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threadline-sdk
Advanced tools
Persistent memory and context layer for AI agents. inject() before your LLM call, update() after. Works with OpenAI, Anthropic, Vercel AI SDK, and LangChain.
The persistent context layer for AI agents.
Every agent you build starts from zero. Threadline changes that.
npm install threadline-sdk
import { Threadline } from "threadline-sdk"
const tl = new Threadline({ apiKey: process.env.THREADLINE_KEY })
// Before your AI call — inject user context
const { injectedPrompt, cacheHint } = await tl.inject(userId, "You are a helpful assistant.")
// After your AI call — update user context
await tl.update({ userId, userMessage, agentResponse })
That's it. Your agent now remembers every user, across every session.
Think of it like OAuth — but for context. You don't build auth from scratch. You shouldn't build memory from scratch either.
tl.inject(userId, basePrompt)Returns { injectedPrompt, cacheHint? }. Use injectedPrompt as your system message. When cacheHint.recommended is true, pass cacheHint.openaiParam as extra_body on supported OpenAI models for 24h prompt cache retention (~50% lower cached input token cost).
tl.update({ userId, userMessage, agentResponse })Extracts and stores context updates from a conversation turn.
FAQs
Persistent memory and context layer for AI agents. inject() before your LLM call, update() after. Works with OpenAI, Anthropic, Vercel AI SDK, and LangChain.
We found that threadline-sdk demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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