LangChain
A popular open-source framework for building applications powered by language models. It provides tools for prompt management, chains, agents, memory, and integration with external tools and data sources.
Why It Matters
LangChain accelerated LLM application development by providing reusable components. It is the most widely adopted framework for building RAG and agent-based systems.
Example
Using LangChain to build a RAG chatbot that connects to a vector database, manages conversation memory, and can call external APIs — all with pre-built components.
Think of it like...
Like a Lego set for AI applications — pre-built, compatible pieces that snap together to create complex structures without building everything from scratch.
Related Terms
Retrieval-Augmented Generation
A technique that enhances LLM outputs by first retrieving relevant information from external knowledge sources and then using that information as context for generation. RAG combines the power of search with the fluency of language models.
Prompt Chaining
A technique where the output of one LLM call becomes the input for the next, creating a pipeline of prompts that together accomplish a complex task.
AI Agent
An AI system that can autonomously plan, reason, and take actions to accomplish goals. Unlike simple chatbots, agents can use tools, make decisions, execute multi-step workflows, and adapt their approach based on results.
Tool Use
The ability of an AI model to interact with external tools, APIs, and systems to accomplish tasks beyond text generation. Tools extend the model's capabilities to include search, calculation, code execution, and more.