LegalView Intelligence Layer
Resolving canonical entity telemetry & graph nodes...
Resolving canonical entity telemetry & graph nodes...
Test real-time statutory RAG endpoints, inspect SHA-256 evidentiary hash certificates, simulate multi-tenant bearer tokens, and generate production client code across 18+ LegalView modules.
Execute conversational RAG queries against Indonesian statutory enactments with verified article citations.
// Awaiting Gateway transmission...
# LegalView Enterprise Python Client (Pydantic / HTTPX)
import httpx
import json
url = "https://app.legalview.id/api/v1/regulations/ai-rag"
headers = {
"Authorization": "Bearer lv_live_89f2d1e0c4a9b7e2f5c8d3a1b0e9f8a7",
"Content-Type": "application/json",
"X-LegalView-Tenant": "SOC2-PROD-GOTO"
}
payload = json.loads('''{}''')
response = httpx.post(url, json=payload, headers=headers, timeout=10.0)
data = response.json()
print(f"Status: {response.status_code} | Engine: {data.get('engine')}")
if "synthesis" in data:
print("\nVerified AI Synthesis:", data["synthesis"]["answer"])
for cite in data["synthesis"].get("citations", []):
print(f" └─ Citation {cite['marker']}: {cite['source']} ({cite['article']})")
else:
print(json.dumps(data, indent=2))