Disclaimer: Experimental PR review

Greptile Summary

Updated On: 2025-09-18 13:08:28 UTC

This PR adds a comprehensive test case to the LangChain end-to-end test suite to verify that the Langfuse CallbackHandler properly handles error scenarios. The test specifically validates that when a LangChain operation fails (such as using an invalid OpenAI model), the resulting Langfuse observation is correctly marked with level='ERROR' and includes the error details in the statusMessage field.

The test follows the established pattern in the codebase by:

1. Setting up a trace with proper metadata (user ID, session ID, tags)
2. Intentionally triggering an error by using an invalid model name 'invalid-model-name-that-does-not-exist'
3. Properly handling the expected error with try-catch blocks
4. Validating that the error was captured and contains expected content
5. Fetching the resulting trace and asserting that observations have the correct error state

This change enhances test coverage for the LangChain integration's error handling capabilities, ensuring that failed operations are properly tracked and observable in Langfuse traces for debugging and monitoring purposes. The test integrates seamlessly with the existing test infrastructure and follows the same timeout patterns (30 seconds) as other tests in the suite.

Confidence score: 5/5

• This PR is safe to merge with minimal risk as it only adds test coverage without modifying production code
• Score reflects the addition of valuable test coverage for error handling scenarios with well-structured test implementation
• No files require special attention as this is a straightforward test addition following established patterns