Update sample_data.py
Browse files- sample_data.py +436 -224
sample_data.py
CHANGED
@@ -1,86 +1,181 @@
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CONCEPT_MAP_JSON = """
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{
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"central_node": "
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"nodes": [
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"id": "
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"relationship": "
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"subnodes": [
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"id": "
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"relationship": "
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"subnodes": [
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"id": "
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"subnodes": [
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"relationship": "
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"id": "
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"relationship": "
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"subnodes": [
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"id": "
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"relationship": "
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"subnodes": [
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"id": "
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"label": "
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"relationship": "
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"subnodes": [
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"id": "
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"label": "
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"relationship": "
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"id": "
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"subnodes": [
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}
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@@ -89,71 +184,53 @@ CONCEPT_MAP_JSON = """
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},
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{
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"id": "
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"label": "
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"subnodes": [
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"id": "
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"relationship": "
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"subnodes": [
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"id": "
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"label": "
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"relationship": "
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"subnodes": [
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"id": "
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"relationship": "
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"id": "
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"label": "
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"relationship": "
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"id": "
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"label": "
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"relationship": "
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"subnodes": [
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"id": "
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"label": "
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"relationship": "
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"subnodes": [
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"id": "
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"label": "
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"relationship": "
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"id": "autonomous_example",
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"label": "Autonomous Vehicles",
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"relationship": "of one"
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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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"id": "problem_solving",
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"label": "Problem Solving",
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"relationship": "can",
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"subnodes": [
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{
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"id": "optimization",
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"label": "Optimization",
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"relationship": "as is",
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"subnodes": [
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"id": "
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"label": "
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"relationship": "
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}
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@@ -165,82 +242,81 @@ CONCEPT_MAP_JSON = """
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}
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"""
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# JSON for Synoptic Chart (horizontal hierarchy) - AI related, 4 levels
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SYNOPTIC_CHART_JSON = """
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{
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"central_node": "AI
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"nodes": [
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{
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"id": "phase1",
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"label": "I.
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"relationship": "
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"subnodes": [
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{
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"id": "
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"label": "1.
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"relationship": "
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"subnodes": [
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{"id": "
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{"id": "
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{
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"id": "
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"label": "2. Data
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"relationship": "
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"subnodes": [
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{"id": "
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{"id": "
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},
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{
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"id": "phase2",
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"label": "II. Model Development",
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"relationship": "
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"subnodes": [
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{
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"id": "
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"label": "1.
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"relationship": "
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"subnodes": [
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{"id": "
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{"id": "
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{
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"id": "
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"label": "2.
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"relationship": "
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"subnodes": [
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{"id": "
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{"id": "
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},
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{
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"id": "phase3",
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"label": "III.
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"relationship": "
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"subnodes": [
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{
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"id": "
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"label": "1.
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"relationship": "
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"subnodes": [
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{"id": "
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{"id": "
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"id": "
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"label": "2.
