Automate Interactions with Contact Center AI: Automate Interactions

Challenge Lab

Qwiklabs [GSP311]

@prakashfoundation YouTube

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Task 1:

clone the repos...

git clone https://github.com/GoogleCloudPlatform/dataflow-contact-center-speech-analysis.git

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Task 1: Create a Cloud Storage Bucket

change the project id.

code :

gsutil mb -l us-central1 gs://[project id]/

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Task 2: Create a Cloud Function

Go to the “saf-longrun-job-func” directory

code :

gcloud functions deploy safLongRunJobFunc --runtime nodejs8 --trigger-resource [project id] --region us-central1 --trigger-event google.storage.object.finalize

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Task 3: Create a BigQuery Dataset and Table

# To create the dataset

code:

bq mk saf

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Task 4: Create Cloud Pub/Sub Topic

code :

gcloud pubsub topics create [Topic_Name]

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Task 5: Create a Cloud Storage Bucket for Staging Contents

wathch the video to complete the task

Create a folder “DFaudio” in the bucket

do it manually

code :

gsutil mb -l [BUCKET_LOCATION] gs://[BUCKET_NAME]/

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Task 6: Deploy a Cloud Dataflow Pipeline

Go to the saf-longrun-job-dataflow directory

code :

python -m virtualenv env -p python3 source env/bin/activate pip install apache-beam[gcp] pip install dateparser

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Now, execute the command given below:

code :

python saflongrunjobdataflow.py \ --project=[PROJECT_ID] \ --region=us-central1 \ --input_topic=projects/[PROJECT_ID]/topics/[Topic_Name] \ --runner=DataflowRunner \ --temp_location=gs://[BUCKET_NAME_FOR_STAGING_CONTENT]/[FOLDER] \ --output_bigquery=[PROJECT_ID]:saf.transcripts \ --requirements_file=requirements.txt

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Task 7: Upload Sample Audio Files for Processing

code:

gsutil -h x-goog-meta-callid:1234567 -h x-goog-meta-stereo:false -h x-goog-meta-pubsubtopicname:[TOPIC_NAME] -h x-goog-meta-year:2019 -h x-goog-meta-month:11 -h x-goog-meta-day:06 -h x-goog-meta-starttime:1116 cp gs://qwiklabs-bucket-gsp311/speech_commercial_mono.flac gs://[YOUR_UPLOADED_AUDIO_FILES_BUCKET_NAME(task1 bucket name)] gsutil -h x-goog-meta-callid:1234567 -h x-goog-meta-stereo:true -h x-goog-meta-pubsubtopicname:[TOPIC_NAME] -h x-goog-meta-year:2019 -h x-goog-meta-month:11 -h x-goog-meta-day:06 -h x-goog-meta-starttime:1116 cp gs://qwiklabs-bucket-gsp311/speech_commercial_stereo.wav gs://[YOUR_UPLOADED_AUDIO_FILES_BUCKET_NAME(task1 bucket name)]

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After performing Task 7: Upload Sample Audio Files for Processing, we have to wait....until we see output in bigquery > dataset > table.

Task 8: Run a Data Loss Prevention Job

code :

select * from (SELECT entities.name,entities.type, COUNT(entities.name) AS count FROM saf.transcripts, UNNEST(entities) entities GROUP BY entities.name, entities.type ORDER BY count ASC ) Where count > 5

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Now, click on “Save Query Results” and select “BigQuery table” option

Enter a name for a new table and save.

Go to the new table in which result is saved and then Click on Export > Scan with DLP

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