Overview¶

The Conversational Agent - Apparel deployment guide provides step-by-step instructions on how to set up and deploy cloud resources for the Conversational Agent - Apparel application.

This guide will guide you through enabling necessary services, configuring Dialogflow, Retail Search, and DHL integration.

By following the instructions in this guide, you will be able to set up the required infrastructure and configure the application components, allowing you to experience the power of conversational AI in the retail domain.

Reference Architecture¶

The following diagram illustrates the solution architecture.

A web application with Dialogflow Messenger embedded as the frontend user interface.
The Agent uses Open API tools to search and recommend products to the end customer.
The Agent uses Application Integration tools to fetch delivery status.

Architecture

Deploy the solution¶

Before you start¶

Create a billing enabled Google Cloud project.
Update your constraints/iam.allowedPolicyMemberDomains organization policy: To allow external domain members if not already.
Go to Cloud shell and clone this repository.

git clone https://github.com/googlecloudplatform/cloud-solutions && \
cd cloud-solutions/projects/conversational-commerce-agent

Enable Services¶

gcloud auth application-default login

export PROJECT_ID=<PROJECT_ID>
gcloud config set project $PROJECT_ID
gcloud auth application-default set-quota-project $PROJECT_ID
gcloud services enable cloudresourcemanager.googleapis.com \
    cloudfunctions.googleapis.com \
    serviceusage.googleapis.com \
    firestore.googleapis.com \
    compute.googleapis.com \
    cloudbuild.googleapis.com \
    storage.googleapis.com \
    run.googleapis.com \
    retail.googleapis.com \
    dialogflow.googleapis.com \
    connectors.googleapis.com \
    secretmanager.googleapis.com \
    iam.googleapis.com \
    iamcredentials.googleapis.com

Provision Cloud Resources¶

You will use the provided terraform script to provision the following resources：

the Conversational Agent,
a Cloud Run that hosts a demo web page
a Cloud Functions
Application Integration.

Here are the steps:

Change to application folder.

cd conversational-agent-apparel

Apply Terraform

terraform init
terraform apply -var project_id="$PROJECT_ID"

When instructed, answer "yes".

You should see output like below:

agent_gs_bucket = "gs://<project-id>-dialogflowcx-assets"
app_integraion = "./app-integration.json"
ui_cloudrun_url = "https://<cloudrun-service-id>.<region>.run.app"

Take note of the following:

agent_gs_bucket you will use this bucket later
app_integration the json file you will use to create the application integration
ui_cloudrun_url the url of the ui, you will use this ui to interact with the Conversational Agent

Create Application Integration¶

Find the Application Integration json file in the working directory when you run terraform apply. The filename is in the terraform output app_integration
Use the file to Create an integration
- Choosing apparel-search-prod as the name.
- Set the region to us-central1.
- Click the Publish button to publish integrations.

Enable Unauthenticated API in Conversational Agent¶

Go to the Conversational Agent console.
In the project selection page, choose your project.
In the Agents selection page, select the Conversational Commerce Agent.
In the left panel, select Integrations, then select Conversational Messenger, click Connect.
- Make sure “Unauthenticated API (anonymous access)” is checked.
- Scroll down and click the “Enable unauthorized API” button.
- Wait for the API to enable, then click Done to close the dialog.

Retail Search Data Import¶

In this demo, we are using the public Flipkart dataset for products. This section introduces the steps to convert the public dataset to Google Cloud Search for Retails data format, and import the converted data into Search for Retail.

Enable Search for Retail service¶

Goto Search for Retail Console.
- Follow the instructions to turn on the APIs, agree to data use terms and turn on search & browse features.
Goto [Vertex AI Search for Retail API Manage console] (https://console.cloud.google.com/apis/api/retail.googleapis.com/).
- Wait several seconds until the Create Credentials button shows up.
- Click the Create Credentials button on the top right to create a service account and associate it with the Search for Retail service
  - In the Which API are you using? page. Leave Select an API field default, and choose Application Data
  - In the Service account details page. Name the service account retail-service
  - in the Grant this service account access to project page. Grant Retail Admin, Storage Object Viewer and Storage Admin role to the service account.
  - Click Done to create the service account.

