RRepoGEO

REPOGEO REPORT · LITE

Alibaba-NLP/VRAG

Default branch main · commit 3cc25fb4 · scanned 6/9/2026, 4:53:13 PM

GitHub: 944 stars · 93 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
3 / 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 Alibaba-NLP/VRAG, 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

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

OVERALL DIRECTION
  • highlicense#1
    Add a LICENSE file to clarify usage rights

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root with a clear open-source license (e.g., Apache-2.0, MIT).
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://huggingface.co/collections/Alibaba-NLP/vrag

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 Alibaba-NLP/VRAG
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 1×
  3. Haystack · recommended 1×
  4. OpenSearch · recommended 1×
  5. Weaviate · recommended 1×
  • CATEGORY QUERY
    Need a RAG framework that can integrate information from different modalities.
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Haystack
    4. OpenSearch
    5. Weaviate
    6. Milvus
    7. Zilliz

    AI recommended 7 alternatives but never named Alibaba-NLP/VRAG. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a toolkit to develop multi-turn multimodal RAG systems using agentic AI.
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. GPT Index
    3. AgentRunner
    4. OpenAIAgent

    AI recommended 4 alternatives but never named Alibaba-NLP/VRAG. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 Alibaba-NLP/VRAG?
    pass
    AI named Alibaba-NLP/VRAG explicitly

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

  • If a team adopts Alibaba-NLP/VRAG in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Alibaba-NLP/VRAG 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 Alibaba-NLP/VRAG solve, and who is the primary audience?
    pass
    AI named Alibaba-NLP/VRAG explicitly

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

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MARKDOWN (README)
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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite