flexmeasures VS Typesense

Hi,

this is for everybody who is interested in clean tech, especially real-time automation within new energy systems.

We've been working on FlexMeasures for a while ― an energy management system (EMS) with a focus on using demand flexibility to its maximum potential.

We're running it in several pilots ourselves, but our aim is to speed up the energy transition across the world. Let's not re-invent the wheel (i.e. a software stack around time series and optimization) too many times. Wherever you are in the world, and whatever setting you might be looking at (energy-modern housing in the U.S., smart e-mobility in Africa, self-balancing microgrids in Indonesia, etc.), maybe some of you will like our approach.

We've decided that making it easy and clear for developers to build such energy solutions can bring the largest gains. The first step towards that goal was a permissive license (Apache 2.0). The latest step we took was a Docker image (we got a Docker-based tutorial here: https://flexmeasures.readthedocs.io/en/latest/tut/toy-exampl...).

You can see the code at https://github.com/FlexMeasures/flexmeasures

Since recently, FlexMeasures is a project within the Linux Energy Foundation (https://www.lfenergy.org/projects/flexmeasures/), which helps to establish a proper governance and quality standard.

Actually, upcoming Thursday is our next Technical Steering Committee meeting, and interested people are warmly invited:

Thursday, June 16 at 8:00 am US Pacific Time / 11:00 am US Eastern

I work on one building block of climate tech ― energy demand flexibility software. Useful in all kinds of settings, like industry or microgrids.

The collaborative aspect is that [our platform](https://github.com/FlexMeasures/flexmeasures) is open source, under a permissive license.

I'm trying to grow a startup on top of it, but the whole idea of doing impactful work is that it's being used to speed up the energy transition everywhere. Less re-inventing the wheel. If you are involved in any projects where energy demand flexibility should be unearthed, please consider using FlexMeasures ― with us or without us. Happy to chat.

Disregarding props-drilling technique in favor of a more reliable and elegant solution we looked for inspiration elsewhere. Another project of ours .find was using Typesense/Algolia components, which looked a bit like black-box/magic, but at the same time provided a clean approach to build complex and highly customizable solutions.

Have you ever tried to look up something, only to realise your search engine doesn't recognise your typos? Typesense to the rescue! It's a fast, typo-tolerant search engine built for an easier browsing experience. The latest version comes with new features such as built-in conversational search, image search, voice search, analytics, and more. Dive into the release notes for the full list of changes and enhancements.

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.