Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.
- Stars
- 2,653
- Star gain
- +7
- Growth score
- 0.0026
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Explore AI open-source repositories ranked by positive star growth over 7d. Compare recent momentum instead of lifetime popularity.
Browse RAG repositories grouped by the active GitHub topic mappings and ranked by recent star growth.
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Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.
🔥🔥DatalinkX异构数据源之间的数据同步系统,支持海量数据的增量或全量同步,同时支持HTTP、Oracle、MySQL、ES等数据源之间的数据流转,支持中间transform算子如SQL算子、大模型算子,底层依赖Flink、Seatunnel引擎,提供流转任务管理、任务级联配置、任务日志采集等功能🔥🔥
Ingest files for retrieval augmented generation (RAG) with open-source Large Language Models (LLMs), all without 3rd parties or sensitive data leaving your network.
The memory your AI should have had from the start. Automatic capture, automatic recall, 100% local. One SQLite file, zero cloud. Works with Claude Code, Claude CLI, Cursor, Codex CLI, Gemini CLI.
AI时代的WordPress,东半球首个积木式AI应用搭建系统,人人都可免费搭建自己的AI应用系统,例如企业智能体系统、AI漫剧系统、AI论文学术系统、AI客服系统...
The open-source context layer for AI agents. PipesHub turns your company's knowledge (Slack, Drive, Jira, GitHub, Microsoft 365 and 40+ connectors) into a permission-aware workspace that agents can search, grep, navigate and cite. MCP, SDKs and built-in agents. Self-hosted.
Config-driven engine that turns JSON into production-grade AI agents. Multi-agent orchestration, 19+ LLM providers, MCP/A2A protocols, RAG, persistent memory, and enterprise compliance (EU AI Act, GDPR, HIPAA). Built on Quarkus.
A RAG pipeline implementation built on the 'Epstein Files 20K' dataset from Hugging Face (Teyler).
✅(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】
China Unicom's Yuanjing Wanwu Agent Platform is an enterprise-grade, multi-tenant AI agent development platform. It helps users build applications such as intelligent agents, workflows, and rag, and also supports model management. The platform features a developer-friendly license, and we welcome all developers to build upon the platform.
Adaptive Chunking: automatically select the best chunking method per document for RAG. Accepted at LREC 2026.
The retrieval layer for production AI systems. Lightning-fast (<10ms) search without vector databases. Built for browser, edge, on-device, and cloud.
Technical resources for AI developers to build applications, agents, and systems using Oracle AI Database and OCI services
[ACL2026] "MiniRAG: Making RAG Simpler with Small and Open-Sourced Language Models"
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
Data and code for FreshLLMs (https://arxiv.org/abs/2310.03214)
Learn vector search with Rust and DataFusion; the C++/BusTub track is deprecated.
⚡️next-generation personal AI assistant powered by LLM, RAG and agent loops, supporting computer-use, browser-use and coding agent, demo: https://demo.openagentai.org
Polyglot document intelligence with a Rust core: extract text, metadata, images, tables, and structured data from 106 formats across 140 file extensions, plus code intelligence for 371 languages. Fifteen bindings, with CLI, REST API, and MCP server.
ARGO is an open-source AI Agent platform that brings Local Manus to your desktop. With one-click model downloads, seamless closed LLM integration, and offline-first RAG knowledge bases, ARGO becomes a DeepResearch powerhouse for autonomous thinking, task planning, and 100% of your data stays locally. Support Win/Mac/Docker.
Momentum Score compares the latest star count with a baseline for the selected window: ln((current stars + 1) / (baseline stars + 1)). Rankings include repositories with positive star gain.
Seven-day and thirty-day history may use estimates reconstructed from GitHub star creation history; estimated values are labeled. The twenty-four-hour ranking uses measured snapshots only.