Hi, this framework is amazing and I try to apply to my RAG app and the result is great. But I see there is some thing that needs to improve.
It is the extracted json metadata, because when User upload document in the backend admin, at this process, It will generate metadata of this document (include file level and chunk level), then insert to vectordb.
But back to chat app, this will be a different frontend chat app for end user and at this time, when user send the query, it won’t get metadata info that is extracted above, of course we can store this metadata json in db or somewhere else, but may be the schema of metadata will not consistently when uploading another documents.
Do you have any ideas about this?
Another things is that, they have just publish Contextual Retrieval, I think it would be the same idea with this framework, what do you think about this ?
https://github.com/run-llama/llama_index/blob/main/docs/docs/examples/cookbooks/contextual_retrieval.ipynb
Thanks for creating such an amazing framework
Hi, this framework is amazing and I try to apply to my RAG app and the result is great. But I see there is some thing that needs to improve.
It is the extracted json metadata, because when User upload document in the backend admin, at this process, It will generate metadata of this document (include file level and chunk level), then insert to vectordb.
But back to chat app, this will be a different frontend chat app for end user and at this time, when user send the query, it won’t get metadata info that is extracted above, of course we can store this metadata json in db or somewhere else, but may be the schema of metadata will not consistently when uploading another documents.
Do you have any ideas about this?
Another things is that, they have just publish Contextual Retrieval, I think it would be the same idea with this framework, what do you think about this ?
https://github.com/run-llama/llama_index/blob/main/docs/docs/examples/cookbooks/contextual_retrieval.ipynb
Thanks for creating such an amazing framework