Split Japanese documents into RAG chunks with overlap
Quiet Works Lab
Cleans Japanese documents and splits them into chunks for retrieval-augmented generation (RAG). Chunks end at sentence boundaries (。！？ and line breaks) instead of in the middle of a word, with an overlap you choose, and keep the metadata fields you name (for example url and title). Each chunk row has its position in the document, ready to embed and load into a vector database.
Input
Output fields
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The Japanese Text Normalizer & RAG Chunker Actor is ready to run with the inputs already set for "Split Japanese documents into RAG chunks with overlap". Sign up or log in and you'll land in Apify Console with a copy of this exact task.
Start the "Split Japanese documents into RAG chunks with overlap" task
The Japanese Text Normalizer & RAG Chunker Actor will start running based on the input automatically. You can also change all the input fields, like texts, split into chunks, and more, to match your specific use case.
Receive the "Split Japanese documents into RAG chunks with overlap" output
Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as document index, chunk index, characters, and more.
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The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Split Japanese documents into RAG chunks with overlap" task via API.
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The Japanese RAG chunking task splits after 。！？ and at line breaks, never inside 「」 or （）. Only a sentence longer than the chunk size is cut, preferably after 、 or a space.
The Japanese RAG chunking task accepts 200 to 100,000 characters per chunk, with an overlap of up to a third of the chunk size. This example uses 200 with an overlap of 40; choose the size your embedding model and retrieval work best with.
Yes. When you read from a dataset, the Japanese RAG chunking task copies the metadata fields you choose, such as url and title, into every chunk row.