Getting Started with LangChain and Claude: Build Your First Production App

LangChain and Claude together give you the most flexible and powerful platform for building production LLM applications in Python. LangChain handles the orchestration scaffolding; Claude handles the reasoning. Here is how to get started.

Install: pip install langchain langchain-anthropic. Set your ANTHROPIC_API_KEY environment variable. You are ready.

The simplest starting point is LCEL (LangChain Expression Language). A basic chain: prompt | model | output_parser. This gives you streaming, error handling, and type safety out of the box.

For RAG: use a Supabase vector store with LangChain's SupabaseVectorStore connector. Embed documents with langchain_openai.OpenAIEmbeddings or Anthropic's own embeddings. Create a retriever, wire it to a RetrievalQA chain with Claude as the LLM.

For agents: LangGraph is the right tool for multi-step agents. Define your state graph, add agent and tool nodes, compile and invoke. LangSmith traces every step for debugging and evaluation.

Production checklist: add LangSmith tracing for observability, use structured output with Pydantic models for data extraction tasks, and deploy on a serverless function or Fly.io for cost efficiency.