langchain-ai/langchain
The agent engineering platform.
LangChain tops AI frameworks at 132,668 GitHub stars -- the go-to for Python developers tackling complex LLM apps. Use langchain-core primitives and 200+ community integrations to build RAG pipelines and multi-agent systems.
Our Review
LangChain is the Python framework for building agents and LLM-powered applications. From langchain-ai with 132,668 stars, it chains components for fast prototyping and production scale.
What LangChain does:
- •One-line install pip install langchain or uv add langchain gets you started instantly.
- •Model swapping init_chat_model("openai:gpt-5.4") connects any LLM from OpenAI, Anthropic, Gemini, or Ollama without rewrites.
- •Data connections link retrievers, vector stores, and tools for real-time RAG and augmentation.
- •Agent orchestration use LangGraph for controllable multi-agent workflows.
- •Observability LangSmith tracks evals, debugging, and traces.
- •Modular packages langchain-core for basics, langchain-community for 200+ integrations.
LangChain ecosystem:
- •LangGraph builds stateful multi-agent apps with cycles and human-in-loop.
- •LangSmith production monitoring, testing, and deployment hub.
- •LangChain Academy free courses for developers and quickstarts.
Getting started:
pip install langchain. Then from langchain_openai import ChatOpenAI; model = ChatOpenAI(model="gpt-4o"). Full quickstart and docs at python.langchain.com/docs.
Limitations:
Requires Python knowledge -- JavaScript/TypeScript users need the separate LangChain.js repo. Performance in benchmarks rates medium vs specialized frameworks like CrewAI. The modular split across langchain-core, langchain-community, and LangGraph means learning multiple packages. Three security CVEs were patched in 2025-2026 (including CVE-2025-68664 critical deserialization) -- keep dependencies updated.
Our Verdict
Python developers build production RAG pipelines and multi-agent systems fastest with LangChain's abstractions. Skip if you avoid frameworks or need data-only RAG.
Vibe builders prototype agents via Academy courses and quickstarts, but expect a learning curve beyond basics.
LangChain sets the standard in 2026 with unmatched ecosystem breadth from langchain-ai. Start here for any serious LLM app.
Frequently Asked Questions
Is LangChain a Python framework?
Yes, LangChain is a primary Python framework. Install it via the command pip install langchain to access specific features like LCEL, which defines application pipelines using the pipe operator as in prompt | llm | StrOutputParser. JavaScript support exists in the separate LangChain.js repo at github.com/langchain-ai/langchainjs.
Is LangChain free or paid?
LangChain is free and open-source under the MIT license. LangSmith observability offers paid tiers for teams needing production monitoring, evals, and trace replay. The free LangSmith plan covers 5,000 traces per month, which covers most early-stage production apps and side projects.
LangChain vs LlamaIndex: which should I use?
LangChain handles agents, RAG, and chains with 200+ integrations. LlamaIndex excels in data indexing and retrieval workflows. LangChain's LCEL composes chains via prompt | llm | parser. Choose LangChain when building agents or needing broad integrations; choose LlamaIndex when data retrieval is the core use case.
How do I start building agents with LangChain?
Install with pip install langchain. Use LangGraph for agents: from langgraph.graph import Graph. Example: graph.add_node("agent", agent_func); graph.add_node("tools", tools_func); graph.add_conditional_edges("agent", should_continue); app = graph.compile(); result = app.invoke({"messages": [HumanMessage(content="hi")]}). Follow the 2026 quickstarts at python.langchain.com/docs or free courses at LangChain Academy (academy.langchain.com).
What is LangSmith and do I need it?
LangSmith from the langchain-ai team provides observability, evals, and debugging for LangChain apps. It is optional but recommended for production -- use it for tracing and testing; skip for quick prototypes. Enable it with LANGCHAIN_TRACING_V2=true and LANGCHAIN_PROJECT=my-app to view input latencies and error traces in the dashboard.
What is langchain?
LangChain tops AI frameworks at 132,668 GitHub stars -- the go-to for Python developers tackling complex LLM apps. Use langchain-core primitives and 200+ community integrations to build RAG pipelines and multi-agent systems.
What license does langchain use?
langchain uses the MIT license.
What are alternatives to langchain?
Explore related tools and alternatives on My AI Guide.
Open source & community-verified
MIT licensed: free to use in any project, no strings attached. 136,646 developers have starred this, meaning the community has reviewed and trusted it.
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