docarray VS jina

I’ve heard of DocArray, a library for multimodal data in transit and Pytorch Lightning which is also a tool for multimodal data. These two sound like a promising solution, but I’m not sure how to use it with databases or cloud storage. Do I need to install any additional packages or dependencies?

I'm considering using these tools for a recommender system for analyzing text data like user reviews: DocArray and the EZ-MMLA Toolkit. Can anyone share their experience with the DocArray and EZ-MMLA Toolkit? I would love to hear about others' experiences before making a final decision.

I have been thinking about trying out DocArray and the EZ-MMLA Toolkit .. Has anyone had experience with these two projects?? Let me know what you think!

For some alternatives, I know there’s DocArray where you can handle text, image and audio data. is basically a toolbox for multimodal data and then there should be Haystack which is also let you build search systems and also has to do something with Transformers and LLMs.

DocArray to manipulate data and interact with the storage backend using document store.

It's already been two weeks since the last alpha release of DocArray v2. And since then a lot has happened — we've merged features we're really proud of, and we've cried tears of joy and misery trying to coerce Python into doing what we want. If you want to learn about interesting Python edge cases or follow the advancement of DocArray v2 development then you’ve come to the right place in this blog post!

The German Fashion12k dataset is available for free use by the Jina AI community. After logging into Jina AI Cloud, you can download it directly in DocArray format:

Jina AI’s DocArray library

You could try spaCy. This is the brains of the operation - an open-source NLP library for advanced NLP in Python. Another is DocArray - It's built on top of NumPy and Dask, and good for preprocessing, modeling, and analysis of text data.

Jina mainly because of their use of neural networks and AI.

Jina - It’s an open-source project where you can build search engines. Well maybe not no code but it claims that you only need a few lines of code for creating projects. The project supports semantic, text, image, audio, and video search. What I’m also interested in is with their neural search and generative AI. I’m also interested in the amount of github repo that they have. I have this on my radar since this is also something I was interested in.

Do you guys have any ideas how we can match images on our database? We’re working on a project that about matching images on our database. We were trying to use SIFT and some other similar methods, but for some reason, nothing doesn’t seem to be working that well. Does anyone have any suggestions for the most effective way to do this? Maybe some open-source solutions like HuggingFace or Jina AI? We just want to make sure our image matching is correct and that part’s been a bit of a struggle on our part.

The tech lets you find 3D models without sifting through tons of text - An information retrieval framework does the heavy lifting and compares models to each other, no descriptions or keywords needed.

Jina AI -They offer a neural search solution that can help build smarter, more efficient search engines. They also have a list of cool github repos that you can check out. Similar to Vertex AI, they have image classification tools, NLPs, fine tuners etc.

Well, it's not exactly a new feature, but we've been working on early support for DocArray v2 in Jina.

Jina let’s you serve all of your models through the same Gateway while deploying them as individual microservices. You can also tie your models together in a pipeline if needed. Also some nice ML focussed features such as dynamic batching.