This repository serves as an educational resource and technical guide for developers learning to integrate large language models into software applications. It provides practical lessons and code examples focused on building systems that perform automated text generation, data analysis, and interactive chat tasks.
The project functions as a framework for understanding how to connect applications to external artificial intelligence services. It covers the implementation of secure authentication, the orchestration of network requests, and the configuration of model parameters such as temperature and output length to control response characteristics.
The materials also detail how to handle multimodal inputs, enabling applications to process and interpret visual data alongside text prompts. Additionally, the guide demonstrates how to implement real-time streaming to deliver model responses incrementally, reducing perceived latency in user interfaces. The content is provided as a collection of Jupyter Notebooks designed for direct study and experimentation.
