LangChain

LangChain is an open-source development framework designed to simplify the creation of applications powered by large language models (LLMs). It provides a modular set of tools and abstractions that allow developers to "chain" together different components—such as prompt templates, memory, and external data sources—to build complex AI workflows. 

Core Components

LangChain's architecture is built around several key modules: 

• Models: A standard interface for interacting with various LLMs (e.g., OpenAI, Anthropic, Google) and embedding models, allowing you to swap providers easily without rewriting your code.
• Chains: The foundational concept where multiple components are linked together to execute a sequence of functions.
• Agents: Systems that use an LLM as a "reasoning engine" to determine which actions to take and which tools to call (like Google Search or calculators) to complete a task.
• Retrieval (RAG): Tools to connect LLMs to external data sources—such as PDFs, databases, or web pages—to provide context-aware responses without retraining the model.
• Memory: Utilities that allow applications to "remember" past interactions, essential for maintaining context in chatbots.