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Update sample_data.py

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  1. sample_data.py +436 -224
sample_data.py CHANGED
@@ -1,86 +1,181 @@
 
 
 
1
  CONCEPT_MAP_JSON = """
2
  {
3
- "central_node": "Artificial Intelligence (AI)",
4
  "nodes": [
5
  {
6
- "id": "ml_fundamental",
7
- "label": "Machine Learning",
8
- "relationship": "is essential for",
9
  "subnodes": [
10
  {
11
- "id": "dl_branch",
12
- "label": "Deep Learning",
13
- "relationship": "for example",
14
  "subnodes": [
15
  {
16
- "id": "cnn_example",
17
- "label": "CNNs",
18
- "relationship": "for example"
 
 
 
 
 
 
 
 
 
 
 
 
19
  },
20
  {
21
- "id": "rnn_example",
22
- "label": "RNNs",
23
- "relationship": "for example"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
24
  }
25
  ]
26
  },
27
  {
28
- "id": "rl_branch",
29
- "label": "Reinforcement Learning",
30
- "relationship": "for example",
31
  "subnodes": [
32
  {
33
- "id": "qlearning_example",
34
- "label": "Q-Learning",
35
- "relationship": "example"
 
 
 
 
 
 
 
 
 
 
 
 
36
  },
37
  {
38
- "id": "pg_example",
39
- "label": "Policy Gradients",
40
- "relationship": "example"
 
 
 
 
 
 
 
 
 
 
 
 
41
  }
42
  ]
43
  }
44
  ]
45
  },
46
  {
47
- "id": "ai_types",
48
- "label": "Types",
49
- "relationship": "formed by",
50
  "subnodes": [
51
  {
52
- "id": "agi_type",
53
- "label": "AGI",
54
- "relationship": "this is",
55
  "subnodes": [
56
  {
57
- "id": "strong_ai",
58
- "label": "Strong AI",
59
- "relationship": "provoked by",
60
  "subnodes": [
61
  {
62
- "id": "human_intel",
63
- "label": "Human-level Intel.",
64
- "relationship": "of"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
65
  }
66
  ]
67
  }
68
  ]
69
  },
70
  {
71
- "id": "ani_type",
72
- "label": "ANI",
73
- "relationship": "this is",
74
  "subnodes": [
75
  {
76
- "id": "weak_ai",
77
- "label": "Weak AI",
78
- "relationship": "provoked by",
79
  "subnodes": [
80
  {
81
- "id": "narrow_tasks",
82
- "label": "Narrow Tasks",
83
- "relationship": "of"
 
 
 
 
 
84
  }
85
  ]
86
  }
@@ -89,71 +184,53 @@ CONCEPT_MAP_JSON = """
89
  ]
90
  },
91
  {
92
- "id": "ai_capabilities",
93
- "label": "Capabilities",
94
- "relationship": "change",
95
  "subnodes": [
96
  {
97
- "id": "data_proc",
98
- "label": "Data Processing",
99
- "relationship": "can",
100
  "subnodes": [
101
  {
102
- "id": "big_data",
103
- "label": "Big Data",
104
- "relationship": "as",
105
  "subnodes": [
106
  {
107
- "id": "analysis_example",
108
- "label": "Data Analysis",
109
- "relationship": "example"
110
  },
111
  {
112
- "id": "prediction_example",
113
- "label": "Prediction",
114
- "relationship": "example"
115
  }
116
  ]
117
  }
118
  ]
119
  },
120
  {
121
- "id": "decision_making",
122
- "label": "Decision Making",
123
- "relationship": "can be",
124
  "subnodes": [
125
  {
126
- "id": "automation",
127
- "label": "Automation",
128
- "relationship": "as",
129
  "subnodes": [
130
  {
131
- "id": "robotics_example",
132
- "label": "Robotics",
133
- "relationship": "Example"},
134
- {
135
- "id": "autonomous_example",
136
- "label": "Autonomous Vehicles",
137
- "relationship": "of one"
138
- }
139
- ]
140
- }
141
- ]
142
- },
143
- {
144
- "id": "problem_solving",
145
- "label": "Problem Solving",
146
- "relationship": "can",
147
- "subnodes": [
148
- {
149
- "id": "optimization",
150
- "label": "Optimization",
151
- "relationship": "as is",
152
- "subnodes": [
153
  {
154
- "id": "algorithms_example",
155
- "label": "Algorithms",
156
- "relationship": "for example"
157
  }
158
  ]
159
  }
@@ -165,82 +242,81 @@ CONCEPT_MAP_JSON = """
165
  }
166
  """
167
 
