profanity VS jina

I had a great experience contributing to this C project (there is also Python involved) https://github.com/profanity-im/profanity

One option, maybe a little clunky - check out profanity (https://profanity-im.github.io/), a terminal based xmpp client. It has a python api. You can write a crude plugin to connect to [email protected] (or whatever user you figure out). Then just listen for incoming messages on a loop. When something is received, run it through a few cases to match the message with the intended event (or discard or whatever). Then probably trigger some external shell script to do the data retrieval, returning to the plugin to send. Profanity runs on pretty much anything.

XMPP client: Profanity

I haven't used it, but if you like irssi you might also like profanity which claims to be inspired by it: https://profanity-im.github.io/

Our website is: https://profanity-im.github.io/

Or, there is profanity (https://profanity-im.github.io/) and there is a python library that makes things go quickly. I had a thought to have a plugin autoconnect the "bot" user to the server, start an omemo session with a user (or users), and listen on a local socket or something for messages to send over the omemo session. I had issues with the omemo enrollment/key exchange sticking though, which made it unreliable.

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.