In this tutorial, we will walk you through the process of installing Weaviate on Windows 10. Weaviate is an open-source knowledge graph that allows users to build and deploy machine learning models using natural language processing.
Before you begin, make sure that you have the following prerequisites:
Weaviate requires Java version 8 or higher to run. If you don't have Java installed on your system, you can download and install it from the official Java website at https://www.java.com/en/download.
Weaviate can be run in a Docker container, so you'll need to have Docker Desktop installed on your system. You can download Docker Desktop from the official Docker website at https://www.docker.com/products/docker-desktop.
Weaviate's source code is hosted on GitHub, so you'll need Git installed on your system to clone the repository. You can download Git from the official Git website at https://git-scm.com/download/win.
Open Git Bash or your preferred terminal and navigate to the directory where you want to install Weaviate. Then, run the following command to clone Weaviate's repository:
git clone https://github.com/semi-technologies/weaviate.git
This will download the latest version of Weaviate's source code to your local system.
Once you have cloned the repository, navigate to the weaviate directory using your terminal and run the following command to build Weaviate's Docker image:
docker build . -t weaviate:latest
This command will build the Docker image for Weaviate and tag it as weaviate:latest. This process may take a few minutes to complete.
After building the Docker image, run the following command to start the Weaviate container:
docker run -p 8080:8080 weaviate:latest
This command will start the Weaviate container and expose the application on port 8080. You can access Weaviate's web interface by navigating to http://localhost:8080 in your browser.
Congratulations! You have successfully installed Weaviate on your Windows 10 machine. From here, you can start exploring the power of Weaviate's natural language processing and machine learning capabilities. If you have any issues or questions, refer to Weaviate's official documentation or ask for help from the community.
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