Graphify / sample_data.py
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CONCEPT_MAP_JSON = """
{
"central_node": "Artificial Intelligence (AI)",
"nodes": [
{
"id": "ml_fundamental",
"label": "Machine Learning",
"relationship": "is essential for",
"subnodes": [
{
"id": "dl_branch",
"label": "Deep Learning",
"relationship": "for example",
"subnodes": [
{
"id": "cnn_example",
"label": "CNNs",
"relationship": "for example"
},
{
"id": "rnn_example",
"label": "RNNs",
"relationship": "for example"
}
]
},
{
"id": "rl_branch",
"label": "Reinforcement Learning",
"relationship": "for example",
"subnodes": [
{
"id": "qlearning_example",
"label": "Q-Learning",
"relationship": "example"
},
{
"id": "pg_example",
"label": "Policy Gradients",
"relationship": "example"
}
]
}
]
},
{
"id": "ai_types",
"label": "Types",
"relationship": "formed by",
"subnodes": [
{
"id": "agi_type",
"label": "AGI",
"relationship": "this is",
"subnodes": [
{
"id": "strong_ai",
"label": "Strong AI",
"relationship": "provoked by",
"subnodes": [
{
"id": "human_intel",
"label": "Human-level Intel.",
"relationship": "of"
}
]
}
]
},
{
"id": "ani_type",
"label": "ANI",
"relationship": "this is",
"subnodes": [
{
"id": "weak_ai",
"label": "Weak AI",
"relationship": "provoked by",
"subnodes": [
{
"id": "narrow_tasks",
"label": "Narrow Tasks",
"relationship": "of"
}
]
}
]
}
]
},
{
"id": "ai_capabilities",
"label": "Capabilities",
"relationship": "change",
"subnodes": [
{
"id": "data_proc",
"label": "Data Processing",
"relationship": "can",
"subnodes": [
{
"id": "big_data",
"label": "Big Data",
"relationship": "as",
"subnodes": [
{
"id": "analysis_example",
"label": "Data Analysis",
"relationship": "example"
},
{
"id": "prediction_example",
"label": "Prediction",
"relationship": "example"
}
]
}
]
},
{
"id": "decision_making",
"label": "Decision Making",
"relationship": "can be",
"subnodes": [
{
"id": "automation",
"label": "Automation",
"relationship": "as",
"subnodes": [
{
"id": "robotics_example",
"label": "Robotics",
"relationship": "Example"},
{
"id": "autonomous_example",
"label": "Autonomous Vehicles",
"relationship": "of one"
}
]
}
]
},
{
"id": "problem_solving",
"label": "Problem Solving",
"relationship": "can",
"subnodes": [
{
"id": "optimization",
"label": "Optimization",
"relationship": "as is",
"subnodes": [
{
"id": "algorithms_example",
"label": "Algorithms",
"relationship": "for example"
}
]
}
]
}
]
}
]
}
"""
# JSON for Synoptic Chart (horizontal hierarchy) - AI related, 4 levels
SYNOPTIC_CHART_JSON = """
{
"central_node": "AI Project Lifecycle",
"nodes": [
{
"id": "phase1",
"label": "I. Problem Definition & Data Acquisition",
"relationship": "Starts with",
"subnodes": [
{
"id": "sub1_1",
"label": "1. Problem Formulation",
"relationship": "Involves",
"subnodes": [
{"id": "sub1_1_1", "label": "1.1. Identify Business Need", "relationship": "e.g."},
{"id": "sub1_1_2", "label": "1.2. Define KPIs", "relationship": "e.g."}
]
},
{
"id": "sub1_2",
"label": "2. Data Collection",
"relationship": "Followed by",
"subnodes": [
{"id": "sub1_2_1", "label": "2.1. Source Data", "relationship": "from"},
{"id": "sub1_2_2", "label": "2.2. Data Cleaning", "relationship": "includes"}
]
}
]
},
{
"id": "phase2",
"label": "II. Model Development",
"relationship": "Proceeds to",
