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ALMAZE: Intelligent Multi-Agent Problem-Solving Ecosystem

ALMAZE Banner

Table of Contents

  1. Introduction
  2. Safety Guidelines
  3. AI Agents
  4. System Architecture
  5. Getting Started
  6. Core Components
  7. Frontend Technologies
  8. Contributing
  9. License

Introduction

ALMAZE is an advanced multi-agent AI system designed to navigate complex problem-solving landscapes. By leveraging specialized agents working in harmony, ALMAZE breaks down intricate challenges and discovers innovative solutions.

Safety Guidelines

To ensure responsible and secure AI interaction:

  • Ethical AI Principles: Prioritize transparency, fairness, and user safety
  • Controlled Environment: Implement strict access controls and monitoring
  • Data Privacy: Protect user information with robust encryption
  • Human Oversight: Maintain human intervention for critical decisions
  • Continuous Validation: Regularly audit agent behaviors and outputs

AI Agents

ALMAZE comprises specialized agents, each with a unique role in solving complex problems:

🧭 Compass (Central Intelligence)

  • Primary Function: Task interpretation and workflow management
  • Analyzes user goals
  • Coordinates agent interactions
  • Guides strategic problem-solving

🏗️ Architect (System Designer)

  • Primary Function: Agent ecosystem management and evolution
  • Creates and refines agent structures
  • Ensures adaptive system capabilities
  • Optimizes agent collaboration frameworks

🔧 Toolsmith (Resource Creator)

  • Primary Function: Developing and maintaining agent tools
  • Crafts specialized resources
  • Enhances agent capabilities
  • Provides necessary instruments for task navigation

🔍 Scout (Knowledge Gatherer)

  • Primary Function: Information exploration and mapping
  • Collects and synthesizes critical data
  • Provides contextual insights
  • Supports informed decision-making

TechSage ( Knowledge Amplifier)

  • Primary Function: Handles tasks related to software development
  • Intelligent Knowledge Mapping
  • Contextual Intelligence
  • Cross-Domain Learning

System Architecture

ALMAZE follows a comprehensive, layered architecture:

  • Backend: Python-based multi-agent system
  • Frontend: React & Next.js web application
  • Authentication: Privy for secure user management
  • Real-time Communication: RestAPIs integration

Getting Started

Prerequisites

Backend Requirements

  • Python 3.8+
  • pip package manager
  • Virtual environment support

Frontend Requirements

  • Node.js 18+
  • npm or yarn
  • Next.js 14
  • React 18+

Backend Installation

# Clone the repository
git clone https://github.com/Almaze-Labs/almaze-api.git
cd almaze-api

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

Frontend Installation

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# Clone the repository
git clone https://github.com/Almaze-Labs/almaze-app.git
cd almaze-app

# Install dependencies
npm install

# Or using yarn
yarn install

# Copy environment template
cp .env.example .env.local

# Fill in required environment variables

Configuration

  1. Configure backend agent parameters
  2. Set up frontend environment variables
  3. Configure authentication providers
  4. Set up database connections

Running the System

Backend

# Basic execution
python app.py

Frontend

# Development mode
npm run dev
# or
yarn dev

# Production build
npm run build
npm run start
# or
yarn build
yarn start

Frontend Technologies

Core Technologies

  • Framework: Next.js 14
  • UI Library: React
  • State Management: Redux Toolkit
  • Authentication: Privy
  • Styling: Tailwind CSS

Key Frontend Features

  • Responsive Design: Mobile and desktop-friendly
  • Real-time Agent Interaction: RestAPIs-powered updates
  • Secure Authentication: Privy-managed user sessions
  • Performance Optimization: Server-side rendering
  • Dynamic Agent Visualization: Interactive agent status and workflow

Authentication Flow

  1. User registers/logs in via Privy
  2. Secure token generation
  3. Role-based access control
  4. Session management

Core Components

  • Multi-Agent Architecture: Collaborative problem-solving ecosystem
  • Dynamic Adaptation: Agents evolve to meet changing challenges
  • Intelligent Coordination: Seamless interaction between specialized agents
  • Flexible Task Management: Advanced workflow optimization

Contributing

We welcome contributions! Help us expand the ALMAZE ecosystem.

Development Setup

# Backend development
cd almaze-api
pip install -r requirements-dev.txt

# Frontend development
cd almaze-app

Contribution Guidelines

  • Follow our Code of Conduct
  • Submit detailed pull requests
  • Maintain clean, documented code
  • Pass all automated tests

License

This project is licensed under the MIT License.

Acknowledgments

  • Inspired by cutting-edge AI research
  • Dedicated to pushing the boundaries of intelligent problem-solving

Disclaimer: ALMAZE is an experimental AI system. Use responsibly and verify critical outputs.

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