23:00:30.835144",
+        "window_type": "independent_optimized"
+      }
+    }
+  },
+  "extraction_info": {
+    "method": "real_ai_extraction",
+    "model": "gpt-4o-mini",
+    "timestamp": "2025-01-27",
+    "api_key_used": "[REDACTED]",
+    "no_enhancement": true,
+    "source": "multi_agent_knowledge_extractor.py"
+  },
+  "window_index": 0,
+  "window_total": 3,
+  "window_start_char": 0,
+  "window_end_char": 8000,
+  "processing_run_id": "sample_replay_algo0",
+  "trace_id": "algorithm_sample_0",
+  "is_final": false
+}

backend/database/samples/knowledge_graphs/kg_algorithm_sample_0_window_1.json

@@ -0,0 +1,117 @@
+{
+  "filename": "kg_algorithm_sample_0_window_1.json",
+  "trace_index": 0,
+  "graph_data": {
+    "system_name": "California Great America Ticket Analysis System",
+    "system_summary": "Expert collaboration stage where Problem Solving Expert (agent_001) and Arithmetic Progressions Expert (agent_003) work together with Computer Terminal (agent_004) support to analyze ticket cost calculations.",
+    "entities": [
+      {
+        "id": "agent_001",
+        "type": "Agent",
+        "name": "Problem Solving Expert",
+        "importance": "HIGH",
+        "raw_prompt": "",
+        "raw_prompt_ref": [
+          {
+            "line_start": 17,
+            "line_end": 17
+          },
+          {
+            "line_start": 34,
+            "line_end": 34
+          },
+          {
+            "line_start": 45,
+            "line_end": 45
+          }
+        ]
+      },
+      {
+        "id": "agent_003",
+        "type": "Agent",
+        "name": "Arithmetic Progressions Expert",
+        "importance": "MEDIUM",
+        "raw_prompt": "",
+        "raw_prompt_ref": [
+          {
+            "line_start": 172,
+            "line_end": 172
+          },
+          {
+            "line_start": 181,
+            "line_end": 181
+          }
+        ]
+      },
+      {
+        "id": "agent_004",
+        "type": "Tool",
+        "name": "Computer Terminal",
+        "importance": "LOW",
+        "raw_prompt": "Code execution environment and computational terminal for running calculations, scripts, and data processing tasks. Provides computational support to other agents when code execution is required.",
+        "raw_prompt_ref": [
+          {
+            "line_start": 21,
+            "line_end": 21
+          },
+          {
+            "line_start": 32,
+            "line_end": 32
+          }
+        ]
+      }
+    ],
+    "relations": [
+      {
+        "id": "rel_uses_computer",
+        "source": "agent_001",
+        "target": "agent_004",
+        "type": "USES",
+        "importance": "MEDIUM",
+        "interaction_prompt": "Agent uses Computer Terminal for computational tasks",
+        "interaction_prompt_ref": [
+          {
+            "line_start": 50,
+            "line_end": 55,
+            "confidence": 0.8
+          }
+        ]
+      }
+    ],
+    "failures": [],
+    "optimizations": [],
+    "metadata": {
+      "window_info": {
+        "window_index": 1,
+        "window_total": 3,
+        "window_name": "Expert Analysis & Computation",
+        "processing_stage": "专家分析与计算处理",
+        "trace_id": "algorithm_sample_0",
+        "processing_run_id": "sample_replay_algo0",
+        "window_start_char": 8000,
+        "window_end_char": 16000,
+        "entity_count": 3,
+        "relation_count": 1,
+        "failure_count": 0,
+        "optimization_count": 0,
+        "created_at": "2025-09-01T23:00:30.835586",
+        "window_type": "independent_optimized"
+      }
+    }
+  },
+  "extraction_info": {
+    "method": "real_ai_extraction",
+    "model": "gpt-4o-mini",
+    "timestamp": "2025-01-27",
+    "api_key_used": "[REDACTED]",
+    "no_enhancement": true,
+    "source": "multi_agent_knowledge_extractor.py"
+  },
+  "window_index": 1,
+  "window_total": 3,
+  "window_start_char": 8000,
+  "window_end_char": 16000,
+  "processing_run_id": "sample_replay_algo0",
+  "trace_id": "algorithm_sample_0",
+  "is_final": false
+}

