gatecraft 0.1.0

A semantic RBAC system with RAG capabilities

Gatecraft

Gatecraft is a semantic Role-Based Access Control (RBAC) system with Retrieval-Augmented Generation (RAG) capabilities. It provides a flexible way to manage access control based on semantic similarity and content understanding.

Features

• Semantic-based access control
• Integration with OpenAI embeddings
• Pinecone vector store support
• Flexible RBAC system
• RAG capabilities

Installation

pip install gatecraft

Quick Start

from gatecraft.core.user import User


from gatecraft.core.role import Role


from gatecraft.core.permission import Permission


from gatecraft.utils.semantic_condition import SemanticCondition


from gatecraft.core.entity import Entity


from gatecraft.core.policy import AccessControlPolicy


from gatecraft.db.semantic_database import SemanticDatabase


from gatecraft.db.pinecone_vector_store import PineconeVectorStore





# Initialize vector store


vector_store = PineconeVectorStore(


**    **api_key="your-pinecone-api-key",


**    **environment="your-environment",


**    **index_name="your-index-name"


)





# Create semantic database


semantic_db = SemanticDatabase(vector_store)





# Create policy


policy = AccessControlPolicy(database=semantic_db)





# Create users and roles


user = User(user_id=1, name="Alice")


role = Role(role_id=1, name="Cat Lover")


permission = Permission(permission_id=1, name="Access Cat Content")





# Add semantic condition


condition = SemanticCondition(term="cat", threshold=0.8)


permission.add_condition(condition)





# Set up relationships


role.add_permission(permission)


user.add_role(role)





# Check access


entity = Entity(entity_id=1, data="A cute kitten playing with yarn")


has_access = policy.is_access_allowed(user, entity)