https://github.com/salesforce/cpq-product-recommendation-demo

Example CPQ product recommendation engine with implementation of the CPQ Product Recommendation Plugin interface.
https://github.com/salesforce/cpq-product-recommendation-demo

apex cpq engine recommendation

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Example CPQ product recommendation engine with implementation of the CPQ Product Recommendation Plugin interface.

• Host: GitHub
• URL: https://github.com/salesforce/cpq-product-recommendation-demo
• Owner: salesforce
• License: bsd-3-clause
• Created: 2020-07-30T15:31:36.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2022-06-22T02:42:41.000Z (over 2 years ago)
• Last Synced: 2024-04-08T00:12:35.631Z (8 months ago)
• Topics: apex, cpq, engine, recommendation
• Language: Python
• Homepage: https://releasenotes.docs.salesforce.com/en-us/winter21/release-notes/rn_sales_cpq_product_recommendations_plugin.htm?edition=&impact=
• Size: 92.8 KB
• Stars: 6
• Watchers: 9
• Forks: 3
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md
  • Code of conduct: CODE_OF_CONDUCT.md
  • Codeowners: CODEOWNERS
  • Security: SECURITY.md

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README

        
# CPQ Product Recommendation Engine Demo

This is a demo recommendation engine which reads all org quotes from salesforce database, 

generates product recommendations and inserts them into the Salesforce database. 

## Architectural Overview

![Architecture](img/architecture.png?raw=true)

The recommendation engine is scheduled to run once a day, which can be configured in [job.py](job.py).

The recommendation custom object records inserted by the engine are queried and processed by the 

CPQ ProductRecommendationPlugin (Eg. [ScoredRecoPluginImpl](apex-plugin-impl/ScoredRecoPluginImpl.cls) in the below architecture diagram) which returns an ordered list of pricebook entries.

A couple of sample implementations of the plugin are provided in the 

directory [apex-plugin-impl](apex-plugin-impl).

## Setup and Run

   - Here's an example of a [recommendation custom object](custom-objects/ProductRecommendation__c)

     that you should add to your org

     before this engine is run to insert the custom object records into your org:

     

     ```

     ProductRecommendation__c {

         Id Product2Id__c,

         Id RecommendedProduct2Id__c,

         Integer Score__c

     }

     ```

   - Set the org login credentials as environment variables using `export`

        ```

        export ORG_USERNAME=

        export ORG_PASSWORD=

        export ORG_SECURITY_TOKEN=

        export ORG_DOMAIN= - should be 'test' or 'login' or 'something.my'

        ```

   - Configure the recommendation custom object in the `bulk.py` code

        - Set the name of your recommendation custom object and its custom fields in the constant variables:

          `RECOMMENDATION_OBJECT`, `PRODUCT_ID_FIELD`, `RECOMMENDED_PRODUCT_ID_FIELD`, `SCORE_FIELD`

        - Construct the recommendation object record in the method - `get_recommendation_record()`

        

   - Open a terminal and `cd` into the project directory

   - Install dependencies

        ```console

        $ pip install -r requirements.txt

   - Make the file executable

        ```console

        $ chmod +x start.sh

   - Invoke the job script

        ```console

        $ ./start.sh

## Run Tests

[pytest](https://pytest.org/) is used to run the integration tests. 


As mentioned above, the org login credentials need to be set as environment variables before running the tests. 


To run the tests, type:

```

$ pytest

```