FAISS Vector Library with LangChain and OpenAI (Semantic Search) 

Hey guys I hope you enjoyed the video! If you did please subscribe to the channel! Join our Data Science Discord Here: discord.com/invite/F7dxbvHUhg If you want to watch a full course on AI check out Datacamp: datacamp.pxf.io/XYD7Qg Want to solve Python data interview questions: stratascratch.com/?via=ryan I'm also open to freelance data projects. Hit me up at ryannolandata@gmail.com *Both Datacamp and Stratascratch are affiliate links.

Brother saw some of your other videos as well , you are doing a superb job here. It feels bad when I see quite a low response from the audience even though your videos are exceptionally knowledgable . keep working hard bro you will grow , best wishes

Ryan, really appreciate you adding how to save and load FAISS vector database at end of this vid. I ran several repeated tests against my saved VDB and it appeared to make NO DIFFERENCE in Open usage or Costs for today = Aug 3, 2024!😂

Thank You. A very important and timely topic. Thank You!. Next, best embeddings ?

hey, I want to see how embeddings look/is stored in vectorStore. I want to store the embeddings in a CSV format. I am using FAISS only. How to store it in CSV format?

Just a question: FAISS is now using only CPU not GPU. I have Windows. How can I get FAISS run with my GPU? If not what alternative vectorbases should I use? It makes a large difference in terms of performance doesnt it?

When I do date related query with FAISS why FAISS not returning perfect result? Do I need to update query for Vector search?

similarity_search gives 4 most similar texts? because I'm getting from 0th to 3rd index results when i query something.

really this is very helpful video

Absolutely brilliant and useful video. You are the REAL rockstar (no pun intended :))! If you are ever looking for content ideas .... here's one: Do a video on building a RAG pipeline on AWS Bedrock. The AWS platform is phenomenal but the documentation is often confusing. And they have a ton of really useful features (like Guardrails).

Great video. I'm dying laughing that you called "PRIME-us" "prim-us" and then said they you guys actually did the same wasabi hazing as Metallica... back at math camp.

Hi bro, Great Video. Hope to see next!

Small Doubt did you pay for OPENAI api key ? Because I have not paid it . If we pay only we would able to use the Embedding models ?

I don't understand the difference between query and retriever. Can someone help me understand this?

hey man this is _really_ good work!! keep on going!

Thanks, how can we apply it to tables such as csv or even sqlite tables?

Great video!

Hi Ryan, you have now idea how this video of yours was good for me. I really appreciate it. Do you know how I can replace the OpenAI stuff and Jan AI (Jan is an offline AI thing that you can download to your computer and remove the dependency from cloud providers/service/internet connection. Thanks again! Keep the good stuff coming! btw, who would say Metallica would help learning AI, huh? LOL

Great video! Good job. Love Metallica as well!!!

New Subscriber !

Hey bro, this is an amazing tutorial, it would be great if you share the code link