ragflow vs llm-app
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| ragflow | llm-app | |
|---|---|---|
| Tagline | RAGFlow: A powerful Retrieval-Augmented Generation with enhanced Agent capabilities in Go | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. |
| Stars | 85k | 59k |
| Forks | 9.8k | 1.4k |
| Open issues | 2.3k | 10 |
| Language | Go | Jupyter Notebook |
| License | Apache-2.0 | MIT |
| Last pushed | Jul 7, 2026 | Jul 5, 2026 |
| Categories | AI Agents, LLM Frameworks | Data & Retrieval, LLM Frameworks |
ragflow
RAGFlow is an advanced open-source RAG engine that incorporates AI agents to provide a superior context layer for LLMs. Built primarily in Go, it offers features such as agentic retrieval and search.
Go
llm-app
Pathway Live Data Framework AI Pipelines provides LLM App Templates for deploying high-accuracy retrieval-augmented generation (RAG) and enterprise search applications. The templates sync with various data sources including file systems, Google Drive, Sharepoint, S3, Kafka, PostgreSQL, real-time APIs.
Jupyter Notebook