🎯 Redesign window KGs as independent processing stages

backend/database/samples/knowledge_graphs/kg_algorithm_sample_1_window_0.json

@@ -3,8 +3,22 @@
   "trace_index": 0,
   "graph_data": {
     "system_name": "Location-Based Restaurant Discovery System",
-    "system_summary": "Initial stage of the Location-Based Restaurant Discovery System focusing on location identification and geographic analysis. The User Restaurant Query (input_001) is processed by the Location-Based Services Expert (agent_001) who begins Geographic Proximity Analysis (task_001). This window shows the foundational setup with 3 entities and 2 relationships.",
+    "system_summary": "User query processing where the restaurant search request (input_001) is handled by Location-Based Services Expert (agent_001) performing Geographic Proximity Analysis (task_001) with Computer Terminal (agent_004) support.",
     "entities": [
+      {
+        "id": "input_001",
+        "type": "Input",
+        "name": "User Restaurant Query",
+        "importance": "HIGH",
+        "raw_prompt": "User request for closest eatery to Harkness Memorial State Park open at 11pm on Wednesdays",
+        "raw_prompt_ref": [
+          {
+            "line_start": 1,
+            "line_end": 3,
+            "confidence": 0.99
+          }
+        ]
+      },
       {
         "id": "agent_001",
         "type": "Agent",
@@ -34,16 +48,16 @@
         ]
       },
       {
-        "id": "input_001",
-        "type": "Input",
-        "name": "User Restaurant Query",
-        "importance": "HIGH",
-        "raw_prompt": "User request for closest eatery to Harkness Memorial State Park open at 11pm on Wednesdays",
+        "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": 1,
-            "line_end": 3,
-            "confidence": 0.99
+            "line_start": 75,
+            "line_end": 80,
+            "confidence": 0.85
           }
         ]
       }
@@ -78,6 +92,21 @@
             "confidence": 0.92
           }
         ]
+      },
+      {
+        "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": [],
@@ -86,17 +115,18 @@
       "window_info": {
         "window_index": 0,
         "window_total": 3,
-        "window_name": "Initial Query Stage",
-        "processing_stage": "初始查询阶段",
+        "window_name": "User Query & Geographic Analysis",
+        "processing_stage": "用户查询与地理分析",
         "trace_id": "algorithm_sample_1",
-        "processing_run_id": "sample_replay_001",
+        "processing_run_id": "sample_replay_002",
         "window_start_char": 0,
-        "window_end_char": 8675,
-        "entity_count": 3,
-        "relation_count": 2,
+        "window_end_char": 8500,
+        "entity_count": 4,
+        "relation_count": 3,
         "failure_count": 0,
         "optimization_count": 0,
-        "created_at": "2025-09-01T20:30:56.631864"
+        "created_at": "2025-09-01T22:13:16.171012",
+        "window_type": "independent_optimized"
       }
     }
   },
@@ -111,8 +141,8 @@
   "window_index": 0,
   "window_total": 3,
   "window_start_char": 0,
-  "window_end_char": 8675,
-  "processing_run_id": "sample_replay_001",
+  "window_end_char": 8500,
+  "processing_run_id": "sample_replay_002",
   "trace_id": "algorithm_sample_1",
   "is_final": false
 }

backend/database/samples/knowledge_graphs/kg_algorithm_sample_1_window_1.json

@@ -3,22 +3,8 @@
   "trace_index": 0,
   "graph_data": {
     "system_name": "Location-Based Restaurant Discovery System",
-    "system_summary": "Data collection stage where the Eateries Expert (agent_002) joins the workflow to perform Restaurant Data Collection (task_002). The system now involves 6 entities working together with 6 relationships established. Computer Terminal support is actively engaged for data processing tasks.",
+    "system_summary": "Independent restaurant data collection stage where Eateries Expert (agent_002) performs Restaurant Data Collection (task_002) to gather comprehensive restaurant information.",
     "entities": [
-      {
-        "id": "agent_001",
-        "type": "Agent",
-        "name": "Location-Based Services Expert",
-        "importance": "HIGH",
-        "raw_prompt": "Specialized in geographic information systems, spatial analysis, and location-based queries. Handles mapping services, distance calculations, and proximity analysis.",
-        "raw_prompt_ref": [
-          {
-            "line_start": 15,
-            "line_end": 25,
-            "confidence": 0.95
-          }
-        ]
