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Hello, I have a basic question because I

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Hello, I have a basic question because I am not understanding something. I'm trying to use chromadb with docker:

import chromadb remote_db = chromadb.HttpClient() chroma_collection = remote_db.get_or_create_collection("quickstart") vector_store = ChromaVectorStore(chroma_collection=chroma_collection) storage_context = StorageContext.from_defaults(vector_store=vector_store) service_context = ServiceContext.from_defaults(embed_model=embed_model) index = VectorStoreIndex.from_documents( documents, storage_context=storage_context, service_context=service_context )
This is the code I want to make it work. I am creating a chromadb collection in one backend where the documents are allocated.
From other backend I want to create this index and make querys.
My question is, why I need to use documents in the last line of the code??
Chromadb doesn't save this data with the related vector???
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8 comments
If you already have your documents setup on chrome db you can do:

Plain Text
vector_store = ChromaVectorStore(chroma_collection=chroma_collection)
index = VectorStoreIndex.from_vector_store(vector_store=vector_store)
from_documents is when you want to add the documents to the vector store through llama_index using like SimpleDirectoryReader or a Llamahub reader
Yess I try that but I got: Error: Embedding dimension 1536 does not match collection dimensionality 384
I am always using always the default embeddings from chroma that is all-MiniLM-L6-v2
Now I am changing the embed_model of llama_index I think that after that everithing is going to be fine
yess I found the same thread. I am with some disk usage problems now to install torch and some packages, If I have another doubt I am going to put it here
Thankssss @Emanuel Ferreira
That worked fine!
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