RRepoGEO

REPOGEO REPORT · LITE

Steven-Luo/MasteringRAG

Default branch main · commit d59a990a · scanned 6/6/2026, 11:03:31 PM

GitHub: 698 stars · 99 forks

AI VISIBILITY SCORE
22 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface Steven-Luo/MasteringRAG, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    rag, llm, retrieval-augmented-generation, enterprise-rag, rag-optimization, document-retrieval, chunking, embedding, reranking, langchain, llamaindex, agent, ollama, hyde, flowise, best-practices
  • highreadme#2
    Reposition the README opening to clarify the repo's purpose

    Why:

    CURRENT
    # 说明

本项目是一个使用LLM（大语言模型）使用RAG技术构建文档问答的项目，将会涵盖企业构建基于RAG的文档问答几乎所有的常见优化手段。
项目重点介绍算法流程，不会将重点放在非常规范化的工程代码上，因此，每一个Notebook文件都可以独立运行，不会做公共逻辑的抽象。
    COPY-PASTE FIX
    # 说明

本项目是一个**专注于企业级RAG系统优化实践的综合指南和代码库**，涵盖了从基础到高级的几乎所有常见RAG优化手段。它**不是一个生产级框架或库**，而是通过一系列独立的Notebook文件，深入探讨RAG算法流程和技术细节，旨在帮助开发者和研究人员掌握构建高性能RAG系统的核心方法。
  • mediumhomepage#3
    Add a homepage URL

    Why:

    COPY-PASTE FIX
    Add a URL to a related blog post, course, or project page (e.g., 'https://your-blog.com/mastering-rag').

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface Steven-Luo/MasteringRAG
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI Embeddings
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI Embeddings · recommended 2×
  2. Cohere Embeddings · recommended 2×
  3. Pinecone · recommended 2×
  4. LlamaIndex · recommended 1×
  5. LangChain · recommended 1×
  • CATEGORY QUERY
    What are the best practices for building and optimizing an enterprise-grade RAG system?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Unstructured.io
    4. OpenAI Embeddings
    5. Hugging Face Transformers
    6. Cohere Embeddings
    7. Pinecone
    8. Weaviate
    9. Qdrant
    10. Elasticsearch
    11. Cohere Re-ranker
    12. OpenAI GPT Models
    13. Anthropic Claude Models
    14. Mistral AI Models
    15. Ragas
    16. Arize AI (Phoenix)
    17. Kubernetes
    18. LangServe
    19. AWS Lambda
    20. Google Cloud Functions
    21. Azure Functions

    AI recommended 21 alternatives but never named Steven-Luo/MasteringRAG. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I improve document retrieval and chunking for better RAG system performance?
    you: not recommended
    AI recommended (in order):
    1. Sentence Transformers (UKPLab/sentence-transformers)
    2. LangChain (langchain-ai/langchain)
    3. LlamaIndex (run-llama/llama_index)
    4. Cohere Embeddings
    5. OpenAI Embeddings
    6. FAISS (facebookresearch/faiss)
    7. Pinecone
    8. Weaviate (weaviate/weaviate)
    9. Qdrant (qdrant/qdrant)

    AI recommended 9 alternatives but never named Steven-Luo/MasteringRAG. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of Steven-Luo/MasteringRAG?
    pass
    AI did not name Steven-Luo/MasteringRAG — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts Steven-Luo/MasteringRAG in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Steven-Luo/MasteringRAG explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo Steven-Luo/MasteringRAG solve, and who is the primary audience?
    pass
    AI did not name Steven-Luo/MasteringRAG — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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Steven-Luo/MasteringRAG — RepoGEO report