import json
import os
import textwrap
from typing import Annotated, Literal, TypedDict
from langgraph.graph import END, START, StateGraph
from declaw import (
Sandbox,
SecurityPolicy,
PIIConfig,
NetworkPolicy,
AuditConfig,
ALL_TRAFFIC,
)
# --- Mock PHI (one denied case — missing A1c, drives the appeal path) ---
PATIENT = {
"patient_id": "p-003",
"patient_name": "Riya Singh",
"member_id": "MBR-7781432",
"ssn": "512-88-4401",
"email": "riya.singh@example.com",
"phone": "+1-415-555-0188",
"diagnoses": ["severe eosinophilic asthma"],
"medications": ["ICS-LABA (high dose)", "montelukast"],
"a1c": None, # absent → payer denies → appeal drafted
"notes": "Exacerbation in last 12 months despite high-dose ICS-LABA.",
}
POLICY_CRITERIA = [
"severe eosinophilic phenotype confirmed",
"trial on high-dose ICS-LABA with continued symptoms",
"eosinophil count documented",
]
# --- LangGraph state shape ---
class PAState(TypedDict, total=False):
patient_id: str
requested_drug: str
evidence: dict
packet: dict
submission_id: str
status: Literal["pending", "approved", "denied"]
denial_reasons: list[str]
appeal_letter: str
audit_log: Annotated[list[dict], "append-only audit trail"]
# --- Policy factories ---
def untrusted_api_policy(allow_domains: list[str]) -> SecurityPolicy:
"""Outbound call to the payer clearinghouse — third-party untrusted API."""
return SecurityPolicy(
pii=PIIConfig(
enabled=True,
types=["ssn", "email", "phone", "person_name"],
action="redact",
rehydrate_response=False, # we don't trust responses from here
),
network=NetworkPolicy(allow_out=allow_domains, deny_out=[ALL_TRAFFIC]),
audit=AuditConfig(enabled=True),
)
def llm_appeal_policy() -> SecurityPolicy:
"""LLM appeal drafting — PHI redacted outbound, rehydrated inbound."""
return SecurityPolicy(
pii=PIIConfig(
enabled=True,
types=["ssn", "email", "phone", "person_name", "ip_address"],
action="redact",
rehydrate_response=True, # originals restored on response
),
network=NetworkPolicy(
allow_out=["api.openai.com", "pypi.org",
"*.pythonhosted.org", "files.pythonhosted.org"],
deny_out=[ALL_TRAFFIC],
),
audit=AuditConfig(enabled=True),
)
# --- Sandbox 1: untrusted payer submit (python template) ---
PAYER_SCRIPT = textwrap.dedent("""
import json
with open("/tmp/in.json") as f:
packet = json.load(f)
# Mock clearinghouse logic: denies when A1c is missing.
has_a1c = packet.get("evidence", {}).get("a1c") is not None
out = {
"submission_id": "PA-9001",
"status": "approved" if has_a1c else "denied",
"reasons": [] if has_a1c else ["missing_a1c"],
}
with open("/tmp/out.json", "w") as f:
json.dump(out, f)
""")
def submit_to_payer(packet: dict) -> dict:
sbx = Sandbox.create(
template="python",
timeout=120,
security=untrusted_api_policy(["*.payer-clearinghouse.com"]),
)
try:
sbx.files.write("/tmp/in.json", json.dumps(packet))
sbx.files.write("/tmp/payer.py", PAYER_SCRIPT)
r = sbx.commands.run("python3 /tmp/payer.py", timeout=60)
if r.exit_code != 0:
raise RuntimeError(f"payer submit failed: {r.stderr}")
return json.loads(sbx.files.read("/tmp/out.json"))
finally:
sbx.kill()
# --- Sandbox 2: LLM appeal draft (ai-agent template, PII redact+rehydrate) ---
APPEAL_SCRIPT = textwrap.dedent("""
import json
from openai import OpenAI
with open("/tmp/in.json") as f:
inp = json.load(f)
client = OpenAI()
resp = client.chat.completions.create(
model="gpt-4.1",
messages=[
{"role": "system", "content": (
"You are a clinical appeals specialist. Draft a concise, "
"professional prior-authorization appeal letter justifying "
"medical necessity. Cite the specific policy criteria the "
"patient meets. Plain text, no markdown. If you see "
"REDACTED_* tokens, treat them as opaque placeholders for "
"patient identifiers."
