If you have a bulleted list with 50 items, a recursive split might try to split at the sentence level inside a bullet, breaking the list semantic. Pre-process lists. Convert \n- Item into a delimiter like [LIST_BREAK] before splitting, then reconstruct. Conclusion: Stop Chunking, Start Structuring RBS-R is not an LLM. It’s not a vector database. It is a hydraulic press for your PDFs—it applies pressure until the content fits the context window, but it always breaks at the joints .
chunks = [] current_chunk = ""
if current_chunk: chunks.append(current_chunk) rbs-r pdf
def rbsr_split(text, max_size=1000, level=0): # Level 0: Section (## Header) # Level 1: Paragraph (\n\n) # Level 2: Sentence (.) # Level 3: Word ( ) if len(tokenizer.encode(text)) <= max_size: return [text] If you have a bulleted list with 50
# Use the current level's delimiter delim = delimiters[level][0] splits = text.split(delim) Conclusion: Stop Chunking, Start Structuring RBS-R is not
Beyond Chunking: Why RBS-R (Recursive Binary Splitting-RAG) is the PDF Preprocessor You’re Missing Tagline: Stop forcing square chunks into round LLM context windows. Introduction: The PDF Paradox PDFs are the cockroaches of the digital world—indestructible, universally hated, and everywhere. In enterprise RAG (Retrieval-Augmented Generation), the PDF remains the primary data source. Yet, most pipelines handle PDFs with a fatal flaw: naive fixed-size chunking .