Pantheon ($EON)
  • Welcome
  • Welcome to Pantheon (EON)
    • Introduction to Pantheon (EON)
      • What is Pantheon (EON)
      • Vision & Philosophy
    • Why Pantheon?
      • Challenges Addressed to EON
      • Use Cases & Applications
    • Technology Foundations
      • Overview of Key Technologies
      • Comparisons with Traditional AI Architectures
  • The Pantheon (EON) Ecosystem
    • User Journey
      • User Workflow: From Prompt to Project
  • The Pantheon (EON) Core
    • Overview
      • Core Principles
      • End-to-End AI Workflow
    • Distributed AI Registry
    • Orchestrators
      • Task Management and Resource Allocation
      • Project Mining
    • Agents
      • Execution Lifecycle
      • Integration with Tools & Memory Systems
    • Tools
      • Atomic Functionality and Monetization
      • Development and Registration Guidelines
    • Projects
      • Building Projects
      • Security & Configuration
  • The Knowledge Layers
    • Overview
    • Shared Memory
    • Private Memory
  • Data Sources
    • Real-Time Data Ingestion
    • Data Schemas
    • Event Listeners
  • Security Control
    • Access Control
    • Registry Security
    • Data Security
    • Tool Security
  • Development & Contribution
    • Frequently Asked Questions
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On this page
  • Key Features of Projects
  • 1. Dynamic Workflows
  • 2. Composable Design
  • 3. Event-Driven Triggers
  • How Projects Work
  • 1. Definition and Configuration
  • 2. Execution and Monitoring
  • 3. Knowledge Retention
  • Why Projects Are Essential
  • Explore Further
  1. The Pantheon (EON) Core

Projects

Projects are the cornerstone of Pantheon (EON), serving as cohesive workflows that orchestrate tools and agents to deliver scalable, multi-step solutions. By defining tasks, configurations, and data pipelines, Projects enable users to deploy AI-driven solutions tailored to their specific needs. Projects can be simple or hierarchical, supporting everything from small tasks to complex, multi-layered workflows.

Key Features of Projects

1. Dynamic Workflows

Projects are designed as Directed Acyclic Graphs (DAGs), which:

  • Organize tasks into sequential and parallel execution paths.

  • Allow for flexible adjustments based on real-time data or changing requirements.

  • Enable modular reconfiguration without impacting the entire workflow.

This flexibility makes Projects ideal for adapting to evolving scenarios.

2. Composable Design

Projects can integrate:

  • Tools: Atomic functionalities for specific tasks.

  • Agents: Intelligent actors that combine tools and memory for complex operations.

  • Sub-Projects: Nested workflows that function as reusable components.

Composable design ensures scalability and reusability across different use cases.

3. Event-Driven Triggers

Projects can respond to real-time events through:

  • Data Ingestion: Using streams like AWS Kinesis or Kafka to trigger workflows.

  • Dynamic Inputs: Adapting execution based on incoming data or user interactions.

  • Predefined Rules: Executing workflows based on specific conditions or triggers.

This event-driven capability ensures Projects remain responsive and relevant.

How Projects Work

1. Definition and Configuration

Projects are defined using YAML or JSON, specifying:

  • Tasks: Tools and agents to be executed.

  • Data Pipelines: Input/output schemas and data sources.

  • Security: Access credentials and private memory usage.

This structured approach ensures clarity and consistency in project deployment.

2. Execution and Monitoring

Once defined, Projects are executed by the Orchestrator:

  • Task Scheduling: Distributes tasks across clusters for optimal performance.

  • Resource Allocation: Dynamically adjusts resources based on workload demands.

  • Real-Time Monitoring: Tracks execution status and provides logs for debugging.

Monitoring ensures Projects are executed reliably and efficiently.

3. Knowledge Retention

Projects can store valuable insights in memory systems:

  • Shared Memory: Contributes to global knowledge for reuse across workflows.

  • Private Memory: Retains project-specific data for future iterations.

Knowledge retention supports continuous learning and improvement within the ecosystem.

Why Projects Are Essential

Projects provide a structured way to:

  • Integrate tools and agents into cohesive workflows.

  • Scale workflows to handle complex, multi-layered solutions.

  • Adapt to changing data and requirements in real time.

These capabilities make Projects a critical component of Pantheon (EON)’s modular and scalable design.

Explore Further

PreviousDevelopment and Registration GuidelinesNextBuilding Projects

Last updated 3 months ago

Building Projects

Learn how to design and implement workflows using Projects

Security & Configuration

Explore how to secure and configure Projects for scalable deployments