Why does LangChain's aapply method fail with an OpenAIObject operand error?

Below is an explanation and some troubleshooting steps based on the LangChain and OpenAI API documentation:

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What’s Happening

The error

TypeError: unsupported operand type(s) for +=: 'OpenAIObject' and 'OpenAIObject'

occurs during the aggregation of token usage in LangChain’s internal _combine_llm_outputs method. This suggests that the fields returned by the OpenAI API for token usage (such as prompt_tokens or completion_tokens) are now wrapped in an OpenAIObject rather than being simple integers, so the built‑in addition operator doesn’t directly work with them.

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Why This May Happen Suddenly

Although you haven’t changed your own code, one or more of your dependencies may have updated in the past few days. Two likely causes include:

• OpenAI API Changes: The response format from the OpenAI API may have changed so that token usage values are now returned as objects rather than plain integers.
• LangChain Updates: LangChain might have updated its handling for token usage aggregation, and the update is not handling the OpenAIObject fields correctly.

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Steps to Troubleshoot and Resolve

1. Check Package Versions:
   Verify the versions of your installed packages (OpenAI and LangChain). It could be that one of these libraries recently updated, leading to this change. For example:

   BASHCopied
   pip freeze | grep -E 'openai|langchain'

   If you see a recent update, consider reverting to an earlier version or checking the changelog for breaking changes.

2. Update LangChain (or OpenAI) if Available:
   Look for any updates or patches in the LangChain repository or on the OpenAI API documentation regarding changes in response structure. Upgrading to the latest patch version might include a fix that correctly extracts or converts the token usage numbers:

   BASHCopied
   pip install --upgrade langchain

3. Manual Conversion Workaround:
   If the issue persists and you need a fast workaround, you can consider intercepting the token usage values and explicitly converting them to integers before they’re aggregated. For example, if you’re implementing a custom chain or subclassing, you could override the method that combines token usage:

   PYTHONCopied
   def _combine_llm_outputs(self, llm_outputs):
       overall_token_usage = {}
       for output in llm_outputs:
           for k, v in output.get("usage", {}).items():
               # Convert the OpenAIObject to an int if needed
               v_int = int(v) if isinstance(v, OpenAIObject) else v
               overall_token_usage[k] = overall_token_usage.get(k, 0) + v_int
       return overall_token_usage

   Note that this change would be inside your own code; modifying the library’s internals is not generally recommended, so it’s best to check whether an update fixes the issue.

4. Review GitHub Issues / Forums:
   Since this started happening suddenly without changes on your end, check if others have reported similar issues in the LangChain GitHub repository or within the OpenAI community. There might be an ongoing discussion or an official recommended fix.

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Conclusion

The error is triggered because the token usage values are now OpenAIObjects rather than integers. Reviewing package versions, updating libraries, and possibly applying a manual conversion (if urgent) will help resolve the issue. Always refer to the latest documentation for any changes introduced by either LangChain or OpenAI.

If you need further assistance or more detailed debugging steps on integrating translations with LangChain, feel free to ask!