with-inngest

A complete Next.js chat application that demonstrates Recall Core with Inngest for background memory extraction.

Features

Chat interface with OpenAI GPT
Automatic memory extraction via Inngest functions
Real-time memory display panel
SQLite persistence
AI SDK wrapper for simplified integration

Prerequisites

Node.js 18+
pnpm
OpenAI API key
Inngest CLI (for local development)

Setup

1. Install dependencies

cd examples/with-inngest
pnpm install

2. Configure environment

cp .env.example .env

Add your OpenAI API key to .env:

OPENAI_API_KEY=sk-proj-your-key-here

3. Start the development server

In one terminal, start the Next.js app:

pnpm dev

In another terminal, start the Inngest dev server:

pnpm dev:inngest

4. Open the app

Visit http://localhost:3000

Project Structure

src/
├── app/
│   ├── api/
│   │   ├── chat/          # Manual memory handling
│   │   ├── ai-sdk/        # AI SDK wrapper approach
│   │   ├── inngest/       # Inngest webhook endpoint
│   │   └── memories/      # List memories endpoint
│   └── page.tsx
├── components/
│   ├── chat-interface.tsx
│   └── memories-panel.tsx
└── lib/
    ├── memory.ts          # Recall instance + AI SDK wrapper
    └── inngest/
        ├── client.ts      # Inngest client
        └── functions.ts   # Memory extraction function

How It Works

Memory Instance

import { createMemory } from '@youcraft/recall'
import { createRecall } from '@youcraft/recall-ai-sdk'

export const memory = createMemory({
  db: sqliteAdapter({ filename: 'recall.db' }),
  extractor: openaiExtractor({ apiKey: process.env.OPENAI_API_KEY! }),
  embeddings: openaiEmbeddings({ apiKey: process.env.OPENAI_API_KEY! }),
})

export const recall = createRecall({
  memory,
  onExtract: async ({ messages, userId }) => {
    await inngest.send({
      name: 'chat/message.completed',
      data: { userId, messages },
    })
  },
})

Chat Endpoint

The example includes two chat endpoints:

/api/chat — Manual approach with explicit memory handling

/api/ai-sdk — Simplified approach using the recall() wrapper:

import { recall } from '@/lib/memory'

const result = streamText({
  model: recall(openai('gpt-5-nano'), { userId: USER_ID }),
  system: 'You are a helpful assistant.',
  messages: convertToModelMessages(messages),
})

Inngest Function

export const extractMemories = inngest.createFunction(
  { id: 'extract-memories' },
  { event: 'chat/message.completed' },
  async ({ event, step }) => {
    const { userId, messages } = event.data

    const conversation = await step.run('format-conversation', async () => {
      return messages.map(m => `${m.role}: ${m.content}`).join('\n')
    })

    const memories = await step.run('extract-memories', async () => {
      return memory.extract(conversation, { userId })
    })

    return { memoriesExtracted: memories.length }
  }
)