AI Product Q&A Chatbot for Magento 2 — User Guide

1. Overview

AI Product Q&A Chatbot for Magento 2 adds an intelligent product assistant directly to Magento product pages.

Customers can ask questions in natural language and receive answers based on the current product’s Magento catalog information. The module is designed to help shoppers quickly understand product features, materials, options, suitability, availability, and other product details without manually searching through long descriptions or specification tabs.

The module follows a Magento-data-first approach:

Magento catalog data → Visual evidence when appropriate → AI-assisted synthesis → Precise limitation when information is unavailable.

Magento remains the primary source of truth.

2. Key Features

The extension includes:

• AI-powered Product Q&A on product pages
• Contextual suggested questions
• Product Assistant drawer
• Multi-turn conversations
• Follow-up questions
• Multi-intent questions
• Product-specific context isolation
• Magento product attribute grounding
• Configurable-product option awareness
• Product image understanding for supported visual questions
• Precise responses when information is unavailable
• Helpful / Not Helpful feedback
• Guest customer support
• Full Page Cache compatibility
• CSRF protection
• Request rate limiting
• Provider fallback handling
• Product switch protection
• Admin interaction history
• Centralized AI provider integration
• Responsive desktop and mobile UI

3. Requirements

Before using the extension, make sure your Magento installation meets the module's supported system requirements.

The exact supported versions depend on the release package.

Typical requirements include:

• Magento Open Source or Adobe Commerce
• Supported PHP version for your Magento release
• MageHQ Core dependencies
• MageHQ AI Commerce integration modules required by the package
• A configured AI provider when AI-assisted responses are enabled

For best results, product catalog information should be reasonably complete.

4. Installation

Upload or install the module according to your MageHQ package installation method.

After placing the module files in Magento, run the usual Magento deployment commands:

bin/magento module:enable Magehq_AIProductQA
bin/magento setup:upgrade
bin/magento setup:di:compile
bin/magento cache:flush

For production mode, deploy static content when required:

bin/magento setup:static-content:deploy -f

Confirm that the module is enabled:

bin/magento module:status Magehq_AIProductQA

5. Configuration

In Magento Admin, open the MageHQ configuration area and locate the AI Product Q&A settings.

The exact menu label may vary slightly by module version.

Enable AI Product Q&A

Set:

Enabled: Yes

This enables Product Q&A on supported product pages.

6. AI Provider Configuration

AI Product Q&A uses MageHQ's centralized AI Commerce configuration.

Depending on your MageHQ setup, you can configure:

• AI provider
• API credentials
• Model
• Connection mode
• Timeout
• Other provider-specific options

API credentials are processed server-side and are not exposed to storefront visitors.

Direct Magento product facts do not necessarily require an AI provider call.

For example:

• SKU
• stock
• price
• explicit material
• explicit color
• configurable options

can be resolved directly from Magento data.

AI is primarily used where semantic interpretation or natural-language synthesis provides additional value.

7. Suggested Questions

The module can automatically display contextual questions on product pages.

Example:

Ask About This Product

Get quick answers about this product.

• What material is this product made from?
• What features does this product have?
• What activities is this product suitable for?
• Ask Something Else

Suggested questions are generated from actual product evidence.

They are not randomly generated AI questions.

For example, if a product contains:

the module may suggest:

• What activities is this suitable for?
• What material is this made from?
• What features does this product have?

8. Unsupported Suggested Questions

The module avoids suggesting questions when the necessary product information is unavailable.

For example, if the catalog does not contain product dimensions, the system should normally avoid suggesting:

What are the exact dimensions?

This reduces the chance that customers click suggested questions that cannot be answered usefully.

9. Product Assistant Drawer

Clicking a suggested question opens the Product Assistant.

Example:

Product Assistant

Montana Wind Jacket

Customer

What material is this product made from?

Product Assistant

The listed materials are nylon and polyester.

The drawer contains:

• current product context
• conversation history
• customer questions
• Product Q&A answers
• contextual follow-up questions
• Helpful / Not Helpful controls
• free-text question field

10. Ask Something Else

Customers can click:

Ask Something Else

The Product Assistant opens and focuses the question input.

No question is submitted automatically.

The customer can then type any product-related question.

Example:

Can I use this jacket for running?

11. One-Click Suggested Questions

Suggested questions require only one click.

The normal flow is:

Click Suggested Question
        ↓
Open Product Assistant
        ↓
Submit Question Automatically
        ↓
Resolve Magento Evidence
        ↓
Generate Answer
        ↓
Display Follow-Up Suggestions

The customer does not need to click Ask again.

12. Follow-Up Questions

Product Q&A supports conversational follow-ups.

Example:

Customer

What material is this made from?

