A guide for modeling and orchestrating agents using design patterns (Evaluator-Optimizer, Context-Augmentation, Prompt-Chaining, Parallelization, Routing, and Orchestrator-Workers).
Digital scams cause devastating impacts across society. MINERVA is an AutoGen implementation of seven agents that helps users identify scam attempts, achieving higher accuracy than baseline prompting methods (88.3% vs. 69.5%).
Combining knowledge graphs with embeddings to enable multi-hop reasoning and contextual understanding in LLMs, while supporting natural language querying.