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About The Project

This demo illustrates the capabilities of Document AI and Gemini.

Deploy the app locally

  • Create a document AI processor , in this case , it is an OCR type processor.

  • Create a .env file with the following environment variables:

    PROJECT_ID='YOUR_PROJECT_ID'
LOCATION='eu'
PROCESSOR_ID ='YOUR_DOCUMENT_AI_PROCESSOR_ID'

  • Create a Dockerfile file

  • Build the image locally, cd into your project folder and run.

    docker buildx build .

  • Run the docker image using the application default credentials used for authentication.

    docker run -v "Path to you loclal application default credentials i.e application_default_credentials.json":/gcp/creds.json:ro  --env GOOGLE_APPLICATION_CREDENTIALS=/gcp/creds.json -p 8080:8080  "YOUR_DOCKER_IMAGE"

  • Access the app via the localhost.

Deploy the app on cloud run

  • Create a document AI processor , in this case , it is an OCR type processor.
  • Create a .env file with the following environment variables: 
    PROJECT_ID='YOUR_PROJECT_ID'
LOCATION='eu'
PROCESSOR_ID ='YOUR_DOCUMENT_AI_PROCESSOR_ID'
  • Create a Dockerfile file
  • Build the image and push it to conatiner registry 
    gcloud builds submit --tag gcr.io/YOUR_PROJECT_ID/DEMO_NAME_OF_YOUR_CHOICE --timeout=1h
  • Create a service in cloud run based on the built image.
  • Access the app via the link provided by the cloud run service.