What is this?

This is the OpenAI Whisper project (https://github.com/openai/whisper - Offline Speech Recognition model) - inside a Container, with an option to deploy as a stand-alone Docker container, or an AWS Lambda function that is container backed.

In summary: it lets you transcribe voice to text extremely accurately and quickly, for free.

How Do I use this?

There are 2 ways to run/interact with this:

• As a "regular container" (Docker) or
• As an AWS Lambda (container backed) function - via an a direct API, or S3 "put" automation.

1.) As a "regular container":

docker exec -it ventz/whisper /bin/bash"

# Assuming you have a 'recording.mp4' and have pulled it/mounted it on the container:
whisper 'recording.mp4' --language English --model base --fp16 False

2.) As an AWS Lambda (container backed) functions:

The idea is that you will setup a S3 bucket with a hook that calls this Lambda when a new object is created or dropped.

This involves:

a.) Tagging the local docker image and pushing it to ECR:

docker tag ventz/whisper:latest 123456789012.dkr.ecr.us-east-1.amazonaws.com/whisper:latest
docker push 123456789012.dkr.ecr.us-east-1.amazonaws.com/whisper:latest

b.) Deploying a new Lambda function from ECR:

aws lambda create-function --region us-east-1 --function-name transcribe \
   --package-type Image  \
   --code ImageUri=<ECR Image URI>   \
   --role  arn:aws:iam::123456789012:role/service-role/transcribe

NOTE: The role needs to have: i.) AWSLambdaBasicExecutionRole (for: 'logs:CreateLogStream', and 'logs:PutLogEvents')

{
   "Version": "2012-10-17",
   "Statement": [
       {
           "Effect": "Allow",
           "Action": "logs:CreateLogGroup",
           "Resource": "arn:aws:logs:us-east-1:123456789012:*"
       },
       {
           "Effect": "Allow",
           "Action": [
               "logs:CreateLogStream",
               "logs:PutLogEvents"
           ],
           "Resource": [
               "arn:aws:logs:us-east-1:123456789012:log-group:/aws/lambda/transcribe:*"
           ]
       }
   ]
}

and

ii.) Write access to S3 bucket:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "VisualEditor0",
            "Effect": "Allow",
            "Action": [
                "s3:PutObject",
                "s3:GetObject",
                "s3:ListBucket"
            ],
            "Resource": "arn:aws:s3:::<YOUR BUCKET NAME>/*"
        }
    ]
}

c.) Update code if you ever re-configure/re-build your container/Dockerfile:

# NOTE: This assumes your function was deployed with the name 'transcribe' 
aws lambda update-function-code --function-name transcribe --image-uri $(aws lambda get-function --function-name transcribe | jq -r '.Code.ImageUri')

You can check when done with:

while [ "$(aws lambda get-function --function-name transcribe | jq -r '.Configuration.LastUpdateStatus')" != "Successful" ]; do
    sleep 1
done

MANUALLY TESTING THE LAMBDA LOCALLY (not within AWS):

docker run -it --rm -d -p 9000:8080 --name whisper ventz/whisper

and then

curl -XPOST "http://localhost:9000/2015-03-31/functions/function/invocations" -d @test-s3-json

NOTE: This is a "fake" event just to make sure you can locally run the lambda. You will need a real s3 bucket and real file/recording + IAM permissions(see test-s3-json)