Prompt Engineering and Llama Index
Daniel explains how prompt engineering is a crucial aspect of LM application development and how it complements the functionalities of Llama Index. He discusses the challenges of feeding in context that exceeds the prompt window and explores strategies like retrieval and synthesis to overcome this limitation.In this clip
From this podcast
Practical AI
Data augmentation with LlamaIndex
Related Questions
What is the best insight on prompt engineering and engaging large language models (LLMs)?
Is there anyone taking a different approach to prompt engineering for large language models that makes the process more accessible to a wider audience, as discussed in the episode Collaboration & evaluation for LLM apps and the clip Fine Tuning Insights?
Is there anyone taking a different approach to prompt engineering for large language models that makes the process more accessible to a wider audience, as discussed in the episode Holistic Evaluation of Generative AI Systems // Jineet Doshi // #280 and the clip LLMs as Jury, as well as in the episode Collaboration & evaluation for LLM apps and the clip Fine Tuning Insights?