Memory and streaming

Agents are stateless by default: each stream() / generate() call gets the messages the client sends, and nothing else. Because nothing is shared between calls, you can safely reuse one agent instance across concurrent runs. Fanning out per-item reviews or classifications over a shared instance keeps every run isolated. Configure memory on the agent to persist history across calls, and use createAgUiHandler to stream the response back. Memory configuration is independent of model selection, so these examples omit model and use openai/gpt-5.4-nano.

Prerequisites

An agent in agents/ (see Agents).
An AG-UI route (see API routes for the createAgUiHandler("assistant") pattern).
A storage backend if you choose conversation memory; the default in-memory driver is fine while developing.

Choose a memory mode

Configure memory on your agent to persist messages across requests. A configured agent accumulates one shared conversation on the instance, so reuse it sequentially (a single chat thread) rather than across concurrent independent runs. For per-item fan-out, create a fresh agent per run instead. To keep the stateless default explicitly (for a single-shot agent that should never persist history), set enabled: false:

export default agent({
  system: "You are a one-shot classifier.",
  memory: { type: "conversation", enabled: false }, // never persists across calls
});

Buffer memory

Keeps the last N messages. Simple and predictable:

// agents/assistant.ts
import { agent } from "veryfront/agent";

export default agent({
  id: "assistant",
  system: "You are a helpful assistant.",
  memory: {
    type: "buffer",
    maxMessages: 50,
  },
});

Conversation memory

Sliding window based on token count. Drops the oldest messages when the limit is reached:

export default agent({
  system: "You are a helpful assistant.",
  memory: {
    type: "conversation",
    maxTokens: 4000,
  },
});

Summary memory

Automatically summarizes older messages to fit more context into fewer tokens:

export default agent({
  system: "You are a research assistant.",
  memory: {
    type: "summary",
  },
});

When the conversation grows long, the agent compresses older messages into a summary while keeping recent messages intact.

Redis memory

For production deployments where multiple server instances share state:

import { agent, createRedisMemory } from "veryfront/agent";
import { getEnv } from "veryfront";
import Redis from "ioredis";

const redis = new Redis(getEnv("REDIS_URL"));

export default agent({
  system: "You are a support agent.",
  memory: createRedisMemory("support", {
    type: "redis",
    client: redis,
    keyPrefix: "chat:memory:",
    ttl: 86400, // 24 hours
  }),
});

Memory operations

Access memory programmatically in API routes:

// app/api/ag-ui/route.ts
import { createAgUiHandler, getAgent } from "veryfront/agent";

export const POST = createAgUiHandler("assistant");

export async function DELETE() {
  const agent = getAgent("assistant");
  await agent.clearMemory();
  return new Response(null, { status: 204 });
}

export async function GET() {
  const agent = getAgent("assistant");
  const messages = await agent.getMemory();
  const stats = await agent.getMemoryStats();
  return Response.json({ messages, stats });
}

getMemoryStats() returns:

{
  totalMessages: 24,
  estimatedTokens: 3200,
  type: "buffer"
}

Streaming

Server-side streaming

Use createAgUiHandler() for chat UI routes. It validates the request, invokes the agent, and returns AG-UI SSE:

// app/api/ag-ui/route.ts
import { createAgUiHandler } from "veryfront/agent";

export const POST = createAgUiHandler("assistant");

Use agent.stream() directly only when you are building a custom transport or non-chat streaming surface.

Client-side consumption

The useChat hook handles the streaming protocol automatically:

"use client";
import { useChat } from "veryfront/chat";

export default function ChatPage() {
  const { messages, input, onChange, onSubmit, isLoading } = useChat();

  return (
    <div>
      {messages.map((m) => (
        <div key={m.id}>
          {m.parts.map((p) => p.type === "text" ? p.text : null)}
        </div>
      ))}
      <form onSubmit={onSubmit}>
        <input value={input} onChange={onChange} disabled={isLoading} />
      </form>
    </div>
  );
}

Non-streaming generation

Use generate() when you need the complete response at once:

const agent = getAgent("assistant");
const result = await agent.generate({
  input: "Write a haiku about programming.",
});
// result.text: full text response
// result.usage: { promptTokens, completionTokens, totalTokens }

Verify it worked

Send two messages on the same threadId (with conversation memory) and confirm the second response references the first message. With curl:

THREAD=$(uuidgen)
curl -s http://localhost:3000/api/ag-ui \
  -H "Content-Type: application/json" \
  -d "{\"threadId\":\"$THREAD\",\"messages\":[{\"id\":\"1\",\"role\":\"user\",\"parts\":[{\"type\":\"text\",\"text\":\"My name is Sam.\"}]}]}"
curl -s http://localhost:3000/api/ag-ui \
  -H "Content-Type: application/json" \
  -d "{\"threadId\":\"$THREAD\",\"messages\":[{\"id\":\"2\",\"role\":\"user\",\"parts\":[{\"type\":\"text\",\"text\":\"What is my name?\"}]}]}"

The second response should mention “Sam”. For streaming, watch the SSE output: tokens arrive incrementally rather than in one chunk.

Getting Started

Concepts

Guides

API Reference

Memory and streaming

Prerequisites

Choose a memory mode

Buffer memory

Conversation memory

Summary memory

Redis memory

Memory operations

Streaming

Server-side streaming

Client-side consumption

Non-streaming generation

Verify it worked

​Prerequisites

​Choose a memory mode

​Buffer memory

​Conversation memory

​Summary memory

​Redis memory

​Memory operations

​Streaming

​Server-side streaming

​Client-side consumption

​Non-streaming generation

​Verify it worked

Prerequisites

Choose a memory mode

Buffer memory

Conversation memory

Summary memory

Redis memory

Memory operations

Streaming

Server-side streaming

Client-side consumption

Non-streaming generation

Verify it worked