LangChain and LLMs: A Guide to Developing NLP Applications (Part 1)
Large Language Models
Large Language Models (LLMs) are a breed of natural language processing (NLP) of specific deep learning algorithms for generating multi-modal content via transformers. Some well-known examples include GPT-3, GPT-4, LaMDA, BLOOM, and LLaMA. ChatGPT has become the “first” LLM-powered chatbot and Bing has rolled out a search engine powered by GPT as well.
What is LangChain?
The LangChain framework is used to interact with LLMs. It offers a useful way to simplify the most common design patterns used in LLMs 👍
1- Iterating over documents to prepare a corpus by implementing pre-processing.
2 -Splitting the documents into chunks
3- Summarizing them
4 -Embedding the document chunks in a vector data source.
5 — Performing searches across documents
6 —Enabling Q+A over docs
Utilizing LangChain
With LangChain, you can create the following applications.
- ❓ Question Answering specific documents
End-to-end Example: Question Answering over Notion Database - 💬 Chatbots
End-to-end…