The Programmable Neuro-Symbolic AGI that lets you program its behavior using Graph-based Prompt Programming: for people who want AI to behave as expected

⛓️ Langflow is a visual framework for building multi-agent and RAG applications. It's open-source, Python-powered, fully customizable, model and vector store agnostic.

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

Chat with AI large language models running natively in your browser. Enjoy private, server-free, seamless AI conversations.

Build and deploy a fully-featured, observable, user-facing RAG backend in minutes.

AI-First Process Automation with Large ([Language (LLMs) / Action (LAMs) / Multimodal (LMMs)] / Visual Language (VLMs)) Models

AI-LIT: Using AI Embeddings to find what is Lost in Translation

A NodeJS RAG framework to easily work with LLMs and embeddings

kani (カニ) is a highly hackable microframework for chat-based language models with tool use/function calling. (NLP-OSS @ EMNLP 2023)

[ACL 2024 Main] NewsBench: A Systematic Evaluation Framework for Assessing Editorial Capabilities of Large Language Models in Chinese Journalism

🪢 Open source LLM engineering platform: Observability, metrics, evals, prompt management, playground, datasets. Integrates with LlamaIndex, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23

Samples showing how to build Java applications powered by Generative AI and LLMs using Spring AI and Spring Boot.

A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)

Paper list about multimodal and large language models, only used to record papers I read in the daily arxiv for personal needs.

Index your memes by their content and text, making them easily retrievable for your meme warfare pleasures.

A platform that enables users to perform private benchmarking of machine learning models. The platform facilitates the evaluation of models based on different trust levels between the model owners and the dataset owners.

a unified framework for leveraging LLMs

JS/TS library to make to easy to build with LLMs. Full support for various LLMs and VectorDBs, Agents, Function Calling, Chain-of-Thought, RAG, Semantic Router and more. Based on the popular Stanford DSP paper. Create and compose efficient prompts using prompt signatures. 🌵 🦙 🔥 ❤️ 🖖🏼

Amplify your team's potential with customizable and secure AI assistants.

🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 11 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