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MedGuard
MedGuard is a robust, production-grade Python library that ensures HIPAA compliance for large language model (LLM) agents. Designed for enterprise applications in healthcare, MedGuard provides comprehensive security, privacy, and compliance frameworks that integrate seamlessly into your AI-driven workflows.
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README preview
MedGuard
MedGuard is a robust, production-grade Python library that ensures HIPAA compliance for large language model (LLM) agents. Designed for enterprise applications in healthcare, MedGuard provides comprehensive security, privacy, and compliance frameworks that integrate seamlessly into your AI-driven workflows. The library guarantees that your AI models and agents operate within strict regulatory boundaries, particularly the Health Insurance Portability and Accountability Act (HIPAA), ensuring the protection of sensitive health data.
Key Features
HIPAA-Compliant Workflows: Ensures that LLM agents handle Protected Health Information (PHI) securely and within HIPAA guidelines.
End-to-End Encryption: Provides automatic encryption for data in transit and at rest to protect sensitive health data.
Audit Logging: Tracks all agent interactions, data access, and usage patterns for auditing and compliance reporting.
Role-Based Access Control (RBAC): Fine-grained control over who can access and interact with specific data points within the system.
Data Anonymization and Masking: Automatically anonymizes or masks PHI when shared, minimizing the risk of data breaches.
Seamless Integration: Designed to integrate with popular AI/LLM libraries such as OpenAI, Hugging Face, and custom LLM architectures.
Configurable Policies: Allows for the customization of compliance policies and controls according to specific organizational needs.
Scalable Infrastructure: Built to support enterprise-level deployments, capable of scaling across cloud, hybrid, and on-premise environments.
Comprehensive Testing Suite: Includes unit tests, integration tests, and compliance checks to ensure secure and reliable operations.
Installation
To install MedGuard, use the following pip command:
pip3 install -U medguard
Quick Start
Here’s a quick guide to get MedGuard up and running in your environment:
1. Setting Up Your MedGuard Environment
from medguard import MedGuard
# Initialize MedGuard with your organization's compliance configuration
medguard = MedGuard(api_key="your_api_key",
encryption_key="your_encryption_key",
compliance_level="HIPAA")
2. Integrating MedGuard with Your LLM Agent
from your_llm_library import YourLLMAgent
# Create an instance of your LLM agent
llm_agent = YourLLMAgent()
# Wrap the LLM agent with MedGuard for HIPAA compliance
compliant_agent = medguard.wrap_agent(llm_agent)
# Use the compliant agent to ensure all communications adhere to HIPAA guidelines
response = compliant_agent.process("Analyze this patient's health record and recommend treatment.")
3. Anonymizing Sensitive Data
# Automatically anonymize sensitive data in the agent's output
anonymized_output = medguard.anonymize(response)
4. Logging and Auditing
# Log and audit all interactions for compliance review
medguard.audit.log_interaction(agent_id="1234", user_id="5678", input_data="Patient data", output_data=response)
Enterprise Features
Role-Based Access Control (RBAC)
MedGuard supports advanced role-based access to ensure only authorized users and systems can access PHI.
# Define roles and permissions
medguard.set_role("doctor", permissions=["read", "write"])
medguard.set_role("nurse", permissions=["read"])
Audit and Compliance Reporting
MedGuard provides detailed audit logs and compliance reports, ensuring that your AI systems remain transparent and fully auditable.