-      },
       {
         "id": "agent_002",
         "type": "Agent",
@@ -33,34 +19,6 @@
           }
         ]
       },
-      {
-        "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": 75,
-            "line_end": 80,
-            "confidence": 0.85
-          }
-        ]
-      },
-      {
-        "id": "task_001",
-        "type": "Task",
-        "name": "Geographic Proximity Analysis",
-        "importance": "HIGH",
-        "raw_prompt": "Analyze geographic proximity between Harkness Memorial State Park and nearby restaurants. Calculate distances and identify closest establishments.",
-        "raw_prompt_ref": [
-          {
-            "line_start": 5,
-            "line_end": 10,
-            "confidence": 0.98
-          }
-        ]
-      },
       {
         "id": "task_002",
         "type": "Task",
@@ -74,53 +32,9 @@
             "confidence": 0.94
           }
         ]
-      },
-      {
-        "id": "input_001",
-        "type": "Input",
-        "name": "User Restaurant Query",
-        "importance": "HIGH",
-        "raw_prompt": "User request for closest eatery to Harkness Memorial State Park open at 11pm on Wednesdays",
-        "raw_prompt_ref": [
-          {
-            "line_start": 1,
-            "line_end": 3,
-            "confidence": 0.99
-          }
-        ]
       }
     ],
     "relations": [
-      {
-        "id": "rel_001",
-        "source": "input_001",
-        "target": "agent_001",
-        "type": "CONSUMED_BY",
-        "importance": "HIGH",
-        "interaction_prompt": "Location-based query consumed by Location-Based Services Expert",
-        "interaction_prompt_ref": [
-          {
-            "line_start": 5,
-            "line_end": 8,
-            "confidence": 0.95
-          }
-        ]
-      },
-      {
-        "id": "rel_002",
-        "source": "agent_001",
-        "target": "task_001",
-        "type": "PERFORMS",
-        "importance": "HIGH",
-        "interaction_prompt": "Location-Based Services Expert performs geographic proximity analysis",
-        "interaction_prompt_ref": [
-          {
-            "line_start": 15,
-            "line_end": 25,
-            "confidence": 0.92
-          }
-        ]
-      },
       {
         "id": "rel_003",
         "source": "agent_002",
@@ -135,102 +49,26 @@
             "confidence": 0.89
           }
         ]
-      },
-      {
-        "id": "rel_005",
-        "source": "task_001",
-        "target": "task_002",
-        "type": "NEXT",
-        "importance": "HIGH",
-        "interaction_prompt": "Geographic analysis leads to restaurant data collection",
-        "interaction_prompt_ref": [
-          {
-            "line_start": 25,
-            "line_end": 30,
-            "confidence": 0.88
-          }
-        ]
-      },
-      {
-        "id": "rel_009",
-        "source": "agent_004",
-        "target": "task_001",
-        "type": "REQUIRED_BY",
-        "importance": "MEDIUM",
-        "interaction_prompt": "Computational task requires Computer Terminal for execution",
-        "interaction_prompt_ref": [
-          {
-            "line_start": 20,
-            "line_end": 25,
-            "confidence": 0.8
-          }
-        ]
-      },
-      {
-        "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": [
-      {
-        "id": "failure_001",
-        "description": "Data Verification Expert failed to properly validate restaurant operating hours due to incorrect Python code implementation, leading to inaccurate 11pm availability data",
-        "raw_text": "",
-        "raw_text_ref": [
-          {
-            "line_start": 60,
-            "line_end": 65,
-            "confidence": 0.9
-          }
-        ],
-        "affected_id": "agent_003",
-        "risk_type": "EXECUTION_ERROR"
-      }
-    ],
-    "optimizations": [
-      {
-        "id": "opt_001",
-        "description": "Enhance location-based services with caching mechanisms and fallback data sources to improve reliability and reduce API dependency",
-        "raw_text": "Implement robust location service tools with redundancy",
-        "raw_text_ref": [
-          {
-            "line_start": 15,
-            "line_end": 25,
-            "confidence": 0.88
-          }
-        ],
-        "affected_ids": [
-          "agent_001"
-        ],
-        "recommendation_type": "TOOL_ENHANCEMENT"
       }
     ],
+    "failures": [],
+    "optimizations": [],
     "metadata": {
       "window_info": {
