RRepoGEO

REPOGEO REPORT · LITE

gkamradt/langchain-tutorials

Default branch main · commit 697c4de4 · scanned 5/11/2026, 6:57:54 AM

GitHub: 7,431 stars · 2,026 forks

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 gkamradt/langchain-tutorials, 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 README's primary purpose as a learning resource

    Why:

    CURRENT
    # Learn LangChain

Overview, Tutorial, and Examples of LangChain
    COPY-PASTE FIX
    Replace the first two lines with: `# LangChain Tutorials: Your Hands-On Learning Path` and `A comprehensive collection of code, videos, and examples to master building applications with LangChain.`
  • hightopics#2
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    langchain, tutorials, learning-path, generative-ai, llms, python, jupyter-notebooks, prompt-engineering
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Add a `LICENSE` file to the repository root, for example, `LICENSE.md` or `LICENSE.txt`, containing the full text of your chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).

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 gkamradt/langchain-tutorials
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI · recommended 1×
  2. huggingface/transformers · recommended 1×
  3. Google AI for Developers · recommended 1×
  4. Google Colab · recommended 1×
  5. langchain-ai/langchain · recommended 1×
  • CATEGORY QUERY
    Where can I find beginner tutorials for building AI applications with language models?
    you: not recommended
    AI recommended (in order):
    1. OpenAI
    2. Hugging Face Transformers (huggingface/transformers)
    3. Google AI for Developers
    4. Google Colab
    5. LangChain (langchain-ai/langchain)
    6. freeCodeCamp.org YouTube Channel
    7. Kaggle Learn

    AI recommended 7 alternatives but never named gkamradt/langchain-tutorials. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to implement document summarization and question answering with generative AI?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. Anthropic Claude
    3. Google Gemini API
    4. Hugging Face Transformers
    5. LangChain
    6. LlamaIndex

    AI recommended 6 alternatives but never named gkamradt/langchain-tutorials. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 gkamradt/langchain-tutorials?
    pass
    AI did not name gkamradt/langchain-tutorials — 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 gkamradt/langchain-tutorials in production, what risks or prerequisites should they evaluate first?
    pass
    AI named gkamradt/langchain-tutorials 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 gkamradt/langchain-tutorials solve, and who is the primary audience?
    pass
    AI did not name gkamradt/langchain-tutorials — 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 gkamradt/langchain-tutorials. 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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MARKDOWN (README)
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gkamradt/langchain-tutorials — 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