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Document-Summarization
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Text Chunking for LLM Context
xberg-chunking
xberg-io/xberg
189
This skill enables splitting extracted text into optimized chunks for LLM context windows or RAG ingestion pipelines. It supports configurable chunk sizes, overlap settings, and various chunker types including text, markdown, YAML, and semantic splitting. Users can utilize token-based sizing for specific models or standalone commands for pre-existing text. Ideal for preparing documents for vector stores or summarization tasks.
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