# August 11: Support for Azure AI Document Intelligence by default, language-aware summaries ### New Features * Added support for language-aware summaries when using LLM-based document extraction. Now the summaries for tables and sections generated by the LLM will follow the language of the source text. * Added support for language-aware entity descriptions with using LLM-based entity extraction. Now the entity descriptions generated by the LLM will follow the language of the source text. * :zap: We have changed the default document preparation method to use Azure AI Document Intelligence, rather than our built-in document parsers. We have found that the fidelity of Azure AI is considerably better for complex PDFs, and provides better support for table extraction, so we have made this the default. **Note:** this does come with increased credit usage per-page, for PDF, DOCX and PPTX documents, but the quality of the extracted documents are noticeably higher for use in RAG pipelines. ### Bugs Fixed * GPLA-3070: Not getting slide count assigned to metadata for PPTX files. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://changelog.graphlit.dev/august-2024/august-11-support-for-azure-ai-document-intelligence-by-default-language-aware-summaries.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.