GraphCanon updated 2w · GitHub synced 2w · 56 views this month
Decision brief
RAGFlow is a Retrieval-Augmented Generation (RAG) engine that integrates AI agents for enhanced context management in LLM applications, built using Go language and released under the Apache-2.0 license.
Good fit when
- - You need an integrated RAG system with AI agent capabilities for better context management in your applications.
- - Your project requires advanced retrieval-augmented generation features that can be further enhanced by intelligent agents.
Avoid when
- - If you specifically require a non-Golang developed RAG engine, as RAGFlow is built entirely in Go.
- - Your setup does not support or need Docker (RAGFlow requires building a Docker image that is approximately 2 GB).
- Requirements:
- Requires Docker; Docker image size is approximately 2 GB; build process requires access to external LLM and embedding services.
Observed Jul 11, 2026 · Source: enrich:decision_facts
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Adoption
Package downloads where a registry match exists. GitHub stars (86,541) are secondary evidence.
- Docker Hub pulls (30d)
- 3,515,500·Docker Hub API·2w
Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of 2w
- Provenance
- Not a fork · Organization account
- As of 2w
- Security (OSV)
- 4 low (4 low)
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Backing
Company context for InfiniFlow. Display-only - separate from trust and ranking.
- Company
- InfiniFlow·GitHub org profile·1mo
- Commercial model
- Pure OSS·GitHub org profile (public repos)·1mo
Install
go get github.com/infiniflow/ragflowHow it fits your stack(91)
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Evidence and technical details
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Overview
RAGFlow integrates Retrieval-Augmented Generation with AI agents to enhance context management for LLM applications.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Aug 1, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Aug 1, 2026
- Languages
- go, python
Source: github.language+pyproject.toml · Aug 1, 2026
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README
🔧 Build a Docker Image
This image is approximately 2 GB in size and relies on external LLM and embedding services.
git clone https://github.com/infiniflow/ragflow.git
cd ragflow/
docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly .
Or if you are behind a proxy, you can pass proxy arguments:
docker build --platform linux/amd64 \
--build-arg http_proxy=http://YOUR_PROXY:PORT \
--build-arg https_proxy=http://YOUR_PROXY:PORT \
-f Dockerfile -t infiniflow/ragflow:nightly .
For agents
This page has a .md twin and JSON over the API.