Alone Labs

VAE FRAMEWORK

BY ALONE LABS

Getting Started with Alone Labs

Learn how to build and deploy autonomous AI systems using the Alone Labs framework.

Installation

pip
conda
pip install alone-labs

Quick Start


from alone_labs import Agent

# Initialize AI agent
agent = Agent(
    model="gpt-4",
    security_level="enterprise"
)

# Define autonomous behavior
@agent.task
async def process_data(dataset):
    analysis = await agent.analyze(dataset)
    report = await agent.generate_report(analysis)
    return report

# Deploy with monitoring
deployment = agent.deploy(
    environment="production",
    monitoring=True
)
                    

Architecture

VAE Architecture Overview

Runtime Layer (Rust) Vector Engine Memory System State Manager Agent Layer (TypeScript) Task Manager Context Plugins Network Layer (Go) API Gateway Load Balancer Service Mesh

Three-layer architecture of the VAE framework

VAE Development Roadmap

Tracking the evolution of autonomous vector-based AI

In Development

Phase 1: Core Architecture

Q1 2025

Vector Processing Engine

75%
  • Advanced SIMD optimization
  • Memory alignment system
  • Cache optimization layer
  • Distributed compute support

Neural Architecture

60%
  • Core neural engine
  • State management system
  • Advanced tensor operations
  • Multi-model integration

Memory Systems

40%
  • KV cache implementation
  • Hierarchical memory model
  • Advanced garbage collection
  • Memory prediction system
Planned

Phase 2: Advanced Features

Q2 2025

Autonomous Systems

  • Self-optimization engine
  • Adaptive learning system
  • Resource management AI
  • Autonomous scaling

Plugin Architecture

  • Core plugin system
  • Security sandbox
  • Plugin marketplace
  • Version management