168
- # JSON for Synoptic Chart (horizontal hierarchy) - AI related, 4 levels
169
  SYNOPTIC_CHART_JSON = """
170
  {
171
- "central_node": "AI Project Lifecycle",
172
  "nodes": [
173
  {
174
  "id": "phase1",
175
- "label": "I. Problem Definition & Data Acquisition",
176
- "relationship": "Starts with",
177
  "subnodes": [
178
  {
179
- "id": "sub1_1",
180
- "label": "1. Problem Formulation",
181
- "relationship": "Involves",
182
  "subnodes": [
183
- {"id": "sub1_1_1", "label": "1.1. Identify Business Need", "relationship": "e.g."},
184
- {"id": "sub1_1_2", "label": "1.2. Define KPIs", "relationship": "e.g."}
185
  ]
186
  },
187
  {
188
- "id": "sub1_2",
189
- "label": "2. Data Collection",
190
- "relationship": "Followed by",
191
  "subnodes": [
192
- {"id": "sub1_2_1", "label": "2.1. Source Data", "relationship": "from"},
193
- {"id": "sub1_2_2", "label": "2.2. Data Cleaning", "relationship": "includes"}
194
  ]
195
  }
196
  ]
197
  },
198
  {
199
  "id": "phase2",
200
- "label": "II. Model Development",
201
- "relationship": "Proceeds to",
202
  "subnodes": [
203
  {
204
- "id": "sub2_1",
205
- "label": "1. Feature Engineering",
206
- "relationship": "Comprises",
207
  "subnodes": [
208
- {"id": "sub2_1_1", "label": "1.1. Feature Selection", "relationship": "e.g."},
209
- {"id": "sub2_1_2", "label": "1.2. Feature Transformation", "relationship": "e.g."}
210
  ]
211
  },
212
  {
213
- "id": "sub2_2",
214
- "label": "2. Model Training",
215
- "relationship": "Involves",
216
  "subnodes": [
217
- {"id": "sub2_2_1", "label": "2.1. Algorithm Selection", "relationship": "uses"},
218
- {"id": "sub2_2_2", "label": "2.2. Hyperparameter Tuning", "relationship": "optimizes"}
219
  ]
220
  }
221
  ]
222
  },
223
  {
224
  "id": "phase3",
225
- "label": "III. Evaluation & Deployment",
226
- "relationship": "Culminates in",
227
  "subnodes": [
228
  {
229
- "id": "sub3_1",
230
- "label": "1. Model Evaluation",
231
- "relationship": "Includes",
232
  "subnodes": [
233
- {"id": "sub3_1_1", "label": "1.1. Performance Metrics", "relationship": "measures"},
234
- {"id": "sub3_1_2", "label": "1.2. Bias & Fairness Audits", "relationship": "ensures"}
235
  ]
236
  },
237
  {
238
- "id": "sub3_2",
239
- "label": "2. Deployment & Monitoring",
240
- "relationship": "Requires",
241
  "subnodes": [
242
- {"id": "sub3_2_1", "label": "2.1. API/Integration Development", "relationship": "for"},
243
- {"id": "sub3_2_2", "label": "2.2. Continuous Monitoring", "relationship": "ensures"}
244
  ]
245
  }
246
  ]
@@ -249,54 +325,53 @@ SYNOPTIC_CHART_JSON = """
249
  }
250
  """
251
 
252
- # JSON for Radial Diagram (central expansion) - AI related, 3 levels with 5->10 structure
253
  RADIAL_DIAGRAM_JSON = """
254
  {
255
- "central_node": "AI Core Concepts & Domains",
256
  "nodes": [
257
  {
258
- "id": "foundational_ml",
259
- "label": "Foundational ML",
260
- "relationship": "builds on",
261
  "subnodes": [
262
- {"id": "supervised_l", "label": "Supervised Learning", "relationship": "e.g."},
263
- {"id": "unsupervised_l", "label": "Unsupervised Learning", "relationship": "e.g."}
264
  ]
265
  },
266
  {
267
- "id": "dl_architectures",
268
- "label": "Deep Learning Arch.",
269
- "relationship": "evolved from",
270
  "subnodes": [
271
- {"id": "cnns_rad", "label": "CNNs", "relationship": "e.g."},
272
- {"id": "rnns_rad", "label": "RNNs", "relationship": "e.g."}
273
  ]
274
  },
275
  {
276
- "id": "major_applications",
277
- "label": "Major AI Applications",
278
- "relationship": "applied in",
279
  "subnodes": [
280
- {"id": "nlp_rad", "label": "Natural Language Processing", "relationship": "e.g."},
281
- {"id": "cv_rad", "label": "Computer Vision", "relationship": "e.g."}
282
  ]
283
  },
284
  {
285
- "id": "ethical_concerns",
286
- "label": "Ethical AI Concerns",
287
- "relationship": "addresses",
288
  "subnodes": [
289
- {"id": "fairness_rad", "label": "Fairness & Bias", "relationship": "e.g."},
290
- {"id": "explainability", "label": "Explainability (XAI)", "relationship": "e.g."}
291
  ]
292
  },
293
  {
294
- "id": "future_trends",
295
- "label": "Future AI Trends",
296
- "relationship": "looking at",
297
  "subnodes": [
298
- {"id": "agi_future", "label": "AGI Development", "relationship": "e.g."},
299
- {"id": "quantum_ai", "label": "Quantum AI", "relationship": "e.g."}
300
  ]
301
  }
302
  ]
@@ -305,101 +380,176 @@ RADIAL_DIAGRAM_JSON = """
305
 
