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Merged
merged 6 commits into from
Mar 15, 2025
Merged

Text Processing Implementation #4

merged 6 commits into from
Mar 15, 2025

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whitmo
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@whitmo whitmo commented Mar 15, 2025

Text Processing Module

Overview

This PR implements a comprehensive text processing module that provides essential functionality for working with text data in the vector store. The implementation follows both Documentation-Driven Development (DDD) and Test-Driven Development (TDD) principles.

Features

Text Tokenization

  • Flexible tokenization strategies
  • Custom tokenizer configuration
  • Support for different languages and formats

Text Chunking

  • Multiple chunking strategies:
    • Fixed-size chunking
    • Paragraph-based chunking
    • Semantic chunking based on content
  • Configurable chunk sizes and overlaps

Metadata Extraction

  • Automatic extraction of metadata from text
  • Support for custom metadata fields
  • Integration with document processing

Text Analysis

  • Text similarity calculation using Levenshtein distance
  • Keyword extraction from text content
  • Text summarization capabilities

Implementation Details

Documentation-Driven Development

The implementation follows the specifications outlined in the implementation plan:

Each feature was designed based on these requirements, with a focus on flexibility and extensibility.

Test-Driven Development

The implementation was guided by comprehensive tests:

  • Unit tests for all pure functions
  • Integration tests for the text processing module
  • Tests for different chunking strategies
  • Tests for metadata extraction and text analysis

All tests are passing, ensuring the reliability of the implementation.

Technical Details

Architecture

  • Pure functions for core text processing operations
  • Modular design for easy extension
  • Clear separation of concerns

Performance Considerations

  • Efficient algorithms for text processing
  • Minimal memory footprint
  • Optimized for large text documents

Next Steps

After merging this PR, the text processing module can be integrated with:

  1. The vector store for improved document indexing
  2. The search functionality for better query processing
  3. The MCP server for enhanced knowledge management

Dependencies

  • Added uuid crate for document ID generation

Testing

All tests are passing, including:

  • 7 integration tests in
  • 5 unit tests in the module's test suite

@whitmo whitmo merged commit a03ccf8 into main Mar 15, 2025
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