From af8dc653bd4c2da7de51f477cccf2c1a1fc46da3 Mon Sep 17 00:00:00 2001 From: EmersonBraun Date: Tue, 4 Aug 2026 20:31:35 -0300 Subject: [PATCH 1/2] feat: add AgentsKit Atlas memory example --- apps/README.md | 1 + apps/agentskit-atlas-memory/.env.example | 4 + apps/agentskit-atlas-memory/.gitignore | 3 + apps/agentskit-atlas-memory/README.md | 56 + apps/agentskit-atlas-memory/package-lock.json | 2272 +++++++++++++++++ apps/agentskit-atlas-memory/package.json | 24 + apps/agentskit-atlas-memory/src/index.ts | 49 + apps/agentskit-atlas-memory/src/lifecycle.ts | 39 + .../tests/lifecycle.test.ts | 59 + apps/agentskit-atlas-memory/tsconfig.json | 12 + 10 files changed, 2519 insertions(+) create mode 100644 apps/agentskit-atlas-memory/.env.example create mode 100644 apps/agentskit-atlas-memory/.gitignore create mode 100644 apps/agentskit-atlas-memory/README.md create mode 100644 apps/agentskit-atlas-memory/package-lock.json create mode 100644 apps/agentskit-atlas-memory/package.json create mode 100644 apps/agentskit-atlas-memory/src/index.ts create mode 100644 apps/agentskit-atlas-memory/src/lifecycle.ts create mode 100644 apps/agentskit-atlas-memory/tests/lifecycle.test.ts create mode 100644 apps/agentskit-atlas-memory/tsconfig.json diff --git a/apps/README.md b/apps/README.md index fcc2852..525cf80 100644 --- a/apps/README.md +++ b/apps/README.md @@ -2,6 +2,7 @@ Javascript and Python apps and demos showcasing how to use MongoDB in GenAI appl | Application | Stack | Description | Directory | |------------|-------|-------------|-----------| +| AgentsKit Atlas Memory | MongoDB Atlas, AgentsKit, TypeScript | Minimal vector-memory lifecycle with replaceable embedding and model providers | [![View Code](https://img.shields.io/badge/view-code-blue?logo=github)](agentskit-atlas-memory) | | Ambient Inventory Agent | MongoDB Atlas, MongoDB Remote MCP, Python, FastAPI, LangGraph, Claude on Amazon Bedrock | Coffee roaster inventory assistant: a deterministic LangGraph monitor raises low-stock alerts, and a streaming LangGraph ReAct agent answers the owner's questions using MongoDB Remote MCP tools | [![View Code](https://img.shields.io/badge/view-code-blue?logo=github)](ambient-inventory-agent) | | Graph RAG Demo | MongoDB Atlas, Python, Node.js, OpenAI | Graph-based RAG implementation demonstrating MongoDB's graph capabilities with hybrid Python/Node.js approach | [![View Code](https://img.shields.io/badge/view-code-blue?logo=github)](graph_rag_demo) | | Local RAG PDF | MongoDB Atlas, Python | Local RAG implementation for PDF processing and querying | [![View Code](https://img.shields.io/badge/view-code-blue?logo=github)](local-rag-pdf) | diff --git a/apps/agentskit-atlas-memory/.env.example b/apps/agentskit-atlas-memory/.env.example new file mode 100644 index 0000000..7eb4bee --- /dev/null +++ b/apps/agentskit-atlas-memory/.env.example @@ -0,0 +1,4 @@ +MONGODB_URI= +MONGODB_DATABASE=agentskit_demo +MONGODB_COLLECTION=memory +MONGODB_VECTOR_INDEX=agentskit_vector_index diff --git a/apps/agentskit-atlas-memory/.gitignore b/apps/agentskit-atlas-memory/.gitignore new file mode 100644 index 0000000..ddc3c2a --- /dev/null +++ b/apps/agentskit-atlas-memory/.gitignore @@ -0,0 +1,3 @@ +.env +node_modules/ +dist/ diff --git a/apps/agentskit-atlas-memory/README.md b/apps/agentskit-atlas-memory/README.md new file mode 100644 index 0000000..dfb15f7 --- /dev/null +++ b/apps/agentskit-atlas-memory/README.md @@ -0,0 +1,56 @@ +# AgentsKit memory with MongoDB Atlas Vector Search + +This minimal TypeScript example uses MongoDB Atlas as a replaceable vector-memory +backend for an agent. It exercises the complete memory lifecycle: store three +documents, retrieve the closest context, print the result, and remove the demo +documents. + +The sample uses small deterministic vectors so the integration is easy to +inspect. In an application, replace them with vectors from any embedding +provider; the MongoDB collection and AgentsKit memory contract stay unchanged. + +## Prerequisites + +- Node.js 20 or newer +- A MongoDB Atlas cluster +- An Atlas Vector Search index named `agentskit_vector_index` on + `agentskit_demo.memory` + +Use this index definition for the sample's