RRepoGEO

REPOGEO REPORT · LITE

hyperonym/basaran

Default branch master · commit a73dc6e7 · scanned 6/21/2026, 9:46:45 PM

GitHub: 1,285 stars · 77 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)

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

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 hyperonym/basaran, 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
  • highhomepage#1
    Add a homepage URL to the repository's 'About' section

    Why:

    COPY-PASTE FIX
    https://github.com/hyperonym/basaran
  • highabout#2
    Refine the repository's 'About' description to explicitly mention self-hosting

    Why:

    CURRENT
    Basaran is an open-source alternative to the OpenAI text completion API. It provides a compatible streaming API for your Hugging Face Transformers-based text generation models.
    COPY-PASTE FIX
    Basaran is an open-source, self-hosted alternative to the OpenAI text completion API. It provides a compatible streaming API for your Hugging Face Transformers-based text generation models, enabling local LLM inference.
  • mediumreadme#3
    Enhance the README's opening paragraph to emphasize self-hosting and local LLMs

    Why:

    CURRENT
    Basaran is an open-source alternative to the OpenAI text completion API. It provides a compatible streaming API for your Hugging Face Transformers-based text generation models.
    COPY-PASTE FIX
    Basaran is an open-source, self-hosted alternative to the OpenAI text completion API, allowing you to run Hugging Face Transformers-based text generation models locally. It provides a compatible streaming API for seamless integration.

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 hyperonym/basaran
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Ollama
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Ollama · recommended 2×
  2. LocalAI · recommended 2×
  3. vLLM · recommended 2×
  4. LiteLLM · recommended 2×
  5. LM Studio · recommended 2×
  • CATEGORY QUERY
    How to self-host open source large language models with an OpenAI-compatible API?
    you: not recommended
    AI recommended (in order):
    1. Ollama
    2. LocalAI
    3. text-generation-webui (oobabooga/text-generation-webui)
    4. vLLM
    5. TGI
    6. LiteLLM
    7. LM Studio

    AI recommended 7 alternatives but never named hyperonym/basaran. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What service allows using local LLMs with existing OpenAI client libraries for text generation?
    you: not recommended
    AI recommended (in order):
    1. LiteLLM
    2. Ollama
    3. LocalAI
    4. vLLM
    5. LM Studio
    6. text-generation-inference

    AI recommended 6 alternatives but never named hyperonym/basaran. 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 hyperonym/basaran?
    pass
    AI named hyperonym/basaran explicitly

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

  • If a team adopts hyperonym/basaran in production, what risks or prerequisites should they evaluate first?
    pass
    AI named hyperonym/basaran 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 hyperonym/basaran solve, and who is the primary audience?
    pass
    AI named hyperonym/basaran 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 hyperonym/basaran. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
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HTML
<a href="https://repogeo.com/en/r/hyperonym/basaran"><img src="https://repogeo.com/badge/hyperonym/basaran.svg" alt="RepoGEO" /></a>
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hyperonym/basaran — 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