"subnodes": [
{
"id": "sub2_1",
"label": "1. Feature Engineering",
"relationship": "Comprises",
"subnodes": [
{"id": "sub2_1_1", "label": "1.1. Feature Selection", "relationship": "e.g."},
{"id": "sub2_1_2", "label": "1.2. Feature Transformation", "relationship": "e.g."}
]
},
{
"id": "sub2_2",
"label": "2. Model Training",
"relationship": "Involves",
"subnodes": [
{"id": "sub2_2_1", "label": "2.1. Algorithm Selection", "relationship": "uses"},
{"id": "sub2_2_2", "label": "2.2. Hyperparameter Tuning", "relationship": "optimizes"}
]
}
]
},
{
"id": "phase3",
"label": "III. Evaluation & Deployment",
"relationship": "Culminates in",
"subnodes": [
{
"id": "sub3_1",
"label": "1. Model Evaluation",
"relationship": "Includes",
"subnodes": [
{"id": "sub3_1_1", "label": "1.1. Performance Metrics", "relationship": "measures"},
{"id": "sub3_1_2", "label": "1.2. Bias & Fairness Audits", "relationship": "ensures"}
]
},
{
"id": "sub3_2",
"label": "2. Deployment & Monitoring",
"relationship": "Requires",
"subnodes": [
{"id": "sub3_2_1", "label": "2.1. API/Integration Development", "relationship": "for"},
{"id": "sub3_2_2", "label": "2.2. Continuous Monitoring", "relationship": "ensures"}
]
}
]
}
]
}
"""
# JSON for Radial Diagram (central expansion) - AI related, 3 levels with 5->10 structure
RADIAL_DIAGRAM_JSON = """
{
"central_node": "AI Core Concepts & Domains",
"nodes": [
{
"id": "foundational_ml",
"label": "Foundational ML",
"relationship": "builds on",
"subnodes": [
{"id": "supervised_l", "label": "Supervised Learning", "relationship": "e.g."},
{"id": "unsupervised_l", "label": "Unsupervised Learning", "relationship": "e.g."}
]
},
{
"id": "dl_architectures",
"label": "Deep Learning Arch.",
"relationship": "evolved from",
"subnodes": [
{"id": "cnns_rad", "label": "CNNs", "relationship": "e.g."},
{"id": "rnns_rad", "label": "RNNs", "relationship": "e.g."}
]
},
{
"id": "major_applications",
"label": "Major AI Applications",
"relationship": "applied in",
"subnodes": [
{"id": "nlp_rad", "label": "Natural Language Processing", "relationship": "e.g."},
{"id": "cv_rad", "label": "Computer Vision", "relationship": "e.g."}
]
},
{
"id": "ethical_concerns",
"label": "Ethical AI Concerns",
"relationship": "addresses",
"subnodes": [
{"id": "fairness_rad", "label": "Fairness & Bias", "relationship": "e.g."},
{"id": "explainability", "label": "Explainability (XAI)", "relationship": "e.g."}
]
},
{
"id": "future_trends",
"label": "Future AI Trends",
"relationship": "looking at",
"subnodes": [
{"id": "agi_future", "label": "AGI Development", "relationship": "e.g."},
{"id": "quantum_ai", "label": "Quantum AI", "relationship": "e.g."}
]
}
]
}
"""
PROCESS_FLOW_JSON = """
{
"start_node": "Start Inference Request",
"nodes": [
{
"id": "user_input",
"label": "Receive User Input (Data)",
"type": "io"
},
{
"id": "preprocess_data",
"label": "Preprocess Data",
"type": "process"
},
{
"id": "validate_data",
"label": "Validate Data Format/Type",
"type": "decision"
},
{
"id": "data_valid_yes",
"label": "Data Valid?",
"type": "decision"
},
{
"id": "load_model",
"label": "Load AI Model (if not cached)",
"type": "process"
},
{
"id": "run_inference",
"label": "Run AI Model Inference",
"type": "process"
},
{
"id": "postprocess_output",
"label": "Postprocess Model Output",
