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# How to Set Up a LangGraph Application with pyproject.toml
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A LangGraph application must be configured with a [LangGraph 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.
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A LangGraph application must be configured with a [LangGraph configuration file](../reference/cli.md#configuration-file) in order to be deployed to LangGraph Platform (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.
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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.
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[tool.poetry]
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name = "my-agent"
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version = "0.0.1"
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description = "An excellent agent build for LangGraph cloud."
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description = "An excellent agent build for LangGraph Platform."
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authors = ["Polly the parrot <1223+polly@users.noreply.github.com>"]
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license = "MIT"
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readme = "README.md"
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@@ -138,7 +138,7 @@ graph = workflow.compile()
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```
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!!! warning "Assign `CompiledGraph` to Variable"
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The build process for LangGraph Cloud requires that the `CompiledGraph` object be assigned to a variable at the top-level of a Python module.
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The build process for LangGraph Platform requires that the `CompiledGraph` object be assigned to a variable at the top-level of a Python module.
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Example file directory:
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