How to Design an Autonomous Multi-Agent Data and Infrastructure Strategy System Using Lightweight Qwen Models for Efficient Pipeline Intelligence?

A new multi-agent data and infrastructure strategy system has been developed utilizing the lightweight Qwen2.5-0.5B-Instruct model, enabling efficient autonomous management of complex data pipelines. This system employs a flexible framework of specialized large language model (LLM) agents responsible for tasks such as data ingestion, quality analysis, and infrastructure optimization, coordinated by an orchestrator to facilitate seamless multi-agent collaboration. Demonstrated through practical applications in e-commerce and IoT environments, this approach showcases how autonomous decision-making can significantly streamline data operations, reduce manual intervention, and enhance pipeline intelligence.