Langflow Integration

Langflow is a low-code tool for building LLM pipelines. If you are using Langflow, you can easily enable LangWatch from their UI for analytics, evaluations and much more.

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Setup

LANGWATCH_API_KEY="your-api-key"

export LANGWATCH_API_KEY="your-api-key"

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Defining custom input and output

You can customize what LangWatch captures as the final input and output of your Langflow component for better observability.

To do this, you can add this two lines of code in the execution function of any Langflow component:

import langwatch
langwatch.get_current_trace().update(input="The user input", output="My bot output")

You can do this by first clicking on the <> Code button in any appropriate component:

Then scroll down to find the def responsible for execution of that component and paste the code above, mapping the variables as needed for your case:

The message on LangWatch will render as you defined:

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Capturing additional metadata

You can also capture additional metadata from your Langflow component. This can be useful for capturing information about the user, the conversation, or any specific information from your system.

Just like for the input and output, you can capture metadata by updating the trace, two very useful cases to capture for example are the user_id and trace_id that groups messages from the same conversation, but you can also capture any other information that you want to track.

import langwatch
langwatch.get_current_trace().update(
  metadata={
    "user_id": self.sender_name,
    "thread_id": self.session_id,
    # any other metadata you want
  }
)

For more information, check out Langflow docs.