RRepoGEO

REPOGEO REPORT · LITE

rashadphz/farfalle

Default branch main · commit a9dd4939 · scanned 5/14/2026, 1:53:13 AM

GitHub: 3,534 stars · 321 forks

AI VISIBILITY SCORE
33 /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
2 / 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 rashadphz/farfalle, 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 explicitly state its category and purpose

    Why:

    CURRENT
    # Farfalle
    
    Open-source AI-powered search engine. (Perplexity Clone)
    COPY-PASTE FIX
    # Farfalle
    
    Open-source AI-powered search engine. (Perplexity Clone)
    
    Farfalle is a full-stack, self-hostable AI answer engine designed to provide summarized search results using local or cloud LLMs, similar to Perplexity AI.
  • mediumtopics#2
    Add more specific topics to reinforce its identity as an AI answer engine

    Why:

    CURRENT
    fastapi, generative-ui, gpt-4o, groq, llm, nextjs, ollama, openai, perplexity, react, search-engine, shadcn-ui, tailwindcss
    COPY-PASTE FIX
    fastapi, generative-ui, gpt-4o, groq, llm, nextjs, ollama, openai, perplexity, react, search-engine, shadcn-ui, tailwindcss, ai-answer-engine, rag, self-hosted-ai, llm-search
  • mediumreadme#3
    Add a 'Why Farfalle?' section to differentiate it from frameworks and clarify its product nature

    Why:

    COPY-PASTE FIX
    ## ✨ Why Farfalle?
    
    Unlike general-purpose LLM frameworks (e.g., Haystack, LlamaIndex) or search databases (e.g., Elasticsearch), Farfalle is a complete, ready-to-deploy AI search engine application. It provides an end-to-end solution for self-hosting a Perplexity-style answer engine, integrating search providers, LLMs, and a full user interface out-of-the-box.

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 rashadphz/farfalle
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
deepset-ai/haystack
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. deepset-ai/haystack · recommended 1×
  2. run-llama/llama_index · recommended 1×
  3. elastic/elasticsearch · recommended 1×
  4. weaviate/weaviate · recommended 1×
  5. opensearch-project/OpenSearch · recommended 1×
  • CATEGORY QUERY
    I need a self-hostable search engine that summarizes results using large language models.
    you: not recommended
    AI recommended (in order):
    1. Haystack (deepset-ai/haystack)
    2. LlamaIndex (run-llama/llama_index)
    3. Elasticsearch (elastic/elasticsearch)
    4. Weaviate (weaviate/weaviate)
    5. OpenSearch (opensearch-project/OpenSearch)
    6. Milvus (milvus-io/milvus)
    7. Qdrant (qdrant/qdrant)

    AI recommended 7 alternatives but never named rashadphz/farfalle. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tools to create a web-based AI answer engine using a Python backend and React frontend?
    you: not recommended
    AI recommended (in order):
    1. FastAPI
    2. Django REST Framework (DRF)
    3. Flask
    4. Hugging Face Transformers
    5. LangChain
    6. spaCy
    7. NLTK (Natural Language Toolkit)
    8. Create React App (CRA)
    9. Next.js
    10. Vite
    11. PostgreSQL
    12. SQLite
    13. MongoDB

    AI recommended 13 alternatives but never named rashadphz/farfalle. 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 rashadphz/farfalle?
    pass
    AI did not name rashadphz/farfalle — 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 rashadphz/farfalle in production, what risks or prerequisites should they evaluate first?
    pass
    AI named rashadphz/farfalle 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 rashadphz/farfalle solve, and who is the primary audience?
    pass
    AI named rashadphz/farfalle explicitly

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

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rashadphz/farfalle — 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