LangChain Enterprise RBAC

Contents

• Overview
• Prerequisites
• Instructions
• Output
• Error Handling
• Examples
• Resources

Overview

Implement role-based access control (RBAC) for LangChain applications with multi-tenant support, model access control, and usage quotas.

Prerequisites

• LangChain application with user authentication
• Identity provider (Auth0, Okta, Azure AD)
• Understanding of RBAC concepts

Instructions

Step 1: Define Permission Model

Create Permission enum with chain, model, feature, and admin permissions. Define roles (viewer, user, power_user, admin) mapping to permission sets.

Step 2: Implement User and Tenant Management

Create Tenant and User models with role-based permission resolution. Users belong to tenants with monthly token limits.

Step 3: Enforce Permissions

Build PermissionChecker with FastAPI decorators (@require_permission) that validate user permissions before chain execution.

Step 4: Control Model Access

Implement ModelAccessController that restricts LLM model access based on user permissions and tenant restrictions.

Step 5: Isolate Tenants

Use context variables (ContextVar) for tenant isolation. Implement TenantScopedVectorStore that filters by tenant ID.

Step 6: Manage Usage Quotas

Build UsageQuotaManager tracking per-tenant token usage with monthly resets and reporting.

See detailed implementation for complete RBAC code.

Output

• Permission model with roles
• User and tenant management
• Model access control
• Tenant isolation
• Usage quotas

Error Handling

Examples

Basic usage: Apply langchain enterprise rbac to a standard project setup with default configuration options.

Advanced scenario: Customize langchain enterprise rbac for production environments with multiple constraints and team-specific requirements.

Resources

• RBAC Best Practices
• Multi-Tenant Architecture
• OAuth 2.0 Scopes

Next Steps

Use langchain-data-handling for data privacy controls.