         "window_index": 1,
         "window_total": 3,
-        "window_name": "Data Collection Stage",
-        "processing_stage": "数据收集阶段",
+        "window_name": "Restaurant Data Collection",
+        "processing_stage": "餐厅数据收集",
         "trace_id": "algorithm_sample_1",
-        "processing_run_id": "sample_replay_001",
-        "window_start_char": 7808,
-        "window_end_char": 16483,
-        "entity_count": 6,
-        "relation_count": 6,
-        "failure_count": 1,
-        "optimization_count": 1,
-        "created_at": "2025-09-01T20:30:56.632296"
+        "processing_run_id": "sample_replay_002",
+        "window_start_char": 8500,
+        "window_end_char": 17500,
+        "entity_count": 2,
+        "relation_count": 1,
+        "failure_count": 0,
+        "optimization_count": 0,
+        "created_at": "2025-09-01T22:13:16.171426",
+        "window_type": "independent_optimized"
       }
     }
   },
@@ -244,9 +82,9 @@
   },
   "window_index": 1,
   "window_total": 3,
-  "window_start_char": 7808,
-  "window_end_char": 16483,
-  "processing_run_id": "sample_replay_001",
+  "window_start_char": 8500,
+  "window_end_char": 17500,
+  "processing_run_id": "sample_replay_002",
   "trace_id": "algorithm_sample_1",
   "is_final": false
 }

backend/database/samples/knowledge_graphs/kg_algorithm_sample_1_window_2.json

@@ -3,36 +3,8 @@
   "trace_index": 0,
   "graph_data": {
     "system_name": "Location-Based Restaurant Discovery System",
-    "system_summary": "This sophisticated system helps users find nearby restaurants based on complex criteria including location proximity, operating hours, and day-specific availability. The process begins with a location-based query from the `User Restaurant Query` (input_001), which is processed by the `Location-Based Services Expert` (agent_001) who performs the `Geographic Proximity Analysis` (task_001). The `Eateries Expert` (agent_002) handles `Restaurant Data Collection` (task_002), while the `Data Verification Expert` (agent_003) performs `Operating Hours Validation` (task_003). The `Computer Terminal` (agent_004) provides computational support throughout the workflow. The system produces comprehensive `Restaurant Recommendations` (output_001) that are delivered to the `End User` (human_001).",
+    "system_summary": "Final verification and delivery stage where Data Verification Expert (agent_003) validates data through Operating Hours Validation (task_003), produces Restaurant Recommendations (output_001), and delivers to End User (human_001).",
     "entities": [
-      {
-        "id": "agent_001",
-        "type": "Agent",
-        "name": "Location-Based Services Expert",
-        "importance": "HIGH",
-        "raw_prompt": "Specialized in geographic information systems, spatial analysis, and location-based queries. Handles mapping services, distance calculations, and proximity analysis.",
-        "raw_prompt_ref": [
-          {
-            "line_start": 15,
-            "line_end": 25,
-            "confidence": 0.95
-          }
-        ]
-      },
-      {
-        "id": "agent_002",
-        "type": "Agent",
-        "name": "Eateries Expert",
-        "importance": "HIGH",
-        "raw_prompt": "Expert in restaurant data, food service information, and dining establishment databases. Collects and analyzes restaurant information including cuisine types, ratings, and amenities.",
-        "raw_prompt_ref": [
-          {
-            "line_start": 35,
-            "line_end": 45,
-            "confidence": 0.92
-          }
-        ]
-      },
       {
         "id": "agent_003",
         "type": "Agent",
@@ -47,48 +19,6 @@
           }
         ]
       },
-      {
-        "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": 75,
-            "line_end": 80,
-            "confidence": 0.85
-          }
-        ]
-      },
-      {
-        "id": "task_001",
-        "type": "Task",
-        "name": "Geographic Proximity Analysis",
-        "importance": "HIGH",
-        "raw_prompt": "Analyze geographic proximity between Harkness Memorial State Park and nearby restaurants. Calculate distances and identify closest establishments.",
-        "raw_prompt_ref": [
-          {
-            "line_start": 5,
-            "line_end": 10,
-            "confidence": 0.98
-          }
-        ]
-      },
-      {
-        "id": "task_002",
-        "type": "Task",
-        "name": "Restaurant Data Collection",
-        "importance": "HIGH",
