RRepoGEO

REPOGEO REPORT · LITE

hyperonym/basaran

Default branch master · commit a73dc6e7 · scanned 5/11/2026, 4:47:21 PM

GitHub: 1,286 stars · 77 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 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
  • hightopics#1
    Add specific LLM inference and API server topics

    Why:

    CURRENT
    generative, gpt, huggingface, language-model, llama, llm, model, natural-language-processing, nlp, openai-api, python, text-generation, transformers
    COPY-PASTE FIX
    generative, gpt, huggingface, language-model, llama, llm, model, natural-language-processing, nlp, openai-api, python, text-generation, transformers, llm-inference, inference-server, api-server
  • mediumreadme#2
    Strengthen README's opening sentence to emphasize 'LLM inference server'

    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 **LLM inference server** that provides an OpenAI-compatible streaming API for your Hugging Face Transformers-based text generation models.
  • mediumhomepage#3
    Add the repository URL as the project homepage

    Why:

    COPY-PASTE FIX
    https://github.com/hyperonym/basaran

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
vllm-project/vllm
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. vllm-project/vllm · recommended 2×
  2. huggingface/text-generation-inference · recommended 2×
  3. BerriAI/litellm · recommended 2×
  4. ollama/ollama · recommended 1×
  5. LM Studio · recommended 1×
  • CATEGORY QUERY
    How to self-host an open-source alternative to OpenAI's text completion API for LLMs?
    you: not recommended
    AI recommended (in order):
    1. Ollama (ollama/ollama)
    2. LM Studio
    3. vLLM (vllm-project/vllm)
    4. Text Generation Inference (TGI) (huggingface/text-generation-inference)
    5. LocalAI (go-skynet/LocalAI)
    6. LiteLLM (BerriAI/litellm)

    AI recommended 6 alternatives but never named hyperonym/basaran. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What's the best way to serve Hugging Face language models with an OpenAI-compatible API?
    you: not recommended
    AI recommended (in order):
    1. vLLM (vllm-project/vllm)
    2. TGI (Text Generation Inference) (huggingface/text-generation-inference)
    3. LiteLLM (BerriAI/litellm)
    4. FastAPI (tiangolo/fastapi)
    5. Hugging Face Transformers (huggingface/transformers)
    6. OpenLLM (bentoml/OpenLLM)

    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

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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