langflow/docs/docs/Support/troubleshooting.mdx

---
title: Troubleshoot Langflow
slug: /troubleshoot
---

import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
import Icon from "@site/src/components/icon";

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 <Icon name="Component" aria-hidden="true" /> **Core components** and  menus, try the following:

* <Icon name="Search" aria-hidden="true" /> **Search** for the component.
* Check other component categories and <Icon name="Blocks" aria-hidden="true" /> [**Bundles**](/components-bundle-components).
* Check [legacy components](/concepts-components#legacy-components), which are hidden by default.
* Check the [Changelog](https://github.com/langflow-ai/langflow/releases/latest) 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](/contributing-github-issues).

## No input in the Playground

If there is no message input field in the **Playground**, make sure your flow has a [**Chat Input** component](/chat-input-and-output) that is connected, directly or indirectly, to the **Input** port of a **Language Model** or **Agent** component.

Because the **Playground** is designed for flows that use an LLM in a query-and-response format, such as chatbots and agents, a flow must have **Chat Input**, **Language Model**/**Agent**, and **Chat Output** components to be fully supported by the **Playground** chat interface.

For more information, see [Test flows in the Playground](/concepts-playground).

## 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](/configuration-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.

### Langflow installation freezes at pip dependency resolution

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

```text
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](/get-started-installation#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:

```bash
Resolved 455 packages in 18.92s
  × Failed to build `webrtcvad==2.0.10`
  ├─▶ The build backend returned an error
  ╰─▶ 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:

```bash
sudo apt-get update
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:

```bash
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.

### Protocol buffers (protoc) required for Intel-based Macs

If you're installing Langflow on an Intel-based Mac, you may encounter installation errors if Protocol Buffers Compiler (`protoc`) is not installed.

This requirement doesn't apply to Apple Silicon Macs on ARM64.

To resolve this issue, install `protoc` using `brew install protobuf`.

For more information, including alternative installation methods, see the [Protocol buffers installation documentation](https://protobuf.dev/installation/).

### 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](https://visualstudio.microsoft.com/downloads/).

## 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:

```bash
> 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:

```bash
> 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`.

### Environment variables not available from terminal

Environment variables set in your terminal aren't automatically available to GUI-based applications like Langflow Desktop when launched through the Finder or the Start Menu.
To set environment variables for Langflow Desktop, see [Set environment variables for Langflow Desktop](/environment-variables#set-environment-variables-for-langflow-desktop).

### Access Langflow Desktop startup logs

If you encounter issues with Langflow Desktop, you might need to [access Langflow Desktop startup logs](/logging#desktop-logs) for debugging.

### User not found or inactive when running multiple flows

When running multiple local Langflow OSS instances on different ports, such as `localhost:7860` and `localhost:7861`, you might see authentication errors in the logs.
For example:

```text
[07/22/25 10:57:07] INFO     2025-07-22 10:57:07 - INFO     - utils - User not found or inactive.
```

To resolve this error, use separate browser instances or browser profiles to access each Langflow instance.

### Package is not installed

In Langflow OSS, you can follow the error message's instructions to install the missing dependency.

To manage dependencies in Langflow Desktop, see [Install custom dependencies in Langflow Desktop](/install-custom-dependencies#langflow-desktop).

### PostgreSQL asyncpg driver compatibility issue

The following error can occur when initializing Langflow with a PostgreSQL database:

```text
sqlalchemy.exc.DBAPIError: (sqlalchemy.dialects.postgresql.asyncpg.Error) <class 'asyncpg.exceptions.DataError'>: invalid input for query argument $7: datetime.datetime(2025, 10, 31, 14, 8, 5... (can't subtract offset-naive and offset-aware datetimes)
```

This error occurs because `asyncpg` has stricter timezone handling than `psycopg2`, and is not fully compatible with Langflow's current database schema.

To resolve this issue, remove `asyncpg` from your installation and use `psycopg2` instead.

### An API key must be passed as query or header

The following error can occur when attempting to sign up on the Langflow sign in page: `An API key must be passed as query or header`.

This means that `LANGFLOW_AUTO_LOGIN` is set to `false`, and only superusers can create and activate non-superuser accounts.
Therefore, you are locked out of this Langflow instance.

If you aren't an administrator, then a superuser must create and activate a non-superuser account before you can sign in.

If you are the administrator, sign in with a superuser account, or restart Langflow with `LANGFLOW_AUTO_LOGIN=true`.

For more information, see [Start Langflow Server with authentication enabled](/api-keys-and-authentication#start-a-langflow-server-with-authentication-enabled).

## Langflow upgrade issues

The following issues can occur when upgrading your Langflow version.

For information about managing Langflow versions, see [Install Langflow](/get-started-installation).

### 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:

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

To resolve this error, clear the cache by deleting the contents of your Langflow cache folder.
The filepath depends on your operating system, installation type, and configuration options.
For more information and default filepaths, see [Memory management options](/memory).

:::danger
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.
:::

### Langflow Desktop says it is running the latest version, but it is actually behind

If you are running Langflow Desktop version 1.4.2 or earlier, the UI might incorrectly report that you are on the latest version when a newer version is available.

This happens because the automatic update feature in the UI was introduced in version 1.4.2.
Earlier versions can't automatically detect or apply updates.

To resolve this issue, uninstall Langflow Desktop, and then [download and install the latest version of Langflow Desktop](https://langflow.org/desktop).

### 422 error when freezing components after upgrading Pydantic/FastAPI dependencies

If you locally upgrade your Pydantic and FastAPI dependencies, you may encounter a 422 error when trying to freeze components.

This error occurs due to changes in how request bodies are handled in newer versions of these dependencies.

If you're experiencing this issue, update your Langflow installation to version 1.6.5 or later, which includes a fix for this issue.

```bash
uv pip install langflow -U
```

## Langflow uninstall issues

The following issues can occur when uninstalling Langflow.

### Dot directory isn't deleted when uninstalling Langflow Desktop on macOS

On macOS, uninstalling Langflow Desktop deletes the `.app` file but doesn't delete files in `~/.langflow`, which includes files generated during usage like cache and settings.

If you reinstall Langflow Desktop, it starts with the existing data from the previous installation.

To fully remove a Langflow Desktop macOS installation, you must also delete `~/.langflow`:

    ```bash
    rm -rf .langflow
    ```

## Langflow MCP issues {#mcp}

The following issues can occur when using Langflow as an MCP server or client.

### Claude for Desktop doesn't use MCP server tools correctly

If Claude for Desktop doesn't use your server's tools correctly, try explicitly defining the path to your local `uvx` or `npx` executable file in the `claude_desktop_config.json` configuration file:

1. To find your `uvx` path, run `which uvx`.

    To find your `npx` path, run `which npx`.

2. In your `claude_desktop_config.json` file, add the path to your Langflow MCP server configuration, as shown in the following examples.

    <Tabs>
    <TabItem value="uvx" label="uvx" default>

    ```json
    {
      "mcpServers": {
        "PROJECT_NAME": {
          "command": "PATH_TO_UVX",
          "args": [
            "mcp-proxy",
            "http://LANGFLOW_SERVER_ADDRESS/api/v1/mcp/project/PROJECT_ID/streamable"
          ]
        }
      }
    }
    ```

    </TabItem>
    <TabItem value="npx" label="npx">

    ```json
    {
      "mcpServers": {
        "PROJECT_NAME": {
          "command": "PATH_TO_NPX",
          "args": [
            "-y",
            "supergateway",
            "--sse",
            "http://LANGFLOW_SERVER_ADDRESS/api/v1/mcp/project/PROJECT_ID/streamable"
          ]
        }
      }
    }
    ```

    </TabItem>
    </Tabs>

### MCP browser-based flows don't open a browser on Windows

This is a known issue when using MCP Tools with browser navigation actions, such as Playwright, on Windows: The agent can execute the tool successfully but the browser tab or window doesn't open.

This issue occurs because the MCP server runs from a Python process, which prevents it from opening browser windows in WSL or Windows.

