Building a Multimodal RAG Pipeline with NVIDIA NeMo Retriever, Hosted NIMs, LanceDB, Reranking, and Grounded Generation

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Building a Multimodal RAG Pipeline with NVIDIA NeMo Retriever, Hosted NIMs, LanceDB, Reranking, and Grounded Generation
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Summary

<p>In this tutorial, we build an advanced multimodal retrieval-augmented generation pipeline with NVIDIA NeMo Retriever. We begin by configuring a Python 3.12 environment, installing the required packages, and performing offline PDF text extraction without relying on a GPU or external API key. We then extend the workflow with hosted NVIDIA NIM endpoints to detect page [&#8230;]</p> <p>The post <a href="https://www.marktechpost.com/2026/08/07/building-a-multimodal-rag-pipeline-with-nvidia-nemo-retriever-hosted-nims-lancedb-reranking-and-grounded-generation/">Building a Multimodal RAG Pipeline with NVIDIA NeMo Retriever, Hosted NIMs, LanceDB, Reranking, and Grounded Generation</a> appeared first on <a href="https://www.marktechpost.com">MarkTechPost</a>.</p>

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