this video is very helpful, thank you. I was upset because of the vector dbs. I will check if I will be able to use the cloud version and buy the paid plan if I am successful
OpenAi embeddings only output Cosine. Milvus has GPU support but only for L2 and IP (not for Cosine) from what I understand? Is there another provider that can output L2 or IP other than openAI? Or does that not make sense to use a GPU for text, is that more intended for images and audio?
@@MilvusVectorDatabase yes but with cosine that would be without GPU support right? As GPU support is only for L2 and IP (not for Cosine)? If that is correct I would need another embeddings system but all I find for text are cosine.
if you want true separation you'll probably need logical partitions, for functional separation i would suggest just adding the username as a metadata field and filtering on it
@@yujiantang Yeah i made something more crazy that i edited langchain and added my own userid field then released my own version😂, i tried adding metadata field but i couldn't do it manually so i did some wierd stuff till it worked.
Thanks for the great information! What does you mean by “to manage utility”?
this video is very helpful, thank you. I was upset because of the vector dbs. I will check if I will be able to use the cloud version and buy the paid plan if I am successful
glad you found it helpful!
OpenAi embeddings only output Cosine. Milvus has GPU support but only for L2 and IP (not for Cosine) from what I understand? Is there another provider that can output L2 or IP other than openAI? Or does that not make sense to use a GPU for text, is that more intended for images and audio?
Milvus 2.3 has cosine similarity metrics
This is a good read zilliz.com/learn/choosing-right-vector-index-for-your-project
@@MilvusVectorDatabase yes but with cosine that would be without GPU support right? As GPU support is only for L2 and IP (not for Cosine)? If that is correct I would need another embeddings system but all I find for text are cosine.
How would you replace ConversationChain with LCEL ? Seems impossible
im using it and its amazing , but im having trouble seperating the memory for each user , any ideas ?
if you want true separation you'll probably need logical partitions, for functional separation i would suggest just adding the username as a metadata field and filtering on it
@@yujiantang Yeah i made something more crazy that i edited langchain and added my own userid field then released my own version😂, i tried adding metadata field but i couldn't do it manually so i did some wierd stuff till it worked.
@@Cuzinz oh but you got it working? i'm curious to see what you did if you wanna share :)
It would be nice if the link to the github repo with the code was provided so I could work through it while watching.