ragflow

★ 92.7k

crg

★ 76

ragflow vs crg

Q: Which is better, ragflow or crg?

By GitHub stars, ragflow has more community adoption, but the best choice depends on your specific use case.

ragflow: RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that integrates RAG with Agent capabilities. It provides a superior context layer for LLMs and offers a streamlined RAG workflow adaptable to enterprises of any scale.; crg: `crg` (formerly `better-code-review-graph`) is a local-first knowledge graph tool for codebases, enabling token-efficient code reviews through semantic search, call-graph resolution, and structural analysis. It integrates with AI agents via MCP for precise context provision, leveraging local ONNX embeddings or cloud models for enhanced code understanding and security scanning.

TL;DR

ragflowRAG / Knowledge Base · ★ 92.7k

When to choose:

Your documents have complex layouts (PDFs, scanned files, tables, slides) and you need layout analysis, OCR, and traceable citations.
You want an Apache-2.0 all-in-one RAG platform where you can inspect and hand-tune template-based chunks in a web UI.

When to skip:

Your server has less than 4 CPU cores and 16 GB RAM; RAGFlow's multi-service stack is heavy.
You want an autonomous web research agent that writes 2,000-word reports from live search rather than indexing a local document corpus; GPT Researcher fits better.

Read ragflow full review →

crgRAG / Knowledge Base · ★ 76

Performing token-efficient code reviews with precise context for AI agents

Read crg full review →

Side-by-Side Comparison

Field

ragflow

crg

Features

ragflow

01Deep document understanding for knowledge extraction from unstructured data.

02Intelligent and template-based chunking with explainable options.

03Grounded citations with reduced hallucinations and traceable references.

04Compatibility with heterogeneous data sources including documents, images, and web pages.

05Automated and effortless RAG workflow orchestration with configurable models and fused re-ranking.

crg

01AND-logic multi-word search for code entities

02Qualified call graph resolution and bare fallback

03Dual-mode fastretrieval ONNX and cloud embeddings (Jina/Gemini/OpenAI/Cohere)

04Paginated and truncated output for large search results

05Integrated security scanning with Semgrep and heuristic rules

Use Cases

ragflow

↳Building high-fidelity, production-ready AI systems with complex data.

↳Developing enterprise-scale knowledge base and intelligent Q&A chatbots.

↳Facilitating intelligent document processing and advanced information retrieval.

crg

↳Performing token-efficient code reviews with precise context for AI agents

↳Conducting semantic search and call-graph resolution across a codebase

↳Analyzing the blast radius and impact of changed files within a repository

↳Running local security scans on code using heuristic rules or Semgrep engine

↳Onboarding new repositories and quickly understanding code structure and relationships

Best For

ragflow

Most PopularEssentialTrending

crg

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FAQ

What is the difference between ragflow and crg?

Both ragflow and crg are in the RAG / Knowledge Base category. ragflow has 92.7k stars, while crg has 76 stars.

Which is better, ragflow or crg?

The best choice depends on your use case. Choose ragflow if Building high-fidelity, production-ready AI systems with complex data., and crg if Performing token-efficient code reviews with precise context for AI agents.

Is ragflow free or open source?

Yes, ragflow is open source on GitHub (Apache-2.0).

Is crg free or open source?

Yes, crg is open source on GitHub (Apache-2.0).

Cloud Infrastructure

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Alternatives to ragflow →Alternatives to crg →ragflow details →crg details →ragflow vs GPT Researcher →haystack vs ragflow →

TL;DR

Side-by-Side Comparison

Features

Use Cases

Best For

FAQ

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