Implements enterprise-grade role-based access control and multi-tenant isolation for LangChain applications.
This skill provides robust patterns for managing security and scalability in LangChain-powered applications, enabling developers to implement granular role-based access control (RBAC), tenant-specific model gating, and strictly isolated vector store retrieval. It offers ready-to-use middleware for FastAPI and Express, usage quota tracking to prevent cost overruns, and comprehensive permission models designed to secure multi-user AI platforms against data leakage and unauthorized model access.
主要功能
011,901 GitHub stars
02Granular Role-Based Access Control (RBAC) with pre-defined permission models
03Multi-tenant isolation for vector stores using strict metadata filtering
04Model access gating to control access to specific LLMs based on user tiers
05Usage quota tracking and enforcement via automated callback handlers
06Middleware integration patterns for both Node.js (Express) and Python (FastAPI)
使用场景
01Building SaaS platforms where multiple organizations share an AI backend with private data
02Restricting premium models like GPT-4o or Claude Sonnet to specific subscription levels
03Enforcing enterprise security compliance by preventing cross-tenant leakage in RAG pipelines
