majiayu000 libagent Skill
When to Use
- Building conversational AI agents with tool capabilities
- Coordinating LLM completions with memory context
- Processing multi-turn conversations with state
- Implementing RAG (retrieval-augmented generation) pipelines
Key Concepts
AgentMind: Core reasoning engine that processes requests through LLM completions, manages conversation state, and coordinates tool execution.
AgentAction: Handles individual tool calls, executes actions, and returns results to the conversation flow.
Usage Patterns
Pattern 1: Basic agent request
import { AgentMind } from "@copilot-ld/libagent";
const mind = new AgentMind(memoryClient, llmClient, toolClient);
const response = await mind.process({
resourceId: conversationId,
content: "What is the weather?",
});
Pattern 2: Streaming responses
for await (const chunk of mind.stream(request)) {
process.stdout.write(chunk.content);
}
Integration
Works with libmemory for context windows, librpc for gRPC clients, and
libllm for completions. Used by the Agent service.