Configuration

How to use the Ai App?

A. Setting up your Ai Connection

Go to the Settings icon (Top left) and choose Connections. Use the + CREATE button and select Type Ai connection LLM, fill in the rest of the requirements. Once created, insert your API-key and select your preferred model. Click TEST connection to validate, and save to store your credentials to the connection.

1. Create and Run a Product Translation Task

Goto the App Tasks section, use the + CREATE button to create a new Task and choose, ai_translate_product as Type. Once create, you we see Parameters option exposed to you.

  • First Parameter is Ai Connection, required, select the connection you made previous.
  • Second Parameter is Channel, required, determines the Akeneo Channel if the attribute value is scope-able by channel.
  • Next Parameters are Source and Destination Locale, these options determine you from and to Translation languages.
  • Last important Parameter is the Attribute Selection, determines the attributes you wish to Translate.

Here is a small example, where we translate a description from French to German.

connection: 'openai-gpt4o'
channel: 'ecommerce'
source_locale: 'fr_FR'
target_locale: 'de_DE'
attributes: ['description']

Once saved, you can RUN the task, and it will create an operation that performs your task.

2. Create and Run a Catalog Translation Task

Goto the App Tasks section, use the + CREATE button to create a new Task and choose, ai_translate_catalog as Type. Once create, you we see Parameters option exposed to you.

  • First Parameter is Ai Connection, required, select the connection you made previous.
  • Next Parameter are Source and Destination Locale, these options determine you from and to Translation languages.
  • Last important Parameter is the Catalog Type Selection, determines the entity labels you want to translate.

Here is a small example, where we translate attribute labels from French to German.

connection: 'openai-gpt4o-mini'
source_locale: 'fr_FR'
target_locale: 'de_DE'
entity: 'attribute'

Once saved, you can RUN the task, and it will create an operation that performs your task.

3. Create and Run a Product Translation Task

Goto the App Tasks section, use the + CREATE button to create a new Task and choose, ai_autocomplete_product as Type. Once create, you we see Parameters option exposed to you.

  • First Parameter is Ai Connection, required, select the connection you made previous.
  • Second Parameter is Channel, required, determines the Akeneo Channel, if the attribute value is scope-able by channel.
  • Next Parameter is Source Locale, determines the Akeneo Locale, if the attribute value is scope-able by locale.
  • Final Parameters are checkboxes that reveal more grouped Parameters per Autocompletion.

! Make sure the Locale you provide has accurate labels, as it will help the LLM understand the request better.

The Ai_Component

The Ai_Component is an attribute that is generated on your Pim, when you run the Task ai_autocomplete_product for the first time. The Task will look for products where the Ai_Component is set the auto_complete, default we don’t se a value. In order to make your product visible for Ai App, you will have to do the following..

  1. SET the Ai_Component attribute in your family(ies).
  2. SET the Ai_Component to auto_complete on the products you wish to be visible.

Once the Product AutoCompleted by the AI, it will SET the Ai_Component to ready_to_review.

Once saved, you can RUN the task, and it will create an operation that performs your task.

3.A [CheckBox] Parameter Autocomplete Product

This Checkbox will help you enrich empty values of a given product. There are a couple of possible choices to further enrich your product values.

3.A.1 Further Enrich your product based on it’s own content

Let’s say you have a product that is 80% ready but still misses some required attributes, Maybe you added some metric attributes recently, that are available inside the product description. In this case your product will provide enough context to further enrich the product. You don’t need to select a Parsable Attribute.

3.A.2 Further Enrich your product based on Source Content

Let’s say you have a product that is NEW and you have a PDF document, or a PDF link that contains useful source Content to further enrich the product. In this case the product itself has not enough context, but you can provide a Parsable Attribute with the correct Product Information. A Parsable Attribute can be a media-attribute with a PDF document, or a text-attribute with an external link to a PDF document.

3.A.3 Exclude|Include Attributes

This parameters determine the attributes you wish to Exclude or Include as enrich-able Product Values. We support the following Types: Metric, Options, Text, TextArea, Boolean, Date.

3.B [CheckBox] Parameter Autocomplete Product Categories

This Checkbox will help you enrich the correct Category for a given product. You have the option to narrow the Category Selection by selecting a Root Category. The Option Top level categories only will narrow to the category list further to only include top level categories. The Category Instructions parameter are the prompt instructions passed to the LLM.

3.B [CheckBox] Parameter Autocomplete Product Family

This Checkbox will help you enrich the correct Family for a given product. The Family Instructions parameter are the prompt instructions passed to the LLM.

3.C Specific Prompts per Attributes

If you want set a specific prompt for an attribute, for example “make this description 300 words long”. You can set this prompt details per attribute, in Akeneo under the attribute GuideLines select the en_US locale

Attribute Guidelines

B. Best practices

  • Experiment with different models, test out what models works best for you.
  • Enrich your Catalog first, make sure your catalog data is labelled correctly and your entity codes are meaningful.
  • Experiment with prompts, tailor the prompts to you liking.

Updated on 01 Oct 2024