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Template Applications

Templates are open source reference applications designed to help you get started quickly when building with LangGraph. They provide working examples of common agentic workflows that can be customized to your needs.

You can create an application from a template using the LangGraph CLI.

Requirements

  • Python >= 3.11
  • LangGraph CLI: Requires langchain-cli[inmem] >= 0.1.58

Install the LangGraph CLI

pip install "langgraph-cli[inmem]" --upgrade

Or via uv (recommended):

uvx --from "langgraph-cli[inmem]" langgraph dev --help

npx @langchain/langgraph-cli --help

Available Templates

Template Description Python JS/TS
New LangGraph Project A simple, minimal chatbot with memory. Repo Repo
ReAct Agent A simple agent that can be flexibly extended to many tools. Repo Repo
Memory Agent A ReAct-style agent with an additional tool to store memories for use across threads. Repo Repo
Retrieval Agent An agent that includes a retrieval-based question-answering system. Repo Repo
Data-Enrichment Agent An agent that performs web searches and organizes its findings into a structured format. Repo Repo

🌱 Create a LangGraph App

To create a new app from a template, use the langgraph new command.

langgraph new

Or via uv (recommended):

uvx --from "langgraph-cli[inmem]" langgraph new

npx @langchain/langgraph-cli new

Next Steps

Review the README.md file in the root of your new LangGraph app for more information about the template and how to customize it.

After configuring the app properly and adding your API keys, you can start the app using the LangGraph CLI:

langgraph dev

Or via uv (recommended):

uvx --from "langgraph-cli[inmem]" --with-editable . langgraph dev
Missing Local Package?

If you are not using uv and run into a "ModuleNotFoundError" or "ImportError", even after installing the local package (pip install -e .), it is likely the case that you need to install the CLI into your local virtual environment to make the CLI "aware" of the local package. You can do this by running python -m pip install "langgraph-cli[inmem]" and re-activating your virtual environment before running langgraph dev.

npx @langchain/langgraph-cli dev

See the following guides for more information on how to deploy your app: