Adaptive Retrieval-Augmented Generation (RAG) Query Strategy
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Dynamically selects the best retrieval strategy based on query type for improved RAG performance.
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About This Workflow
Overview
This workflow implements an Adaptive Retrieval-Augmented Generation (RAG) system. It intelligently classifies incoming user queries into four categories: Factual, Analytical, Opinion, and Contextual. Based on this classification, it then applies a specialized retrieval strategy to enhance the query, aiming to provide more accurate, comprehensive, or contextually relevant responses from a knowledge base.
Key Features
- Query classification into Factual, Analytical, Opinion, and Contextual categories.
- Specialized retrieval strategies for each query type:
- Factual: Focuses on precision and direct information retrieval.
- Analytical: Breaks down complex queries into sub-questions for comprehensive coverage.
- Opinion: Identifies diverse perspectives on subjective topics.
- Contextual: Infers and integrates user-specific context for tailored responses.
- Dynamic selection of prompt and output instructions based on the chosen strategy.
How To Use
- Import the workflow: Load this JSON into your n8n instance.
- Configure Credentials: Ensure you have the necessary AI model credentials set up in n8n for the 'Query Classification' and 'Strategy' nodes.
- Connect Data Sources: Integrate your knowledge base or data sources into the relevant nodes where information is retrieved or processed.
- Trigger the Workflow: Send user queries to the 'Chat' webhook trigger to initiate the adaptive RAG process.
Apps Used
Workflow JSON
{
"id": "376317be-83cf-42d2-af9d-4989f285f2c3",
"name": "Adaptive Retrieval-Augmented Generation (RAG) Query Strategy",
"nodes": 0,
"category": "AI & Machine Learning",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: 376317be-83cf...
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