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README.md

Graph Database-Powered Q&A Chatbot

This app connects a Neo4j graph database to a Gemini LLM via LangChain to enable natural language Q&A over a graph schema. It uses the default Neo4j Movie database as its dataset.

🎥 YouTube Video: Walkthrough on setup and running the app

Watch the video

🎞️ Demo Context

This chatbot uses Neo4j's built-in Movie Database, which includes:

  • Actors
  • Movies
  • Directors
  • Relationships like ACTED_IN and DIRECTED

You can ask natural language questions like:

  • "Who acted in The Matrix?"
  • "List all movies directed by Christopher Nolan."
  • "Which actors have worked together in more than one movie?"
  • "Give me movies released after 2000 featuring Keanu Reeves."

Or any other information available in the Movie graph database.

🔧 Neo4J GraphDB Installation

✅ Download and Install Neo4j Desktop:

  • Visit neo4j.com/download/
  • Click Download, fill in the registration form.
  • Copy the Neo4j Desktop Activation Key.
  • Install Neo4j Desktop with default settings.
  • Launch the app, accept the license agreement.
  • Paste the activation key to activate.

⚙️ Configure Neo4j Database:

  • Open Neo4j Desktop → Open the Movie DBMS example project.
  • Go to the Plugins tab → Install APOC and restart.
  • Go to Details → Click Reset DBMS password and set your new password.

🛠️ Setup Instructions

✅ Prerequisites

  • Python 3.10 or higher
  • pip (Python package installer)

📦 Installation & Running App

  1. Clone the repository:

    git clone https://github.com/genieincodebottle/generative-ai.git
cd genai-usecases\graph-qa

  2. Open the Project in VS Code or any code editor.

  3. Create a virtual environment by running the following command in the terminal:

    pip install uv #if uv not installed
uv venv
.venv\Scripts\activate # On Linux -> source venv/bin/activate

  4. Create a requirements.txt file and add the following libraries:

    langchain>=0.3.27
langchain-community>=0.2.1
langchain-google-genai>=2.1.8
neo4j>=5.28.1
streamlit>=1.47.1
streamlit-chat>=0.1.1
python-dotenv==1.1.1

  5. Install dependencies:

    uv pip install -r requirements.txt

  6. Configure Environment

    • Rename .env.example → .env
    • Update with your keys:
    GOOGLE_API_KEY=your_key_here # Using the free-tier API Key
NEO4J_URI="bolt://localhost:7687"
NEO4J_USERNAME="neo4j"
NEO4J_PASSWORD="your_new_password"

  7. Code Files Overview

    • utils.py: Backend logic - connects to Neo4j, loads env variables, runs LangChain-based Q&A logic.
    • app.py: Streamlit-based frontend - user inputs questions, displays answers from the graph DB.

  8. Run the App

    streamlit run app.py

⚠️ Troubleshooting

If you see an error like:

neo4j.exceptions.ServiceUnavailable: Couldn't connect to localhost:7687 (resolved to ('[::1]:7687', '127.0.0.1:7687')):  
Failed to establish connection to ResolvedIPv6Address(('::1', 7687, 0, 0))

✅ Open the Neo4j Desktop dashboard, go to the Settings tab, and verify that the Bolt port (7687) is enabled.

📌 Ensure the following line exists and is not commented out in the settings:

dbms.connector.bolt.listen_address=:7687

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