Ingesting and Querying Large Document Collections with ...

At a glance

The community member is trying to find a way to pass a large number of documents to llamaindex so they can ask their large language models (LLMs) to answer questions about them. The comments suggest starting with the llamaindex documentation, but the community member is encountering issues with installing and using the library. They have provided a sample Python script that is not working due to import errors. The community members discuss potential solutions, such as using a different Python version and correcting the imports, but there is no explicitly marked answer.

Useful resources

mmeaning

I try to find a way to pass a big amount fo documents to llamaindex, so I could ask my LLMS to answer questions about them

14 comments

WWhiteFang_Jr

Yes, You are right

WWhiteFang_Jr

You can start from here: https://docs.llamaindex.ai/en/stable/getting_started/starter_example/

mmeaning

hey ! thanks for creating this thread

mmeaning

I've installed it using the instructions but I'm getting an error so far :

mmeaning

Plain Text

`
(llama_env) meaning@Ottis llamaindex_project % pip list | grep llama-index
llama-index                             0.12.2
llama-index-agent-openai                0.4.0
llama-index-cli                         0.4.0
llama-index-core                        0.12.2
llama-index-embeddings-openai           0.3.1
llama-index-indices-managed-llama-cloud 0.6.3
llama-index-legacy                      0.9.48.post4
llama-index-llms-openai                 0.3.2
llama-index-multi-modal-llms-openai     0.3.0
llama-index-program-openai              0.3.1
llama-index-question-gen-openai         0.3.0
llama-index-readers-file                0.4.0
llama-index-readers-llama-parse         0.4.0
(llama_env) meaning@Ottis llamaindex_project % nano query_documents.py
(llama_env) meaning@Ottis llamaindex_project % python query_documents.py
Traceback (most recent call last):
  File "/Users/meaning/llamaindex_project/query_documents.py", line 2, in <module>
    from llama_index import SimpleDirectoryReader, VectorStoreIndex
ImportError: cannot import name 'SimpleDirectoryReader' from 'llama_index' (unknown location)

mmeaning

I've create a short python script :

mmeaning

Plain Text

`
import requests
from llama_index import SimpleDirectoryReader, VectorStoreIndex
from llama_index.llms.ollama import Ollama

# Configure Ollama as the backend LLM
ollama = Ollama(
    model="llama3:8b-instruct-q6_K",  # Specify the model
    base_url="http://127.0.0.1:11434"  # Local URL for Ollama
)

# Load the documents
documents_path = "/Users/meaning/Downloads/PES"
documents = SimpleDirectoryReader(documents_path).load_data()

# Create an index with Ollama
index = VectorStoreIndex.from_documents(documents, llm=ollama)

# Query the index
query_engine = index.as_query_engine()
response = query_engine.query("What are the key points mentioned in my documents?")
print(f"Ollama response: {response}")

mmeaning

but output is :

mmeaning

Plain Text

`
(llama_env) meaning@Ottis llamaindex_project % python query_documents.py
Traceback (most recent call last):
  File "/Users/meaning/llamaindex_project/query_documents.py", line 2, in <module>
    from llama_index import SimpleDirectoryReader, VectorStoreIndex
ImportError: cannot import name 'SimpleDirectoryReader' from 'llama_index' (unknown location)

mmeaning

is there no project that actually enables me to install llamaindex inside a container, get a nice webui to link my files, and link it to my running ollama ?

mmeaning

that would be fantastic

mmeaning

ok it looks like it didn't like python 3.13... works better with 3.11

WWhiteFang_Jr

The imports are not correct:
from llama_index.core import SimpleDirectoryReader, VectorStoreIndex

Add a reply

Find answers from the community

Ingesting and Querying Large Document Collections with LlamaIndex