RAGFlow open-source RAG engine with agent capabilities trending on GitHub
RAGFlow is an open-source Retrieval-Augmented Generation engine that combines RAG with agent capabilities, positioned as a context layer for LLMs. The project has accumulated over 83,000 GitHub stars with 111 new stars today, indicating sustained community interest. It is maintained by Infiniflow and represents a notable open-source tooling option in the RAG/agent ecosystem.
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Production Agentic RAG Course Repository Gains Traction on GitHub
A GitHub repository titled 'production-agentic-rag-course' by jamwithai has accumulated 6,158 stars with 45 added today, indicating community interest in production-grade agentic retrieval-augmented generation systems. The repository appears to be an educational resource focused on deploying agentic RAG pipelines in production environments. Its trending status reflects ongoing developer demand for practical guidance on agentic and RAG architectures.
Flowise: open-source visual builder for AI agents gains traction on GitHub
Flowise is an open-source TypeScript project for building AI agents and LLM workflows through a visual drag-and-drop interface. The repository has accumulated over 53,000 GitHub stars with 107 new stars on the day of observation. It represents a no-code/low-code approach to agent and chain construction in the LangChain ecosystem.
Langflow: Visual AI Agent and Workflow Builder Trending on GitHub
Langflow is an open-source Python framework for building and deploying AI-powered agents and workflows, currently accumulating 148,425 total GitHub stars with 155 new stars today. It provides a visual interface for composing LLM-based pipelines and agent workflows. The continued traction signals ongoing community interest in low-code/visual tooling for AI agent construction.
awesome-llm-apps: 100+ Runnable AI Agent & RAG Application Examples
A curated GitHub repository collecting over 100 deployable AI agent and RAG (Retrieval-Augmented Generation) applications built with LLMs. The collection is designed for practical use — clone, customize, and ship. With 110,915 total stars and 202 added today, it reflects strong community interest in applied LLM tooling.
HippoRAG: RAG framework combining knowledge graphs and Personalized PageRank for continuous knowledge integration
HippoRAG is an open-source RAG framework published at NeurIPS 2024 by the OSU NLP Group that draws on models of human long-term memory to enable LLMs to continuously integrate knowledge across external documents. It combines retrieval-augmented generation with knowledge graphs and Personalized PageRank to improve multi-hop and associative retrieval. The repository has accumulated 3,742 GitHub stars with ongoing community traction.
MLflow trending on GitHub as open-source AI engineering platform
MLflow, an open-source platform for managing AI/ML workflows, is trending on GitHub with 26,442 total stars and 22 new stars today. The project supports agents, LLMs, and traditional ML models, offering debugging, evaluation, monitoring, and optimization capabilities for production AI applications. It is a mature, widely-used tooling platform in the MLOps space.
FastGPT: open-source knowledge-base platform with RAG and visual workflow orchestration
FastGPT is an open-source TypeScript platform for building knowledge-based question-answering systems on top of LLMs, featuring data processing pipelines, RAG retrieval, and a visual AI workflow editor. The project has accumulated 28,533 GitHub stars with modest daily growth (+65), indicating steady community traction. It targets developers who want to deploy RAG-based QA systems without extensive configuration.
HistoRAG: A RAG framework embedding historiographical methodology for historical research
Researchers introduce HistoRAG, a Retrieval-Augmented Generation framework that adapts RAG architecture to the epistemological requirements of historical scholarship. Key interventions include separated retrieval and generation, temporal windowing to ensure balanced source representation across time periods, and LLM-as-judge evaluation for transparent relevance judgments. The framework is evaluated on SPIEGELragged, a corpus of 102,189 Der Spiegel articles from 1950–1979, revealing concrete deficiencies in standard RAG for historical work (e.g., era-specific vocabulary failures, weak correlation between vector similarity and LLM-assessed relevance). The paper also introduces the concept of 'Zwischentexte' as a framework for responsible integration of LLM-generated text into scholarly practice.