RRepoGEO

REPOGEO REPORT · LITE

weiwill88/Local_Pdf_Chat_RAG

Default branch main · commit 90073f17 · scanned 6/3/2026, 10:56:54 AM

GitHub: 910 stars · 170 forks

AI VISIBILITY SCORE
22 /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
1 / 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 weiwill88/Local_Pdf_Chat_RAG, 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
  • highabout#1
    Add a clear English description to the 'About' section

    Why:

    CURRENT
    🧠 纯原生 Python 实现的 RAG 框架 | FAISS + BM25 混合检索 | 支持 Ollama / SiliconFlow | 适合新手入门学习
    COPY-PASTE FIX
    🧠 A pure Python RAG framework for beginners to learn, featuring FAISS + BM25 hybrid retrieval and support for local Ollama / SiliconFlow LLMs for document Q&A.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT License) in the root of the repository.
  • mediumhomepage#3
    Update or remove the homepage link

    Why:

    CURRENT
    https://item.jd.com/14639741.html
    COPY-PASTE FIX
    Remove the current homepage link, or replace it with a relevant project website or documentation if one exists.

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 weiwill88/Local_Pdf_Chat_RAG
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LlamaIndex
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LlamaIndex · recommended 2×
  2. LangChain · recommended 2×
  3. Haystack · recommended 2×
  4. Faiss · recommended 2×
  5. sentence-transformers · recommended 1×
  • CATEGORY QUERY
    How to implement a local RAG system for various document types using Python for learning?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Haystack
    4. Faiss
    5. sentence-transformers
    6. ChromaDB
    7. Weaviate

    AI recommended 7 alternatives but never named weiwill88/Local_Pdf_Chat_RAG. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What Python framework offers hybrid retrieval and local LLM integration for document Q&A?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Haystack
    4. RAGatouille
    5. Sentence-Transformers
    6. Faiss
    7. Annoy
    8. Hnswlib
    9. pyserini
    10. rank_bm25
    11. transformers
    12. Llama.cpp
    13. Ollama

    AI recommended 13 alternatives but never named weiwill88/Local_Pdf_Chat_RAG. 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 weiwill88/Local_Pdf_Chat_RAG?
    pass
    AI did not name weiwill88/Local_Pdf_Chat_RAG — likely talking about a different project

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

  • If a team adopts weiwill88/Local_Pdf_Chat_RAG in production, what risks or prerequisites should they evaluate first?
    pass
    AI named weiwill88/Local_Pdf_Chat_RAG 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 weiwill88/Local_Pdf_Chat_RAG solve, and who is the primary audience?
    pass
    AI did not name weiwill88/Local_Pdf_Chat_RAG — likely talking about a different project

    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 weiwill88/Local_Pdf_Chat_RAG. 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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weiwill88/Local_Pdf_Chat_RAG — 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