Microsoft's Open Source AI Agent Beginner's Tutorial. This project is a tutorial on AI intelligent agents (AI Agents) crafted by Microsoft specifically for beginners, divided into 10 courses, including detailed instructions, videos, and sample code.

Machine Learning Code Converter Across Frameworks. This project can convert machine learning models, tools, and libraries from one framework to another. Developers can easily complete code transformations using simple functions and supports mainstream frameworks such as TensorFlow, PyTorch, and JAX.

import ivy
import torch
import tensorflow as tf

def torch_fn(x):
    x = torch.abs(x)
    return torch.sum(x)

x1 = torch.tensor([1., 2.])
x1 = tf.convert_to_tensor([1., 2.])

# Transpilation happens eagerly
tf_fn = ivy.transpile(test_fn, source="torch", target="tensorflow")

# tf_fn is now tensorflow code and runs efficiently
ret = tf_fn(x1)

Open Source AI Meeting Assistant. This is an AI-driven real-time meeting recording and summary generation tool that can be used offline. It is completely free and open source, supporting self-hosting, semantic search, content export, and more, suitable for Windows and macOS platforms.

Starting from Zero to Train a Vision Multi-Modality Model. This project is a step-by-step guide on how to train a 26M parameter vision multi-modality model from scratch, including a complete training process and a full set of tools, costing only 1.3 yuan and taking only 1 hour.

AI Agent Visualization Development Platform. This is a Python-based visual development platform for AI agents that is powerful and easy to use. It supports building workflows, running test cases, memory management, file uploads, structured outputs, RAG (Retrieval-Augmented Generation), multimodality, and evaluation, while also being compatible with over 100 large model service providers.

Handcrafting Various AI Algorithms and Models with Excel. This project implements and demonstrates the core algorithms and concepts of artificial intelligence and deep learning using Excel, allowing beginners to operate and understand the principles of AI, including matrix multiplication, MLP, RNN, Transformer, ResNet, etc., in a unique and easy-to-understand form, reducing the threshold for learning AI.

Easy-to-Use Multi-platform LLM Chatbot. This project is an LLM chatbot and development framework built with Python, supporting integration with various messaging platforms and large language models. It offers a visual management panel and a flexible plugin extension mechanism, with features like rate limiting, whitelists, keyword filtering, image understanding, and speech-to-text.

Open-source Low-code RAG Platform. This is an RAG platform built based on LangChain and LlamaIndex, supporting one-click Docker deployment. It features an easy-to-use web interface that offers data upload, model management, internet connectivity, and prompt template functionalities, allowing users to effortlessly build, debug, and publish RAG applications without writing any code.

Open Source LLM Evaluation Framework. This framework is designed to evaluate Large Language Models (LLMs), capable of testing model performance across various tasks. It offers over 60 academic benchmarks, supports multiple model frameworks, local models, cloud services (like OpenAI), hardware acceleration, and the capability to customize tasks.

AI Tool for Removing Image Watermarks. This is an open-source image restoration tool based on TensorFlow that can remove watermarks from images with just one command.