neomjs/neo
Neo
Neo is an autonomous engineering platform and multi-agent orchestration framework designed to build, review, and maintain production codebases. It coordinates a swarm of multiple language models through a messaging and event system to automate complex software development workflows without manual intervention.
The platform utilizes a semantic knowledge graph manager to distill session logs and documentation into a queryable topology, preserving project history and context across AI interactions. It supports multi-tenant deployment of agent swarms that employ persistent memory and structured markdown documentation to maintain consistency across tasks.
Additional capabilities include a real-time application state mutator for patching methods within a running memory heap and a shared-worker state orchestrator to synchronize a single application instance across multiple browser windows. The system isolates application logic and state management in dedicated worker threads to prevent main-thread freezes.
Features
- Autonomous Software Engineering - Coordinates multiple language models to autonomously develop, review, and maintain production codebases.
- Agent Swarms - Coordinates a swarm of multiple language models through a messaging and event system to autonomously maintain codebases.
- Agent Memory Persistence - Provides autonomous agents with long-term storage and structured documentation to maintain consistency across different tasks.
- Multi-Agent Orchestration Frameworks - Provides a framework for coordinating communication and event triggers between specialized AI agents.
- AI Agent State Coordination - Manages messaging and wake events between AI maintainers to automate complex software development workflows.
- Autonomous Software Engineering - Automates the complete software development lifecycle using a coordinated swarm of multiple language models.
- Knowledge Graphs - Utilizes a semantic knowledge graph to distill session logs and documentation into a queryable topology for AI context.
- Knowledge Graph Builders - Transforms session logs into a queryable semantic topology to preserve project history and context for AI agents.
- Session Log Distillers - Distills session logs and documentation into a queryable semantic topology to preserve project history for AI models.
- Knowledge Graph Management - Manages interconnected project history as a semantic knowledge graph to provide context for LLMs.
- Autonomous Codebase Managers - Coordinates a swarm of language models to autonomously write, review, and maintain production codebases.
- Multi-Tenant Deployments - Launches multi-tenant swarms of models that autonomously build and maintain codebases using persistent memory.
- Knowledge Base Management - Stores and retrieves markdown documentation to provide a structured, versioned information source for automated agents.
- Heap Mutations - Updates application configurations in real time by inspecting component trees and patching methods within the running memory heap.
- Runtime State Mutators - Implements a real-time mutator for patching methods and configurations directly within the running application heap.
- Multi-Tenant Agent Deployment - Launches and manages isolated instances of AI engineering teams for multiple tenants to maintain diverse codebases.
- Event Messaging Systems - Implements a shared messaging and event system to coordinate communication between members of an AI agent swarm.
- Live Heap Patching - Inspects component trees and patches methods to update configurations within a running application heap in real time.
- Miscellaneous Tools - Web worker-based UI framework.
Star history
How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
