RRepoGEO

REPOGEO REPORT · LITE

OpenGVLab/InternGPT

Default branch main · commit a04d6dd6 · scanned 6/28/2026, 9:27:51 PM

GitHub: 3,204 stars · 234 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
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 OpenGVLab/InternGPT, 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 the README's opening paragraph to emphasize its role as an interactive visual editing platform

    Why:

    CURRENT
    InternGPT (short for iGPT) / InternChat (short for iChat) is pointing-language-driven visual interactive system, allowing you to interact with ChatGPT by clicking, dragging and drawing using a pointing device.
    COPY-PASTE FIX
    InternGPT (iGPT) is an open-source, pointing-language-driven visual interactive platform designed for multimodal AI models, enabling users to interact with large language models like ChatGPT through clicking, dragging, and drawing for advanced image and video editing tasks.
  • mediumtopics#2
    Add more specific topics related to interactive AI platforms and visual editing

    Why:

    CURRENT
    chatgpt, click, draggan, foundation-model, gpt, gpt-4, gradio, husky, image-captioning, imagebind, internimage, langchain, llama, llm, multimodal, sam, segment-anything, vicuna, video-generation, vqa
    COPY-PASTE FIX
    chatgpt, click, draggan, foundation-model, gpt, gpt-4, gradio, husky, image-captioning, imagebind, internimage, langchain, llama, llm, multimodal, sam, segment-anything, vicuna, video-generation, vqa, interactive-ai, visual-editing, multimodal-platform, llm-interface, ai-demo-platform
  • lowreadme#3
    Add a 'Why InternGPT?' or 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    ## Why InternGPT?
Unlike general demo platforms such as Gradio or Hugging Face Spaces, InternGPT is specifically designed as a pointing-language-driven visual interactive system. It focuses on enabling precise, region-specific image and video editing and generation through direct interaction with large language models, significantly enhancing communication efficiency and accuracy for complex visual tasks.

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 OpenGVLab/InternGPT
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Spaces
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Spaces · recommended 2×
  2. Gradio · recommended 1×
  3. PyTorch · recommended 1×
  4. TensorFlow · recommended 1×
  5. JAX · recommended 1×
  • CATEGORY QUERY
    How can I build an interactive demo platform for multimodal AI models with visual editing?
    you: not recommended
    AI recommended (in order):
    1. Gradio
    2. PyTorch
    3. TensorFlow
    4. JAX
    5. OpenCV
    6. Pillow
    7. Streamlit
    8. Hugging Face Spaces
    9. Dash
    10. Panel
    11. Voila
    12. Jupyter widgets
    13. React
    14. Vue.js
    15. Angular
    16. FastAPI
    17. Flask

    AI recommended 17 alternatives but never named OpenGVLab/InternGPT. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools allow visual interaction with large language models for image and video tasks?
    you: not recommended
    AI recommended (in order):
    1. Gradio (gradio-app/gradio)
    2. Streamlit (streamlit/streamlit)
    3. Hugging Face Spaces
    4. FiftyOne (voxel51/fiftyone)
    5. Weights & Biases (wandb/wandb)
    6. Label Studio (heartexlabs/label-studio)

    AI recommended 6 alternatives but never named OpenGVLab/InternGPT. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 OpenGVLab/InternGPT?
    pass
    AI named OpenGVLab/InternGPT explicitly

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

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

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

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OpenGVLab/InternGPT — 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