semantic-kernel
sqlite-vss
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semantic-kernel | sqlite-vss | |
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47 | 16 | |
18,111 | 1,426 | |
6.4% | - | |
9.9 | 8.0 | |
5 days ago | about 2 months ago | |
C# | C++ | |
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.
semantic-kernel
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#SemanticKernel – 📎Chat Service demo running Phi-2 LLM locally with #LMStudio
There is an amazing sample on how to create your own LLM Service class to be used in Semantic Kernel. You can view the Sample here: https://github.com/microsoft/semantic-kernel/blob/3451a4ebbc9db0d049f48804c12791c681a326cb/dotnet/samples/KernelSyntaxExamples/Example16_CustomLLM.cs
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Semantic Tests for SemanticKernel Plugins using skUnit
This week, I had the chance to explore the SemanticKernel code base, particularly the core plugins. SemanticKernel comes equipped with these built-in plugins:
- FLaNK Stack for 04 December 2023
- Semantic Kernel
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Getting Started with Semantic Kernel and C#
In this article we'll look at the high-level capabilities building AI orchestration systems in C# with Semantic Kernel, a rapidly maturing open-source AI orchestration framework.
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Agency: Pure Go LangChain Alternative
I'm using Semantic Kernel (https://github.com/microsoft/semantic-kernel) and it's really nice. Makes building more complex workflows really simple without sacrificing control.
A bunch of examples (https://github.com/microsoft/semantic-kernel/blob/main/dotne...) for how to handle just about anything you need to do with OAI with a lot less boilerplate.
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New: LangChain templates – fastest way to build a production-ready LLM app
I haven't tried it but there's Microsoft semantic-kernel.
https://github.com/microsoft/semantic-kernel
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Overview: AI Assembly Architectures
Semantic Kernel github.com/microsoft/semantic-kernel
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Automated Routing of Tasks to Optimal Models: A PR for Semantic-Kernel
The need for efficient model routing has been a point of discussion in the community. Addressing this, I've submitted a pull request to Semantic-Kernel that introduces an automated multi-model connector.
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?
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
chroma - the AI-native open-source embedding database
langchain - 🦜🔗 Build context-aware reasoning applications
pgvector-go - pgvector support for Go
guidance - A guidance language for controlling large language models.
milvus-lite - A lightweight version of Milvus wrapped with Python.
guidance - A guidance language for controlling large language models. [Moved to: https://github.com/guidance-ai/guidance]
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
autogen - A programming framework for agentic AI. Discord: https://aka.ms/autogen-dc. Roadmap: https://aka.ms/autogen-roadmap
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
multi-gpt - A Clojure interface into the GPT API with advanced tools like conversational memory, task management, and more