The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text

The universal tool suite for vector database management. Manage Pinecone, Chroma, Qdrant, Weaviate and more vector databases with ease.

Notebooks & Example Apps for Search & AI Applications with Elasticsearch

FastAPI Backend for a Conversational Agent using Cohere, (Azure) OpenAI, Langchain & Langgraph and Qdrant as VectorDB

Hello everyone this repo will contain my journey of machine learning and DeepLearning with some exciting projects

TinyVecDB is an ultra fast embedded vector database.

⚡️Lightning fast in-memory VectorDB written in rust🦀

⚡️ Transform AI/ML operations: Transparency, Control and Cost Optimization. ⚡️

Example application querying data in different ways

Elysium Knowledge Repository is an open source initiative to embed all of Humanity's multi-modal knowledge and wisdom.

Avalok AI is easy to use platform to build search on documents including S3 bucket. We add ability to add RAG to get answers to your questions.

With ME_GPT, you can store your cherished memories in a local vector database and leverage them to give Chat GPT the extraordinary ability to clone your unique personality and knowledge.

This Repository collects my material about my course (Mastering Vector Databases for AI applicstions) by Eng/ Mohammed Agoor

Two approaches to generating optimized embeddings in the Retrieval-Augmented Generation (RAG) Pattern

I just wanna build my own LLM with RAG

VectorCV is a React app w/ a Flask Back-end that allows you (recruiters) to enter your candidates' CV's and find out who are the best candidates for the job. This is all done through embeddings, vector databases and queries by GPT-3.5

The simple client of NautilusDB, a Clound-Native Vector Search Service

A Quick Note taking application, which runs locally within the browser.

RAG pipeline framework for Localized LLM users

This project uses Python, Hugging Face (sentence-transformers), Milvus + Docker (container running Vector DB) to create a vector database, populate it with details of many people (names, ages, salaries, addresses and their introductions) and enable searching and querying on the database contents using Cosine-Similarity distances on IVF Flat index.