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What is the correct process to leverage Prompt Builder in a Salesforce org?
When using Prompt Builder in a Salesforce org, the correct process involves several important steps:
1. Select the appropriate prompt template type based on the use case.
2. Develop the prompt within the prompt workspace, where the template is created and customized.
3. Select CRM-derived grounding data to be dynamically inserted into the prompt, ensuring that the AI-generated responses are based on accurate and relevant data.
4. Pick the model to use for generating responses, either using Salesforce's built-in models or custom ones.
5. Test and validate the generated responses to ensure accuracy and effectiveness.
* Option B is correct as it follows the proper steps for using Prompt Builder.
* Option A and Option C do not capture the full process correctly.
* Salesforce Prompt Builder Documentation: https://help.salesforce.com/s/articleView?id=sf.prompt_builder_overview.htm
What is the primary function of the planner service in the Agent system?
The primary function of the planner service in the Agent system is to identify copilot actions that should be taken in response to user utterances. This service is responsible for analyzing the conversation and determining the appropriate actions (such as querying records, generating a response, or taking another action) that the Agent should perform based on user input.
Universal Containers (UC) is discussing its AI strategy in an agile Scrum meeting.
Which business requirement would lead An Agentforce to recommend connecting to an external foundational model via Einstein Studio (Model Builder)?
Einstein Studio (Model Builder) allows organizations to connect and utilize external foundational models while fine-tuning them with company-specific data. This capability is particularly suited to businesses like Universal Containers (UC) that require customization of foundational models to better align with their unique data and use cases.
* Option A: Adjusting model temperature is a parameter-level setting for controlling randomness in AI-generated responses but does not necessitate connecting to an external foundational model.
* Option B: This is the correct answer because Einstein Studio supports fine-tuning external models with proprietary company data, enabling a tailored and more accurate AI solution for UC.
* Option C: Changing frequency penalties is another parameter-level adjustment and does not require external foundational models or Einstein Studio.
* 'Using Einstein Studio to Connect Foundational Models | Salesforce Trailhead' .
An Agentforce wants to include data from the response of external service invocation (REST API callout) into the prompt template.
How should the Agentforce Specialist meet this requirement?
An Agentforce wants to include data from the response of an external service invocation (REST API callout) into a prompt template. The goal is to incorporate dynamic data retrieved from an external API into the AI-generated content.
Solution:
* Use External Service Record Merge Fields
* External Service Integration:
o Definition: External Services in Salesforce allow the integration of external REST APIs into Salesforce without custom code.
o Registration: The external service must be registered in Salesforce, defining the API's schema and methods.
* External Service Record Merge Fields:
o Purpose: Enables the inclusion of data from external service responses directly into prompt templates using merge fields.
o Functionality:
Dynamic Data Inclusion: Allows prompt templates to access and use data returned from REST API callouts.
Merge Fields Syntax: Use merge fields in the prompt template to reference specific data points from the API response.
Implementation Steps:
1. Register the External Service:
o Use External Services to register the REST API in Salesforce.
o Define the API's schema, including methods and data structures.
2. Create a Named Credential:
o Configure authentication and endpoint details for the external API.
3. Use External Service in Flow:
o Build a Flow that invokes the external service and captures the response.
o Ensure the flow outputs the necessary data for use in the prompt template.
4. Configure the Prompt Template:
o Use External Service Record merge fields in the prompt template to reference data from the flow's output.
o Syntax Example: {{flowOutputVariable.fieldName}}
Why Other Options are Less Suitable:
* Option A (Convert the JSON to an XML merge field):
o Irrelevance: Converting JSON to XML merge fields is unnecessary and complicates the process.
o Unsupported Method: Salesforce prompt templates do not support direct inclusion of XML merge fields from JSON conversion.
* Option C (Use ''Add Prompt Instructions'' flow element):
o Purpose of Add Prompt Instructions:
Allows adding instructions to the prompt within a flow but does not facilitate including external data.
o Limitation: Does not directly help in incorporating external service responses into the prompt template.
* Salesforce Agentforce Specialist Documentation - Integrating External Services with Prompt Templates:
o Explains how to use External Services and merge fields in prompt templates.
* Salesforce Help - Using Merge Fields with External Data:
o Provides guidance on referencing external data in templates using merge fields.
* Salesforce Trailhead - External Services and Flow:
o Offers a practical understanding of integrating external APIs using External Services and Flow.
Conclusion:
By using External Service Record merge fields, the Agentforce Specialist can effectively include data from external REST API responses into prompt templates, ensuring that the AI-generated content is enriched with up-to-date and relevant external data.
An Agentforce wants to ground a new prompt template with the User related list.
What should the Agentforce Specialist consider?
Salesforce has restrictions on which objects and related lists can be used for grounding prompt templates. This is likely due to security and privacy concerns related to user data.
While it might seem intuitive to use the User related list to provide context to the LLM, Salesforce prevents this to ensure that sensitive user information is not inadvertently exposed or misused.
Therefore, the Agentforce Specialist needs to explore alternative ways to incorporate the necessary user information into the prompt template, perhaps by using other related objects or fields that are supported.
