Adaptive RAG strategy with query classification & retrieval (Gemini & Qdrant)
n8n30 modulesv1.0agentchatTriggerembeddingsGoogleGeminiexecuteWorkflowTriggerlmChatGoogleGeminimemoryBufferWindowrespondToWebhooksetsummarizeswitchvectorStoreQdrant
This n8n workflow implements a version of the Adaptive Retrieval-Augmented Generation (RAG) framework. It recognizes that the best way to retrieve information often depends on the type of question asked. Instead of a one-size-fits-all approach, this workflow adapts its strategy based on the user's query intent. 🌟 How it Works 1. Receive Query: Takes a user query as input (along with context like a chat session ID and Vector Store collection ID if used as sub-workflow). 2. Classify Query: First,
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