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Neo4J AI Experiments

Neo4J AI Experiments is a JavaScript tutorial repository containing examples that connect Neo4j with local AI models to generate Cypher from natural-language prompts, perform vector search and demonstrate retrieval-augmented generation with sample text. It also includes database seeding and response caching.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Neo4J AI Experiments — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when studying or adapting tutorial code for a local-model, Neo4j-backed query or RAG prototype.

Who it is for

  • Developers learning to connect local AI models with Neo4j.
  • Builders exploring natural-language querying, vector search or RAG patterns.

Documented uses

  • Turn natural-language prompts into Cypher queries for Neo4j.
  • Explore vector search and RAG using Neo4j and sample text.
  • Set up a seeded example database and examine response caching.
Before you choose

Requirements & limits

  • The documented environment requires Ollama, Docker and Node.js; Node.js v22 or later is recommended.
  • The README names Gemma 7B and DeepSeek Coder 6.7B as the models to pull.
  • Examples include a natural-language-to-Cypher application, a separate vector-search example and a RAG example using sample text.
  • The project is licensed under MIT.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up the Neo4j AI example

Prepare the documented local environment, seed its database and launch the application.

Before you start

  • Ollama
  • Docker
  • Node.js (v22 or later recommended)

Steps

  1. Start Ollama with ollama serve, then pull gemma:7b and deepseek-coder:6.7b.

  2. Start Neo4j with docker-compose up -d.

  3. Install project dependencies with the command below.

    Documented command
    npm ci

  4. Seed the database with the command below, then launch the app with the command below.

    Documented command
    npm run seed
    Documented command
    npm run dev

  5. Run the command below twice to observe the documented caching behavior.

    Documented command
    sh request.sh

Expected outcome

A launched example application with a seeded Neo4j database; the repeated request script is provided to observe caching behavior.

Guide limitations

  • The repository documents a tutorial setup using local models and sample data; it does not establish suitability for production workloads.
Documentation 1 ↗
COMPARE OPTIONS

Compare options for Vector search

These projects document a common task and share a project role. This is a source-based comparison, not an execution benchmark or a guarantee of interchangeability.

ProjectDocumented purposePlatformAccess and requirements
Neo4J AI ExperimentsTurn natural-language prompts into Cypher queries for Neo4j.Docker, Self-hosted, Server
Chatbot with PDF for Semantic SearchPrepare document content as embeddings and save it to a supported vector database.WebThe repository is identified as open source and publicly visible on GitHub.
AI LLM PlaygroundAsk questions about PDF documents through an assistant interface.Web
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
16 October 2026
Original website title
ErickWendel/neo4j-ai-experiments · Official homepage title · retained in its source language
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