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LangChain Agent

Agent built with LangChain.js. Chains, retrievers, and tool use — served as a production REST API.

agentlangchainchains
Deploy this example

Agent built with LangChain. Use chains, retrievers, and tool use — all served as a production REST API.

What's included

  • LangChain integration — chains, retrievers, and tool use
  • Chains — compose prompts and LLM calls into reusable pipelines
  • Retrievers — connect to vector stores and RAG workflows
  • Tool use — LangChain tools invoked by the agent
  • Production API — REST endpoint ready for deployment

When to use this

Pick this example when you want to:

  • Build agents with LangChain and Reminix
  • Use chains, retrievers, or RAG in your agent
  • Leverage the LangChain ecosystem (loaders, tools, integrations)

Project structure

├── agents/
│   └── chain.py                # LangChain agent
├── main.py                     # Entry point — serve(agents)
├── pyproject.toml
└── reminix.config.toml

Quick start

Deploy the example and invoke the agent via the Reminix API. LangChain handles chains, retrievers, and tool execution — you get a production REST endpoint with full LangChain capabilities.