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import gradio as gr
import json
from graphviz import Digraph
import os
from tempfile import NamedTemporaryFile
from sample_data import COMPLEX_SAMPLE_JSON # El JSON de ejemplo se mantiene sin cambios
def generate_concept_map(json_input: str) -> str:
"""
Generate concept map from JSON and return as image file
Args:
json_input (str): JSON describing the concept map structure.
REQUIRED FORMAT EXAMPLE:
{
"central_node": "AI",
"nodes": [
{
"id": "ml",
"label": "Machine Learning",
"relationship": "subcategory",
"subnodes": [
{
"id": "dl",
"label": "Deep Learning",
"relationship": "type",
"subnodes": [
{
"id": "cnn",
"label": "CNN",
"relationship": "architecture"
}
]
}
]
}
]
}
Returns:
str: Path to generated PNG image file
"""
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")
dot = Digraph(
name='ConceptMap',
format='png',
graph_attr={
'rankdir': 'TB', # Top-to-Bottom
'splines': 'ortho', # Straight lines
'bgcolor': 'white', # Fondo blanco
'pad': '0.5' # ¡Este es el margen! 0.5 pulgadas
}
)
# Base color for the central node
base_color = '#19191a' # Casi negro
# Central node (now a rounded box)
dot.node(
'central',
data['central_node'],
shape='box', # Ahora es un rectángulo
style='filled,rounded', # Redondeado
fillcolor=base_color, # Color base
fontcolor='white',
fontsize='16' # Un poco más grande para el título
)
# Helper function to recursively add nodes and edges
def add_nodes_and_edges(parent_id, nodes_list, current_depth=0):
# Calculate color for current depth, making it lighter
lightening_factor = 0.12 # How much lighter each level gets
# Convert base_color hex to RGB
base_r = int(base_color[1:3], 16)
base_g = int(base_color[3:5], 16)
base_b = int(base_color[5:7], 16)
# Calculate current node color
current_r = base_r + int((255 - base_r) * current_depth * lightening_factor)
current_g = base_g + int((255 - base_g) * current_depth * lightening_factor)
current_b = base_b + int((255 - base_b) * current_depth * lightening_factor)
# Clamp values to 255
current_r = min(255, current_r)
current_g = min(255, current_g)
current_b = min(255, current_b)
node_fill_color = f'#{current_r:02x}{current_g:02x}{current_b:02x}'
# Font color: white for dark nodes, black for very light nodes
font_color = 'white' if current_depth * lightening_factor < 0.6 else 'black'
# Edge colors can remain constant or change. Let's make them slightly visible.
edge_color = '#4a4a4a' # Un gris oscuro para las líneas
font_size = max(9, 14 - (current_depth * 2)) # Adjust font size based on depth
edge_font_size = max(7, 10 - (current_depth * 1))
for node in nodes_list:
node_id = node.get('id')
label = node.get('label')
relationship = node.get('relationship')
if not all([node_id, label, relationship]):
raise ValueError(f"Invalid node: {node}")
dot.node(
node_id,
label,
shape='box', # Rectángulo
style='filled,rounded', # Redondeado
fillcolor=node_fill_color,
fontcolor=font_color,
fontsize=str(font_size)
)
dot.edge(
parent_id,
node_id,
label=relationship,
color=edge_color,
fontcolor=edge_color, # Color de la fuente de la arista también gris
fontsize=str(edge_font_size)
)
if 'subnodes' in node:
add_nodes_and_edges(node_id, node['subnodes'], current_depth + 1)
# Start processing from the top-level nodes connected to the central node
add_nodes_and_edges('central', data.get('nodes', []), current_depth=1) # Initial depth is 1 for nodes under central
# Save to temporary file
with NamedTemporaryFile(delete=False, suffix='.png') as tmp:
dot.render(tmp.name, format='png', cleanup=True)
return tmp.name + '.png'
except json.JSONDecodeError:
return "Error: Invalid JSON format"
except Exception as e:
return f"Error: {str(e)}"
if __name__ == "__main__":
demo = gr.Interface(
fn=generate_concept_map,
inputs=gr.Textbox(
value=COMPLEX_SAMPLE_JSON,
placeholder="Paste JSON following the documented format",
label="Structured JSON Input",
lines=25
),
outputs=gr.Image(
label="Generated Concept Map",
type="filepath",
show_download_button=True
),
title="AI Concept Map (Custom Style)",
description="Generates an AI concept map with custom rounded boxes, color gradient, and white background."
)
demo.launch(
mcp_server=True,
share=False,
server_port=7860,
server_name="0.0.0.0"
) |