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57 changes: 57 additions & 0 deletions java-recipes/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,63 @@
</div>
<br>

## Setup

This project uses Docker Compose to set up a complete environment for running Java-based AI applications with Redis. The environment includes:

- A Jupyter Notebook server with Java kernel support
- Redis Stack (includes Redis and RedisInsight)
- Pre-installed dependencies for AI/ML workloads

### Prerequisites

- [Docker](https://docs.docker.com/get-docker/) and [Docker Compose](https://docs.docker.com/compose/install/)
- OpenAI API key (for notebooks that use OpenAI services)

### Environment Configuration

1. Create a `.env` file in the project root with your OpenAI API key:

```bash
OPENAI_API_KEY=your_openai_api_key_here
```

## Running the Project

1. Clone the repository (if you haven't already):

```bash
git clone https://github.com/redis-developer/redis-ai-resources.git
cd redis-ai-resources/java-recipes
```

2. Start the Docker containers:

```bash
docker-compose up -d
```

3. Access the Jupyter environment:
- Open your browser and navigate to [http://localhost:8888](http://localhost:8888)
- The token is usually shown in the docker-compose logs. You can view them with:

```bash
docker-compose logs jupyter
```

4. Access RedisInsight:
- Open your browser and navigate to [http://localhost:8001](http://localhost:8001)
- Connect to Redis using the following details:
- Host: redis-java
- Port: 6379
- No password (unless configured)

5. When finished, stop the containers:

```bash
docker-compose down
```

## Notebooks

| Notebook | Description |
Expand Down