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2222
23+ ## Setup
24+
25+ This project uses Docker Compose to set up a complete environment for running Java-based AI applications with Redis. The environment includes:
26+
27+ - A Jupyter Notebook server with Java kernel support
28+ - Redis Stack (includes Redis and RedisInsight)
29+ - Pre-installed dependencies for AI/ML workloads
30+
31+ ### Prerequisites
32+
33+ - [ Docker] ( https://docs.docker.com/get-docker/ ) and [ Docker Compose] ( https://docs.docker.com/compose/install/ )
34+ - OpenAI API key (for notebooks that use OpenAI services)
35+
36+ ### Environment Configuration
37+
38+ 1 . Create a ` .env ` file in the project root with your OpenAI API key:
39+
40+ ``` bash
41+ OPENAI_API_KEY=your_openai_api_key_here
42+ ```
43+
44+ ## Running the Project
45+
46+ 1 . Clone the repository (if you haven't already):
47+
48+ ``` bash
49+ git clone https://github.com/redis-developer/redis-ai-resources.git
50+ cd redis-ai-resources/java-recipes
51+ ```
52+
53+ 2 . Start the Docker containers:
54+
55+ ``` bash
56+ docker-compose up -d
57+ ```
58+
59+ 3 . Access the Jupyter environment:
60+ - Open your browser and navigate to [ http://localhost:8888 ] ( http://localhost:8888 )
61+ - The token is usually shown in the docker-compose logs. You can view them with:
62+
63+ ``` bash
64+ docker-compose logs jupyter
65+ ```
66+
67+ 4. Access RedisInsight:
68+ - Open your browser and navigate to [http://localhost:8001](http://localhost:8001)
69+ - Connect to Redis using the following details:
70+ - Host: redis-java
71+ - Port: 6379
72+ - No password (unless configured)
73+
74+ 5. When finished, stop the containers:
75+
76+ ` ` ` bash
77+ docker-compose down
78+ ` ` `
79+
2380# # Notebooks
2481
2582| Notebook | Description |
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