Rbs-r Pdf Review

chunks = [] current_chunk = ""

if current_chunk: chunks.append(current_chunk)

for segment in splits: # Re-add delimiter except for first segment if current_chunk: segment = delim + segment temp_chunk = current_chunk + segment if len(tokenizer.encode(temp_chunk)) <= max_size: current_chunk = temp_chunk else: if current_chunk: chunks.append(current_chunk) # Recursively split the oversized segment at the next level if level + 1 < len(delimiters): chunks.extend(rbsr_split(segment, max_size, level + 1)) else: # Force split at word boundary chunks.append(segment) current_chunk = "" rbs-r pdf

# Use the current level's delimiter delim = delimiters[level][0] splits = text.split(delim)

delimiters = [ ('\n## ', 'section'), # High level ('\n\n', 'paragraph'), # Medium level ('. ', 'sentence'), # Low level (' ', 'word') # Minimum level ] chunks = [] current_chunk = "" if current_chunk: chunks

Use pdfplumber or unstructured.io to extract bounding boxes . RBS-R cares about Y-coordinates. If two text blocks have the same Y-axis, they are the same line. If the Y-axis delta is large, it’s a new paragraph.

If you are building a RAG pipeline over financial reports, academic papers, or legal documents, implement RBS-R on Day 1. It requires 50 lines of code and increases your answer_ relevancy score by 15–20% without a single fine-tuning step. If two text blocks have the same Y-axis,

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 .

return chunks The magic of RBS-R for PDFs isn't just the splitting; it's the inheritance .