Langchain: Framework for Building LLMs Applications

Author(s): Adipta Martulandi

Originally published on Towards AI.

An Introduction to Langchain for Developing Applications with Large Language Models

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Since the emergence of ChatGPT, Artificial Intelligence, particularly in the field of Natural Language Processing (NLP) and Large Language Models (LLMs), has seen an unprecedented surge in popularity. The ability of models like ChatGPT to understand and generate natural text has unlocked new possibilities for AI-powered applications, ranging from virtual assistants to more intelligent recommendation systems.

Amid this wave of enthusiasm, various frameworks have been developed to simplify the process of building applications powered by LLMs. These frameworks are designed to address challenges such as data management, model processing, and integration. One of the most popular among them is Langchain.

Langchain is an open-source framework designed to simplify the development of applications powered by Large Language Models (LLMs). It provides tools and abstractions that help developers streamline tasks like chaining together LLM prompts, managing memory, and connecting to external data sources. Langchain is particularly useful for building conversational agents, information retrieval systems, and other applications where structured interaction with LLMs is essential.

Langchain’s popularity stems from its versatility and ease of use. It abstracts much of the complexity involved in working with LLMs, making it accessible to… Read the full blog for free on Medium.

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Published via Towards AI