Pavan Belagatti’s Post

Like to build powerful #GenAI applications? Possible with #LangChain! Developed by Harrison Chase, and debuted in October 2022, LangChain serves as an open-source platform designed for constructing sturdy applications powered by Large Language Models, such as chatbots like ChatGPT and various tailor-made applications. Langchain seeks to equip data engineers with an all-encompassing toolkit for utilizing LLMs in diverse use-cases, such as chatbots, automated question-answering, text summarization, and beyond. The image below shows how LangChain handles and processes information to respond to user prompts. Initially, the system starts with a large document containing a vast array of data. This document is then broken down into smaller, more manageable chunks. These chunks are subsequently embedded into vectors — a process that transforms the data into a format that can be quickly and efficiently retrieved by the system. These vectors are stored in a vector store, essentially a database optimized for handling vectorized data. When a user inputs a prompt into the system, LangChain queries this vector store to find information that closely matches or is relevant to the user's request. The system employs large LLMs to understand the context and intent of the user's prompt, which guides the retrieval of pertinent information from the vector store. Once the relevant information is identified, the LLM uses it to generate or complete an answer that accurately addresses the query. This final step culminates in the user receiving a tailored response, which is the output of the system's data processing and language generation capabilities. Get started with LangChain in my tutorial: https://lnkd.in/d44ni9f2