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"relationship": "
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"subnodes": [
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{"id": "
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{"id": "
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}
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"""
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# JSON for Radial Diagram (central expansion) - AI related, 3 levels with 5->10 structure
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RADIAL_DIAGRAM_JSON = """
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{
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"central_node": "AI
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"nodes": [
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{
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"id": "
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"label": "
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"relationship": "
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"subnodes": [
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{"id": "
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{"id": "
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"id": "
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"label": "
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"relationship": "
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"subnodes": [
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{"id": "
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{"id": "
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"id": "
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"label": "
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"subnodes": [
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{"id": "
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{"id": "
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"id": "
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@@ -305,101 +380,176 @@ RADIAL_DIAGRAM_JSON = """
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PROCESS_FLOW_JSON = """
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{
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"start_node": "
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"nodes": [
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"id": "
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"type": "
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"id": "
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"type": "process"
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"id": "
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"type": "decision"
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"id": "
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"type": "decision"
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"id": "
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"type": "process"
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"type": "process"
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"type": "process"
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"id": "
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"type": "io"
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"type": "end"
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}
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],
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"connections": [
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{"from": "start_node", "to": "
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{"from": "
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{"from": "
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}
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"""
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# New JSON for Work Breakdown Structure (WBS) Diagram - similar to image, but not identical
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WBS_DIAGRAM_JSON = """
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{
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"project_title": "AI
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"phases": [
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{
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"id": "
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"label": "
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"tasks": [
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"subtasks": [
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"id": "
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"label": "Design
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"sub_subtasks": [
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"sub_sub_subtasks": [
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"final_level_tasks": [
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"subtasks": [
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"sub_subtasks": [
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"sub_sub_subtasks": [
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"final_level_tasks": [
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"""
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# Enhanced Sample Data for AI Diagram Generator
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# Modern and practical AI-related sample data
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CONCEPT_MAP_JSON = """
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{
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"central_node": "Generative AI Ecosystem",
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"nodes": [
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{
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"id": "foundation_models",
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"label": "Foundation Models",
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"relationship": "powered by",
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"subnodes": [
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{
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"id": "llm_models",
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"label": "Large Language Models",
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"relationship": "includes",
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17 |
"subnodes": [
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{
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"id": "gpt_family",
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20 |
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"label": "GPT Family",
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21 |
+
"relationship": "such as",
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22 |
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"subnodes": [
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23 |
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{
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24 |
+
"id": "gpt4",
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25 |
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"label": "GPT-4",
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26 |
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"relationship": "latest version"
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27 |
+
},
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28 |
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{
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29 |
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"id": "chatgpt",
|
30 |
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"label": "ChatGPT",
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31 |
+
"relationship": "application"
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32 |
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}
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33 |
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]
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34 |
},
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{
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"id": "claude_family",
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37 |
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"label": "Claude Family",
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38 |
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"relationship": "such as",
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{
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"label": "Claude 3 Opus",
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43 |
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"relationship": "advanced model"
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44 |
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},
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45 |
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{
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46 |
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"id": "claude_sonnet",
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"label": "Claude Sonnet",
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48 |
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"relationship": "balanced model"
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49 |
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}
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50 |
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]
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51 |
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},
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52 |
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{
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53 |
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"id": "opensource_llm",
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"label": "Open Source LLMs",
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55 |
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56 |
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{
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60 |
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"relationship": "by Meta"
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61 |
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},
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62 |
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{
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63 |
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"id": "mistral",
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64 |
