RRepoGEO

REPOGEO REPORT · LITE

shibing624/ChatPDF

Default branch main · commit 2c57d1f4 · scanned 6/12/2026, 1:52:14 PM

GitHub: 853 stars · 144 forks

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 shibing624/ChatPDF, 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 to emphasize it's a complete, local-first application

    Why:

    CURRENT
    The current H1 is 'ChatPDF' with a subtitle '基于本地 LLM 做检索知识问答(RAG)'.
    COPY-PASTE FIX
    Add an English sentence right after the H1, such as: 'A complete, self-hostable application to chat with your local PDF, DOC, and TXT files using private, local LLMs, without external agent libraries.'
  • mediumabout#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://github.com/shibing624/ChatPDF
  • mediumreadme#3
    Add a sentence to the README's English introduction highlighting its pure, local-first implementation

    Why:

    CURRENT
    The detailed explanation of '无须安装任何第三方agent库' is currently in the '介绍' section.
    COPY-PASTE FIX
    Add a sentence to the English introduction, for example: 'Built purely with local LLM, embedding, and reranker models, ChatPDF offers a complete RAG solution for your documents without requiring any third-party agent libraries.'

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 shibing624/ChatPDF
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LlamaIndex
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LlamaIndex · recommended 1×
  2. Llama 3 · recommended 1×
  3. Mistral · recommended 1×
  4. ChromaDB · recommended 1×
  5. FAISS · recommended 1×
  • CATEGORY QUERY
    How can I build a system to chat with my local documents using a private LLM?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. Llama 3
    3. Mistral
    4. ChromaDB
    5. FAISS
    6. LangChain
    7. Ollama
    8. LM Studio
    9. PrivateGPT
    10. Haystack
    11. Weaviate
    12. Qdrant
    13. sentence-transformers
    14. Streamlit
    15. Flask
    16. Gradio

    AI recommended 16 alternatives but never named shibing624/ChatPDF. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a solution to implement RAG with various document types using entirely local models.
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex (run-llama/llama_index)
    2. LangChain (langchain-ai/langchain)
    3. Haystack (deepset-ai/haystack)
    4. Ollama (ollama/ollama)
    5. Hugging Face Transformers (huggingface/transformers)
    6. Sentence Transformers (UKPLab/sentence-transformers)

    AI recommended 6 alternatives but never named shibing624/ChatPDF. 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 shibing624/ChatPDF?
    pass
    AI named shibing624/ChatPDF explicitly

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

  • If a team adopts shibing624/ChatPDF in production, what risks or prerequisites should they evaluate first?
    pass
    AI named shibing624/ChatPDF 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 shibing624/ChatPDF solve, and who is the primary audience?
    pass
    AI named shibing624/ChatPDF 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 shibing624/ChatPDF. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/shibing624/ChatPDF.svg)](https://repogeo.com/en/r/shibing624/ChatPDF)
HTML
<a href="https://repogeo.com/en/r/shibing624/ChatPDF"><img src="https://repogeo.com/badge/shibing624/ChatPDF.svg" alt="RepoGEO" /></a>
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shibing624/ChatPDF — 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