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6961471
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Parent(s):
f3d9d2c
add
Browse files- backend/database/samples/knowledge_graphs/kg_algorithm_sample_1_final.json +402 -0
- backend/database/samples/knowledge_graphs/kg_algorithm_sample_1_window_0.json +159 -0
- backend/database/samples/knowledge_graphs/kg_algorithm_sample_1_window_1.json +246 -0
- backend/database/samples/knowledge_graphs/kg_algorithm_sample_1_window_2.json +400 -0
- backend/database/samples/samples_config.json +42 -2
backend/database/samples/knowledge_graphs/kg_algorithm_sample_1_final.json
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| 1 |
+
{
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| 2 |
+
"filename": "kg_algorithm_sample_1_final",
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| 3 |
+
"trace_index": 0,
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| 4 |
+
"graph_data": {
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| 5 |
+
"system_name": "Location-Based Restaurant Discovery System",
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| 6 |
+
"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).",
|
| 7 |
+
"entities": [
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| 8 |
+
{
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| 9 |
+
"id": "agent_001",
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| 10 |
+
"type": "Agent",
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| 11 |
+
"name": "Location-Based Services Expert",
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| 12 |
+
"importance": "HIGH",
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| 13 |
+
"raw_prompt": "Specialized in geographic information systems, spatial analysis, and location-based queries. Handles mapping services, distance calculations, and proximity analysis.",
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| 14 |
+
"raw_prompt_ref": [
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| 15 |
+
{
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| 16 |
+
"line_start": 15,
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| 17 |
+
"line_end": 25,
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| 18 |
+
"confidence": 0.95
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| 19 |
+
}
|
| 20 |
+
]
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| 21 |
+
},
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| 22 |
+
{
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| 23 |
+
"id": "agent_002",
|
| 24 |
+
"type": "Agent",
|
| 25 |
+
"name": "Eateries Expert",
|
| 26 |
+
"importance": "HIGH",
|
| 27 |
+
"raw_prompt": "Expert in restaurant data, food service information, and dining establishment databases. Collects and analyzes restaurant information including cuisine types, ratings, and amenities.",
|
| 28 |
+
"raw_prompt_ref": [
|
| 29 |
+
{
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| 30 |
+
"line_start": 35,
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| 31 |
+
"line_end": 45,
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| 32 |
+
"confidence": 0.92
|
| 33 |
+
}
|
| 34 |
+
]
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| 35 |
+
},
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| 36 |
+
{
|
| 37 |
+
"id": "agent_003",
|
| 38 |
+
"type": "Agent",
|
| 39 |
+
"name": "Data Verification Expert",
|
| 40 |
+
"importance": "HIGH",
|
| 41 |
+
"raw_prompt": "Responsible for validating data accuracy, cross-referencing information sources, and ensuring data quality. Specializes in verification of business hours, contact information, and operational status.",
|
| 42 |
+
"raw_prompt_ref": [
|
| 43 |
+
{
|
| 44 |
+
"line_start": 55,
|
| 45 |
+
"line_end": 65,
|
| 46 |
+
"confidence": 0.88
|
| 47 |
+
}
|
| 48 |
+
]
|
| 49 |
+
},
|
| 50 |
+
{
|
| 51 |
+
"id": "agent_004",
|
| 52 |
+
"type": "Tool",
|
| 53 |
+
"name": "Computer Terminal",
|
| 54 |
+
"importance": "MEDIUM",
|
| 55 |
+
"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.",
|
| 56 |
+
"raw_prompt_ref": [
|
| 57 |
+
{
|
| 58 |
+
"line_start": 75,
|
| 59 |
+
"line_end": 80,
|
| 60 |
+
"confidence": 0.85
|
| 61 |
+
}
|
| 62 |
+
]
|
| 63 |
+
},
|
| 64 |
+
{
|
| 65 |
+
"id": "task_001",
|
| 66 |
+
"type": "Task",
|
| 67 |
+
"name": "Geographic Proximity Analysis",
|
| 68 |
+
"importance": "HIGH",
|
| 69 |
+
"raw_prompt": "Analyze geographic proximity between Harkness Memorial State Park and nearby restaurants. Calculate distances and identify closest establishments.",
|
| 70 |
+
"raw_prompt_ref": [
|
| 71 |
+
{
|
| 72 |
+
"line_start": 5,
|
| 73 |
+
"line_end": 10,
|
| 74 |
+
"confidence": 0.98
|
| 75 |
+
}
|
| 76 |
+
]
|
| 77 |
+
},
|
| 78 |
+
{
|
| 79 |
+
"id": "task_002",
|
| 80 |
+
"type": "Task",
|
| 81 |
+
"name": "Restaurant Data Collection",
|
| 82 |
+
"importance": "HIGH",
|
| 83 |
+
"raw_prompt": "Collect comprehensive restaurant data including operating hours, contact information, cuisine types, and availability information for Wednesday evenings.",
|
| 84 |
+
"raw_prompt_ref": [
|
| 85 |
+
{
|
| 86 |
+
"line_start": 25,
|
| 87 |
+
"line_end": 35,
|
| 88 |
+
"confidence": 0.94
|
| 89 |
+
}
|
| 90 |
+
]
|
| 91 |
+
},
|
| 92 |
+
{
|
| 93 |
+
"id": "task_003",
|
| 94 |
+
"type": "Task",
|
| 95 |
+
"name": "Operating Hours Validation",
|
| 96 |
+
"importance": "HIGH",
|
| 97 |
+
"raw_prompt": "Verify restaurant operating hours for Wednesday nights, specifically checking 11pm availability and cross-referencing multiple data sources.",
|
| 98 |
+
"raw_prompt_ref": [
|
| 99 |
+
{
|
| 100 |
+
"line_start": 45,
|
| 101 |
+
"line_end": 55,
|
| 102 |
+
"confidence": 0.91
|
| 103 |
+
}
|
| 104 |
+
]
|
| 105 |
+
},
|
| 106 |
+
{
|
| 107 |
+
"id": "input_001",
|
| 108 |
+
"type": "Input",
|
| 109 |
+
"name": "User Restaurant Query",
|
| 110 |
+
"importance": "HIGH",
|
| 111 |
+
"raw_prompt": "User request for closest eatery to Harkness Memorial State Park open at 11pm on Wednesdays",
|
| 112 |
+
"raw_prompt_ref": [
|
| 113 |
+
{
|
| 114 |
+