306
  PROCESS_FLOW_JSON = """
307
  {
308
- "start_node": "Start Inference Request",
309
  "nodes": [
310
  {
311
- "id": "user_input",
312
- "label": "Receive User Input (Data)",
313
- "type": "io"
314
  },
315
  {
316
- "id": "preprocess_data",
317
- "label": "Preprocess Data",
 
 
 
 
 
318
  "type": "process"
319
  },
320
  {
321
- "id": "validate_data",
322
- "label": "Validate Data Format/Type",
323
  "type": "decision"
324
  },
325
  {
326
- "id": "data_valid_yes",
327
- "label": "Data Valid?",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
328
  "type": "decision"
329
  },
330
  {
331
- "id": "load_model",
332
- "label": "Load AI Model (if not cached)",
333
  "type": "process"
334
  },
335
  {
336
- "id": "run_inference",
337
- "label": "Run AI Model Inference",
338
  "type": "process"
339
  },
340
  {
341
- "id": "postprocess_output",
342
- "label": "Postprocess Model Output",
343
  "type": "process"
344
  },
345
  {
346
- "id": "send_response",
347
- "label": "Send Response to User",
348
  "type": "io"
349
  },
350
  {
351
- "id": "log_error",
352
- "label": "Log Error & Notify User",
353
  "type": "process"
354
  },
355
  {
356
- "id": "end_inference_process",
357
- "label": "End Inference Process",
 
 
 
 
 
358
  "type": "end"
359
  }
360
  ],
361
  "connections": [
362
- {"from": "start_node", "to": "user_input", "label": "Request"},
363
- {"from": "user_input", "to": "preprocess_data", "label": "Data Received"},
364
- {"from": "preprocess_data", "to": "validate_data", "label": "Cleaned"},
365
- {"from": "validate_data", "to": "data_valid_yes", "label": "Check"},
366
- {"from": "data_valid_yes", "to": "load_model", "label": "Yes"},
367
- {"from": "data_valid_yes", "to": "log_error", "label": "No"},
368
- {"from": "load_model", "to": "run_inference", "label": "Model Ready"},
369
- {"from": "run_inference", "to": "postprocess_output", "label": "Output Generated"},
370
- {"from": "postprocess_output", "to": "send_response", "label": "Ready"},
371
- {"from": "send_response", "to": "end_inference_process", "label": "Response Sent"},
372
- {"from": "log_error", "to": "end_inference_process", "label": "Error Handled"}
 
 
 
 
 
 
 
373
  ]
374
  }
375
  """
376
 
377
- # New JSON for Work Breakdown Structure (WBS) Diagram - similar to image, but not identical
378
  WBS_DIAGRAM_JSON = """
379
  {
380
- "project_title": "AI Model Development Project",
381
  "phases": [
382
  {
383
- "id": "phase_prep",
384
- "label": "Preparation",
385
  "tasks": [
386
  {
387
- "id": "task_1_1_vision",
388
- "label": "Identify Vision",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
389
  "subtasks": [
390
  {
391
- "id": "subtask_1_1_1_design_staff",
392
- "label": "Design & Staffing",
393
  "sub_subtasks": [
394
  {
395
- "id": "ss_task_1_1_1_1_env_setup",
396
- "label": "Environment Setup",
397
  "sub_sub_subtasks": [
398
  {
399
- "id": "sss_task_1_1_1_1_1_lib_install",
400
- "label": "Install Libraries",
401
  "final_level_tasks": [
402
- {"id": "ft_1_1_1_1_1_1_data_access", "label": "Grant Data Access"}
403
  ]
404
  }
405
  ]
@@ -411,26 +561,70 @@ WBS_DIAGRAM_JSON = """
411
  ]
412
  },
413
  {
414
- "id": "phase_plan",
415
- "label": "Planning",
416
  "tasks": [
417
  {
418
- "id": "task_2_1_cost_analysis",
419
- "label": "Cost Analysis",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
420
  "subtasks": [
421
  {
422
- "id": "subtask_2_1_1_benefit_analysis",
423
- "label": "Benefit Analysis",
424
  "sub_subtasks": [
425
  {
426
- "id": "ss_task_2_1_1_1_risk_assess",
427
- "label": "AI Risk Assessment",
428
  "sub_sub_subtasks": [
429
  {
430
- "id": "sss_task_2_1_1_1_1_model_selection",
431
- "label": "Model Selection",
432
  "final_level_tasks": [
433
- {"id": "ft_2_1_1_1_1_1_data_strategy", "label": "Data Strategy"}
434
  ]
435
  }
436
  ]
@@ -442,26 +636,45 @@ WBS_DIAGRAM_JSON = """
442
  ]
443
  },
444
  {
445
- "id": "phase_dev",
446
- "label": "Development",
447
  "tasks": [
448
  {
449
- "id": "task_3_1_change_mgmt",
450
- "label": "Data Preprocessing",
451
  "subtasks": [
452
  {
453
- "id": "subtask_3_1_1_implementation",
454
- "label": "Feature Engineering",
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
455
  "sub_subtasks": [
456
  {
457
- "id": "ss_task_3_1_1_1_beta_testing",
458
- "label": "Model Training",
459
  "sub_sub_subtasks": [
460
  {
461
- "id": "sss_task_3_1_1_1_1_other_task",
462
- "label": "Model Evaluation",
463
  "final_level_tasks": [
464
- {"id": "ft_3_1_1_1_1_1_hyperparam_tune", "label": "Hyperparameter Tuning"}
465
  ]
466
  }
467
  ]
@@ -474,5 +687,4 @@ WBS_DIAGRAM_JSON = """
474
  }
475
  ]
476
  }
477
-
478
- """
 
1
+ # Enhanced Sample Data for AI Diagram Generator
2
+ # Modern and practical AI-related sample data
3
+
4
  CONCEPT_MAP_JSON = """
5
  {
6
+ "central_node": "Generative AI Ecosystem",
7
  "nodes": [
8
  {
9
+ "id": "foundation_models",
10
+ "label": "Foundation Models",
11
+ "relationship": "powered by",
12
  "subnodes": [
13
  {
14
+ "id": "llm_models",
15
+ "label": "Large Language Models",
16
+ "relationship": "includes",
17
  "subnodes": [
18
  {
19
+ "id": "gpt_family",
20
+ "label": "GPT Family",
21
+ "relationship": "such as",
22
+ "subnodes": [
23
+ {
24
+ "id": "gpt4",
25
+ "label": "GPT-4",
26
+ "relationship": "latest version"
27
+ },
28
+ {
29
+ "id": "chatgpt",
30
+ "label": "ChatGPT",
31
+ "relationship": "application"
32
+ }
33
+ ]
34
  },
35
  {
36
+ "id": "claude_family",
37
+ "label": "Claude Family",
38
+ "relationship": "such as",
39
+ "subnodes": [
40
+ {
41
+ "id": "claude3",
42
+ "label": "Claude 3 Opus",
43
+ "relationship": "advanced model"
44
+ },
45
+ {
46
+ "id": "claude_sonnet",
47
+ "label": "Claude Sonnet",
48
+ "relationship": "balanced model"
49
+ }
50
+ ]
51
+ },
52
+ {
53
+ "id": "opensource_llm",
54
+ "label": "Open Source LLMs",
55
+ "relationship": "alternatives",
56
+ "subnodes": [
57
+ {
58
+ "id": "llama3",
59
+ "label": "LLaMA 3",
60
+ "relationship": "by Meta"
61
+ },
62
+ {
63
+ "id": "mistral",
64
+ "label": "Mistral 7B",
65
+ "relationship": "efficient"
66
+ }
67
+ ]
68
  }
69
  ]
70
  },
71
  {
72
+ "id": "multimodal_models",
73
+ "label": "Multimodal Models",
74
+ "relationship": "extends to",
75
  "subnodes": [
76
  {
77
+ "id": "vision_language",
78
+ "label": "Vision-Language Models",
79
+ "relationship": "including",
80
+ "subnodes": [
81
+ {
82
+ "id": "dall_e3",
83
+ "label": "DALL-E 3",
84
+ "relationship": "image generation"
85
+ },
86
+ {
87
+ "id": "midjourney",
88
+ "label": "Midjourney v6",
89
+ "relationship": "artistic creation"
90
+ }
91
+ ]
92
  },
93
  {
94
+ "id": "video_models",
95
+ "label": "Video Generation",
96
+ "relationship": "emerging with",
97
+ "subnodes": [
98
+ {
99
+ "id": "sora",
100
+ "label": "Sora",
101
+ "relationship": "by OpenAI"
102
+ },
103
+ {
104
+ "id": "runway",
105
+ "label": "Runway Gen-2",
106
+ "relationship": "creative tools"
107
+ }
108
+ ]
109
  }
110
  ]
111
  }
112
  ]
113
  },
114
  {
115
+ "id": "ai_applications",
116
+ "label": "Real-World Applications",
117
+ "relationship": "deployed in",
118
  "subnodes": [
119
  {
120
+ "id": "enterprise_ai",
121
+ "label": "Enterprise Solutions",
122
+ "relationship": "transforming",
123
  "subnodes": [
124
  {
125
+ "id": "ai_assistants",
126
+ "label": "AI Assistants",
127
+ "relationship": "like",
128
  "subnodes": [
129
  {
130
+ "id": "copilot",
131
+ "label": "GitHub Copilot",
132
+ "relationship": "code generation"
133
+ },
134
+ {
135
+ "id": "duet_ai",
136
+ "label": "Google Duet AI",
137
+ "relationship": "workspace integration"
138
+ }
139
+ ]
140
+ },
141
+ {
142
+ "id": "automation",
143
+ "label": "Process Automation",
144
+ "relationship": "through",
145
+ "subnodes": [
146
+ {
147
+ "id": "rpa_ai",
148
+ "label": "AI-Enhanced RPA",
149
+ "relationship": "intelligent automation"
150
+ },
151
+ {
152
+ "id": "document_ai",
153
+ "label": "Document Intelligence",
154
+ "relationship": "data extraction"
155
  }
156
  ]
157
  }
158
  ]
159
  },
160
  {
161
+ "id": "creative_ai",
162
+ "label": "Creative Industries",
163
+ "relationship": "revolutionizing",
164
  "subnodes": [
165
  {
166
+ "id": "content_creation",
167
+ "label": "Content Generation",
168
+ "relationship": "enabling",
169
  "subnodes": [
170
  {
171
+ "id": "marketing_ai",
172
+ "label": "Marketing Copy",
173
+ "relationship": "automated creation"
174
+ },
175
+ {
176
+ "id": "game_assets",
177
+ "label": "Game Asset Generation",
178
+ "relationship": "procedural design"
179
  }
180
  ]
181
  }
 
