First Coffee Break

Welcome back from your coding marathon! It's time for a well-deserved coffee break. In this chapter, we take a step back to review what you've accomplished and where you stand in building your very own AI application.

Learnings

You'll find a recap of the key insights gained so far, including how to interact with language models, build conversation history, and create embeddings for information retrieval. You’ll also see why dataset quality is crucial and how it affects the performance of your RAG system.

Status of Our Application

We’ll discuss the current state of your application, highlighting its capabilities as well as areas that need improvement before it’s ready for real-world use. This includes issues with conversation history, data retrieval mechanisms, and response accuracy.

Takeaways

This section offers valuable lessons learned from working on this project. You'll discover why creating a robust RAG solution isn't always straightforward and the importance of treating AI models as potentially unreliable sources that require careful validation.

Our Next Steps

Finally, we outline what’s next in your journey. We’ll explore different language models to better understand their behavior and limitations. Then, you’ll dive into Tool Calling, a powerful technique for enhancing your application's functionality.

So grab a cup of coffee, take a deep breath, and get ready to reflect on your progress and plan the exciting steps ahead!