unstructured-pdf-generation

Generate synthetic PDFs for RAG by defining custom content descriptions and document size configurations. The Skill outputs LLM-generated unstructured PDF documents to facilitate RAG pipeline testing and knowledge base population.

Yes, RAG evaluation data is generated as companion JSON files containing question and guideline pairs. These files enable automated evaluation of retrieval pipelines alongside the synthetic PDF documents.

Yes, synthetic PDF generation supports direct upload to Databricks Unity Catalog Volumes. You can specify the target catalog, schema, and folder path to automatically store the generated unstructured data.

The best way to populate a knowledge base with synthetic unstructured data is using LLM-generated PDFs with custom descriptions. This automates creating realistic technical or policy documents specifically for testing retrieval systems.

No dependencies are required to create LLM-generated PDFs for document generation. The Skill operates independently to produce synthetic PDFs and JSON evaluation files for RAG systems.