Azure AIGEN Demos alternatives for AI agents.

21 Lessons, Get Started Building with Generative AI

One delightful Ruby framework for every major AI provider. Build AI agents, chatbots, RAG apps, and multimodal workflows in beautiful, expressive code.

A repository of code samples for Vector search capabilities in Azure AI Search.

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.

SeaTunnel is a multimodal, high-performance, distributed, massive data integration tool.

Retrieval and Retrieval-augmented LLMs

Find related notes and excerpts while writing. Your link building copilot displays relevant content in graph + list view. A local embedding model powers semantic search. Zero setup. No API key.

A blazing fast inference solution for text embeddings models

An Obsidian plugin to interact with your privacy focused AI-Assistant making your second brain even smarter!

text2vec, text to vector. 文本向量表征工具，把文本转化为向量矩阵，实现了Word2Vec、RankBM25、Sentence-BERT、CoSENT等文本表征、文本相似度计算模型，开箱即用。

A deep dive into embeddings starting from fundamentals

A curated list of Generative AI tools, works, models, and references

Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.

Fast State-of-the-Art Static Embeddings

This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models

Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB).