How to fix the ModuleNotFoundError, AttributeError, and NotImplementedError exceptions in LangChain

Whether you're playing around with LangChain or building the next big RAG LLM app, you'll probably run into one of these issues at some point.

How to fix common exceptions in LangChain written on a black and white background with question marks
How to Fix the Common ModuleNotFoundError, AttributeError, and NotImplementedError Exceptions in LangChain

This is probably going to be a very short post, but since I've been recently active on StackOverflow I saw an increasing number of questions from users having issues that can be solved using a simple fix.

While the fix is pretty straightforward, this post may be helpful to whoever is looking for a quick solution.

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This post will be updated in the future to include similar errors and issues with LangChain.

tl;dr

If you're playing around with the Python LangChain package and run into a ModuleNotFoundError, AttributeError, or NotImplementedError, even if you've followed the steps in the official documentation, you'll need to make sure that you're running the latest version of LangChain.

For more information and insights regarding these exceptions, read below.


Common LangChain Issues

Let's take a quick look at the below common issues from the web:

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There are more issues, as well as duplicates of the above. Only the above issues were mentioned to keep this post simple and short.

Getting the ModuleNotFoundError Exception

ModuleNotFoundError occurs when Python fails to load a specific module. You may run into one or more similar issues:

  • modulenotfounderror: no module named 'langchain'
  • modulenotfounderror: no module named 'langchain.agents'
  • modulenotfounderror: no module named 'langchain.document_loaders'
  • modulenotfounderror: no module named 'langchain.embeddings.base' 

If you find yourself wasting hours trying to debug one of the above (or any other similar) exception, scroll to the bottom of this post to try a quick solution.

Getting the AttributeError Exception

An AttributeError in Python is an exception (or error) that occurs when an object does not have the specified attribute or method that you're trying to access.

An example of this exception in LangChain:

...
chain.input_schema.schema()
...

# May result in the below error
AttributeError: 'RunnableSequence' object has no attribute 'input_schema'

Example of AttributeError in LangChain

This means that the chain of type RunnableSequence does not have an input_schema attribute.

Getting the NotImplementedError Exception

NotImplementedError in Python is an exception that is raised when a function or method has not been implemented in a given class.

An example of this exception in LangChain:

...
pipeline.save("file.json")
...

# May result in the below error
NotImplementedError: Saving not supported for this chain type.

Example of NotImplementedError in LangChain

This means that the save method that is being called on the pipeline object is simply not implemented or supported.

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Due to the frequent LangChain package updates, the most probable reason for such issues and exceptions is an outdated version of LangChain on your machine. You could have simply installed LangChain a few days ago, but the docs got updated the next day.

How to solve these exceptions

The first thing you should try is to upgrade your LangChain version. You can simply do so by running this pip command in your terminal:

pip install langchain==0.0.329

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Version 0.0.329 is the latest as of today (Nov. 2, 2023). You can see a release history on this page.

To check your current version using pip, run the following command in your terminal and look for the Version attribute:

pip show langchain

>> Name: langchain
>> Version: 0.0.327

The second thing you can try it to check your Python version. Sometimes having multiple Python versions could make things messy. It seems that moving to Python version 11.x solves most of the ModuleNotFoundError exceptions.


If these suggestions do not resolve your problem, feel free to leave a comment below. If you're on StackOverflow, feel free to ask a new question and tag LangChain. I also try to assist there if I can.

Conclusion

Given that LangChain is still relatively new and going through multiple updates and changes due to its increasing popularity and growing community, the team is releasing a new version almost every couple of days.

So, in case you run into similar issues as the ones we've seen in this post, check your installed version first and upgrade if needed. If you're still having issues, go ahead and subscribe for 0$ to share your issue in the comments below!

Thanks for reading and I hope this post helped in your coding journey.