Overview

Threadless AI is hosted memory for AI agents. Before every model call, your agent hands over what is new in the conversation and gets back the request ready to submit to OpenAI. After the reply, it reports the reply. That is the whole integration.

Between those calls we keep the conversation's history in proportion. Old episodes leave the model's view when they matter least, their facts stay behind, and recall brings them back when the conversation turns to them. The model you call, the key you call it with and your agent loop stay yours.

The three calls

1. decorate, before every model call: send what is new since the last call, get back the full request body.
2. Submit the request to OpenAI with your own key, exactly as you do now.
3. report, after the reply: hand over the response. It returns at once and the work runs in the background.

Add the note tool to your tools once. When episodes are leaving the model's view, the request asks the model to write their facts with it; your handler answers noted and nothing else.

Where to start

• Quickstart: a working loop in TypeScript or Python, for Chat Completions or Responses.
• The three calls: decorate, report and the note tool in detail.
• Memory ids: one memory per conversation.
• Concepts: episodes, traces, activation, fading, sleep and recall.
• API reference: the HTTP API, if you are not using an SDK.

If you are an agent setting this up, read /setup.md and follow it step by step. Every docs page is also served as markdown at its path plus .md, and /llms.txt indexes them.

SDKs

Both are thin clients over the runtime API at https://api.threadlessai.com/v1. Each surface (chat for Chat Completions, responses for Responses) has decorate, report and the note tool.