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
agent-harness
agentic-ai
agentic-nagive
agentic-retrieval
agentic-search
ai
ai-agents
context-engine
context-engineering
context-management
harness-engineering
knowledge-compilation
rag
retrieval-augmented-generation
search-harness
Updated 2026-10-11 12:29:20 +00:00
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
agent-framework
agentic-ai
agentic-rag
agents
ai
ai-agents
context-engineering
framework
genai
generative-ai
information-retrieval
large-language-models
llm
mcp
multi-agent
orchestration
python
rag
retrieval-augmented-generation
semantic-search
Updated 2026-10-10 17:28:09 +00:00