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[SPARKNLP-1103] Adding support to read power point files #14491

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Description

This pull request introduces a new feature that enables reading and parsing Microsoft PowerPoint files (.pptx and .ppt) into a structured Spark DataFrame. Leveraging this functionality allows for efficient processing and analysis of PowerPoint slides content, seamlessly integrating with Spark NLP for enhanced downstream natural language processing tasks.

Important: Please do not merge this PR until #14489 is merged.

Motivation and Context

  • Structured Data Representation: By transforming PowerPoint slides content into a well-defined DataFrame structure, we enable seamless integration with Spark’s powerful analytical and data processing capabilities.
  • Scalability: Leveraging Spark’s distributed architecture, this feature supports the efficient processing of large volumes of PowerPoint slides data, which is critical for big data projects.
  • Simplified Data Manipulation: Working with a structured DataFrame simplifies data manipulation tasks, such as filtering, aggregating, and transforming PowerPoint slides content, reducing complexity and improving productivity.
  • Enhanced Context for LLM Tasks: By organizing Excel sheets into structured formats, we can curate and provide more specific, context-rich content for large language model (LLM) prompts. This improves the quality of LLM-generated outputs by allowing for more targeted and relevant contextual information, which is essential for applications like NLU and content generation.

How Has This Been Tested?

Screenshots (if appropriate):

  • Local Tests
  • Google Colab notebook
  • Databricks notebooks

Types of changes

  • Bug fix (non-breaking change which fixes an issue)
  • Code improvements with no or little impact
  • New feature (non-breaking change which adds functionality)
  • Breaking change (fix or feature that would cause existing functionality to change)

Checklist:

  • My code follows the code style of this project.
  • My change requires a change to the documentation.
  • I have updated the documentation accordingly.
  • I have read the CONTRIBUTING page.
  • I have added tests to cover my changes.
  • All new and existing tests passed.

@danilojsl danilojsl added DON'T MERGE Do not merge this PR new-feature Introducing a new feature labels Dec 24, 2024
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