184
  ]
185
  },
186
  {
187
+ "id": "ai_infrastructure",
188
+ "label": "AI Infrastructure",
189
+ "relationship": "supported by",
190
  "subnodes": [
191
  {
192
+ "id": "compute_resources",
193
+ "label": "Compute Resources",
194
+ "relationship": "requiring",
195
  "subnodes": [
196
  {
197
+ "id": "gpu_clusters",
198
+ "label": "GPU Clusters",
199
+ "relationship": "powered by",
200
  "subnodes": [
201
  {
202
+ "id": "nvidia_h100",
203
+ "label": "NVIDIA H100",
204
+ "relationship": "latest generation"
205
  },
206
  {
207
+ "id": "tpu_v5",
208
+ "label": "Google TPU v5",
209
+ "relationship": "specialized chips"
210
  }
211
  ]
212
  }
213
  ]
214
  },
215
  {
216
+ "id": "mlops_platform",
217
+ "label": "MLOps Platforms",
218
+ "relationship": "managed by",
219
  "subnodes": [
220
  {
221
+ "id": "model_serving",
222
+ "label": "Model Serving",
223
+ "relationship": "via",
224
  "subnodes": [
225
  {
226
+ "id": "huggingface",
227
+ "label": "Hugging Face",
228
+ "relationship": "model hub"
229
+ },
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
230
  {
231
+ "id": "vertex_ai",
232
+ "label": "Vertex AI",
233
+ "relationship": "Google Cloud"
234
  }
235
  ]
236
  }
 
242
  }
243
  """
244
 
 
245
  SYNOPTIC_CHART_JSON = """
246
  {
247
+ "central_node": "Modern AI Development Pipeline",
248
  "nodes": [
249
  {
250
  "id": "phase1",
251
+ "label": "I. Data Engineering & Preparation",
252
+ "relationship": "begins with",
253
  "subnodes": [
254
  {
255
+ "id": "data_strategy",
256
+ "label": "1. Data Strategy",
257
+ "relationship": "establishing",
258
  "subnodes": [
259
+ {"id": "data_sources", "label": "1.1. Multi-Source Integration", "relationship": "includes", "subnodes": []},
260
+ {"id": "data_governance", "label": "1.2. Privacy & Compliance", "relationship": "ensures", "subnodes": []}
261
  ]
262
  },
263
  {
264
+ "id": "data_pipeline",
265
+ "label": "2. Data Pipeline",
266
+ "relationship": "building",
267
  "subnodes": [
268
+ {"id": "etl_process", "label": "2.1. ETL/ELT Workflows", "relationship": "implements", "subnodes": []},
269
+ {"id": "feature_store", "label": "2.2. Feature Store Setup", "relationship": "centralizes", "subnodes": []}
270
  ]
271
  }
272
  ]
273
  },
274
  {
275
  "id": "phase2",
276
+ "label": "II. Model Development & Training",
277
+ "relationship": "continues to",
278
  "subnodes": [
279
  {
280
+ "id": "experimentation",
281
+ "label": "1. Experimentation Platform",
282
+ "relationship": "enabling",
283
  "subnodes": [
284
+ {"id": "experiment_tracking", "label": "1.1. MLflow/W&B Integration", "relationship": "tracks", "subnodes": []},
285
+ {"id": "hyperparameter_opt", "label": "1.2. AutoML & HPO", "relationship": "optimizes", "subnodes": []}
286
  ]
287
  },
288
  {
289
+ "id": "distributed_training",
290
+ "label": "2. Scalable Training",
291
+ "relationship": "leveraging",
292
  "subnodes": [
293
+ {"id": "multi_gpu", "label": "2.1. Multi-GPU Training", "relationship": "accelerates", "subnodes": []},
294
+ {"id": "model_parallelism", "label": "2.2. Model Parallelism", "relationship": "enables", "subnodes": []}
295
  ]
296
  }
297
  ]
298
  },
299
  {
300
  "id": "phase3",
301
+ "label": "III. Deployment & Operations",
302
+ "relationship": "culminates in",
303
  "subnodes": [
304
  {
305
+ "id": "model_deployment",
306
+ "label": "1. Production Deployment",
307
+ "relationship": "implementing",
308
  "subnodes": [
309
+ {"id": "edge_deployment", "label": "1.1. Edge Computing", "relationship": "optimizes", "subnodes": []},
310
+ {"id": "api_gateway", "label": "1.2. API Management", "relationship": "exposes", "subnodes": []}
311
  ]
312
  },
313
  {
314
+ "id": "monitoring_ops",
315
+ "label": "2. AI Operations",
316
+ "relationship": "maintaining",
317
  "subnodes": [
318
+ {"id": "model_monitoring", "label": "2.1. Drift Detection", "relationship": "monitors", "subnodes": []},
319
+ {"id": "feedback_loop", "label": "2.2. Continuous Learning", "relationship": "improves", "subnodes": []}
320
  ]
321
  }
322
  ]
 
325
  }
326
  """
327
 
 
328
  RADIAL_DIAGRAM_JSON = """
329
  {
330
+ "central_node": "AI Innovation Hub",
331
  "nodes": [
332
  {
333
+ "id": "emerging_tech",
334
+ "label": "Emerging Technologies",
335
+ "relationship": "advancing through",
336
  "subnodes": [
337
+ {"id": "quantum_ml", "label": "Quantum Machine Learning", "relationship": "breakthrough in", "subnodes": []},
338
+ {"id": "neuromorphic", "label": "Neuromorphic Computing", "relationship": "inspired by", "subnodes": []}
339
  ]
340
  },
341
  {
342
+ "id": "ai_safety",
343
+ "label": "AI Safety & Ethics",
344
+ "relationship": "ensuring through",
345
  "subnodes": [
346
+ {"id": "alignment", "label": "AI Alignment Research", "relationship": "focusing on", "subnodes": []},
347
+ {"id": "explainable_ai", "label": "Explainable AI (XAI)", "relationship": "providing", "subnodes": []}
348
  ]
349
  },
350
  {
351
+ "id": "industry_impact",
352
+ "label": "Industry Transformation",
353
+ "relationship": "disrupting",
354
  "subnodes": [
355
+ {"id": "healthcare_ai", "label": "AI in Healthcare", "relationship": "revolutionizing", "subnodes": []},
356
+ {"id": "fintech_ai", "label": "AI in Finance", "relationship": "automating", "subnodes": []}
357
  ]
358
  },
359
  {
360
+ "id": "research_frontiers",
361
+ "label": "Research Frontiers",
362
+ "relationship": "exploring",
363
  "subnodes": [
364
+ {"id": "agi_research", "label": "AGI Development", "relationship": "pursuing", "subnodes": []},
365
+ {"id": "consciousness_ai", "label": "Machine Consciousness", "relationship": "investigating", "subnodes": []}
366
  ]
367
  },
368
  {
369
+ "id": "ai_ecosystem",
370
+ "label": "AI Ecosystem",
371
+ "relationship": "building",
372
  "subnodes": [
373
+ {"id": "open_source", "label": "Open Source Community", "relationship": "contributing to", "subnodes": []},
374
+ {"id": "ai_startups", "label": "AI Startup Ecosystem", "relationship": "innovating in", "subnodes": []}
375
  ]
376
  }
377
  ]
 
