The Anatomy of a Full Large Language Model Langchain Application

Author(s): Mostafa Ibrahim

Originally published on Towards AI.

A deep dive — data extraction, initializing the model, splitting the data, embeddings, vector databases, modeling, and inference

Photo by Simone Hutsch on Unsplash

We are seeing a lot of use cases for langchain apps and large language models these days. After inspecting a lot of them and building a few myself, I wanted to write this article about the common concepts, ideas, and essentially the steps of building an LLM-langchain-powered application. Most of my experience is tailored toward semantic search and question-answering, so there might be slight differences for other NLP tasks (I doubt they will be major differences though).

I won’t be covering web scraping or acquiring the dataset in the first place since this is quite a… Read the full blog for free on Medium.

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Published via Towards AI