File size: 5,212 Bytes
7c43635 9912372 7c43635 9912372 7c43635 9912372 7c43635 9912372 7c43635 9912372 7c43635 a2fe2e6 7c43635 a2fe2e6 7c43635 9912372 7c43635 9912372 7c43635 9912372 7c43635 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 |
import gradio as gr
import json
from graphviz import Digraph
import base64
def generate_concept_map(json_input: str) -> str:
"""
Generate concept map from JSON and return as base64 image
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
"""
try:
if not json_input.strip():
return "Error: Empty input"
data = json.loads(json_input)
if 'central_node' not in data or 'nodes' not in data:
raise ValueError("Missing required fields: central_node or nodes")
# Create graph
dot = Digraph(
name='ConceptMap',
format='png',
graph_attr={
'rankdir': 'TB',
'splines': 'ortho',
'bgcolor': 'transparent'
}
)
# Central node
dot.node(
'central',
data['central_node'],
shape='ellipse',
style='filled',
fillcolor='#2196F3',
fontcolor='white',
fontsize='14'
)
# Process nodes
for node in data['nodes']:
node_id = node.get('id')
label = node.get('label')
relationship = node.get('relationship')
# Validate node
if not all([node_id, label, relationship]):
raise ValueError(f"Invalid node: {node}")
# Create main node
dot.node(
node_id,
label,
shape='box',
style='filled',
fillcolor='#4CAF50',
fontcolor='white',
fontsize='12'
)
# Connect to central node
dot.edge(
'central',
node_id,
label=relationship,
color='#9C27B0',
fontsize='10'
)
# Process subnodes
for subnode in node.get('subnodes', []):
sub_id = subnode.get('id')
sub_label = subnode.get('label')
sub_rel = subnode.get('relationship')
if not all([sub_id, sub_label, sub_rel]):
raise ValueError(f"Invalid subnode: {subnode}")
dot.node(
sub_id,
sub_label,
shape='diamond',
style='filled',
fillcolor='#FF5722',
fontcolor='white',
fontsize='10'
)
dot.edge(
node_id,
sub_id,
label=sub_rel,
color='#E91E63',
fontsize='8'
)
# Convert to base64 image
img_data = dot.pipe(format='png')
img_base64 = base64.b64encode(img_data).decode()
return f"data:image/png;base64,{img_base64}"
except json.JSONDecodeError:
return "Error: Invalid JSON format"
except Exception as e:
return f"Error: {str(e)}"
if __name__ == "__main__":
# Sample JSON for placeholder
sample_json = """
{
"central_node": "Artificial Intelligence (AI)",
"nodes": [
{
"id": "ml",
"label": "Machine Learning",
"relationship": "core_component",
"subnodes": [
{"id": "sl", "label": "Supervised Learning", "relationship": "type_of"},
{"id": "ul", "label": "Unsupervised Learning", "relationship": "type_of"}
]
},
{
"id": "nlp",
"label": "Natural Language Processing",
"relationship": "application_area",
"subnodes": [
{"id": "sa", "label": "Sentiment Analysis", "relationship": "technique"},
{"id": "tr", "label": "Translation", "relationship": "technique"}
]
}
]
}
"""
demo = gr.Interface(
fn=generate_concept_map,
inputs=gr.Textbox(
value=sample_json, # Pre-filled sample JSON
placeholder="Paste structured JSON here...",
label="JSON Input",
lines=15
),
outputs=gr.Textbox(
label="Image URL",
placeholder="Base64 image URL will appear here"
),
title="Concept Map Generator",
description="Create concept maps from JSON for web display"
)
demo.launch(
mcp_server=True,
share=False,
server_port=7860,
server_name="0.0.0.0"
) |