import graphviz
import json
from tempfile import NamedTemporaryFile
import os
from graph_generator_utils import add_nodes_and_edges # Reusing common utility

def generate_process_flow_diagram(json_input: str, base_color: str) -> str:
    """
    Generates a Process Flow Diagram (Flowchart) from JSON input.

    Args:
        json_input (str): A JSON string describing the process flow structure.
                          It must follow the Expected JSON Format Example below.
        base_color (str): The hexadecimal color string (e.g., '#19191a') for the base
                          color of the nodes, from which a gradient will be generated.

    Returns:
        str: The filepath to the generated PNG image file.

    Expected JSON Format Example:
    {
      "start_node": "Start Process",
      "nodes": [
        {
          "id": "step1",
          "label": "Gather Requirements",
          "type": "process",
          "relationship": "Next",
          "subnodes": [
            {"id": "step1_1", "label": "Define Scope", "type": "process", "relationship": "Then"}
          ]
        },
        {
          "id": "decision1",
          "label": "Is Data Available?",
          "type": "decision",
          "relationship": "Check",
          "subnodes": [
            {"id": "path_yes", "label": "Process Data", "type": "process", "relationship": "Yes"},
            {"id": "path_no", "label": "Collect More Data", "type": "process", "relationship": "No"}
          ]
        },
        {
          "id": "end_node",
          "label": "End Process",
          "type": "end",
          "relationship": "Concludes"
        }
      ],
      "connections": [
        {"from": "start_node", "to": "step1"},
        {"from": "step1", "to": "decision1"},
        {"from": "decision1", "to": "path_yes", "label": "Yes"},
        {"from": "decision1", "to": "path_no", "label": "No"},
        {"from": "path_yes", "to": "end_node"},
        {"from": "path_no", "to": "end_node"}
      ]
    }
    """
    try:
        if not json_input.strip():
            return "Error: Empty input"
            
        data = json.loads(json_input)
        
        # Determine specific node shapes for flowchart types
        node_shapes = {
            "process": "box",
            "decision": "diamond",
            "start": "Mrecord", # Rounded box for start/end
            "end": "Mrecord",    # Rounded box for start/end
            "io": "parallelogram", # Input/Output
            "document": "note",
            "default": "box"
        }

        dot = graphviz.Digraph(
            name='ProcessFlowDiagram',
            format='png',
            graph_attr={
                'rankdir': 'TB',        # Top-to-Bottom flow is common for flowcharts
                'splines': 'ortho',     # Straight lines with 90-degree bends
                'bgcolor': 'white',     # White background
                'pad': '0.5'            # Padding around the graph
            },
            node_attr={'style': 'filled,rounded', 'fontcolor': 'white', 'fontsize': '12'} # Default node style
        )
        
        # Add all nodes based on JSON structure
        all_nodes = {}
        if 'start_node' in data:
            all_nodes[data['start_node']] = {"label": data['start_node'], "type": "start"}
        
        for node_data in data.get('nodes', []):
            all_nodes[node_data['id']] = node_data

        # Add nodes with specific shapes and styles
        for node_id, node_info in all_nodes.items():
            node_type = node_info.get("type", "default")
            shape = node_shapes.get(node_type, "box") # Default to box if type is unknown

            # Calculate color for current node based on a simplified depth or fixed for process flow
            # For simplicity in process flow, let's keep the base color for all primary nodes for now,
            # or apply a subtle gradient if depth is truly defined in a meaningful way.
            # Here, we'll use the base_color for all nodes, making the color selection more direct.
            
            # Simple color lightening for sub-levels if 'subnodes' are used in a nested process
            # This logic mimics graph_generator_utils but is adapted for the specific flow structure
            # For a pure flowchart, often nodes are all the same color.
            # If you want gradient for subprocesses, the current_depth logic needs to be more robust for different node types.
            
            # Let's use base_color directly for all main nodes and only apply gradient for 'subnodes'
            # For now, we'll pass current_depth=0 to add_nodes_and_edges when called recursively
            # to ensure the main flow nodes are consistent.

            dot.node(
                node_id,
                node_info['label'],
                shape=shape,
                style='filled,rounded',
                fillcolor=base_color, # Use the selected base color
                fontcolor='white' if base_color == '#19191a' else 'black', # Adjust for readability
                fontsize='14'
            )

        # Add connections (edges)
        for connection in data.get('connections', []):
            dot.edge(
                connection['from'],
                connection['to'],
                label=connection.get('label', ''),
                color='#4a4a4a', # Dark gray for lines
                fontcolor='#4a4a4a',
                fontsize='10'
            )
        
        # If there's a start_node, ensure it's visually marked
        if 'start_node' in data:
            dot.node(data['start_node'], data['start_node'], shape=node_shapes['start'], style='filled,rounded', fillcolor='#2196F3', fontcolor='white', fontsize='14')
        if 'end_node' in data and data['end_node'] in all_nodes:
             dot.node(data['end_node'], all_nodes[data['end_node']]['label'], shape=node_shapes['end'], style='filled,rounded', fillcolor='#F44336', fontcolor='white', fontsize='14')


        # 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)}"