RRepoGEO

REPOGEO REPORT · LITE

varunshenoy/GraphGPT

Default branch main · commit dcea106f · scanned 5/25/2026, 9:08:02 AM

GitHub: 4,428 stars · 396 forks

AI VISIBILITY SCORE
40 /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
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 varunshenoy/GraphGPT, 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 opening statement to emphasize demonstration value

    Why:

    CURRENT
    *Note: this is a toy project I built out over a weekend. If you want to use knowledge graphs in your project, check out GPT Index.

GraphGPT converts unstructured natural language into a knowledge graph.
    COPY-PASTE FIX
    GraphGPT is an experimental demonstration of how Large Language Models (LLMs) can convert unstructured natural language into a visual knowledge graph. Built over a weekend, it showcases the potential for natural language interfaces to interact with and build graph-based data.

Pass in the synopsis of your favorite movie, a passage from a confusing Wikipedia page, or transcript from a video to generate a graph visualization of entities and their relationships.
  • mediumtopics#2
    Expand GitHub Topics with more specific keywords

    Why:

    CURRENT
    gpt-3, knowledge-graph
    COPY-PASTE FIX
    gpt-3, knowledge-graph, llm, natural-language-processing, graph-visualization, text-to-graph, ai-models
  • lowreadme#3
    Add a 'Key Features' section to the README

    Why:

    COPY-PASTE FIX
    ## Key Features
*   **Natural Language to Knowledge Graph Conversion:** Transforms unstructured text (movie synopses, Wikipedia passages, video transcripts) into structured entities and relationships using LLMs.
*   **Interactive Graph Visualization:** Renders generated knowledge graphs visually, allowing for easy understanding of complex relationships.
*   **Successive Graph Updates:** Supports updating existing graphs with new information or creating entirely new structures through subsequent queries.

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 varunshenoy/GraphGPT
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Neo4j
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Neo4j · recommended 2×
  2. Stanford CoreNLP · recommended 2×
  3. Hugging Face Transformers · recommended 2×
  4. Google Cloud Natural Language API · recommended 2×
  5. spaCy · recommended 1×
  • CATEGORY QUERY
    What are the best tools for extracting and visualizing knowledge graphs from unstructured text?
    you: not recommended
    AI recommended (in order):
    1. Neo4j
    2. spaCy
    3. Stanford CoreNLP
    4. Hugging Face Transformers
    5. Neo4j Browser
    6. Bloom
    7. GraphDB
    8. GATE
    9. Stardog
    10. Kùzu
    11. NetworkX
    12. Matplotlib
    13. Plotly
    14. Pyvis
    15. Google Cloud Natural Language API
    16. Google Cloud Dataflow
    17. BigQuery
    18. UIMA
    19. Apache Jena

    AI recommended 19 alternatives but never named varunshenoy/GraphGPT. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I automatically build knowledge graphs from natural language using AI models?
    you: not recommended
    AI recommended (in order):
    1. Stanford OpenIE
    2. Stanford CoreNLP
    3. OpenNRE
    4. Hugging Face Transformers
    5. SpaCy
    6. Neo4j
    7. py2neo
    8. neo4j-driver
    9. Graph Data Science Library (GDS)
    10. Amazon Neptune
    11. Google Cloud Natural Language API
    12. Azure Text Analytics
    13. IBM Watson Natural Language Understanding (NLU)

    AI recommended 13 alternatives but never named varunshenoy/GraphGPT. 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 varunshenoy/GraphGPT?
    pass
    AI named varunshenoy/GraphGPT explicitly

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

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

    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 varunshenoy/GraphGPT. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/varunshenoy/GraphGPT.svg)](https://repogeo.com/en/r/varunshenoy/GraphGPT)
HTML
<a href="https://repogeo.com/en/r/varunshenoy/GraphGPT"><img src="https://repogeo.com/badge/varunshenoy/GraphGPT.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

varunshenoy/GraphGPT — 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