Assistant

The listed materials are nylon and polyester.

Customer

Is that good for outdoor use?

The module retains relevant conversation context and understands that the second question relates to the current product and previous answer.

13. Contextual Follow-Up Suggestions

After an answer, the module can display additional questions.

For example:

The product is made from nylon and polyester.

Suggested follow-ups may include:

• What features does it have?
• What activities is it suitable for?
• What options are available?

Follow-up suggestions also use the current product's available evidence.

14. Imperfect English

Customers do not need to write perfectly formed questions.

Examples include:

what color this?
this is bag?
can use rain?
what material this?
this good hiking?
why you say black?

The module attempts to interpret the shopper's intended meaning rather than requiring exact phrases.

15. Multi-Intent Questions

Customers may ask several questions in one message.

Example:

Is it in stock, what material is it made from, and does it have a warranty?

Product Q&A handles each requested part independently.

A response might be:

Yes, it is currently in stock. The listed material is polyester. The available product information does not specify a warranty.

The system should not silently ignore unanswered parts.

16. Missing Product Information

Product Q&A does not need to invent information when Magento does not contain the answer.

For example:

Customer

Does this product have a warranty?

If warranty information is unavailable:

The available product information does not specify a warranty.

This is known as a precise limitation.

17. Product Image Understanding

For supported visually observable questions, Product Q&A can optionally use the product image as secondary evidence.

Typical examples include:

• visible color
• basic shape
• visible pattern
• visible strap or handle
• general visual style

Magento data still has priority.

18. Color Example

If Magento contains:

Color: Black

Product Q&A can confidently answer:

The listed color is black.

If Magento does not contain a color but the product image clearly appears black:

The product appears to be black in the image. The catalog information does not list an official color, so I can't confirm the exact color name.

Visual observations are not presented as official product specifications.

19. Visual Evidence Limitations

Product images should not be used to determine facts that cannot be reliably identified visually.

The module should not infer the following only from an image:

• exact material
• waterproof rating
• durability
• weight
• exact dimensions
• stock
• price
• warranty
• shipping
• compatibility
• official variant availability

When such information is unavailable, Product Q&A returns a precise limitation.

20. Product Context Protection

Every conversation is associated with the current Magento product.

Product Q&A validates product context across:

PDP
→ request
→ product
→ evidence
→ answer

Information from one product should not be used to answer questions about another product.

21. Switching Products

Suppose a customer asks about Product A:

What colors are available?

Then navigates to Product B and asks:

Is this black too?

Product Q&A should resolve the second question using Product B information.

Product A's attributes must not leak into Product B's response.

22. Previous Answer References

Customers can ask questions about previous answers.

Examples:

Why did you say that?
Why did you say it's black?
Where did that come from?
Is that correct?
What do you mean?

Product Q&A uses the relevant conversation context to explain or correct the previous answer.

It should not simply return a generic product summary.

23. Correcting a Previous Answer

Previous Product Assistant messages are conversation context, not authoritative catalog data.

If a previous answer conflicts with Magento data, the module can correct it.

Example:

That earlier answer was incorrect. The current Magento product information lists the color as Orange.

Magento product evidence remains authoritative.

24. Magento Evidence Priority

The module follows approximately this evidence hierarchy:

DIRECT Magento Evidence
        ↓
Strong Grounded Support
        ↓
Visual Observation
        ↓
Precise Limitation

Examples of direct evidence include:

• product attributes
• configurable options
• custom options
• stock
• SKU
• product descriptions
• explicit catalog values

25. Product Attribute Semantics

The module preserves attribute meaning.

For example:

Activity:
Gym, Hiking, Trail, Urban

may be described as:

Suitable activities include gym, hiking, trail, and urban use.

It should not incorrectly say:

Key features include Gym, Hiking, Trail, Urban.

Likewise:

Features:
Waterproof, Lightweight, Laptop Sleeve

can be described as actual product features.

26. Product Options

When product options are available, customers can ask:

What options are available?

Product Q&A may use:

• configurable attributes
• selectable options
• custom product options

to answer the question.

The module does not invent unavailable variants.

27. Product Availability

When Magento contains reliable stock information, customers may ask:

Is this in stock?

Product Q&A uses Magento stock data rather than AI-generated assumptions.

28. Product Suitability Questions

Customers can ask semantic questions such as:

Is this suitable for hiking?

The assistant may combine relevant catalog evidence such as:

Activity: Hiking
Features: Waterproof, Lightweight

and respond:

Based on the listed hiking activity and waterproof, lightweight features, this product appears suitable for hiking.

This is a bounded inference based on catalog evidence.

29. Product Assistant Feedback

Customers can rate Product Q&A responses using: