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Optimizing Retrieval Agents with Shirley Wu - Weaviate Podcast #115!

Weaviate Podcast

CHAPTER

Optimizing Retrieval Agents through Prompt Strategies

This chapter examines the intricacies of causal inference in the development of retrieval agents, particularly under the Stark benchmark. The discussion covers the integration of diverse data sources and the concept of contrastive prompt optimization to enhance language models' performance in responding to queries. Additionally, it highlights the evolutionary processes in prompt development, emphasizing the analysis of action sequences and the application of advanced methodologies for improving agent reasoning.

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