Multistore Configuration Guide

NextGenAiAssistant is built to seamlessly handle content generation in multistore environments. Depending on how you create threads, you can target specific stores or apply content across all stores. Let’s explore how multistore functionality works with the three available thread creation methods:


1. Mass Actions for Products or Categories

When using Mass Actions (available in the product or category listing pages) to generate content for multiple items:

  • Store Selection: In the Mass Action form, you can manually select which stores will receive the generated content. This allows you to customize content for specific stores or apply it to all stores in one go.
  • Multistore Flexibility: The selected stores will determine where the generated data (e.g., product descriptions, category metadata) is applied, ensuring efficient multistore management.

2. Product Edit Page

You can generate content directly from the Product Edit page under the AI Assistant tab:

  • Store Selection: Similar to mass actions, the form includes an option to select the target stores for which the prompt should be executed.
  • Granular Control: This allows you to update content for individual products across specific stores, ensuring that product information is consistent and accurate.

3. Create And Run Thread

The Create And Run Thread form offers even more flexibility for creating custom threads, but its behavior depends on the store context in the PrestaShop admin panel:

  • Specific Store Context: If you’re operating within the context of a specific store (e.g., Store A), the thread will only generate content for that store.
  • All Stores Context: If you’re in the All Stores context, the system will create separate threads for all stores. This ensures content is applied consistently across your multistore environment without requiring manual store selection.

How Store Context Affects Thread Creation

For both Mass Actions and Product Edit forms:

  • You always have manual control over which stores will receive the generated content.

For the Create And Run Thread form:

  • The store context determines the scope:
  • In a specific store context, the content is generated for that store only.
  • In the All Stores context, the content is generated for every store in your setup.

Multilanguage Content Generation

In addition to multistore support, the module also allows content generation for multiple languages within a store.

1. Selecting Languages for Threads:

  • If your store operates in multiple languages, you can select one or more languages during thread creation.
  • For each selected language, the module will create a separate thread, ensuring that content is tailored to each specific language.

2. Independent Language Threads:

  • Each language will have its own unique thread, ensuring content such as product descriptions, metadata, or category details are generated and managed independently for each language.

Example Workflow: Generating Descriptions for a Multistore, Multilingual Setup

1. Create a New Thread:

  • Select Product as the entity type.
  • Choose multiple stores (e.g., Store A, Store B).
  • Select multiple languages (e.g., English, French).

2. Result:

  • For each language in each selected store, a separate thread is created.
  • This means Store A (English), Store A (French), Store B (English), and Store B (French) will each have their own thread, allowing for precise control over generated content.

Key Benefits of Multistore and Multilanguage Support

  • Customizable Store Targeting: Easily tailor content for specific stores or apply it globally.
  • Automatic Adaptation to Store Context: The system dynamically adjusts based on the current store context.
  • Efficient Multilingual Content Management: Generate and manage content for multiple languages in a streamlined process.

By leveraging the multistore and multilanguage capabilities of NextGenAiAssistant, you can efficiently manage complex content generation tasks while maintaining control over where and how the content is applied.

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