To work around this issue, use the standalone MCP server approach documented in the [Playwright MCP repository](https://github.com/microsoft/playwright-mcp?tab=readme-ov-file#standalone-mcp-server).
After the server is up and running, you can add it as an HTTP/SSE server in Langflow.

For other browser navigation tools, see the provider's documentation for specific troubleshooting guidance.

### "No tools or prompts connected" on MCP servers in mixed Windows/WSL environments

If you encounter "No tools or prompts connected" errors or connection failures when using Langflow Desktop as an MCP server with clients running in different environments, such as Langflow on a Windows host and an MCP client in WSL, this is due to network isolation between Windows and WSL environments.

WSL cannot directly access Windows localhost services, and Langflow running on a Windows host is not accessible from WSL clients at `localhost:7860`.

To work around this issue, run the server and host in the same operating environment.

Alternatively, configure Langflow Desktop to accept connections from WSL at the default Windows IP address of `10.255.255.254:7860` instead of `localhost`.

### MCP Tools component loses Tool Mode option after upgrading flows {#mcp-tools-component-loses-tool-mode-option-after-upgrading-flows}

If you upgrade an existing flow that uses the [**MCP Tools** component](/mcp-tools) in **Tool Mode**, the component might lose its **Tool Mode** setting after upgrading the flow.
This can break flows that rely on the component's **Tool Mode** to expose MCP tools to agents.

If you experience this when upgrading a flow that you created in Langflow version 1.7.1 or earlier, do the following:

1. Select the **MCP Tools** component in your flow.
2. Click <Icon name="Code" aria-hidden="true"/> **Code** to open the component's code editor.
3. In the component's template structure, locate the `tool_mode` field under `inputs`.
   The field can be either missing or set to `false`.
4. Add the `tool_mode` field if it's missing, and set it to `true`:

   ```python
   tool_mode = True
   ```

5. Click **Check & Save** to apply the code changes.

## Token length limit errors in Embedding Model components

Token length errors can happen if your chunking strategy doesn't align with your embedding model's tokenization limits.
For more information, see [Tokenization errors due to chunk size](/split-text#chunk-size).

## Document processing errors in Docker containers

If you're running Langflow in a Docker container, you might encounter errors when using components that handle files or images, such as the [**Read File** component](/read-file) or [**Docling** components](/bundles-docling). To resolve these errors, you might need to install additional system dependencies.

When running Langflow in a Linux-based Docker container, Docling requires system libraries that aren't included in the base Docker image. If you see errors related to document or image processing, add the following to your Dockerfile:

```dockerfile
RUN apt-get update && apt-get install -y libgl1 libglib2.0-0
```

These dependencies are required by Docling for document processing operations.

For more information about customizing Docker images, see [Customize the Langflow Docker image with your own code](/deployment-docker#customize-the-langflow-docker-image).

## 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](/components-custom-components#error-handling-and-logging).

### Custom components not appearing in the visual editor

If your custom components are not appearing in the Langflow visual editor, try the following troubleshooting steps:

1. Ensure your components follow the [required directory structure](https://docs.langflow.org/components-custom-components#directory-structure-requirements).
    ```
    /your/custom/components/path/       # Base directory set by LANGFLOW_COMPONENTS_PATH
        └── category_name/              # Required category subfolder that determines menu name
            ├── __init__.py             # Required
            └── custom_component.py     # Component file
    ```

2. Verify each category directory includes an `__init__.py` file.
This is required for Python to recognize the directory as a module.

3. Use the command line argument instead of the environment variable for `LANGFLOW_COMPONENTS_PATH`.
If you're using the `LANGFLOW_COMPONENTS_PATH` environment variable and components aren't loading, try the `--components-path` command line argument instead:

    ```bash
    uv run langflow run --components-path /path/to/your/custom/components
    ```

If you continue to experience issues, please [report them on GitHub](https://github.com/langflow-ai/langflow/issues) with details about your directory structure and component setup.

## See also

- [Langflow GitHub Issues and Discussions](/contributing-github-issues)
- [Langflow telemetry](/contributing-telemetry)