Create a RAG Chain using LangChain 0.1.0 (New version)

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Create a RAG Chain using LangChain 0.1.0 (New version)
Create a RAG Chain using LangChain 0.1.0 (New version)
In this video we explore a crash course of the new Langchain version (0.1.0) in python. This will allow you to create RAG chains in Langchain to chat with your documents.

We will be showcasing LangChain, a revolutionary Python library that empowers developers to create context-aware and reasoning-driven applications using powerful language models.

In the video, we will create several chains using the new version of LangChain to chat with a website. The final chain that we build here is a history-aware chain that takes the history of the conversation into account to answer your questions.

Useful links:
Google Colab:
Official LangChain Documentation:
️ Buy me a coffee (or a beer): (thank you!)
Consulting call –

What is LangChain?
LangChain is a framework designed to elevate your applications to new heights. It enables the creation of context-aware applications by connecting language models to various sources of context, allowing them to reason and provide intelligent responses.

Quickstart Highlights:
1. Get Set Up with LangChain: Learn how to seamlessly set up the LangChain ecosystem to kickstart your development journey.

2. Basic Components Mastery: Explore the fundamental components of LangChain, including prompt templates, models, and output parsers. Harness the power of these components to enhance your applications.

3. LangChain Expression Language: Delve into the protocol that serves as the backbone of LangChain. Discover how the LangChain Expression Language (LCEL) facilitates component chaining, enabling seamless integration and communication between different elements.

4. Build Your First Chains: Follow our step-by-step guide to construct a set of simple yet powerful chains using LangChain. Witness firsthand the capabilities that this innovative library brings to your projects.

️ Why LangChain?
LangChain opens up a world of possibilities, allowing you to create intelligent applications that understand context and make informed decisions. Whether you’re a seasoned developer or a coding enthusiast, LangChain is your gateway to building the next generation of language-powered applications.

‍ Who is This For?
This Quickstart tutorial is perfect for developers looking to harness the potential of language models in their applications. No matter your experience level, this guide provides a straightforward introduction to LangChain’s capabilities.

Level Up Your Development Game with LangChain!
Don’t miss out on this opportunity to revolutionize your application development process. Join us in this Quickstart tutorial and unlock the true potential of language models. Get ready to code smarter, reason better, and create applications that stand out!

0:00 Intro
1:19 Installing Langchain
4:06 Get API Keys and Initialize LLM
6:40 Create Your First Chain
10:22 Add Output Parser to Your Chain
13:21 What is a RAG Chain
14:55 Load Text From a Website
19:35 Create a Vector Store
22:44 Create a Document Chain
29:04 Create a RAG Chain
33:24 Retriever Chain with History
43:06 RAG Chain with History
50:35 Conclusion

#LangChain #PythonLibrary #LanguageModels #DeveloperTutorial

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