Microsoft Excel Document Loader

Microsoft Excel is a spreadsheet program that features calculation tools, pivot tables, and a macro programming language. This module provides functionality to load and process Excel files using SheetJS.

This module provides a sophisticated Excel document loader that can:

• Load multiple Excel file formats
• Process multiple worksheets
• Convert rows to structured documents
• Handle various data types
• Preserve cell formatting
• Extract metadata per row
• Support type inference

Inputs

Required Parameters

• Excel File: The Excel file(s) to process (.xls, .xlsx, .xlsm, .xlsb)

Optional Parameters

• Text Splitter: A text splitter to process the extracted content
• Additional Metadata: JSON object with additional metadata
• Omit Metadata Keys: Comma-separated list of metadata keys to omit

Outputs

• Document: Array of document objects containing metadata and pageContent
• Text: Concatenated string from pageContent of documents

Features

• Multiple format support
• Multi-sheet processing
• Data type preservation
• Metadata extraction
• Type inference
• Error handling
• Memory-efficient processing

Supported Formats

• Excel Binary (.xls)
• Excel Workbook (.xlsx)
• Excel Macro-Enabled (.xlsm)
• Excel Binary Workbook (.xlsb)

Data Type Handling

Supported Types

• Text (string)
• Numbers (number)
• Dates (date)
• Booleans (boolean)
• Formulas (calculated values)
• Empty cells (null)

Document Structure

Each document contains:

• pageContent: Formatted row content as key-value pairs
• metadata:
  • worksheet: Sheet name
  • rowNum: Row index
  • Original column values
  • Additional custom metadata

Row Processing

Each row is converted to a document with:

• Key-value pairs for each cell
• Preserved column headers
• Type information
• Row position

Metadata Attributes

Default attributes include:

• worksheet: Sheet or Worksheet Name (string)
• rowNum: Row index (number)
• Dynamic attributes based on column headers

Notes

• Uses SheetJS for parsing
• Preserves data types
• Handles multiple sheets
• Infers column types
• Memory-efficient processing
• Error handling for invalid files
• Flexible output formats
• Column type inference