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  * [ Get started ](/docs/get_started)

    * [ Introduction ](/docs/get_started/introduction)
    * [ Installation ](/docs/get_started/installation)
    * [ Quickstart ](/docs/get_started/quickstart)
    * [ Security ](/docs/security)
  * [ LangChain Expression Language ](/docs/expression_language/)

    * [ Get started ](/docs/expression_language/get_started)
    * [ Why use LCEL ](/docs/expression_language/why)
    * [ Interface ](/docs/expression_language/interface)
    * [ Streaming ](/docs/expression_language/streaming)
    * [ How to ](/docs/expression_language/how_to/)

    * [ Cookbook ](/docs/expression_language/cookbook/)

    * [ LangChain Expression Language (LCEL) ](/docs/expression_language/)
  * [ Modules ](/docs/modules/)

    * [ Model I/O ](/docs/modules/model_io/)

    * [ Retrieval ](/docs/modules/data_connection/)

    * [ Agents ](/docs/modules/agents/)

    * [ Chains ](/docs/modules/chains)
    * [ More ](/docs/modules/memory/)

  * [ LangServe ](/docs/langserve)
  * [ LangSmith ](/docs/langsmith/)

  * [ LangGraph ](/docs/langgraph)

  * [ ](/)
  * [ Get started  ](/docs/get_started)
  * Quickstart 

On this page

#  Quickstart

In this quickstart we'll show you how to:

  * Get setup with LangChain, LangSmith and LangServe 
  * Use the most basic and common components of LangChain: prompt templates, models, and output parsers 
  * Use LangChain Expression Language, the protocol that LangChain is built on and which facilitates component chaining 
  * Build a simple application with LangChain 
  * Trace your application with LangSmith 
  * Serve your application with LangServe 

That's a fair amount to cover! Let's dive in.

##  Setup  ​

###  Jupyter Notebook  ​

This guide (and most of the other guides in the documentation) uses [ Jupyter
notebooks ](https://jupyter.org/) and assumes the reader is as well. Jupyter
notebooks are perfect for learning how to work with LLM systems because
oftentimes things can go wrong (unexpected output, API down, etc) and going
through guides in an interactive environment is a great way to better
understand them.

You do not NEED to go through the guide in a Jupyter Notebook, but it is
recommended. See [ here ](https://jupyter.org/install) for instructions on how
to install.

###  Installation  ​

To install LangChain run:

  * Pip 
  * Conda 

    
    
    pip install langchain  
    
    
    
    conda install langchain -c conda-forge  
    

For more details, see our [ Installation guide
](/docs/get_started/installation) .

###  LangSmith  ​

Many of the applications you build with LangChain will contain multiple steps
with multiple invocations of LLM calls. As these applications get more and
more complex, it becomes crucial to be able to inspect what exactly is