Generative AI with Python

3.11    Summary

In this chapter, we embarked on a comprehensive exploration of LLMs.

We began in Section 3.1 with a brief history of LLMs, tracing their evolution and the advancements that have led to their current state. This foundational knowledge sets the stage for understanding the practical aspects of working with LLMs. We then delved, in Section 3.2, into the technical implementation of LLMs via Python. This section provided insights into how to trigger LLM calls, emphasizing the versatility and adaptability of the process. By showcasing how different providers such as OpenAI or Groq can be employed, we highlighted the flexibility to integrate any LLM of your choice, thus broadening the scope of application.

In Section 3.3, we explored ...