RRepoGEO

REPOGEO REPORT · LITE

pgvector/pgvector-python

Default branch master · commit 5b06584a · scanned 5/19/2026, 2:37:32 AM

GitHub: 1,481 stars · 93 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
28 /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
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 pgvector/pgvector-python, 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
  • hightopics#1
    Add relevant topics for better categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    pgvector, postgresql, python, vector-database, vector-embeddings, vector-search, django, sqlalchemy, psycopg, machine-learning, ai
  • highreadme#2
    Reposition README H1/opening to clarify its role as the official Python client for pgvector

    Why:

    CURRENT
    # pgvector-python

pgvector support for Python
    COPY-PASTE FIX
    # pgvector-python

Python client for pgvector, providing seamless integration with PostgreSQL for vector embeddings and similarity search across popular frameworks like Django, SQLAlchemy, and Psycopg.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://pgvector.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 pgvector/pgvector-python
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
pgvector/pgvector
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. pgvector/pgvector · recommended 2×
  2. facebookresearch/faiss · recommended 2×
  3. psycopg/psycopg2 · recommended 1×
  4. psycopg/psycopg · recommended 1×
  5. supabase/supabase · recommended 1×
  • CATEGORY QUERY
    How can I store and query vector embeddings efficiently in Python using PostgreSQL?
    you: not recommended
    AI recommended (in order):
    1. pgvector (pgvector/pgvector)
    2. psycopg2 (psycopg/psycopg2)
    3. psycopg3 (psycopg/psycopg)
    4. Supabase (supabase/supabase)
    5. LangChain (langchain-ai/langchain)
    6. LlamaIndex (run-llama/llama_index)
    7. SQLAlchemy (sqlalchemy/sqlalchemy)
    8. Faiss (facebookresearch/faiss)
    9. Hnswlib (nmslib/hnswlib)

    AI recommended 9 alternatives but never named pgvector/pgvector-python. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What's the best way to add vector search capabilities to my Django or SQLAlchemy application?
    you: not recommended
    AI recommended (in order):
    1. pgvector (pgvector/pgvector)
    2. Qdrant (qdrant/qdrant)
    3. Weaviate (weaviate/weaviate)
    4. Pinecone
    5. Chroma (chroma-core/chroma)
    6. Elasticsearch (elastic/elasticsearch)
    7. Faiss (facebookresearch/faiss)

    AI recommended 7 alternatives but never named pgvector/pgvector-python. 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 pgvector/pgvector-python?
    pass
    AI did not name pgvector/pgvector-python — 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 pgvector/pgvector-python in production, what risks or prerequisites should they evaluate first?
    pass
    AI named pgvector/pgvector-python 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 pgvector/pgvector-python solve, and who is the primary audience?
    pass
    AI named pgvector/pgvector-python explicitly

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

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pgvector/pgvector-python — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite