Recursive Language Models (RLMs): The Answer to Context Rot in Large Language Models

It looks like the code for recursive_aggregate is cut off. Let's complete it and ensure that all necessary functions are defined properly to handle recursive aggregation of extracted information.

Here’s how you can finish the recursive_aggregate function and add a simple implementation for generate_final_answer.

Complete Code

python
 
1import openai
2
3def chunk_document(document: str, chunk_size: int = 3000, overlap: int = 200) -> List[str]:
4    """Split document into overlapping chunks. Uses semantic boundaries (section breaks) when possible."""
5    # Try to split on section boundaries first
6    sections = document.split("-----" * 4)
7    
8    chunks = []
9    current_chunk = ""
10    
11    for section in sections:
12        if count_tokens(current_chunk + section) > chunk_size:
13            if current_chunk.strip():
14                chunks.append(current_chunk.strip())
15            current_chunk = section
16        else:
17            current_chunk += "\n\n" + section
18    
19    if current_chunk.strip():
20        chunks.append(current_chunk.strip())
21    
22    return chunks
23
24def extract_from_chunk(chunk: str, question: str, chunk_index: int) -> str:
25    """Process a single chunk and
26
27[Read the full article at Towards AI - Medium](https://pub.towardsai.net/recursive-language-models-rlms-the-answer-to-context-rot-in-large-language-models-b5fb9d302cb4?source=rss----98111c9905da---4)
28
29---
30
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