☁️ Build multimodal AI applications with cloud-native stack

Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP

👑 Easy-to-use and powerful NLP and LLM library with 🤗 Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including 🗂Text Classification, 🔍 Neural Search, ❓ Question Answering, ℹ️ Information Extraction, 📄 Document Intelligence, 💌 Sentiment Analysis etc.

Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database​.

💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows

🌊 A Human-in-the-Loop workflow for creating HD images from text

Represent, send, store and search multimodal data

🎯 Task-oriented embedding tuning for BERT, CLIP, etc.

MTEB: Massive Text Embedding Benchmark

The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.

Epsilla is a high performance Vector Database Management System. Try out hosted Epsilla at https://cloud.epsilla.com/

SGPT: GPT Sentence Embeddings for Semantic Search

The prime repository for state-of-the-art Multilingual Question Answering research and development.

PostgreSQL vector database extension for building AI applications

A Python vector database you just need - no more, no less.

Jina examples and demos to help you get started

An easy to use Neural Search Engine. Index latent vectors along with JSON metadata and do efficient k-NN search.

Elasticsearch plugin for nearest neighbor search. Store vectors and run similarity search using exact and approximate algorithms.

Neural Search