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Tag: RAG

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Hamming AI: Revolutionizing Prompt Engineering and AI Agent Reliability

Implementing Retrieval-Augmented Generation (RAG) and AI agents can be a complex and intricate process. The performance of a Language Learning Model (LLM) can vary significantly with minor adjustments to parameters like function call definitions or retrieval settings. Hand-crafting prompts often involve extensive trial and error, and updates to models can render previously effective prompts useless.…
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