RRepoGEO

REPOGEO REPORT · LITE

patterns-ai-core/langchainrb

Default branch main · commit 5fb5be6c · scanned 5/23/2026, 3:07:48 PM

GitHub: 1,983 stars · 260 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
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 patterns-ai-core/langchainrb, 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
    Clarify the repository's unique identity in the README's opening

    Why:

    CURRENT
    💎🔗 Langchain.rb
⚡ Building LLM-powered applications in Ruby ⚡
    COPY-PASTE FIX
    💎🔗 Langchain.rb (patterns-ai-core/langchainrb)
⚡ The leading Ruby gem for building LLM-powered applications ⚡
  • mediumtopics#2
    Expand topics to include 'langchain' and core functionalities

    Why:

    CURRENT
    agents, ai-agents, artificial-intelligence, machine-learning, ml, rubyml, vector-search
    COPY-PASTE FIX
    agents, ai-agents, artificial-intelligence, machine-learning, ml, rubyml, vector-search, langchain, llm-orchestration, retrieval-augmented-generation, prompt-engineering
  • lowreadme#3
    Add a 'Comparison' section to differentiate from alternatives

    Why:

    COPY-PASTE FIX
    ## Comparison

[Add a section here explaining how patterns-ai-core/langchainrb differentiates itself from other Ruby LLM libraries like Ruby-LLM, and clarify its relationship to other projects named 'LangChain' in the Ruby ecosystem.]

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 patterns-ai-core/langchainrb
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Ruby-LLM
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Ruby-LLM · recommended 2×
  2. langchain-rb/langchain-rb · recommended 1×
  3. openai/openai-ruby · recommended 1×
  4. googleapis/google-cloud-ruby · recommended 1×
  5. jnunemaker/httparty · recommended 1×
  • CATEGORY QUERY
    What's the best way to integrate large language models into a Ruby application?
    you: not recommended
    AI recommended (in order):
    1. LangChain.rb (langchain-rb/langchain-rb)
    2. OpenAI Ruby Gem (openai/openai-ruby)
    3. Google AI Ruby Gem (googleapis/google-cloud-ruby)
    4. HTTParty (jnunemaker/httparty)
    5. Faraday (lostisland/faraday)
    6. Llama.cpp (ggerganov/llama.cpp)
    7. Ruby-LLM

    AI recommended 7 alternatives but never named patterns-ai-core/langchainrb. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a Ruby library for building AI-powered chatbots with retrieval augmented generation.
    you: not recommended
    AI recommended (in order):
    1. LangChain.rb
    2. Ruby-LLM
    3. OpenAI Ruby Gem
    4. Faiss Ruby
    5. Pgvector

    AI recommended 5 alternatives but never named patterns-ai-core/langchainrb. 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 patterns-ai-core/langchainrb?
    pass
    AI did not name patterns-ai-core/langchainrb — 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 patterns-ai-core/langchainrb in production, what risks or prerequisites should they evaluate first?
    pass
    AI named patterns-ai-core/langchainrb 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 patterns-ai-core/langchainrb solve, and who is the primary audience?
    pass
    AI named patterns-ai-core/langchainrb explicitly

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

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