This two-hour crash course walks you through Retrieval-Augmented Generation (RAG) with Langchain, showing how to hook your LLM up to external knowledge bases (no retraining required) so it always stays on point. All the code lives in a handy GitHub repo for you to clone and play with.
RAG supercharges your model by letting it pull in domain-specific or internal docs before answering, boosting relevance, accuracy, and cost-efficiency without busting your budget.
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