llama_index Library ImportError in Python

Python’s dynamic nature and its extensive libraries make it a favorite among developers. However, with great power comes great responsibility, and sometimes, great headaches. One such headache can be the ImportError. Recently, I encountered a problem when trying to import certain modules from the llama_index library. In this post, I’ll walk you through the problem and provide a unique solution to resolve it.

The Problem

we may encounter the following error when trying to import modules from llama_index:

ImportError: cannot import name 'VectorStoreIndex' from 'llama_index' (unknown location)

Here’s the exact code snippet that caused the issue:

from llama_index import VectorStoreIndex, SimpleDirectoryReader, ServiceContext
from llama_index.llms import HuggingFaceLLM
from llama_index.prompts.prompts import SimpleInputPrompt

I had run this same code successfully earlier in the day, so this error was puzzling. Even after reinstalling the library using !pip install llama_index, the problem persisted across various environments, including local Jupyter notebooks, Google Colab, and Amazon SageMaker.

Understanding the Cause

After some investigation, I found that the llama_index library had undergone some updates, leading to changes in its module structure. The documentation provided the necessary insights to adapt to these changes.

The Solution

To resolve the ImportError, follow these steps:

1. Update Your Imports: The modules have been reorganized. Here’s how you should update your import statements:

   from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, ServiceContext
   from llama_index.llms.huggingface import HuggingFaceLLM
   from llama_index.prompts import SimpleInputPrompt
   

2. Reinstall the Library: Ensure that you are using the latest version of the library. Sometimes, uninstalling and reinstalling can resolve any leftover conflicts from previous versions.

   pip uninstall llama_index
   pip install llama_index
   

3. Check for Additional Dependencies: If you need to use a specific vector store like Chroma, you may need additional installations:

   pip install llama-index-vector-stores-chroma
   

   And then import it as follows:

   from llama_index.vector_stores.chroma import ChromaVectorStore
   

Practical Example

Here’s a complete example incorporating the updated imports and demonstrating their usage:

from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, ServiceContext
from llama_index.llms.huggingface import HuggingFaceLLM
from llama_index.prompts import SimpleInputPrompt

# Initialize the components
vector_store = VectorStoreIndex()
directory_reader = SimpleDirectoryReader('/path/to/data')
service_context = ServiceContext()

# Example LLM and prompt
llm = HuggingFaceLLM(model_name='gpt-3.5-turbo')
prompt = SimpleInputPrompt(prompt_text="What is the capital of France?")

# Usage demonstration
data = directory_reader.read()
vector_store.add_documents(data)
response = llm.generate(prompt)
print(response)

Encountering import errors can be frustrating, especially when library updates cause breaking changes. By following the steps outlined above, you should be able to resolve the ImportError related to llama_index and adapt your code to work with the updated library structure. Always refer to the latest documentation for any changes in module organization and dependencies.