Get Started with Qdrant Vector Database: Build your First RAG (Part 1)

In this tutorial, I'll guide you through the exciting world of vector databases and show you how to harness the power of Qdrant for advanced and high-performant vector similarity search.

🔍 What is Qdrant?
Qdrant is more than just a vector database; it's your ticket to the future of Gen AI applications. With its powerful and convenient API, you can seamlessly store, search, and manage vectors with additional payload, making it perfect for various applications like neural network matching, semantic-based searches, and faceted searches.

🦀 Built for Speed and Reliability
Qdrant is crafted in Rust 🦀, ensuring exceptional speed and reliability even under high loads. It transforms your embeddings or neural network encoders into full-fledged applications for matching, searching, recommending, and much more!

🛠️ Setting up Qdrant
I'll walk you through setting up Qdrant using Docker, so you can hit the ground running with your Gen AI projects.

📚 BGE Embeddings from Huggingface
To supercharge your vector database, we're leveraging the "BGE Embeddings" model by BAAI on Huggingface, widely recognized as one of the best open-source embedding models. Get ready to unlock the full potential of your data.

🪄 Langchain Orchestration
Learn how to use Langchain as an orchestrator to streamline your workflow and make your AI projects more efficient and powerful than ever before.

If you find this tutorial helpful, don't forget to hit that thumbs-up button, leave a comment with your questions or feedback, and subscribe to the channel for more exciting Gen AI and tech tutorials.

#generativeai #ai #python

[khoapham]

Have you made part 2 yet? I am looking forward to it

[gamefleek]

Thanks for the video. Very well done and looking forward to part #2.

[shivamroy]

It's a great video again. Super informative. Also, I appreciate that you mostly show projects using Open Source resources and that the projects are quite near production-ready.

[dipanshuporwal]

It is a great session to start with Qdrant Vector DB. I am not able to find 2nd part of this. If not published yet, then can you please let me know when it will be available?

[sjimosui]

Wow such golden content for Free just amazing!!
Eagerly waiting for part 2😮

[duygyem]

It's really awesome. Thanks bro. God bless you!

[rakeshkumarrout]

if i am using qdrant cloud and i have stored the embeddings inside the cloud db of qdrant how can i use this with the llm for question answering?
without rewritting the embeddings ?

[FredyGonzales]

Tuve que venirlo a repasar, y le puse para trabajarlo con MultiLenguaje y funciona perfecto en español, muchas gracias maestro ObiWan.

[SunilSamson]

If you stop the docker and then restart it, will the data still be there in qdrant?
edit - it exists.

BTW - Beautiful walkthrough !!!

[anielrossi]

what are you using for completion in PowerShell?

[madhusudhanreddy]

What are the other embedding models available ?

[CesarVegaL]

You are doing an excellent job in sharing your knowledge. I hope we can contribute to the development of the programming language called Mojo. I have already begun studying it, but it would be beneficial to understand its application in AI, which is its intended purpose, as far as I know.

[MahaDS-oztx]

can u share the continuity playlist in sequence with part1 and part2

[sorvex]

My qdrant instance broke on semantic search when I reached 400k vectors (internal timeout of 60s on search). It is running on 1 shard with hsnw and quantization enabled. Do you have any suggestions what it could be? A smaller collection worksjust fine. A cloud engineer also did a security patch on the kubernetes cluster shortly before it broke, don't know if that is relevant.

If I set index_only to true (so it only search indexed vectors) it comes out empty, but with status 200, so it seems to me the indexing mechanism of qdrant broke?

[FatimaHABIB-jmji]

Thanks for the video, what is "code . " means ? I tried it but it is not recognized

[Cedric_]

Thank you, is there any way you can make Part 2

[AngelWhite]

OMG! Thats what i want.
just one little question: I have 8GB RAM AND Core i 5 8th gen (NO GPU). will the Vector embeddings model BAAI work on my system ?
thanks.

[neilvenmascarinas]

where is the part 2 sir, I can't see it in your videos? btw sir, I love your videos really helpful:)

[aiboltoleu]

Sound quality is bad. Try to use a different headset next time.