@sisu-ai/mw-conversation-buffer

Helpers for shaping basic conversation state. Keep recent messages small and relevant without implementing your own trimming logic.

Setup

npm i @sisu-ai/mw-conversation-buffer

Exports

• inputToMessage — appends { role:'user', content: ctx.input } when present.
• conversationBuffer({ window=12 }) — keeps the first message and the last window messages.

What It Does

• Converts ctx.input into a user chat message.
• Prunes older messages with a simple, fast sliding window.

This pair is intentionally tiny and deterministic. It never summarizes or alters message contents — it only appends and trims.

How It Works

• inputToMessage: If ctx.input is set, appends { role: 'user', content: ctx.input } to ctx.messages, then calls next().
• conversationBuffer({ window = 12 }): If ctx.messages.length > window, it keeps the first message (commonly a system prompt) plus the last window messages, mutating ctx.messages in place.

Why keep “first + last N”? The first message is usually your system instruction; the tail is the most recent conversational state. This rule is robust for many apps.

Usage

import { inputToMessage, conversationBuffer } from '@sisu-ai/mw-conversation-buffer';

const app = new Agent()
  .use(inputToMessage)
  .use(conversationBuffer({ window: 12 }));

Recommended ordering:

• Place inputToMessage early so downstream middleware sees a full message list.
• Apply conversationBuffer after appending new messages (user/tool) and before generation to cap context size.

When To Use

• Chat apps/CLIs where conversation grows and you need bounded context.
• Prototypes and demos that benefit from predictable behavior.
• As a guardrail before providers with strict token limits.

When Not To Use

• Single‑turn flows that don’t keep history.
• Workflows that manage context elsewhere (RAG pipelines or custom budgeting).
• Cases requiring semantic compression/summarization (use a compressor middleware instead).

Notes & Gotchas

• Role‑agnostic trim: trimming is positional, not role‑aware. If you must always keep specific roles/messages, compose your own policy.
• System prompt stability: the first message is preserved; ensure it’s the one you want to keep.
• Message vs token: window is in messages, not tokens. For strict token budgets, pair with usage tracking or a tokenizer‑aware compressor.
• In‑place mutation: conversationBuffer mutates ctx.messages. Create references after trimming if you pass them elsewhere.

Community & Support

Discover what you can do through examples or documentation. Check it out at https://github.com/finger-gun/sisu. Example projects live under examples/ in the repo.

• Code of Conduct
• Contributing Guide
• License
• Report a Bug
• Request a Feature