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Retrieval-Augmented Generation: Keep Answers Grounded in Documents
Retrieval-augmented generation (RAG) combines document retrieval with language-model generation. Instead of asking a model to rely only on its learned knowledge, the application retrieves relevant passages and supplies them as context.A typical pipeline extracts text, splits it into chunks, generates embeddings, and stores them in a searchable index. At query time, the system retrieves candidate c...
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Posted By webguru_aicloud
1 week agoWriting Better AI Prompts With Context and Acceptance Criteria
A useful prompt communicates the task, context, constraints, and expected output. More words do not automatically make a prompt better; the goal is to remove ambiguity that would materially change the result.Describe the audience and intended use, then provide the relevant source material. Specify constraints such as tone, length, supported technologies, or facts that must not be invented. If the...
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