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"label": "Mistral 7B",
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65 |
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"relationship": "efficient"
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66 |
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}
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67 |
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]
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68 |
}
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]
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70 |
},
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{
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72 |
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"id": "multimodal_models",
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73 |
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"label": "Multimodal Models",
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74 |
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"relationship": "extends to",
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75 |
"subnodes": [
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{
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77 |
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"id": "vision_language",
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"label": "Vision-Language Models",
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"relationship": "including",
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80 |
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{
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"id": "dall_e3",
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"label": "DALL-E 3",
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"relationship": "image generation"
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},
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{
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"id": "midjourney",
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88 |
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"label": "Midjourney v6",
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89 |
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"relationship": "artistic creation"
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90 |
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}
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91 |
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]
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92 |
},
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{
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94 |
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"id": "video_models",
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95 |
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"label": "Video Generation",
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96 |
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"relationship": "emerging with",
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"subnodes": [
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{
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"label": "Sora",
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"relationship": "by OpenAI"
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102 |
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},
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{
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"id": "runway",
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"label": "Runway Gen-2",
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106 |
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"relationship": "creative tools"
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107 |
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}
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108 |
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]
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109 |
}
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110 |
]
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111 |
}
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112 |
]
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113 |
},
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114 |
{
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115 |
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"id": "ai_applications",
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116 |
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"label": "Real-World Applications",
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117 |
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"relationship": "deployed in",
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118 |
"subnodes": [
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119 |
{
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120 |
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"id": "enterprise_ai",
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121 |
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"label": "Enterprise Solutions",
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122 |
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"relationship": "transforming",
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123 |
"subnodes": [
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124 |
{
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125 |
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"id": "ai_assistants",
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126 |
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"label": "AI Assistants",
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127 |
+
"relationship": "like",
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128 |
"subnodes": [
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129 |
{
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130 |
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"id": "copilot",
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131 |
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"label": "GitHub Copilot",
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132 |
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"relationship": "code generation"
|
133 |
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},
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134 |
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{
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135 |
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"id": "duet_ai",
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136 |
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"label": "Google Duet AI",
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137 |
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"relationship": "workspace integration"
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138 |
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}
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139 |
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]
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140 |
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},
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141 |
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{
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142 |
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"id": "automation",
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143 |
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"label": "Process Automation",
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144 |
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"relationship": "through",
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145 |
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"subnodes": [
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146 |
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{
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147 |
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"id": "rpa_ai",
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148 |
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"label": "AI-Enhanced RPA",
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149 |
+
"relationship": "intelligent automation"
|
150 |
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},
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151 |
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{
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152 |
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"id": "document_ai",
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153 |
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"label": "Document Intelligence",
|
154 |
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"relationship": "data extraction"
|
155 |
}
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156 |
]
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157 |
}
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158 |
]
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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",
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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 |
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"label": "AI Infrastructure",
|
189 |
+
"relationship": "supported by",
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190 |
"subnodes": [
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191 |
{
|
192 |
+
"id": "compute_resources",
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193 |
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"label": "Compute Resources",
|
194 |
+
"relationship": "requiring",
|
195 |
"subnodes": [
|
196 |
{
|
197 |
+
"id": "gpu_clusters",
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198 |
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"label": "GPU Clusters",
|
199 |
+
"relationship": "powered by",
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200 |
"subnodes": [
|
201 |
{
|
202 |
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"id": "nvidia_h100",
|
203 |
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"label": "NVIDIA H100",
|
204 |
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"relationship": "latest generation"
|
205 |
},
|
206 |
{
|
207 |
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"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",
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219 |
"subnodes": [
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220 |
{
|
221 |
+
