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20 search results found

Txtai ⭐ 6,143

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

Postgresml ⭐ 5,135

The GPU-powered AI application database. Get your app to market faster using the simplicity of SQL and the latest NLP, ML + LLM models.

Llmware ⭐ 1,859

Providing enterprise-grade LLM-based development framework, tools, and fine-tuned models.

All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.

Infinity ⭐ 936

The AI-native database built for LLM applications, providing incredibly fast vector and full-text search

Vectordb ⭐ 829

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

Neum AI is a best-in-class framework to manage the creation and synchronization of vector embeddings at large scale.

Fastembed ⭐ 531

Fast, Accurate, Lightweight Python library to make State of the Art Embedding

Vectordb Recipes ⭐ 267

High quality resources & applications for LLMs, multi-modal models and VectorDBs

Angle-optimized Text Embeddings | 🔥 SOTA on STS and MTEB Leaderboard

Awesome Llm Rag ⭐ 147

Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models

Chatgpt Your Files ⭐ 111

Production-ready MVP for securely chatting with your documents using pgvector

Amazon Bedrock Samples ⭐ 90

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

Fastembed Rs ⭐ 73

Rust implementation of @Qdrant/fastembed.

Vectorboard ⭐ 39

Open Source Embeddings Optimisation and Eval Framework for RAG/LLM Applications. Documentations at https://docs.vectorboard.ai/introduction

Ragswift ⭐ 30

🚀 Power of Scalable RAG - A scalable centralized embeddings platform for efficient embedding and retrieval to build RAG applications faster

RestAI is an AIaaS (AI as a Service) open-source platform. Built on top of Llamaindex, Langchain and Transformers. Precise embeddings usage and tuning. Free form agents. Automatic load and unload of local LLMs.

Gpt All Local ⭐ 15

A "chat with your data" example: using a large language models (LLM) to interact with our own (local) data. Everything is local: the embedding model, the LLM, the vector database. This is an example of retrieval-augmented generation (RAG): we find relevant sections from our documents and pass it to the LLM as part of the prompt (see pics).

Fastembed Js ⭐ 12

FastEmbed-JS is a Typescript/NodeJS implementation of @Qdrant/fastembed.

Aws Llm Sagemaker ⭐ 11

SageMaker Ployglot based RAG opensearch

Interactive Rag ⭐ 8

Using MongoDB Atlas + ActionWeaver, we can build a user proxy agent that efficiently retrieves and ingests relevant information. This agent presents the data to the user in an interactive and customizable manner, enhancing the overall user experience.

Openai Embeddings ⭐ 6

OpenAI chatGPT hybrid search and retrieval augmented generation

Fastembed Go ⭐ 5

FastEmbed-go is a Go implementation of @Qdrant/fastembed.

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