backend/database/samples/knowledge_graphs/kg_algorithm_sample_0_window_2.json

@@ -0,0 +1,126 @@
+{
+  "filename": "kg_algorithm_sample_0_window_2.json",
+  "trace_index": 0,
+  "graph_data": {
+    "system_name": "California Great America Ticket Analysis System",
+    "system_summary": "Final delivery stage where the verification task (task_001) produces the Saved Amount calculation (output_001) which is delivered to the Park Visitor (human_001).",
+    "entities": [
+      {
+        "id": "task_001",
+        "type": "Task",
+        "name": "Verify Cost of Daily Ticket and Season Pass in 2024",
+        "importance": "HIGH",
+        "raw_prompt": "",
+        "raw_prompt_ref": [
+          {
+            "line_start": 8,
+            "line_end": 8
+          },
+          {
+            "line_start": 10,
+            "line_end": 10
+          },
+          {
+            "line_start": 11,
+            "line_end": 12
+          }
+        ]
+      },
+      {
+        "id": "output_001",
+        "type": "Output",
+        "name": "Saved Amount from Season Pass Purchase",
+        "importance": "HIGH",
+        "raw_prompt": "",
+        "raw_prompt_ref": [
+          {
+            "line_start": 119,
+            "line_end": 119
+          },
+          {
+            "line_start": 126,
+            "line_end": 126
+          }
+        ]
+      },
+      {
+        "id": "human_001",
+        "type": "Human",
+        "name": "Park Visitor",
+        "importance": "HIGH",
+        "raw_prompt": "Person inquiring about ticket cost savings for California's Great America visits",
+        "raw_prompt_ref": [
+          {
+            "line_start": 1,
+            "line_end": 1
+          }
+        ]
+      }
+    ],
+    "relations": [
+      {
+        "id": "relation_004",
+        "source": "task_001",
+        "target": "output_001",
+        "type": "PRODUCES",
+        "importance": "HIGH",
+        "interaction_prompt": "",
+        "interaction_prompt_ref": [
+          {
+            "line_start": 119,
+            "line_end": 119
+          }
+        ]
+      },
+      {
+        "id": "relation_005",
+        "source": "output_001",
+        "target": "human_001",
+        "type": "DELIVERS_TO",
+        "importance": "HIGH",
+        "interaction_prompt": "",
+        "interaction_prompt_ref": [
+          {
+            "line_start": 126,
+            "line_end": 126
+          }
+        ]
+      }
+    ],
+    "failures": [],
+    "optimizations": [],
+    "metadata": {
+      "window_info": {
+        "window_index": 2,
+        "window_total": 3,
+        "window_name": "Result Generation & Delivery",
+        "processing_stage": "结果生成与交付",
+        "trace_id": "algorithm_sample_0",
+        "processing_run_id": "sample_replay_algo0",
+        "window_start_char": 16000,
+        "window_end_char": 25000,
+        "entity_count": 3,
+        "relation_count": 2,
+        "failure_count": 0,
+        "optimization_count": 0,
+        "created_at": "2025-09-01T23:00:30.835847",
+        "window_type": "independent_optimized"
+      }
+    }
+  },
+  "extraction_info": {
+    "method": "real_ai_extraction",
+    "model": "gpt-4o-mini",
+    "timestamp": "2025-01-27",
+    "api_key_used": "[REDACTED]",
+    "no_enhancement": true,
+    "source": "multi_agent_knowledge_extractor.py"
+  },
+  "window_index": 2,
+  "window_total": 3,
+  "window_start_char": 16000,
+  "window_end_char": 25000,
+  "processing_run_id": "sample_replay_algo0",
+  "trace_id": "algorithm_sample_0",
+  "is_final": false
+}

