RRepoGEO

REPOGEO REPORT · LITE

InternLM/InternLM-XComposer

Default branch main · commit 0f70c3e3 · scanned 6/26/2026, 3:43:53 PM

GitHub: 2,924 stars · 174 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
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 InternLM/InternLM-XComposer, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add specific topics for streaming video/audio and conversational AI

    Why:

    CURRENT
    chatgpt, foundation, gpt, gpt-4, instruction-tuning, language-model, large-language-model, large-vision-language-model, llm, mllm, multi-modality, multimodal, supervised-finetuning, vision-language-model, vision-transformer, visual-language-learning
    COPY-PASTE FIX
    chatgpt, foundation, gpt, gpt-4, instruction-tuning, language-model, large-language-model, large-vision-language-model, llm, mllm, multi-modality, multimodal, supervised-finetuning, vision-language-model, vision-transformer, visual-language-learning, streaming-video, streaming-audio, real-time-ai, conversational-ai, video-llm, audio-llm, multimodal-interaction
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    Add a relevant URL (e.g., project page, main research page, or a dedicated demo page) to the repository's homepage field.

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 InternLM/InternLM-XComposer
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
NVIDIA DeepStream SDK
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. NVIDIA DeepStream SDK · recommended 1×
  2. NVIDIA Riva · recommended 1×
  3. Google Cloud Video AI · recommended 1×
  4. Google Cloud Speech-to-Text · recommended 1×
  5. Dialogflow · recommended 1×
  • CATEGORY QUERY
    Seeking a multimodal AI system for real-time processing and interaction with long streaming video.
    you: not recommended
    AI recommended (in order):
    1. NVIDIA DeepStream SDK
    2. NVIDIA Riva
    3. Google Cloud Video AI
    4. Google Cloud Speech-to-Text
    5. Dialogflow
    6. AWS Rekognition Video
    7. AWS Transcribe
    8. Amazon Lex
    9. OpenCV
    10. PyTorch
    11. TensorFlow
    12. Vosk
    13. Kaldi
    14. Azure Video Analyzer
    15. Azure Cognitive Services
    16. Speech Service
    17. Language Service

    AI recommended 17 alternatives but never named InternLM/InternLM-XComposer. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best large vision-language models for conversational AI with video and audio input?
    you: not recommended
    AI recommended (in order):
    1. Google Gemini
    2. OpenAI GPT-4o
    3. Meta Llama 3
    4. Microsoft Copilot
    5. Google PaLM 2
    6. BLIP-2
    7. InstructBLIP
    8. Flamingo

    AI recommended 8 alternatives but never named InternLM/InternLM-XComposer. 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 InternLM/InternLM-XComposer?
    pass
    AI named InternLM/InternLM-XComposer explicitly

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

  • If a team adopts InternLM/InternLM-XComposer in production, what risks or prerequisites should they evaluate first?
    pass
    AI named InternLM/InternLM-XComposer 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 InternLM/InternLM-XComposer solve, and who is the primary audience?
    pass
    AI named InternLM/InternLM-XComposer 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 InternLM/InternLM-XComposer. 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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HTML
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InternLM/InternLM-XComposer — 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