Introduction

This project demonstrates how to create an Amazon Connect task from a phone call with Amazon Transcribe and Comprehend. This can be an alternative to a voicemail, except that the "voicemail" is turned into a Connect Task, which gets routed/assigned.

Solution Overview

About your CDK Python project

You should explore the contents of the repo. The cdk.json file tells the CDK Toolkit how to execute your application.

This project is set up like a standard Python project. The initialization process also creates a virtualenv within this project, stored under the .venv directory. To create the virtualenv it assumes that there is a python3 executable in your path with access to the venv package. If for any reason the automatic creation of the virtualenv fails, you can create the virtualenv manually once the init process completes.

To manually create a virtualenv on MacOS and Linux:

$ python3 -m venv .venv

After the init process completes and the virtualenv is created, you can use the following step to activate your virtualenv.

$ source .venv/bin/activate

If you are a Windows platform, you would activate the virtualenv like this:

% .venv\Scripts\activate.bat

Once the virtualenv is activated, you can install the required dependencies.

$ pip install -r requirements.txt

At this point you can now synthesize the CloudFormation template for this code.

$ cdk synth

You can now begin exploring the source code, contained in the hello directory. There is also a very trivial test included that can be run like this:

$ pytest

To add additional dependencies, for example other CDK libraries, just add to your requirements.txt file and rerun the pip install -r requirements.txt command.

Useful commands

• cdk ls list all stacks in the app
• cdk synth emits the synthesized CloudFormation template
• cdk deploy deploy this stack to your default AWS account/region
• cdk diff compare deployed stack with current state
• cdk docs open CDK documentation

Deploy the solution

1. Clone this repo to your local computer
2. Follow the instructions from the About your CDK Pyton project above to prepare the CDK Python environment in the folder you clone the repo above
3. Make sure that you set the proper AWS_PROFILE in your environment (as this set of account/region/credentials will be used by CDK)
   • On Mac: export AWS_PROFILE=user1 where user1 is the name of your aws profile in the $HOME/.aws folder
   • On Windows: setx AWS_PROFILE user1, where user1 is the name of your aws profile in the $HOME/.aws folder
4. Bootstrap your account and region: cdk bootstrap
5. Go the the AWS DynamoDB Console, select table contactDetails
   • Select Manage DynamoDB Stream , select New and old images, and Enable the stream
   • Note the Latest stream ARN
   
6. Update the cdk.json file with appropriate context parameters (instanceId, contactFlowId, and eventSourceArn).
   • eventSourceArn is the Latest stream ARN value in step 5
7. Deploy the solution with cdk deploy, and wait for it to finish
8. Check the deployed resource by going to the AWS CloudFormation Dashboard, select that stack that has just been deployed (record-comprend-task), and select the Resources tab. Note the following lambdas (whose ARN’s will be used in the Contact Flow in step 13):
   • Logical ID starts with comprehendtasklambda
   • Logical ID starts with trackingtasklambda
   
9. Import the Amazon Lex bot
   • Go to the Amazon Lex Console.
   • On the Actions dropdown menu, choose Import.
   • Browse to assets folder and select the RecordComprehendTask.zip file to import
   • Create and publish the Lex bot
10. Enable the Lex bot for use in your Contact Flow.
    • Go to the AWS Connect Console, select your instance, then select Contact Flows on the left panel
    • Add the Lex bot that you created in step 4 for use in your Contact Flows
    
11. Enable the Lambdas for use in your Contact Flow
12. Import the Contact Flow.
    • Open the kvsStreamingFlow CF deployed in the prerequisite Amazon Connect real time transcription solution
    • Replace it by importing the kvsStreamingFlow.json CF in the assets folder
13. Update the kvsStreamingFlow CF with appropriate Lex bot and Lambdas
    • Update the Invoke AWS Lambda function block with the kvsConsumerTrigger lambda deployed in the prerequisite Amazon Connect real time transcription solution.
    • Update the Get customer input block with the Lex bot deployed in step 9
    • Update the Invoke AWS Lambda function block with the trackingtasklambda function deployed in step 3.
    • Go to the AWS Connect Console, select your instance, then select Contact Flows on the left panel.
    • Add the two lambdas you noted in step 8 for use in your Contact Flows.
    • Note that the lambda that starts with kvsConsumerTrigger should’ve already been added when deploying the pre-requisite Amazon Connect real time transcription solution.
    

Testing

1. In your Amazon Connect instance, choose the Routing icon from the navigation bar, and choose phone numbers.
2. Choose the phone number you want to associate with your new contact flow to edit.

Clean up

1. Run cdk destroy on the stack deployed in this solution.
2. Go to the Amazon Lex Dashboard and delete the Lex bot created in step 9.

Security

See CONTRIBUTING for more information.

License

This library is licensed under the MIT-0 License. See the LICENSE file.