#----------------------------------------------------------------------------
   PINECONE_TOKEN=your-api-key # Replace your-api-key with your personal API key
   ```

3. Build and run the application. In a terminal, change directory to your
   `docker-genai` directory and run the following command.

   ```console
   $ docker compose up --build
   ```

   Docker Compose builds and runs the application based on the services defined
   in the `docker-compose.yaml` file. When the application is running, you'll
   see the logs of 2 services in the terminal.

   In the logs, you'll see the services are exposed on ports `8503` and `8504`.
   The two services are complimentary to each other.

   The `yt-whisper` service is running on port `8503`. This service feeds the
   Pinecone database with videos that you want to archive in your knowledge
   database. The following section explores this service.

## Using the yt-whisper service

The yt-whisper service is a YouTube video processing service that uses the OpenAI
Whisper model to generate transcriptions of videos and stores them in a Pinecone
database. The following steps show how to use the service.

1. Open a browser and access the yt-whisper service at [http://localhost:8503](http://localhost:8503).
2. Once the application appears, in the **Youtube URL** field specify a Youtube video URL
   and select **Submit**. The following example uses
   [https://www.youtube.com/watch?v=yaQZFhrW0fU](https://www.youtube.com/watch?v=yaQZFhrW0fU).

   

   The yt-whisper service downloads the audio of the video, uses Whisper to
   transcribe it into a WebVTT (`*.vtt`) format (which you can download), then
   uses the text-embedding-3-small model to create embeddings, and finally
   uploads those embeddings in to the Pinecone database.

   After processing the video, a video list appears in the web app that informs
   you which videos have been indexed in Pinecone. It also provides a button to
   download the transcript.