https://github.com/deepgram/amazon-connect-integration
Enables transcribing Amazon Connect calls with Deepgram
https://github.com/deepgram/amazon-connect-integration
Last synced: 5 months ago
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Enables transcribing Amazon Connect calls with Deepgram
- Host: GitHub
- URL: https://github.com/deepgram/amazon-connect-integration
- Owner: deepgram
- License: mit-0
- Created: 2023-08-24T16:15:35.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-05-21T00:38:09.000Z (about 2 years ago)
- Last Synced: 2025-03-17T12:14:16.887Z (over 1 year ago)
- Language: Java
- Size: 89.8 KB
- Stars: 2
- Watchers: 10
- Forks: 2
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# amazon-connect-integration
This repo enables real-time transcription of Amazon Connect calls with Deepgram, using self-hosted AWS infrastructure. For detailed documentation, see https://developers.deepgram.com/docs/deepgram-with-amazon-connect.
## Deploy the Integration
1. Create ECR repos for `kvs_dg_trigger` and `kvs_dg_integrator`:
```shell
aws ecr create-repository --repository-name kvs-dg-trigger
aws ecr create-repository --repository-name kvs-dg-integrator
```
2. Log in to ECR with the Docker CLI:
```
aws ecr get-login-password --region | docker login --username AWS --password-stdin .dkr.ecr..amazonaws.com
```
3. In the `kvs_dg_trigger` folder, build the Docker image for the trigger Lambda:
```shell
docker build --platform linux/amd64 -t .dkr.ecr..amazonaws.com/kvs-dg-trigger:latest .
```
4. In the `kvs_dg_integrator` folder, build the Docker image for the integrator task:
```shell
docker build --platform linux/amd64 -t .dkr.ecr..amazonaws.com/kvs-dg-integrator:latest .
```
5. Push the new Docker images to ECR:
```shell
docker push .dkr.ecr..amazonaws.com/kvs-dg-trigger:latest
docker push .dkr.ecr..amazonaws.com/kvs-dg-integrator:latest
```
6. Run `cloudformation.yaml` in AWS CloudFormation to spin up all of the necessary AWS resources.
## Run the Sample Contact Flow
Also included is an Amazon Connect contact flow that demonstrates how to use the deployed integration. To run the contact flow:
1. Add the newly deployed trigger Lambda to your Amazon Connect instance ([guide](https://docs.aws.amazon.com/connect/latest/adminguide/connect-lambda-functions.html#add-lambda-function)).
2. Enable live media streaming in your Amazon Connect instance ([guide](https://docs.aws.amazon.com/connect/latest/adminguide/enable-live-media-streams.html)). Choosing **No data retention** is fine, unless you plan to load test the integration with the built-in load testing functionality, in which case you should choose a retention period at least as long as your load test duration.
3. Create a new inbound contact flow and import `sample_contact_flow.json` ([guide](https://docs.aws.amazon.com/connect/latest/adminguide/contact-flow-import-export.html#how-to-import-export-contact-flows)).
4. In the **Deepgram Configuration** block, go to **Edit Settings** and update `dg_callback` to a URL where you want to receive the transcripts. The transcripts will be sent as POST requests to the URL you provide. For testing, you can use a site like [Beeceptor](https://beeceptor.com/) to create a URL that will display the contents of the POST requests.
5. In the **Invoke Trigger Lambda** block, go to **Edit Settings** and select the trigger Lambda function from the **Function ARN** dropdown.
6. Save and publish the contact flow.
7. Assign the contact flow to a phone number ([guide](https://docs.aws.amazon.com/connect/latest/adminguide/associate-claimed-ported-phone-number-to-flow.html)).
8. Call into the phone number. After it plays the initial message, say something and watch your callback server to make sure your words are being transcribed.