"line_start": 1,
|
| 115 |
+
"line_end": 3,
|
| 116 |
+
"confidence": 0.99
|
| 117 |
+
}
|
| 118 |
+
]
|
| 119 |
+
},
|
| 120 |
+
{
|
| 121 |
+
"id": "output_001",
|
| 122 |
+
"type": "Output",
|
| 123 |
+
"name": "Restaurant Recommendations",
|
| 124 |
+
"importance": "HIGH",
|
| 125 |
+
"raw_prompt": "Comprehensive restaurant recommendations with verified operating hours and proximity information",
|
| 126 |
+
"raw_prompt_ref": [
|
| 127 |
+
{
|
| 128 |
+
"line_start": 90,
|
| 129 |
+
"line_end": 95,
|
| 130 |
+
"confidence": 0.93
|
| 131 |
+
}
|
| 132 |
+
]
|
| 133 |
+
},
|
| 134 |
+
{
|
| 135 |
+
"id": "human_001",
|
| 136 |
+
"type": "Human",
|
| 137 |
+
"name": "End User",
|
| 138 |
+
"importance": "HIGH",
|
| 139 |
+
"raw_prompt": "User seeking restaurant recommendations near a specific location with time constraints",
|
| 140 |
+
"raw_prompt_ref": [
|
| 141 |
+
{
|
| 142 |
+
"line_start": 1,
|
| 143 |
+
"line_end": 1,
|
| 144 |
+
"confidence": 0.95
|
| 145 |
+
}
|
| 146 |
+
]
|
| 147 |
+
}
|
| 148 |
+
],
|
| 149 |
+
"relations": [
|
| 150 |
+
{
|
| 151 |
+
"id": "rel_001",
|
| 152 |
+
"source": "input_001",
|
| 153 |
+
"target": "agent_001",
|
| 154 |
+
"type": "CONSUMED_BY",
|
| 155 |
+
"importance": "HIGH",
|
| 156 |
+
"interaction_prompt": "Location-based query consumed by Location-Based Services Expert",
|
| 157 |
+
"interaction_prompt_ref": [
|
| 158 |
+
{
|
| 159 |
+
"line_start": 5,
|
| 160 |
+
"line_end": 8,
|
| 161 |
+
"confidence": 0.95
|
| 162 |
+
}
|
| 163 |
+
]
|
| 164 |
+
},
|
| 165 |
+
{
|
| 166 |
+
"id": "rel_002",
|
| 167 |
+
"source": "agent_001",
|
| 168 |
+
"target": "task_001",
|
| 169 |
+
"type": "PERFORMS",
|
| 170 |
+
"importance": "HIGH",
|
| 171 |
+
"interaction_prompt": "Location-Based Services Expert performs geographic proximity analysis",
|
| 172 |
+
"interaction_prompt_ref": [
|
| 173 |
+
{
|
| 174 |
+
"line_start": 15,
|
| 175 |
+
"line_end": 25,
|
| 176 |
+
"confidence": 0.92
|
| 177 |
+
}
|
| 178 |
+
]
|
| 179 |
+
},
|
| 180 |
+
{
|
| 181 |
+
"id": "rel_003",
|
| 182 |
+
"source": "agent_002",
|
| 183 |
+
"target": "task_002",
|
| 184 |
+
"type": "PERFORMS",
|
| 185 |
+
"importance": "HIGH",
|
| 186 |
+
"interaction_prompt": "Eateries Expert performs restaurant data collection",
|
| 187 |
+
"interaction_prompt_ref": [
|
| 188 |
+
{
|
| 189 |
+
"line_start": 35,
|
| 190 |
+
"line_end": 45,
|
| 191 |
+
"confidence": 0.89
|
| 192 |
+
}
|
| 193 |
+
]
|
| 194 |
+
},
|
| 195 |
+
{
|
| 196 |
+
"id": "rel_004",
|
| 197 |
+
"source": "agent_003",
|
| 198 |
+
"target": "task_003",
|
| 199 |
+
"type": "PERFORMS",
|
| 200 |
+
"importance": "HIGH",
|
| 201 |
+
"interaction_prompt": "Data Verification Expert performs operating hours validation",
|
| 202 |
+
"interaction_prompt_ref": [
|
| 203 |
+
{
|
| 204 |
+
"line_start": 55,
|
| 205 |
+
"line_end": 65,
|
| 206 |
+
"confidence": 0.87
|
| 207 |
+
}
|
| 208 |
+
]
|
| 209 |
+
},
|
| 210 |
+
{
|
| 211 |
+
"id": "rel_005",
|
| 212 |
+
"source": "task_001",
|
| 213 |
+
"target": "task_002",
|
| 214 |
+
"type": "NEXT",
|
| 215 |
+
"importance": "HIGH",
|
| 216 |
+
"interaction_prompt": "Geographic analysis leads to restaurant data collection",
|
| 217 |
+
"interaction_prompt_ref": [
|
| 218 |
+
{
|
| 219 |
+
"line_start": 25,
|
| 220 |
+
"line_end": 30,
|
| 221 |
+
"confidence": 0.88
|
| 222 |
+
}
|
| 223 |
+
]
|
| 224 |
+
},
|
| 225 |
+
{
|
| 226 |
+
"id": "rel_006",
|
| 227 |
+
"source": "task_002",
|
| 228 |
+
"target": "task_003",
|
| 229 |
+
"type": "NEXT",
|
| 230 |
+
"importance": "HIGH",
|
| 231 |
+
"interaction_prompt": "Restaurant data collection followed by operating hours validation",
|
| 232 |
+
"interaction_prompt_ref": [
|
| 233 |
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{
|
| 234 |
+
"line_start": 45,
|
| 235 |
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"line_end": 50,
|
| 236 |
+
"confidence": 0.85
|
| 237 |
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}
|
| 238 |
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]
|
| 239 |
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},
|
| 240 |
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{
|
| 241 |
+
"id": "rel_007",
|
| 242 |
+
"source": "task_003",
|
| 243 |
+
"target": "output_001",
|
| 244 |
+
"type": "PRODUCES",
|
| 245 |
+
"importance": "HIGH",
|
| 246 |
+
"interaction_prompt": "Validation task produces final restaurant recommendations",
|
| 247 |
+
"interaction_prompt_ref": [
|
| 248 |
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{
|
| 249 |
+
"line_start": 90,
|
| 250 |
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"line_end": 95,
|
| 251 |
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"confidence": 0.92
|
| 252 |
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}
|
| 253 |
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]
|
| 254 |
+
},
|
| 255 |
+
{
|
| 256 |
+
"id": "rel_008",
|
| 257 |
+
"source": "output_001",
|
| 258 |
+
"target": "human_001",
|
| 259 |
+
"type": "DELIVERS_TO",
|
| 260 |
+
"importance": "HIGH",
|
| 261 |
+
"interaction_prompt": "Restaurant recommendations delivered to end user",
|
| 262 |
+
"interaction_prompt_ref": [
|
| 263 |
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{
|
| 264 |
+
"line_start": 95,
|
| 265 |
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"line_end": 100,
|
| 266 |
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"confidence": 0.93
|
| 267 |
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}
|
| 268 |
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]
|
| 269 |
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},
|
| 270 |
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{
|
| 271 |
+
"id": "rel_009",
|
| 272 |
+
"source": "agent_004",
|
| 273 |
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"target": "task_001",
|
| 274 |
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"type": "REQUIRED_BY",
|
| 275 |
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"importance": "MEDIUM",
|
| 276 |