-        "raw_prompt": "Collect comprehensive restaurant data including operating hours, contact information, cuisine types, and availability information for Wednesday evenings.",
-        "raw_prompt_ref": [
-          {
-            "line_start": 25,
-            "line_end": 35,
-            "confidence": 0.94
-          }
-        ]
-      },
       {
         "id": "task_003",
         "type": "Task",
@@ -103,20 +33,6 @@
           }
         ]
       },
-      {
-        "id": "input_001",
-        "type": "Input",
-        "name": "User Restaurant Query",
-        "importance": "HIGH",
-        "raw_prompt": "User request for closest eatery to Harkness Memorial State Park open at 11pm on Wednesdays",
-        "raw_prompt_ref": [
-          {
-            "line_start": 1,
-            "line_end": 3,
-            "confidence": 0.99
-          }
-        ]
-      },
       {
         "id": "output_001",
         "type": "Output",
@@ -147,51 +63,6 @@
       }
     ],
     "relations": [
-      {
-        "id": "rel_001",
-        "source": "input_001",
-        "target": "agent_001",
-        "type": "CONSUMED_BY",
-        "importance": "HIGH",
-        "interaction_prompt": "Location-based query consumed by Location-Based Services Expert",
-        "interaction_prompt_ref": [
-          {
-            "line_start": 5,
-            "line_end": 8,
-            "confidence": 0.95
-          }
-        ]
-      },
-      {
-        "id": "rel_002",
-        "source": "agent_001",
-        "target": "task_001",
-        "type": "PERFORMS",
-        "importance": "HIGH",
-        "interaction_prompt": "Location-Based Services Expert performs geographic proximity analysis",
-        "interaction_prompt_ref": [
-          {
-            "line_start": 15,
-            "line_end": 25,
-            "confidence": 0.92
-          }
-        ]
-      },
-      {
-        "id": "rel_003",
-        "source": "agent_002",
-        "target": "task_002",
-        "type": "PERFORMS",
-        "importance": "HIGH",
-        "interaction_prompt": "Eateries Expert performs restaurant data collection",
-        "interaction_prompt_ref": [
-          {
-            "line_start": 35,
-            "line_end": 45,
-            "confidence": 0.89
-          }
-        ]
-      },
       {
         "id": "rel_004",
         "source": "agent_003",
@@ -207,36 +78,6 @@
           }
         ]
       },
-      {
-        "id": "rel_005",
-        "source": "task_001",
-        "target": "task_002",
-        "type": "NEXT",
-        "importance": "HIGH",
-        "interaction_prompt": "Geographic analysis leads to restaurant data collection",
-        "interaction_prompt_ref": [
-          {
-            "line_start": 25,
-            "line_end": 30,
-            "confidence": 0.88
-          }
-        ]
-      },
-      {
-        "id": "rel_006",
-        "source": "task_002",
-        "target": "task_003",
-        "type": "NEXT",
-        "importance": "HIGH",
-        "interaction_prompt": "Restaurant data collection followed by operating hours validation",
-        "interaction_prompt_ref": [
-          {
-            "line_start": 45,
-            "line_end": 50,
-            "confidence": 0.85
-          }
-        ]
-      },
       {
         "id": "rel_007",
         "source": "task_003",
@@ -266,136 +107,26 @@
             "confidence": 0.93
           }
         ]
-      },
-      {
-        "id": "rel_009",
-        "source": "agent_004",
-        "target": "task_001",
-        "type": "REQUIRED_BY",
-        "importance": "MEDIUM",
-        "interaction_prompt": "Computational task requires Computer Terminal for execution",
-        "interaction_prompt_ref": [
-          {
-            "line_start": 20,
-            "line_end": 25,
-            "confidence": 0.8
-          }
-        ]
-      },
-      {
-        "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": [
-      {
-        "id": "failure_001",
-        "description": "Data Verification Expert failed to properly validate restaurant operating hours due to incorrect Python code implementation, leading to inaccurate 11pm availability data",
-        "raw_text": "",
-        "raw_text_ref": [
-          {
-            "line_start": 60,
-            "line_end": 65,
-            "confidence": 0.9
-          }
-        ],
-        "affected_id": "agent_003",
-        "risk_type": "EXECUTION_ERROR"
-      },
-      {
-        "id": "failure_002",
