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Retrieval-Augmented Generation (RAG) is rapidly emerging as a robust framework for organizations seeking to harness the full power of generative AI with their business data. As enterprises seek to ...

In benchmark evaluations, Pleias-RAG-350M and Pleias-RAG-1B outperform most open-weight models under 4 billion parameters, including Llama-3.1-8B and Qwen-2.5-7B, on tasks such as HotPotQA ...

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Comparing it to custom-built RAG systems or alternative solutions can help you make an informed decision. The Responses API excels in pairing document retrieval with LLMs like GPT-4 to generate ...