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Optimizing Documents for RAG Indexing

Improve RAG answer quality by preparing your documents before ingestion.

Retrieval Augmented Generation (RAG) combines the power of Natural Language Processing (NLP) with the capabilities of Large Language Models (LLMs) to let applications understand natural speech and learn from ingested knowledge.

Even with the best LLM, the model is unlikely to be trained or optimized for your specific use case. Tog get the gest results, you you need to refine your inputs before documents are processed. You will still benefit from NLP and document chunking but some upfront preparation is required.

This section covers everything you need to know about document optimization:

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