RRepoGEO

REPOGEO REPORT · LITE

wenda-LLM/wenda

Default branch main · commit f577766a · scanned 5/21/2026, 11:38:10 PM

GitHub: 6,179 stars · 791 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 wenda-LLM/wenda, 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
    Strengthen README's opening to emphasize private, self-hosted platform for limited resources

    Why:

    CURRENT
    本项目设计目标为实现针对特定环境的高效内容生成，同时考虑个人和中小企业的计算资源局限性，以及知识安全和私密性问题。
    COPY-PASTE FIX
    本项目设计目标为实现针对特定环境的高效内容生成，特别针对个人和中小企业，提供一个可私有化部署、支持本地知识库、并高效利用有限计算资源的LLM调用平台，同时保障知识安全和私密性。
  • hightopics#2
    Add more descriptive topics to improve categorization

    Why:

    CURRENT
    chatglm-6b, chatrwkv, rwkv
    COPY-PASTE FIX
    chatglm-6b, chatrwkv, rwkv, llm-platform, private-llm, knowledge-base, rag, self-hosted, local-llm, content-generation, ai-assistant
  • mediumhomepage#3
    Set the 'Homepage' URL in repository settings (replace placeholder)

    Why:

    COPY-PASTE FIX
    https://your-project-homepage.com

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 wenda-LLM/wenda
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Ollama
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Ollama · recommended 1×
  2. LlamaIndex · recommended 1×
  3. LangChain · recommended 1×
  4. Chroma · recommended 1×
  5. FAISS · recommended 1×
  • CATEGORY QUERY
    How to deploy a private large language model platform with a local knowledge base?
    you: not recommended
    AI recommended (in order):
    1. Ollama
    2. LlamaIndex
    3. LangChain
    4. Chroma
    5. FAISS
    6. LM Studio
    7. PrivateGPT
    8. LocalAI
    9. Hugging Face Transformers
    10. Weaviate
    11. Qdrant

    AI recommended 11 alternatives but never named wenda-LLM/wenda. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What platform helps run diverse large language models on limited resources for content generation?
    you: not recommended
    AI recommended (in order):
    1. RunPod
    2. Google Cloud Vertex AI
    3. Hugging Face Inference Endpoints
    4. Modal
    5. Replicate
    6. Vast.ai

    AI recommended 6 alternatives but never named wenda-LLM/wenda. 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 wenda-LLM/wenda?
    pass
    AI named wenda-LLM/wenda explicitly

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

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

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

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  • Brand-free category queries5 vs 2 in Lite
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wenda-LLM/wenda — RepoGEO report