# How to Build from Source

This section shows how to build the Document Summarization Sample Application from the source.

> **Note:** 
> - The build instruction is applicable only on an Ubuntu system. Build from source is not supported for the sample application on [Edge Microvisor Toolkit (EMT)](https://github.com/open-edge-platform/edge-microvisor-toolkit). The user is recommended to use prebuilt images on EMT. 

## Prerequisites

Before you begin, ensure that you have the following prerequisites:

- Docker platform installed on your system: [Installation Guide](https://docs.docker.com/get-docker/).

## Steps to Build from Source

1. **Clone the Repository**:
    - Clone the Document Summarization Sample Application repository:
      ```bash
      git clone https://github.com/open-edge-platform/edge-ai-libraries.git edge-ai-libraries
      ```
      **Note**: Adjust the repo link appropriately in case of forked repo.

2. **Navigate to the Directory**:
    - Go to the directory where the Dockerfile is located:
      ```bash
      cd edge-ai-libraries/sample-applications/document-summarization
      ```
	  
3. **Set Up Environment Variables**:
    - Set up the following environment variables:

      ```bash
      # OVMS Configuration
      export VOLUME_OVMS=<model-export-path-for-OVMS>  # For example, use: export VOLUME_OVMS="$PWD"
      export LLM_MODEL="microsoft/Phi-3.5-mini-instruct"

      # Docker Image Registry Configuration
      export REGISTRY="intel/"
      export TAG=1.0.1
      ```

      To run a **GATED MODEL** like Llama models, the user will need to pass their [huggingface token](https://huggingface.co/docs/hub/security-tokens#user-access-tokens). The user will need to request access to specific model by going to the respective model page on HuggingFace.

      _Go to https://huggingface.co/settings/tokens to get your token._

      ```bash
      # Login using huggingface-cli
      pip install huggingface-hub
      huggingface-cli login
      # pass hugging face token
      ```

      > **Note:**
      > OpenTelemetry and OpenLit Configurations are optional. Set these only if there is an OTLP endpoint available.

      > ```bash
      >  export OTLP_ENDPOINT=<OTLP-endpoint>
      >  export no_proxy=${no_proxy},$OTLP_ENDPOINT,
      >   ```
      
    - Run the following script to set up the rest of the environment:

        ```bash
        source ./setup.sh
        ```

4. **Build the Docker Image**:
    - Build the Docker image for the Document Summarization Sample Application:
      ```bash
      docker compose build
      ```

5. **Run the Docker Container**:
    - Run the Docker container using the built image:
      ```bash
      docker compose up
      ```
      
    - This will start:
     
        - The OVMS service for model serving (gRPC: port 9300, REST: port 8300)
        
        - The FastAPI backend service (port 8090)
        
        - The Gradio UI service (port 9998)
        
        - The nginx (port 8101)

6. **Access the Application**:
    - Open a browser and go to `http://<host-ip>:8101` to access the application dashboard.

## Verification

- Ensure that the application is running by checking the Docker container status:
  ```bash
  docker ps
  ```
- Access the application dashboard and verify that it is functioning as expected.

## Troubleshooting

- If you encounter any issues during the build or run process, check the Docker logs for errors:
  ```bash
  docker logs <container-id>
  ```