Get up to speed with Retrieval-Augmented Generation (RAG) in just two hours using Langchain. RAG lets your LLM tap into an external, authoritative knowledge base—boosting accuracy and relevance without retraining the model. Dive into the GitHub repo for hands-on tutorials and ready-made code samples.
You’ll walk through optimizing LLM outputs by referencing curated data outside the training set, making it ideal for company wikis, research archives or any niche domain. It’s a lean, cost-effective way to supercharge your AI projects without blowing up your compute bill.
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