LangChain
ragAssess
LangChain is one of the most widely-adopted frameworks for building LLM-powered applications — particularly RAG pipelines (connecting LLMs to your own documents and data). However, for agent orchestration, its successor LangGraph is now recommended.
Buy vs Build
LangChain is a build framework. There is no "buy" version — it's open-source Python (and JavaScript) code you include in your application.
Why It's in Assess (Not Trial)
LangChain has 80K+ GitHub stars and remains extremely useful, but the team has been clear: use LangGraph for agents, not LangChain. The reasons:
- LangChain's agent abstraction is verbose and hard to debug
- LangGraph, built by the same team, provides a cleaner mental model for stateful agent workflows
- LangChain's "chain" abstraction was designed for sequential pipelines, not the branching, looping nature of modern agents
Where LangChain is still excellent:
- RAG pipelines — connecting LLMs to PDFs, databases, websites, and knowledge bases
- Document Q&A — build "chat with your docs" applications quickly
- Integration breadth — 600+ integrations with data sources, vector stores, and tools
- LCEL (LangChain Expression Language) — declarative syntax for composing retrieval + generation pipelines
When to Use LangChain vs LangGraph
| Use Case | Recommended Tool |
|---|---|
| RAG / document search | LangChain |
| Chat with your docs | LangChain |
| Multi-step agent workflows | LangGraph |
| Complex branching logic | LangGraph |
Getting Started
pip install langchain langchain-anthropic langchain-community
from langchain_anthropic import ChatAnthropic
from langchain_core.prompts import ChatPromptTemplate
chain = ChatPromptTemplate.from_template("Explain {topic} to a beginner") | ChatAnthropic(model="claude-sonnet-4-6")
result = chain.invoke({"topic": "vector databases"})
Key Characteristics
| Property | Value |
|---|---|
| Language | Python and JavaScript/TypeScript |
| License | MIT |
| Integrations | 600+ data sources and tools |
| Provider | LangChain Inc. |
| Website | python.langchain.com |
| GitHub | langchain-ai/langchain |
Further Reading
- LangChain Python docs
- LangChain Expression Language (LCEL)
- LangGraph (successor for agents) — use this for agent orchestration instead
- Open SWE — LangChain's autonomous coding agent framework, built on LangGraph — the ecosystem's evolution from chains → graphs → full autonomous agents