Langchain vs. LlamaIndex vs. OpenAI Assistants
Which one should you use?
Good morning fellow AI enthusiast! This week's iteration focuses on the last video of our 3-course series on RAG and LLMs with Towards AI, Activeloop, and the Intel Corporation Disruptor Initiative!
In this one, we help you demystify the role of the most popular options for building your LLM application: LlamaIndex, LangChain, OpenAI Assistants (and GPTs), and building everything from scratch. But most importantly, we guide you in making the best choice for your own application.
Let's dive right into it!
1️⃣ Langchain vs LlamaIndex vs OpenAI GPTs: Which one should you use?
Are you using Large Language Models (LLMs) in your work and seeking the most effective way to leverage their power for your application? Then this video is for you. Let’s dive into LLM application development, comparing the paths of building your own framework from scratch by utilizing established platforms like LangChain, LlamaIndex, and OpenAI Assistants:
2️⃣ More about our course...
Tl;dr: The course is about showing everything about RAG and build advanced reliable RAG-based applications, and it is completely free!
Is the course for you?
If you want to learn how to build better RAG-based applications, leverage LlamaIndex, LangChain, or OpenAI toolsets better and have intermediate Python knowledge, you should be all set to take and complete the course.
This course is designed with a wide audience in mind, including beginners in AI, current machine learning engineers, students, and professionals considering a career transition to AI.
We aim to provide you with the necessary tools to apply and tailor Large Language Models and blend with your own datasets across a wide range of industries to make AI more accessible and practical.
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Thank you for reading, and we wish you a fantastic week! Be sure to have enough rest and sleep!
Louis-François Bouchard
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