ragflow
★ 92.7k
vs
distillery
★ 25
ragflow vs distillery
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.; distillery: Distillery is a team knowledge base accessed through Claude Code skills. It captures, classifies, connects, and surfaces team knowledge using natural language commands. It stores knowledge as vector embeddings in DuckDB, running locally or as a hosted service.
01
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.
distilleryRAG / Knowledge Base · ★ 25
Capture and retrieve team knowledge during development
02
Side-by-Side Comparison
Field
ragflowdistilleryCategory
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 92.7k
★ 25
License
Apache-2.0
NOASSERTION
Install Command
docker compose -f docker-compose.yml up -d
claude plugin marketplace add norrietaylor/distillery && claude plugin install distillery
Updated
1d ago
3d ago
Open Source
Yes
Yes
Tags
RAG, AI Agent, LLM
claude-code, duckdb, embeddings
03
Features
ragflow01Deep 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.
distillery01/distill - Capture session knowledge with dedup detection
02/recall - Semantic search with provenance
03/pour - Multi-entry synthesis with citations
04/bookmark - Store URLs with auto-generated summaries
05/digest - Team activity summary from internal entries
04
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.
distillery↳Capture and retrieve team knowledge during development
↳Record meeting minutes with append updates
↳Track technical decisions and architectural context
05
Best For
ragflowMost PopularEssentialTrending
distillery—
FAQ
FAQ
What is the difference between ragflow and distillery?
Both ragflow and distillery are in the RAG / Knowledge Base category. ragflow has 92.7k stars, while distillery has 25 stars.
Which is better, ragflow or distillery?
The best choice depends on your use case. Choose ragflow if Building high-fidelity, production-ready AI systems with complex data., and distillery if Capture and retrieve team knowledge during development.
Is ragflow free or open source?
Yes, ragflow is open source on GitHub (Apache-2.0).
Is distillery free or open source?
Yes, distillery is open source on GitHub (NOASSERTION).
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