The knowledge chunk splitter uses the same AI splitting method as the knowledge base import to divide your content into complete knowledge blocks. You can paste text directly into the input box, or upload txt, docx, xlsx, pptx, or pdf files — the system first extracts the plain text from each file before processing. After you press send, the screen streams the splitting progress: the AI first scans the whole document to build a chapter structure map, then splits by priority — by chapter when the text has chapters, by paragraph when it has no chapters, and by concept when it has neither chapters nor paragraphs — so that each block presents one complete chapter, paragraph, or concept, and automatically generates search keywords that include the book title and chapter names. When splitting is done, the screen shows all knowledge blocks in JSONL format identical to the downloadable file, and a JSONL file is generated with a download link. Each line is one knowledge block record with output (the original text of the block), keyword, remark (x/y, marking which part of the content it is out of the total), and vector (the block content encoded into an embedding by an AI vector model, ready for vector search) fields. The resulting JSONL file can be imported into a knowledge base directly with the knowledge base's Import JSON feature, or used for RAG retrieval and fine-tuning data preparation. Long content is analyzed window by window, so please wait for the stream to finish.