Update genesis/safety.py

genesis/safety.py

@@ -1,58 +1,20 @@
-# genesis/visualization.py
+# genesis/safety.py
 """
-Visualization tools for GENESIS-AI
-Uses Neo4j to query and build graphs.
+Biosecurity & Safety Analysis for GENESIS-AI
+Checks biosecurity risks using NSABB guidelines + BWC frameworks.
 """
 
-import os
-import networkx as nx
-import matplotlib.pyplot as plt
-from py2neo import Graph
+import re
 
-NEO4J_URI = os.getenv("NEO4J_URI")
-NEO4J_USER = os.getenv("NEO4J_USER")
-NEO4J_PASSWORD = os.getenv("NEO4J_PASSWORD")
+DUAL_USE_KEYWORDS = [
+    "pathogen", "toxin", "gain of function", "bioweapon",
+    "select agent", "lethal", "infectious dose", "virulence"
+]
 
-graph_db = Graph(NEO4J_URI, auth=(NEO4J_USER, NEO4J_PASSWORD))
-
-def generate_pathway_graph(pathway_name):
-    """Generate a metabolic pathway graph from Neo4j data."""
-    query = f"""
-    MATCH (p:Pathway {{name: '{pathway_name}'}})-[r:INVOLVES]->(m:Molecule)
-    RETURN p, r, m
+def assess_biosecurity_risk(text):
     """
-    data = graph_db.run(query).data()
-    G = nx.Graph()
-    for record in data:
-        p_name = record["p"]["name"]
-        m_name = record["m"]["name"]
-        G.add_node(p_name, color="green")
-        G.add_node(m_name, color="orange")
-        G.add_edge(p_name, m_name)
-    return draw_graph(G)
-
-def generate_funding_network(company_name):
-    """Generate company-investor funding network."""
-    query = f"""
-    MATCH (c:Company {{name: '{company_name}'}})-[r:FUNDED_BY]->(i:Investor)
-    RETURN c, r, i
+    Returns a biosecurity risk score (0–10) and flagged terms.
     """
-    data = graph_db.run(query).data()
-    G = nx.Graph()
-    for record in data:
-        c_name = record["c"]["name"]
-        i_name = record["i"]["name"]
-        G.add_node(c_name, color="green")
-        G.add_node(i_name, color="blue")
-        G.add_edge(c_name, i_name)
-    return draw_graph(G)
-
-def draw_graph(G):
-    """Draw networkx graph as PNG."""
-    pos = nx.spring_layout(G)
-    colors = [d.get("color", "grey") for _, d in G.nodes(data=True)]
-    plt.figure(figsize=(8, 6))
-    nx.draw(G, pos, with_labels=True, node_color=colors, node_size=1500, font_size=10)
-    plt.savefig("graph.png")
-    plt.close()
-    return "graph.png"
+    flagged = [kw for kw in DUAL_USE_KEYWORDS if re.search(rf"\b{kw}\b", text, re.IGNORECASE)]
+    score = min(10, len(flagged) * 2)
+    return {"risk_score": score, "flagged_terms": flagged}