Build from Source

Build the Multimodal Embedding Serving microservice from source to customize, debug, or extend its functionality. In this guide, you will:

• Set up your development environment.

• Compile the source code and resolve dependencies.

• Generate a runnable build for local testing or deployment.

This guide is ideal for developers who want to work directly with the source code.

Prerequisites

Before you begin, ensure the following:

• System Requirements: Verify your system meets the minimum requirements.

• This guide assumes basic familiarity with Git commands, Python virtual environments, and terminal usage. If you are new to these concepts, see:

  • Git Documentation

  • Python Virtual Environments

Steps to Build

This section provides a detailed note on how to build the Multimodal Embedding Serving microservice.

(Optional) Docker Compose builds the Multimodal Embedding Serving with a default image and tag name. If you want to use a different image and tag, export these variables:

export REGISTRY_URL="your-container-registry-url"
export PROJECT_NAME="your-project-name"
export TAG="your-tag"

Note: PROJECT_NAME will be suffixed to REGISTRY_URL to create a namespaced url. Final image name will be created/pulled by further suffixing the application name and tag with the namespaced url.

Note: If variables are set using above command, the final image names for Multimodal Embedding Serving would be <your-container-registry-url>/<your-project-name>/multimodal-embedding-serving:<your-tag>.

If variables are not set, in that case, the TAG will have default value as latest. Hence, final image will be multimodal-embedding-serving:latest.

1. Clone the Repository:

git clone https://github.com/open-edge-platform/edge-ai-libraries.git edge-ai-libraries
cd edge-ai-libraries/microservices/multimodal-embedding-service

2. Set up environment values:

Follow all the instructions provided in the Get Started document to set up the environment variables.

Note: To build or run with GPU support, set EMBEDDING_DEVICE=GPU before sourcing setup.sh.

3. Build the Docker image:

To build the Docker image, run the following command:

docker compose -f docker/compose.yaml build

4. Run the service:

docker compose -f docker/compose.yaml  up

This will run the service in either CPU or GPU mode depending on your environment variable settings.

Validation

Verify Build Success:

• Check the logs. Look for confirmation messages indicating the microservice started successfully.

Supporting Resources

• Overview

• System Requirements

• API Reference