Boyang Yan

LangChain Academy

2 min read

Setup

Clone repo

git clone https://github.com/langchain-ai/langchain-academy.git
cd langchain-academy

Create an environment and install dependencies

python3 -m venv lc-academy-env
source lc-academy-env/bin/activate
pip install -r requirements.txt

Running Jupyter notebooks

jupyter notebook

Sign up for LangSmith

Sign up here. You can reference LangSmith docs here.

Then, set

LANGCHAIN_API_KEY
LANGCHAIN_TRACING_V2=true

in your environment.

Set up OpenAI API key

If you don’t have an OpenAI API key, you can sign up here. Then, set

OPENAI_API_KEY

in your environment.

Tavily Search API is a search engine optimized for LLMs and RAG, aimed at efficient, quick, and persistent search results. You can sign up for an API key here. It’s easy to sign up and offers a generous free tier. Some lessons in Module 4 will use Tavily. Then, set

TAVILY_API_KEY

in your environment.

Set up LangGraph Studio

  • LangGraph Studio is a custom IDE for viewing and testing agents.
  • Studio can be run locally and opened in your browser on Mac, Windows, and Linux.
  • See documentation here on the local Studio development server and here.

Graphs for LangGraph Studio are in the module-x/studio/ folders. To start the local development server, run the following command in your terminal in the /studio directory each module:

langgraph dev

You should see the following output:

Open your browser and navigate to the Studio UI: https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:2024

  • To use Studio, you will need to create a .env file with the relevant API keys
  • Run this from the command line to create these files for module 1 to 6, as an example:
for i in {1..6}; do
  cp module-$i/studio/.env.example module-$i/studio/.env
  echo "OPENAI_API_KEY=\"$OPENAI_API_KEY\"" > module-$i/studio/.env
done
echo "TAVILY_API_KEY=\"$TAVILY_API_KEY\"" >> module-4/studio/.env

Reference List

  1. https://academy.langchain.com/

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