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Smart Chat Routing Between Gemini and GPT Models Based on Query Complexity

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Created by: Daniel Nkencho || daniel-automates

Daniel Nkencho

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Last update 2 days ago

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Adaptive LLM Router for Optimized AI Chat Responses

Elevate your AI chatbots with intelligent model selection: automatically route simple queries to cost-effective LLMs and complex ones to powerful ones, balancing performance and expenses seamlessly.

What It Does

This workflow listens for chat messages, uses a lightweight Gemini model to classify query complexity, then selects and routes to the optimal LLM (Gemini 2.5 Pro for complex, OpenAI GPT-4.1 Nano for simple) to generate responses—ensuring efficient resource use.

Key Features

  • Complexity Classifier - Quick assessment using Gemini 2.0 Flash
  • Dynamic Model Switching - Routes to premium or budget models based on needs
  • Chat Trigger - Webhook-based for real-time conversations
  • Current Date Awareness - Injects $now into system prompt
  • Modular Design - Easy to add more models or adjust rules
  • Cost Optimization - Reserves heavy models for demanding tasks only

Perfect For

  • Chatbot Developers: Build responsive, cost-aware AI assistants
  • Customer Support: Handle routine vs. technical queries efficiently
  • Educational Tools: Simple facts vs. in-depth explanations
  • Content Creators: Quick ideas vs. detailed writing assistance
  • Researchers: Basic lookups vs. complex analysis
  • Business Apps: Optimize API costs in production environments

Technical Highlights

Harnessing n8n's LangChain nodes, this workflow demonstrates:

  • Webhook triggers for instant chat handling
  • Agent-based classification with strict output rules
  • Conditional model selection for AI chains
  • Integration of multiple LLM providers (Google Gemini, OpenAI)
  • Scalable architecture for expanding model options

Ideal for minimizing AI costs while maximizing response quality. No coding required—import, configure credentials, and deploy!