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Telemetry

Langflow uses anonymous telemetry to collect statistics about feature usage and performance. The Langflow team uses this data to identify popular features and areas that need improvement based on actual usage patterns. This helps prioritize development efforts on the most impactful changes and popular features.

Privacy​

The Langflow team respects your privacy, and the team is committed to protecting your data.

Langflow telemetry doesn't collect any personal information or sensitive data. All telemetry data is anonymized and used solely for improving Langflow.

Opt out of telemetry​

To opt out of telemetry, set DO_NOT_TRACK=True in your Langflow environment variables before starting Langflow. This disables telemetry data collection.

Data that Langflow collects​

Langflow telemetry collects data on flow runs, your environment, and component usage.

Run​

This telemetry event is sent every time a flow is executed.

  • IsWebhook: Indicates whether the operation was triggered with a webhook.
  • Seconds: Duration in seconds for how long the operation lasted, providing insights into performance.
  • Success: Boolean value indicating whether the operation was successful, helping identify potential errors or issues.
  • ErrorMessage: Provides error message details if the operation was unsuccessful, aiding in troubleshooting and enhancements.

Shutdown​

This telemetry event captures information about application lifecycle and runtime duration.

  • TimeRunning: Total runtime before shutdown, which is useful for understanding the application lifecycle and optimizing uptime.

Version​

This telemetry event is sent once when the telemetry service starts.

  • Version: The specific version of Langflow used, which helps in tracking feature adoption and compatibility.
  • Platform: Operating system of the host machine, which helps determine the most popular platforms for development and testing efforts.
  • Python: The version of Python used, assisting in maintaining compatibility and support for various Python versions.
  • Arch: Architecture of the system, such as x86 or ARM, which helps prioritize hardware optimization and testing in the Langflow codebase.
  • AutoLogin: Indicates whether the auto-login feature is enabled, reflecting user preference settings.
  • CacheType: Type of caching mechanism used, which impacts performance and efficiency.
  • BackendOnly: Boolean indicating whether Langflow is running in backend-only mode, useful for understanding deployment configurations.
  • Desktop: Indicates whether Langflow is running in desktop mode (Langflow Desktop), helping to understand usage patterns across different deployment types.

Playground​

This telemetry event monitors performance and usage patterns in the Playground environment.

  • Seconds: Duration in seconds for Playground execution, offering insights into performance during testing or experimental stages.
  • ComponentCount: Number of components used in the Playground, which helps understand complexity and usage patterns.
  • Success: Success status of the Playground operation, aiding in identifying the stability of experimental features.

Component​

This telemetry event is sent for each component execution.

  • Name: Identifies the component, providing data on which components are most utilized or prone to issues.
  • Seconds: Time taken by the component to execute, offering performance metrics.
  • Success: Whether the component operated successfully, which helps in quality control.
  • ErrorMessage: Details of any errors encountered, crucial for debugging and improvement.
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