GitHub - nomic-ai/nomic: Interact, analyze and structure massive text, image, embedding, audio and video datasets

NeMo Curator

NeMo Curator is a Python library specifically designed for scalable and efficient dataset preparation. It greatly accelerates data curation by leveraging GPUs with Dask and RAPIDS, resulting in significant time savings. The library provides a customizable and modular interface, simplifying pipeline expansion and accelerating model conv... See more

Welcome to prompttools created by Hegel AI! This repo offers a set of open-source, self-hostable tools for experimenting with, testing, and evaluating LLMs, vector databases, and prompts. The core idea is to enable developers to evaluate using familiar interfaces like code, notebooks, and a local playground.

In just a few lines of codes, you can t

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Mem0: The Memory Layer for Personalized AI

Mem0 provides a smart, self-improving memory layer for Large Language Models, enabling personalized AI experiences across applications.

Note: The Mem0 repository now also includes the Embedchain project. We continue to maintain and support Embedchain ❤️. You can find the Embedchain codebase in the embedchai

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VectorDB-recipes

Dive into building GenAI applications! This repository contains examples, applications, starter code, & tutorials to help you kickstart your GenAI projects.

• These are built using LanceDB, a free, open-source, serverless vectorDB that requires no setup .


• It integrates into python data ecosystem so you can simply start using these

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Original creator : Jesse Zhang (GH: emptycrown, Twitter: @thejessezhang), who courteously donated the repo to LlamaIndex!

This is a simple library of all the data loaders / readers / tools / llama-packs that have been created by the community. The goal is to make it extremely easy to connect large language models to a large variety of knowledge sour... See more

Description

PyNest is designed to help structure your APIs in an intuitive, easy to understand, and enjoyable way.

With PyNest, you can build scalable and maintainable APIs with ease. The framework supports dependency injection, type annotations, decorators, and code generation, making it easy to write clean and testable code.

This framework is not a... See more

Overview

AIConfig saves prompts, models and model parameters as source control friendly configs. This allows you to iterate on prompts and model parameters separately from your application code .

1. Prompts as configs : a standardized JSON format to store generative AI model settings, prompt inputs/outputs, and flexible metadata.


2. Model-agnostic SDK :

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