Update concept_map_generator.py

concept_map_generator.py

@@ -4,13 +4,18 @@ from tempfile import NamedTemporaryFile
 import os
 from graph_generator_utils import add_nodes_and_edges
 
-def generate_concept_map(json_input: str) -> str:
+def generate_concept_map(json_input: str, base_color: str) -> str:
     """
     Generates a concept map from JSON input.
 
     Args:
         json_input (str): A JSON string describing the concept map structure.
                           It must follow the Expected JSON Format Example below.
+        base_color (str): The hexadecimal color string (e.g., '#19191a') for the base
+                          color of the nodes, from which a gradient will be generated.
+
+    Returns:
+        str: The filepath to the generated PNG image file.
 
     Expected JSON Format Example:
     {
@@ -26,33 +31,8 @@ def generate_concept_map(json_input: str) -> str:
               "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": "cnn_example", "label": "CNNs", "relationship": "for example"},
+                {"id": "rnn_example", "label": "RNNs", "relationship": "for example"}
               ]
             }
           ]
@@ -67,119 +47,13 @@ def generate_concept_map(json_input: str) -> str:
               "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"
-                    }
-                  ]
-                }
+                {"id": "strong_ai", "label": "Strong AI", "relationship": "provoked by"}
               ]
             }
           ]
         }
       ]
     }
-
-    Returns:
-        str: The filepath to the generated PNG image file.
     """
     try:
         if not json_input.strip():
@@ -201,7 +75,9 @@ def generate_concept_map(json_input: str) -> str:
             }
         )
         
-        base_color = '#19191a' # Base color for the central node and gradient
+        # Ensure base_color is valid, fallback if not
+        if not isinstance(base_color, str) or not base_color.startswith('#') or len(base_color) != 7:
+            base_color = '#19191a' # Fallback to default dark if invalid
 
         # Central node styling (rounded box, dark color)
         dot.node(