RRepoGEO

REPOGEO REPORT · LITE

jd-opensource/JoyAI-VL-Interaction

Default branch main · commit 9d07596b · scanned 6/25/2026, 7:13:20 PM

GitHub: 686 stars · 47 forks

AI VISIBILITY SCORE
17 /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
1 / 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 jd-opensource/JoyAI-VL-Interaction, 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
  • highabout#1
    Add a concise 'About' description for the repository

    Why:

    COPY-PASTE FIX
    An 8B-scale, fully open vision-language interaction model with a complete deployable system — the model, training recipe, time-aligned interaction data, and a real-time streaming stack, all in one repository.
  • hightopics#2
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    vision-language-model, multimodal-ai, real-time-interaction, llm, streaming, deployable-system, ai-model, deep-learning
  • mediumhomepage#3
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    https://joyai-vl-video-future-academy-jd.github.io/JoyAI-VL-Interaction/

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 jd-opensource/JoyAI-VL-Interaction
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
FFmpeg
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. FFmpeg · recommended 1×
  2. GStreamer · recommended 1×
  3. OpenCV · recommended 1×
  4. Google Cloud Speech-to-Text API · recommended 1×
  5. AWS Transcribe Streaming · recommended 1×
  • CATEGORY QUERY
    How to implement a real-time video-language interaction system for live streaming applications?
    you: not recommended
    AI recommended (in order):
    1. FFmpeg
    2. GStreamer
    3. OpenCV
    4. Google Cloud Speech-to-Text API
    5. AWS Transcribe Streaming
    6. AssemblyAI
    7. OpenAI Whisper (openai/whisper)
    8. TensorFlow Lite (tensorflow/tensorflow)
    9. PyTorch Mobile (pytorch/pytorch)
    10. NVIDIA DeepStream SDK
    11. OpenVINO Toolkit (openvinotoolkit/openvino)
    12. YOLO (You Only Look Once) models
    13. OpenAI GPT-4
    14. GPT-3.5 Turbo
    15. Hugging Face Transformers Library (huggingface/transformers)
    16. Google Cloud Natural Language API
    17. LangChain (langchain-ai/langchain)
    18. Apache Kafka (apache/kafka)
    19. RabbitMQ (rabbitmq/rabbitmq-server)
    20. WebSockets
    21. Redis Pub/Sub (redis/redis)

    AI recommended 21 alternatives but never named jd-opensource/JoyAI-VL-Interaction. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an open-source, deployable vision-language model with training data and streaming support.
    you: not recommended
    AI recommended (in order):
    1. LLaVA
    2. BLIP-2
    3. MiniGPT-4
    4. OpenFlamingo
    5. InstructBLIP
    6. Fuyu-8B

    AI recommended 6 alternatives but never named jd-opensource/JoyAI-VL-Interaction. 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 jd-opensource/JoyAI-VL-Interaction?
    pass
    AI did not name jd-opensource/JoyAI-VL-Interaction — 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 jd-opensource/JoyAI-VL-Interaction in production, what risks or prerequisites should they evaluate first?
    pass
    AI named jd-opensource/JoyAI-VL-Interaction 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 jd-opensource/JoyAI-VL-Interaction solve, and who is the primary audience?
    pass
    AI did not name jd-opensource/JoyAI-VL-Interaction — 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?

Embed your GEO score

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MARKDOWN (README)
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jd-opensource/JoyAI-VL-Interaction — 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