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docs: Correct the reference repo in the Cloud - Setup App (pyproject.toml) documents (#1607)

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docs/docs/cloud/deployment/setup_pyproject.md
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# How to Set Up a LangGraph Application for Deployment
A LangGraph application must be configured with a [LangGraph API configuration file](../reference/cli.md#configuration-file) in order to be deployed to LangGraph Cloud (or to be self-hosted). This how-to guide discusses the basic steps to setup a LangGraph application for deployment using `pyproject.toml` to define your package's dependencies.
A LangGraph application must be configured with a [LangGraph API configuration file](../reference/cli.md#configuration-file) in order to be deployed to LangGraph Cloud (or to be self-hosted). This how-to guide discusses the basic steps to setup a LangGraph application for deployment using `pyproject.toml` to define your package's dependencies.
This walkthrough is based on [this repository](https://github.com/langchain-ai/langgraph-example), which you can play around with to learn more about how to setup your LangGraph application for deployment.
This walkthrough is based on [this repository](https://github.com/langchain-ai/langgraph-example-pyproject), which you can play around with to learn more about how to setup your LangGraph application for deployment.
!!! tip "Setup with requirements.txt"
If you prefer using `requirements.txt` for dependency management, check out [this how-to guide](./setup.md).
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Dependencies can optionally be specified in one of the following files: `pyproject.toml`, `setup.py`, or `requirements.txt`. If none of these files is created, then dependencies can be specified later in the [LangGraph API configuration file](#create-langgraph-api-config).
The dependencies below will be included in the image, you can also use them in your code, as long as with a compatible version range:
```
langgraph>=0.2.7,<0.3.0
langgraph-checkpoint>=1.0.4