Chaining Einstein Copilot Custom Actions

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Image created by DALL-E 3 based in a prompt by Bob Buzzard

Introduction

I've been testing out Salesforce's Einstein Copilot assistant for a few weeks now, but typically I've been tacking a single custom action onto the end of one or more standard actions, and usually a Prompt Template where I can easily ground it with some data from a specific record. 

Something that hasn't been overly clear to me is how I can link a couple of custom actions and pass information other than record ids between them. The kind of information that would be shown to the user if it was a single action, or the kind of information that the user had to provide in a request.

Scenario

The other aspect I was interested in was some kind of DML. I've seen examples where a record gets created or fields get changed based on a request, but the beta standard actions don't have this capability, so it was clear I'd need to build that myself. So the scenario I came up with was : Given an opportunity, it's existing related activities, and a few rules (like if it's about to close someone should be in contact every day), Copilot suggests a follow up task and inserts it into the Salesforce database. 

This can't easily (or sensibly, really) be done in a single custom action. I guess I could create a custom Apex action that uses a Prompt Template to get a task recommendation from the LLM and then inserts it, but it seems a bit clunky and isn't overly reusable. What I want here are two custom actions:

1. A Prompt Template custom action that gets the suggestion for the task from the LLM
2. An Apex custom action that takes the details of the suggestion and uses it to create a Salesforce task.

I also don't want to have to expend a lot of effort processing the recommendation response to pick out the important details - if I'm writing that much code I might as well figure out the task that I need as well.

Implementation

The key aspect of the Prompt Template is explaining how I want the response to be formatted, so that it can be easily processed by Apex code. I was half expecting to have to use few shot prompting to get this to work, but was pleasantly surprised to find that I could just describe it in natural language with a few rules about labelling:

Generate a recommendation for a follow up task in JSON format, including the following details:

- The subject of the task with the element label 'subject'

- A brief description with the element label 'description' - this should include the names of anyone other than the user responsible for the task who should be involved

- The date the task should be completed by, in DD/MM/YYYY format with the element label' due_date'

- The record id of the user who is responsible for the task with the element label 'user_id'

- {!$Input:Candidate_Opportunity.Id} with the element label 'what_id'

Do not include any supporting text, output JSON only.

Note that I did have to remind it not to add any text over and above the JSON output - this is something LLMs tend to suffer from a lot in my experience, always wanting to a add a "here you go" or "as requested". Nice that they try to be polite, but not helpful when you need structured data!

Trying this out in Copilot Builder showed that I was getting the output that I wanted:

Note that while there is the additional text of 'Great, I have generated ...', that's Copilot rather than the LLM, so if I can chain this to another custom action I'll just get the JSON format data.

My Apex Custom Action code is surprisingly svelte:

public with sharing class CopilotOppFollowUpTask 
{
    @InvocableMethod(label='Create Task' description='Creates a task')
    public static List<String> createTask(List<String> tasksJSON) {

        JSONParser parser=JSON.createParser(tasksJSON[0]);
        Map<String, String> params=new Map<String, String>();

        while (null!=parser.nextToken()) 
        {
            if (JSONToken.FIELD_NAME==parser.getCurrentToken())
            {
                String name=parser.getText();
                parser.nextToken();
                String value=parser.getText();
                System.debug('Name = ' + name + ', Value = ' + value);
                params.put(name, value);
            }
        }

        String dateStr=params.get('due_date');

        Date dueDate=date.newInstance(Integer.valueOf(dateStr.substring(6,10)),
                                      Integer.valueOf(dateStr.substring(3, 5)),
                                      Integer.valueOf(dateStr.substring(0, 2)));

        Task task=new Task(Subject=params.get('subject'),
                           Description=params.get('description'),
                           ActivityDate=dueDate,
                           OwnerId=params.get('user_id'),
                           WhatId=params.get('what_id'));

        insert task;
        
        return new List<String>{'Task created with id ' + task.Id};
    }
}

All that's needed to make it available for a Custom Action is the invocable aspect :

    @InvocableMethod(label='Create Task' description='Creates a task')

When I define the custom action, it's all about the instruction:

which hopefully is enough for the Copilot reasoning engine to figure out it can use the JSON format output from the task recommendation action. Of course I still need to give Copilot the correct instruction so it understands it needs to chain the actions:

And here's the task it came up with:

Related Posts

• Einstein Copilot Custom Actions
• Einstein Prompt Templates in Apex - the Sales Coach
• Einstein Prompt Grounding with Apex
• Hands on with Salesforce Copilot
• Hands On with Prompt Builder
• Salesforce Help for Prompt Builder
• Salesforce Admins Ultimate Guide to Prompt Builder

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