🧬 Copilot-LD

An intelligent agent leveraging GitHub Copilot and Linked Data

Copilot-LD

Traditional RAG systems treat knowledge as plain text, leading to responses based on text similarity rather than actual meaning. Copilot-LD is different: it uses structured linked data to understand relationships and context, delivering responses grounded in your knowledge graph—not just matching keywords.

Key Features

🎯 Amazingly Accurate

Semantic understanding through linked data preserves relationships and context. Content chunks align with meaning, not arbitrary character limits. Dual-index search finds both content and purpose.

⚡️ Incredibly Fast

In-memory vector operations eliminate API latency. Pre-computed embeddings mean zero runtime API cost. Parallel processing and optimized indexes deliver sub-second responses.

🛡️ Robustly Secure

Network-isolated backend services with HMAC authentication. Policy-based access control for all resources. Minimal container images (under 10 MB) reduce attack surface. Time-limited tokens prevent replay attacks.

✨ Elegantly Simple

Plain JavaScript with zero external dependencies beyond Node.js built-ins. No framework complexity or deployment woes. Easy to understand, audit, and operate. Everything in only 6,000 lines of clean code.

What Can You Build?

🚀 Autonomous Agents

Create intelligent agents that autonomously select and execute tools to accomplish complex tasks. The agent analyzes requests, determines which tools to invoke, and chains multiple operations together—all without manual intervention.

🧠 Knowledge Graph Explorers

Navigate organizational knowledge through graph queries that traverse relationships between entities. Discover connections, hierarchies, and dependencies using RDF triple patterns to uncover insights hidden in your data.

🧩 Decision Support Systems

Build systems that combine graph traversal with semantic search to analyze policies, procedures, and relationships. Agents automatically gather relevant information, evaluate constraints, and provide reasoned recommendations.

🎬 Workflow Automation

Deploy agents that understand your processes and autonomously execute multi-step workflows. They query knowledge graphs to understand dependencies, invoke appropriate tools, and adapt to changing conditions.

Getting Started

Get started with our step-by-step guides:

  1. Configuration Guide - Set up environment variables and YAML configuration
  2. Processing Guide - Transform HTML knowledge into searchable resources
  3. Deployment Guide - Launch with Docker Compose or AWS CloudFormation
  4. Development Guide - Run locally with live reloading

Ready to dive deeper?

  1. Concepts – Understand linked data, RAG, and architectural decisions
  2. Architecture – Explore system structure and communication patterns
  3. Reference – Detailed service implementations and package APIs