Voice to Knowledge Graph Demo

Project Description

This demo showcases a Gradio application that converts spoken audio into a visual knowledge graph. Users can record their voice, and the application transcribes the audio, extracts relevant nodes and relationships, and visualizes them in a Neo4j knowledge graph.

System Requirements

• Anaconda or Miniconda

Installation

Step 1: Clone the Repository

Clone this repository to your local machine using:

git clone https://github.com/Reynold97/VTKG.git
cd VTKG

Step 2: Create a Conda Environment

Create a Conda environment using:

conda create -p ./env python=3.10 -y

Step 3: Activate the Environment

Activate the newly created environment:

conda activate ./env

Step 4: Install Required Packages

Install all required packages listed in requirements.txt:

pip install -r requirements.txt

Step 5: Create a Neo4j database instance

You will need to have a running Neo4j instance. One option is to create a free Neo4j database instance in their Aura cloud service. You can also run the database locally using the Neo4j Desktop application, or running a docker container. You can run a local docker container by running the executing the following script:

docker run \
    --name neo4j \
    -p 7474:7474 -p 7687:7687 \
    -d \
    -e NEO4J_AUTH=neo4j/pleaseletmein \
    -e NEO4J_PLUGINS=\[\"apoc\"\]  \
    neo4j:latest

If you are using the docker container, you need to wait a couple of second for the database to start.

Step 6: Create a .env file

Create a .env file in the root directory with the following structure

DEEPGRAM_API_KEY=
OPENAI_API_KEY=
NEO4J_USER=
NEO4J_PASS=
NEO4J_URL=

Step 7: Running the Application

Run the application with:

python app.py

This will start the Gradio app, which is accessible via a web browser. Follow the on-screen instructions to record your voice and generate the knowledge graph.

Usage

Record Audio: Click the 'Record' button and speak into your microphone. Submit: Submit the audio recording to process. View Graph: After processing, go to your Neo4j instance to inspect the knowledge graph.