Category Archives: LangChain
Building an OpenAI Chatbot with LangChain
Have you ever wondered how to use OpenAI APIs to create custom chatbots? With advancements in large language models (LLMs), anyone can develop intelligent, customized chatbots tailored to specific needs. In this blog, we’ll explore how LangChain and OpenAI LLMs work together to help you build your own AI-driven chatbot from scratch. Prerequisites Before getting started, ensure you have Python (version 3.8 or later) installed and the required libraries. You can install the necessary packages using the following command: Setting Up OpenAI API Key To use OpenAI’s services, you need an API key, which you can obtain by signing up at OpenAI’s website (OpenAI) and generating a key from the …
Building a RAG Application with LangChain: Example Code
The combination of Retrieval-Augmented Generation (RAG) and powerful language models enables the development of sophisticated applications that leverage large datasets to answer questions effectively. In this blog, we will explore the steps to build an LLM RAG application using LangChain. Prerequisites Before diving into the implementation, ensure you have the required libraries installed. Execute the following command to install the necessary packages: Setting Up Environment Variables LangChain integrates with various APIs to enable tracing and embedding generation, which are crucial for debugging workflows and creating compact numerical representations of text data for efficient retrieval and processing in RAG applications. Set up the required environment variables for LangChain and OpenAI: Step …
I found it very helpful. However the differences are not too understandable for me