# The Magento multi-store bug every AI description generator has — and how we fixed it

> Source: <https://dev.to/angeo/the-magento-multi-store-bug-every-ai-description-generator-has-and-how-we-fixed-it-59b1>
> Published: 2026-05-22 05:02:09+00:00

A client came to us with 8,000 SKUs across four store views — English, Dutch, German, French. Descriptions were either copied from supplier PDFs or missing entirely. The fix was obviously AI generation. The less obvious problem was that **every existing module we evaluated had the same architectural bug**.

So we built our own, made it MIT-licensed, and put it on Packagist. This post is about the bug, the fix, and the four-provider abstraction (including a free one) we shipped on top.

🔗 Originally published on

[https://angeo.dev/magento-2-ai-product-description-generator/]

## The bug nobody talks about

Most Magento 2 AI content modules call this:

``` php
$product = $this->productRepository->get($sku, editMode: true);
$product->setCustomAttribute('description', $generated);
$this->productRepository->save($product);
```

Looks fine. It isn't. Without an explicit `$storeId`

, this loads and saves in the**default scope**— Magento's global, store-view-independent fallback. When you save back, you overwrite** every store view at once**. The Dutch store gets English descriptions. The German store gets English descriptions. The French store gets English descriptions.

This is not a configuration problem. The multi-store architecture works correctly — the tooling ignores it. Writing to the default scope is simpler to implement than writing per store. Every commercial module we tested took the simpler path.

The right way:

``` php
// Load the product in the target store scope
$product = $this->productRepository->get($sku, false, $storeId);
$product->setCustomAttribute('description', $generated);

// Save with explicit store scope (Magento_Catalog\Model\Product\Action)
$this->productService->updateAttributes($sku, $generated, $storeId);
```

The difference is one parameter. The architectural cost is iterating stores around your generation loop. The data cost of skipping it is silently corrupting your multi-language catalog.

## The framework around the fix

The store-scope fix is the boring part. The interesting part is everything you need around it.

```
┌─────────────────────────────────────────────────────┐
│       Angeo Multi-Store AI Content Framework        │
├──────────────┬──────────────────┬───────────────────┤
│  SKU Source  │ Store Iteration  │   AI Provider     │
│  ──────────  │  ──────────────  │  ──────────────── │
│  Catalog     │  Store 1 (EN)    │  OpenAI           │
│  G.Sheets    │  Store 2 (NL)    │  Claude           │
│  CLI --sku   │  Store 3 (DE)    │  Gemini           │
│              │  Store 4 (FR)    │  Groq (free)      │
├──────────────┴──────────────────┴───────────────────┤
│               Content Pipeline                      │
│  load(sku, storeId) → prompt → generate → save      │
├─────────────────────────────────────────────────────┤
│                    Output                           │
│  Magento DB · Local CSV · Google Sheets API v4      │
└─────────────────────────────────────────────────────┘
```

Four layers:

-**Provider Layer**— uniform interface across OpenAI, Claude, Gemini, Groq -** Store Iteration Layer**— resolves all active store views before processing any SKUs -** Content Pipeline**— for each store × SKU: load in scope → build prompt → generate → save in scope -** I/O Layer**— reads SKUs from catalog, Google Sheet, or CLI; writes to Magento DB, CSV, and Google Sheets

The provider abstraction is the part most people will copy. One interface:

```
interface AiProviderInterface
{
    public function generate(string $system, string $user): string;
}
```

Wired in `di.xml`

:

```
<type name="Angeo\AiDescriptionUpdater\Service\AiProviderService">
  <arguments>
    <argument name="providers" xsi:type="array">
      <item name="openai" xsi:type="object">...OpenAiProvider</item>
      <item name="claude" xsi:type="object">...ClaudeProvider</item>
      <item name="gemini" xsi:type="object">...GeminiProvider</item>
      <item name="groq"   xsi:type="object">...GroqProvider</item>
    </argument>
  </arguments>
</type>
```

Adding a fifth provider is one class + one line. The pipeline, store iteration, and I/O don't change. This is the pattern, not just the code.

## The four-provider benchmark

200 product descriptions from a real Dutch jewellery store, same system prompt, same product names, all four providers.

### Speed (avg per description)

| Provider | Model | Avg. time |
|---|---|---|
| Groq | llama-3.3-70b-versatile | 0.8s |
| Groq | mixtral-8x7b-32768 | 0.6s |
| gemini-2.0-flash | 1.2s | |
| Anthropic | claude-haiku-4-5 | 1.1s |
| OpenAI | gpt-4.1-mini | 1.4s |
| OpenAI | gpt-4.1 | 2.1s |
| Anthropic | claude-sonnet-4-6 | 2.8s |

For 32,000 generations (8,000 SKUs × 4 store views):**Groq ≈ 7 hours, GPT-4.1 ≈ 19 hours**.

