This repository contains course materials for learning the Langchain concepts. Below are the Jupyter notebooks used in the course with a brief description of each:
-
models_basics.ipynb: This notebook introduces the fundamental concepts of models in Langchain, detailing their structure and functionality.
-
models_prompts_parsers.ipynb: This notebook delves into the basics of models in Langchain, with a focus on prompts and parsers.
-
chains.ipynb: This notebook introduces chains in Langchain, elucidating their function and importance in the structure of the language model. We learn about the different types of chain and their use.
-
memory.ipynb: This notebook explores the memory aspects of Langchain, explaining how data is stored and retrieved.
-
indexes.ipynb: This notebook covers the concept of indexes in Langchain, focusing on their creation, usage, and maintenance.
-
agents.ipynb: This notebook explains the concept of agents in Langchain, covering how they interact and communicate within the system.
-
chatgpt_plugins.ipynb: This notebook provides an overview of how to utilize plugins with ChatGPT in Langchain for enhanced functionality.
-
evaluation.ipynb: This notebook discusses the methods and strategies for evaluating performance in Langchain.
Note: The descriptions above are general and might not fully capture the content of each notebook. Please refer to the notebooks themselves for detailed information.