Adaptive RAG Strategy with Query Classification & Retrieval (Gemini & Qdrant)

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 a sub-workflow). 2. **Classify Query:** First, the workflow classifies the query into a predefined category. This template uses four examples: * **Factual:** For specific facts. * **Analytical:** For deeper explanations or comparisons. * **Opinion:** For subjective viewpoints. * **Contextual:** For questions relying on specific background. 3. **Select & Adapt Strategy:** Based on the classification, it selects a corresponding strategy to prepare for information retrieval. The example strategies aim to: * **Factual:** Refine the query for precision. * **Analytical:** Break the query into sub-questions for broad coverage. * **Opinion:** Identify different viewpoints to look for. * **Contextual:** Incorporate implied or user-specific context. 4. **Retrieve Info:** Uses the output of the selected strategy to search the specified knowledge base (Qdrant vector store - change as needed) for relevant documents. 5. **Generate Response:** Constructs a response using the retrieved documents, guided by a prompt tailored to the original query type. By adapting the retrieval strategy, this workflow aims to provide more relevant results tailored to the user's intent. ## Usage & Flexibility * **Sub-Workflow:** Designed to be called from other n8n workflows, passing `user_query`, `chat_memory_key`, and `vector_store_id` as inputs. * **Chat Testing:** Can also be triggered directly via the n8n Chat interface for easy testing and interaction. * **Customizable Framework:** The query categories (Factual, Analytical, etc.) and the associated retrieval strategies are examples. You can modify or replace them entirely to fit your specific domain or requirements. ## Requirements * **Credentials:** You will need API credentials configured in your n8n instance for: * Google Gemini (AI Models) * Qdrant (Vector Store)