In this post, we continue our journey through LangChain’s Quickstart guide, exploring how to enhance your chains by integrating conversation history.

Recap of Our Progress

Here’s what we’ve set up so far:

• retriever: Retrives a list of relevant documents based on the input text.
• document_chain: Generates LLM responses using the user’s questions and the list of documents.
• create_retrieval_chain: Combines retriever and document_chain to answer queries by referencing documents.

In this series, we’ll explore the ‘Quickstart’ section of the LangChain documentation.
In this article, we discuss how to expand LLM knowledge using information on the internet.

Below, I outline the sections of code from our previous article that we’ll use again in this article.

In this series, we’ll explore the ‘Quickstart’ section of the LangChain documentation.
In this article, we focus on LLMs, prompt templates, and chains.

1. Installation

To get started, install langchain and its OpenAI extension, langchain-openai:

Continuing from the previous “Hello World” program, this session dives into building a memo app with the following functionalities:

1. A text box for entering a memo.
2. A shortcut (Control+S) for saving the contents of the text box to a file.
3. Displaying the file contents in the text box upon app launch.

1. Setting Up the Text Box

Let’s get started by building on our previous program. First, we create the root window and place a frame inside it. Within this frame, we’ll set up the text box for memo entry.

In this series, we’ll be leveraging Tkinter, Python’s built-in GUI library, to create a memo app.

Getting Started with the “Hello World” Program

Let’s begin by exploring how to use Tkinter with the following “Hello World” program outlined in its official documentation.

In this article, I’ll show you how to skip the execution of cells in Jupyter Notebook based on certain conditions.
The methods described here are applicable to Google Colaboratory and Kaggle Notebooks.

How to Skip a Cell Execution

To skip cell execution, create a custom magic command as follows:

1. First, create a skip magic command that does nothing.

   python

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    Jupyter