Building Advanced Reasoning Agent Teams with Centralized Prompt Management using Agno and mlflow

Demonstrates building a multi-agent reasoning system using the Agno framework, where specialized AI agents collaborate to solve complex problems. The system integrates MLflow for centralized prompt management and versioning, uses Claude and OpenAI models for reasoning capabilities, and stores outputs in Qdrant vector database for long-term memory. Features three coordination modes (route, collaborate, coordinate) and includes practical implementation for financial analysis comparing NVIDIA and Tesla stocks.