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This would be a game-changer for handling massive files without blowing up memory—love the idea! |
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Feature request
Introduce support for semantic chunking in LangChain's iterator-based file processing. This enhancement would allow LangChain to efficiently process large files without loading them entirely into memory by leveraging the iterator approach. By integrating semantic chunking, the system can break down content into meaningful segments, enhancing contextual understanding for language models while maintaining scalability for large files.
Motivation
Benefits:
Handle large files efficiently by processing data in chunks using an iterator.
Enable context-aware chunking without memory overload.
Improve overall model comprehension for large documents.
This approach aligns with LangChain's focus on scalable, efficient language model integrations for diverse applications.
Proposal (If applicable)
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