chunk导致知识被隔断? #3729
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To address the issue of incomplete matches due to chunking in version 2.2, consider implementing these strategies:
Here's an example function for creating chunks with overlap: def create_chunks_with_overlap(text, chunk_size, overlap_size):
chunks = []
i = 0
while i < len(text):
if i + chunk_size + overlap_size > len(text) and i != 0:
chunks.append(text[i - overlap_size:])
break
chunks.append(text[i:i+chunk_size+overlap_size])
i += chunk_size
return chunks This function demonstrates generating chunks with an overlap, but integrating it with your system will require adjustments to handle dynamic chunk sizes and overlaps effectively. Remember, the goal is to ensure that the chunking process does not compromise the integrity of the information, especially for key terms that are crucial for matching. Adjusting your chunking strategy and matching algorithms as suggested should help mitigate the issue of incomplete matches due to chunk boundaries. Sources
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我用的好像是2.2的版本把 然后源码是对输入进行了chunk的切分。
然后现在存在一个问题,不知道怎么优化
假设chunk是250字,文档是1000字(方便说明,不考虑overlap的情况),那么就会被切分成4块(这里用1,2,3,4标记),然后会对问题进行匹配,由于文本开头和结尾大概会有一些关键词在里面,可以匹配,然后3,4可能就不在这个关键词里,导致匹配不完整,存在信息缺失,比方说就匹配到1,4,然后真正的答案是在2,3里面 ,那么LLM没有得到2,3的信息,肯定答不对这个问题,那么要怎么解决这个问题呢?
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