good-first-issue VS Typesense

First Contributions, EddieHub Issue Finder, goodfirstissue.dev, goodfirstissues.com, firsttimersonly.com.

https://goodfirstissue.dev might be a great place to check :)

Another source is mentor feedback, somebody who tells you he thinks you can do it, some projects seem more open to new contributors, search good first issue, if you will open an issue saying you are willing to commit to say 1-2h a week for a year i believe you will get help.

Good First Issue

Good First Issue website curates the issues with good first issue tag from various open-source projects and displays them with a nice and clean UI.

If that doesn't work, get on https://socialcoder.org/Home/Index or contribute to an open source project - https://goodfirstissue.dev/.

OSS contributions: https://goodfirstissue.dev/

You can also use websites like up-for-grabs, goodfirstissue, or CodeTriage to find projects with open issues. Find one that looks easy or interesting to you and comment on it, asking if you can take a shot at it.

There are actually plenty of non-ES products that are way easier to integrate and tune (and get better results with less effort).

- Typesense (https://github.com/typesense/typesense)

- Algolia

- Google Programmable Search Engine (https://programmablesearchengine.google.com/about/)

Typesense - Open Source Alternative to Algolia

If you like your penny take a look at Typesense https://typesense.org/ - nothing to complain here. Especially nothing complain about pricing.

I work on Typesense [1] (historically considered an open source alternative to Algolia).

We then launched vector search in Jan 2023, and just last week we launched the ability to generate embeddings from within Typesense.

You'd just need to send JSON data, and Typesense can generate embeddings for your data using OpenAI, PaLM API, or built-in models like S-BERT, E-5, etc (running on a GPU if you prefer) [2]

You can then do a hybrid (keyword + semantic) search by just sending the search keywords to Typesense, and Typesense will automatically generate embeddings for you internally and return a ranked list of keyword results weaved with semantic results (using Rank Fusion).

You can also combine filtering, faceting, typo tolerance, etc - the things Typesense already had.

[1] https://github.com/typesense/typesense

[2] https://typesense.org/docs/0.25.0/api/vector-search.html

For something small with a minimal footprint, I'd recommend Typesense. https://github.com/typesense/typesense

I haven’t used Publish, but I’d assume you could use something like https://typesense.org/ to index and search the vault.

A cheaper option would be to use https://typesense.org. You can use DynamoDb streams to automatically load records. It has worked well for me.

Try tigris | typesense for faster search

I’m also checking out Typesense as a possibility for replacing Elastic: https://typesense.org/