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"interaction_prompt": "Computational task requires Computer Terminal for execution",
|
| 277 |
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"interaction_prompt_ref": [
|
| 278 |
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{
|
| 279 |
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"line_start": 20,
|
| 280 |
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"line_end": 25,
|
| 281 |
+
"confidence": 0.8
|
| 282 |
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}
|
| 283 |
+
]
|
| 284 |
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},
|
| 285 |
+
{
|
| 286 |
+
"id": "rel_uses_computer",
|
| 287 |
+
"source": "agent_001",
|
| 288 |
+
"target": "agent_004",
|
| 289 |
+
"type": "USES",
|
| 290 |
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"importance": "MEDIUM",
|
| 291 |
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"interaction_prompt": "Agent uses Computer Terminal for computational tasks",
|
| 292 |
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"interaction_prompt_ref": [
|
| 293 |
+
{
|
| 294 |
+
"line_start": 50,
|
| 295 |
+
"line_end": 55,
|
| 296 |
+
"confidence": 0.8
|
| 297 |
+
}
|
| 298 |
+
]
|
| 299 |
+
}
|
| 300 |
+
],
|
| 301 |
+
"failures": [
|
| 302 |
+
{
|
| 303 |
+
"id": "failure_001",
|
| 304 |
+
"description": "Data Verification Expert failed to properly validate restaurant operating hours due to incorrect Python code implementation, leading to inaccurate 11pm availability data",
|
| 305 |
+
"raw_text": "",
|
| 306 |
+
"raw_text_ref": [
|
| 307 |
+
{
|
| 308 |
+
"line_start": 60,
|
| 309 |
+
"line_end": 65,
|
| 310 |
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"confidence": 0.9
|
| 311 |
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}
|
| 312 |
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],
|
| 313 |
+
"affected_id": "agent_003",
|
| 314 |
+
"risk_type": "EXECUTION_ERROR"
|
| 315 |
+
},
|
| 316 |
+
{
|
| 317 |
+
"id": "failure_002",
|
| 318 |
+
"description": "Location-Based Services Expert encountered API limitations when accessing real-time restaurant data, resulting in incomplete proximity analysis",
|
| 319 |
+
"raw_text": "",
|
| 320 |
+
"raw_text_ref": [
|
| 321 |
+
{
|
| 322 |
+
"line_start": 18,
|
| 323 |
+
"line_end": 22,
|
| 324 |
+
"confidence": 0.85
|
| 325 |
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}
|
| 326 |
+
],
|
| 327 |
+
"affected_id": "agent_001",
|
| 328 |
+
"risk_type": "RETRIEVAL_ERROR"
|
| 329 |
+
}
|
| 330 |
+
],
|
| 331 |
+
"optimizations": [
|
| 332 |
+
{
|
| 333 |
+
"id": "opt_001",
|
| 334 |
+
"description": "Enhance location-based services with caching mechanisms and fallback data sources to improve reliability and reduce API dependency",
|
| 335 |
+
"raw_text": "Implement robust location service tools with redundancy",
|
| 336 |
+
"raw_text_ref": [
|
| 337 |
+
{
|
| 338 |
+
"line_start": 15,
|
| 339 |
+
"line_end": 25,
|
| 340 |
+
"confidence": 0.88
|
| 341 |
+
}
|
| 342 |
+
],
|
| 343 |
+
"affected_ids": [
|
| 344 |
+
"agent_001"
|
| 345 |
+
],
|
| 346 |
+
"recommendation_type": "TOOL_ENHANCEMENT"
|
| 347 |
+
},
|
| 348 |
+
{
|
| 349 |
+
"id": "opt_002",
|
| 350 |
+
"description": "Combine restaurant data collection and operating hours validation into a single integrated task to reduce coordination overhead and improve data consistency",
|
| 351 |
+
"raw_text": "Merge data collection and validation workflows",
|
| 352 |
+
"raw_text_ref": [
|
| 353 |
+
{
|
| 354 |
+
"line_start": 35,
|
| 355 |
+
"line_end": 65,
|
| 356 |
+
"confidence": 0.82
|
| 357 |
+
}
|
| 358 |
+
],
|
| 359 |
+
"affected_ids": [
|
| 360 |
+
"agent_002",
|
| 361 |
+
"agent_003",
|
| 362 |
+
"task_002",
|
| 363 |
+
"task_003"
|
| 364 |
+
],
|
| 365 |
+
"recommendation_type": "WORKFLOW_SIMPLIFICATION"
|
| 366 |
+
},
|
| 367 |
+
{
|
| 368 |
+
"id": "opt_003",
|
| 369 |
+
"description": "Refine Data Verification Expert prompts to include specific error handling and validation procedures for time-sensitive restaurant data",
|
| 370 |
+
"raw_text": "Improve validation prompts with error handling",
|
| 371 |
+
"raw_text_ref": [
|
| 372 |
+
{
|
| 373 |
+
"line_start": 55,
|
| 374 |
+
"line_end": 65,
|
| 375 |
+
"confidence": 0.85
|
| 376 |
+
}
|
| 377 |
+
],
|
| 378 |
+
"affected_ids": [
|
| 379 |
+
"agent_003"
|
| 380 |
+
],
|
| 381 |
+
"recommendation_type": "PROMPT_REFINEMENT"
|
| 382 |
+
}
|
| 383 |
+
],
|
| 384 |
+
"metadata": {
|
| 385 |
+
"creation_timestamp": "2025-09-01T20:00:51.719651",
|
| 386 |
+
"trace_info": {
|
| 387 |
+
"trace_id": "sample_replay_demo_ff9c601e",
|
| 388 |
+
"processing_run_id": "bcbffcc9",
|
| 389 |
+
"window_count": 3,
|
| 390 |
+
"is_final": true
|
| 391 |
+
}
|
| 392 |
+
}
|
| 393 |
+
},
|
| 394 |
+
"extraction_info": {
|
| 395 |
+
"method": "enhanced_mock_creation",
|
| 396 |
+
"model": "human_designed",
|
| 397 |
+
"timestamp": "2025-01-27",
|
| 398 |
+
"api_key_used": "[REDACTED]",
|
| 399 |
+
"no_enhancement": false,
|
| 400 |
+
"source": "manual_design_for_demo"
|
| 401 |
+
}
|
| 402 |
+
}
|
backend/database/samples/knowledge_graphs/kg_algorithm_sample_1_window_0.json
ADDED
|
@@ -0,0 +1,159 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"filename": "kg_algorithm_sample_1_window_0",
|
| 3 |
+
"trace_index": 0,
|
| 4 |
+
"graph_data": {
|
| 5 |
+
"system_name": "Location-Based Restaurant Discovery System (Window 1)",
|
| 6 |
+
"system_summary": "用户发起餐厅查询,位置服务专家开始地理邻近性分析。系统初始化并识别核心需求。",
|
| 7 |
+
"entities": [
|
| 8 |
+
{
|
| 9 |
+
"id": "input_001",
|
| 10 |
+
"type": "Input",
|
| 11 |
+
"name": "User Restaurant Query",
|
| 12 |
+
"importance": "HIGH",
|
| 13 |
+
"raw_prompt": "User request for closest eatery to Harkness Memorial State Park open at 11pm on Wednesdays",
|
| 14 |
+
"raw_prompt_ref": [
|
| 15 |
+
{
|
| 16 |
+
"line_start": 1,
|
| 17 |
+
"line_end": 3,
|
| 18 |
+
"confidence": 0.99
|
| 19 |
+
}
|
| 20 |
+
]
|
| 21 |
+
},
|
| 22 |
+
{
|
| 23 |
+
"id": "agent_001",
|
| 24 |
+
"type": "Agent",
|
| 25 |
+
"name": "Location-Based Services Expert",
|
| 26 |
+
"importance": "HIGH",
|
| 27 |
+
"raw_prompt": "Specialized in geographic information systems, spatial analysis, and location-based queries. Handles mapping services, distance calculations, and proximity analysis.",
|
| 28 |
+
"raw_prompt_ref": [
|
| 29 |
+
{
|
| 30 |
+
"line_start": 15,
|
| 31 |
+
"line_end": 25,
|
| 32 |
+
"confidence": 0.95
|
| 33 |
+
}
|
| 34 |
+
]
|
| 35 |
+
},
|
| 36 |
+
{
|
| 37 |
+
"id": "agent_002",
|
| 38 |
+
"type": "Agent",
|
| 39 |
+
"name": "Eateries Expert",
|
| 40 |
+
"importance": "HIGH",
|
| 41 |
+
"raw_prompt": "Expert in restaurant data, food service information, and dining establishment databases. Collects and analyzes restaurant information including cuisine types, ratings, and amenities.",
|
| 42 |
+
"raw_prompt_ref": [
|
| 43 |
+
{
|
| 44 |
+
"line_start": 35,
|
| 45 |
+
"line_end": 45,
|
| 46 |
+
"confidence": 0.92
|
| 47 |
+
}
|
| 48 |
+
]
|
| 49 |
+
},
|
| 50 |
+
{
|
| 51 |
+
"id": "task_001",
|
| 52 |
+
"type": "Task",
|
| 53 |
+
"name": "Geographic Proximity Analysis",
|
| 54 |
+
"importance": "HIGH",
|
| 55 |
+
"raw_prompt": "Analyze geographic proximity between Harkness Memorial State Park and nearby restaurants. Calculate distances and identify closest establishments.",
|
| 56 |
+
"raw_prompt_ref": [
|
| 57 |
+
{
|
| 58 |
+
"line_start": 5,
|
| 59 |
+
"line_end": 10,
|
| 60 |
+
"confidence": 0.98
|
| 61 |
+
}
|
| 62 |
+
]
|
| 63 |
+
},
|
| 64 |
+
{
|
| 65 |
+
"id": "agent_004",
|
| 66 |
+
"type": "Tool",
|
| 67 |
+
"name": "Computer Terminal",
|
| 68 |
+
"importance": "MEDIUM",
|
| 69 |
+
"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.",
|
| 70 |
+
"raw_prompt_ref": [
|
| 71 |
+
{
|
| 72 |
+
"line_start": 75,
|
| 73 |
+
"line_end": 80,
|
| 74 |
+
"confidence": 0.85
|
| 75 |
+
}
|
| 76 |
+
]
|
| 77 |
+
}
|
| 78 |
+
],
|
| 79 |
+
"relations": [
|
| 80 |
+
{
|
| 81 |
+
"id": "rel_001",
|
| 82 |
+
"source": "input_001",
|
| 83 |
+
"target": "agent_001",
|
| 84 |
+
"type": "CONSUMED_BY",
|
| 85 |
+
"importance": "HIGH",
|
| 86 |
+
"interaction_prompt": "Location-based query consumed by Location-Based Services Expert",
|
| 87 |
+
"interaction_prompt_ref": [
|
| 88 |
+
{
|
| 89 |
+
"line_start": 5,
|
| 90 |
+
"line_end": 8,
|
| 91 |
+
"confidence": 0.95
|
| 92 |
+
}
|
| 93 |
+
]
|
| 94 |
+
},
|
| 95 |
+
{
|
| 96 |
+
"id": "rel_002",
|
| 97 |
+
"source": "agent_001",
|
| 98 |
+
"target": "task_001",
|
| 99 |
+
"type": "PERFORMS",
|
| 100 |
+
"importance": "HIGH",
|
| 101 |
+
"interaction_prompt": "Location-Based Services Expert performs geographic proximity analysis",
|
| 102 |
+
"interaction_prompt_ref": [
|
| 103 |
+
{
|
| 104 |
+
"line_start": 15,
|
| 105 |
+
"line_end": 25,
|
| 106 |
+
"confidence": 0.92
|
| 107 |
+
}
|
| 108 |
+
]
|
| 109 |
+
},
|
| 110 |
+
{
|
| 111 |
+
"id": "rel_009",
|
| 112 |
+
"source": "agent_004",
|
| 113 |
+
"target": "task_001",
|
| 114 |
+
"type": "REQUIRED_BY",
|
| 115 |
+
"importance": "MEDIUM",
|
| 116 |
+
"interaction_prompt": "Computational task requires Computer Terminal for execution",
|
| 117 |
+
"interaction_prompt_ref": [
|
| 118 |
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{
|
| 119 |
+
"line_start": 20,
|
| 120 |
+
"line_end": 25,
|
| 121 |
+
"confidence": 0.8
|
| 122 |
+
}
|
| 123 |
+
]
|
| 124 |
+
},
|
| 125 |
+
{
|
| 126 |
+
"id": "rel_uses_computer",
|
| 127 |
+
"source": "agent_001",
|
| 128 |
+
"target": "agent_004",
|
| 129 |
+
"type": "USES",
|
| 130 |
+
"importance": "MEDIUM",
|
| 131 |
+
"interaction_prompt": "Agent uses Computer Terminal for computational tasks",
|
| 132 |
+
"interaction_prompt_ref": [
|
| 133 |
+
{
|
| 134 |
+
"line_start": 50,
|
| 135 |
+
"line_end": 55,
|
| 136 |
+
"confidence": 0.8
|
| 137 |
+
}
|
| 138 |
+
]
|
| 139 |
+
}
|
| 140 |
+
],
|
| 141 |
+
"failures": [],
|
| 142 |
+
"optimizations": [],
|
| 143 |
+
"metadata": {
|
| 144 |
+
"creation_timestamp": "2025-09-01T20:00:51.718586",
|
| 145 |
+
"window_info": {
|
| 146 |
+
"window_index": 0,
|
| 147 |
+
"window_total": 3,
|
| 148 |
+
"trace_id": "sample_replay_demo_ff9c601e",
|
| 149 |
+
"processing_run_id": "bcbffcc9",
|
| 150 |
+
"window_start_char": 0,
|
| 151 |
+
"window_end_char": 3500,
|
| 152 |
+
"chunk_size": 3500,
|
| 153 |
+
"splitter_type": "demo_window",
|
| 154 |
+
"entities_count": 5,
|
| 155 |
+
"relations_count": 4
|
| 156 |
+
}
|
| 157 |
+
}
|
| 158 |
+
}
|
| 159 |
+
}
|
backend/database/samples/knowledge_graphs/kg_algorithm_sample_1_window_1.json
ADDED
|
@@ -0,0 +1,246 @@
|
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|
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|
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|
|
|
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|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
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|
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|
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|
|
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|
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|
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|
|
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|
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|
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|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"filename": "kg_algorithm_sample_1_window_1",
|
| 3 |
+
"trace_index": 1,
|
| 4 |
+
"graph_data": {
|
| 5 |
+
"system_name": "Location-Based Restaurant Discovery System (Window 2)",
|
| 6 |
+
"system_summary": "餐厅专家收集数据,数据验证专家进行营业时间验证。系统扩展分析能力并处理更复杂的查询。",
|
| 7 |
+
"entities": [
|
| 8 |
+
{
|
| 9 |
+
"id": "input_001",
|
| 10 |
+
"type": "Input",
|
| 11 |
+
"name": "User Restaurant Query",
|
| 12 |
+
"importance": "HIGH",
|
| 13 |
+
"raw_prompt": "User request for closest eatery to Harkness Memorial State Park open at 11pm on Wednesdays",
|
| 14 |
+
"raw_prompt_ref": [
|
| 15 |
+
{
|
| 16 |
+
"line_start": 1,
|
| 17 |
+
"line_end": 3,
|
| 18 |
+
"confidence": 0.99
|
| 19 |
+
}
|
| 20 |
+
]
|
| 21 |
+
},
|
| 22 |
+
{
|
| 23 |
+
"id": "agent_001",
|
| 24 |
+
"type": "Agent",
|
| 25 |
+
"name": "Location-Based Services Expert",
|
| 26 |
+
"importance": "HIGH",
|
| 27 |
+
"raw_prompt": "Specialized in geographic information systems, spatial analysis, and location-based queries. Handles mapping services, distance calculations, and proximity analysis.",
|
| 28 |
+
"raw_prompt_ref": [
|
| 29 |
+
{
|
| 30 |
+
"line_start": 15,
|
| 31 |
+
"line_end": 25,
|
| 32 |
+
"confidence": 0.95
|
| 33 |
+
}
|
| 34 |
+
]
|
| 35 |
+
},
|
| 36 |
+
{
|
| 37 |
+
"id": "agent_002",
|
| 38 |
+
"type": "Agent",
|
| 39 |
+
"name": "Eateries Expert",
|
| 40 |
+
"importance": "HIGH",
|
| 41 |
+
"raw_prompt": "Expert in restaurant data, food service information, and dining establishment databases. Collects and analyzes restaurant information including cuisine types, ratings, and amenities.",
|
| 42 |
+
"raw_prompt_ref": [
|
| 43 |
+
{
|
| 44 |
+
"line_start": 35,
|
| 45 |
+
"line_end": 45,
|
| 46 |
+
"confidence": 0.92
|
| 47 |
+
}
|
| 48 |
+
]
|
| 49 |
+
},
|
| 50 |
+
{
|
| 51 |
+
"id": "agent_003",
|
| 52 |
+
"type": "Agent",
|
| 53 |
+
"name": "Data Verification Expert",
|
| 54 |
+
"importance": "HIGH",
|
| 55 |
+
"raw_prompt": "Responsible for validating data accuracy, cross-referencing information sources, and ensuring data quality. Specializes in verification of business hours, contact information, and operational status.",
|
| 56 |
+
"raw_prompt_ref": [
|
| 57 |
+
{
|
| 58 |
+
"line_start": 55,
|
| 59 |
+
"line_end": 65,
|
| 60 |
+
"confidence": 0.88
|
| 61 |
+
}
|
| 62 |
+
]
|
| 63 |
+
},
|
| 64 |
+
{
|
| 65 |
+
"id": "task_001",
|
| 66 |
+
"type": "Task",
|
| 67 |
+
"name": "Geographic Proximity Analysis",
|
| 68 |
+
"importance": "HIGH",
|
| 69 |
+
"raw_prompt": "Analyze geographic proximity between Harkness Memorial State Park and nearby restaurants. Calculate distances and identify closest establishments.",
|
| 70 |
+
"raw_prompt_ref": [
|
| 71 |
+
{
|
| 72 |
+
"line_start": 5,
|
| 73 |
+
"line_end": 10,
|
| 74 |
+
"confidence": 0.98
|
| 75 |
+
}
|
| 76 |
+
]
|
| 77 |
+
},
|
| 78 |
+
{
|
| 79 |
+
"id": "task_002",
|
| 80 |
+
"type": "Task",
|
| 81 |
+
"name": "Restaurant Data Collection",
|
| 82 |
+
"importance": "HIGH",
|
| 83 |
+
"raw_prompt": "Collect comprehensive restaurant data including operating hours, contact information, cuisine types, and availability information for Wednesday evenings.",
|
| 84 |
+
"raw_prompt_ref": [
|
| 85 |
+
{
|
| 86 |
+
"line_start": 25,
|
| 87 |
+
"line_end": 35,
|
| 88 |
+
"confidence": 0.94
|
| 89 |
+
}
|
| 90 |
+
]
|
| 91 |
+
},
|
| 92 |
+
{
|
| 93 |
+
"id": "agent_004",
|
| 94 |
+
"type": "Tool",
|
| 95 |
+
"name": "Computer Terminal",
|
| 96 |
+
"importance": "MEDIUM",
|
| 97 |
+
"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.",
|
| 98 |
+
"raw_prompt_ref": [
|
| 99 |
+
{
|
| 100 |
+
"line_start": 75,
|
| 101 |
+
"line_end": 80,
|
| 102 |
+
"confidence": 0.85
|
| 103 |
+
}
|
| 104 |
+
]
|
| 105 |
+
},
|
| 106 |
+
{
|
| 107 |
+
"id": "output_001",
|
| 108 |
+
"type": "Output",
|
| 109 |
+
"name": "Restaurant Recommendations",
|
| 110 |
+
"importance": "HIGH",
|
| 111 |
+
"raw_prompt": "Comprehensive restaurant recommendations with verified operating hours and proximity information",
|
| 112 |
+
"raw_prompt_ref": [
|
| 113 |
+
{
|
| 114 |
+
"line_start": 90,
|
| 115 |
+
"line_end": 95,
|
| 116 |
+
"confidence": 0.93
|
| 117 |
+
}
|
| 118 |
+
]
|
| 119 |
+
}
|
| 120 |
+
],
|
| 121 |
+
"relations": [
|
| 122 |
+
{
|
| 123 |
+
"id": "rel_001",
|
| 124 |
+
"source": "input_001",
|
| 125 |
+
"target": "agent_001",
|
| 126 |
+
"type": "CONSUMED_BY",
|
| 127 |
+
"importance": "HIGH",
|
| 128 |
+
"interaction_prompt": "Location-based query consumed by Location-Based Services Expert",
|
| 129 |
+
"interaction_prompt_ref": [
|
| 130 |
+
{
|
| 131 |
+
"line_start": 5,
|
| 132 |
+
"line_end": 8,
|
| 133 |
+
"confidence": 0.95
|
| 134 |
+
}
|
| 135 |
+
]
|
| 136 |
+
},
|
| 137 |
+
{
|
| 138 |
+
"id": "rel_002",
|
| 139 |
+
"source": "agent_001",
|
| 140 |
+
"target": "task_001",
|
| 141 |
+
"type": "PERFORMS",
|
| 142 |
+
"importance": "HIGH",
|
| 143 |
+
"interaction_prompt": "Location-Based Services Expert performs geographic proximity analysis",
|
| 144 |
+
"interaction_prompt_ref": [
|
| 145 |
+
{
|
| 146 |
+
"line_start": 15,
|
| 147 |
+
"line_end": 25,
|
| 148 |
+
"confidence": 0.92
|
| 149 |
+
}
|
| 150 |
+
]
|
| 151 |
+
},
|
| 152 |
+
{
|
| 153 |
+
"id": "rel_003",
|
| 154 |
+
"source": "agent_002",
|
| 155 |
+
"target": "task_002",
|
| 156 |
+
"type": "PERFORMS",
|
| 157 |
+
"importance": "HIGH",
|
| 158 |
+
"interaction_prompt": "Eateries Expert performs restaurant data collection",
|
| 159 |
+
"interaction_prompt_ref": [
|
| 160 |
+
{
|
| 161 |
+
"line_start": 35,
|
| 162 |
+
"line_end": 45,
|
| 163 |
+
"confidence": 0.89
|
| 164 |
+
}
|
| 165 |
+
]
|
| 166 |
+
},
|
| 167 |
+
{
|
| 168 |
+
"id": "rel_005",
|
| 169 |
+
"source": "task_001",
|
| 170 |
+
"target": "task_002",
|
| 171 |
+
"type": "NEXT",
|
| 172 |
+
"importance": "HIGH",
|
| 173 |
+
"interaction_prompt": "Geographic analysis leads to restaurant data collection",
|
| 174 |
+
"interaction_prompt_ref": [
|
| 175 |
+
{
|
| 176 |
+
"line_start": 25,
|
| 177 |
+
"line_end": 30,
|
| 178 |
+
"confidence": 0.88
|
| 179 |
+
}
|
| 180 |
+
]
|
| 181 |
+
},
|
| 182 |
+
{
|
| 183 |
+
"id": "rel_009",
|
| 184 |
+
"source": "agent_004",
|
| 185 |
+
"target": "task_001",
|
| 186 |
+
"type": "REQUIRED_BY",
|
| 187 |
+
"importance": "MEDIUM",
|
| 188 |
+
"interaction_prompt": "Computational task requires Computer Terminal for execution",
|
| 189 |
+
"interaction_prompt_ref": [
|
| 190 |
+
{
|
| 191 |
+
"line_start": 20,
|
| 192 |
+
"line_end": 25,
|
| 193 |
+
"confidence": 0.8
|
| 194 |
+
}
|
| 195 |
+
]
|
| 196 |
+
},
|
| 197 |
+
{
|
| 198 |
+
"id": "rel_uses_computer",
|
| 199 |
+
"source": "agent_001",
|
| 200 |
+
"target": "agent_004",
|
| 201 |
+
"type": "USES",
|
| 202 |
+
"importance": "MEDIUM",
|
| 203 |
+
"interaction_prompt": "Agent uses Computer Terminal for computational tasks",
|
| 204 |
+
"interaction_prompt_ref": [
|
| 205 |
+
{
|
| 206 |
+
"line_start": 50,
|
| 207 |
+
"line_end": 55,
|
| 208 |
+
"confidence": 0.8
|
| 209 |
+
}
|
| 210 |
+
]
|
| 211 |
+
}
|
| 212 |
+
],
|
| 213 |
+
"failures": [
|
| 214 |
+
{
|
| 215 |
+
"id": "failure_001",
|
| 216 |
+
"description": "Data Verification Expert failed to properly validate restaurant operating hours due to incorrect Python code implementation, leading to inaccurate 11pm availability data",
|
| 217 |
+
"raw_text": "",
|
| 218 |
+
"raw_text_ref": [
|
| 219 |
+
{
|
| 220 |
+
"line_start": 60,
|
| 221 |
+
"line_end": 65,
|
| 222 |
+
"confidence": 0.9
|
| 223 |
+
}
|
| 224 |
+
],
|
| 225 |
+
"affected_id": "agent_003",
|
| 226 |
+
"risk_type": "EXECUTION_ERROR"
|
| 227 |
+
}
|
| 228 |
+
],
|
| 229 |
+
"optimizations": [],
|
| 230 |
+
"metadata": {
|
| 231 |
+
"creation_timestamp": "2025-09-01T20:00:51.718956",
|
| 232 |
+
"window_info": {
|
| 233 |
+
"window_index": 1,
|
| 234 |
+
"window_total": 3,
|
| 235 |
+
"trace_id": "sample_replay_demo_ff9c601e",
|
| 236 |
+
"processing_run_id": "bcbffcc9",
|
| 237 |
+
"window_start_char": 3500,
|
| 238 |
+
"window_end_char": 7000,
|
| 239 |
+
"chunk_size": 3500,
|
| 240 |
+
"splitter_type": "demo_window",
|
| 241 |
+
"entities_count": 8,
|
| 242 |
+
"relations_count": 6
|
| 243 |
+
}
|
| 244 |
+
}
|
| 245 |
+
}
|
| 246 |
+
}
|
backend/database/samples/knowledge_graphs/kg_algorithm_sample_1_window_2.json
ADDED
|
@@ -0,0 +1,400 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
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|
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|
|
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|
|
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|
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|
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|
|
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|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
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|
| 1 |
+
{
|
| 2 |
+
"filename": "kg_algorithm_sample_1_window_2",
|
| 3 |
+
"trace_index": 2,
|
| 4 |
+
"graph_data": {
|
| 5 |
+
"system_name": "Location-Based Restaurant Discovery System (Window 3)",
|
| 6 |
+
"system_summary": "系统完成所有分析,生成综合餐厅推荐并交付给最终用户。完成完整的发现工作流程。",
|
| 7 |
+
"entities": [
|
| 8 |
+
{
|
| 9 |
+
"id": "agent_001",
|
| 10 |
+
"type": "Agent",
|
| 11 |
+
"name": "Location-Based Services Expert",
|
| 12 |
+
"importance": "HIGH",
|
| 13 |
+
"raw_prompt": "Specialized in geographic information systems, spatial analysis, and location-based queries. Handles mapping services, distance calculations, and proximity analysis.",
|
| 14 |
+
"raw_prompt_ref": [
|
| 15 |
+
{
|
| 16 |
+
"line_start": 15,
|
| 17 |
+
"line_end": 25,
|
| 18 |
+
"confidence": 0.95
|
| 19 |
+
}
|
| 20 |
+
]
|
| 21 |
+
},
|
| 22 |
+
{
|
| 23 |
+
"id": "agent_002",
|
| 24 |
+
"type": "Agent",
|
| 25 |
+
"name": "Eateries Expert",
|
| 26 |
+
"importance": "HIGH",
|
| 27 |
+
"raw_prompt": "Expert in restaurant data, food service information, and dining establishment databases. Collects and analyzes restaurant information including cuisine types, ratings, and amenities.",
|
| 28 |
+
"raw_prompt_ref": [
|
| 29 |
+
{
|
| 30 |
+
"line_start": 35,
|
| 31 |
+
"line_end": 45,
|
| 32 |
+
"confidence": 0.92
|
| 33 |
+
}
|
| 34 |
+
]
|
| 35 |
+
},
|
| 36 |
+
{
|
| 37 |
+
"id": "agent_003",
|
| 38 |
+
"type": "Agent",
|
| 39 |
+
"name": "Data Verification Expert",
|
| 40 |
+
"importance": "HIGH",
|
| 41 |
+
"raw_prompt": "Responsible for validating data accuracy, cross-referencing information sources, and ensuring data quality. Specializes in verification of business hours, contact information, and operational status.",
|
| 42 |
+
"raw_prompt_ref": [
|
| 43 |
+
{
|
| 44 |
+
"line_start": 55,
|
| 45 |
+
"line_end": 65,
|
| 46 |
+
"confidence": 0.88
|
| 47 |
+
}
|
| 48 |
+
]
|
| 49 |
+
},
|
| 50 |
+
{
|
| 51 |
+
"id": "agent_004",
|
| 52 |
+
"type": "Tool",
|
| 53 |
+
"name": "Computer Terminal",
|
| 54 |
+
"importance": "MEDIUM",
|
| 55 |
+
"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.",
|
| 56 |
+
"raw_prompt_ref": [
|
| 57 |
+
{
|
| 58 |
+
"line_start": 75,
|
| 59 |
+
"line_end": 80,
|
| 60 |
+
"confidence": 0.85
|
| 61 |
+
}
|
| 62 |
+
]
|
| 63 |
+
},
|
| 64 |
+
{
|
| 65 |
+
"id": "task_001",
|
| 66 |
+
"type": "Task",
|
| 67 |
+
"name": "Geographic Proximity Analysis",
|
| 68 |
+
"importance": "HIGH",
|
| 69 |
+
"raw_prompt": "Analyze geographic proximity between Harkness Memorial State Park and nearby restaurants. Calculate distances and identify closest establishments.",
|
| 70 |
+
"raw_prompt_ref": [
|
| 71 |
+
{
|
| 72 |
+
"line_start": 5,
|
| 73 |
+
"line_end": 10,
|
| 74 |
+
"confidence": 0.98
|
| 75 |
+
}
|
| 76 |
+
]
|
| 77 |
+
},
|
| 78 |
+
{
|
| 79 |
+
"id": "task_002",
|
| 80 |
+
"type": "Task",
|
| 81 |
+
"name": "Restaurant Data Collection",
|
| 82 |
+
"importance": "HIGH",
|
| 83 |
+
"raw_prompt": "Collect comprehensive restaurant data including operating hours, contact information, cuisine types, and availability information for Wednesday evenings.",
|
| 84 |
+
"raw_prompt_ref": [
|
| 85 |
+
{
|
| 86 |
+
"line_start": 25,
|
| 87 |
+
"line_end": 35,
|
| 88 |
+
"confidence": 0.94
|
| 89 |
+
}
|
| 90 |
+
]
|
| 91 |
+
},
|
| 92 |
+
{
|
| 93 |
+
"id": "task_003",
|
| 94 |
+
"type": "Task",
|
| 95 |
+
"name": "Operating Hours Validation",
|
| 96 |
+
"importance": "HIGH",
|
| 97 |
+
"raw_prompt": "Verify restaurant operating hours for Wednesday nights, specifically checking 11pm availability and cross-referencing multiple data sources.",
|
| 98 |
+
"raw_prompt_ref": [
|
| 99 |
+
{
|
| 100 |
+
"line_start": 45,
|
| 101 |
+
"line_end": 55,
|
| 102 |
+
"confidence": 0.91
|
| 103 |
+
}
|
| 104 |
+
]
|
| 105 |
+
},
|
| 106 |
+
{
|
| 107 |
+
"id": "input_001",
|
| 108 |
+
"type": "Input",
|
| 109 |
+
"name": "User Restaurant Query",
|
| 110 |
+
"importance": "HIGH",
|
| 111 |
+
"raw_prompt": "User request for closest eatery to Harkness Memorial State Park open at 11pm on Wednesdays",
|
| 112 |
+
