RRepoGEO

REPOGEO REPORT · LITE

IlyaRice/RAG-Challenge-2

Default branch main · commit 452d688d · scanned 6/27/2026, 4:43:11 AM

GitHub: 2,387 stars · 488 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 IlyaRice/RAG-Challenge-2, 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 relevant topics to the repository

    Why:

    COPY-PASTE FIX
    rag, llm, retrieval-augmented-generation, enterprise-rag, document-qa, pdf-parsing, vector-search, llm-reranking, chain-of-thought, competition-solution, advanced-rag
  • highreadme#2
    Reposition the README's opening paragraph to emphasize its role as an example

    Why:

    CURRENT
    # RAG Challenge Winner Solution
    
    **Read more about this project:Russian: https://habr.com/ru/articles/893356/
    - English: https://abdullin.com/ilya/how-to-build-best-rag/
    
    This repository contains the winning solution for both prize nominations in the RAG Challenge competition. The system achieved state-of-the-art results in answering questions about company annual reports using a combination of:
    COPY-PASTE FIX
    # RAG Challenge Winner Solution: An Advanced RAG Implementation Example
    
    **Read more about this project:Russian: https://habr.com/ru/articles/893356/
    - English: https://abdullin.com/ilya/how-to-build-best-rag/
    
    This repository showcases the **winning solution** for the Enterprise RAG Challenge competition, providing a concrete example of state-of-the-art techniques for accurate document question answering on enterprise datasets. The system achieved state-of-the-art results in answering questions about company annual reports using a combination of:
  • mediumhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://abdullin.com/ilya/how-to-build-best-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 IlyaRice/RAG-Challenge-2
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LlamaIndex
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LlamaIndex · recommended 2×
  2. LangChain · recommended 2×
  3. Weaviate · recommended 2×
  4. Pinecone · recommended 2×
  5. Haystack · recommended 1×
  • CATEGORY QUERY
    How to implement advanced RAG techniques for accurate document question answering?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Haystack
    4. Weaviate
    5. Pinecone
    6. Cohere Rerank
    7. OpenSearch

    AI recommended 7 alternatives but never named IlyaRice/RAG-Challenge-2. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking examples of effective RAG implementations for querying large enterprise document sets.
    you: not recommended
    AI recommended (in order):
    1. Azure AI Search
    2. Azure OpenAI Service
    3. AWS Kendra
    4. Amazon Bedrock
    5. Elasticsearch
    6. LangChain
    7. LlamaIndex
    8. OpenAI API
    9. Anthropic API
    10. Pinecone
    11. Weaviate
    12. Google Cloud Vertex AI Search
    13. Vertex AI Foundation Models
    14. Milvus
    15. Zilliz

    AI recommended 15 alternatives but never named IlyaRice/RAG-Challenge-2. 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 IlyaRice/RAG-Challenge-2?
    pass
    AI did not name IlyaRice/RAG-Challenge-2 — 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 IlyaRice/RAG-Challenge-2 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named IlyaRice/RAG-Challenge-2 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 IlyaRice/RAG-Challenge-2 solve, and who is the primary audience?
    pass
    AI did not name IlyaRice/RAG-Challenge-2 — 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?

Embed your GEO score

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IlyaRice/RAG-Challenge-2 — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite
IlyaRice/RAG-Challenge-2 — RepoGEO report