)},
{"role": "user", "content": json.dumps(inp)},
],
max_completion_tokens=600,
)
with open("/tmp/out.json", "w") as f:
json.dump({"letter": resp.choices[0].message.content}, f)
""")
def draft_appeal(packet: dict, reasons: list[str]) -> str:
if not os.getenv("OPENAI_API_KEY"):
raise SystemExit("Set OPENAI_API_KEY before running this example.")
sbx = Sandbox.create(
template="ai-agent",
timeout=300,
security=llm_appeal_policy(),
envs={"OPENAI_API_KEY": os.environ["OPENAI_API_KEY"]},
)
try:
sbx.files.write("/tmp/in.json", json.dumps({
"submission_id": packet["submission_id"],
"denial_reasons": reasons,
"packet": packet,
}))
sbx.files.write("/tmp/appeal.py", APPEAL_SCRIPT)
r = sbx.commands.run("python3 /tmp/appeal.py", timeout=240)
if r.exit_code != 0:
raise RuntimeError(f"appeal draft failed: {r.stderr}")
return json.loads(sbx.files.read("/tmp/out.json"))["letter"]
finally:
sbx.kill()
# --- LangGraph nodes ---
def gather(state: PAState) -> PAState:
return {"evidence": PATIENT,
"audit_log": [{"node": "gather"}]}
def assemble_packet(state: PAState) -> PAState:
return {"packet": {
"patient_id": state["patient_id"],
"drug": state["requested_drug"],
"evidence": state["evidence"],
"policy_criteria": POLICY_CRITERIA,
}, "audit_log": [{"node": "assemble_packet"}]}
def submit(state: PAState) -> PAState:
print("[node submit] entering python sandbox (untrusted clearinghouse)")
result = submit_to_payer(state["packet"])
# submit_to_payer returns the submission_id with the packet so the
# appeal-draft node can reference it.
state["packet"]["submission_id"] = result["submission_id"]
return {
"submission_id": result["submission_id"],
"status": result["status"],
"denial_reasons": result["reasons"],
"audit_log": [{"node": "submit", "sandboxed": True,
"result": result["status"]}],
}
def appeal(state: PAState) -> PAState:
print("[node appeal] entering ai-agent sandbox (gpt-4.1, PHI redacted+rehydrated)")
letter = draft_appeal(state["packet"], state["denial_reasons"])
return {"appeal_letter": letter,
"audit_log": [{"node": "appeal", "sandboxed": True,
"model": "gpt-4.1"}]}
def route_after_submit(state: PAState) -> str:
return "appeal" if state["status"] == "denied" else END
def build_graph():
g = StateGraph(PAState)
g.add_node("gather", gather)
g.add_node("assemble_packet", assemble_packet)
g.add_node("submit", submit)
g.add_node("appeal", appeal)
g.add_edge(START, "gather")
g.add_edge("gather", "assemble_packet")
g.add_edge("assemble_packet", "submit")
g.add_conditional_edges("submit", route_after_submit,
{"appeal": "appeal", END: END})
g.add_edge("appeal", END)
return g.compile()
def main() -> None:
graph = build_graph()
result = graph.invoke({
"patient_id": "p-003",
"requested_drug": "mepolizumab",
})
print("\n=== Prior Auth Result ===")
print(f"Patient: {result['patient_id']}")
print(f"Drug: {result['requested_drug']}")
print(f"Submission ID: {result.get('submission_id')}")
print(f"Status: {result.get('status')}")
if result.get("status") == "denied":
print(f"Reasons: {result['denial_reasons']}")
print("\n--- Appeal Letter (gpt-4.1, PHI rehydrated by declaw proxy) ---")
print(result["appeal_letter"])
if __name__ == "__main__":
main()