### Cost (per 1,000 descriptions, ~200 words each)

| Provider | Model | Cost / 1k |
|---|---|---|
| Groq | llama-3.3-70b-versatile | $0.00 (free tier) |
| gemini-2.0-flash | ~$0.08 | |
| OpenAI | gpt-4.1-mini | ~$0.24 |
| Anthropic | claude-haiku-4-5 | ~$0.32 |
| OpenAI | gpt-4.1 | ~$1.80 |
| Anthropic | claude-sonnet-4-6 | ~$2.40 |

### Quality (manual review of 200 samples)

| Criteria | Groq Llama 3.3 | GPT-4.1-mini | GPT-4.1 | Claude Sonnet |
|---|---|---|---|---|
| Factual accuracy | ★★★★☆ | ★★★★☆ | ★★★★★ | ★★★★★ |
| Language fluency | ★★★★☆ | ★★★★☆ | ★★★★★ | ★★★★★ |
| SEO keyword use | ★★★☆☆ | ★★★★☆ | ★★★★☆ | ★★★★☆ |
| HTML formatting | ★★★★☆ | ★★★★☆ | ★★★★★ | ★★★★★ |**Practical recommendation:** Validate prompts with Groq first — it's free, fast, and good enough to test workflow. Production on GPT-4.1-mini if SEO keyword density matters. Flagship products on GPT-4.1 or Claude Sonnet if copy quality directly affects conversion.

## Why Groq matters

Groq's free tier is 14,400 requests/day. No credit card. Llama 3.3 70B output quality is genuinely good — ~1 star behind GPT-4.1 in our review, mostly on SEO keyword density.

For 8,000 SKUs × 4 stores = 32,000 calls, you're at ~1.85 days on the free tier. For most stores under 5,000 SKUs, this is**free production-grade AI content generation** if you're patient.

No other Magento module supports Groq at time of writing. This was the killer feature for our client.

## Installation

```
composer require angeo/module-ai-description-updater
bin/magento setup:upgrade
bin/magento setup:di:compile
bin/magento cache:flush
```

First run (Groq, ~5 minutes from zero):

```
# 1. Get a free API key at console.groq.com
# 2. In admin: Stores → Configuration → Angeo → AI Description Updater
#    AI Provider = Groq (Free), paste key, Dry Run = Yes
# 3. Test on one SKU
bin/magento angeo:ai-description:run --sku=MY-SKU-001 --dry-run

# 4. If output looks good, disable dry-run and run the batch
bin/magento angeo:ai-description:run
```

Other useful flags:

```
bin/magento angeo:ai-description:run --sku=ABC-123     # single SKU, all stores
bin/magento angeo:ai-description:run --store=2         # single store view
bin/magento angeo:ai-description:run --dry-run         # generate, don't save
```

CLI-first by design. The 8,000-SKU client doesn't want a UI; they want cron.

## Why it's open source

The honest answer: distribution. We sell AEO audits and full-stack Magento services. The modules are how stores find us. The code is free; the expertise applied to a specific store is not.

It's a familiar model — Vercel does it with Next.js, Sentry does it with sentry-php. The artefact is open; the operator is the product.

## Key takeaways for Magento devs

-**Default-scope writes are silent multi-store corruption.** Audit any AI/content module before installing on a multi-store catalog. Look for`$storeId`

parameters in`productRepository->get()`

and save calls. -**Provider abstraction is one interface plus a** Don't hardcode OpenAI. Future you (or future LLM pricing) will thank you.`di.xml`

array. -**Groq is the current sweet spot for free Magento AI generation.** Llama 3.3 70B output is production-acceptable for most stores; the 14,400/day cap is workable for catalogs under ~5,000 SKUs. -**GPT-4.1-mini is the best paid-tier value.** Comparable to GPT-4.1 at ~17% of the cost. -**CLI + cron beats admin UI for catalogs above ~500 SKUs.** Click-by-click generation isn't a workflow.

## Links

-**Module on Packagist:**`angeo/module-ai-description-updater`

-**Full benchmark + FAQ:**[angeo.dev/magento-2-ai-product-description-generator](https://angeo.dev/magento-2-ai-product-description-generator/) -** Why AI search changes Magento descriptions:**[angeo.dev/magento-product-descriptions-in-the-age-of-ai-search](https://angeo.dev/magento-product-descriptions-in-the-age-of-ai-search/) -**The technical why:**[angeo.dev/magento-product-description-invisible-ai-chatgpt](https://angeo.dev/magento-product-description-invisible-ai-chatgpt/)

*Originally published on angeo.dev. Questions or feedback — drop a comment.*