The Fine Print

import json
from typing import TypedDict, Dict, Any
from langgraph.graph import StateGraph, END
from langchain_openai import ChatOpenAI
class ISOCheckState(TypedDict):
    resource_id: str
    telemetry_data: Dict[str, Any]
    asset_context: Dict[str, Any]
    iso_control: str
    is_compliant: bool
    audit_notes: str
llm = ChatOpenAI(model="gpt-4o", temperature=0)
def ingest_telemetry(state: ISOCheckState) -> dict:
    return {"resource_id": "bucket-public-cdn"}
def query_asset_registry(state: ISOCheckState) -> dict:
    return {"asset_context": {"purpose": "static-website-hosting"}}
def evaluate_compliance(state: ISOCheckState) -> dict:
    prompt = f"""
Evaluate ISO 27001 Control A.8.12 (Data Leakage Prevention).
Telemetry: {json.dumps(state['telemetry_data'])}
Asset Context: {json.dumps(state['asset_context'])}
Is this configuration compliant? Answer with JSON containing 'compliant' (boolean) and 'reason' (string).
"""
    res = llm.invoke(prompt)
    is_comp = "true" in res.content.lower() and "non-compliant" not in res.content.lower()
    return {"is_compliant": is_comp, "audit_notes": res.content}
workflow = StateGraph(ISOCheckState)
workflow.add_node("ingest", ingest_telemetry)
workflow.add_node("cmdb", query_asset_registry)
workflow.add_node("eval", evaluate_compliance)
workflow.set_entry_point("ingest")
workflow.add_edge("ingest", "cmdb")
workflow.add_edge("cmdb", "eval")
workflow.add_edge("eval", END)
app = workflow.compile()
if __name__ == "__main__":
    res = app.invoke({
        "resource_id": "bucket-public-cdn",
        "telemetry_data": {},
        "asset_context": {},
        "iso_control": "A.8.12",
        "is_compliant": False,
        "audit_notes": ""
    })
    print(f"Compliant: {res['is_compliant']}\nNotes: {res['audit_notes']}")