In this series of articles, we will learn how you can use LangChain with ChatGPT or GPT4All to create AI-powered apps using your own data.
Previously, the power of AI was limited to only a very specific community. But thanks to amazing open-source software like LangChain and GPT4All, now it is accessible to anyone who knows how to write code.
I don't think you need an introduction to ChatGPT if you are reading this article. But still, let me briefly talk about it.
ChatGPT is a GPT-powered app created by OpenAI where you can find information in a conversation-like manner. You can talk to it and you can ask questions in simple plain English and the app understands the context of your question and comes up with relevant answers.
ChatGPT understands English and it writes perfect English free of grammatical errors. All this has been made possible due to the immense amount of text on which its models have been trained.
ChatGPT is a proprietary software of OpenAI and you cannot use it for free in commercial projects. For high-volume use, you can use their API in your software but it is expensive if you are going to use it on a higher scale and if your business doesn't make good money.
GPT4All solves this problem and it allows you to run GPT-based NLP models right on your own hardware. Combining LangChain with it, you can feed your own data to NLP models using GPT4All and you can create amazing software.
LangChain is an abstraction layer on NLP models that lets you easily feed those models your own data so you will make the models respond to you based on the facts that you provide. By default, LLMs like OpenAI GPT-3 and GPT4 are capable of answering questions based on the information that they were trained on. They don't have access to real-time external information.
The process through which you can educate those models is called embedding where you need to convert the natural language data to numerical representations called vectors. Data Scientists with advanced AI / ML skills are capable of doing this but for a programmer without advanced AI and ML knowledge, this is a challenging task where LangChain comes in and simplifies this process.
LangChain allows you to use embedding classes for NLP models and you can use the data loaders to load your text files and CSV files that contain information in natural language, i.e. plain English. Once you feed the models with your data, they will respond to you based on the information that you have provided.
In simple words, you can educate NLP models using your own data with the help of tools provided by LangChain and then they will be capable of answering questions related to it.
In the next chapters, we will explore how to use OpenAI and GPT4All GPT models with your own data.