GitHub - outlines-dev/outlines: Neuro Symbolic Text Generation

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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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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AI Template & SPR Library

Featuring advanced prompts and SPRs

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Prompt Engineering

Advanced GPTs

Template Library

e your own prompts and genera

Sugarcane AI is an open-source framework designed to simplify and accelerate LLM app development. With a focus on fine-tuned Language Models (LLMs), prompt management, and Workflow Plugins, Sugarcane AI empowers developers to build, train, and manage complex LLM applications effortlessly. 🎉

Why Sugarcane AI? : Key Features of Microservices Framewor... See more

The AI engineering framework

Marvin is a lightweight AI engineering framework for building natural language interfaces that are reliable, scalable, and easy to trust.

Sometimes the most challenging part of working with generative AI is remembering that it's not magic; it's software. It's new, it's nondeterministic, and it's incredibly powerful - but... See more

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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SGLang is a structured generation language designed for large language models (LLMs). It makes your interaction with LLMs faster and more controllable by co-designing the frontend language and the runtime system.

The core features of SGLang include:

• A Flexible Front-End Language : This allows for easy programming of LLM applications with multiple ch

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