"raw_prompt_ref": [
|
| 113 |
+
{
|
| 114 |
+
"line_start": 1,
|
| 115 |
+
"line_end": 3,
|
| 116 |
+
"confidence": 0.99
|
| 117 |
+
}
|
| 118 |
+
]
|
| 119 |
+
},
|
| 120 |
+
{
|
| 121 |
+
"id": "output_001",
|
| 122 |
+
"type": "Output",
|
| 123 |
+
"name": "Restaurant Recommendations",
|
| 124 |
+
"importance": "HIGH",
|
| 125 |
+
"raw_prompt": "Comprehensive restaurant recommendations with verified operating hours and proximity information",
|
| 126 |
+
"raw_prompt_ref": [
|
| 127 |
+
{
|
| 128 |
+
"line_start": 90,
|
| 129 |
+
"line_end": 95,
|
| 130 |
+
"confidence": 0.93
|
| 131 |
+
}
|
| 132 |
+
]
|
| 133 |
+
},
|
| 134 |
+
{
|
| 135 |
+
"id": "human_001",
|
| 136 |
+
"type": "Human",
|
| 137 |
+
"name": "End User",
|
| 138 |
+
"importance": "HIGH",
|
| 139 |
+
"raw_prompt": "User seeking restaurant recommendations near a specific location with time constraints",
|
| 140 |
+
"raw_prompt_ref": [
|
| 141 |
+
{
|
| 142 |
+
"line_start": 1,
|
| 143 |
+
"line_end": 1,
|
| 144 |
+
"confidence": 0.95
|
| 145 |
+
}
|
| 146 |
+
]
|
| 147 |
+
}
|
| 148 |
+
],
|
| 149 |
+
"relations": [
|
| 150 |
+
{
|
| 151 |
+
"id": "rel_001",
|
| 152 |
+
"source": "input_001",
|
| 153 |
+
"target": "agent_001",
|
| 154 |
+
"type": "CONSUMED_BY",
|
| 155 |
+
"importance": "HIGH",
|
| 156 |
+
"interaction_prompt": "Location-based query consumed by Location-Based Services Expert",
|
| 157 |
+
"interaction_prompt_ref": [
|
| 158 |
+
{
|
| 159 |
+
"line_start": 5,
|
| 160 |
+
"line_end": 8,
|
| 161 |
+
"confidence": 0.95
|
| 162 |
+
}
|
| 163 |
+
]
|
| 164 |
+
},
|
| 165 |
+
{
|
| 166 |
+
"id": "rel_002",
|
| 167 |
+
"source": "agent_001",
|
| 168 |
+
"target": "task_001",
|
| 169 |
+
"type": "PERFORMS",
|
| 170 |
+
"importance": "HIGH",
|
| 171 |
+
"interaction_prompt": "Location-Based Services Expert performs geographic proximity analysis",
|
| 172 |
+
"interaction_prompt_ref": [
|
| 173 |
+
{
|
| 174 |
+
"line_start": 15,
|
| 175 |
+
"line_end": 25,
|
| 176 |
+
"confidence": 0.92
|
| 177 |
+
}
|
| 178 |
+
]
|
| 179 |
+
},
|
| 180 |
+
{
|
| 181 |
+
"id": "rel_003",
|
| 182 |
+
"source": "agent_002",
|
| 183 |
+
"target": "task_002",
|
| 184 |
+
"type": "PERFORMS",
|
| 185 |
+
"importance": "HIGH",
|
| 186 |
+
"interaction_prompt": "Eateries Expert performs restaurant data collection",
|
| 187 |
+
"interaction_prompt_ref": [
|
| 188 |
+
{
|
| 189 |
+
"line_start": 35,
|
| 190 |
+
"line_end": 45,
|
| 191 |
+
"confidence": 0.89
|
| 192 |
+
}
|
| 193 |
+
]
|
| 194 |
+
},
|
| 195 |
+
{
|
| 196 |
+
"id": "rel_004",
|
| 197 |
+
"source": "agent_003",
|
| 198 |
+
"target": "task_003",
|
| 199 |
+
"type": "PERFORMS",
|
| 200 |
+
"importance": "HIGH",
|
| 201 |
+
"interaction_prompt": "Data Verification Expert performs operating hours validation",
|
| 202 |
+
"interaction_prompt_ref": [
|
| 203 |
+
{
|
| 204 |
+
"line_start": 55,
|
| 205 |
+
"line_end": 65,
|
| 206 |
+
"confidence": 0.87
|
| 207 |
+
}
|
| 208 |
+
]
|
| 209 |
+
},
|
| 210 |
+
{
|
| 211 |
+
"id": "rel_005",
|
| 212 |
+
"source": "task_001",
|
| 213 |
+
"target": "task_002",
|
| 214 |
+
"type": "NEXT",
|
| 215 |
+
"importance": "HIGH",
|
| 216 |
+
"interaction_prompt": "Geographic analysis leads to restaurant data collection",
|
| 217 |
+
"interaction_prompt_ref": [
|
| 218 |
+
{
|
| 219 |
+
"line_start": 25,
|
| 220 |
+
"line_end": 30,
|
| 221 |
+
"confidence": 0.88
|
| 222 |
+
}
|
| 223 |
+
]
|
| 224 |
+
},
|
| 225 |
+
{
|
| 226 |
+
"id": "rel_006",
|
| 227 |
+
"source": "task_002",
|
| 228 |
+
"target": "task_003",
|
| 229 |
+
"type": "NEXT",
|
| 230 |
+
"importance": "HIGH",
|
| 231 |
+
"interaction_prompt": "Restaurant data collection followed by operating hours validation",
|
| 232 |
+
"interaction_prompt_ref": [
|
| 233 |
+
{
|
| 234 |
+
"line_start": 45,
|
| 235 |
+
"line_end": 50,
|
| 236 |
+
"confidence": 0.85
|
| 237 |
+
}
|
| 238 |
+
]
|
| 239 |
+
},
|
| 240 |
+
{
|
| 241 |
+
"id": "rel_007",
|
| 242 |
+
"source": "task_003",
|
| 243 |
+
"target": "output_001",
|
| 244 |
+
"type": "PRODUCES",
|
| 245 |
+
"importance": "HIGH",
|
| 246 |
+
"interaction_prompt": "Validation task produces final restaurant recommendations",
|
| 247 |
+
"interaction_prompt_ref": [
|
| 248 |
+
{
|
| 249 |
+
"line_start": 90,
|
| 250 |
+
"line_end": 95,
|
| 251 |
+
"confidence": 0.92
|
| 252 |
+
}
|
| 253 |
+
]
|
| 254 |
+
},
|
| 255 |
+
{
|
| 256 |
+
"id": "rel_008",
|
| 257 |
+
"source": "output_001",
|
| 258 |
+
"target": "human_001",
|
| 259 |
+
"type": "DELIVERS_TO",
|
| 260 |
+
"importance": "HIGH",
|
| 261 |
+
"interaction_prompt": "Restaurant recommendations delivered to end user",
|
| 262 |
+
"interaction_prompt_ref": [
|
| 263 |
+
{
|
| 264 |
+
"line_start": 95,
|
| 265 |
+
"line_end": 100,
|
| 266 |
+
"confidence": 0.93
|
| 267 |
+
}
|
| 268 |
+
]
|
| 269 |
+
},
|
| 270 |
+
{
|
| 271 |
+
"id": "rel_009",
|
| 272 |
+
"source": "agent_004",
|
| 273 |
+
"target": "task_001",
|
| 274 |
+
"type": "REQUIRED_BY",
|
| 275 |
+
"importance": "MEDIUM",
|
| 276 |
+
"interaction_prompt": "Computational task requires Computer Terminal for execution",
|
| 277 |
+
"interaction_prompt_ref": [
|
| 278 |
+
{
|
| 279 |
+
"line_start": 20,
|
| 280 |
+
"line_end": 25,
|
| 281 |
+
"confidence": 0.8
|
| 282 |
+
}
|
| 283 |
+
]
|
| 284 |
+
},
|
| 285 |
+
{
|
| 286 |
+
"id": "rel_uses_computer",
|
| 287 |
+
"source": "agent_001",
|
| 288 |
+
"target": "agent_004",
|
| 289 |
+
"type": "USES",
|
| 290 |
+
"importance": "MEDIUM",
|
| 291 |
+
"interaction_prompt": "Agent uses Computer Terminal for computational tasks",
|
| 292 |
+
"interaction_prompt_ref": [
|
| 293 |
+
{
|
| 294 |
+
"line_start": 50,
|
| 295 |
+
"line_end": 55,
|
| 296 |
+
"confidence": 0.8
|
| 297 |
+
}
|
| 298 |
+
]
|
| 299 |
+
}
|
| 300 |
+
],
|
| 301 |
+
"failures": [
|
| 302 |
+
{
|
| 303 |
+
"id": "failure_001",
|
| 304 |
+
"description": "Data Verification Expert failed to properly validate restaurant operating hours due to incorrect Python code implementation, leading to inaccurate 11pm availability data",
|
| 305 |
+
"raw_text": "",
|
| 306 |
+
"raw_text_ref": [
