Llama Index Setup for Knowledge Graph and LLM Agents

Question

Hello just starting to build a knowledge graph or long term memory for my LLM agents

evaluating llama index for the same.

Couple of quick questions -

is there a s3 bucket loder in llama index
i dont understand vector_store = ChromaVectorStore(chroma_collection=chroma_collection)

storage_context = StorageContext.from_defaults(vector_store=vector_store)
why do i need to send the vector store while load index and storage context both when storage context itself knows whats the vector store used ?

do i need to store the embeddings at some blob storage as well, incase my vector store goes down i might need to recreate all of those ?

WhiteFang_Jr · Answer

Hey!Yes there is: https://llamahub.ai/l/readers/llama-index-readers-s3?from=How are you loading back the index,index = VectorStoreIndex.from_vector_store(vector_store=vector_store)If you are creating storage_context then you will have to pass in your vector_store ref else it will create a default one on its own. You can, if the service goes down like ( Qdrant or chroma, which has never happened to me ) , then yeah if the service does not gets up correctly you'll have to re-do the embeddings process again.

purple crow · Answer

thanks @WhiteFang_Jr for answeringif u have more context on the storage context, can u tell me more on when to use it as why would i need to store documents separately, index store separately etc ?

WhiteFang_Jr · Answer

yeah sure, you can read more about storage context here: https://docs.llamaindex.ai/en/stable/module_guides/storing/

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Llama Index Setup for Knowledge Graph and LLM Agents