LectuLibre Builds Chunking Pipeline to Translate Full Books Using Claude AI

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Startup LectuLibre developed a multi-stage text-chunking pipeline to translate entire 300-page books using Anthropic's Claude AI models. A full book typically runs 90,000–120,000 words, or up to 160,000 tokens, making single-API-call translation impractical due to rate limits, high costs, and degraded output quality. The team initially split text by paragraphs at roughly 10,000-token intervals but found this broke sentences at boundaries and lost narrative context across chapters. They improved accuracy by switching to the tiktoken tokenizer for precise token counts and introduced overlapping paragraphs between chunks to preserve continuity. Each chunk was also prefixed with a preamble containing the book's title, author, and a recurring-terms glossary to maintain consistent character names and terminology throughout the translation.

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