I Built an Adaptive RAG System That Routes Queries by Complexity.

📰 Medium · Python

Learn how to build an adaptive RAG system that routes queries by complexity using a Go + Python architecture and gRPC

advanced Published 13 Jun 2026
Action Steps
  1. Design a three-tier retrieval system to handle complex queries
  2. Implement a Go + Python architecture using gRPC for efficient communication
  3. Develop an adaptive routing system that directs queries based on complexity
  4. Benchmark the system using 180 questions and three frontier LLMs
  5. Evaluate and refine the system's performance based on the benchmark results
Who Needs to Know This

This benefits software engineers and AI researchers working on complex query systems, as it provides a scalable and efficient solution for routing queries

Key Insight

💡 Using a three-tier retrieval system and adaptive routing can significantly improve the efficiency of complex query systems

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🤖 Built an adaptive RAG system that routes queries by complexity! 🚀

Key Takeaways

Learn how to build an adaptive RAG system that routes queries by complexity using a Go + Python architecture and gRPC

Full Article

Three retrieval tiers, a Go + Python architecture over gRPC, and an honest benchmark across 180 questions judged by three frontier LLMs. Continue reading on Generative AI »
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