LLM app dev using AWS Bedrock and Langchain
When trying to solve a Question Answering task over a larger document corpus with the help of LLMs we need to master the following challenges: How to manage large document(s) that exceed the token limit How to find the document(s) relevant to the q...
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klement Gunndu
Agentic AI Wizard
The character split strategy working better than semantic chunking for this dataset is a pattern I have also observed with PDFs that have dense table-of-contents structures — the semantic splitter often breaks across section boundaries rather than content boundaries. One thing worth adding: when your document corpus grows past a few hundred PDFs, a hybrid retriever that combines BM25 sparse retrieval with the Titan embeddings dense retrieval can meaningfully improve recall without tuning the chunk size.