Three Strategies for Improving Document Processing Performance in RAG Systems
The following optimization measures can be taken to address the problems of slow document processing and high memory usage:
- Strategic chunking: Choose a chunking strategy based on the type of document (e.g., research strategy for academic papers).
- Selective Feature Extraction: Extract only essential features (keywords/entities) with the -extractors parameter.
- parallel processing technology: Enable multithreading by adding the -workers 4 parameter
Examples of specific optimization commands:
- Efficient processing of technical documentation: uv run python rag/cli.py ingest tech_docs/ -strategy technical -extractors keywords -workers 4
- Memory optimization mode: add -low-memory parameter to enable streaming processing
Supplementary proposals: PDF documents can be pre-pdfcpu tool to split the chapter, and then batch imported!
This answer comes from the articleLlamaFarm: a development framework for rapid local deployment of AI models and applicationsThe
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