Introduction

The world of artificial intelligence (AI) is evolving day by day, and LangChain is attracting a lot of attention. LangChain is a framework for streamlining application development using large-scale language models (LLMs). This article will explain LangChain in detail through 15 chapters, from the basics to applications.

We will add a new chapter to the article to explain the installation of LangChain. Below is a proposal for a new chapter that fits the existing article structure:

Introduction 2. Installing and configuring LangChain

To use LangChain, you must first properly install it and configure the environment. Below we will explain the installation steps and basic environment settings.

LangChain can be easily installed using pip, a Python package manager, by running the following command:

pip install langchain

If you use the OpenAI API, please also install the following packages:

pip install openai

Setting environment variables When using LangChain, especially when using external APIs, you need to set the appropriate environment variables. For example, to set your OpenAI API key:

api_key = os.getenv("OPENAI_API_KEY")

Basic use case

Once the installation and environment configuration are complete, you can check the operation of LangChain with a simple code like the following:

from langchain.llms import OpenAI

llm = OpenAI(temperature=0.9)
text = "What would be a good company name for a company that makes colorful socks?"
print(llm(text))

This code uses a model from OpenAI to generate names for companies that manufacture colorful socks.

Important points to note LangChain is under active development, so we recommend regularly updating to the latest version. Depending on the API or service you use, you may need to install or configure additional packages. There may be fees for using the API, so be sure to check the terms of use and pricing. With these steps, the basic environment for using LangChain will be ready.