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docs: update getting started docs for studio (#3542)
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@@ -59,12 +59,10 @@ LangGraph makes it easy to manage conversation [memory](../concepts/memory.md) i
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[Human-in-the-loop](../concepts/human_in_the_loop.md) functionality allows
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you to involve humans in the decision-making process of your graph. These how-to guides show how to implement human-in-the-loop workflows in your graph.
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Key workflows:
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- [How to wait for user input](human_in_the_loop/wait-user-input.ipynb): A basic example that shows how to implement a human-in-the-loop workflow in your graph using the `interrupt` function.
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- [How to review tool calls](human_in_the_loop/review-tool-calls.ipynb): Incorporate human-in-the-loop for reviewing/editing/accepting tool call requests before they executed using the `interrupt` function.
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Other methods:
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@@ -290,10 +288,9 @@ Graph execution can take a while, and sometimes users may change their mind abou
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LangGraph Studio is a built-in UI for visualizing, testing, and debugging your agents.
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- [How to connect to a LangGraph Cloud deployment](../cloud/how-tos/test_deployment.md)
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- [How to connect to a LangGraph Platform deployment](../cloud/how-tos/test_deployment.md)
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- [How to connect to a local dev server](../how-tos/local-studio.md)
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- [How to connect to a local deployment (Docker)](../cloud/how-tos/test_local_deployment.md)
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- [How to test your graph in LangGraph Studio (MacOS only)](../cloud/how-tos/invoke_studio.md)
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- [How to interact with threads in LangGraph Studio](../cloud/how-tos/threads_studio.md)
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- [How to add nodes as dataset examples in LangGraph Studio](../cloud/how-tos/datasets_studio.md)
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- [How to engineer prompts in LangGraph Studio](../cloud/how-tos/iterate_graph_studio.md)
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@@ -312,4 +309,4 @@ These are the guides for resolving common errors you may find while building wit
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These guides provide troubleshooting information for errors that are specific to the LangGraph Platform.
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- [INVALID_LICENSE](../troubleshooting/errors/INVALID_LICENSE.md)
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- [INVALID_LICENSE](../troubleshooting/errors/INVALID_LICENSE.md)
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@@ -1,15 +1,6 @@
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# How to connect a local agent to LangGraph Studio
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This guide shows you how to connect your local agent to [LangGraph Studio](../concepts/langgraph_studio.md) for visualization, interaction, and debugging.
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## Connection Options
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There are two ways to connect your local agent to LangGraph Studio:
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- [Development Server](../concepts/langgraph_studio.md#development-server-with-web-ui): Python package, all platforms, no Docker
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- [LangGraph Desktop](../concepts/langgraph_studio.md#desktop-app): Application, Mac only, requires Docker
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In this guide we will cover how to use the development server as that is generally an easier and better experience.
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This guide shows you how to connect your local agent to [LangGraph Studio](../concepts/langgraph_studio.md) for visualization, interaction, and debugging using the development server.
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## Setup your application
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@@ -24,9 +15,8 @@ You will need to make sure to install the `inmem` extras.
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???+ note "Minimum version"
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The minimum version to use the `inmem` extra with `langgraph-cli` is `0.1.55`.
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Python 3.11 or higher is required.
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The minimum version to use the `inmem` extra with `langgraph-cli` is `0.1.55`.
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Python 3.11 or higher is required.
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```shell
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pip install -U "langgraph-cli[inmem]"
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@@ -41,7 +31,7 @@ pip install -U "langgraph-cli[inmem]"
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langgraph dev
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```
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This will look for the `langgraph.json` file in your current directory.
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This will look for the `langgraph.json` file in your current directory.
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In there, it will find the paths to the graph(s), and start those up.
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It will then automatically connect to the cloud-hosted studio.
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@@ -89,4 +79,4 @@ Then attach your preferred debugger:
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2. Click + and select "Python Debug Server"
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3. Set IDE host name: `localhost`
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4. Set port: `5678` (or the port number you chose in the previous step)
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5. Click "OK" and start debugging
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5. Click "OK" and start debugging
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