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Troubleshoot Langflow

This page provides troubleshooting advice for issues you might encounter when using Langflow or contributing to Langflow.

Missing components​

As Langflow development continues, components are often recategorized or deprecated for better alignment or to prepare for new components.

If a component appears to be missing from the expected location on the component sidebar, try the following:

  • Search for the component or check other component categories, including Bundles.
  • Expose legacy components, which are hidden by default.
  • Check the Changelog for component changes in recent releases.
  • Make sure the component isn't already present in your flow if it is a single-use component.

If you still cannot locate the component, see Langflow GitHub Issues and Discussions.

No input in the Playground​

If there is no text box for input in the Playground, make sure your flow has a Input component that is connected to the Input port of another component.

Missing key, no key found, or invalid API key​

If you get an API key error when running a flow, try the following:

  • For all components that require credentials, make sure those components have a valid credential in the component's settings, such as the API key field.
  • If you store your credentials in Langflow global variables, make sure you selected the correct global variable and that the variable contains a valid credential.
  • Make sure the provided credentials are active, have the required permissions, and, if applicable, have sufficient funds in the account to execute the required action. For example, model providers require credits to use their LLMs.

Langflow installation issues​

The following issues can occur when installing Langflow.

C++ build tools required for Langflow Desktop on Windows​

Microsoft Windows installations of Langflow Desktop require a C++ compiler that may not be present on your system. If you receive a C++ Build Tools Required! error, follow the on-screen prompt to install Microsoft C++ Build Tools, or install Microsoft Visual Studio.

Langflow installation freezes at pip dependency resolution​

Installing Langflow OSS with pip install langflow slowly fails with this error message:


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pip is looking at multiple versions of <<library>> to determine which version is compatible with other requirements. This could take a while.

To work around this issue, install Langflow with uv instead of pip, as explained in Install and run the Langflow OSS Python package.

Linux installation fails to build required package​

When you try to install Langflow OSS on Linux, installation fails because of outdated or missing packages:


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Resolved 455 packages in 18.92s
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× Failed to build `webrtcvad==2.0.10`
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├─▶ The build backend returned an error
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╰─▶ Call to `setuptools.build_meta:__legacy__.build_wheel` failed (exit status: 1)

To resolve this error, install the required build dependencies, and then retry the Langflow installation:


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sudo apt-get update
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sudo apt-get install build-essential python3-dev

If upgrading your packages doesn't fix the issue, install gcc separately, and then retry the Langflow installation:


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sudo apt-get install gcc

Installation failure from webrtcvad package​

If you experience an error from the webrtcvad package, run uv pip install webrtcvad-wheels in your virtual environment, and then retry the Langflow installation.

Langflow startup issues​

The following issues can occur when attempting to start Langflow.

No langflow.__main__ module​

When you try to run Langflow with the command langflow run, you encounter the following error:


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> No module named 'langflow.__main__'

To resolve this issue, try the following:

  1. Run uv run langflow run instead of langflow run.
  2. If that doesn't work, reinstall the latest Langflow version with uv pip install langflow -U.
  3. If that doesn't work, reinstall Langflow and its dependencies with uv pip install langflow --pre -U --force-reinstall.

Langflow runTraceback​

When you try to run Langflow using the command langflow run, you encounter the following error:


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> langflow runTraceback (most recent call last): File ".../langflow", line 5, in <module> from langflow.__main__ import mainModuleNotFoundError: No module named 'langflow.__main__'

There are two possible reasons for this error:

  • Multiple Langflow installations: You installed Langflow using pip install langflow but you already had a previous version of Langflow installed in your system. In this case, you might be running the wrong executable.

    To solve this issue, run the correct executable by running python -m langflow run instead of langflow run.

    If that doesn't work, try uninstalling and reinstalling Langflow with uv pip install langflow --pre -U.

  • Version conflict during installation: Some version conflicts might have occurred during the installation process. To resolve this issue, reinstall Langflow and its dependencies by running python -m pip install langflow --pre -U --force-reinstall.

Langflow upgrade issues​

The following issues can occur when upgrading your Langflow version.

For information about managing Langflow versions, see Install Langflow.

Something went wrong running migrations​

The following error can occur during Langflow upgrades when the new version can't override langflow-pre.db in the Langflow cache folder:


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> Something went wrong running migrations. Please, run 'langflow migration --fix'

To resolve this error, clear the cache by deleting the contents of the Langflow cache folder.

important

Clearing the cache erases your settings. If you want to retain your settings files, create a backup of those files before clearing the cache folder.

The cache folder location depends on your OS:

  • Linux: home/<username>/.cache/langflow/
  • WSL2 on Windows: home/<username>/.cache/langflow/
  • macOS: /Users/<username>/Library/Caches/langflow/

MCP server issues​

Custom components and integrations issues​

For troubleshooting advice for a third-party integration, see the information about that integration in the Langflow documentation and the provider's documentation.

If you are building a custom component, see Error handling and logging for custom Python components.

See also​

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