File size: 10,404 Bytes
373ebe3
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7cd1bcd
 
 
 
 
 
 
b4ddcf6
7cd1bcd
 
 
 
 
 
 
 
b4ddcf6
7cd1bcd
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
373ebe3
 
 
 
 
 
7cd1bcd
 
 
5610a1a
7cd1bcd
 
 
29bc850
7cd1bcd
 
 
 
 
 
 
 
 
 
 
373ebe3
29bc850
7cd1bcd
 
 
 
 
d48c4b6
 
 
 
7cd1bcd
d48c4b6
 
 
 
 
 
 
 
7cd1bcd
373ebe3
 
 
 
 
 
 
 
 
 
 
 
7cd1bcd
373ebe3
 
7cd1bcd
d48c4b6
 
b4ddcf6
d48c4b6
 
 
 
7cd1bcd
d48c4b6
 
 
 
 
 
 
d4f660f
d48c4b6
 
29bc850
d48c4b6
 
 
 
 
 
 
 
 
373ebe3
d48c4b6
 
 
 
 
7cd1bcd
 
 
 
 
 
 
 
 
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
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
# import graphviz
# import json
# from tempfile import NamedTemporaryFile
# import os

# def generate_timeline_diagram(json_input: str, output_format: str) -> str:
#     """
#     Generates a serpentine timeline diagram from JSON input.

#     Args:
#         json_input (str): A JSON string describing the timeline structure.
#                           It must follow the Expected JSON Format Example below.

#     Expected JSON Format Example:
#     {
#       "title": "AI Development Timeline",
#       "events_per_row": 4,
#       "events": [
#         {
#           "id": "event_1",
#           "label": "Machine Learning Foundations",
#           "date": "1950-1960",
#           "description": "Early neural networks and perceptrons"
#         },
#         {
#           "id": "event_2",
#           "label": "Expert Systems Era",
#           "date": "1970-1980",
#           "description": "Rule-based AI systems"
#         },
#         {
#           "id": "event_3",
#           "label": "Neural Network Revival",
#           "date": "1980-1990",
#           "description": "Backpropagation algorithm"
#         }
#       ]
#     }

#     Returns:
#         str: The filepath to the generated PNG image file.
#     """
#     try:
#         if not json_input.strip():
#             return "Error: Empty input"
            
#         data = json.loads(json_input)
        
#         if 'events' not in data:
#             raise ValueError("Missing required field: events")

#         dot = graphviz.Digraph(
#             name='Timeline',
#             format='png',
#             graph_attr={
#                 'rankdir': 'TB',        # Top-to-Bottom
#                 'splines': 'ortho',     # Straight lines with 90-degree bends
#                 'bgcolor': 'white',     # White background
#                 'pad': '0.8',           # Padding around the graph
#                 'nodesep': '3.0',       # Increased spacing between nodes horizontally
#                 'ranksep': '2.5'        # Increased spacing between ranks vertically
#             }
#         )
        
#         # base_color = '#19191a' 
#         base_color = '#BEBEBE'
        
#         title = data.get('title', '')
#         events = data.get('events', [])
#         events_per_row = data.get('events_per_row', 4)  
        
#         if not events:
#             raise ValueError("Timeline must contain at least one event")

#         if title:
#             dot.node(
#                 'title',
#                 title,
#                 shape='plaintext',
#                 fontsize='18',
#                 fontweight='bold',
#                 fontcolor=base_color,
#                 pos="6,2!" 
#             )
        
#         total_events = len(events)
        
#         for i, event in enumerate(events):
#             event_id = event.get('id', f'event_{i}')
#             event_label = event.get('label', f'Event {i+1}')
#             event_date = event.get('date', '')
#             event_description = event.get('description', '')
            
#             if event_date and event_description:
#                 full_label = f"{event_date}\\n{event_label}\\n{event_description}"
#             elif event_date:
#                 full_label = f"{event_date}\\n{event_label}"
#             elif event_description:
#                 full_label = f"{event_label}\\n{event_description}"
#             else:
#                 full_label = event_label
            
#             if total_events == 1:
#                 opacity = 'FF'
#             else:
#                 opacity_value = int(255 * (1.0 - (i * 0.7 / (total_events - 1))))
#                 opacity = format(opacity_value, '02x')
            
#             node_color = f"{base_color}{opacity}"
#             font_color = 'white' if i < total_events * 0.7 else 'black'
            
#             row = i // events_per_row
#             col = i % events_per_row
            
#             if row % 2 == 1:
#                 visual_col = events_per_row - 1 - col
#             else:
#                 visual_col = col
            
#             dot.node(
#                 event_id,
#                 full_label,
#                 shape='box',
#                 style='filled,rounded',
#                 fillcolor=node_color,
#                 fontcolor=font_color,
#                 fontsize='12',
#                 width='2.5',
#                 height='1.2',
#                 pos=f"{visual_col * 4.5},{-row * 3}!"  
#             )
        
#         for i in range(len(events) - 1):
#             current_event_id = events[i].get('id', f'event_{i}')
#             next_event_id = events[i + 1].get('id', f'event_{i + 1}')
            
#             dot.edge(
#                 current_event_id,
#                 next_event_id,
#                 color='#666666',
#                 arrowsize='0.8',
#                 penwidth='2'
#             )
        
#         dot.engine = 'neato'

#         with NamedTemporaryFile(delete=False, suffix=f'.{output_format}') as tmp:
#             dot.render(tmp.name, format=output_format, cleanup=True)
#             return f"{tmp.name}.{output_format}"

#     except json.JSONDecodeError:
#         return "Error: Invalid JSON format"
#     except Exception as e:
#         return f"Error: {str(e)}"
import graphviz
import json
from tempfile import NamedTemporaryFile
import os

def generate_timeline_diagram(json_input: str, output_format: str) -> str:
    """
    Generates a serpentine timeline diagram from JSON input.

    Args:
        json_input (str): A JSON string describing the timeline structure.
                          It must follow the Expected JSON Format Example below.

    Expected JSON Format Example:
    {
      "title": "AI Development Timeline",
      "events_per_row": 4,
      "events": [
        {
          "id": "event_1",
          "label": "Machine Learning Foundations",
          "date": "1950-1960",
          "description": "Early neural networks and perceptrons"
        },
        {
          "id": "event_2",
          "label": "Expert Systems Era",
          "date": "1970-1980",
          "description": "Rule-based AI systems"
        },
        {
          "id": "event_3",
          "label": "Neural Network Revival",
          "date": "1980-1990",
          "description": "Backpropagation algorithm"
        }
      ]
    }

    Returns:
        str: The filepath to the generated PNG image file.
    """
    try:
        if not json_input.strip():
            return "Error: Empty input"
            
        data = json.loads(json_input)
        
        if 'events' not in data:
            raise ValueError("Missing required field: events")

        dot = graphviz.Digraph(
            name='Timeline',
            format='png',
            graph_attr={
                'rankdir': 'TB',
                'splines': 'ortho',
                'bgcolor': 'white',
                'pad': '0.8',
                'nodesep': '3.0',
                'ranksep': '2.5'
            }
        )
        
        base_color = '#BEBEBE'
        
        title = data.get('title', '')
        events = data.get('events', [])
        events_per_row = data.get('events_per_row', 4)  
        
        if not events:
            raise ValueError("Timeline must contain at least one event")

        if title:
            dot.node(
                'title',
                title,
                shape='plaintext',
                fontsize='18',
                fontweight='bold',
                fontcolor='#404040',
                pos="6,2!" 
            )
        
        total_events = len(events)
        
        for i, event in enumerate(events):
            event_id = event.get('id', f'event_{i}')
            event_label = event.get('label', f'Event {i+1}')
            event_date = event.get('date', '')
            event_description = event.get('description', '')
            
            if event_date and event_description:
                full_label = f"{event_date}\\n{event_label}\\n{event_description}"
            elif event_date:
                full_label = f"{event_date}\\n{event_label}"
            elif event_description:
                full_label = f"{event_label}\\n{event_description}"
            else:
                full_label = event_label
            
            lightening_factor = 0.08
            base_r = int(base_color[1:3], 16)
            base_g = int(base_color[3:5], 16)
            base_b = int(base_color[5:7], 16)
            
            current_r = base_r + int((255 - base_r) * i * lightening_factor)
            current_g = base_g + int((255 - base_g) * i * lightening_factor)
            current_b = base_b + int((255 - base_b) * i * lightening_factor)
            
            current_r = min(255, current_r)
            current_g = min(255, current_g)
            current_b = min(255, current_b)
            
            node_color = f'#{current_r:02x}{current_g:02x}{current_b:02x}'
            font_color = 'black'
            
            row = i // events_per_row
            col = i % events_per_row
            
            if row % 2 == 1:
                visual_col = events_per_row - 1 - col
            else:
                visual_col = col
            
            dot.node(
                event_id,
                full_label,
                shape='box',
                style='filled,rounded',
                fillcolor=node_color,
                fontcolor=font_color,
                fontsize='12',
                width='2.5',
                height='1.2',
                pos=f"{visual_col * 4.5},{-row * 3}!"  
            )
        
        for i in range(len(events) - 1):
            current_event_id = events[i].get('id', f'event_{i}')
            next_event_id = events[i + 1].get('id', f'event_{i + 1}')
            
            dot.edge(
                current_event_id,
                next_event_id,
                color='#4a4a4a',
                arrowsize='0.8',
                penwidth='2'
            )
        
        dot.engine = 'neato'

        with NamedTemporaryFile(delete=False, suffix=f'.{output_format}') as tmp:
            dot.render(tmp.name, format=output_format, cleanup=True)
            return f"{tmp.name}.{output_format}"

    except json.JSONDecodeError:
        return "Error: Invalid JSON format"
    except Exception as e:
        return f"Error: {str(e)}"