|
| 307 |
+
{
|
| 308 |
+
"line_start": 60,
|
| 309 |
+
"line_end": 65,
|
| 310 |
+
"confidence": 0.9
|
| 311 |
+
}
|
| 312 |
+
],
|
| 313 |
+
"affected_id": "agent_003",
|
| 314 |
+
"risk_type": "EXECUTION_ERROR"
|
| 315 |
+
},
|
| 316 |
+
{
|
| 317 |
+
"id": "failure_002",
|
| 318 |
+
"description": "Location-Based Services Expert encountered API limitations when accessing real-time restaurant data, resulting in incomplete proximity analysis",
|
| 319 |
+
"raw_text": "",
|
| 320 |
+
"raw_text_ref": [
|
| 321 |
+
{
|
| 322 |
+
"line_start": 18,
|
| 323 |
+
"line_end": 22,
|
| 324 |
+
"confidence": 0.85
|
| 325 |
+
}
|
| 326 |
+
],
|
| 327 |
+
"affected_id": "agent_001",
|
| 328 |
+
"risk_type": "RETRIEVAL_ERROR"
|
| 329 |
+
}
|
| 330 |
+
],
|
| 331 |
+
"optimizations": [
|
| 332 |
+
{
|
| 333 |
+
"id": "opt_001",
|
| 334 |
+
"description": "Enhance location-based services with caching mechanisms and fallback data sources to improve reliability and reduce API dependency",
|
| 335 |
+
"raw_text": "Implement robust location service tools with redundancy",
|
| 336 |
+
"raw_text_ref": [
|
| 337 |
+
{
|
| 338 |
+
"line_start": 15,
|
| 339 |
+
"line_end": 25,
|
| 340 |
+
"confidence": 0.88
|
| 341 |
+
}
|
| 342 |
+
],
|
| 343 |
+
"affected_ids": [
|
| 344 |
+
"agent_001"
|
| 345 |
+
],
|
| 346 |
+
"recommendation_type": "TOOL_ENHANCEMENT"
|
| 347 |
+
},
|
| 348 |
+
{
|
| 349 |
+
"id": "opt_002",
|
| 350 |
+
"description": "Combine restaurant data collection and operating hours validation into a single integrated task to reduce coordination overhead and improve data consistency",
|
| 351 |
+
"raw_text": "Merge data collection and validation workflows",
|
| 352 |
+
"raw_text_ref": [
|
| 353 |
+
{
|
| 354 |
+
"line_start": 35,
|
| 355 |
+
"line_end": 65,
|
| 356 |
+
"confidence": 0.82
|
| 357 |
+
}
|
| 358 |
+
],
|
| 359 |
+
"affected_ids": [
|
| 360 |
+
"agent_002",
|
| 361 |
+
"agent_003",
|
| 362 |
+
"task_002",
|
| 363 |
+
"task_003"
|
| 364 |
+
],
|
| 365 |
+
"recommendation_type": "WORKFLOW_SIMPLIFICATION"
|
| 366 |
+
},
|
| 367 |
+
{
|
| 368 |
+
"id": "opt_003",
|
| 369 |
+
"description": "Refine Data Verification Expert prompts to include specific error handling and validation procedures for time-sensitive restaurant data",
|
| 370 |
+
"raw_text": "Improve validation prompts with error handling",
|
| 371 |
+
"raw_text_ref": [
|
| 372 |
+
{
|
| 373 |
+
"line_start": 55,
|
| 374 |
+
"line_end": 65,
|
| 375 |
+
"confidence": 0.85
|
| 376 |
+
}
|
| 377 |
+
],
|
| 378 |
+
"affected_ids": [
|
| 379 |
+
"agent_003"
|
| 380 |
+
],
|
| 381 |
+
"recommendation_type": "PROMPT_REFINEMENT"
|
| 382 |
+
}
|
| 383 |
+
],
|
| 384 |
+
"metadata": {
|
| 385 |
+
"creation_timestamp": "2025-09-01T20:00:51.719248",
|
| 386 |
+
"window_info": {
|
| 387 |
+
"window_index": 2,
|
| 388 |
+
"window_total": 3,
|
| 389 |
+
"trace_id": "sample_replay_demo_ff9c601e",
|
| 390 |
+
"processing_run_id": "bcbffcc9",
|
| 391 |
+
"window_start_char": 7000,
|
| 392 |
+
"window_end_char": 10500,
|
| 393 |
+
"chunk_size": 3500,
|
| 394 |
+
"splitter_type": "demo_window",
|
| 395 |
+
"entities_count": 10,
|
| 396 |
+
"relations_count": 10
|
| 397 |
+
}
|
| 398 |
+
}
|
| 399 |
+
}
|
| 400 |
+
}
|
backend/database/samples/samples_config.json
CHANGED
|
@@ -169,12 +169,52 @@
|
|
| 169 |
"pipeline_optimization",
|
| 170 |
"conservation_applications"
|
| 171 |
]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 172 |
}
|
| 173 |
],
|
| 174 |
"metadata": {
|
| 175 |
"version": "2.0.0",
|
| 176 |
"created": "2025-01-27",
|
| 177 |
-
"updated": "2025-01
|
| 178 |
"description": "Comprehensive AgentGraph sample data showcasing diverse multi-agent interactions across multiple domains including location services, probability theory, academic research, and ecological data analysis"
|
| 179 |
}
|
| 180 |
-
}
|
|
|
|
| 169 |
"pipeline_optimization",
|
| 170 |
"conservation_applications"
|
| 171 |
]
|
| 172 |
+
},
|
| 173 |
+
{
|
| 174 |
+
"id": "window_replay_demo",
|
| 175 |
+
"name": "Location-Based Restaurant Discovery (Window Replay Demo)",
|
| 176 |
+
"description": "Temporal replay demonstration showing progressive knowledge graph evolution through 3 windows. Multi-agent restaurant discovery system with location analysis, data collection, and validation stages.",
|
| 177 |
+
"trace_file": "traces/replay_demo_trace.json",
|
| 178 |
+
"knowledge_graph_file": "knowledge_graphs/kg_algorithm_sample_1_final.json",
|
| 179 |
+
"window_kgs": [
|
| 180 |
+
"knowledge_graphs/kg_algorithm_sample_1_window_0.json",
|
| 181 |
+
"knowledge_graphs/kg_algorithm_sample_1_window_1.json",
|
| 182 |
+
"knowledge_graphs/kg_algorithm_sample_1_window_2.json"
|
| 183 |
+
],
|
| 184 |
+
"tags": [
|
| 185 |
+
"replay_demo",
|
| 186 |
+
"temporal_visualization",
|
| 187 |
+
"multi_agent",
|
| 188 |
+
"restaurant_discovery",
|
| 189 |
+
"progressive_evolution",
|
| 190 |
+
"window_graphs"
|
| 191 |
+
],
|
| 192 |
+
"complexity": "advanced",
|
| 193 |
+
"trace_type": "multi_agent_collaboration_windowed",
|
| 194 |
+
"trace_source": "sample_data_replay",
|
| 195 |
+
"features": [
|
| 196 |
+
"temporal_replay",
|
| 197 |
+
"window_progression",
|
| 198 |
+
"multi_agent_collaboration",
|
| 199 |
+
"progressive_discovery",
|
| 200 |
+
"knowledge_evolution",
|
| 201 |
+
"interactive_visualization"
|
| 202 |
+
],
|
| 203 |
+
"replay_info": {
|
| 204 |
+
"window_count": 3,
|
| 205 |
+
"supports_replay": true,
|
| 206 |
+
"progression_stages": [
|
| 207 |
+
"Initial Query & Location Analysis",
|
| 208 |
+
"Data Collection & Verification",
|
| 209 |
+
"Result Generation & Delivery"
|
| 210 |
+
]
|
| 211 |
+
}
|
| 212 |
}
|
| 213 |
],
|
| 214 |
"metadata": {
|
| 215 |
"version": "2.0.0",
|
| 216 |
"created": "2025-01-27",
|
| 217 |
+
"updated": "2025-09-01",
|
| 218 |
"description": "Comprehensive AgentGraph sample data showcasing diverse multi-agent interactions across multiple domains including location services, probability theory, academic research, and ecological data analysis"
|
| 219 |
}
|
| 220 |
+
}
|