three-dimensional vectors: + +```json +{ + "fields": [ + { + "type": "vector", + "path": "embedding", + "numDimensions": 3, + "similarity": "cosine" + } + ] +} +``` + +## Run the example + +```bash +cp .env.example .env +npm install +node --env-file=.env --import tsx src/index.ts +``` + +Set `MONGODB_URI` in `.env` before running. The database, collection, and index +names can also be changed there. + +The script deletes its sample records before and after the run, so repeated +executions do not leave demo data behind. + +## Validate without credentials + +```bash +npm run typecheck +npm test +``` + +The deterministic test exercises the collection boundary and verifies the +generated `$vectorSearch` pipeline without contacting Atlas. diff --git a/apps/agentskit-atlas-memory/package-lock.json b/apps/agentskit-atlas-memory/package-lock.json new file mode 100644 index 0000000..1a384fe --- /dev/null +++ b/apps/agentskit-atlas-memory/package-lock.json @@ -0,0 +1,2272 @@ +{ + "name": "agentskit-atlas-memory", + "version": "1.0.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "agentskit-atlas-memory", + "version": "1.0.0", + "dependencies": { + "@agentskit/memory": "^0.11.6", + "mongodb": "^7.5.0" + }, + "devDependencies": { + "@types/node": "^26.1.2", + "tsx": "^4.23.5", + 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"^0.11.6", + "mongodb": "^7.5.0" + }, + "devDependencies": { + "@types/node": "^26.1.2", + "tsx": "^4.23.5", + "typescript": "^7.0.2", + "vitest": "^4.1.10" + }, + "engines": { + "node": ">=20" + } +} diff --git a/apps/agentskit-atlas-memory/src/index.ts b/apps/agentskit-atlas-memory/src/index.ts new file mode 100644 index 0000000..c0e85d9 --- /dev/null +++ b/apps/agentskit-atlas-memory/src/index.ts @@ -0,0 +1,49 @@ +import { mongoAtlasVectorStore } from '@agentskit/memory' +import type { MongoCollectionLike } from '@agentskit/memory' +import { MongoClient } from 'mongodb' +import type { Collection, Document, Filter } from 'mongodb' +import { runMemoryLifecycle } from './lifecycle.js' + +function required(name: string): string { + const value = process.env[name] + if (!value) throw new Error(`Missing ${name}`) + return value +} + +function asAgentsKitCollection(collection: Collection): MongoCollectionLike { + return { + insertMany(documents) { + return collection.insertMany(documents) + }, + deleteMany(filter) { + return collection.deleteMany(filter as Filter) + }, + aggregate(pipeline: Array>) { + const cursor = collection.aggregate(pipeline) + return { + toArray: async () => await cursor.toArray() as unknown as T[], + } + }, + } +} + +const client = new MongoClient(required('MONGODB_URI')) + +try { + await client.connect() + + const database = process.env.MONGODB_DATABASE ?? 'agentskit_demo' + const collectionName = process.env.MONGODB_COLLECTION ?? 'memory' + const indexName = process.env.MONGODB_VECTOR_INDEX ?? 'agentskit_vector_index' + const collection = client.db(database).collection(collectionName) + const memory = mongoAtlasVectorStore({ + collection: asAgentsKitCollection(collection), + indexName, + topK: 2, + }) + const matches = await runMemoryLifecycle(memory) + + console.log(JSON.stringify(matches, null, 2)) +} finally { + await client.close() +} diff --git a/apps/agentskit-atlas-memory/src/lifecycle.ts b/apps/agentskit-atlas-memory/src/lifecycle.ts new file mode 100644 index 0000000..0272138 --- /dev/null +++ b/apps/agentskit-atlas-memory/src/lifecycle.ts @@ -0,0 +1,39 @@ +import type { mongoAtlasVectorStore } from '@agentskit/memory' + +type AtlasMemory = ReturnType + +export const sampleDocuments = [ + { + id: 'deployment-boundary', + content: 'Keep model providers behind an adapter boundary.', + embedding: [1, 0, 0], + metadata: { topic: 'architecture' }, + }, + { + id: 'retrieval-boundary', + content: 'Keep retrieval independent from the agent runtime.', + embedding: [0.8, 0.2, 0], + metadata: { topic: 'retrieval' }, + }, + { + id: 'evaluation-boundary', + content: 'Evaluate behavior before changing model providers.', + embedding: [0, 0, 1], + metadata: { topic: 'evaluation' }, + }, +] + +export async function runMemoryLifecycle(memory: AtlasMemory) { + const ids = sampleDocuments.map((document) => document.id) + const remove = memory.delete + if (!remove) throw new Error('This example requires a memory backend with delete support') + + await remove(ids) + await memory.store(sampleDocuments) + + try { + return await memory.search([1, 0, 0], { topK: 2 }) + } finally { + await remove(ids) + } +} diff --git a/apps/agentskit-atlas-memory/tests/lifecycle.test.ts b/apps/agentskit-atlas-memory/tests/lifecycle.test.ts new file mode 100644 index 0000000..976c4a2 --- /dev/null +++ b/apps/agentskit-atlas-memory/tests/lifecycle.test.ts @@ -0,0 +1,59 @@ +import { describe, expect, it, vi } from 'vitest' +import { mongoAtlasVectorStore } from '@agentskit/memory' +import type { MongoCollectionLike } from '@agentskit/memory' +import { runMemoryLifecycle, sampleDocuments } from '../src/lifecycle.js' + +describe('MongoDB Atlas memory lifecycle', () => { + it('stores, retrieves, and removes the example documents', async () => { + const insertMany = vi.fn(async () => ({ acknowledged: true })) + const deleteMany = vi.fn(async () => ({ acknowledged: true })) + const aggregateCalls: Array>> = [] + const collection: MongoCollectionLike = { + insertMany, + deleteMany, + aggregate(pipeline: Array>) { + aggregateCalls.push(pipeline) + return { + toArray: async () => [ + { + _id: 'deployment-boundary', + content: sampleDocuments[0].content, + metadata: sampleDocuments[0].metadata, + score: 0.98, + }, + ] as T[], + } + }, + } + const memory = mongoAtlasVectorStore({ + collection, + indexName: 'agentskit_vector_index', + topK: 2, + }) + + const matches = await runMemoryLifecycle(memory) + + expect(insertMany).toHaveBeenCalledOnce() + expect(aggregateCalls).toEqual([[ + { + $vectorSearch: { + index: 'agentskit_vector_index', + path: 'embedding', + queryVector: [1, 0, 0], + numCandidates: 20, + limit: 2, + }, + }, + { $project: { content: 1, metadata: 1, score: { $meta: 'vectorSearchScore' } } }, + ]]) + expect(deleteMany).toHaveBeenCalledTimes(2) + expect(matches).toEqual([ + { + id: 'deployment-boundary', + content: sampleDocuments[0].content, + metadata: sampleDocuments[0].metadata, + score: 0.98, + }, + ]) + }) +}) diff --git a/apps/agentskit-atlas-memory/tsconfig.json b/apps/agentskit-atlas-memory/tsconfig.json new file mode 100644 index 0000000..1e62a2f --- /dev/null +++ b/apps/agentskit-atlas-memory/tsconfig.json @@ -0,0 +1,12 @@ +{ + "compilerOptions": { + "target": "ES2022", + "module": "NodeNext", + "moduleResolution": "NodeNext", + "strict": true, + "noEmit": true, + "skipLibCheck": true, + "types": ["node"] + }, + "include": ["src", "tests"] +} From 6b2e0b6b6d3c9cba0e87f80f620ebe11c36e0804 Mon Sep 17 00:00:00 2001 From: EmersonBraun Date: Tue, 4 Aug 2026 21:22:01 -0300 Subject: [PATCH 2/2] fix: retry Atlas search while indexing --- apps/agentskit-atlas-memory/README.md | 8 ++- apps/agentskit-atlas-memory/src/lifecycle.ts | 20 ++++++- .../tests/lifecycle.test.ts | 57 ++++++++++++++++--- 3 files changed, 72 insertions(+), 13 deletions(-) diff --git a/apps/agentskit-atlas-memory/README.md b/apps/agentskit-atlas-memory/README.md index dfb15f7..297e8bf 100644 --- a/apps/agentskit-atlas-memory/README.md +++ b/apps/agentskit-atlas-memory/README.md @@ -42,8 +42,12 @@ node --env-file=.env --import tsx src/index.ts Set `MONGODB_URI` in `.env` before running. The database, collection, and index names can also be changed there. -The script deletes its sample records before and after the run, so repeated -executions do not leave demo data behind. +Atlas Vector Search indexes new records asynchronously. The example retries the +search at one-second intervals for up to five attempts while the stored records +become queryable. It +deletes its sample records before and after the run, including when indexing +does not complete within that retry window, so repeated executions do not leave +demo data behind. ## Validate without credentials diff --git a/apps/agentskit-atlas-memory/src/lifecycle.ts b/apps/agentskit-atlas-memory/src/lifecycle.ts index 0272138..c00cd0d 100644 --- a/apps/agentskit-atlas-memory/src/lifecycle.ts +++ b/apps/agentskit-atlas-memory/src/lifecycle.ts @@ -2,6 +2,12 @@ import type { mongoAtlasVectorStore } from '@agentskit/memory' type