# Adaptive RAG agent for query classification and response generation
This automation workflow enables precise, context-aware responses to diverse user queries by applying adaptive RAG strategies based on query type. Designed for AI developers and SaaS platforms requiring intelligent, scalable support systems.
## Who it´s for
- AI developers building adaptive chatbots
- Companies using RAG for customer support
- Analysts needing differentiated query processing
- Knowledge base owners aiming to improve AI-powered search
- SaaS products with multi-functional support needs
## What the automation does
- Receives user input via chat, API, or webhook
- Classifies query into one of four types: factual, analytical, opinion-based, or contextual
- Applies tailored retrieval strategy (e.g., sub-questions for analytics)
- Modifies search query and retrieves documents from Qdrant using Gemini embeddings
- Generates final response using retrieved context and conversation history
- Ensures relevance and depth through dynamic prompt engineering
## What´s included
- Ready-to-use n8n workflow with LangChain and adaptive RAG logic
- Trigger handlers: chat_input, http_webhook, execute_workflow_trigger
- Integrations with Google Gemini, Qdrant, n8n Chat Interface, and Webhook API
- Basic setup and adaptation guide
## Requirements for setup
- n8n instance with LangChain node access
- Google Gemini API key
- Configured Qdrant vector database with embedded documents
- Understanding of vector databases and LLM workflows
## Benefits and outcomes
- Higher response accuracy through adaptive retrieval
- Reduced support load via autonomous query handling
- Improved UX with personalized, context-rich answers
- Multi-channel scalability (chat, CRM, API)
- Handling of complex analytical and opinion-based queries without manual intervention
## Important: template only
Important: you are purchasing a ready-made automation workflow template only. Rollout into your infrastructure, connecting specific accounts and services, 1:1 setup help, custom adjustments for non-standard stacks and any consulting support are provided as a separate paid service at an individual rate. To discuss custom work or 1:1 help, contact via chat
query classification
adaptive RAG
user query processing
AI agent with memory
vector database search
context-aware responses
dialogue history processing
Qdrant integration
Google Gemini embeddings
n8n workflow
chatbot with classification
API query handling
intelligent knowledge base search
question type analysis
LLM response generation
multi-strategy processing
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