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The algorithm used to extract the text from a page or component as input for ChatGPT currently works with a heuristic that renders common attributes like jcr:title, title, subtitle, linkTitle, jcr:description, text, code, copyright, defaultValue, exampleCode, suffix, exampleResult, footer (see ApproximateMarkdownServiceImpl.java), and add special cases for special components using ApproximateMarkdownServicePlugin . That seems to work fine for standard components, but will output nothing or little for custom components that have custom attributes (which is pretty common in AEM / Composum development). Thus we have to improve that.
Variants:
Turn it around and output common attributes like jcr:title, title, subtitle, linkTitle, text, header, footer as they are, filter out system attributes by name and value (we probably won't want to output any attribute with a namespace and also not attributes with numbers, booleans, dates (?), arrays (?) )
Extract the text content from the HTML rendering of a page or component. (advantage: that contains content included from elsewhere, disadvantage: it includes irrelevant content like navigations, advertisements, headers, footers etc.)
Additionally, see whether we can easily rework it to produce HTML when needed.
The text was updated successfully, but these errors were encountered:
The algorithm used to extract the text from a page or component as input for ChatGPT currently works with a heuristic that renders common attributes like jcr:title, title, subtitle, linkTitle, jcr:description, text, code, copyright, defaultValue, exampleCode, suffix, exampleResult, footer (see ApproximateMarkdownServiceImpl.java), and add special cases for special components using ApproximateMarkdownServicePlugin . That seems to work fine for standard components, but will output nothing or little for custom components that have custom attributes (which is pretty common in AEM / Composum development). Thus we have to improve that.
Variants:
Additionally, see whether we can easily rework it to produce HTML when needed.
The text was updated successfully, but these errors were encountered: