Update synoptic_chart_generator.py
Browse files- synoptic_chart_generator.py +17 -55
synoptic_chart_generator.py
CHANGED
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@@ -4,13 +4,18 @@ from tempfile import NamedTemporaryFile
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import os
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from graph_generator_utils import add_nodes_and_edges
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def generate_synoptic_chart(json_input: str) -> str:
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"""
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Generates a synoptic chart (horizontal flowchart) from JSON input.
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Args:
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json_input (str): A JSON string describing the synoptic chart structure.
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It must follow the Expected JSON Format Example below.
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Expected JSON Format Example:
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{
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@@ -19,24 +24,15 @@ def generate_synoptic_chart(json_input: str) -> str:
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{
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"id": "phase1",
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"label": "I. Problem Definition & Data Acquisition",
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"relationship": "Starts
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"subnodes": [
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{
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"id": "sub1_1",
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"label": "1. Problem Formulation",
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"relationship": "Involves",
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"subnodes": [
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{"id": "sub1_1_1", "label": "1.1. Identify Business Need", "relationship": "e.g."},
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{"id": "sub1_1_2", "label": "1.2. Define KPIs", "relationship": "e.g."}
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]
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},
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{
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"id": "sub1_2",
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"label": "2. Data Collection",
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"relationship": "Followed by",
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"subnodes": [
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{"id": "
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{"id": "
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]
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}
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]
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@@ -44,58 +40,20 @@ def generate_synoptic_chart(json_input: str) -> str:
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{
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"id": "phase2",
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"label": "II. Model Development",
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"relationship": "Proceeds
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"subnodes": [
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{
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"id": "sub2_1",
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"label": "1. Feature Engineering",
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"relationship": "Comprises",
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"subnodes": [
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{"id": "sub2_1_1", "label": "1.1. Feature Selection", "relationship": "e.g."},
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{"id": "sub2_1_2", "label": "1.2. Feature Transformation", "relationship": "e.g."}
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]
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},
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{
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"id": "sub2_2",
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"label": "2. Model Training",
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"relationship": "Involves",
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"subnodes": [
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{"id": "sub2_2_1", "label": "2.1. Algorithm Selection", "relationship": "uses"},
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{"id": "sub2_2_2", "label": "2.2. Hyperparameter Tuning", "relationship": "optimizes"}
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]
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}
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]
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},
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{
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"id": "phase3",
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"label": "III. Evaluation & Deployment",
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"relationship": "Culminates in",
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"subnodes": [
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{
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"id": "sub3_1",
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"label": "1. Model Evaluation",
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"relationship": "Includes",
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"subnodes": [
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{"id": "sub3_1_1", "label": "1.1. Performance Metrics", "relationship": "measures"},
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{"id": "sub3_1_2", "label": "1.2. Bias & Fairness Audits", "relationship": "ensures"}
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]
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},
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{
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"id": "sub3_2",
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"label": "2. Deployment & Monitoring",
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"relationship": "Requires",
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"subnodes": [
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{"id": "
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{"id": "sub3_2_2", "label": "2.2. Continuous Monitoring", "relationship": "ensures"}
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]
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}
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]
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}
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]
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}
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Returns:
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str: The filepath to the generated PNG image file.
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"""
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try:
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if not json_input.strip():
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@@ -119,6 +77,10 @@ def generate_synoptic_chart(json_input: str) -> str:
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}
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)
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base_color = '#19191a' # Base color for the central node and gradient
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# Central node styling (rounded box, dark color)
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import os
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from graph_generator_utils import add_nodes_and_edges
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def generate_synoptic_chart(json_input: str, base_color: str) -> str:
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"""
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Generates a synoptic chart (horizontal flowchart) from JSON input.
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Args:
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json_input (str): A JSON string describing the synoptic chart structure.
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It must follow the Expected JSON Format Example below.
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base_color (str): The hexadecimal color string (e.g., '#19191a') for the base
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color of the nodes, from which a gradient will be generated.
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Returns:
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str: The filepath to the generated PNG image file.
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Expected JSON Format Example:
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{
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{
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"id": "phase1",
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"label": "I. Problem Definition & Data Acquisition",
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"relationship": "Starts\\nwith",
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"subnodes": [
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{
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"id": "sub1_1",
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"label": "1. Problem Formulation",
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"relationship": "Involves\\n(Steps)",
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"subnodes": [
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{"id": "sub1_1_1", "label": "1.1. Identify Business Need", "relationship": "e.g.\\n(Need)"},
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{"id": "sub1_1_2", "label": "1.2. Define KPIs", "relationship": "e.g.\\n(Metrics)"}
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]
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}
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]
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{
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"id": "phase2",
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"label": "II. Model Development",
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"relationship": "Proceeds\\nto",
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"subnodes": [
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{
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"id": "sub2_1",
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"label": "1. Feature Engineering",
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"relationship": "Comprises\\n(Features)",
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"subnodes": [
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{"id": "sub2_1_1", "label": "1.1. Feature Selection", "relationship": "e.g.\\n(Select)"}
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]
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}
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]
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}
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]
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}
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"""
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try:
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if not json_input.strip():
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}
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)
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# Ensure base_color is valid, fallback if not
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if not isinstance(base_color, str) or not base_color.startswith('#') or len(base_color) != 7:
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base_color = '#19191a' # Fallback to default dark if invalid
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base_color = '#19191a' # Base color for the central node and gradient
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# Central node styling (rounded box, dark color)
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