koala73/worldmonitor
World Monitor is a real-time global intelligence dashboard for AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface.
Awesome AI Agents › LLM-Powered Platforms
asinghcsu/AgenticRAG-Survey
Agentic-RAG is a comprehensive survey and resource repository focused on the advanced paradigm of Retrieval-Augmented Generation (RAG) systems enhanced with autonomous AI agents, termed Agentic RAG. This project explores the integration of intelligent agents into the RAG pipeline to overcome limitations of traditional RAG systems, such as handling dynamic, multi-step reasoning tasks, adaptability, and complex workflow orchestration. The repository complements a detailed survey paper and provides supplementary materials including visualizations, taxonomies, and practical insights to facilitate understanding and adoption of Agentic RAG by researchers and practitioners. The core of Agentic RAG lies in its foundational agentic patterns: reflection, planning, tool use, and multi-agent collaboration. These patterns empower the system to iteratively refine outputs, create structured workflows, interact with external tools and APIs, and collaborate across multiple agents to solve complex problems efficiently. The repository offers a detailed taxonomy of Agentic RAG architectures, including single-agent, multi-agent, hierarchical, corrective, adaptive, and graph-based systems, providing a structured understanding of the field. Additionally, the project presents a comparative analysis between traditional RAG, Agentic RAG, and Agentic Document Workflows (ADW), highlighting their respective strengths, weaknesses, and ideal application scenarios. Real-world applications span diverse industries such as healthcare, education, finance, and legal analysis, demonstrating the practical impact and versatility of Agentic RAG systems. The repository also addresses challenges and future directions, including scalability, ethical AI considerations, multimodal integration, and human-agent collaboration, making it a forward-looking resource. It includes implementation techniques, tools, blogs, tutorials, and practical use cases, making it a valuable hub for advancing the capabilities and adoption of Agentic RAG systems in AI research and development.
https://github.com/asinghcsu/AgenticRAG-Survey
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