text-embeddings

Infinity is a high-throughput, low-latency serving engine for text-embeddings, reranking models, clip, clap and colpali

Declarative way to run AI models in React Native on device, powered by ExecuTorch.

Train Models Contrastively in Pytorch

A client side vector search library that can embed, store, search, and cache vectors. Works on the browser and node. It outperforms OpenAI's text-embedding-ada-002 and is way faster than Pinecone and other VectorDBs.

Open Source Text Embedding Models with OpenAI Compatible API

Go module for fetching embeddings from embeddings providers

.NET library for local embedding generation using ONNX and Microsoft.Extensions.AI

LightweightEmbeddings is a fast, free, and unlimited API service for multilingual embeddings and reranking, with support for both text and images and guaranteed uptime.

Flask API for generating text embeddings using OpenAI or sentence_transformers

Vectrain is a high-performance, modular, plug-and-play RAG pipeline that ingests data, generates vector embeddings, and stores them in vector databases for semantic search, recommendations, and analytics.

Docsifer is a powerful tool for converting various data formats into Markdown for applications such as indexing, text analysis, and more. It supports PDF, PowerPoint, Word, Excel, Images, Audio, HTML, and other text-based formats, and leverages LLMs to enhance performance.