sqlite-vss
mdx
sqlite-vss | mdx | |
---|---|---|
17 | 99 | |
1,487 | 16,838 | |
- | 0.9% | |
8.0 | 8.7 | |
about 2 months ago | 7 days ago | |
C++ | JavaScript | |
MIT License | MIT License |
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.
sqlite-vss
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I'm writing a new vector search SQLite Extension
I guess this is an answer to the GitHub issue I opened against SQLite-vss a couple of months ago?
https://github.com/asg017/sqlite-vss/issues/124
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Embeddings are a good starting point for the AI curious app developer
Perhaps sqlite-vss? It adds vector searches to sqlite.
https://github.com/asg017/sqlite-vss
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How to Enhance Content with Semantify
Utilizing sqlite-vss to store and query vector embeddings managed by a local SQLite database, Semantify conducts fast, precise vector searches within these embeddings to find and recommend relevant content, ensuring readers are presented with articles that truly match their interests.
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SQLite vs. Chroma: A Comparative Analysis for Managing Vector Embeddings
Whether you’re navigating through well-known options like SQLite, enriched with the sqlite-vss extension, or exploring other avenues like Chroma, an open-source vector database, selecting the right tool is paramount. This article compares these two choices, guiding you through the pros and cons of each, helping you choose the right tool for storing and querying vector embeddings for your project.
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Vector database is not a separate database category
Here is a SQLite extension that uses Faiss under the hood.
https://github.com/asg017/sqlite-vss
Not associated with the project, just love SQLite and find it very useful.
- SQLite-Vss: A SQLite Extension for Vector Search
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Introduction to Vector Search and Embeddings
Vector Databases: As your data grows, efficiently searching through millions of vectors can become a challenge. Specialized vector databases like FAISS, Annoy, or Elasticsearch's vector search capabilities can be explored to manage and search through large-scale vector data. Your sentence is grammatically correct. In addition, databases like SQLite and PostgreSQL have extensions, such as sqlite-vss and pgvector, that can be used to store and query vector embeddings, respectively.
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The Problem with LangChain
I had a go at one of those a few months ago: https://datasette.io/plugins/datasette-faiss
Alex Garcia built a better one here as a SQLite Rust extension: https://github.com/asg017/sqlite-vss
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Every request, every microsecond: scalable machine learning at Cloudflare
Since the problem domain is that of anomaly detection from constructed request feature embeddings, I wonder if an ANN-search methodology using an embedded database (such as https://github.com/asg017/sqlite-vss or similar) was explored.
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Disrupting the AI Scene with Open Source and Open Innovation
As I searched for "sqlite vector plugin" I didn't find any results, before a couple of weeks ago. Two weeks ago I found Alex' SQLite VSS plugin for SQLite. The library was an amazing piece of engineering from an "idea perspective". However, as I started playing around with it, I realised it was ipso facto like "Titanic". Beautiful and amazing, but destined to leak water and sink to the bottom of the ocean because of what we software engineers refers to as "memory leaks".
mdx
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How to Enhance Content with Semantify
Semantify was made for content creators, marketers, and anyone looking to enhance their long-form written content. Currently only supporting MDX-based content, It automates the enrichment of MDX blog posts by adding AI-generated Q&A sections that summarize the content, and recommendations for semantically similar posts. This not only makes the content more accessible and engaging but also helps in establishing deeper connections between different posts, ultimately keeping the reader engaged for longer periods.
- MDX – use JSX in your Markdown content
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No CMS? Writing Our Blog in React
https://mdxjs.com/
> We thought this would be a no-brainer and that there would be some CMS/SSG libraries out there that made this Markdown conversion process easy and facilitated integration with any number of frontend frameworks.
You thought correct:
- NextJS MDX integration: https://nextjs.org/docs/pages/building-your-application/conf...
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Introducing Content Collections
The example above uses react-markdown, but you can use any library you want to render the markdown content. You can also use a transform function to modify the markdown content during the build process. Here is an example that uses MDX to compile the markdown content.
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Creating a static Next.js 14 Markdown Blog - An Adventure
MDX is a js library that allows us to import a markdown file as a react component and use it anywhere.
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Building Stunning Docs: Diving Deep into Docusaurus Customization
/blog/ - This directory contains all the markdown files, of your site blogs, you can simply add a new blog by using markdown, or simply remove a blog file by deleting its file, you can combine the markdown with MDX, resulting a well-written blog post.
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Show HN: Create email templates with Markdown and JSX
Hey HN!
This is a little personal project I've been hacking on for the past ~week, somewhat inspired by this blog post [0] ("My Wonderful HTML Email Workflow").
Basically I just wanted an easy way to create email templates in MDX [1] (Markdown + JSX), using React Email [2] components.
It's still a bit of a work in progress (and a bit slow at the moment) but wanted to share in case anyone else finds it interesting!
[0] https://www.joshwcomeau.com/react/wonderful-emails-with-mjml...
[1] https://mdxjs.com/
[2] https://react.email/
- Nota is a language for writing documents, like academic papers and blog posts
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WYSIWYG for MDX?! Introducing Vrite's Hybrid Editor
That’s why formats like Markdown (MD) and MDX (MD with support for JSX) are so popular for use cases like documentation, knowledge bases, or technical blogs. They allow you to use any kind of custom formatting or elements and then process the content for publishing. On top of that, they’re great for implementing a docs-as-code approach, where your documentation lives right beside your code (i.e. in a Git repo).
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Build a blog app with new Next.js 13 app folder and Contentlayer
MDX
What are some alternatives?
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
next-mdx-remote - Load mdx content from anywhere through getStaticProps in next.js
chroma - the AI-native open-source embedding database
remark-gfm - remark plugin to support GFM (autolink literals, footnotes, strikethrough, tables, tasklists)
pgvector-go - pgvector support for Go
markdoc - A powerful, flexible, Markdown-based authoring framework.
milvus-lite - A lightweight version of Milvus wrapped with Python.
astro - The web framework for content-driven websites. ⭐️ Star to support our work!
typesense-instantsearch-semantic-search-demo - A demo that shows how to build a semantic search experience with Typesense's vector search feature and Instantsearch.js
emoji-shortcodes-for-markdown - 1000+ Emoji Finder app for Markdown, GitHub, Campfire, Slack, Discord and more...
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
eleventy 🕚⚡️ - A simpler site generator. Transforms a directory of templates (of varying types) into HTML.