AtlasMemory = ReturnType +type LifecycleOptions = { + maxSearchAttempts?: number + retryDelayMs?: number + sleep?: (delayMs: number) => Promise +} + export const sampleDocuments = [ { id: 'deployment-boundary', @@ -23,16 +29,26 @@ export const sampleDocuments = [ }, ] -export async function runMemoryLifecycle(memory: AtlasMemory) { +export async function runMemoryLifecycle(memory: AtlasMemory, options: LifecycleOptions = {}) { const ids = sampleDocuments.map((document) => document.id) const remove = memory.delete if (!remove) throw new Error('This example requires a memory backend with delete support') + const maxSearchAttempts = options.maxSearchAttempts ?? 5 + const retryDelayMs = options.retryDelayMs ?? 1_000 + const sleep = options.sleep ?? ((delayMs: number) => new Promise((resolve) => setTimeout(resolve, delayMs))) + await remove(ids) await memory.store(sampleDocuments) try { - return await memory.search([1, 0, 0], { topK: 2 }) + for (let attempt = 1; attempt <= maxSearchAttempts; attempt += 1) { + const matches = await memory.search([1, 0, 0], { topK: 2 }) + if (matches.some((match) => ids.includes(match.id))) return matches + if (attempt < maxSearchAttempts) await sleep(retryDelayMs) + } + + throw new Error(`Stored documents were not visible after ${maxSearchAttempts} search attempts`) } finally { await remove(ids) } diff --git a/apps/agentskit-atlas-memory/tests/lifecycle.test.ts b/apps/agentskit-atlas-memory/tests/lifecycle.test.ts index 976c4a2..35b995b 100644 --- a/apps/agentskit-atlas-memory/tests/lifecycle.test.ts +++ b/apps/agentskit-atlas-memory/tests/lifecycle.test.ts @@ -4,24 +4,18 @@ import type { MongoCollectionLike } from '@agentskit/memory' import { runMemoryLifecycle, sampleDocuments } from '../src/lifecycle.js' describe('MongoDB Atlas memory lifecycle', () => { - it('stores, retrieves, and removes the example documents', async () => { + function createMemory(searchResults: Array>>) { const insertMany = vi.fn(async () => ({ acknowledged: true })) const deleteMany = vi.fn(async () => ({ acknowledged: true })) const aggregateCalls: Array>> = [] + let searchCall = 0 const collection: MongoCollectionLike = { insertMany, deleteMany, aggregate(pipeline: Array>) { aggregateCalls.push(pipeline) return { - toArray: async () => [ - { - _id: 'deployment-boundary', - content: sampleDocuments[0].content, - metadata: sampleDocuments[0].metadata, - score: 0.98, - }, - ] as T[], + toArray: async () => (searchResults[searchCall++] ?? []) as T[], } }, } @@ -31,6 +25,19 @@ describe('MongoDB Atlas memory lifecycle', () => { topK: 2, }) + return { aggregateCalls, deleteMany, insertMany, memory } + } + + const match = { + _id: 'deployment-boundary', + content: sampleDocuments[0].content, + metadata: sampleDocuments[0].metadata, + score: 0.98, + } + + it('stores, retrieves, and removes immediately visible documents', async () => { + const { aggregateCalls, deleteMany, insertMany, memory } = createMemory([[match]]) + const matches = await runMemoryLifecycle(memory) expect(insertMany).toHaveBeenCalledOnce() @@ -56,4 +63,36 @@ describe('MongoDB Atlas memory lifecycle', () => { }, ]) }) + + it('retries while stored documents are still being indexed', async () => { + const { aggregateCalls, deleteMany, memory } = createMemory([[], [match]]) + const sleep = vi.fn(async () => {}) + + const matches = await runMemoryLifecycle(memory, { + maxSearchAttempts: 3, + retryDelayMs: 25, + sleep, + }) + + expect(aggregateCalls).toHaveLength(2) + expect(sleep).toHaveBeenCalledOnce() + expect(sleep).toHaveBeenCalledWith(25) + expect(deleteMany).toHaveBeenCalledTimes(2) + expect(matches[0]?.id).toBe('deployment-boundary') + }) + + it('cleans up and fails after the search retry budget is exhausted', async () => { + const { aggregateCalls, deleteMany, memory } = createMemory([[], [], []]) + const sleep = vi.fn(async () => {}) + + await expect(runMemoryLifecycle(memory, { + maxSearchAttempts: 3, + retryDelayMs: 25, + sleep, + })).rejects.toThrow('Stored documents were not visible after 3 search attempts') + + expect(aggregateCalls).toHaveLength(3) + expect(sleep).toHaveBeenCalledTimes(2) + expect(deleteMany).toHaveBeenCalledTimes(2) + }) })