"id": "model_serving",
|
222 |
+
"label": "Model Serving",
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223 |
+
"relationship": "via",
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224 |
"subnodes": [
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225 |
{
|
226 |
+
"id": "huggingface",
|
227 |
+
"label": "Hugging Face",
|
228 |
+
"relationship": "model hub"
|
229 |
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},
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|
230 |
{
|
231 |
+
"id": "vertex_ai",
|
232 |
+
"label": "Vertex AI",
|
233 |
+
"relationship": "Google Cloud"
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234 |
}
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235 |
]
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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",
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253 |
"subnodes": [
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254 |
{
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255 |
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"id": "data_strategy",
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256 |
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"label": "1. Data Strategy",
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257 |
+
"relationship": "establishing",
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258 |
"subnodes": [
|
259 |
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{"id": "data_sources", "label": "1.1. Multi-Source Integration", "relationship": "includes", "subnodes": []},
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260 |
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{"id": "data_governance", "label": "1.2. Privacy & Compliance", "relationship": "ensures", "subnodes": []}
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261 |
]
|
262 |
},
|
263 |
{
|
264 |
+
"id": "data_pipeline",
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265 |
+
"label": "2. Data Pipeline",
|
266 |
+
"relationship": "building",
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267 |
"subnodes": [
|
268 |
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{"id": "etl_process", "label": "2.1. ETL/ELT Workflows", "relationship": "implements", "subnodes": []},
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269 |
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{"id": "feature_store", "label": "2.2. Feature Store Setup", "relationship": "centralizes", "subnodes": []}
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270 |
]
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271 |
}
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272 |
]
|
273 |
},
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274 |
{
|
275 |
"id": "phase2",
|
276 |
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"label": "II. Model Development & Training",
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277 |
+
"relationship": "continues to",
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278 |
"subnodes": [
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279 |
{
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280 |
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"id": "experimentation",
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281 |
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"label": "1. Experimentation Platform",
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282 |
+
"relationship": "enabling",
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283 |
"subnodes": [
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284 |
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{"id": "experiment_tracking", "label": "1.1. MLflow/W&B Integration", "relationship": "tracks", "subnodes": []},
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285 |
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{"id": "hyperparameter_opt", "label": "1.2. AutoML & HPO", "relationship": "optimizes", "subnodes": []}
|
286 |
]
|
287 |
},
|
288 |
{
|
289 |
+
"id": "distributed_training",
|
290 |
+
"label": "2. Scalable Training",
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291 |
+
"relationship": "leveraging",
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292 |
"subnodes": [
|
293 |
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{"id": "multi_gpu", "label": "2.1. Multi-GPU Training", "relationship": "accelerates", "subnodes": []},
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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",
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303 |
"subnodes": [
|
304 |
{
|
305 |
+
"id": "model_deployment",
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306 |
+
"label": "1. Production Deployment",
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307 |
+
"relationship": "implementing",
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308 |
"subnodes": [
|
309 |
+
{"id": "edge_deployment", "label": "1.1. Edge Computing", "relationship": "optimizes", "subnodes": []},
|
310 |
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{"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",
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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 |
}
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322 |
]
|
|
|
325 |
}
|
326 |
"""
|
327 |
|
|
|
328 |
RADIAL_DIAGRAM_JSON = """
|
329 |
{
|
330 |
+
"central_node": "AI Innovation Hub",
|
331 |
"nodes": [
|
332 |
{
|
333 |
+
"id": "emerging_tech",
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334 |
+
"label": "Emerging Technologies",
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335 |
+
"relationship": "advancing through",
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336 |
"subnodes": [
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337 |
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{"id": "quantum_ml", "label": "Quantum Machine Learning", "relationship": "breakthrough in", "subnodes": []},
|
338 |
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{"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 |
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"label": "Research Frontiers",
|
362 |
+
"relationship": "exploring",
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363 |
"subnodes": [
|
364 |
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{"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",
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370 |
+
"label": "AI Ecosystem",
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371 |
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"relationship": "building",
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372 |
"subnodes": [
|
373 |
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{"id": "open_source", "label": "Open Source Community", "relationship": "contributing to", "subnodes": []},
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374 |
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{"id": "ai_startups", "label": "AI Startup Ecosystem", "relationship": "innovating in", "subnodes": []}
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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 |
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{
|
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 |
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{
|
456 |
+
"id": "end_process",
|
457 |
+
"label": "Complete",
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458 |
"type": "end"
|
459 |
}
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460 |
],
|
461 |
"connections": [
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462 |
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{"from": "start_node", "to": "auth_check", "label": "Begin"},
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463 |
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{"from": "auth_check", "to": "auth_valid", "label": "Verify"},
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464 |
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{"from": "auth_valid", "to": "request_router", "label": "Authorized"},
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465 |
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{"from": "auth_valid", "to": "error_handler", "label": "Denied"},
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466 |
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{"from": "request_router", "to": "cache_check", "label": "Route"},
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467 |
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{"from": "cache_check", "to": "deliver_response", "label": "Cache Hit"},
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468 |
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{"from": "cache_check", "to": "model_selector", "label": "Cache Miss"},
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469 |
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{"from": "model_selector", "to": "load_balancer", "label": "Selected"},
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470 |
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{"from": "load_balancer", "to": "inference_engine", "label": "Assigned"},
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471 |
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{"from": "inference_engine", "to": "quality_check", "label": "Generated"},
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472 |
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{"from": "quality_check", "to": "post_processor", "label": "Pass"},
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473 |
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{"from": "quality_check", "to": "fallback_model", "label": "Fail"},
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474 |
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{"from": "fallback_model", "to": "post_processor", "label": "Retry"},
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475 |
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{"from": "post_processor", "to": "response_cache", "label": "Processed"},
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476 |
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{"from": "response_cache", "to": "analytics_log", "label": "Cached"},
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477 |
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{"from": "analytics_log", "to": "deliver_response", "label": "Logged"},
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478 |
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{"from": "deliver_response", "to": "end_process", "label": "Delivered"},
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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 |
+
"""
|
|