Welcome to the LangChain Tutorial Repository! This repository contains a collection of tutorials and examples to help you get started with the LangChain Library, a powerful Python library for natural language processing and text analysis.
The LangChain Library is an open-source Python library designed to simplify and accelerate the development of natural language processing applications. Whether you're a beginner or an experienced developer, these tutorials will walk you through the basics of using LangChain to process and analyze text data effectively.
Before diving into the tutorials, make sure you have installed the LangChain and OpenAI Libraries. You can install them using pip:
pip install langchain openaiPlease refer to the official LangChain documentation for more detailed installation instructions and library features.
Depending on the tutorial you run, you may need to install the following libraries:
python-dotenv: Used to read the .env file containing the OpenAI API Keyipykernel: Enables running this notebook in VSCodeyoutube-transcript-api: Fetches YouTube video transcriptspytube: Fetches YouTube video metadatatiktoken: Counts tokens in a text
If you are new to LangChain, we recommend starting with the Getting Started section of the documentation. There, you will learn the fundamentals of the library and the basic concepts required for the tutorials.
The tutorials in this repository cover a range of topics and use cases to demonstrate how to use LangChain for various natural language processing tasks. Each tutorial is contained in a separate Jupyter Notebook for easy viewing and execution.
| Tutorial Name | Description |
|---|---|
| YouTube Loader | Analyze YouTube Videos with LangChain and GPT-3.5. |
| Podcast transcript QA | Chat With your favorite podcast using GPT-3.5. |
| Second Brain (Obsidian) QA | QA over your second brain with LangChain |
| LangChain Prompt Templates | How to use Langchain's Prompt templates |
| LangChain Chains | How to use Langchain's Chains |
| Basic LangChain Agents | The basic usage of LangChain Agents |
Feel free to explore the tutorials in any order you prefer, depending on your interests and prior experience with the LangChain Library.
This project is licensed under the MIT License. You are free to use, modify, and distribute this code in your projects. We appreciate attribution if you use this library for your work.