oxide
txtai
oxide | txtai | |
---|---|---|
9 | 356 | |
276 | 6,990 | |
- | 2.6% | |
0.0 | 9.3 | |
over 1 year ago | 9 days ago | |
Rust | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
oxide
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SQLite Functions for Working with JSON
Sorry about that, it's just a shortcut for https://github.com/fcoury/oxide.
- Ask HN: What are your “scratch own itch” projects?
- Looking for paid advanced Rust tutoring
- OxideDB - Teach your PostgreSQL database how to speak MongoDB Wire Protocol.
- Show HN: OxideDB – Teach PostgreSQL Database How to Speak MongoDB Wire Protocol
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Ask HN: What Are You Working On? (August 2022)
Mostly on MongoDB to PostgreSQL translation server: http://oxidedb.com or https://demo.oxidedb.com.
I have been wanting to dive deep into a Rust project and the challenge of implementing the MongoDB protocol and then translating it into some sort of SQL counterpart was the first thing that really clicked and got me excited enough to get me working on it nonstop for 3 weeks now.
Some backstory:
I have created a product that relies on MongoDB for a document store but doesn’t really need any of the distributed features to really justify having a hosted MongoDB or DocumentDB instance. Now that we’re trying to turn this into a product, we’re seeing that some companies have a little bit of resistance around managing yet another database. Most of our clients already have and manage PostgreSQL in one form or another. I knew that PostgreSQL already offered first class JSON support, but I didn’t want to rewrite the application data layer from scratch if I could avoid it. That’s when I started researching if there was a “proxy” that would translate the MongoDB protocol - that I was completely ignorant about - into PostgreSQL. To my surprise there was nothing ready for production use but I found MangoDB that later on became FerretDB. I delved into the code and was in love with the idea. The team around is really nice, but I found that they had greater ambitions - they basically wanted to offer multiple backends, namely Tigris, on top of PostgreSQL.
On the other hand, I have been waiting to find an excuse to delve deeply into the rust ecosystem but never really found something I was passionate about until I had the idea of challenging myself to see if I could learn about the protocol that MongoDB uses by relying on their public documentation and the hints I found on FerretDB.
Another thing I added to my toolbelt while developing this was about creating parsers. In order to transform MongoDB JSON to SQL queries, I ported an existing library from the MongoDB team from PEG.js to pest.rs!
It’s in very early stages, and it’s work from someone that is not yet super comfortable with the stack so keep in mind this is the beginning of a journey for me that I embarked out of pure joy on getting a tiny bit better on rust and making things click internally.
- OxideDB – Teach PostgreSQL Database How to Speak MongoDB Wire Protocol
txtai
- Show HN: FileKitty – Combine and label text files for LLM prompt contexts
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What contributing to Open-source is, and what it isn't
I tend to agree with this sentiment. Many junior devs and/or those in college want to contribute. Then they feel entitled to merge a PR that they worked hard on often without guidance. I'm all for working with people but projects have standards and not all ideas make sense. In many cases, especially with commercial open source, the project is the base of a companies identity. So it's not just for drive-by ideas to pad a resume or finish a school project.
For those who do want to do this, I'd recommend writing an issue and/or reaching out to the developers to engage in a dialogue. This takes work but it will increase the likelihood of a PR being merged.
Disclaimer: I'm the primary developer of txtai (https://github.com/neuml/txtai), an open-source vector database + RAG framework
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Build knowledge graphs with LLM-driven entity extraction
txtai is an all-in-one embeddings database for semantic search, LLM orchestration and language model workflows.
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Bootstrap or VC?
Bootstrapping only works if you have the runway to do it and you don't feel the need to grow fast.
With NeuML (https://neuml.com), I've went the bootstrapping route. I've been able to build a fairly successful open source project (txtai 6K stars https://github.com/neuml/txtai) and a revenue positive company. It's a "live within your means" strategy.
VC funding can have a snowball effect where you need more and more. Then you're in the loop of needing funding rounds to survive. The hope is someday you're acquired or start turning a profit.
I would say both have their pros and cons. Not all ideas have the luxury of time.
- txtai: An embeddings database for semantic search, graph networks and RAG
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Ask HN: What happened to startups, why is everything so polished?
I agree that in many cases people are puffing their feathers to try to be something they're not (at least not yet). Some believe in the fake it until you make it mentality.
With NeuML (https://neuml.com), the website is a simple HTML page. On social media, I'm honest about what NeuML is, that I'm in my 40s with a family and not striving to be the next Steve Jobs. I've been able to build a fairly successful open source project (txtai 6K stars https://github.com/neuml/txtai) and a revenue positive company. For me, authenticity and being genuine is most important. I would say that being genuine has been way more of an asset than liability.
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Are we at peak vector database?
I'll add txtai (https://github.com/neuml/txtai) to the list.
There is still plenty of room for innovation in this space. Just need to focus on the right projects that are innovating and not the ones (re)working on problems solved in 2020/2021.
- Txtai: An all-in-one embeddings database for semantic search and LLM workflows
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Generate knowledge with Semantic Graphs and RAG
txtai is an all-in-one embeddings database for semantic search, LLM orchestration and language model workflows.
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Show HN: Open-source Rule-based PDF parser for RAG
Nice project! I've long used Tika for document parsing given it's maturity and wide number of formats supported. The XHTML output helps with chunking documents for RAG.
Here's a couple examples:
- https://neuml.hashnode.dev/build-rag-pipelines-with-txtai
- https://neuml.hashnode.dev/extract-text-from-documents
Disclaimer: I'm the primary author of txtai (https://github.com/neuml/txtai).
What are some alternatives?
rmkit - | remarkable app framework | https://rmkit.dev
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
skeleton - A fully featured UI toolkit for Svelte + Tailwind. [Moved to: https://github.com/skeletonlabs/skeleton]
tika-python - Tika-Python is a Python binding to the Apache Tika™ REST services allowing Tika to be called natively in the Python community.
PicoPico - Pico-8 Player
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
pyroscope-rs - Pyroscope Profiler for Rust. Profile your Rust applications.
faiss - A library for efficient similarity search and clustering of dense vectors.
reframe - LeapTable 🦘- The fastest way to build, deploy, and manage LLM-powered agents on tabular data (dataframes, SQL tables and Spreadsheets). [Moved to: https://github.com/peterwnjenga/leaptable]
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
needle - A CLI tool that finds a needle (opening/intro and ending/credits) in a haystack (TV or anime episode).
paperai - 📄 🤖 Semantic search and workflows for medical/scientific papers