Popular GitHub Repositories for Practical Applications

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.

Learn how to design, develop, deploy and iterate on production-grade ML applications.

GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.

Low-code platform for building business applications. Connect to databases, cloud storages, GraphQL, API endpoints, Airtable, Google sheets, OpenAI, etc and build apps using drag and drop application builder. Built using JavaScript/TypeScript. ?

Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.

AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

?? Build multimodal AI applications with cloud-native stack

An open protocol enabling communication and interoperability between opaque agentic applications.

Turns Data and AI algorithms into production-ready web applications in no time.

Self-Hosting Guide. Learn all about locally hosting (on premises & private web servers) and managing software applications by yourself or your organization. Including Cloud, LLMs, WireGuard, Automation, Home Assistant, and Networking.

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

A toolkit for making real world machine learning and data analysis applications in C++

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

? Easy-to-use and powerful NLP and LLM library with ? Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including ?Text Classification, ? Neural Search, ? Question Answering, ?? Information Extraction, ? Document Intelligence, ? Sentiment Analysis etc.

Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.

Build high-quality LLM apps - from prototyping, testing to production deployment and monitoring.

A curated list of practical guide resources of LLMs (LLMs Tree, Examples, Papers)

BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more.

TensorZero creates a feedback loop for optimizing LLM applications — turning production data into smarter, faster, and cheaper models.