Learn LLM Fundamentals and Build a RAG Application from Scratch

PDF parsing can be messy, leading to poorly formatted text chunks (especially with tables or multi-column layouts).

Start with plain text and markdown first to validate your logic. For PDFs, try specialized loaders like PyMuPDFLoader in LangChain.

Suboptimal chunking strategy might cut sentences in half, causing the LLM to lose context.

Use LangChain's RecursiveCharacterTextSplitter with an appropriate chunk overlap (e.g., 200 characters) to preserve context between chunks.

Accidentally embedding a massive number of documents at once could result in unexpected API costs.

Test your embedding loop with just 1-2 small documents first. Monitor your API dashboard billing limits.