"type": "process"
},
{
"id": "send_response",
"label": "Send Response to User",
"type": "io"
},
{
"id": "log_error",
"label": "Log Error & Notify User",
"type": "process"
},
{
"id": "end_inference_process",
"label": "End Inference Process",
"type": "end"
}
],
"connections": [
{"from": "start_node", "to": "user_input", "label": "Request"},
{"from": "user_input", "to": "preprocess_data", "label": "Data Received"},
{"from": "preprocess_data", "to": "validate_data", "label": "Cleaned"},
{"from": "validate_data", "to": "data_valid_yes", "label": "Check"},
{"from": "data_valid_yes", "to": "load_model", "label": "Yes"},
{"from": "data_valid_yes", "to": "log_error", "label": "No"},
{"from": "load_model", "to": "run_inference", "label": "Model Ready"},
{"from": "run_inference", "to": "postprocess_output", "label": "Output Generated"},
{"from": "postprocess_output", "to": "send_response", "label": "Ready"},
{"from": "send_response", "to": "end_inference_process", "label": "Response Sent"},
{"from": "log_error", "to": "end_inference_process", "label": "Error Handled"}
]
}
"""
# New JSON for Work Breakdown Structure (WBS) Diagram - similar to image, but not identical
WBS_DIAGRAM_JSON = """
{
"project_title": "AI Model Deployment Project",
"phases": [
{
"id": "phase_1_prep",
"label": "1. Preparation",
"tasks": [
{
"id": "task_1_1_goal_scope",
"label": "1.1. Define Goal & Scope",
"subtasks": [
{
"id": "subtask_1_1_1_ai_problem",
"label": "1.1.1. AI Problem Definition",
"granular_tasks": [
{
"id": "gt_1_1_1_1_understand_req",
"label": "1.1.1.1. Understand Requirements",
"sub_granular_tasks": [
{
"id": "sgt_1_1_1_1_1_gather_stakeholder_input",
"label": "1.1.1.1.1. Gather Stakeholder Input",
"final_tasks": [
{"id": "ft_1_1_1_1_1_1_interview_users", "label": "1.1.1.1.1.1. Interview Users"},
{"id": "ft_1_1_1_1_1_2_analyze_feedback", "label": "1.1.1.1.1.2. Analyze Feedback"},
{"id": "ft_1_1_1_1_1_3_document_needs", "label": "1.1.1.1.1.3. Document Needs"}
]
}
]
}
]
}
]
},
{
"id": "task_1_2_resource_id",
"label": "1.2. Identify Resources",
"subtasks": [
{
"id": "subtask_1_2_1_data_sources",
"label": "1.2.1. Data Sources Identification",
"granular_tasks": [
{
"id": "gt_1_2_1_1_list_internal_data",
"label": "1.2.1.1. List Internal Data",
"sub_granular_tasks": [
{
"id": "sgt_1_2_1_1_1_check_db_access",
"label": "1.2.1.1.1. Check DB Access",
"final_tasks": [
{"id": "ft_1_2_1_1_1_1_verify_credentials", "label": "1.2.1.1.1.1. Verify Credentials"},
{"id": "ft_1_2_1_1_1_2_test_connections", "label": "1.2.1.1.1.2. Test Connections"},
{"id": "ft_1_2_1_1_1_3_secure_apis", "label": "1.2.1.1.1.3. Secure APIs"}
]
}
]
}
]
}
]
},
{
"id": "task_1_3_env_setup",
"label": "1.3. Environment Setup",
"subtasks": [
{
"id": "subtask_1_3_1_cloud_infra",
"label": "1.3.1. Cloud Infra. Provisioning",
"granular_tasks": [
{
"id": "gt_1_3_1_1_deploy_vms",
"label": "1.3.1.1. Deploy VMs",
"sub_granular_tasks": [
{
"id": "sgt_1_3_1_1_1_select_instance_types",
"label": "1.3.1.1.1. Select Instance Types",
"final_tasks": [
{"id": "ft_1_3_1_1_1_1_gpu_spec", "label": "1.3.1.1.1.1. GPU Spec"},
{"id": "ft_1_3_1_1_1_2_cpu_mem", "label": "1.3.1.1.1.2. CPU/Mem"},
{"id": "ft_1_3_1_1_1_3_storage_opts", "label": "1.3.1.1.1.3. Storage Options"}
]
}
]
}
]
}
]
}
]
}
]
}
"""