sample_data.py

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 Development Project",
  "phases": [
    {
      "id": "phase_prep",
      "label": "Preparation",
      "tasks": [
        {
          "id": "task_1_1_vision",
          "label": "Identify Vision",
          "subtasks": [
            {
              "id": "subtask_1_1_1_design_staff",
              "label": "Design & Staffing",
              "sub_subtasks": [
                {
                  "id": "ss_task_1_1_1_1_env_setup",
                  "label": "Environment Setup",
                  "sub_sub_subtasks": [
                    {
                      "id": "sss_task_1_1_1_1_1_lib_install",
                      "label": "Install Libraries",
                      "final_level_tasks": [
                        {"id": "ft_1_1_1_1_1_1_data_access", "label": "Grant Data Access"}
                      ]
                    }
                  ]
                }
              ]
            }
          ]
        }
      ]
    },
    {
      "id": "phase_plan",
      "label": "Planning",
      "tasks": [
        {
          "id": "task_2_1_cost_analysis",
          "label": "Cost Analysis",
          "subtasks": [
            {
              "id": "subtask_2_1_1_benefit_analysis",
              "label": "Benefit Analysis",
              "sub_subtasks": [
                {
                  "id": "ss_task_2_1_1_1_risk_assess",
                  "label": "AI Risk Assessment",
                  "sub_sub_subtasks": [
                    {
                      "id": "sss_task_2_1_1_1_1_model_selection",
                      "label": "Model Selection",
                      "final_level_tasks": [
                        {"id": "ft_2_1_1_1_1_1_data_strategy", "label": "Data Strategy"}
                      ]
                    }
                  ]
                }
              ]
            }
          ]
        }
      ]
    },
    {
      "id": "phase_dev",
      "label": "Development",
      "tasks": [
        {
          "id": "task_3_1_change_mgmt",
          "label": "Data Preprocessing",
          "subtasks": [
            {
              "id": "subtask_3_1_1_implementation",
              "label": "Feature Engineering",
              "sub_subtasks": [
                {
                  "id": "ss_task_3_1_1_1_beta_testing",
                  "label": "Model Training",
                  "sub_sub_subtasks": [
                    {
                      "id": "sss_task_3_1_1_1_1_other_task",
                      "label": "Model Evaluation",
                      "final_level_tasks": [
                        {"id": "ft_3_1_1_1_1_1_hyperparam_tune", "label": "Hyperparameter Tuning"}
                      ]
                    }
                  ]
                }
              ]
            }
          ]
        }
      ]
    }
  ]
}

"""