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LangChain is an open-source framework for building applications with large language models. It provides modular components for prompt management, chaining, retrieval-augmented generation (RAG), and connector integrations to external data sources. LangChain accelerates development of robust LLM-driven services while requiring careful handling of costs, latenc…
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LangChain is a software framework for connecting large language models with prompts, tools, data sources, and multi-step execution flows.
LangChain emerged in 2022 from the problem of connecting language models to application context and actions. The project initiated by Harrison Chase grew from a Python library into an ecosystem with runtime and observability tools.
Treat LangChain as an orchestration layer: a model generates or decides, prompts shape context, retrievers supply knowledge, tools reach systems, and chains or agents coordinate steps. The application defines control boundaries and state around the model.
It shapes input and context for a model call.
It finds relevant documents or records as additional context.
It lets a model invoke a defined external function.
LangChain helps prototype and build applications that connect LLMs to organizational data or actions. Production systems also need prompt tests, agent limits, privacy controls, cost management, and tracing.
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