Platform Architecture & Core Components

Prometheus Swarm employs a sophisticated multi-agent architecture, inspired by industrial assembly lines and powered by a decentralized network. This design allows for efficient, scalable, and reliable software development.

• Overall Architecture: At its core, Prometheus Swarm orchestrates a flow of specialized AI agents:
  1. A Planner Agent (often leveraging a powerful model like GPT-4) ingests user requirements (from natural language descriptions, design meeting transcripts, etc.) and breaks the project down into a detailed plan with narrowly-scoped tasks and modules. Emphasis is placed on identifying all components and potential ambiguities upfront.
  2. These scoped tasks are distributed to a swarm of Builder Agents. Each builder agent is responsible for coding a specific module or feature in isolation, often in parallel with other builder agents (horizontal scaling).
  3. Once modules are written, Tester Agents (including “Red Team” or “Red Hat” agents) take over. They pull the entire repository, deploy the application in a sandbox environment, and write/execute test scripts to find logical flaws, security vulnerabilities, or integration issues. These agents often use different perspectives or AI models to catch a wider range of problems.
  4. An Architect/Optimizer Agent reviews the assembled project holistically after modules pass tests. It looks for redundancies, opportunities for refactoring, and ensures all components integrate seamlessly. This entire process is version-controlled using Git, with agents often committing to separate branches and creating pull requests for review (by other agents or human overseers).
• Core Software Components: Key modules within the Prometheus Swarm ecosystem (many available in the Prometheus-Swarm GitHub organization) include:
  • Prometheus Swarm (Core Framework): This is the central orchestration engine. It manages agent workflows, state, context, and integrates with various AI models (e.g., GPT-4, Claude). It provides type-safe interfaces for code generation and ensures agents work together effectively. (Likely found in PrometheusMonorepo or a core prometheus-swarm repository).
  • Prometheus Test Framework: A dedicated framework that ensures rigorous testing is embedded in the development lifecycle. It manages test execution, worker (agent) allocation for testing tasks, and reporting. This underpins the “test early and often” principle of the swarm. (Potentially in a prometheus-test repository).
  • Knowledge Integration (KNO SDK & .kno files): Prometheus utilizes an innovative system for managing context and knowledge through embeddings. Project requirements, existing code, and documentation are converted into vector embeddings (often stored in .kno folders within the repository). Agents load these embeddings to gain relevant context for their specific tasks, minimizing hallucinations and reducing the need for large prompt sizes. The kno-sdk likely provides tools to create, manage, and query these knowledge embeddings.
  • Agent Libraries & Specializations: The swarm consists of various specialized agents, often maintained in their own repositories or modules. Examples include:
    • feature-builder: Agents focused on writing new features and associated documentation.
    • bug-finder: Agents dedicated to static analysis and identifying bugs or security vulnerabilities.
    • docs-summarizer / Documentation Agent: Agents responsible for generating and maintaining comprehensive documentation. Each agent type may employ different AI models or fine-tuned strategies best suited for its role.
• Decentralized Hosting (Koii Network): The computational power for Prometheus Swarm is provided by the Koii Network, a decentralized network of community-run nodes (potentially over 100,000). Tasks from the Prometheus Swarm (like running an AI model for code generation or executing a test suite) are distributed to these nodes. This decentralized approach offers:
  • Scalability: A vast pool of compute resources for parallel execution.
  • Resilience: No single point of failure.
  • Cost-Efficiency: Leverages a marketplace of compute providers, with incentives often paid in various tokens. Koii’s infrastructure (sometimes referred to as Cloud2) enables even consumer-grade devices to contribute to this distributed supercomputer.

• Diagram/Visualization: (Consider adding an architectural diagram here showing the flow: User Input -> Planner Agent -> Parallel Builder Agents (each with .kno context) -> Tester Agents -> Architect/Optimizer Agent -> Git Repository Output, all running on the Koii Decentralized Network.)

• References: For deeper technical dives, explore the PrometheusMonorepo and other repositories within the Prometheus-Swarm GitHub organization.