Відео

How to make retrieval time intelligent meaning retrive the latest without using metadata/payload. Latest can be from any year going back to previous years that is latest available.

Colpali (and other similar models) are really game changing. Manually handcraft pdfs with text images table etc is really a pain in the ass!

Want video on how embeddings work

very insightful, I learned a lot!

Where is the next tutorial?

Thanks for this video. Unfortunately, you lost me at 28:00, where the main.py script ran into a lot of connection errors. Also, where does qdrant come from? There is no service running at :6333 on my machine.

You’re the absolute best! 💐

Very interesting project !

Nice!

Great video! Could you please consider increase the audio gain when recording the video? Thanks!

I always enjoy talking to “rob”

I do have a question about it: What if I was to add another LLM layer after the cache returnable? To kind of change the answer, to do not feel that we are always getting the same answer. What are the downsides of doing that, and how could I do it properly?

Hello, Evgenia, great job!!! I'm from Brazil, so please forgive my English. I replicated your project and need to make some changes. I need to recommend products to customers, so I select a customer (or even several customers) from a drop-down list, then select some filters such as: region, average purchase, spending and others, then the automation analyzes the customer's purchase history and recommends the products. Any suggestions on how I can do this? I would be immensely grateful. Bye

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thanks for creating this video, very helpful to me, please continuous create another usecase using this n8n workflow thanks

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Thanks for the explanation broww

Evgenia, great video. If you have free time, shoot more videos using n8n and Qdrant. It is very interesting.

Jerde Path

Nice. Thanks

Great video! I'm curious: are there any tools or strategies that could help determine when to apply filters to embeddings based on user input? For example, identifying when to filter results by price. With Qdrant, you could leverage payloads for this purpose... This would allow semantic search on a filtered set.

ZCMNBV❤️‍🔥😊🏕🌄🚅😴🇧🇭

Even though the content is amazingly excellent the accent is poor and it makes the content pretty hard to understand

Hey Evgeniya! I followed the rabbit trail from the N8N community meetup video to this one, which was fantastic. Thanks for doing this. I am strategically all in on the whole low-code automation and RAG bandwagon, and have been doing copious research. I loved this presentation at the community meetup, as well as following along with this. I'd like to make the right decision for our organization when it comes to handling embeddings and data retrieval needs for our particular offerings. I have a few questions. I was hoping you could point me in the right direction. Would the comments here be the best place to do that, or is there an email address or chat platform you'd point me towards? I'd like to give you an idea of where we're at, what our goals are, what I know, and what I have access to in a general way, but as specifically as needs be, so you can tell me why or why not I should look at a solution such as yours. I have several books and things like that I'm reading, and a few different choices that I'm weighing. I want to make sure something fits within my personal skill set, as well as the outcomes that I'm looking to specifically produce. I am, however, willing to learn. It all comes down to the return on time investment, I guess. Thanks for replying to this. I look forward to hearing from you more. 😊

Awesome video <3 Could you share link of Google Colab? Thanks bro <3

how to use the existing ddrant database as reteriver

Poor edit

Can you share the Google Colab link?

Awesome Webinar. Keep going freens

Hi , what is the "Qdrant Url " and where can I get it ?

i was amazing with your speaking speed lol

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