Skip to content

PDF Processing

This guide explains how the PDF processing works in Ollama PDF RAG.

Document Loading

The application uses LangChain's PDF loader to read and process PDF documents. Here's how it works:

  1. Upload a PDF through the Streamlit interface
  2. The PDF is loaded and parsed into text
  3. Text is split into manageable chunks
  4. Chunks are processed for better context retention

Chunking Strategy

Documents are split using the following parameters:

  • Chunk size: 1000 characters (configurable)
  • Chunk overlap: 200 characters (configurable)
  • Split by: Character

This ensures: - Manageable chunk sizes for the model - Sufficient context overlap - Preservation of document structure

Text Processing

The text processing pipeline includes:

  1. Extraction: Converting PDF to raw text
  2. Cleaning: Removing artifacts and formatting
  3. Splitting: Creating overlapping chunks
  4. Indexing: Preparing for vector storage

Configuration

You can adjust processing parameters in the application:

chunk_size = 1000  # Characters per chunk
chunk_overlap = 200  # Overlap between chunks

Best Practices

  1. Document Quality
  2. Use searchable PDFs
  3. Ensure good scan quality
  4. Check text extraction quality

  5. Chunk Size

  6. Larger for detailed context
  7. Smaller for precise answers
  8. Balance based on model capacity

  9. Memory Management

  10. Monitor RAM usage
  11. Adjust chunk size if needed
  12. Clean up collections regularly