chroma
sqlite-vss
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chroma | sqlite-vss | |
---|---|---|
32 | 16 | |
12,189 | 1,455 | |
8.5% | - | |
9.7 | 8.0 | |
8 days ago | about 2 months ago | |
Python | C++ | |
Apache License 2.0 | 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.
chroma
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Let’s build AI-tools with the help of AI and Typescript!
Package installer for Python (pip), we use this for installing the Python-based packages, such as Jupyter Lab, and we're going to use this for installing other Python-based tools like the Chroma DB vector database
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Mixtral 8x22B
Optional: You can use SillyTavern[1] for a more "rich" chat experience
The above lets me chat, at least superficially, with my friend. It's nice for simple interactions and banter; I've found it to be a positive and reflective experience.
0. https://www.trychroma.com/
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7 Vector Databases Every Developer Should Know!
Chroma DB is a newer entrant in the vector database arena, designed specifically for handling high-dimensional color vectors. It's particularly useful for applications in digital media, e-commerce, and content discovery, where color similarity plays a crucial role in search and recommendation algorithms.
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AI Grant Traction in OSS Startups
View on GitHub
- Qdrant, the Vector Search Database, raised $28M in a Series A round
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Vector Databases: A Technical Primer [pdf]
For Python I believe Chroma [1] can be used embedded.
For Go I recently started building chromem-go, inspired by the Chroma interface: https://github.com/philippgille/chromem-go
It's neither advanced nor for scale yet, but the RAG demo works.
[1] https://github.com/chroma-core/chroma
- Chroma – the open-source embedding database
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Show HN: Embeddings Solution for Personal Journal
The formatting is a bit off.
The web app is here: https://jumblejournal.org
The DB used is here: https://www.trychroma.com/
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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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How to use Chroma to store and query vector embeddings
Create a new project directory for our example project. Next, we need to clone the Chroma repository to get started. At the root of your project directory let's clone Chroma into it:
sqlite-vss
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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".
- SQLite extension for efficient vector search, based on Faiss
What are some alternatives?
SillyTavern - LLM Frontend for Power Users.
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
faiss - A library for efficient similarity search and clustering of dense vectors.
pgvector-go - pgvector support for Go
golang-ical - A ICS / ICal parser and serialiser for Golang.
milvus-lite - A lightweight version of Milvus wrapped with Python.
AutoGPT - AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
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
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
SillyTavern - LLM Frontend for Power Users. [Moved to: https://github.com/SillyTavern/SillyTavern]
multi-gpt - A Clojure interface into the GPT API with advanced tools like conversational memory, task management, and more