Check Langchain Version : Chris

Check Langchain Version
by: Chris
blow post content copied from  Be on the Right Side of Change
click here to view original post

5/5 - (1 vote)

To check the version of LangChain installed on your system, open a terminal or command prompt and type the following command:

pip show langchain

This command will display information about the installed LangChain package, including the version number.

A Few Words on Langchain

LangChain 🦜🔗 is a powerful framework designed to build applications that harness the capabilities of large language models. It enables developers to create customized solutions that not only efficiently access language models via APIs, but also integrate with various data sources, providing enhanced functionality and versatility.

The framework offers a robust interface and multiple options for data-augmented generation, allowing developers to create state-of-the-art question-answering and chatbot applications.

Installation and Setup

To begin setting up the LangChain, make sure you have Python installed on your machine. You can use either pip or conda package managers to install the necessary packages. 🛠

First, install LangChain using the pip package manager by running the following command:

pip install langchain

Alternatively, you can use conda to install LangChain by executing this command:

conda install langchain -c conda-forge

Once LangChain is installed, you will need to integrate it with various model providers, data stores, and APIs according to your requirements. For example, when using OpenAI’s APIs, start by installing their SDK. To do so, simply run:

pip install openai

Langchain Models 🦜🔗

In this section, we will discuss the different types of models used in Langchain, focusing on GPT and LLMS.


GPT, or Generative Pre-trained Transformers, are a class of large language models that excel in various NLP tasks. They are known for their ability to generate coherent and contextually relevant text by leveraging knowledge extracted from massive amounts of training data. GPT models can be integrated into Langchain applications to enhance their capabilities for tasks such as text generation, question-answering, and more.


LLMS stands for Large Language Model Systems, which are a broader category of models encompassing GPT models and other state-of-the-art language models. Langchain supports LLMS and aims to provide an easy-to-use framework for integrating these cutting-edge models into your applications, making them data-aware and powerful. LLMS can help improve an application’s performance by connecting language models with other sources of data and leveraging their memory capabilities.

By incorporating GPT models and other LLMS into Langchain, developers can create innovative applications that harness the power of language models to deliver extraordinary results.💡

Langchain Interface

Langchain provides a robust interface for developers using both Python and JavaScript/TypeScript. In this section, we’ll discuss how to access the Langchain interface using these languages.

Python Module

The 🦜🔗 LangChain module is readily available for Python projects and can be installed using the pip package manager. To get started, simply run this command:

pip install langchain

After installation, you can import the Langchain interface in your Python code to access its functionalities. Here’s an example of how to do that:

import langchain

# Your langchain code here

JavaScript/TypeScript Version

Likewise, Langchain offers a comprehensive package for JavaScript and TypeScript developers. The js/ts version can be found on their website at

To use the Langchain interface in your JavaScript or TypeScript project, you can import the package in your code. For instance, in a JavaScript project, you might have the following code snippet:

const langchain = require("langchain");

// Your langchain code here

And in a TypeScript project, you can import Langchain like this:

import * as langchain from "langchain";

// Your langchain code here

Frequently Asked Questions

How do I check the version of LangChain?

To check the version of LangChain installed on your system, open a terminal or command prompt and type the following command:

pip show langchain

This command will display information about the installed LangChain package, including the version number.

Where can I find documentation for LangChain?

The official LangChain documentation can be found at LangChain’s website. The documentation provides a quickstart guide, installation instructions, and various examples to help you get started.

Are there examples using LangChain?

Yes, there are examples available that demonstrate how to use LangChain for various tasks like building chatbots, generative question-answering, summarization, and more. These examples can be found in LangChain’s GitHub repository and also on Pinecone’s website.

Is LangChain compatible with Python?

LangChain is compatible with Python, and it is designed to be used as a Python library. You can install LangChain using pip or conda, and the library can be easily integrated into your Python projects.

Which model is used by LangChain?

LangChain is a framework built around Large Language Models (LLMs). It integrates with various model providers and datastores to create advanced use-cases for LLMs. Some examples of LLMs used with LangChain include GPT-3 and open-source alternatives.

Do LangChain and LLM have any differences?

LangChain is a framework that allows users to build applications and pipelines around Large Language Models (LLMs). While LLMs are the underlying technology, LangChain helps users to efficiently and effectively use them for tasks like chatbots, generative question-answering, summarization, and more. So, LangChain is a tool that leverages the capabilities of LLMs, while LLMs are the models themselves.

🔗🦜 Recommended: Langchain Python Tutorial: Quick and Easy Guide for Beginners

June 30, 2023 at 09:21PM
Click here for more details...

The original post is available in Be on the Right Side of Change by Chris
this post has been published as it is through automation. Automation script brings all the top bloggers post under a single umbrella.
The purpose of this blog, Follow the top Salesforce bloggers and collect all blogs in a single place through automation.