RRepoGEO

REPOGEO REPORT · LITE

FunAudioLLM/FunMusic

Default branch main · commit 0aefb55b · scanned 6/25/2026, 10:47:29 AM

GitHub: 1,363 stars · 139 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
28 /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
2 / 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 FunAudioLLM/FunMusic, 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
  • highreadme#1
    Clarify repo identity and value proposition in README's opening

    Why:

    CURRENT
    The README starts with many links and then introduces 'InspireMusic' as the focus, potentially obscuring the main project's identity and purpose.
    COPY-PASTE FIX
    Add a clear, concise opening sentence to the README, such as: 'FunAudioLLM/FunMusic is a comprehensive PyTorch-based toolkit for high-quality, long-form music, song, and audio generation, featuring the InspireMusic model and its capabilities.'
  • mediumtopics#2
    Expand topics to include generative AI specifics

    Why:

    CURRENT
    audio-generation, audio-processing, music-generation, pytorch
    COPY-PASTE FIX
    audio-generation, audio-processing, music-generation, pytorch, generative-ai, audio-llm, text-to-music
  • lowhomepage#3
    Add a homepage URL to the About section

    Why:

    COPY-PASTE FIX
    https://funaudiollm.github.io/inspiremusic

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 FunAudioLLM/FunMusic
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
tensorflow/magenta
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. tensorflow/magenta · recommended 1×
  2. openai/jukebox · recommended 1×
  3. huggingface/transformers · recommended 1×
  4. riffusion/riffusion · recommended 1×
  5. AudioLM · recommended 1×
  • CATEGORY QUERY
    What are some robust toolkits for generating high-quality, long-form music and audio content?
    you: not recommended
    AI recommended (in order):
    1. Google Magenta (tensorflow/magenta)
    2. OpenAI Jukebox (openai/jukebox)
    3. Hugging Face Transformers (huggingface/transformers)
    4. Riffusion (riffusion/riffusion)
    5. AudioLM
    6. AIVA
    7. Amper Music

    AI recommended 7 alternatives but never named FunAudioLLM/FunMusic. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a PyTorch-based framework to programmatically create diverse music, songs, and audio.
    you: not recommended
    AI recommended (in order):
    1. AudioGen
    2. MusicGen
    3. Diffusers
    4. TorchAudio
    5. Jukebox
    6. Magenta

    AI recommended 6 alternatives but never named FunAudioLLM/FunMusic. 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 FunAudioLLM/FunMusic?
    pass
    AI did not name FunAudioLLM/FunMusic — 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 FunAudioLLM/FunMusic in production, what risks or prerequisites should they evaluate first?
    pass
    AI named FunAudioLLM/FunMusic 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 FunAudioLLM/FunMusic solve, and who is the primary audience?
    pass
    AI named FunAudioLLM/FunMusic 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 FunAudioLLM/FunMusic. 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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FunAudioLLM/FunMusic — 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
FunAudioLLM/FunMusic — RepoGEO report