380
 
381
  PROCESS_FLOW_JSON = """
382
  {
383
+ "start_node": "AI Request Initiated",
384
  "nodes": [
385
  {
386
+ "id": "auth_check",
387
+ "label": "Authentication & Rate Limiting",
388
+ "type": "process"
389
  },
390
  {
391
+ "id": "auth_valid",
392
+ "label": "Valid Request?",
393
+ "type": "decision"
394
+ },
395
+ {
396
+ "id": "request_router",
397
+ "label": "Request Router",
398
  "type": "process"
399
  },
400
  {
401
+ "id": "cache_check",
402
+ "label": "Check Response Cache",
403
  "type": "decision"
404
  },
405
  {
406
+ "id": "model_selector",
407
+ "label": "Model Selection Logic",
408
+ "type": "process"
409
+ },
410
+ {
411
+ "id": "load_balancer",
412
+ "label": "Load Balancer",
413
+ "type": "process"
414
+ },
415
+ {
416
+ "id": "inference_engine",
417
+ "label": "Run Inference",
418
+ "type": "process"
419
+ },
420
+ {
421
+ "id": "quality_check",
422
+ "label": "Quality Assessment",
423
  "type": "decision"
424
  },
425
  {
426
+ "id": "post_processor",
427
+ "label": "Post-Processing & Filtering",
428
  "type": "process"
429
  },
430
  {
431
+ "id": "response_cache",
432
+ "label": "Update Cache",
433
  "type": "process"
434
  },
435
  {
436
+ "id": "analytics_log",
437
+ "label": "Log Analytics",
438
  "type": "process"
439
  },
440
  {
441
+ "id": "deliver_response",
442
+ "label": "Deliver Response",
443
  "type": "io"
444
  },
445
  {
446
+ "id": "error_handler",
447
+ "label": "Error Handler",
448
  "type": "process"
449
  },
450
  {
451
+ "id": "fallback_model",
452
+ "label": "Fallback Model",
453
+ "type": "process"
454
+ },
455
+ {
456
+ "id": "end_process",
457
+ "label": "Complete",
458
  "type": "end"
459
  }
460
  ],
461
  "connections": [
462
+ {"from": "start_node", "to": "auth_check", "label": "Begin"},
463
+ {"from": "auth_check", "to": "auth_valid", "label": "Verify"},
464
+ {"from": "auth_valid", "to": "request_router", "label": "Authorized"},
465
+ {"from": "auth_valid", "to": "error_handler", "label": "Denied"},
466
+ {"from": "request_router", "to": "cache_check", "label": "Route"},
467
+ {"from": "cache_check", "to": "deliver_response", "label": "Cache Hit"},
468
+ {"from": "cache_check", "to": "model_selector", "label": "Cache Miss"},
469
+ {"from": "model_selector", "to": "load_balancer", "label": "Selected"},
470
+ {"from": "load_balancer", "to": "inference_engine", "label": "Assigned"},
471
+ {"from": "inference_engine", "to": "quality_check", "label": "Generated"},
472
+ {"from": "quality_check", "to": "post_processor", "label": "Pass"},
473
+ {"from": "quality_check", "to": "fallback_model", "label": "Fail"},
474
+ {"from": "fallback_model", "to": "post_processor", "label": "Retry"},
475
+ {"from": "post_processor", "to": "response_cache", "label": "Processed"},
476
+ {"from": "response_cache", "to": "analytics_log", "label": "Cached"},
477
+ {"from": "analytics_log", "to": "deliver_response", "label": "Logged"},
478
+ {"from": "deliver_response", "to": "end_process", "label": "Delivered"},
479
+ {"from": "error_handler", "to": "end_process", "label": "Handled"}
480
  ]
481
  }
482
  """
483
 
 
484
  WBS_DIAGRAM_JSON = """
485
  {
486
+ "project_title": "Enterprise AI Platform Implementation",
487
  "phases": [
488
  {
489
+ "id": "phase_foundation",
490
+ "label": "Foundation & Architecture",
491
  "tasks": [
492
  {
493
+ "id": "task_requirements",
494
+ "label": "Requirements Analysis",
495
+ "subtasks": [
496
+ {
497
+ "id": "subtask_stakeholder",
498
+ "label": "Stakeholder Mapping",
499
+ "sub_subtasks": [
500
+ {
501
+ "id": "ss_task_interviews",
502
+ "label": "Executive Interviews",
503
+ "sub_sub_subtasks": [
504
+ {
505
+ "id": "sss_task_schedule",
506
+ "label": "Schedule Sessions",
507
+ "final_level_tasks": [
508
+ {"id": "ft_prep_materials", "label": "Prepare Materials"}
509
+ ]
510
+ }
511
+ ]
512
+ }
513
+ ]
514
+ },
515
+ {
516
+ "id": "subtask_technical",
517
+ "label": "Technical Assessment",
518
+ "sub_subtasks": [
519
+ {
520
+ "id": "ss_task_infra",
521
+ "label": "Infrastructure Audit",
522
+ "sub_sub_subtasks": [
523
+ {
524
+ "id": "sss_task_compute",
525
+ "label": "Compute Resources",
526
+ "final_level_tasks": [
527
+ {"id": "ft_gpu_assessment", "label": "GPU Capacity Planning"}
528
+ ]
529
+ }
530
+ ]
531
+ }
532
+ ]
533
+ }
534
+ ]
535
+ },
536
+ {
537
+ "id": "task_architecture",
538
+ "label": "Solution Architecture",
539
  "subtasks": [
540
  {
541
+ "id": "subtask_design",
542
+ "label": "System Design",
543
  "sub_subtasks": [
544
  {
545
+ "id": "ss_task_microservices",
546
+ "label": "Microservices Architecture",
547
  "sub_sub_subtasks": [
548
  {
549
+ "id": "sss_task_api_design",
550
+ "label": "API Design",
551
  "final_level_tasks": [
552
+ {"id": "ft_api_specs", "label": "OpenAPI Specifications"}
553
  ]
554
  }
555
  ]
 
561
  ]
562
  },
563
  {
564
+ "id": "phase_implementation",
565
+ "label": "Core Implementation",
566
  "tasks": [
567
  {
568
+ "id": "task_data_platform",
569
+ "label": "Data Platform",
570
+ "subtasks": [
571
+ {
572
+ "id": "subtask_data_lake",
573
+ "label": "Data Lake Setup",
574
+ "sub_subtasks": [
575
+ {
576
+ "id": "ss_task_storage",
577
+ "label": "Storage Configuration",
578
+ "sub_sub_subtasks": [
579
+ {
580
+ "id": "sss_task_s3_setup",
581
+ "label": "S3 Bucket Setup",
582
+ "final_level_tasks": [
583
+ {"id": "ft_lifecycle_policies", "label": "Lifecycle Policies"}
584
+ ]
585
+ }
586
+ ]
587
+ }
588
+ ]
589
+ },
590
+ {
591
+ "id": "subtask_streaming",
592
+ "label": "Real-time Pipeline",
593
+ "sub_subtasks": [
594
+ {
595
+ "id": "ss_task_kafka",
596
+ "label": "Kafka Implementation",
597
+ "sub_sub_subtasks": [
598
+ {
599
+ "id": "sss_task_topics",
600
+ "label": "Topic Design",
601
+ "final_level_tasks": [
602
+ {"id": "ft_schema_registry", "label": "Schema Registry"}
603
+ ]
604
+ }
605
+ ]
606
+ }
607
+ ]
608
+ }
609
+ ]
610
+ },
611
+ {
612
+ "id": "task_ml_platform",
613
+ "label": "ML Platform",
614
  "subtasks": [
615
  {
616
+ "id": "subtask_mlops",
617
+ "label": "MLOps Setup",
618
  "sub_subtasks": [
619
  {
620
+ "id": "ss_task_ci_cd",
621
+ "label": "CI/CD Pipeline",
622
  "sub_sub_subtasks": [
623
  {
624
+ "id": "sss_task_github_actions",
625
+ "label": "GitHub Actions",
626
  "final_level_tasks": [
627
+ {"id": "ft_model_registry", "label": "Model Registry Integration"}
628
  ]
629
  }
630
  ]
 
636
  ]
637
  },
638
  {
639
+ "id": "phase_deployment",
640
+ "label": "Deployment & Operations",
641
  "tasks": [
642
  {
643
+ "id": "task_production",
644
+ "label": "Production Deployment",
645
  "subtasks": [
646
  {
647
+ "id": "subtask_kubernetes",
648
+ "label": "Kubernetes Orchestration",
649
+ "sub_subtasks": [
650
+ {
651
+ "id": "ss_task_helm",
652
+ "label": "Helm Charts",
653
+ "sub_sub_subtasks": [
654
+ {
655
+ "id": "sss_task_autoscaling",
656
+ "label": "Auto-scaling Config",
657
+ "final_level_tasks": [
658
+ {"id": "ft_hpa_setup", "label": "HPA Configuration"}
659
+ ]
660
+ }
661
+ ]
662
+ }
663
+ ]
664
+ },
665
+ {
666
+ "id": "subtask_monitoring",
667
+ "label": "Observability Stack",
668
  "sub_subtasks": [
669
  {
670
+ "id": "ss_task_prometheus",
671
+ "label": "Prometheus Setup",
672
  "sub_sub_subtasks": [
673
  {
674
+ "id": "sss_task_grafana",
675
+ "label": "Grafana Dashboards",
676
  "final_level_tasks": [
677
+ {"id": "ft_alert_rules", "label": "Alert Configuration"}
678
  ]
679
  }
680
  ]
 
687
  }
688
  ]
689
  }
690
+ """