description LangChain Expression Language (LCEL) Overview
LCEL is not a full agent builder but rather the foundational, modern way to compose LLM calls, prompt templates, and output parsers within the LangChain ecosystem. Its strength lies in its explicit, declarative nature, making complex chains predictable, testable, and highly optimized for performance. It is the recommended building block for anyone using LangChain to ensure reliable, structured output from their agents.
help LangChain Expression Language (LCEL) FAQ
What is LangChain Expression Language in plain terms?
LangChain Expression Language is a declarative way to compose Runnables such as prompt templates, chat models and output parsers. Pipe-style composition lets one step's output become the next step's input. [LangChain](https://www.langchain.com/blog/langchain-expression-language)
Is LCEL a complete agent builder?
No. LCEL is the chain-composition layer, while tools, memory, state and longer agent loops usually require LangChain agent components or LangGraph. [LangChain](https://docs.langchain.com/oss/python/langchain/agents)
What execution modes does an LCEL chain support?
LangChain's Runnable interface provides synchronous, asynchronous, batch and streaming methods for composed chains. A simple RunnableSequence can therefore serve one request, many inputs or a token-streaming user interface. [LangChain Runnable reference](https://reference.langchain.com/python/langchain-core/runnables/base/Runnable)
Can LCEL call Google Vertex AI?
Yes, a LangChain model integration such as ChatVertexAI can be composed inside an LCEL chain using the langchain-google-vertexai package. LangChain now marks ChatVertexAI as deprecated for Gemini and points new code toward ChatGoogleGenerativeAI, so the package choice matters. [LangChain Vertex AI integration](https://docs.langchain.com/oss/python/integrations/chat/google_vertex_ai)
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