[Fixed] No Module Named Langchain

Langchain is a widely used library to provide you with ease of access in the world of Large language models (LLMs).

About the error

So, you might be working on a chatbot or a code generation tool or a generative question answering (GQA) model, and you might have felt the need to use a langchain for the necessary imports. However, after executing the piece of code, you got the ‘No module named langchain’ error. This article covers the reasons for this error along with the methods of resolving this error.

Reasons for the Error No module named langchain

You may find the ‘No module named langchain’ error due to a couple of reasons like the ones listed below:

The library was not found.
The path to the langchain library is not correct.
The environment of the langchain doesn’t match the Python environment.

Resolving the error

The given methods will help you avoid the No module named langchain error or get rid of it completely.

Update langchain library

use the pip command to update the given module. Sometimes, the installation process is not complete. You just need to enter this command in the terminal or command prompt:

pip install –upgrade langchain

However, if you’re working on Python v3.9, you can specify it in the command itself like this:

pip3.9 install –upgrade langchain

Also, in the case of version 3.10, use the following command:

python3.10 -m pip install langchain

Rectify the path of the langchain module

Use the given command to see if the langchain belongs to the path or not.

import sys

print(sys.path)

In case it is not present, you should consider adding the path of the langchain module to the environment variables also.

Environment correction

Sometimes, there can be an issue with the environment where you have installed the langchain module. You need to see if the environment where the langchain module exists is the same as your Python environment.

This implies that if a Python 2 or Python 3 environment exists, make sure that you install a similar version of langchain.

Also, you may work in a virtual environment. To create a virtual environment, enter the given prompt:

python -m ensurepip –default-pip

If you’re working with Python 3.9, run the following:

python3.9 -m ensurepip --default-pip

The next step includes setting up this environment using: python -m venv mylangchainenv

For Python 3.9, the command is: python3.9 -m venv mylangchainenv

Now, you can activate this environment either on Windows or Mac or Linux using the first and second commands, respectively.

On Windows, run: mylangchainenv\Scripts\activate

On macOS and Linux, run: mylangchainenv/bin/activate

The last step involves installing the langchain library in this virtual environment using pip install –upgrade langchain.

Other libraries

You need to check if other langchain dependencies, like langchain agents, have been correctly installed. Some of them are langchain.agents or langchain.document_loaders.

Resolving ‘No module named langchain’ with databricks

The best solution is to update the pip command. Each notebook in Databricks is segregated to prevent confusion. Different notebooks have packages with different versions of the same module, so Databricks notebooks are separated from each other. You can, however, install this package at the cluster level too. This can happen in cases when the same langchain module works with those notebooks.

Replace the package name with the langchain here.

dbutils.library.installPyPI(“package-name”)

This will reduce your time and space occupancy.

Resolving the error with Linux

ModuleNotFoundError: No module named ‘langchain’ is a common error in Linux.

Does langchain exist?

In order to combat this error, first, you should verify whether the langchain library exists or not.

$ pip show langchain

If it says the package is not found, then it shows there is some issue with the installation.

Installing langchain

Next up, you need to install the library. Now, there are three specifications. You can install langchain’s minimal version, use the version with LLMS providers, or install the version with its complete components. The given methods are used to install this library in these three ways.

$ pip install langchain  #1
$ pip install langchain[llms]   # 2
$ pip install langchain[all]      #3

Reinstalling LangChain

If any of these don’t provide the solution to you, consider reinstalling the library after uninstalling it.

pip uninstall langchain

pip install langchain

no module named ‘langchain.chat_models’

This error arises when the langchain.chat_models module can’t be found. You can see if the environment variables list has a langchain. For Linux, you can use this command:

export PYTHONPATH=/path/to/langchain:$PYTHONPATH

Otherwise, see if any other file exists that you have named langchain.py. There may be some ambiguity, and the interpreter might import that file instead of the langchain library.

If this doesn’t work, use the ‘pip show langchain’ command to see if the library exists or not and then install it using the pip command only, which is ‘pip install langchain’.

no module named ‘langchain.callbacks.manager’

The older langchain module versions might not consist of the callbacks.manager module. Thus, you should install the updated version only. Version 0.0.140 supports this. Else, you should consider re-installing the library. This will resolve the no module named ‘langchain.callbacks.manager’ error.

no module named ‘langchain.memory’

The version issue exists here as well. The older versions of langchain didn’t have the memory module. You should consider installing the updated 0.0.140 version of the langchain library.

no module named ‘langchain.utilities’

You should consider installing the langchain library again. You may choose a virtual environment. Otherwise, upgrade pip. Versions of pip and setuptools that are outdated can lead to incorrect package installations.

pip install --upgrade pip setuptools

Tips while working with langchain

Here are some tips for you while working with langchain.

Python 3.6 or higher supports the langchain module.
The same goes for a jupyter notebook.
LangChain documentation is necessary to check. It has other details about the library.

FAQs

What are the key factors of using a langchain?

Productivity, Scalability, Flexibility, and Reliability are its top factors.

Conclusion

This article covers ‘No module named langchain’ in detail. It discusses methods to resolve this error and certain tips that will be handy to the user while working with the langchain library.