Import data to Search for Retail¶

These scripts report errors if the Search for Retail service is not ready for use, if you see errors when running the following scripts. Please wait 5 minutes and try again.

This demo solution consists of two different use cases - Apparel and Cosmetic.

To setup Apparel use case demo.

Switch to the data-ingestion folder and download Flipkart dataset.

cd ../data-ingestion
mkdir -p dataset

curl -L -o \
dataset/archive.zip https://www.kaggle.com/api/v1/datasets/download/PromptCloudHQ/flipkart-products
unzip dataset/archive.zip -d dataset

To setup Cosmetic use case demo.

Switch to the data-ingestion folder and download Flipkart cosmetic dataset.

cd ../data-ingestion
mkdir -p dataset

curl -L -o \
dataset/archive.zip https://www.kaggle.com/api/v1/datasets/download/shivd24coder/cosmetic-brand-products-dataset
unzip dataset/archive.zip -d dataset

Setup environment variables.

export PROJECT_ID=<YOUR PROJECT ID>
gcloud config set project $PROJECT_ID

export PROJECT_NUMBER=$(gcloud projects describe $PROJECT_ID \
  --format="value(projectNumber)")
echo $PROJECT_NUMBER

Convert Flipkart dataset to Search for Retail format.
- Note that in this demo, we use Branch 1 as the default branch. For more information about Search for Retail Branches, please see the documentation.

python3 -m venv .venv
source .venv/bin/activate

pip install -r requirements.txt --require-hashes

python3 flipkart_to_retail_search.py \
   -i dataset/flipkart_com-ecommerce_sample.csv \
   -o dataset/flipkart-all.jsonl -p $PROJECT_NUMBER -b 1

Update Search for Retail catalog level attribute controls.

python3 update_controls.py -n $PROJECT_NUMBER

Import data and set the default branch.
- Note that large catalog imports can take hours to fully propagate. Before the data is fully propagated your conversation with the agent may end up with no search results.
- For demo purposes, you may want to reduce the size of the final dataset to reduce the time of import.
- Catalog and product information is imported to Branch 1, which is set as the default branch.

export BUCKET_NAME=${PROJECT_ID}-dialogflowcx-assets

python3 import_to_retail_search.py -i dataset/flipkart-all.jsonl -g $BUCKET_NAME \
   -n $PROJECT_NUMBER -b 1 --set-default-branch

You may see errors below, which indicates this product has invalid data. The problematic product will be ignored and not imported to Search for Retail.

INFO:root:error_samples {
  code: 3
  message: "The string in \"product.attributes.value.text\" must be with a length limit of 256 Unicode characters, but 1447 Unicode characters found."
  details {
    type_url: "type.googleapis.com/google.rpc.ResourceInfo"
    value: "\022Fgs://kalschi-conv-commerce-11-dialogflowcx-assets/flipkart-all.jsonl:2"
  }
}

Verify the deployment¶

Navigate to ui_cloudrun_url you noted down in the previous step.
Follow the demo guide to verify the deployment.

Troubleshooting¶

Agent returns no product but asks which product I want¶

Go to Cloud Run, apparel-search-cf, Logs
- Check the latest Cloud Run calls. If you see products in the response payload like below where some products do not have details. The dataset is not fully propagated, please wait a moment and try again.

Log
RAW RESULT: [{'id': 'a0f262830d970a2921ca58ce6177fdbc', 'product': {'name': 'projects/646255812645/locations/global/catalogs/default_catalog/branches/1/products/a0f262830d970a2921ca58ce6177fdbc'}}, ...
Retail Search Exception: 'title'