Hi, I have an issue where my RAG code, which is not retrieving information the from the document and the document is embedded as well. What will be the cause of this issue. I have tried many things like changing chunk size, change the top_k retriever as well. The code I am running is as fellows;
Output response: The provided context does not mention anything about PSL 2024 spends, so I cannot answer this question from the provided context.
There is document named PSL 2024 Analysis but the model is using PSL 2023 Analysis which contain no information about 2024. Kindly help me regarding this issue that why the model is not using the 2024 document. Does it do with the embeddings?
This is the response I am getting. It is picking the required document but not retrieving the information in it. Can you help why it is showing embedding=none when I am apply the embedding model.
Hi Logan, I have parsed the documents with llama_parser but encountering an error when using this line of code "index = VectorStoreIndex.from_documents(pdfdocuments , service_context=service_context)". The Error message is Unknown document type: <class 'llama_index.core.schema.Document'>. Can you provide some help on this. Thanks.
I have imported from llama_index import ( VectorStoreIndex, ServiceContext, SimpleDirectoryReader, load_index_from_storage, set_global_service_context )