# genesis/visualization.py
import networkx as nx
import matplotlib.pyplot as plt
import io
import base64

def _graph_to_image_bytes(G, layout_func=nx.spring_layout):
    """Helper: Convert NetworkX graph to PNG bytes."""
    plt.figure(figsize=(8, 6))
    pos = layout_func(G)
    nx.draw_networkx_nodes(G, pos, node_size=1500, node_color="#34d399", alpha=0.9)
    nx.draw_networkx_edges(G, pos, width=2, alpha=0.5, edge_color="#6b7280")
    nx.draw_networkx_labels(G, pos, font_size=10, font_family="sans-serif", font_color="white")
    plt.axis("off")

    buf = io.BytesIO()
    plt.savefig(buf, format="png", bbox_inches="tight")
    plt.close()
    buf.seek(0)
    return buf

def generate_pathway_graph(entities, relationships):
    """
    Create a pathway relationship graph for synthetic biology concepts.
    entities: list of strings
    relationships: list of dicts {source, target, type}
    Returns: file path to PNG
    """
    G = nx.DiGraph()
    for entity in entities:
        G.add_node(entity)

    for rel in relationships:
        G.add_edge(rel["source"], rel["target"], label=rel["type"])

    buf = _graph_to_image_bytes(G)
    file_path = "/tmp/pathway_graph.png"
    with open(file_path, "wb") as f:
        f.write(buf.read())
    return file_path

def generate_funding_network(companies):
    """
    Create a funding network graph.
    companies: list of dicts {name, investors}
    Returns: file path to PNG
    """
    G = nx.Graph()
    for comp in companies:
        company_node = f"🏢 {comp['name']}"
        G.add_node(company_node)
        investors = [i.strip() for i in comp["investors"].split(",")]
        for inv in investors:
            inv_node = f"💰 {inv}"
            G.add_node(inv_node)
            G.add_edge(company_node, inv_node)

    buf = _graph_to_image_bytes(G, layout_func=nx.kamada_kawai_layout)
    file_path = "/tmp/funding_network.png"
    with open(file_path, "wb") as f:
        f.write(buf.read())
    return file_path