Requirements
- Python >= 3.11
- LangGraph CLI: Requires langchain-cli[inmem] >= 0.1.58
Install the LangGraph CLI
uv
(recommended):
Available Templates
Template | Description | Link |
---|---|---|
New LangGraph Project | A simple, minimal chatbot with memory. | Repo |
ReAct Agent | A simple agent that can be flexibly extended to many tools. | Repo |
Memory Agent | A ReAct-style agent with an additional tool to store memories for use across threads. | Repo |
Retrieval Agent | An agent that includes a retrieval-based question-answering system. | Repo |
Data-Enrichment Agent | An agent that performs web searches and organizes its findings into a structured format. | Repo |
π± Create a LangGraph App
To create a new app from a template, use thelanggraph new
command.
uv
(recommended):
Next Steps
Review theREADME.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:
uv
(recommended):
Missing Local Package?
If you are not using
uv
and run into a βModuleNotFoundError
β or βImportError
β, 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 βawareβ 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
.- Launch Local LangGraph Server: This quick start guide shows how to start a LangGraph Server locally for the ReAct Agent template. The steps are similar for other templates.
- Deploy to LangGraph Platform: Deploy your LangGraph app using LangGraph Platform.