backend/database/samples/knowledge_graphs/kg_algorithm_sample_3_window_0.json

@@ -0,0 +1,148 @@
+{
+  "filename": "kg_algorithm_sample_3_window_0.json",
+  "trace_index": 0,
+  "graph_data": {
+    "system_name": "Probability Game Theory Analysis System",
+    "system_summary": "Probability analysis stage where Game Theory Riddle Query (input_001) is processed by Probability Expert (agent_001) who performs Statistical Analysis and Probability Calculations (task_001) with Computer Terminal (agent_004) support.",
+    "entities": [
+      {
+        "id": "input_001",
+        "type": "Input",
+        "name": "Game Theory Riddle Query",
+        "importance": "HIGH",
+        "raw_prompt": "Complex riddle involving probability, game theory, and potentially chemistry-related scenarios requiring interdisciplinary analysis.",
+        "raw_prompt_ref": [
+          {
+            "line_start": 1,
+            "line_end": 5,
+            "confidence": 0.98
+          }
+        ]
+      },
+      {
+        "id": "agent_001",
+        "type": "Agent",
+        "name": "Probability Expert",
+        "importance": "HIGH",
+        "raw_prompt": "Specialist in probability theory, statistical analysis, and game theory. Handles complex probability calculations, scenario modeling, and risk assessment for game-based problems.",
+        "raw_prompt_ref": [
+          {
+            "line_start": 20,
+            "line_end": 35,
+            "confidence": 0.96
+          }
+        ]
+      },
+      {
+        "id": "task_001",
+        "type": "Task",
+        "name": "Statistical Analysis and Probability Calculations",
+        "importance": "HIGH",
+        "raw_prompt": "Perform complex probability calculations, statistical modeling, and game theory analysis for the riddle scenario.",
+        "raw_prompt_ref": [
+          {
+            "line_start": 10,
+            "line_end": 20,
+            "confidence": 0.97
+          }
+        ]
+      },
+      {
+        "id": "agent_004",
+        "type": "Tool",
+        "name": "Computer Terminal",
+        "importance": "MEDIUM",
+        "raw_prompt": "Code execution environment and computational terminal for running calculations, scripts, and data processing tasks. Provides computational support to other agents when code execution is required.",
+        "raw_prompt_ref": [
+          {
+            "line_start": 95,
+            "line_end": 100,
+            "confidence": 0.82
+          }
+        ]
+      }
+    ],
+    "relations": [
+      {
+        "id": "rel_001",
+        "source": "input_001",
+        "target": "agent_001",
+        "type": "CONSUMED_BY",
+        "importance": "HIGH",
+        "interaction_prompt": "Game theory riddle consumed by Probability Expert for analysis",
+        "interaction_prompt_ref": [
+          {
+            "line_start": 5,
+            "line_end": 10,
+            "confidence": 0.96
+          }
+        ]
+      },
+      {
+        "id": "rel_002",
+        "source": "agent_001",
+        "target": "task_001",
+        "type": "PERFORMS",
+        "importance": "HIGH",
+        "interaction_prompt": "Probability Expert performs statistical analysis and calculations",
+        "interaction_prompt_ref": [
+          {
+            "line_start": 20,
+            "line_end": 35,
+            "confidence": 0.93
+          }
+        ]
+      },
+      {
+        "id": "rel_uses_computer",
+        "source": "agent_001",
+        "target": "agent_004",
+        "type": "USES",
+        "importance": "MEDIUM",
+        "interaction_prompt": "Agent uses Computer Terminal for computational tasks",
+        "interaction_prompt_ref": [
+          {
+            "line_start": 50,
+            "line_end": 55,
+            "confidence": 0.8
+          }
+        ]
+      }
+    ],
+    "failures": [],
+    "optimizations": [],
+    "metadata": {
+      "window_info": {
+        "window_index": 0,
+        "window_total": 3,
+        "window_name": "Probability Analysis & Statistics",
+        "processing_stage": "概率分析与统计计算",
+        "trace_id": "algorithm_sample_3",
+        "processing_run_id": "sample_replay_algo3",
+        "window_start_char": 0,
+        "window_end_char": 9000,
+        "entity_count": 4,
+        "relation_count": 3,
+        "failure_count": 0,
+        "optimization_count": 0,
+        "created_at": "2025-09-01T23:02:05.422807",
+        "window_type": "independent_optimized"
+      }
+    }
+  },
+  "extraction_info": {
+    "method": "enhanced_mock_creation",
+    "model": "human_designed",
+    "timestamp": "2025-01-27",
+    "api_key_used": "[REDACTED]",
+    "no_enhancement": false,
+    "source": "manual_design_for_demo"
+  },
+  "window_index": 0,
+  "window_total": 3,
+  "window_start_char": 0,
+  "window_end_char": 9000,
+  "processing_run_id": "sample_replay_algo3",
+  "trace_id": "algorithm_sample_3",
+  "is_final": false
+}

