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LangChain is a code-first framework for building LLM applications and AI agent workflows, with optional LangSmith tools to trace, evaluate, and monitor agents used in production systems.
LangChain is an open-source software framework you use in code to build applications that work with large language models (LLMs), including agent-style workflows.
It's not a no-code tool-you write Python or TypeScript and compose building blocks (like prompts, tools, retrieval, and execution logic) into an app.
If you want debugging, evaluation, monitoring, or managed deployment features, LangChain's ecosystem also includes LangSmith (a hosted product with pricing) alongside open-source frameworks like LangGraph for more controllable agent flows.
LangChain is best for developers and AI builders who want code-level control over LLM apps and AI agent workflows, and teams who may also want LangSmith for testing, observability, and deployment.
You build with LangChain by writing Python/TypeScript and composing components into an application, rather than designing a visual workflow in a UI.
Agent behavior is implemented through application logic and frameworks in the ecosystem (for example, LangGraph is positioned for building custom agents with low-level control).
LangSmith is LangChain's paid platform for tracing, evaluation, and monitoring/alerting; it's also associated with deployment capabilities depending on plan.
LangChain (the framework) is open-source, while LangSmith is a paid product with multiple plans (including Developer, Plus, and Enterprise). Pricing and included usage vary by plan and are listed on LangChain's official pricing page.
View official pricingDify is a platform/UI for building LLM apps (often with visual workflows), while LangChain is primarily code-first libraries (plus LangSmith as an optional platform layer). If you want maximum code control, LangChain is usually the better fit; if you want faster UI-driven assembly, Dify is often faster.
Learn more about DifyRelevance AI is positioned as a hosted platform for building/running agent systems, while LangChain is a developer framework ecosystem (and LangSmith is the optional hosted layer for tracing/evals/deployment). Choose LangChain when you want to own the codebase and architecture; choose a platform when you want more "ready-made" hosted operations.
Learn more about Relevance AILast updated: December 2025
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