RRepoGEO

REPOGEO REPORT · LITE

weaviate/recipes

Default branch main · commit 3b84b178 · scanned 6/5/2026, 10:43:17 PM

GitHub: 940 stars · 192 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 weaviate/recipes, 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 README H1 to emphasize "notebooks" and "examples"

    Why:

    CURRENT
    # Welcome to Weaviate Recipes 💚

This repository covers end-to-end examples of the various features and integrations with Weaviate.
    COPY-PASTE FIX
    # Weaviate Recipes 💚: End-to-End Notebooks for Weaviate Features & Integrations
  • highlicense#2
    Add a LICENSE file to the repository root

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT, Apache-2.0, or your preferred license) in the repository root.
  • mediumhomepage#3
    Add a homepage URL to the repository's "About" section

    Why:

    COPY-PASTE FIX
    Set the homepage URL to 'https://weaviate.io/developers/weaviate/recipes' (or the most relevant Weaviate documentation page for recipes).

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 weaviate/recipes
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 2×
  2. facebookresearch/faiss · recommended 2×
  3. huggingface/transformers · recommended 2×
  4. Pinecone · recommended 1×
  5. UKP-SQuARE/sentence-transformers · recommended 1×
  • CATEGORY QUERY
    How to implement retrieval-augmented generation using a vector database with practical examples?
    you: not recommended
    AI recommended (in order):
    1. Pinecone
    2. LangChain (langchain-ai/langchain)
    3. sentence-transformers (UKP-SQuARE/sentence-transformers)
    4. OpenAI
    5. Weaviate (weaviate/weaviate)
    6. Qdrant (qdrant/qdrant)
    7. Chroma (chroma-core/chroma)
    8. Cohere Embeddings
    9. Milvus (milvus-io/milvus)
    10. Faiss (facebookresearch/faiss)
    11. Anthropic's Claude
    12. Google's Gemini
    13. Llama 2
    14. Hugging Face
    15. transformers (huggingface/transformers)
    16. Ragas (explodinggradients/ragas)

    AI recommended 16 alternatives but never named weaviate/recipes. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking python notebooks demonstrating advanced vector search and generative AI integrations for LLMs.
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex (LlamaIndex/llama_index)
    2. LangChain (langchain-ai/langchain)
    3. Hugging Face Transformers (huggingface/transformers)
    4. Hugging Face Datasets (huggingface/datasets)
    5. sentence-transformers (UKPLab/sentence-transformers)
    6. FAISS (facebookresearch/faiss)
    7. Annoy (spotify/annoy)
    8. ScaNN
    9. Pinecone (pinecone-io/examples)
    10. Weaviate (weaviate/weaviate-examples)
    11. Qdrant (qdrant/qdrant-documentation)
    12. DeepLearning.AI

    AI recommended 12 alternatives but never named weaviate/recipes. 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 weaviate/recipes?
    pass
    AI named weaviate/recipes explicitly

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

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

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

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weaviate/recipes — 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