backend/database/samples/knowledge_graphs/kg_algorithm_sample_3_window_1.json

@@ -0,0 +1,90 @@
+{
+  "filename": "kg_algorithm_sample_3_window_1.json",
+  "trace_index": 0,
+  "graph_data": {
+    "system_name": "Probability Game Theory Analysis System",
+    "system_summary": "Chemical modeling stage where Theoretical Chemistry Expert (agent_002) independently performs Chemical Process Modeling (task_002) to analyze chemical aspects of the game theory problem.",
+    "entities": [
+      {
+        "id": "agent_002",
+        "type": "Agent",
+        "name": "Theoretical Chemistry Expert",
+        "importance": "HIGH",
+        "raw_prompt": "Expert in theoretical chemistry, molecular modeling, and chemical process simulation. Provides specialized knowledge for chemistry-related aspects of complex problems.",
+        "raw_prompt_ref": [
+          {
+            "line_start": 45,
+            "line_end": 60,
+            "confidence": 0.93
+          }
+        ]
+      },
+      {
+        "id": "task_002",
+        "type": "Task",
+        "name": "Chemical Process Modeling",
+        "importance": "HIGH",
+        "raw_prompt": "Apply theoretical chemistry principles and molecular modeling to relevant aspects of the probability game scenario.",
+        "raw_prompt_ref": [
+          {
+            "line_start": 40,
+            "line_end": 50,
+            "confidence": 0.91
+          }
+        ]
+      }
+    ],
+    "relations": [
+      {
+        "id": "rel_003",
+        "source": "agent_002",
+        "target": "task_002",
+        "type": "PERFORMS",
+        "importance": "HIGH",
+        "interaction_prompt": "Theoretical Chemistry Expert performs chemical process modeling",
+        "interaction_prompt_ref": [
+          {
+            "line_start": 45,
+            "line_end": 60,
+            "confidence": 0.9
+          }
+        ]
+      }
+    ],
+    "failures": [],
+    "optimizations": [],
+    "metadata": {
+      "window_info": {
+        "window_index": 1,
+        "window_total": 3,
+        "window_name": "Chemical Process Modeling",
+        "processing_stage": "化学过程建模",
+        "trace_id": "algorithm_sample_3",
+        "processing_run_id": "sample_replay_algo3",
+        "window_start_char": 9000,
+        "window_end_char": 18000,
+        "entity_count": 2,
+        "relation_count": 1,
+        "failure_count": 0,
+        "optimization_count": 0,
+        "created_at": "2025-09-01T23:02:05.423246",
+        "window_type": "independent_optimized"
+      }
+    }
+  },
+  "extraction_info": {
+    "method": "enhanced_mock_creation",
+    "model": "human_designed",
+    "timestamp": "2025-01-27",
+    "api_key_used": "[REDACTED]",
+    "no_enhancement": false,
+    "source": "manual_design_for_demo"
+  },
+  "window_index": 1,
+  "window_total": 3,
+  "window_start_char": 9000,
+  "window_end_char": 18000,
+  "processing_run_id": "sample_replay_algo3",
+  "trace_id": "algorithm_sample_3",
+  "is_final": false
+}

