RRepoGEO

REPOGEO REPORT · LITE

neo4j-labs/llm-graph-builder

Default branch main · commit 4a412f46 · scanned 6/20/2026, 8:16:51 AM

GitHub: 4,874 stars · 832 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 neo4j-labs/llm-graph-builder, 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 to clarify it's an end-to-end application

    Why:

    CURRENT
    Transform unstructured data (PDFs, DOCs, TXTs, YouTube videos, web pages, etc.) into a structured Knowledge Graph stored in Neo4j using the power of Large Language Models (LLMs) and the LangChain framework. This application allows you to upload files from various sources (local machine, GCS, S3 bucket, or web sources), choose your preferred LLM model, and generate a Knowledge Graph.
    COPY-PASTE FIX
    The Knowledge Graph Builder is a complete application that transforms unstructured data (PDFs, DOCs, TXTs, YouTube videos, web pages, etc.) into a structured Knowledge Graph stored in Neo4j. It leverages Large Language Models (LLMs) and the LangChain framework to provide an end-to-end solution for uploading files from various sources (local machine, GCS, S3 bucket, or web sources), choosing your preferred LLM model, and generating a Neo4j Knowledge Graph.
  • mediumtopics#2
    Add more specific topics to emphasize application and automation

    Why:

    CURRENT
    data-import, genai, graph, graph-rag, graph-search, graphdb, graphrag, knowledge-graph, langchain, neo4j, rag, unstructured-data, vectordb
    COPY-PASTE FIX
    data-import, genai, graph, graph-rag, graph-search, graphdb, graphrag, knowledge-graph, langchain, neo4j, rag, unstructured-data, vectordb, knowledge-graph-generation, llm-application, data-to-graph
  • lowreadme#3
    Add a note about the 'Labs' status and its implications

    Why:

    COPY-PASTE FIX
    ### Neo4j Labs Project Status
This project is part of Neo4j Labs, meaning it is experimental and not officially supported for production environments. While actively developed, it may not adhere to the same stability guarantees as official Neo4j products.

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 neo4j-labs/llm-graph-builder
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI GPT-4 / GPT-3.5 Turbo
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI GPT-4 / GPT-3.5 Turbo · recommended 1×
  2. OpenAI Python API client · recommended 1×
  3. LangChain · recommended 1×
  4. LlamaIndex · recommended 1×
  5. Anthropic Claude · recommended 1×
  • CATEGORY QUERY
    How to automatically create a knowledge graph from unstructured documents using large language models?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4 / GPT-3.5 Turbo
    2. OpenAI Python API client
    3. LangChain
    4. LlamaIndex
    5. Anthropic Claude
    6. Google Gemini
    7. Google Cloud Vertex AI
    8. PaLM 2
    9. Amazon Bedrock
    10. AI21 Labs Jurassic-2
    11. Amazon Titan
    12. Hugging Face Transformers
    13. Llama 2
    14. Mistral
    15. Mixtral 8x7B
    16. Falcon 40B
    17. Neo4j Knowledge Graph Platform

    AI recommended 17 alternatives but never named neo4j-labs/llm-graph-builder. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Python tool to extract entities and build a Neo4j knowledge graph from documents?
    you: not recommended
    AI recommended (in order):
    1. spaCy (explosion/spaCy)
    2. py2neo (py2neo-org/py2neo)
    3. neo4j-driver (neo4j/neo4j-python-driver)
    4. Haystack (deepset-ai/haystack)
    5. Graphistry (graphistry/pygraphistry)
    6. Stanford CoreNLP
    7. stanza (stanfordnlp/stanza)
    8. pycorenlp (smilli/pycorenlp)
    9. Textacy (chartbeat-labs/textacy)
    10. pykeen (pykeen/pykeen)
    11. Ampligraph (Accenture/AmpliGraph)

    AI recommended 11 alternatives but never named neo4j-labs/llm-graph-builder. 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 neo4j-labs/llm-graph-builder?
    pass
    AI did not name neo4j-labs/llm-graph-builder — 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 neo4j-labs/llm-graph-builder in production, what risks or prerequisites should they evaluate first?
    pass
    AI named neo4j-labs/llm-graph-builder 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 neo4j-labs/llm-graph-builder solve, and who is the primary audience?
    pass
    AI named neo4j-labs/llm-graph-builder explicitly

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

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neo4j-labs/llm-graph-builder — 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