Update app.py

app.py

@@ -9,19 +9,7 @@ def generate_concept_map(json_input: str) -> str:
     
     Args:
         json_input (str): JSON describing the concept map structure.
-            Required format:
-            {
-                "central_node": "Main concept",
-                "nodes": [
-                    {
-                        "id": "unique_identifier",
-                        "label": "Node label",
-                        "relationship": "Relationship to parent",
-                        "subnodes": [...]  # Optional
-                    }
-                ]
-            }
-    
+        
     Returns:
         str: Base64 data URL of the generated concept map
     """
@@ -45,7 +33,7 @@ def generate_concept_map(json_input: str) -> str:
             }
         )
         
-        # Central node
+        # Central node (ellipse)
         dot.node(
             'central',
             data['central_node'],
@@ -56,7 +44,7 @@ def generate_concept_map(json_input: str) -> str:
             fontsize='14'
         )
         
-        # Process nodes
+        # Process nodes (rectangles)
         for node in data['nodes']:
             node_id = node.get('id')
             label = node.get('label')
@@ -66,7 +54,7 @@ def generate_concept_map(json_input: str) -> str:
             if not all([node_id, label, relationship]):
                 raise ValueError(f"Invalid node: {node}")
                 
-            # Create main node
+            # Create main node (rectangle)
             dot.node(
                 node_id,
                 label,
@@ -86,7 +74,7 @@ def generate_concept_map(json_input: str) -> str:
                 fontsize='10'
             )
             
-            # Process subnodes
+            # Process subnodes (rectangles with lighter fill)
             for subnode in node.get('subnodes', []):
                 sub_id = subnode.get('id')
                 sub_label = subnode.get('label')
@@ -98,9 +86,9 @@ def generate_concept_map(json_input: str) -> str:
                 dot.node(
                     sub_id,
                     sub_label,
-                    shape='diamond',
+                    shape='box',
                     style='filled',
-                    fillcolor='#FF5722',
+                    fillcolor='#FFA726',
                     fontcolor='white',
                     fontsize='10'
                 )
@@ -134,8 +122,24 @@ if __name__ == "__main__":
           "label": "Machine Learning",
           "relationship": "core_component",
           "subnodes": [
-            {"id": "sl", "label": "Supervised Learning", "relationship": "type_of"},
-            {"id": "ul", "label": "Unsupervised Learning", "relationship": "type_of"}
+            {
+              "id": "sl",
+              "label": "Supervised Learning",
+              "relationship": "type_of",
+              "subnodes": [
+                {"id": "reg", "label": "Regression", "relationship": "technique"},
+                {"id": "clf", "label": "Classification", "relationship": "technique"}
+              ]
+            },
+            {
+              "id": "ul",
+              "label": "Unsupervised Learning",
+              "relationship": "type_of",
+              "subnodes": [
+                {"id": "clus", "label": "Clustering", "relationship": "technique"},
+                {"id": "dim", "label": "Dimensionality Reduction", "relationship": "technique"}
+              ]
+            }
           ]
         },
         {
@@ -143,8 +147,40 @@ if __name__ == "__main__":
           "label": "Natural Language Processing",
           "relationship": "application_area",
           "subnodes": [
-            {"id": "sa", "label": "Sentiment Analysis", "relationship": "technique"},
-            {"id": "tr", "label": "Translation", "relationship": "technique"}
+            {
+              "id": "sa",
+              "label": "Sentiment Analysis",
+              "relationship": "task",
+              "subnodes": [
+                {"id": "tc", "label": "Text Classification", "relationship": "method"},
+                {"id": "absa", "label": "Aspect-Based Sentiment Analysis", "relationship": "method"}
+              ]
+            },
+            {
+              "id": "tr",
+              "label": "Translation",
+              "relationship": "task",
+              "subnodes": [
+                {"id": "nmt", "label": "Neural Machine Translation", "relationship": "method"},
+                {"id": "rbt", "label": "Rule-Based Translation", "relationship": "method"}
+              ]
+            }
+          ]
+        },
+        {
+          "id": "cv",
+          "label": "Computer Vision",
+          "relationship": "application_area",
+          "subnodes": [
+            {
+              "id": "od",
+              "label": "Object Detection",
+              "relationship": "task",
+              "subnodes": [
+                {"id": "yolo", "label": "YOLO", "relationship": "algorithm"},
+                {"id": "rcnn", "label": "R-CNN", "relationship": "algorithm"}
+              ]
+            }
           ]
         }
       ]
@@ -159,12 +195,13 @@ if __name__ == "__main__":
             label="JSON Input",
             lines=15
         ),
-        outputs=gr.Textbox(
-            label="Image URL",
-            placeholder="Base64 image URL will appear here"
+        outputs=gr.Image(
+            label="Concept Map",
+            type="filepath",
+            interactive=False
         ),
-        title="Concept Map Generator",
-        description="Create concept maps from JSON for web display"
+        title="Advanced Concept Map Generator",
+        description="Create complex concept maps from JSON with direct image output"
     )
     
     demo.launch(