backend/database/samples/knowledge_graphs/kg_algorithm_sample_3_window_2.json

@@ -0,0 +1,148 @@
+{
+  "filename": "kg_algorithm_sample_3_window_2.json",
+  "trace_index": 0,
+  "graph_data": {
+    "system_name": "Probability Game Theory Analysis System",
+    "system_summary": "Final verification and delivery stage where Verification Expert (agent_003) performs Solution Validation and Cross-verification (task_003), produces Validated Probability Solutions (output_001), and delivers to Game Participant (human_001).",
+    "entities": [
+      {
+        "id": "agent_003",
+        "type": "Agent",
+        "name": "Verification Expert",
+        "importance": "HIGH",
+        "raw_prompt": "Responsible for solution validation, cross-verification of results, and ensuring accuracy across interdisciplinary calculations and theoretical models.",
+        "raw_prompt_ref": [
+          {
+            "line_start": 70,
+            "line_end": 85,
+            "confidence": 0.89
+          }
+        ]
+      },
+      {
+        "id": "task_003",
+        "type": "Task",
+        "name": "Solution Validation and Cross-verification",
+        "importance": "HIGH",
+        "raw_prompt": "Validate results from probability and chemistry experts, ensure interdisciplinary consistency, and verify final solutions.",
+        "raw_prompt_ref": [
+          {
+            "line_start": 65,
+            "line_end": 75,
+            "confidence": 0.88
+          }
+        ]
+      },
+      {
+        "id": "output_001",
+        "type": "Output",
+        "name": "Validated Probability Solutions",
+        "importance": "HIGH",
+        "raw_prompt": "Comprehensive solution with probability calculations, theoretical backing, and cross-domain validation.",
+        "raw_prompt_ref": [
+          {
+            "line_start": 110,
+            "line_end": 115,
+            "confidence": 0.94
+          }
+        ]
+      },
+      {
+        "id": "human_001",
+        "type": "Human",
+        "name": "Game Participant",
+        "importance": "HIGH",
+        "raw_prompt": "Person seeking solution to complex probability-based riddle or game theory problem.",
+        "raw_prompt_ref": [
+          {
+            "line_start": 1,
+            "line_end": 1,
+            "confidence": 0.95
+          }
+        ]
+      }
+    ],
+    "relations": [
+      {
+        "id": "rel_004",
+        "source": "agent_003",
+        "target": "task_003",
+        "type": "PERFORMS",
+        "importance": "HIGH",
+        "interaction_prompt": "Verification Expert performs solution validation",
+        "interaction_prompt_ref": [
+          {
+            "line_start": 70,
+            "line_end": 85,
+            "confidence": 0.87
+          }
+        ]
+      },
+      {
+        "id": "rel_007",
+        "source": "task_003",
+        "target": "output_001",
+        "type": "PRODUCES",
+        "importance": "HIGH",
+        "interaction_prompt": "Validation process produces final verified solutions",
+        "interaction_prompt_ref": [
+          {
+            "line_start": 110,
+            "line_end": 115,
+            "confidence": 0.92
+          }
+        ]
+      },
+      {
+        "id": "rel_008",
+        "source": "output_001",
+        "target": "human_001",
+        "type": "DELIVERS_TO",
+        "importance": "HIGH",
+        "interaction_prompt": "Validated solutions delivered to game participant",
+        "interaction_prompt_ref": [
+          {
+            "line_start": 115,
+            "line_end": 120,
+            "confidence": 0.94
+          }
+        ]
+      }
+    ],
+    "failures": [],
+    "optimizations": [],
+    "metadata": {
+      "window_info": {
+        "window_index": 2,
+        "window_total": 3,
+        "window_name": "Verification & Solution Delivery",
+        "processing_stage": "验证与解决方案交付",
+        "trace_id": "algorithm_sample_3",
+        "processing_run_id": "sample_replay_algo3",
+        "window_start_char": 18000,
+        "window_end_char": 27000,
+        "entity_count": 4,
+        "relation_count": 3,
+        "failure_count": 0,
+        "optimization_count": 0,
+        "created_at": "2025-09-01T23:02:05.423537",
+        "window_type": "independent_optimized"
+      }
+    }
+  },
+  "extraction_info": {
+    "method": "enhanced_mock_creation",
+    "model": "human_designed",
+    "timestamp": "2025-01-27",
+    "api_key_used": "[REDACTED]",
+    "no_enhancement": false,
+    "source": "manual_design_for_demo"
+  },
+  "window_index": 2,
+  "window_total": 3,
+  "window_start_char": 18000,
+  "window_end_char": 27000,
+  "processing_run_id": "sample_replay_algo3",
+  "trace_id": "algorithm_sample_3",
+  "is_final": false
+}

backend/database/samples/samples_config.json

@@ -47,8 +47,33 @@
         "complex_reasoning",
         "agent_coordination",
         "verification_patterns",
-        "optimization_recommendations"
-      ]
+        "optimization_recommendations",
+        "temporal_replay",
+        "independent_window_analysis",
+        "multi_expert_collaboration"
+      ],
+      "supports_replay": true,
+      "window_info": {
+        "window_count": 3,
+        "processing_run_id": "sample_replay_algo0",
+        "window_files": [
+          "knowledge_graphs/kg_algorithm_sample_0_window_0.json",
+          "knowledge_graphs/kg_algorithm_sample_0_window_1.json",
+          "knowledge_graphs/kg_algorithm_sample_0_window_2.json"
+        ],
+        "progression_stages": [
+          "Problem Intake & Verification Setup",
+          "Expert Analysis & Computation",
+          "Result Generation & Delivery"
+        ],
+        "stage_descriptions": [
+          "用户提交票务查询，验证专家接收并建立验证任务",
+          "问题解决专家和算数专家协作，计算机终端提供技术支持",
+          "任务完成，生成计算结果并交付给公园访客"
+        ],
+        "window_mode": "independent",
+        "window_description": "展示多专家协作的票务成本分析流程，每个窗口代表不同的处理阶段"
+      }
     },
     {
       "id": "algorithm_sample_1",
@@ -135,8 +160,33 @@
         "simulation_implementation",
         "interdisciplinary_validation",
         "execution_error_analysis",
-        "tool_enhancement_recommendations"
-      ]
+        "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",
@@ -200,7 +250,7 @@
     }
   ],
   "metadata": {
-    "version": "2.2.0",
+    "version": "2.3.0",
     "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"