RRepoGEO

REPOGEO REPORT · LITE

sdan/vlite

Default branch master · commit 21c1d8aa · scanned 6/6/2026, 2:41:47 PM

GitHub: 764 stars · 39 forks

AI VISIBILITY SCORE
35 /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
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 sdan/vlite, 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
    vector-database, embedded-database, python, numpy, rag, langchain, vector-search, local-rag
  • highreadme#2
    Clarify the tech stack in the README's opening

    Why:

    CURRENT
    # vlite

a simple and blazing fast vector database
    COPY-PASTE FIX
    # vlite

a simple, blazing fast, and embedded vector database built entirely in Python with NumPy.
  • mediumreadme#3
    Strengthen README's opening to highlight 'embedded' and 'local RAG'

    Why:

    CURRENT
    there is no database you need to set up, no server to run, and no complex configuration. just install vlite and start using it. take the CTX file with you wherever you go. its like a browser cookie but with embeddings.
    COPY-PASTE FIX
    There's no database to set up, no server to run, and no complex configuration. Just install vlite and start using it as an embedded vector store, perfect for local RAG applications. Take the CTX file with you wherever you go; it's like a browser cookie but with embeddings.

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 sdan/vlite
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
chroma-core/chroma
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. chroma-core/chroma · recommended 1×
  2. lancedb/lancedb · recommended 1×
  3. facebookresearch/faiss · recommended 1×
  4. nmslib/hnswlib · recommended 1×
  5. qdrant/qdrant · recommended 1×
  • CATEGORY QUERY
    What's a fast, lightweight vector database solution for local RAG applications?
    you: not recommended
    AI recommended (in order):
    1. Chroma (chroma-core/chroma)
    2. LanceDB (lancedb/lancedb)
    3. FAISS (facebookresearch/faiss)
    4. Hnswlib (nmslib/hnswlib)
    5. Qdrant (qdrant/qdrant)

    AI recommended 5 alternatives but never named sdan/vlite. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an embedded vector store built with Python for easy integration.
    you: not recommended
    AI recommended (in order):
    1. Chroma
    2. LanceDB
    3. Faiss
    4. Annoy
    5. Hnswlib

    AI recommended 5 alternatives but never named sdan/vlite. 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 sdan/vlite?
    pass
    AI named sdan/vlite explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of sdan/vlite. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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HTML
<a href="https://repogeo.com/en/r/sdan/vlite"><img src="https://repogeo.com/badge/sdan/vlite.svg" alt="RepoGEO" /></a>
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  • Brand-free category queries5 vs 2 in Lite
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