Compliance & Auditing - LangChain in Production

Learn how to ensure compliance, enable auditing, and meet regulatory requirements for LangChain applications

🏛️ Compliance Overview

LangChain applications may be subject to regulations (GDPR, HIPAA, SOC2, etc.). This guide covers compliance strategies, auditing patterns, and data governance for production systems.

---

📋 Regulatory Frameworks

• GDPR: Data privacy, user consent, right to be forgotten
• HIPAA: Healthcare data protection
• SOC2: Security, availability, processing integrity, confidentiality, privacy

---

🧑‍💻 Auditing Patterns

• Log all access, changes, and data flows
• Use immutable audit logs (blockchain, append-only storage)
• Automate audit report generation

---

🛡️ Data Governance

• Define data ownership and stewardship
• Enforce data retention and deletion policies
• Monitor for unauthorized access and data leaks

---

🧩 Example: Audit Logging Middleware

from fastapi import FastAPI, Request
import logging

app = FastAPI()
logger = logging.getLogger("audit")

@app.middleware("http")
async def audit_middleware(request: Request, call_next):
    logger.info(f"Access: {request.method} {request.url}")
    response = await call_next(request)
    return response

---

🔗 Next Steps

• Data Privacy
• Governance Patterns
• Model Evaluation

---

Key Compliance Takeaways:

• Understand and map regulatory requirements
• Log and audit all access and changes
• Automate compliance reporting
• Govern data ownership and retention
• Continuously monitor for compliance gaps