https://github.com/langchain-ai/langchain-academy
https://github.com/langchain-ai/langchain-academy
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/langchain-ai/langchain-academy
- Owner: langchain-ai
- Created: 2024-07-23T23:57:41.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2025-03-26T18:24:15.000Z (3 months ago)
- Last Synced: 2025-04-13T04:55:47.894Z (3 months ago)
- Language: Jupyter Notebook
- Homepage: https://academy.langchain.com
- Size: 37.6 MB
- Stars: 1,118
- Watchers: 27
- Forks: 741
- Open Issues: 16
-
Metadata Files:
- Readme: README.md
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## Introduction
Welcome to LangChain Academy!
This is a growing set of modules focused on foundational concepts within the LangChain ecosystem.
Module 0 is basic setup and Modules 1 - 4 focus on LangGraph, progressively adding more advanced themes.
In each module folder, you'll see a set of notebooks. A LangChain Academy accompanies each notebook
to guide you through the topic. Each module also has a `studio` subdirectory, with a set of relevant
graphs that we will explore using the LangGraph API and Studio.
## Setup
### Python version
To get the most out of this course, please ensure you're using Python 3.11 or later.
This version is required for optimal compatibility with LangGraph. If you're on an older version,
upgrading will ensure everything runs smoothly.
```
python3 --version
```
### Clone repo
```
git clone https://github.com/langchain-ai/langchain-academy.git
$ cd langchain-academy
```
### Create an environment and install dependencies
#### Mac/Linux/WSL
```
$ python3 -m venv lc-academy-env
$ source lc-academy-env/bin/activate
$ pip install -r requirements.txt
```
#### Windows Powershell
```
PS> python3 -m venv lc-academy-env
PS> Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope Process
PS> lc-academy-env\scripts\activate
PS> pip install -r requirements.txt
```
### Running notebooks
If you don't have Jupyter set up, follow installation instructions [here](https://jupyter.org/install).
```
$ jupyter notebook
```
### Setting up env variables
Briefly going over how to set up environment variables. You can also
use a `.env` file with `python-dotenv` library.
#### Mac/Linux/WSL
```
$ export API_ENV_VAR="your-api-key-here"
```
#### Windows Powershell
```
PS> $env:API_ENV_VAR = "your-api-key-here"
```
### Set OpenAI API key
* If you don't have an OpenAI API key, you can sign up [here](https://openai.com/index/openai-api/).
* Set `OPENAI_API_KEY` in your environment
### Sign up and Set LangSmith API
* Sign up for LangSmith [here](https://smith.langchain.com/), find out more about LangSmith
* and how to use it within your workflow [here](https://www.langchain.com/langsmith), and relevant library [docs](https://docs.smith.langchain.com/)!
* Set `LANGCHAIN_API_KEY`, `LANGCHAIN_TRACING_V2=true` in your environment
### Set up Tavily API for web search
* 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](https://tavily.com/).
It's easy to sign up and offers a very generous free tier. Some lessons (in Module 4) will use Tavily.
* 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](https://langchain-ai.github.io/langgraph/concepts/langgraph_studio/#local-development-server) on the local Studio development server and [here](https://langchain-ai.github.io/langgraph/how-tos/local-studio/#run-the-development-server).
* 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:
```
- 🚀 API: http://127.0.0.1:2024
- 🎨 Studio UI: https://smith.langchain.com/studio/?baseUrl=http://127.0.0.1:2024
- 📚 API Docs: http://127.0.0.1:2024/docs
```
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
```