LlamaIndex is a data framework for your LLM applications

Drag & drop UI to build your customized LLM flow

Build ChatGPT over your data, all with natural language

The easiest way to use Agentic RAG in any enterprise

Zep | The Memory Foundation For Your AI Stack

Data framework for your LLM applications. Focus on server side solution

Deploy your agentic worfklows to production

🚀 Introducing 🐪 CAMEL: a game-changing role-playing approach for LLMs and auto-agents like BabyAGI & AutoGPT! Watch two agents 🤝 collaborate and solve tasks together, unlocking endless possibilities in #ConversationalAI, 🎮 gaming, 📚 education, and more! 🔥

Easiest and laziest way for building multi-agent LLMs applications.

LLPhant - A comprehensive PHP Generative AI Framework using OpenAI GPT 4. Inspired by Langchain

Open source guides/codes for mastering deep learning to deploying deep learning in production in PyTorch, Python, Apptainer, and more.

Large Language Models (LLMs) tutorials & sample scripts, ft. langchain, openai, llamaindex, gpt, chromadb & pinecone

LangStream. Event-Driven Developer Platform for Building and Running LLM AI Apps. Powered by Kubernetes and Kafka.

RESTai is an AIaaS (AI as a Service) open-source platform. Built on top of LlamaIndex & Langchain. Supports any public LLM supported by LlamaIndex and any local LLM suported by Ollama/vLLM/etc. Precise embeddings usage and tuning. Image generation (Dall-E, SD, Flux).

Learn to build and deploy AI apps.

Tech Stack for Building, Evaluating, and Deploying your LLM Application

Starter App to Build Your Own App to Query Doc Collections with Large Language Models (LLMs) using LlamaIndex, Langchain, OpenAI and more (MIT Licensed)

This repo is to showcase how you can run a model locally and offline, free of OpenAI dependencies.

This project enhances the construction of RAG applications by addressing challenges, improving accessibility, scalability, and managing data and user access. It uses Django, Llamaindex, and Google Drive for effective database management.

Code from tutorials presented on the "Code AI with Rok" YouTube channel