# Installing LangChain: How to install LangChain and get started with it

## Introduction

LangChain is an open-source framework for developing applications powered by large language models (LLMs). It provides a high-level API that makes it easy to chain together multiple LLMs, as well as other data sources and tools, to create complex applications.

This blog post will show you how to install LangChain and get started with it. We will cover the following topics:

* How to install LangChain using Pip, Conda, or from source
    
* How to import the `langchain` module
    
* How to create a chain
    
* How to add steps to a chain
    
* How to execute a chain
    
* How to get the results of a chain
    

I hope this blog post will be helpful for you if you are interested in learning how to use LangChain.

Let's get started!

## Installing LangChain

There are three ways to install LangChain:

**Using Pip**

To install LangChain using Pip, you will need to have the Pip package manager installed. If you don't have Pip installed, you can install it by following the instructions on the Pip website: [https://pip.pypa.io/en/stable/installing/](https://pip.pypa.io/en/stable/installing/).

Once Pip is installed, you can install LangChain by running the following command in your terminal:

```plaintext
pip install langchain
```

This will install the latest stable version of LangChain.

**Using Conda**

To install LangChain using Conda, you will need to have the Conda package manager installed. If you don't have Conda installed, you can install it by following the instructions on the Conda website: [https://docs.conda.io/en/latest/](https://docs.conda.io/en/latest/).

Once Conda is installed, you can install LangChain by running the following command in your terminal:

```plaintext
conda install langchain -c conda-forge

```

This will install the latest stable version of LangChain.

**From source**

To install LangChain from source, you will need to have Git installed. If you don't have Git installed, you can install it by following the instructions on the Git website: [https://git-scm.com/book/en/v2/Getting-Started-Installing-Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git).

Once Git is installed, you can clone the LangChain repository by running the following command in your terminal:

```plaintext
git clone https://github.com/langchain-ai/langchain.git
```

This will create a directory called `langchain` in your current working directory.

To install LangChain from source, you can run the following command in the `langchain` directory, be sure that the directory is `PATH/TO/REPO/langchain/libs/langchain` running::

```plaintext
pip install -e .
```

This will install LangChain from the source code.

  
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## **Environment setup**

Using LangChain usually requires integrating with one or more model providers, data stores, APIs, and so on. For this example, we will use OpenAI's model APIs.

First, we need to install the OpenAI Python package:

```plaintext
pip install openai
```

Accessing the API requires an API key. You can get an API key by creating an account and going to this link: [https://openai.com/api/](https://openai.com/api/). Once you have a key, you need to set it as an environment variable by running the following command:

```plaintext
export OPENAI_API_KEY="..."
```

If you prefer not to set an environment variable, you can pass the key in directly to the `openai_api_key` named parameter when you initialize the `OpenAI` LLM class:

```plaintext
from langchain.llms import OpenAI

llm = OpenAI(openai_api_key="...")
```

Adding an Simple Code to call Code , before our next blog in detail:

```plaintext
from langchain.llms import OpenAI
from langchain.chat_models import ChatOpenAI

llm = OpenAI()
chat_model = ChatOpenAI()

llm.predict("hi!")
>>> "Hi"

chat_model.predict("hi!")
>>> "Hi"
```

We will learn About them in detail in next blog.