LCEL (LangChain Expression Language)

The new way to compose chains: python chain = prompt | model | StrOutputParser() result = chain.invoke({"topic": "AI"}) Pipe operator chains components. Streaming, async, batch all free.

python async for chunk in chain.astream({"topic": "AI"}): print(chunk, end="")

Callbacks for Observability

python from langchain.callbacks import LangChainTracer tracer = LangChainTracer(projectname="my-app") chain.invoke(input, config={"callbacks": [tracer]}) Logs to LangSmith. Critical for debugging production.

LangChain wraps a lot. Use try/except around invoke(). Specific errors: - OutputParserException: schema mismatch - RateLimitError: provider throttling - Timeout: slow LLM

python from langchaincore.runnables import RunnableRetry chainwithretry = chain.withretry(stopafterattempt=3)

python from langchain.cache import SQLiteCache import langchain langchain.llmcache = SQLiteCache() Identical inputs return cached output.

Common Production Issues

Chain breaking changes: pin versions - Bloated bundle: only import what you use - Hidden token costs: log every call - Wrong abstraction: use vanilla client for hot paths

Alternative: Build It Yourself

For maximum control, skip LangChain: python from anthropic import Anthropic client = Anthropic() def querywithrag(question, vectorstore): chunks = vectorstore.search(question, k=5) response = client.messages.create( model="claude-sonnet-4-6", messages=[{"role": "user", "content": f"Context: {chunks}\n\nQuestion: {question}"}] ) return response.content[0].text 50 lines. No framework. Full control.

LangChain Production Patterns 2026 — Guide

Q: When to Use LangChain

Document loaders (huge selection) - RAG pipelines (LCEL composability) - Multi-step chains (well-supported) - Prototyping (huge ecosystem)

Q: When to Escape LangChain

Performance-critical paths (overhead is real) - Simple single-call workflows (raw client is fine) - Long-term maintenance (breaking changes are common)

LangChain Production Patterns 2026

LangChain in production: where it shines, where to escape, real patterns. When to Use LangChain - Document loaders huge selection - RAG pipelines LCEL composability - Multi-step chains well-supported - Prototyping huge ecosystem When to Escape LangChain - Performance-critical paths overhead is real - Simple single-call workflows raw client is fine - Long-term maintenance breaking changes are comm…

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