infiniflow/ragflow
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
Star History
Momentum
+2.3K
STARS · LAST 30 DAYS
76
PER DAY
#7
MOST-STARRED Go
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +532 | +2.3K | +6.8K |
| Per day | 76 | 76 | 76 |
| Forks gained | +54 | +217 | +542 |
ragflow gained 2.3K stars in the last 30 days, about 76 a day, and now has 91.4K. It is about 3 years old and has averaged roughly 30.5K stars a year. It ranks #7 among Go repositories and #94 across all languages on GitHubRepo.
Trending Record
6
DAYS ON TRENDING
#87
BEST RANK
Sep 23, 2026
FIRST APPEARANCE
Active
STATUS TODAY
ragflow has maintained a continuous presence across global trending indexes, peaking at #87. Below is the 30-day activity profile:
💡 Overview
ragflow is an open-source project written in Go: 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.
Engineered for speed, consistency, and developer ease, it solves common hurdles in agent-harness, agentic-ai, agentic-nagive. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Go for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ go install github.com/infiniflow/ragflow@latest⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Go >= 1.21 runtime environment
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
ragflow coordinates its core functionality through a modular Go pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with ragflow.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install ragflow using your package manager: `go install github.com/infiniflow/ragflow@latest`
Initialize your project workspace or configuration file for ragflow.
Import ragflow into your codebase or invoke it directly from your terminal.
Execute your test suite or run `ragflow --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Go, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
infiniflow/ragflow is currently ranked #94 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #89 | thedotmack/claude-mem | TypeScript | ★ 94.7K | Compare ↗ |
| #90 | 3b1b/manim | Python | ★ 94.3K | Compare ↗ |
| #91 | sherlock-project/sherlock | Python | ★ 92.8K | Compare ↗ |
| #92 | vllm-project/vllm | Python | ★ 92.8K | Compare ↗ |
| #93 | louislam/uptime-kuma | JavaScript | ★ 91.9K | Compare ↗ |
| #94 | infiniflow/ragflow This Project | Go | ★ 91.4K | |
| #95 | django/django | Python | ★ 91.2K | Compare ↗ |
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Frequently Asked Questions
What does ragflow do? +
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
What language is ragflow written in? +
The primary language is Go. Topics include: agent-harness, agentic-ai, agentic-nagive, agentic-retrieval, agentic-search.
Is ragflow actively maintained? +
Yes, the last recorded push was on Sep 28, 2026 with 1,533 open issues being tracked.
How many stars does ragflow have? +
ragflow has 91,402 stars and 10,839 forks on GitHub.
How does ragflow rank among GitHub repositories? +
With 91,402 stars, infiniflow/ragflow is ranked #94 globally across all repositories tracked on GitHubRepo and #7 among Go projects.
What license is ragflow distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
