Jupyter Notebook agents

21 Lessons, Get Started Building with Generative AI

Examples and guides for using the OpenAI API

18 Lessons to Get Started Building AI Agents

Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.

🔊 Text-Prompted Generative Audio Model

Google Research

In-depth tutorials on LLMs, RAGs and real-world AI agent applications.

📚 从零开始构建大模型

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.

A simple screen parsing tool towards pure vision based GUI agent

50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.

✅（已完结）超级全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】【大飞 大模型Agent】

Anthropic's educational courses

A guidance language for controlling large language models.

End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.

Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services

Get started with building Fullstack Agents using Gemini 2.5 and LangGraph

Sample code and notebooks for Generative AI on Google Cloud, with Gemini Enterprise Agent Platform

A multi-voice TTS system trained with an emphasis on quality

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑‍🔬

本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.

FinRobot: An Open-Source AI Agent Platform for Financial Applications using LLMs 🚀 🚀 🚀

Sweep: AI coding assistant for JetBrains

Overview and tutorial of the LangChain Library

每个人都能看懂的大模型知识分享，LLMs春/秋招大模型面试前必看，让你和面试官侃侃而谈

A collection of examples that show how to use CrewAI framework to automate workflows.

Repo for the Complete Agentic AI Engineering Course

【🔞🔞🔞 内含不适合未成年人阅读的图片】基于我擅长的编程、绘画、写作展开的 AI 探索和总结：StableDiffusion 是一种强大的图像生成模型，能够通过对一张图片进行演化来生成新的图片。ChatGPT 是一个基于 Transformer 的语言生成模型，它能够自动为输入的主题生成合适的文章。而 Github Copilot 是一个智能编程助手，能够加速日常编程活动。

Neo4j graph construction from unstructured data using LLMs

《大模型白盒子构建指南》：一个全手搓的Tiny-Universe

Materials for the Hugging Face Diffusion Models Course

Technical resources for AI developers to build applications, agents, and systems using Oracle AI Database and OCI services

Learn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native Cloud Technologies: OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, Rancher Desktop, and Kubernetes.

GenAI Cookbook

Sutskever 30 implementations inspired by https://papercode.vercel.app/ | For Agents, use https://github.com/pageman/Sutskever-Agent | Polyglot / Multi-Backed version at https://github.com/pageman/sutskever-30-beyond-numpy

Everything you need to know to build your own RAG application

Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.

35 production-grade agentic AI architectures (Reflexion, LATS, GraphRAG, MemGPT, Voyager, BrowserAgent, ...) — a Python library and runnable textbook with multi-provider LLM support and a 17-task benchmark leaderboard.

[ICLR 2023] ReAct: Synergizing Reasoning and Acting in Language Models

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.

🦖 𝗟𝗲𝗮𝗿𝗻 about 𝗟𝗟𝗠𝘀, 𝗟𝗟𝗠𝗢𝗽𝘀, and 𝘃𝗲𝗰𝘁𝗼𝗿 𝗗𝗕𝘀 for free by designing, training, and deploying a real-time financial advisor LLM system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 𝘷𝘪𝘥𝘦𝘰 & 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴

Automatic Generation of Visualizations and Infographics using Large Language Models

Jupyter Notebooks to help you get hands-on with Pinecone vector databases

A Production-ready Reinforcement Learning AI Agent Library brought by the Applied Reinforcement Learning team at Meta.

Learn to build your Second Brain AI assistant with LLMs, agents, RAG, fine-tuning, LLMOps and AI systems techniques.

Multi-agent systems, memory, planning, reasoning loops

机器学习、深度学习的学习路径及知识总结

Multi-agent systems, memory, planning, reasoning loops

The Open Source Memory Layer For Autonomous Agents

Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.

This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.

Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.

动手学Ollama，CPU玩转大模型部署，在线阅读地址：https://datawhalechina.github.io/handy-ollama/

Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.

Paper2Agent is a multi-agent AI system that automatically transforms research papers into interactive AI agents with minimal human input.

A set of Deep Reinforcement Learning Agents implemented in Tensorflow.

Official repository of 'Visual-RFT: Visual Reinforcement Fine-Tuning' & 'Visual-ARFT: Visual Agentic Reinforcement Fine-Tuning'’

This repository is deprecated and will be archived

Awesome resources for in-context learning and prompt engineering: Mastery of the LLMs such as ChatGPT, GPT-3, and FlanT5, with up-to-date and cutting-edge updates.

Build an email assistant with human-in-the-loop and memory

LangChain 공식 Document, Cookbook, 그 밖의 실용 예제를 바탕으로 작성한 한국어 튜토리얼입니다. 본 튜토리얼을 통해 LangChain을 더 쉽고 효과적으로 사용하는 방법을 배울 수 있습니다.

Run any Llama 2 locally with gradio UI on GPU or CPU from anywhere (Linux/Windows/Mac). Use `llama2-wrapper` as your local llama2 backend for Generative Agents/Apps.

Implementation of all RL algorithms in a simpler way

A comprehensive guide to building RAG-based LLM applications for production.

Practical course about Large Language Models.

MAI-UI: Real-World Centric Foundation GUI Agents ranging from 2B to 235B

Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0

WFGY is heading toward WFGY 5.0 Polaris Protocol, a major open-source release for AI reasoning, RAG, agents, and real-world workflows. Includes Problem Map, Global Debug Card, WFGY 4.0, and the CFV Easter Egg.

An experimentation and research platform to investigate the interaction of automated agents in an abstract simulated network environments.

Vision utilities for web interaction agents 👀

Implementing the 4 agentic patterns from scratch

Generate images from texts. In Russian

This course is designed to guide beginners through the exciting world of Edge AI, covering fundamental concepts, popular models, inference techniques, device-specific applications, model optimization, and the development of intelligent Edge AI agents.

This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks.

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

Build production-ready LLM applications and advanced agents using Python, LangChain, and LangGraph. This is the companion repository for the book on generative AI with LangChain.

A group of notebooks and other files which can help you learn AI from scratch.

LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. Jupyter notebooks on loading and indexing data, creating prompt templates, CSV agents, and using retrieval QA chains to query the custom data. Projects for using a private LLM (Llama 2) for chat with PDF files, tweets sentiment analysis.

Open-source tool to visualise your RAG 🔮

I leverage OpenAI and ChatGPT to do hackerish things

Stock Trading Bot using Deep Q-Learning

本项目围绕吴恩达老师在DeepLearning.AI出品的Agentic-ai系列课程，为学习者打造中文翻译与知识整理教程。项目提供课程内容翻译、知识点梳理和示例代码解读等内容，欢迎大家Star!

Building Apps with LLMs

Codes for "Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models".

Notebooks & Example Apps for Search & AI Applications with Elasticsearch

LangChain, LangGraph Open Tutorial for everyone!

[NeurIPS'23 Spotlight] "Mind2Web: Towards a Generalist Agent for the Web" -- the first LLM-based web agent and benchmark for generalist web agents

A central, open resource for data and tools related to chain-of-thought reasoning in large language models. Developed @ Samwald research group: https://samwald.info/

Resource, examples & tutorials for multimodal AI, RAG and agents using vector search and LLMs

Labs to explore AI Models, MCP servers, and Agents with the AI Gateway powered by Azure API Management and Microsoft Foundry 🚀

Transformer models from BERT to GPT-4, environments from Hugging Face to OpenAI. Fine-tuning, training, and prompt engineering examples. A bonus section with ChatGPT, GPT-3.5-turbo, GPT-4, and DALL-E including jump starting GPT-4, speech-to-text, text-to-speech, text to image generation with DALL-E, Google Cloud AI,HuggingGPT, and more