FXGL VS pgvector

I downloaded javafx from here: https://github.com/AlmasB/FXGL as a zip, extracted it, then went to my project structure and added it to my libraries. For a couple seconds it seems to work, but then I get the error again, and the folder isn't showing up in my external libraries.

Java seems to have gained a second wind in recent years, and the innovation in this ecosystem is speeding up. Java 20 and LTS release 21 are expected to happen this year. RIFE2, an actively-developed pure-Java web framework, has recently caught my attention. Like Javalin, it appears to be built on top of the successful Jetty server. I also started exploring FXGL for building games with Java. Lastly, as concerns over COVID-19 variants wane I expect an increase in Java developers participating in community events. For example, Chicago finally had its first in-person JConf event and the Chicago Java User Group (CJUG) is easing back into in-person events.

Have you checked FXGL? It’s built on top of JavaFX.

You might get some good use out of FXGL, a Java / JavaFX / Kotlin Game Library. It would probably save you implementing some things from scratch. It might not cover everything that you need, but it probably be at least somewhat helpful.

If you don't mind depending on all of JavaFX you could also try: https://github.com/AlmasB/FXGL Haven't tried it myself but seems like an easy way to start making a game. The author is a university lecturer, so there are plenty of tutorials for games. As the other comment said, Compose Desktop would be a nice choice for a chess game, with the added benefit of easy porting to Android in case you're interested in learning it!

I can highly recommend FXGL https://github.com/AlmasB/FXGL to get started building simpler 2d games before looking into 3d engines which can be daunting unless that’s what you are in for. Nice and easy api’s with everything you need as well as lots of example games to learn from.

Sure. See FXGL

GitHub sources: https://github.com/AlmasB/FXGL

Either libGDX (https://libgdx.com) or FXGL (http://almasb.github.io/FXGL/) . libGDX is more complicated and more powerful, FGXL is better suited for simpler games and so easier for beginners, but recently it's development is quite active and more and more features are available.

# Install Postgres and pgvector !apt-get update && apt install postgresql postgresql-server-dev-14 !git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git !cd pgvector && make && make install # Start database !service postgresql start !sudo -u postgres psql -U postgres -c "ALTER USER postgres PASSWORD 'pass';"

When talking about Vector Databases, in the market we can find the specialized ones and multi-model, most of the major database providers like Oracle, PostgreSQL or MongoDB, for mention some of them, have integrated a specific solution to retrieve vector data.

For this example, I wanted to focus on how pgvector  – an open-source vector similarity search for Postgres – can be used to identify data similarities that exist in enterprise data.

pgvector supports dense vector search well, but it does not have plan to support sparse vector.

There's an issue in the pgvector repo about someone having several ~10-20million row tables and getting acceptable performance with the right hardware and some performance tuning: https://github.com/pgvector/pgvector/issues/455

I'm in the early stages of evaluating pgvector myself. but having used pinecone I currently am liking pgvector better because of it being open source. The indexing algorithm is clear, one can understand and modify the parameters. Furthermore the database is postgresql, not a proprietary document store. When the other data in the problem is stored relationally, it is very convenient to have the vectors stored like this as well. And postgresql has good observability and metrics. I think when it comes to flexibility for specialized applications, pgvector seems like the clear winner. But I can definitely see pinecone's appeal if vector search is not a core component of the problem/business, as it is very easy to use and scales very easily

The Spring AI project aims to streamline the development of applications that incorporate artificial intelligence functionality without unnecessary complexity. On this example we use features like: Embedding, Prompts, ETL and save all embedding on PGvector(Postgres Vector database)

Official GitHub repository of the pgvector extension

pgvector 0.6.0 was just released and will be available on Supabase projects soon. Again, a special shout out to Andrew Kane and everyone else who worked on parallel index builds.

The pgvector extension adds vector similarity search capabilities to your PostgreSQL database. To use the extension, you have to first create it in your database. You can install the extension, by connecting to your database and running the CREATE EXTENSION command from the psql command prompt: