ALIBABA · objective · 20% of the exam
LLM Retrieval-Augmented Generation — LLM Engineer (Professional)
The official ALIBABA documentation our LLM Retrieval-Augmented Generation practice questions are cited to. Review the primary sources, then practise.
Official references for this objective
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Alibabacloud — Knowledge base - Alibaba Cloud Model Studio - Alibaba Cloud Documentation Center
if you add the product name as metadata to all chunks, the knowledge base can accurately filter for chunks that are related to "Product A"
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Alibabacloud — Deploy RAG chatbot on PAI-EAS with vector database - Platform For AI - Alibaba Cloud Documentation Center
The LLM Integrated Deployment option deploys the RAG service and the LLM in the same EAS service instance.
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Alibabacloud — Deploy and call a RAG-based LLM chatbot service - - Alibaba Cloud Documentation Center
LLM-Separated Deployment : Deploys only the RAG service, while the large language model runs as a separate service.
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Alibabacloud — Building a RAG Pipeline on Alibaba Cloud with Vector Search - Alibaba Cloud Community
retrieval must honor permissions at query time rather than relying on the model to “do the right thing.” Storing ACL metadata with embeddings and filtering
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Alibabacloud — Embedding - Alibaba Cloud Model Studio - Alibaba Cloud Documentation Center
The generation cost is unchanged , and the API call overhead is identical to the single-vector mode. Requires more storage , and the system architecture
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Alibabacloud — What is OpenSearch LLM-Based Conversational Search Edition - OpenSearch - Alibaba Cloud Documentation Center
Multimodal understanding lets users search with product images as well as text. Results include direct product links for one-click access to the target item.