RRepoGEO

REPOGEO REPORT · LITE

gabber-dev/gabber

Default branch main · commit 9e6f0f7e · scanned 6/28/2026, 5:43:02 PM

GitHub: 1,106 stars · 109 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 gabber-dev/gabber, 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
    Reposition README opening to clarify project purpose

    Why:

    CURRENT
    Gabber is an engine for building real-time AI across all modalities — voice, text, video, and more. It supports graph-based apps with multiple participants and simultaneous media streams. Our goal is to give developers the **most powerful, developer-friendly AI app builder** available.
    COPY-PASTE FIX
    Gabber is a real-time AI engine for developers to build multimodal AI applications that can see, hear, and speak using live camera, microphone, and screen inputs. It supports graph-based apps with multiple participants and simultaneous media streams, aiming to be the **most powerful, developer-friendly AI app builder** available for interactive AI experiences.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    real-time-ai, multimodal-ai, ai-engine, webrtc, voice-ai, video-ai, nlp, developer-tools, ai-applications, livekit
  • mediumreadme#3
    Clarify the existing license in the README

    Why:

    COPY-PASTE FIX
    This project is licensed under [Insert specific license name(s) here, e.g., 'a custom license combining Apache-2.0 and MIT components']. Please see the [LICENSE](LICENSE) file for full details.

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 gabber-dev/gabber
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
TensorRT
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. TensorRT · recommended 2×
  2. NVIDIA Riva · recommended 1×
  3. NVIDIA-AI-IOT/deepstream_sdk · recommended 1×
  4. Google Cloud AI Platform · recommended 1×
  5. Speech-to-Text API · recommended 1×
  • CATEGORY QUERY
    How to build real-time AI applications that process voice, text, and video streams?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA Riva
    2. DeepStream SDK (NVIDIA-AI-IOT/deepstream_sdk)
    3. TensorRT
    4. Google Cloud AI Platform
    5. Speech-to-Text API
    6. Video AI API
    7. Natural Language API
    8. Dialogflow
    9. AWS AI Services
    10. Amazon Transcribe
    11. Amazon Rekognition
    12. Amazon Comprehend
    13. Amazon Polly
    14. OpenVINO Toolkit (openvinotoolkit/openvino)
    15. Kaldi (kaldi-asr/kaldi)
    16. Mozilla DeepSpeech (mozilla/DeepSpeech)
    17. OpenCV (opencv/opencv)
    18. TensorFlow Extended (TFX) (tensorflow/tfx)
    19. PyTorch (pytorch/pytorch)
    20. TensorFlow (tensorflow/tensorflow)
    21. Kafka (apache/kafka)
    22. RabbitMQ (rabbitmq/rabbitmq-server)
    23. FastAPI (tiangolo/fastapi)
    24. gRPC (grpc/grpc)
    25. Azure AI Platform
    26. Azure Cognitive Services Speech
    27. Azure Cognitive Services Vision
    28. Azure Cognitive Services Language

    AI recommended 28 alternatives but never named gabber-dev/gabber. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help develop interactive AI apps using live camera and microphone inputs?
    you: not recommended
    AI recommended (in order):
    1. OpenCV
    2. PyAudio
    3. SoundDevice
    4. TensorFlow.js
    5. PyTorch
    6. MediaPipe
    7. Unity
    8. Barracuda
    9. Electron
    10. p5.js
    11. ml5.js
    12. Flutter
    13. ML Kit
    14. TensorFlow Lite
    15. dlib
    16. TensorRT
    17. OpenVINO

    AI recommended 17 alternatives but never named gabber-dev/gabber. 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 gabber-dev/gabber?
    pass
    AI named gabber-dev/gabber explicitly

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

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

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

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gabber-dev/gabber — 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