🔗 AgentNetwork Study Pipeline

A 4-agent P2P learning system built on AgentNetwork mesh

Daemon-1: [Orchestrator] ←→ P2P Mesh ←→ [Knowledge Agent]
Daemon-2: [Quiz Agent]     ←→ P2P Mesh ←→ [Explanation Agent]

git clone <repo>
cp .env.example .env  # add your OpenRouter key
bash start_all.sh

The orchestrator uses anet svc discover to locate available services by skill and anet svc call to invoke them across the mesh. That keeps the agents loosely coupled, so the pipeline can discover and call the right service without hardcoded host routing.

• Orchestrator: receives the user topic, discovers collaborators, and coordinates the study flow.
• Knowledge Agent: retrieves or generates the explanation for the requested topic.
• Quiz Agent: turns the knowledge into multiple-choice questions.
• Explanation Agent: explains why a wrong answer is incorrect and provides a useful tip.

• LLM knowledge retrieval
• MCQ generation
• Wrong answer explanation
• Learning path suggestions
• Animated P2P visualization

#AgentNetwork