The overall architecture of the RAG agents is shown in the figure above. Retrieval-augmented User Proxy agent, called RetrieveUserProxyAgent, and a Retrieval-augmented AssistantĪgent, called RetrieveAssistantAgent, both of which are extended from built-in agents from AutoGen. In this blog post, we introduce RAG agents ofĪutoGen that allows retrieval-augmented generation. Limitations of LLMs by incorporating external documents. Retrieval augmentation has emerged as a practical and effective approach for mitigating the intrinsic We also showcase two advanced usage of RAG agents, integrating with group chat and building a Chat.We showcase customizations of RAG agents, such as customizing the embedding function, the text.We introduce RetrieveUserProxyAgent and RetrieveAssistantAgent, RAG agents of AutoGen thatĪllows retrieval-augmented generation, and its basic usage.
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