Programming
How to use LangChain output parsers to structure large language models responses
If you're wondering how you can convert the text returned by an LLM to a Pydantic (JSON) model in your Python app, this post is for you.
LangChain
LangChain is an open-source framework that enables building simple and complex Large Language Model (LLM) powered applications. It allows us to use chains to orchestrate a series of prompts to achieve a desired outcome. No matter your level of expertise, you'll find the material simple and easy to follow. Go ahead, and take a peak at some of the articles below.
Machine Learning
What is the difference between fine-tuning and vector embeddings
In this post, we're going to define what fine-tuning and vector embeddings are and look at which approach could be better suited for your specific use case.
Programming
How to Integrate and Handle LLM Memory using LangChain
LLMs are stateless, meaning they do not have memory that lets them keep track of conversations. However, using LangChain we'll see how to integrate and manage memory easily.
Programming
How to convert natural language text to SQL using LangChain
In this post, we're going to look at how you can use LangChain and OpenAI's GPT model to convert natural language queries to SQL, execute them, and get an answer from your database in plain English.
Programming
What is the difference between LlamaIndex and LangChain
In this post, we'll briefly compare LangChain and LlamaIndex and look at the key features of each solution so that you can choose which is the best suited for your next LLM-powered app.