Starred repositories
A collection of recent papers on building autonomous agent. Two topics included: RL-based / LLM-based agents.
[CVPR'25] Official Implementations for Paper - MagicQuill: An Intelligent Interactive Image Editing System
Distributed SQL database in Rust, written as an educational project
📚 C/C++ 技术面试基础知识总结，包括语言、程序库、数据结构、算法、系统、网络、链接装载库等知识及面试经验、招聘、内推等信息。This repository is a summary of the basic knowledge of recruiting job seekers and beginners in the direction of C/C++ technology, in…
本书为《C++17 the complete guide》的个人中文翻译，仅供学习和交流使用，侵删
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
Framework for benchmarking vector search engines
Tantivy is a full-text search engine library inspired by Apache Lucene and written in Rust
ClickBench: a Benchmark For Analytical Databases
Benchmarks of approximate nearest neighbor libraries in Python
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text.
A minimal programming example for a chat server
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
Use ChatGPT to summarize the arXiv papers. 全流程加速科研，利用chatgpt进行论文全文总结+专业翻译+润色+审稿+审稿回复
Curated list of project-based tutorials
AI-native HTAP database with Git-for-Data and built-in vector search, serving as the data and memory backbone for intelligent agents and applications.
Apache Doris is an easy-to-use, high performance and unified analytics database.
Automated testing to find logic and performance bugs in database systems
Design patterns implemented in Java
中文文本分类，TextCNN，TextRNN，FastText，TextRCNN，BiLSTM_Attention，DPCNN，Transformer，基于pytorch，开箱即用。
CNN-RNN中文文本分类，基于TensorFlow
Convolutional Neural Network for Text Classification in Tensorflow
Library for fast text representation and classification.
all kinds of text classification models and more with deep learning