majiayu000 libmemory Skill
When to Use
- Building context windows for LLM calls
- Managing conversation history with token limits
- Constructing prompts from messages and tools
- Optimizing context for model token budgets
Key Concepts
WindowBuilder: Constructs context windows by selecting messages and tools that fit within token budget.
MemoryIndex: Stores conversation message identifiers for retrieval.
Token budgeting: Allocates tokens across system prompt, history, and tools.
Usage Patterns
Pattern 1: Build context window
import { WindowBuilder } from "@copilot-ld/libmemory";
const builder = new WindowBuilder(tokenizer);
const window = await builder.build({
messages: conversationHistory,
tools: availableTools,
budget: 4000,
});
Pattern 2: Factory usage
import { createWindow } from "@copilot-ld/libmemory";
const window = await createWindow(resourceId, {
maxTokens: 4000,
systemPrompt: "You are a helpful assistant.",
});
Integration
Used by Memory service and Agent service. Works with libllm for token counting.