LangChain
AI Developer ToolsFramework for building LLM-powered applications and AI agents
About LangChain
LangChain is a framework for developing applications powered by large language models. It provides composable building blocks for LLM chains, retrieval-augmented generation (RAG) pipelines, AI agents, and memory management. LangChain also offers LangSmith for observability and testing, and LangGraph for building stateful multi-step AI agents. It is one of the most widely adopted frameworks in the LLM developer ecosystem.
Editorial Assessment
LangChain is an open-source framework for building LLM-powered applications — agents, RAG (retrieval-augmented generation) pipelines, and multi-step chains — available in Python and JavaScript/TypeScript. Created by Harrison Chase and Ankush Gola in 2022, LangChain became the dominant framework for prototyping AI applications during the rapid adoption period of 2023, largely due to its extensive abstractions for connecting LLMs to external tools, databases, and APIs. LangSmith is the production observability and evaluation platform layered on top: it logs every LLM call and chain step, provides a prompt playground, enables A/B dataset testing of prompts and chains, and delivers latency/token usage analytics. LangSmith Developer plan is free (3K traces/month), Plus $39/month (unlimited traces), Team $299/month, Enterprise custom. LangChain Expression Language (LCEL) simplifies composing chains declaratively. LangGraph is the multi-agent orchestration framework for building stateful, cyclical agent workflows beyond the simpler chain paradigm. The main criticism of LangChain is that its abstractions introduced too much complexity for production applications — many teams find raw API calls simpler than the framework's abstraction layers. Despite this, LangSmith has become a standard observability tool across teams that moved away from the LangChain framework itself.
- Most widely adopted framework for LLM application prototyping in 2023-2024
- LangSmith provides comprehensive LLM observability, tracing, and evaluation in production
- LangGraph enables stateful multi-agent workflows beyond simple chains
- Large ecosystem of integrations with vector databases, tools, and LLM providers
- LangSmith free tier (3K traces/month) makes it accessible for small teams
- LangChain Hub for sharing and versioning prompts
- Framework abstractions criticized for adding complexity that outweighs benefits in production
- Many production teams prefer raw API calls over LangChain's abstraction layers
- Rapid version changes in 2023 caused frequent breaking changes
- LangGraph adds significant learning curve for agentic workflows
- LangSmith pricing scales significantly for high-trace-volume production use
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Who It's For
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Founders
- Harrison Chase
- Ankush Gola
Products & Tools
Open-source Python and JavaScript framework for building LLM applications including RAG pipelines, agents, and multi-step chains.
LLM observability, evaluation, and prompt management platform for monitoring and improving AI applications in production.
Sources & Verification
- LangSmith PricingOfficial Pricing
- LangChain WebsiteOfficial Website
Last reviewed September 2026
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LangChain FAQs
Is LangChain free?
The LangChain Python and JavaScript libraries are open source and free to use. LangSmith (observability and testing) has a free Developer plan with limited trace volume; paid plans support team collaboration and production use.
What is LangGraph?
LangGraph is a framework built on top of LangChain for creating stateful, multi-step AI agents with cyclical computation graphs. It enables building complex agents that can loop, branch, and maintain state across steps.
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