-        "description": "Location-Based Services Expert encountered API limitations when accessing real-time restaurant data, resulting in incomplete proximity analysis",
-        "raw_text": "",
-        "raw_text_ref": [
-          {
-            "line_start": 18,
-            "line_end": 22,
-            "confidence": 0.85
-          }
-        ],
-        "affected_id": "agent_001",
-        "risk_type": "RETRIEVAL_ERROR"
-      }
-    ],
-    "optimizations": [
-      {
-        "id": "opt_001",
-        "description": "Enhance location-based services with caching mechanisms and fallback data sources to improve reliability and reduce API dependency",
-        "raw_text": "Implement robust location service tools with redundancy",
-        "raw_text_ref": [
-          {
-            "line_start": 15,
-            "line_end": 25,
-            "confidence": 0.88
-          }
-        ],
-        "affected_ids": [
-          "agent_001"
-        ],
-        "recommendation_type": "TOOL_ENHANCEMENT"
-      },
-      {
-        "id": "opt_002",
-        "description": "Combine restaurant data collection and operating hours validation into a single integrated task to reduce coordination overhead and improve data consistency",
-        "raw_text": "Merge data collection and validation workflows",
-        "raw_text_ref": [
-          {
-            "line_start": 35,
-            "line_end": 65,
-            "confidence": 0.82
-          }
-        ],
-        "affected_ids": [
-          "agent_002",
-          "agent_003",
-          "task_002",
-          "task_003"
-        ],
-        "recommendation_type": "WORKFLOW_SIMPLIFICATION"
-      },
-      {
-        "id": "opt_003",
-        "description": "Refine Data Verification Expert prompts to include specific error handling and validation procedures for time-sensitive restaurant data",
-        "raw_text": "Improve validation prompts with error handling",
-        "raw_text_ref": [
-          {
-            "line_start": 55,
-            "line_end": 65,
-            "confidence": 0.85
-          }
-        ],
-        "affected_ids": [
-          "agent_003"
-        ],
-        "recommendation_type": "PROMPT_REFINEMENT"
       }
     ],
+    "failures": [],
+    "optimizations": [],
     "metadata": {
       "window_info": {
         "window_index": 2,
         "window_total": 3,
-        "window_name": "Complete Processing Stage",
-        "processing_stage": "完整处理阶段",
+        "window_name": "Data Verification & Delivery",
+        "processing_stage": "数据验证与交付",
         "trace_id": "algorithm_sample_1",
-        "processing_run_id": "sample_replay_001",
-        "window_start_char": 15616,
+        "processing_run_id": "sample_replay_002",
+        "window_start_char": 17500,
         "window_end_char": 26025,
-        "entity_count": 10,
-        "relation_count": 10,
-        "failure_count": 2,
-        "optimization_count": 3,
-        "created_at": "2025-09-01T20:30:56.632700"
+        "entity_count": 4,
+        "relation_count": 3,
+        "failure_count": 0,
+        "optimization_count": 0,
+        "created_at": "2025-09-01T22:13:16.171686",
+        "window_type": "independent_optimized"
       }
     }
   },
@@ -409,9 +140,9 @@
   },
   "window_index": 2,
   "window_total": 3,
-  "window_start_char": 15616,
+  "window_start_char": 17500,
   "window_end_char": 26025,
-  "processing_run_id": "sample_replay_001",
+  "processing_run_id": "sample_replay_002",
   "trace_id": "algorithm_sample_1",
   "is_final": false
 }

backend/database/samples/samples_config.json

@@ -80,27 +80,32 @@
         "tool_enhancement_recommendations",
         "temporal_replay",
         "progressive_knowledge_evolution",
-        "window_based_visualization"
+        "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_001",
+        "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": [
-          "Location Analysis & Initial Query",
-          "Data Collection & Verification",
-          "Result Processing & Delivery"
+          "User Query & Geographic Analysis",
+          "Restaurant Data Collection",
+          "Data Verification & Delivery"
         ],
         "stage_descriptions": [
-          "用户查询处理和位置识别，位置专家开始地理分析",
-          "餐厅专家加入进行数据收集，计算工具提供支持，开始出现验证问题",
-          "数据验证专家完成最终验证，完整的结果处理和交付流程"
-        ]
+          "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"
       }
     },
     {
@@ -195,7 +200,7 @@
     }
   ],
   "metadata": {
-    "version": "2.1.0",
+    "version": "2.2.0",
     "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"