Logs

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

Langflow produces logs for individual flows and the Langflow application itself using the structlog library for logging.

By default, OSS Langflow writes logs to stdout. To write logs to a file, set LANGFLOW_LOG_FILE to the desired path.

Log storage

The LANGFLOW_CONFIG_DIR environment variable controls where Langflow stores its configuration and data files. The default location depends on your operating system:

• Langflow Desktop:

  • macOS: /Users/<username>/Library/Logs/com.LangflowDesktop
  • Windows: C:\Users\<username>\AppData\Local\com.LangflowDesktop\logs

• OSS Langflow (all installation methods, including uv pip install and git clone):

  • macOS: /Users/<username>/Library/Caches/langflow
  • Linux: /home/<username>/.cache/langflow
  • Windows/WSL: C:\Users\<username>\AppData\Local\langflow\langflow\Cache

To customize log storage locations and behaviors, set the following Langflow environment variables in your Langflow .env file, and then start Langflow with uv run langflow run --env-file .env:

View logs in real-time

By default, OSS Langflow writes logs to stdout. To write logs to a file that you can tail, do the following:

1. Set LANGFLOW_LOG_FILE to a file path in your .env file:

   textCopy

   LANGFLOW_LOG_FILE=/path/to/langflow.log
   

2. Start Langflow with your .env file:

   bashCopy

   uv run langflow run --env-file .env
   

3. Change to the directory where you set LANGFLOW_LOG_FILE:

   <Tabs groupId="cd-command"> <TabItem value="macOS" label="macOS" default>
   bashCopy

   cd /Users/**USERNAME**/Library/Caches/langflow
   

   </TabItem> <TabItem value="Windows" label="Windows">
   cmdCopy

   cd C:\Users\**USERNAME**\AppData\Local\com.LangflowDesktop\logs
   

   </TabItem> </Tabs>

4. Tail the log file:

   <Tabs groupId="tail-command"> <TabItem value="macOS" label="macOS" default>
   bashCopy

   tail -f langflow.log
   

   </TabItem> <TabItem value="Windows" label="Windows">
   cmdCopy

   Get-Content -Wait -Path langflow.log
   

   </TabItem> </Tabs>

   If you don't see new log entries, check that Langflow is running, and perform some actions to generate logs events. You can also check the terminal where you started Langflow to see if logs are being printed there.

Flow and component logs

After you run a flow, you can inspect the logs for each component and flow run. For example, you can inspect Message objects ingested and generated by Input and Output components.

View flow logs

In the visual editor, click Logs to view logs for the entire flow:

Then, click the cells in the inputs and outputs columns to inspect the Message objects. For example, the following Message data could be the output from a Chat Input component:

    "messages": [
    {
        "message": "What's the recommended way to install Docker on Mac M1?",
        "sender": "User",
        "sender_name": "User",
        "session_id": "Session Apr 21, 17:37:04",
        "stream_url": null,
        "component_id": "ChatInput-4WKag",
        "files": [],
        "type": "text"
    }
    ],

In the case of Input/Output components, the original input might not be structured as a Message object. For example, a language model component can pass a raw text response to a Chat Output component that is then transformed into a Message object.

You can find .log files for flows at your Langflow installation's log storage location. For filepaths, see Log storage.

View chat logs

In the Playground, you can inspect the chat history for each chat session. For more information, see View chat history.

View output from a single component

When debugging issues with the format or content of a flow's output, it can help to inspect each component's output to determine where data is being lost or malformed.

To view the output produced by a single component during the most recent run, click <Icon name="TextSearch" aria-hidden="true"/> Inspect output on the component in the visual editor.

Access Langflow Desktop logs {#desktop-logs}

If you encounter issues with Langflow Desktop, you might need to access startup logs for debugging. Follow the steps for your operating system.

1. Open Terminal and run:

   bashCopy

   cd ~/Library/Logs/com.LangflowDesktop
   

2. To open the folder and view the log files, run the command:

   bashCopy

   open .
   

3. Locate the langflow.log file.

1. Open the Command Prompt (CMD), and then run the following command:

   cmdCopy

   cd %LOCALAPPDATA%\com.LangflowDesktop\cache
   

2. Open the folder and view the log files:

   cmdCopy

   start .
   

3. Locate the langflow.log file.

You can use the log file to investigate the issue on your own, add context to a GitHub Issue, or send it to support for debugging assistance.

The log file is only created when Langflow Desktop runs. If you don't see a log file, try starting Langflow Desktop first, then check for the log file.

Log format

By default, structlog uses ConsoleRenderer to produce human-readable output with the following structure:

For example:

2026-05-17T18:18:29Z [info     ] incoming request    logger=langflow.api.run flow_id=flow-718 user_id=user-4823

JSON log format

Set LANGFLOW_LOG_ENV=container to switch structlog's terminal processor to JSONRenderer, so every line written to stdout is a JSON object containing the event message, level, timestamp, logger name, exception structure, and service metadata.

A typical record in JSON mode looks like the following:

{
  "event": "incoming request",
  "level": "info",
  "logger": "langflow.api.run",
  "timestamp": "2026-05-17T18:18:29.100798Z",
  "service": "langflow",
  "version": "1.10.0",
  "environment": "production",
  "user_id": "user-4823",
  "flow_id": "flow-718",
  "authorization": "***",
  "cookie": "***",
  "request_body": {
    "input": "Tell me a joke",
    "api_key": "***",
    "session_id": "Session Apr 21, 17:37:04"
  }
}

When a log record includes an exception, the exception field contains a structured traceback instead of a plain string:

{
  "event": "flow run failed",
  "level": "error",
  "logger": "langflow.api.run",
  "timestamp": "2026-05-17T18:18:32.412Z",
  "service": "langflow",
  "exception": [
    {
      "exc_type": "ConnectionError",
      "exc_value": "upstream returned 503",
      "frames": [
        {"filename": "/app/.../runner.py", "lineno": 142, "name": "run_flow"}
      ]
    }
  ]
}

Frame locals, which are local variables at each stack frame, are intentionally excluded by default because they can contain API keys, request bodies, and environment values. Set LANGFLOW_LOG_TRACE_LOCALS=true to include them for local debugging.

Stdlib loggers

Third-party libraries that use Python's standard logging module (uvicorn, sqlalchemy, httpx, langchain, asyncio) are routed through the same JSON stream in container mode. Their original logger name is preserved on the logger field, so log queries that work for application loggers also work for library output.

OpenTelemetry trace correlation

If opentelemetry-api is installed and an active span is present, every log record automatically picks up trace_id and span_id. OpenTelemetry is not a hard dependency; if it is not installed, the processor is a no-op and nothing else changes.

See also

• Grafana and Loki
• Logs endpoints
• Memory management options
• Configure an external PostgreSQL database
• Grafana and Loki